text:
First Place on The Religion Quiz
Each parent is proud of they're child's achievements either in school, sports, in folklore, or life in general .
Children of the Serbian School at the Cathedral of the Diocese of the Canadian Church of Sv. Father Nikolai, who took part in the Children's Assembly in the Monastery of Christ's Transfiguration in Milton, put a smile on the face of their parents, priests, teachers and the entire Serb community in Hamilton.
On Saturday, June 10, 2017, about seventy students from seven Serbian schools gathered at the Children's Assembly. They competed from Orthodox religious education, Serbian history and Serbian language. The questions were not easy, but it was therefore a strong desire to justify the trust shown, and that the effort and time they spent had a deserved acknowledgment.
And finally, when the winner was declared, the joy of children, parents and their priest Djuro was great. All the years of attendance of the Serbian school and religious education paid off in the end.
It should be pointed out that the pupils of the Serbian School of St. Father Nicholas of Hamilton at the Cathedral of the Diocese of Canada won the first place in the knowledge of the religion in 2010, and this victory continued the tradition and once again demonstrated and demonstrated their dedication to the Orthodox faith and the teachings of Christ and the testimony of the Gospel.
Serbian School Field Trip to Pioneer Village 2017
Serbian church school officially opened September 18, 1964 and consisted of 76 students with Hamilton Priest Borko Borcic as the first teacher.
At a church meeting on July 1969 it was decided that a church newspaper, "GLASNIK," would be printed. It is in this publication that the children of 2013 received a section under the name "Glasnicic". An amateur group of student-actors was formed and have performed in short form, the following plays: Little Red Riding Hood, House of the Hedgehog, Blowfly Palace, Wolf and the Seven Lambs, Grandpa's Birthday, The Three Pigs, Snow White and the Seven Dwarfs, Cinderella. We have had the pleasure of hosting Belgrade-actors from the "Pan Theater," which performed the play "Horse Tooth of our King." We were also delighted by the members of the children's theatre group, "Pulse Theatre", from Toronto who performed "Charlotte's Web."
In the last ten years our school of the Serbian Language has been recognized by the Hamilton-Wentworth District School Board.
In order to preserve the religion and tradition, every grade has their own slava and the teachers and the priests make sure that the icon, the bread, wheat and candle are found on the table of celebrators.
Our priests, Father Djuro Samac and Father Milojko Dimitric, give us the blessing every Friday and they participate in the planning of all aspects our Serbian Church School.
It is with pride that we proclaim that we are the oldest school of the Serbian language in this territory. We will never desert our religion and language and are happy that we live in a country which supports and contributes to safeguarding of our mother language and the culture of all societies so that we may try to transfer our national identity to new generations.
The students of our school participate in the yearly competitions held at the Monastery in Milton and they have achieved remarkable results in religion, history and culture, as well as in the Serbian language.
With hard work and much effort by the administration of the Serbian school, in 2008 the school bought new furniture (school desks and chairs) and in that way renewed the school's inventory. In the years that followed all classes were painted, much resource material was purchased for the execution of our lectures, and a projector for the showing of movies or other video material was purchased. The Executive of the Serbian school have tried to provide much support and guidance to the teachers and students so that their experience was as rewarding and enriched as possible. Over the years the school has organized many trips, educational in nature, for the students; including a trip to the Planetarium in Hamilton and the Royal Ontario Museum in Toronto We have also organized a fun trip at the end of each school year.
Many student volunteers have passed through the school, helping teachers, and in so doing have earned their volunteer certificate required to graduate from high school. Because they as well as the previous teachers, administrators and parent volunteers have all been an integral part of our success, we thank them and wish them many blessings from God.
Easter Celebration in our Church
Students of the Serbian school recited at the Church Slava!
Serbian School Trip to Serbian Museum in Windsor
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St.Sava Day Celebration
On Saturday January
27, 2018, St. Sava day celebration took place with participation of children attending Serbian school at St. Nicholas Serbian Orthodox Cathedral in Hamilton.
addressed to guests, parents, teachers and especially to our children came from Mr. Milan Matijevic, vice-president of the Church-school congregation and Serbian school.
"I hope you will agree with me, when I say that this St. Sava day celebration was one of the best in the past years. Not that I am saying that previous celebrations were of poor quality or less value, but this one looked to me as unforgettable.
Starting with our children at the stage, with our priests, V.Rev Djuro and V. Rev. Dejan, Our Father, three hymns, kumovi Branko and Sladjana Savic with their children Stefan and Milana and our children in their folklore costumes from our folklore organizations.
All of you had the opportunity to see your children on the stage, from JK/SK to grade eight. You saw and heard them, how unbelievably easy they performed their recitals and shows in Serbian language the performances of our children last night was sufficient to fill our hearts
with pride and happiness by seeing and hearing our children and their command of our Serbian language. Considering that we have a school generation that was 100% born and raised in Canada, and with such a good command of Serbian language we have witnessed
at St. Sava day celebration, believe me, we proudly can say that you as parents succeeded in accomplishing the very difficult task to secure our Serbian language alive, to preserve identity of your children and your culture, and the most important your faith.
Children, of course come to school to socialise, to be happy among their friends, and of course that our teachers are at their disposal to help them and support them either in Serbian or English languages.
With such a good foundation of our Serbian language, our children are capable to become familiar with many historical facts, Serbian history, culture, faith and many other interesting facts from our past.
All this is achievable with help from our teachers and our priests and of course our parents as they l can teach our children at their homes, but this can not replace social aspect, friendship, excursions, picnics, celebrations and Fridays at Serbian School at St. Nicholas Serbian
Orthodox Cathedral at Nash Rd. in Hamilton.
A special thank you goes to our students Emilija and Natalija for their fantastic performance as MC, it was not an easy task. Thanks also goes out to our priests and teachers. Thank you dear parents who helped in the kitchen, at the bar, selling cakes and tickets. Thanks
to Circle of Serbian Sisters and their support and hard work in the kitchen.
Thanks goes to all our sponsors, as without their support the success of our celebration would not be so great.
But before all and most of all thanks goes to our Heavenly Father and our Saint Sava.
St. Nicholas Serbian School
Milan Matijevic


Do you offer transfers to the resort?
Yes we do provide a complimentary transfer from the pier to the resort upon check in, all you need to do is inform us of your arrival time and the name of your ferry company at least one day prior. If you need to be picked up from another resort on Koh Tao you will need to inform us of the name of your resort and the time you would like to be picked up.
Do you have any specials for Honeymoon couples?
Please visit the packages page of our website to see our honeymoon specials: Kindly inform us if you will be traveling on your honeymoon and we will try to make your stay as special as possible.
Yes, all room rates quoted include breakfast.
How do I get to Koh Tao?
Does your resort offer snorkeling trips/scuba diving?
We do indeed offer private snorkeling trips from the resort; these can be booked at reception one day prior. If you would like to undertake a scuba diving course we are happy to assist you in finding a dive school nearby.
When is the best time to visit Koh Tao?
Koh Tao is a beautiful to visit all year round, however please note that monsoon season occurs in October and November and it is typically raining in these two months.
Extra beds are possible in SOME room types at an extra charge/per night. Please see the room description to determine if an extra bed is possible. If you require an extra bed please contact us prior to booking.
What payment options do you accept in your resort?
We accept Visa, Master Card and Thai Baht.
Early check ins and late check outs may be possible at the discretion of reception. If it is not possible we do have storage for luggage at reception, and you are welcome to use all resort facilities while you are waiting for check in or check out.
How much deposit do you require to secure my booking?
View Point Resort will ask for 100% payment of your room booking(s) to secure your reservation. Walk-in guests are also asked to pay 100% before check-in.
To avoid cancellation fees, cancellation has to take place 31 days prior to your arrival. For cancellations occurring between 30 and 15 days prior to your arrival date, 50% of the full room deposit will be retained. For cancellations occurring 14 days or less prior to your arrival date and for no shows, your room deposit will be retained in full. We regret that no refund will be granted for early check-out of View Point Resort.


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Startup Funding Rounds
Startup Funding and how it works?
The term "funding round" relates to the several rounds of investment that companies must have to raise money. As a startup's performance, client base, and evidence expand, its value will rise in successive rounds of valuing the business. At various points in a startup's development, it is possible to raise a range of different sources of capital. Pre-seed, seed, Series A (Series B), and elsewhere are all types of rounds. They're known as venturing rounds when they're backed by venture capital but don't fit into any other category. As a firm grows, it raises more money in each successive round of investment than the prior one.
Various Types of Startup Funding Rounds
Startups may be funded in a variety of ways, including the following:
A seed round is often sought when a concept is developed prototype developed. Encouraging indications that the service or product given is in high demand should be present. Typically, seed financing is utilised for research & innovation, market analysis, or team growth. There are seed accelerators that accept startup applications, grant seed funding, and allow the firm to demonstrate its commodities to more significant investors.
Round one of Series A:
Investors should be wary of this round since the firm is probably still in its early stages, making it a high-risk bet. In return for financial support, a company's creators and workers are often issued a Series A round of stakes.
Round of Series B
The company's value is anticipated to rise during this time. With more experience, the financial risk is reduced. Consequently, the cost to spend is also increased. The company's worth is determined by how well it performs in contrast to the rest of its industry and its current assets and future revenue prospects. There should be a rise in customers, income, and the success of goods and services at this stage. Private equity firms and venture capital firms are often involved in this financing round.
Round of Series C
A Series C another round of financing may be necessary when a company is poised for fast development. To acquire a rival firm, a corporation often has to have shown its viability in the industry, raised its share of the market or expanded, or created new products and services.
Pre Public Round
When a company's products and services have garnered enough popularity, it may elect to go public. Mergers and acquisitions, capital raising, price cuts, and other anti-competitive measures may be financed using the money obtained.
Angel Round
Suddenly, an angel round appears. When an angel round happens, it's usually at the startup phase, if not sooner. Before a considerable cash flow, companies at this stage generally need investment to pay the expenses of everyday operations. There are situations when a hybrid of the seed round and the angel round exists. A significant portion of the money raised in seed and angel rounds comes from family and friends and angel investors who are willing to put their money into startups. Investors often give a small amount of money in return for stock in a company. When a new company has a short track history, the risk is more significant than an established one.
A professional investment may also come forward and offer you financing in return for a share of stock in the firm if you can show that the concept or the company is gaining momentum. These investors, referred to as "investment firms," are on the watch for promising startups and make an early investment for them for a bit of interest. A company's current workings are usually out of their hands, so they only look at the creators and the team to see if they could put money where their mouth is and generate a profit. The venture capitalist will recoup their original investment and a constant stream of profits if they are successful in turning a profit.
Liquidity has been a true partner in our growth. We were able to work with the Liquidity team to structure, close, and draw down on a facility at a moment in time when the capital markets were paralyzed by the uncertainty of the global pandemic. Their ability to operate with a speed of execution critical for a dynamic, high growth startup has been second to none. This comes from a deep appreciation and commitment to the entrepreneur that Liquidity has demonstrated in every interaction with the team from CEO to Investment Manager.
Neal Shenoy
CEO, Homer
Working with the Mars growth team has been a pleasure. From the initial discussion, with a couple of API keys, the entire effortless DD process took only a few days and they presented us with a term sheet.
Aidan Lister
CEO, Uptick
With Liquidity's funding, we will aggressively expand on our sales and marketing efforts to grow our customer base and double revenues in 2021 and 2022
Niraj Ranjan
*Dynamics is designed to support only companies with over 12 months of sales history

redpajama_set_name: RedPajamaCommonCrawl


The Gammel mobile file pedestal offers organization and storage space for any office setting. Made in Italy from eco-friendly materials, the oak wood finish of the frame contrasts beautifully with the white high gloss drawer fronts. The top drawer locks for privacy.


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Flash flood watch issued for Upstate
Updated: 12:39 AM EDT Apr 29, 2013
A flash flood watch in effect until 8 p.m. Sunday for much of the region.The National Weather Service in Greenville-Spartanburg issued a flash flood watch for portions of northeast Georgia, western North Carolina and Upstate South Carolina. Greenville, Oconee, Pickens and Spartanburg counties are included in the watch area.To check for alerts in your area, click here.To track the rain with interactive radar, click here.Habersham, Rabun and Stephens counties in northeast Georgia and Buncombe, eastern Polk, Graham, Haywood, Henderson, Macon, Madison, northern Jackson counties and Rutherford mountains in North Carolina.A wide band of moderate to heavy showers and embedded thunderstorms will track across the region through the day. The duration and intensity of the rainfall rates is expected to result in flash flooding along small stream and creeks and possibly the head water areas of main rivers.Flash flooding is very dangerous. Residents should monitor later forecasts and be prepared to take action should flash flood warnings be issued.
A flash flood watch in effect until 8 p.m. Sunday for much of the region.
The National Weather Service in Greenville-Spartanburg issued a flash flood watch for portions of northeast Georgia, western North Carolina and Upstate South Carolina. Greenville, Oconee, Pickens and Spartanburg counties are included in the watch area.
To check for alerts in your area, click here.
To track the rain with interactive radar, click here.
Habersham, Rabun and Stephens counties in northeast Georgia and Buncombe, eastern Polk, Graham, Haywood, Henderson, Macon, Madison, northern Jackson counties and Rutherford mountains in North Carolina.
A wide band of moderate to heavy showers and embedded thunderstorms will track across the region through the day.
The duration and intensity of the rainfall rates is expected to result in flash flooding along small stream and creeks and possibly the head water areas of main rivers.
Flash flooding is very dangerous. Residents should monitor later forecasts and be prepared to take action should flash flood warnings be issued.


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Well-known Ukrainian beauty showed curvy in swimsuit: "Goddess"
magictr | June 28, 2019 | Entertainment | No Comments
Lily Rebrik two after birth, the figure is just great
Well-known Ukrainian TV presenter and actress Lily Rebrik involved in the new set. The girl shared photos on the social network page.
In the photos leading to the white leotard accentuates the lush bust, wearing a hat with a brim and high heels. As such, the Lily is brought to the audience in one of the films.
"Today was another great day of shooting in the film project, whose title is still a secret… When I allowed myself to swim in the pool in the middle of the day??))) When I allowed myself to come in swimsuit and hat to work?? Only in the movies! Only in the movies under actress swimsuit wear high heel shoes," wrote in the post Rebrik.
Fans praised the actress, calling her "beautiful", "goddess" and "star".
"Very nice shape", "Wow! Lily, You are gorgeous", "Can only envy", "Class, work, dream, dream about this", "that's a woman", "You're a very attractive girl, as you hold yourself in this form!","You really do not know" — continue to write followers.
We will remind, this year Rebrik celebrated the Passover for the first time the four of us. Youngest daughter Pauline Monday, April 30 was a year old. The baby it was the first Easter and the first holiday for the family in this composition. In Instagram leading shared colorful images.
Odessa was struck by a destructive element, in the city of chaos: horrific pictures of the consequences
Heart to the famous actress: "her beauty has conquered the world"
"Knocked down": in search of the missing child in the Kharkiv region raised the aviation
With a child, dead in the water Park, said goodbye to all the village: the details of the tragedy
That day the family visited the Easter service and consecrated Easter cakes. Four posed with Easter baskets, as well as inside the temple.
"Christ Is Risen! Happiness and peace… our First Easter the four of us," wrote rebryk under the post.
Subscribers artist never tired of touched photos. They want family warmth, peace and kindness.
Note, for the first time, newborn daughter Lily off to go. Family, husband and choreographer Andrew Wild, was photographed for the magazine together. In particular, in the lens were their 6-year-old daughter Diana.
"Well, meet wild Polina. All of our #DECACA in the collection," said Lily.
According to fans leading baby just like him. However, others argue that the two daughters went to the artist.
In the pictures the family looks perfect and happy.
We will remind, in the family of the famous Ukrainian leading real drama: "Mom, I will not love".
As reported Politeka, the soloist of the group "Neangely" have shown, how to rest after work.
Also Politeka wrote that the daughter of the captain boasted geeky photo in a bikini.
Meghan Markle splitting of Prince Harry with his brother: "it's very bad"
MARUV first told about his disease: "I learned to cope with the pain"
Shameless Polyakova dumped all the charm in the mini-swimsuit: "Burn those buns!"
Like Meghan Markle managed to get Prince brother of the Duchess revealed the truth


text:
Q: Regex for matching specific URL with multiple conditions I have the following regex pattern
const pattern = /^\/(abc|def|something\/thisone|en|ppp){1}/i;
const mat = pattern.exec(myURL);
Here How do I change the above pattern so that it wont match something/thisone but when it is followed by any params like so: something/thisone/<anystring/number> ..?
Tried:
const pattern = /^\/(abc|def|something\/thisone\/.*|en|ppp){1}/i;
const pattern = /^\/(abc|def|something\/thisone\/.+|en|ppp){1}/i;
Nothing seems to work..
Valid urls:
www.mysite.com/abc/
www.mysite.com/abc
www.mysite.com/def/
www.mysite.com/something/thisone/whatever
www.mysite.com/something/thisone/whatever/
www.mysite.com/something/thisone/whatever?u=90

A: After viewing added examples, knowing that OP does not want to capture anything, let's simplify this to:
www\.mysite\.com\/(?:abc|def|something\/thisone(?:\/[^\/\s]+)+)\/?

Explanation:
www\.mysite\.com         # match www.mysite.com
\/                       # followed by `/`
(?:                      # non-capturing group 1
  abc                    # 'abc'
  |                      # OR
  def                    # 'def'
  |                      # OR
  something\/thisone     # 'something/thisone' followed by
  (?:                    # non-capturing group 2
    \/                   # '/'
    [^\/\s]+             # 1 or more chars, not '/' or space
  )+                     # END group 2. 1 or more times.
)                        # END group 1
\/?                      # optional closing /

For examples: regex101

A: You can try this:
const pattern = /^\/(abc|def|something\/thisone\/[0-9a-zA-Z]*){1}/i;
The pattern [0-9a-zA-Z]* should match any number of alphanumeric characters.

A: Try this simple regex expression.

let regex = /.*something\/thisone\/.+/g

let string1 = 'something/thisone/acd';
let string2 = 'something/thisone/abc/';
let string3 = 'something/thisone';
let string4 = 'https://somedomain/something/thisone/123';

console.log(string1.match(regex));
console.log(string2.match(regex));
console.log(string3.match(regex));
console.log(string4.match(regex));

redpajama_set_name: RedPajamaStackExchange


text:
Justia Patents With Means Enabling Price ReadingUS Patent for Remote weigh station with delayed fraud intervention Patent (Patent # 10,366,379)
Remote weigh station with delayed fraud intervention
Jan 30, 2017 - NCR Corporation
Various embodiments herein each include at least one of systems, methods, software, and devices, such as remote weigh stations and ancillary devices thereof enabled to detect fraud possibilities during a product weighing at facilities, such as retail outlets. Some such embodiments include image processing to identify possible fraud.
Latest NCR Corporation Patents:
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Retail shrink mostly comes from customers stealing, cashier sweet-hearting, and employee theft. Item substitution fraud occurring at Self-Service Checkout (SSCO) and Point-Of-Sale (POS) terminals is one of the key shrink issues. Perpetrators commit the fraud by checking out an expensive item (e.g., a bottle of bourbon) as a cheap produce item (e.g., banana). For example, rather than scanning a barcode of an item, the item is placed on a scale, an item type is keyed in or otherwise selected such as bananas, and the item is priced at checkout by weight rather than by the product barcode.
These types of fraud occur primarily at checkout terminal. However, modern retail outlets continually evolve to reduce operating expenses and to provide customers enhanced, or at least differentiated shopping experiences. To these ends, some retail outlets, such as supermarkets, big-box stores, and boutique grocers have begun placing weigh stations in shopping areas where items are sold by weight, such as produce, spices, candy, grains, and the like. These weigh stations include a scale and functions and devices to identify a product being weighed and a label printer to print labels to be affixed to weighed products to enable the products to be priced at checkout, e.g., barcodes, product identifier numbers. Customers are thereby able to choose exactly an amount they want to purchase and scales can even be removed from checkout terminals.
As new solutions are added to the retail environment, such as remote weigh stations, nefarious actors typically move quickly to discover and exploit vulnerabilities.
Various embodiments herein each include at least one of systems, methods, software, and devices, such as remote weigh stations and ancillary devices thereof enabled to detect fraud possibilities during a product weight at facilities, such as retail outlets.
One embodiment, in the form of a method, includes receiving product identification input, a weight, and an image of an item present on a scale surface of a non-POS weigh station device and processing at least one of the weight and the image in view of the product identification input according to at least one validation process to obtain a validation result. When the validation result indicates validation success, the method includes outputting data to be printed on a scanable label to be affixed to the item. However, when the validation result indicates validation failure, the method includes outputting data to be printed on a scanable label to be affixed to the item to cause a notification to be output upon presentment at a POS terminal indicating the validation failure. The notification to be output at the POS terminal is a notification for a cashier or other attendant to intervene in the transaction to investigate for purposes of fraud prevention. The notification may be output directly from the POS terminal, such as an SSCO or an assisted POS terminal, on from another location or device, such as from an SSCO attendant terminal, supervisor terminal, or other location or device.
Another method embodiment includes receiving a product identifier and an image of an item present on a scale surface of a non-point of sale weigh station device and processing the image in view of the product identifier according to at least one validation process to obtain a validation result. When the validation result indicates validation success, this method includes outputting data to be printed on a scanable label to be affixed to the item. Otherwise this method includes outputting data to be printed on a scanable label to be affixed to the item to cause a notification to be output upon presentment at a point of sale terminal indicating a validation failure.
A further embodiment is a non-point of sale self-service terminal, such as a remote weigh stations. The non-point of sale self-service terminal of this embodiment includes a product scanner including at least one imaging device, an input device, a scale, and a label printer. The non-point of sale self-service terminal also includes a processor and a memory device storing instructions executable by the processor to perform data processing activities. The data processing activities may include receiving a product identifier, from the input device or the product scanner, and an image, from at least one imaging device of the product scanner, of an item present on the scale. The data processing activities further process the image in view of the product identifier according to at least one validation process to obtain a validation result and when the result indicates success, the data processing activities include printing, with the label printer, a scanable label to be affixed to the item. Otherwise, the data processing activities proceed with printing, with the label printer, a scanable label to be affixed to the item to cause a notification to be output upon presentment at a point of sale terminal indicating a validation failure.
FIG. 1 is a logical block diagram illustrating components of a weigh station having a scanner, according to an example embodiment.
FIG. 2 is a logical block diagram of a system architecture including at least one weigh station, according to an example embodiment.
FIG. 3 is a block flow diagram of a method, according to an example embodiment.
FIG. 6 is a block diagram of a computing device, according to an example embodiment.
Various embodiments herein each include at least one of systems, methods, software, and devices, such as scales, imaging devices, and product scanners (e.g., barcode scanners), enabled to detect possible fraud during a weighing event at remote weigh stations such as may be deployed at retail outlets. Such embodiments provide reliable results by applying fraud detection processes based on a number of factors, such as known product characteristics that can be measured by a scale, detected in images, and the like. These characteristics of products may be product specific or generalized and associated with a product. Thus, when a customer scans a product at a weigh station or enters an identifier of the product, specific or generalized product characteristics can be obtained and compared against the product presented for weighing. When a mismatch is identified and thereby indicating a potential fraud situation, various embodiment may issue one or more notifications to prevent the fraud from occurring. In one embodiment, a notification requiring employee intervention can be issued immediately. However, other embodiments may encode data printed on a label to be printed by the weigh station to cause the notification to be provided at a checkout station, such as an SSCO terminal or assisted checkout terminal.
The weigh station, in some such embodiments, includes efficient algorithms to enable a product scanner deployed therewith, such as the NCR RealScan 7879 Bi-Optic Imager available from NCR Corporation of Duluth, Ga., other other computing device with at least one imaging device and a scale coupled thereto, to detect possible fraud, such as item substitution fraud, in real-time. Note that item substitution fraud is sometimes referred to as bourbon item substitution fraud. The algorithms of some embodiments achieve an outstanding sub one-second real-time performance by not using an item database, thus, avoiding lengthy database searches and record matching. Instead, the algorithms of some embodiments use insightful, yet lean image processing techniques to swiftly identify the presence, or lack thereof, of certain features present in one or more collected images of an item presented at checkout. Some embodiments may fuse together identified features to boost detection accuracy against item substitution fraud. Some embodiments may also or alternatively include consideration of other factors, such as weight, color, profile shapes, label text, and other features that may be identified from sensors and devices that may be coupled to a remote weigh station.
These and other embodiments are described herein with reference to the figures.
In the following detailed description, reference is made to the accompanying drawings that form a part hereof, and in which is shown by way of illustration specific embodiments in which the inventive subject matter may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice them, and it is to be understood that other embodiments may be utilized and that structural, logical, and electrical changes may be made without departing from the scope of the inventive subject matter. Such embodiments of the inventive subject matter may be referred to, individually and/or collectively, herein by the term "invention" merely for convenience and without intending to voluntarily limit the scope of this application to any single invention or inventive concept if more than one is in fact disclosed.
The following description is, therefore, not to be taken in a limited sense, and the scope of the inventive subject matter is defined by the appended claims.
The functions or algorithms described herein are implemented in hardware, software or a combination of software and hardware in one embodiment. The software comprises computer executable instructions stored on computer readable media such as memory or other type of storage devices. Further, described functions may correspond to modules, which may be software, hardware, firmware, or any combination thereof. Multiple functions are performed in one or more modules as desired, and the embodiments described are merely examples. The software is executed on a digital signal processor, ASIC, microprocessor, or other type of processor operating on a system, such as a personal computer, server, a router, or other device capable of processing data including network interconnection devices.
Some embodiments implement the functions in two or more specific interconnected hardware modules or devices with related control and data signals communicated between and through the modules, or as portions of an application-specific integrated circuit. Thus, the exemplary process flow is applicable to software, firmware, and hardware implementations.
FIG. 1 is a diagram illustrating components of a weigh station 100 having a scanner 108, according to an example embodiment. It is to be noted that the weigh station 100 is shown schematically in greatly simplified form, with example components relevant to understanding various embodiments herein. The same situation may be true for the other various components of the weigh station 100. Also, note that the weigh station 100 may include more or fewer components in some embodiments. Additionally, the weigh station 100 may take quite a different form in some embodiments, such as by being a computing device (e.g., a Raspberry Pi board or other small computer) with a scale, an imaging device, and a label printer coupled thereto.
Furthermore, the various components included in the FIG. 1 as illustrated and arranged are provided for illustration purposes only. It is to be noted that other arrangements with more or fewer components are possible without departing from the contributions herein, in particular with regard to automatic and remote scanner configuration.
Moreover, the methods and weigh station presented herein and below may include all or some combination of the components shown in the context of the weigh station 100. Further, although a weigh station 100 is illustrated as including a scanner 108, the scanner 108 may be a standalone element or an element of other systems, devices, and terminals in other embodiment. Examples of terminal-types that may include a scanner 108 other than a weigh station 100 are self-service terminals (SSTs) such as SSCO terminals, POS terminals, clerk operated and self-service library checkout stations, time-keeping terminals, and the like. Additionally, references to POS terminals herein and in the claims are general references to both POS and SSCO terminals, unless expressly stated otherwise.
The methods of some embodiments are programmed as executable instructions stored in memory and/or non-transitory computer-readable storage media and executed on one or more processors associated with the components and devices herein.
The weigh station 100 includes one or more displays 102 that present information of a weigh station system 104 coupled to the one or more displays 102. Information presented by the one or more displays 102 includes information relevant in a retail context and with regard to operation of the weigh station 100, such as instructive prompts to enter a product identifier or to scan a product, to place a product on the scale, and to affix a printed label to the product. The one or more displays may also present a measured weight of a product, product information once the product is known from an input identifier or a scan of a barcode, a price per unit of weight, and other information. The weigh station 100 also includes the scanner 108.
The scanner 108 may be referred to as a barcode scanner as that is the task most commonly associated with such devices. During operation of the weigh station 100, items may be placed within a scan field of the scanner 108. One or more imaging devices 118 of the scanner 108, such as one or more of cameras and laser scanners then scan a barcode and information read therefrom is communicated to the weigh station system 104. The weigh station system 104 then uses that data to identify the item placed within the scan field of the scanner 108 and performs an additional function. The additional function may include a price lookup.
The scanner 108 may include one or more scan fields, such as two scan fields of hi-optic scanners that are commonly seen in grocery and discount retail outlets. Each scan field may include one or more imaging devices 118, such as cameras. In some embodiments, a total of four or more cameras may be included in one or both of the scan fields, combined. In addition to the imaging devices 118, the scanner 108 may include various other components. The various other components may include an integrated scale 110 such as may be used in a grocery outlet to weigh items such as produce and one or both of a speaker 112 and display lighting 116 to output audio a visual signals such as signals of (un)successful scans. The scanner 108 may also include scan field lighting 120 that may be turned on and off and adjusted based on a detected presence of an item to be scanned. The scanner 108 also includes one or more of at least one of a hardware communication interface 114 or a software or firmware communication interface 132 that enables to scanner to communicate with at least the weigh station system 104 communication interface 106 and, in some embodiments, over a network.
During typical operation, the scanner 108 is operated according to instructions executed on a processor 122. The processor may be a single or multi-core ASIC, digital signal processor, microprocessor, or other type of processor. The instructions may be firmware 126 or software 130 stored in one or more memories 124. The one or more memories 124 may be or include volatile and non-volatile memories, write-protected memories, write-once memories, random access memory (RAM), read only memories (ROM), and other memory and data storage types and devices.
The instructions as may be stored in firmware 126 or as software 130 in memory 124 are typically executed according configuration settings stored in the memory 124. The configuration settings 128 configure operation of the scanner 108 and the various components therein. For example, the configuration settings 108 may configure speaker 112 volume, display lighting 116 outputs, scan field lighting 120 brightness, decoding algorithm of the imaging device(s) 118 and the instructions, one or more communication protocols used to communicate data from the scanner 108 to the weigh station system 104, such as via a wired or wireless communication interface 106 of the weigh station system 104, scale 110 operating parameters (e.g., unit of measure as ounces, pounds, grams, kilograms), among other configuration settings of the particular scanner 108 an embodiment may include. In some embodiments, the configuration settings 128 may include a firmware version, a software version, and the like. Thus, when a configuration is set or updated, the setting or updating of the configuration settings 128 may include population and updates of any of the configuration settings 128 of a particular embodiment, including an update to firmware and software present on the scanner.
In some embodiments, the configuration settings 128 stored in the scanner 108 memory 124 may include configuration settings 128 for one or more fraud detection processes, such as one or more item substitution fraud detection processes. The one or more fraud detection processes, including the item substitution fraud detection processes, may be process stored as software 130 or firmware 126 within the memory 124 or other device within the scanner 108 or the weigh station system 104. These fraud detection processes are typically triggered for execution upon receipt of a command from the weigh station system 104, such as upon receipt of input into the weigh station system 104 to weigh a presented item on the scale 110. The fraud detection processes, which may be executed by the processor 122 or a processor of the weigh station system 104, operate against images received from the one or more imaging device 118 cameras or other cameras that may be coupled to either the weigh station system 104 or the scanner 108.
The fraud detection processes may be defined in the software 130 or firmware 126. In some embodiments, the item substitution fraud detection processes are generic processes that may be flexibly configured within configuration settings 128 or configuration settings of the weigh station system 104. For example, some embodiments may include one or more item substitution fraud detection processes that are simply defined within the software 130 when the software is authored. Some of these processes may be modified through the configuration settings 128. In some other embodiments, the item substitution fraud detection processes are a collection of different processes in the software 130 or firmware 126 that may be linked together by configuration settings 128 to form larger, conditional item substitution fraud detection processes. In other embodiments, fraud detection processes may be accessed via a network by providing one or both of data and images to a cloud-based fraud detection resource. Regardless of the form and configuration of the fraud detection processes, the fraud detection processes generally process data images captured by imaging device(s) 118 and the scale 110 to identify features of presented items represented therein. In some embodiments, the fraud detection processes operate to determine whether the weight of the item is within a reasonable range for the product presented for weighing or whether a presented item is a manmade item or a produce item. For example, it is unlikely someone would be purchasing two pounds of a spice. Further, determining whether an item is manmade generally includes identifying features in images that rarely, if ever, occur in natural products, such as produce. Such features may include straight lines, parallel lines, certain shape silhouettes, glare or an amount or size of glare occurrences, among other features.
FIG. 2 is a logical block diagram of a system 200 architecture including at least one weigh station 2041-N, according to an example embodiment. The system 200 is deployed in a retail outlet, such as a grocery store. The system 200 includes at least one weigh station 2041-N typically deployed in a produce area of a grocery store or other area where items are sold per unity of weight. The weigh station(s) 2041-N may be connected to a network in some embodiments to perform tasks such as price lookups to obtain a current price of a product when presented or periodic retrievals of product pricing data for local storage, such as daily. In some embodiments, a weigh station 2041-N, when weighing an item presented on a scale thereof for pricing, performs at least one validation process to verify the item presented matches a product identifier either manually input or received from a product scanner that scanned a barcode affixed to the presented item. When a match is verified, at least within a certain probability, a price for the item may be determined and a label printed to be affixed to the item for scanning at a checkout terminal. However, when a match is not verified, such as when the item does not match the product of the product identifier or the match has a probability lower than an acceptable threshold, fraud prevention is triggered. The fraud prevention may simply include locking the weigh station 2041-N and requesting an employee to intervene to resolve the issue. However, for many reasons, an intervention at that time may not be desired. For example because the cause might simply be a customer error, no law has been broken or loss incurred yet, staffing a weigh station 2041-N area may not be desired, among other reasons. In such situations, a label may still be printed, but the label is scanned at a checkout station, an intervention will be initiated to resolve the potential fraud issue.
Thus, when a label is generated and printed for a presented item, the weigh station 2041-N, in some embodiments, may upload all or a portion of the label data to a price lookup or other store database 206. Also uploaded to the database 206 may be images and other sensor data (e.g., weight) related to the transaction at the weigh station 2041-N to make that data available for review by security personnel prior to or when the customer presents the item at checkout. Security personnel may then clear identified fraud potential if fraud is not involved through verification of the pictures, may monitor the individual customer while in the store, summon law enforcement authorities, or take other action. Additionally, the images may be used as evidence, for training, and further fraud detection process development and refining. Subsequently when the customer presents the item for purchase at checkout, the checkout terminal may retrieve the data associated with the label from the database 206 or that data may have been encoded in the barcode printed and affixed to the item.
In some embodiments, a customer bags and weighs produce, such as a bag of green beans, and presents them for weighing at a weigh station 2041 in the produce department. A controller of the weigh station 2041 retrieves the produce item price-per-weight (e.g., pound) from the database 206 or from a local memory, and calculates the cost. The weigh station 2041 controller may then analyze the items being weighed for possible fraud scenarios as embodied in one or more fraud detection processes that may be local to the weigh station 2041 or accessed as web services or other processes on a network. The weigh station 2041 controller may then print a barcode for the customer to affix to their bag of produce. The weigh station controller 2041 may also store the price, weight, and fraud detection analysis results in, or associates them with, the printed barcode, such as by storing them to the database 206. The customer may then finish their shopping, and proceeds to a POS terminal 208, cashier assisted, SSCO, or otherwise. The printed barcode affixed to the produce bag is then scanned and need not be weighed. A POS terminal 208 controller retrieves the price, weight, and fraud detection analysis results from the produce barcode or from the database 206, considers the fraud detection data, and triggers a customer assistance intervention if fraud potentially present. In some SSCO embodiments, a weight of the item may be requested and verified, as well as performance of additional fraud detection processing.
FIG. 3 is a block flow diagram of a method 300, according to an example embodiment. The method 300 is an example of a method that may be performed in whole or in part on a controller or other computing of a weigh station or within a scanner that is part of a weigh station, in various embodiments.
The method 300 includes receiving 302 product identification input, a weight, and an image of an item present on a scale surface of a non-point of sale weigh station device and processing 304 at least one of the weight and the image in view of the product identification input according to at least one validation process to obtain a validation result. In such embodiments, when the validation result indicates validation success, the method 300 includes outputting 306 data to be printed on a scanable label to be affixed to the item. Otherwise, when the validation result indicates validation failure, the method 300 includes outputting 308 data to be printed on a scanable label to be affixed to the item to cause a notification to be output upon presentment at a point of sale terminal indicating the validation failure.
In some embodiments of the method 300, the product identification input includes at least one of a price per unit of weight and a product identifier to retrieve product data. Also, the product data retrievable with the product identifier may include a price per unit of weight and product property data that is utilized by the at least one validation process to perform validation that a product presented matches the received product identification input. The price per unit of weight may be retrieved based on at least a portion of the product identifier from a memory device of the non-point of sale weigh station device.
In another embodiment of the method 300, the product identification input is received 302 as a data item read by a scanning process or device from the image of the item present on the scale. The validation process in some of these and other embodiments may include a set of validation processes that each execute to identify one or more properties of an item presented on the scale surface as captured in the received 302 image. Note that the received 302 image may be one or a plurality of images in different embodiments. Also, when there is only one image, the one image may include a composite view with each view captured by a different imaging device or a single imaging device that captures the composite view through an arrangement of mirrors. Additionally, in other embodiments, one or more captured images may be moving images (i.e., video, video clips, etc.).
In some embodiments, one validation process may be performed on the received 302 image to remove a background of the image leaving only the item presented on the scale surface. The image, with the background removed may then be used to perform at least one additional validation process that outputs the validation result. The validation result may include or be based at least in part on an indication of whether the presented item is a naturally occurring or man-made item. In some such embodiments, the at least one additional validation process may include one or more of a silhouette detection process, a glare detection process, a straight line process, and a parallel line process, among others.
The silhouette detection process may process an image to leave a silhouette of the presented item which is then compared to a reference model of a man-made item and when relatively matched, outputs an indication the presented item is likely man-made. The glare detection process may evaluate areas within the presented item image portion for distinct occurrences of glare and when a number of glare occurrences larger than a first threshold is greater than a second threshold, an indication the presented item is likely man-made may be output. In both the straight and parallel line process, a Hough transform may be performed on the image of the presented item and then one or both of the straight-line detection and parallel line detection process may be performed thereon. When the straight line detection process identifies a number of straight lines longer than a length threshold greater than a count threshold, an indication the presented item is likely man-made may be output. When the parallel line detection process identifies at least two parallel lines that each have at least a minimum length and separated by at least a minimum distance, outputting an indication the presented item is likely man-made.
In some embodiments of the method 300, the received 302 image is one of a plurality of received 302 images where each image captured either from a different angle, zoom, or resolution. In one such embodiment, at least one of the silhouette detection, glare detection, straight line detection, and parallel line detection processes are performed on at least two images and the output 308 of the indication that the presented item is likely man-made is output 308 only upon reaching the same conclusion through the respective process upon processing at least two images. In some of these and other embodiments, when an output 308 of only one of the silhouette detection, glare detection, straight line detection, and parallel line detection processes output an indication that the presented item is likely man-made with regard to only a single image, the method 300 may include performing further processing 304 with regard to that single image to identify at least one additional feature present therein to confirm that the item present in the image is man-made. The method 300 in such embodiments may then output 308 an indication that the presented item is likely man-made when the at least one additional feature is present in the image.
In some of these background removal embodiments, removing the background may include down sampling each image, of one or more received 302 images, to a lower resolution and subtracting a background reference image from) a current image. The background reference image subtracted in this process is of an identical resolution and captured by a respective camera that captured the current image. A pixel-by-pixel comparison may then be performed between reference image pixels and current image pixel and removal of the pixel from the current image may be done when the difference between current image pixel value and the reference image pixel value is lesser than a threshold. The threshold value may be variable in some embodiments and determined based on the value of one of the current image and reference image pixel values.
FIG. 4 is a block flow diagram of a method 400, according to an example embodiment. The method 400 is another example of a method that may be performed on or at a weigh station. The method 400 includes receiving 402 a product identifier and an image of an item present on a scale surface of a non-point of sale weigh station device and 404 processing the image in view of the product identifier according to at least one validation process to obtain a validation result. When the validation result indicates validation success, the method 400 outputs 406 data to be printed on a scanable label to be affixed to the item. Otherwise the method 400 outputs 408 data to be printed on a scanable label to be affixed to the item to cause a notification to be output upon presentment at a point of sale terminal indicating a validation failure.
FIG. 5 is a block flow diagram of a method 500, according to an example embodiment. The method 500 is an example of an item substitution fraud detection process that is provided as an example of one fraud detection process that may be performed in some embodiments. Other fraud detection processes may also or alternatively be performed in some embodiments.
The method 500 is an example of an item substitution fraud detection process that is made up of several sub-processes, which themselves may be referred to herein as processes. The method 500 may be defined in software or firmware within a scanner as described above. In some other embodiments, the method 500 may be defined in scanner configuration settings that reference and interrelate the included sub-processes. In some embodiments, the method 500 is defined to determine if an item presented at a weigh station is an item of produce or is a man-made item. The method 500 may be triggered on a scanner upon receipt of input indicating an item is presented for weighing. When the item presented is determined to be man-made rather than produce or other non-man-made item when the item presented is supposedly produce, a signal is returned by the process to perform one or more actions, such as not accepting the item, freezing the weigh station, or other actions as described above.
The method 500 in some embodiments includes receiving at least one reference image 502 and at least one current image 504. As a scanner or a weigh station in general may include a plurality of cameras, the number of reference images 502 and current images received may be dependent upon the number of cameras, in some embodiments. In typical embodiments, a reference image 502 is stored in a scanner memory for each scanner camera. A reference image 502 is an image captured by a respective camera at a time when no items are present within the field of view. A reference image 502 therefore generally is a representation of a background that will be included in a current image captured by the respective camera. Thus, in some embodiments, when a current image 504 is received from a camera, a reference image 502 for the respective camera can be retrieved from memory and is therefore received by the method 500.
The current image 504 may then be down sampled 506 to a lower resolution. The reference image 502 may also be equally down sampled 506 in some embodiments. However, the reference image 502 may have been previously down sampled 506 in some embodiments. In some embodiments, the down sampling 506 is a pyramidal down sampling that is performed in a 2×2 manner to combine vertically adjacent pixels and horizontally adjacent pixels. The down sampling 506 may be performed once, twice, three, four, or more times, depending on the size of the received current image 504 and reference image 502, when the reference image is down sampled 506. The amount of down sampling 506 performed may also be dependent upon the amount of processing resources and utilization load of processing resource on the weigh station or other device performing the method 500.
After the down sampling 506 is complete, the reference image 502 may be subtracted 508 from the current image 504. As the current image 504 is captured by the same camera as the reference image 502, the current image includes a presented item and background therein. The subtracting 508 therefore may identifying pixels between the two images that have identical values and remove those pixels from the current image 504. The result is a subtracted image 510 that includes only the presented item and other things that are in the current image but not previously present in the reference image 502, such as a portion of a body of a person presenting the item.
The subtracted image 510 is then processed by a brightness-to-noise process 512. The brightness to noise process 512 performs a pixel-by-pixel comparison of pixel values between pixels of the subtracted image 510 and corresponding pixels of the reference image 502. In some embodiments, when a difference between two pixels reveals the subtracted image 510 pixel having a brightness value greater than the corresponding reference image 502 pixel by an amount less than a threshold, the pixel is removed from the subtracted image 510. This threshold, in some embodiments, is variable based on a brightness value of the pixel in either the reference image 502 or the subtracted image 510. For example, the threshold may be determined in whole or in part as a percentage of the brightness of one of these pixels. This may be a five percent threshold in some embodiments, such that the difference in brightness value must be more than five percent of a brightness value of the reference image 502 pixel. Once the pixel-by-pixel comparison is complete, a foreground image 514 remains that includes only an item presented.
Next, or in parallel to the described operations of the method 500 since the reference image 502 and current image 504 were down sampled 506, the method 500 includes performing edge detection 516 processing on the current image 504. The edge detection 516 processing may be performed against a copy of the current image 504 as received or against a down-sampled 506 copy. Hotspot masking 518 may then be performed to adjust pixel brightness in areas of the image being processed to adjust for known bright areas of the image. The hotspot masking 518, in some embodiments, may adjust pixel brightness higher or lower. The hotspot masking 518 may be performed according to one or more configuration settings in some embodiments. At this point, the image will include edges of items present in the original received current image 504 with the edge represented as lines.
Next, silhouette detection 520 is performed on the image in view of one or more reference models of man-made items, and other items in some embodiments. The one or more reference models utilized by the silhouette detection 520 each include a silhouette of interest, such as a silhouette of a man-made item, which may be silhouette of a bottle, a box, or other item. A reference model utilized in silhouette detection 520 may also be referred to as a model or a silhouette model. The silhouette detection 520 operates to determine if a silhouette of a reference model is present as lines remaining in the image being processed. As a distance of an item present in a current image is dependent upon a distance from a camera that captured the image, a silhouette of a reference model may be scaled to determine of a match can be found at different relative sizes.
When no match is found by the silhouette detection 520, the process fails at 522 and the processing may continue to an orientation check 524. When a match is found, the method 500 outputs a signal at 522 to the weigh station indicating the item is man-made, and therefore not an item of produce. The method 500 then ends. In embodiments where a plurality of current images 504 are being processed, the result of the silhouette detection 510 may need to be identical with regard to at least two or more of the current images 504 before determining whether the silhouette detection 520 fails or not at 522. In some embodiments, the method 500 only proceeds from the silhouette detection 520 to the orientation check 524 when at least one current image 504 has been successful in identifying a known silhouette of a reference model, but not enough to be classified as true. When no silhouettes are detected, the method may proceed to perform glare detection.
As described above, the orientation check 524 is performed when a silhouette was detected in at least one image. The orientation check 524 is performed to confirm a man-made item is present in an image for which a silhouette was identified, but not enough of the other images confirmed the silhouette. The orientation check 526 searches for other details within the image within which a silhouette was identified, such as the presence of text, a label, angle orientation of lines of the silhouette, and other such features that may be present in the image. When confirmation is made, the method 500 outputs a signal at 526 to the weigh station indicating the item is man-made, and therefore not an item of produce. The method 500 then ends. However, if confirmation is not made, the method 500 proceeds from 526 to the glare detection 530 process.
Next, or again in parallel to the described operations of the method 500 since the reference image 502 and current image 504 were down sampled, the method 500 includes performing hotspot masking 528 on either the current image 504 as it was received or as down sampled 506. Hotspot masking 528 may be performed to adjust pixel brightness in areas of the image being processed to adjust for known bright or dark areas of the image. The hotspot masking 528, in some embodiments, may adjust pixel brightness higher or lower. The hotspot masking 528 may be performed according to one or more configuration settings in some embodiments.
Subsequently, the glare detection 530 process may be called following either the silhouette detection 520 or the orientation check 524, as described above. The glare detection 530 searches for a number of glare areas within the image output by the hotspot masking 528 process defined by pixels having a brightness greater than a certain value that occur in contiguous image areas having at least a certain length and width. When the number of such areas is sufficient in view of a glare detection threshold, the glare detection 530 process is satisfied and the method 500 outputs a signal at 532 to the weigh station indicating the item is man-made, and therefore not an item of produce. The method 500 then ends. However, if the glare detection threshold is not satisfied, the method 500 proceeds from 532 to the straight-line detection 536 process.
At some point in the performance of the method 500 prior to execution of the straight line detection 536 process, a Hough transform 534 process is performed on an image copy output by the hotspot masking 518. The Hough transform 534 process is an image feature extraction process that identifies lines in the image. The straight-line detection 536 process then evaluates lines located in the image by the Hough transform 534 process in view of a rule. The rule in some embodiments, which may be set in a configuration setting, looks for lines having a more than five lines with a length greater than 30 pixels. When there are more than five lines having a length greater than 30 pixels, the straight-line detection 536 process is satisfied and the method 500 outputs a signal at 538 to the weigh station indicating the item is man-made, and therefore not an item of produce. The method 500 then ends. However, the straight-line detection 536 process is not satisfied, the method 500 proceeds from 538 to the parallel line detection 540 process.
The parallel line detection 540 process operates against the image output by the Hough transform 534 process to determine whether there are at least two parallel lines having a length of at least ten pixels and separated by a distance of at least 25 pixels present in the image. The number of parallel lines, length thereof, and distance between may vary in different embodiments and may be configurable in some embodiments.
When satisfactory parallel lines are identified, the parallel line detection 540 process is satisfied and the method 500 outputs a signal at 542 to the weigh station indicating the item is man-made, and therefore not an item of produce. The method 500 then ends. However, if the parallel line detection 540 process is not satisfied, the method 500 proceeds outputs a signal at 542 to the weigh station indicating the item is likely an item of produce and the method 500 ends.
The method 500 is merely one example of an item substitution fraud detection process that may be defined in and executed on or at a weigh station. The various elements of the method 500 may be fewer, greater, different, and performed in a different order, in various embodiments.
FIG. 6 is a block diagram of a computing device, according to an example embodiment. In one embodiment, multiple such computer systems are utilized in a distributed network to implement multiple components in a transaction-based environment. An object-oriented, service-oriented, or other architecture may be used to implement such functions and communicate between the multiple systems and components. One example computing device in the form of a computer 610, may include a processing unit 602, memory 604, removable storage 612, and non-removable storage 614. Although the example computing device is illustrated and described as computer 610, the computing device may be in different forms in different embodiments. For example, the computing device may instead be a smartphone, a tablet, smartwatch, or other computing device including the same or similar elements as illustrated and described with regard to FIG. 6. Devices such as smartphones, tablets, and smartwatches are generally collectively referred to as mobile devices. Further, although the various data storage elements are illustrated as part of the computer 610, the storage may also or alternatively include cloud-based storage accessible via a network, such as the Internet. In some other embodiments, the example computing device may be in the form of a weigh station system or the computer 610 may be a computer that controls a weigh station.
In the computer 610, the memory 604 may include volatile memory 606 and non-volatile memory 608. Computer 610 may include—or have access to a computing environment that includes a variety of computer-readable media, such as volatile memory 606 and non-volatile memory 608, removable storage 612 and non-removable storage 614. Computer storage includes random access memory (RAM), read only memory (ROM), erasable programmable read-only memory (EPROM) and electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD ROM), Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium capable of storing computer-readable instructions.
Computer 610 may include or have access to a computing environment that includes input 616, output 618, and a communication connection 620. The input 616 may include one or more of a touchscreen, touchpad, mouse, keyboard, camera, one or more device-specific buttons, one or more sensors integrated within or coupled via wired or wireless data connections to the computer 610, and other input devices. The computer 610 may operate in a networked environment using a communication connection 620 to connect to one or more remote computers, such as database servers, web servers, and other computing device. An example remote computer may include a personal computer (PC), server, router, network PC, a peer device or other common network node, or the like. The communication connection 620 may be a network interface device such as one or both of an Ethernet card and a wireless card or circuit that may be connected to a network. The network may include one or more of a Local Area Network (LAN), a Wide Area Network (WAN), the Internet, and other networks. In some embodiments, the communication connection 620 may also or alternatively include a transceiver device, such as a BLUETOOTH® device that enables the computer 610 to wirelessly receive data from and transmit data to other BLUETOOTH® devices.
Computer-readable instructions stored on a computer-readable medium are executable by the processing unit 602 of the computer 610. A hard drive (magnetic disk or solid state), CD-ROM, and RAM are some examples of articles including a non-transitory computer-readable medium. For example, various computer programs 625 or apps, such as one or more applications and modules implementing one or more of the methods illustrated and described herein or an app or application that executes on a mobile device or is accessible via a web browser, may be stored on a non-transitory computer-readable medium.
It will be readily understood to those skilled in the art that various other changes in the details, material, and arrangements of the parts and method stages which have been described and illustrated in order to explain the nature of the inventive subject matter may be made without departing from the principles and scope of the inventive subject matter as expressed in the subjoined claims.
receiving product identification input, a weight, and an image of an item present on a scale surface of a non-point of sale weigh station device;
processing at least one of the weight and the image in view of the product identification input according to at least one validation process to obtain a validation result;
when the validation result indicates validation success, outputting data to be printed on a scanable label to be affixed to the item; and
when the validation result indicates validation failure, outputting data to be printed on a scanable label to be affixed to the item to cause a notification to be output upon presentment at a point of sale terminal indicating the validation failure.
2. The method of claim 1, wherein the product identification input includes at least one of a price per unit of weight and a product identifier to retrieve product data.
3. The method of claim 2, wherein the product data retrievable with the product identifier includes a price per unit of weight and product property data that is utilized by the at least one validation process to perform validation that a product presented matches the received product identification input.
4. The method of claim 3, wherein the price per unit of weight is retrieved based on at least a portion of the product identifier from a memory device of the non-point of sale weigh station device.
5. The method of claim 1, wherein the product identification input is received as a data item read by a scanning process or device from the image of the item present on the scale.
6. The method of claim 1, wherein the validation process includes a set of validation processes that each execute to identify one or more properties of an item presented on the scale surface as captured in the received image.
7. The method of claim 6, wherein at least one validation process is performed with regard to the received image to remove a background of the image leaving only the item presented on the scale surface and to perform at least one additional validation process that outputs the validation result, the validation result including or based at least in part on an indication of whether the presented item is a naturally occurring or man-made item, the at least one additional validation process including at least one of:
a silhouette detection process that processes an image to leave a silhouette of the presented item which is then compared to a reference model of a man-made item and when relatively matched, outputting an indication the presented item is likely man-made;
a glare detection process that evaluates areas within the presented item image portion for distinct occurrences of glare and when a number of glare occurrences larger than a first threshold is greater than a second threshold, outputting an indication the presented item is likely man-made; and
performing a Hough transform on the image of the presented item and performing at least one of a straight-line detection process and a parallel line detection process, wherein: when the straight line detection identifies a number of straight lines longer than a third threshold greater than a fourth threshold, outputting an indication the presented item is likely man-made; and when the parallel line detection identifies at least two parallel lines each having at least a minimum length and separated by at least a minimum distance, outputting an indication the presented item is likely man-made.
the received image is one of a plurality of received images, each image captured either from a different angle, zoom, or resolution;
at least one of the silhouette detection, glare detection, straight line detection, and parallel line detection processes are performed on at least two images and the output of the indication that the presented item is likely man-made is output only upon reaching the same conclusion through the respective process upon processing at least two images; and
when an output of only one of the silhouette detection, glare detection, straight line detection, and parallel line detection processes output an indication that the presented item is likely man-made with regard to only a single image, performing further processing with regard to that single image to identify at least one additional feature present therein to confirm that the item present in the image is man-made and outputting an indication that the presented item is likely man-made when the at least one additional feature is present in the image.
9. The method of claim 7, wherein removing the background of the at least one image includes:
down sampling each image, of one or more received images, to a lower resolution;
subtracting a background reference image from a current image, the background reference image subtracted being of an identical resolution and captured by a respective camera that captured the current image; and
performing a pixel-by-pixel comparison between reference image pixels and current image pixels and removing the pixel from the current image when the difference between current image pixel value and the reference image pixel value is lesser than a threshold value, the threshold value variable determined based on the value of one of the current image and reference image pixel values.
10. The method of claim 1, wherein the output is output to a label printer.
11. A method comprising:
receiving a product identifier and an image of an item present on a scale surface of a non-point of sale weigh station device;
processing the image in view of the product identifier according to at least one validation process to obtain a validation result; and
when the validation result indicates validation success, outputting data to be printed on a scanable label to be affixed to the item; otherwise
outputting data to be printed on a scanable label to be affixed to the item to cause a notification to be output upon presentment at a point of sale terminal indicating a validation failure.
12. The method of claim 11, wherein the product identifier includes at least one of a price per unit of weight and a product identifier number to retrieve product data.
13. The method of claim 12, wherein the product data retrievable with the product identifier includes a price per unit of weight and product property data that is utilized by the at least one validation process to perform validation that a product presented matches the received product identification input.
14. The method of claim 11, wherein the product identifier is received as a data item from a product scanner or as read by a scanning process from the image of the item present on the scale.
15. The method of claim 11, wherein the validation process includes a set of validation processes that each execute to identify one or more properties of an item presented on the scale surface as captured in the received image.
16. The method of claim 15, wherein at least one validation process is performed with regard to the received image to remove a background of the image leaving only the item presented on the scale surface and to perform at least one additional validation process that outputs the validation result.
17. The method of claim 16, wherein the validation result includes or is based at least in part on an indication of whether the presented item is a naturally occurring or man-made item as determined by at least one of silhouette, glare, detection, and straight line detection processes.
18. A non-point of sale self-service terminal comprising:
a product scanner including at least one imaging device;
an input device;
a scale;
a label printer;
a memory device storing instructions executable by the processor to perform data processing activities comprising: receiving a product identifier, from the input device or the product scanner, and an image, from at least one imaging device of the product scanner, of an item present on the scale; processing the image in view of the product identifier according to at least one validation process to obtain a validation result; and when the validation result indicates validation success, printing, with the libel printer, a scanable label to be affixed to the item; otherwise printing, with the label printer, a scanable label to be affixed to the item to cause a notification to be output upon presentment at a point of sale terminal indicating a validation failure.
19. The non-point of sale self-service terminal of claim 18, further comprising:
a network interface device; and
wherein the data processing activities, when the validation result does not indicate success, further comprise: generating a unique identifier and associating a further data item therewith indicating the validation failure; encoding the unique identifier and the further data item in the data for printing to the scanable label; transmitting, via the network interface device, the unique identifier and the further data item to a database accessible by point of sale terminals upon a scan of the printed scanable label affixed to the item.
20. The non-point of sale self-service terminal of claim 19, wherein when the validation result indicates validation success, the data processing activities further comprise:
retrieving price per unit of weight data from the memory device based on the product identifier;
calculating a price based on a weight received from the scale multiplied by the retrieved price per unit of weight;
encoding the price in the data for printing on the scanable label to be affixed to the item.
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Filed: Jan 30, 2017
Date of Patent: Jul 30, 2019
Patent Publication Number: 20180218350
Assignee: NCR Corporation (Atlanta, GA)
Inventor: John Crooks (Duluth, GA)
Primary Examiner: Ashford S Hayles
Application Number: 15/419,285
Current U.S. Class: With Means Enabling Price Reading (186/61)
International Classification: G06Q 20/20 (20120101); G07G 1/00 (20060101); G06K 7/14 (20060101); G06K 1/12 (20060101); G01G 19/414 (20060101);


Orange County alt-rockers Kiev released their debut full-length album, Falling Bough Wisdom Teeth, in October of last year. In support of the record, the band is kicking off a west coast tour today with fellow Californians Bad Suns.
Having recently unveiled their otherworldly video for Falling Bough Wisdom Teeth album cut "Be Gone Dull Cage," the band has now dropped an incredible live video of "Solving and Running"- shot in a stunningly picturesque desert locale.
Falling Bough Wisdom Teeth was produced & engineered by Chris Shaw (Wilco, Phish, Super Furry Animals), and pays homage to collective band influences & minimalist pioneer Steve Reich. The members of Kiev have strong connections to the world of visual art, and have orchestrated & added a multi-faceted 3D element to their live performances. Additionally, the LP art was originally a band favorite by renowned contemporary artist Walton Ford, who gave the band his blessing to use it as the cover for Falling Bough Wisdom Teeth upon hearing the record & how it spoke to his painting.


A sponge ball that looks just like an Mandarin orange.
Audiences love these, especially with all the stories you come up with! Tell them the grocery store offered a 2-for-1 special, and turn 1 ball into 2! Or the reverse – you know you bought 2, but when you got home, there was only 1! The grocer felt so badly, he turned them into 4!


text:
Liberia: ICRC helps authorities improve living conditions for prison inmates
Monrovia Central Prison, Liberia. An ICRC delegate talks to an inmate after accommodation is sprayed against bed bugs. CC BY-NC-ND / ICRC / J. Jallah
The ICRC recently helped the Liberian authorities fumigate Monrovia Central Prison against bed bugs. This is part of our support to prison authorities in their efforts to improve conditions for inmates, which also includes basic infrastructure improvements and training.
It is Thursday morning in Monrovia. An environmental health team from the Ministry of Health and an ICRC team arrive at Monrovia Central Prison. Their mission: to fumigate the entire prison to combat the bed bugs that have infested the cells for months.
"Bed bugs feed on humans. They don't spread diseases, but the bites really make you miserable," says Olukunbi A. Orimoloye, the ICRC detention nurse in Liberia. After detainees alerted us to the presence of the blood-sucking insects, we provided chemicals for a seven-day fumigation operation covering 141 cells and corridors.
"This spraying represents major progress and it needs to be repeated quarterly," says health ministry official Kollie Kennedy. "Unfortunately, our government doesn't have the money to purchase the chemicals."
Monrovia Central Prison, Liberia. Equipment and chemicals stand ready for the fumigation operation. CC BY-NC-ND / ICRC / J. Jallah
Detainees wait in the ICRC-built sunbath area while the effects of the chemical to wear off so they can safely return to their cells. Daniel,* one of the inmates, tells us: "Spraying has reduced the biting and killed the cockroaches, but mosquitoes and rats are still a serious problem and we would like the ICRC to provide us with mosquito nets."
Monrovia Central Prison, Liberia. The joint fumigation team of the Ministry of Health and the Bureau of Corrections and Rehabilitation discusses the spraying operation. CC BY-NC-ND / ICRC / J. Jallah
The ICRC is helping prison authorities improve the living conditions of the inmates, and this has involved repairing sewerage systems and building or refurbishing wells in several Liberian prisons. "We also provide medicines, food and basic items, and the ICRC has recently provided 12 food carriers and 4 food trays for easy delivery of food to inmates of Monrovia Central Prison," says Miroslawa Czerna, the ICRC protection coordinator in Liberia.
Monrovia Central Prison, Liberia. An operator fumigates a cell. CC BY-NC-ND / ICRC / J. Jallah
The ICRC has also been supporting other prisons in Liberia. We have installed a water tower, water pumps and two new kitchens equipped with energy-efficient stoves. In addition, the ICRC has refurbished a clinic and supplied it with drugs and equipment. Finally, we have trained staff and inmates in such areas as the prevention of infection, kitchen hygiene and store-room management.
* Not his real name
Helping detainees


text:
Мухаметхан Сахипгареевич Кулаев (, 1873—1958) — государственный и общественный деятель, участник Башкирского национального движения, Председатель Башкирского Правительства, учёный-филолог и исследователь башкирского языка, врач, доктор медицинских наук.

Биография
Происходил из усерганских башкир, родился 25 января (8 февраля по новому стилю) 1873 года в деревне Зианчурина Орского уезда Оренбургской губернии(ныне Кувандыкский район Оренбургской области). Сначала учился в медресе при мечети в родной деревне, а через два года перешёл в открывшуюся русско-башкирскую школу. После её окончания в 1886 году поступил в Оренбургскую гимназию. Окончив обучение в гимназии в 1896 году, поехал в Казань для поступления на медицинский факультет Казанского университета. Но инородцам, нехристианам доступ был туда закрыт, и поэтому он решил перейти в православие, крестился он прямо у священника университетской церкви и стал Мстиславом Александровичем.

В 1902 году получает диплом врача и назначается доктором в госпитале города Казань. В 1910 году получает степень доктора медицинских наук. Кроме врачебной науки занимается изучением фонетического строя и грамматики башкирского языка. Является автором алфавита и букваря для башкир на русской графической основе и 1912 году издает книгу «Основы звукопроизношения и азбука для башкир».

В 1913 году был направлен на врачебную работу в город Варшава. С начала Первой мировой войны вплоть до Октябрьской революции и выхода России из войны с Германией служил главным врачом 275-го полевого госпиталя Юго-Западного фронта. После начала революции возвращается в Казань, затем в Оренбург по приглашению Председателя Башкирского Правительства Шарифа Ахметовича Манатова. C этого момента начинает активно участвовать в Башкирском национальном движении.

После начала переговоров с Советскими властями о переходе Башкирского Войска в сторону Красной Армии, в селе Темясово 26 января 1919 года состоялась реорганизация Башкирского правительства. Его новым председателем был избран М. А. Кулаев, а А.-З. Валидов — стал командующим Башкирским войском. Это правительство и стремилось оформить автономию уже в Советской системе.
Башкирское правительство направило свою делегацию в Москву в составе председателя Башкирского правительства М. Кулаева, члена Башкирского правительства Муллаяна Халикова и командира Башкирского Войска Абдрашита Бикбавова для переговоров об образовании Башкирской автономной республики.

В итоге 20 марта 1919 года в Москве было подписано Соглашение центральной Советской власти с Башкирским Правительством о Советской Автономной Башкирии. Этот исторический акт со стороны Советского правительства подписали председатель Совнаркома В. И. Ленин, и.о. председателя ВЦИК Михаил Владимирский и наркомнац И. В. Сталин, с башкирской стороны — председатель Башкирского правительства М. Кулаев, член Башкирского центрального шуро М. Халиков и адъютант Башкирского войска А. Бикбавов.

После возвращения из Москвы М. Кулаев отпросился съездить в Казань к семье и заболел там сыпным тифом, пролежал в больнице и навсегда остался там, отошел от большой опасной политики, занялся врачебной деятельностью, свободное время отдавал изучению проблем родного языка. Им изданы труды: «О звуках башкирского языка» (1928), «Твердый алфавит башкирского языка» (1928), и «О глаголах башкирского языка» (1930). Неизданными остались «Башкирско-русский словарь», «Синтаксис башкирского языка» и «Система синтаксиса в усерганском говоре».

Умер в 1959 году.

Избранные труды
 Основы звукопроизношения и азбука для башкир. Казань, 1912. 18 с.
 Әлепей. 1919. 35 с.
 О звуках башкирского языка. Казань, 1928, 60 с.
 Твердый алфавит башкирского языка. Казань, 1928. 16 с.
 О глаголах башкирского языка. Казань, 1930. 103 с.

Литература
 Баишев М. Деревня Зианчурино Орского уезда Оренбургской губернии // Записки Оренбургского Отдела Императорского Русского Географического Общества. Петербург, 1895.
 Касимов С. Ф. Автономия Башкортостана. Уфа: Китап, 1997.
 Ураксин З.Г. Тәҙрә уйыусы // Уфа: Китап, 2015.

Примечания

Ссылки

20 марта 1918 г. "Соглашение ВЦИК и СНК с Башкирским областным Советом об организации Автономной Башкирской Советской Республики Декреты Советской Власти. т.4 Москва 1968"

Члены Башкирского правительства
Государственные деятели Башкирской АССР
Исследователи башкирского языка
Деятели башкирского национального движения

redpajama_set_name: RedPajamaWikipedia


Complete and successful esophageal reflux measurement in 6 steps!
Medical Measurement Systems developed the Virtual Instructor Program™ to successfully guide users through the software program of the Ohmega. The pre-defined protocol includes questions and answers in database set-up, calibration, recording, and printing of results. Below you will find a demonstration of the VIP.


text:
21 Feb / FK Magazine / Interview
10 minutes with Berndt Arell of Fotografiska
Berndt Arell (1959) has been a director of various art museums in Finland and Sweden – the Helsinki City Art Museum (2001-07), the Museum of Contemporary Art Kiasma in Helsinki (2007–2009), the Nationalmuseum in Stockholm (2014-2017). He has also been a director of the Swedish Cultural Foundation. In 2018 Arell joined Fotografiska as exhibition producer on the cusp of the organisation's global expansion. His task is to produce exhibitions for the upcoming season across all four venues – Stockholm, London, New York and Tallinn.
This May he will join the Riga Photomonth Portfolio Reviews. Applications are now open for photographers who wish to show their work to a range of international photography experts.
How did you start working at Fotografiska and what is your daily routine there?
I started working last year focusing on the exhibitions for our new branches – this year we will open in London, New York and Tallinn. We haven't yet gone public with dates and shows.
Fotografiska in Stockholm
How would you describe the exhibition policy of Fotografiska?
Fotografiska offers a broad overview of photography, historical, modern and contemporary – both still and moving images. It is a challenging combination of photojournalism, fashion, documentary and fine arts.
What has been the biggest challenge so far?
As the audiences are very versatile – it is a challenge to communicate the same artistic expression in a different "tone".
Which components make a great exhibition?
The most important – it goes without saying – is the artist. The high quality of art is essential and the communication with the audiences is also important – the way you interpret your work to the public, guests without cooking it down to "the only right way". For me, the curatorial process, close and together with the artist is the most rewarding part – in which I include the exhibition architect, lighting designer and all co-workers.
A view from an exhibition at Fotografiska in Stockholm
Which exhibition has surprised and inspired you lately?
Anna Clarén's installation When everything changed, which was showed at Fotografiska in 2018. A very private and brave story about the artist's own family, what happens when your child is autistic – we can hear the voices of the father (spouse of the artist) and the siblings… touching and important. Did not leave a dry eye.
What do you like about portfolio reviews and why photographers should take part?
It is kind of a dialogue between the two participants. To make it challenging and interesting for both parts, you need to expect to receive at least as much as you give. My experience is like that. I face a lot of new art, knowledge and ideas in a portfolio review – a momentum for which I am grateful. I would never miss an opportunity to connect to new artists (some of whom I would never meet in another forum maybe). It is often like a successful blind date.
3 Dec '15 / Arnis Balčus / Interview
Interview with Elina Heikka
Collecting and exhibiting photographs, digital age and other challenges that face the Director of the Finnish Museum of Photography.
13 Apr '17 / FK Magazine / Blog
FK Prize 2017 finalists announced
Ten young Latvian photographers will compete for the FK Prize 2017.
7 Oct '14 / Ieva Raudsepa / Interview
Interview with Adrian Kelterborn
The former Magnum multimedia producer Adrian Kelterborn now works as an independent director and producer.


text:
Kem Cetinay reveals Dancing On Ice anxiety
Kem Cetinay says his 'Dancing On Ice' anxiety was the worst the show's producers have ever seen.
The former 'Love Island' star is now the digital host for ITV's figure skating competition for the current series after appearing as a contestant last year – when he finished in fourth place – and he has admitted he even had to lock himself away because of his overwhelming nerves.
Speaking to the latest issue of OK! Magazine, he said: "You have to push me off the rink normally, but doing it in front of a camera, I got the worst anxiety.
"ITV said I had the worse nerves they'd ever seen. I wouldn't talk to anyone and I'd lock myself in my room. I don't get nervous about hosting though, that's just fun!"
Last month, the 22-year-old star apologised to contestant Gemma Collins after claiming that she had been late to rehearsals for a group performance because she was "having a nap", and revealed she'd left a live show early because she was "bored".
However, Gemma insisted she hadn't done anything she was accused of and her good friend was later said to have apologised to her.
A source said at the time: "Gemma was so upset after watching 'This Morning '- there are plenty of things that go on behind-the-scenes during the making of a show but she's been purposefully singled out.
"She was accused of having a nap during a dress rehearsal but that wasn't the case – she asked whether there would be time for one and was told there wouldn't be.
"Kem and her are good friends and it felt like he'd betrayed her by making the comments he did, which he's since massively apologised for.
"But Kem was only doing his job as 'Dancing On Ice' digital presenter and part of that is revealing what goes on when the cameras stop rolling."
Kem Cetinay
Linda Robson's cancer gene fears
Linda Robson is set to undergo genetic testing, as she worries about giving her daughters the breast cancer gene.
Zara McDermott begs for Sam Thompson's forgiveness
Zara McDermott has begged for Sam Thompson's forgiveness, after it emerged she cheated on him last year. The 'Love...
Joey Essex 'splits from Brenda Santos'
Joey Essex has reportedly split from Brenda Santos. The former 'TOWIE' star - who went public with the Brazilian...
Children In Need set for 10pm finish due to filming restrictions
'Children In Need' is reportedly set to finish at 10pm due to filming restrictions. The BBC's annual charity fundraising...
Chelsee Healey and Kelle Bryan's racism discussion
Chelsee Healey and Kelle Bryan are to discuss how to talk about racism with kids. The 'Hollyoaks' actresses -...


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The Honda Shop in Midland sits at the base of some of the very best riding roads in the State and we have started a list of our top riding roads in Perth and surrounds for you to try and enjoy.
There is nothing better than spending some time exploring and enjoying the excellent riding locations we have in Perth and around Western Australia.
If you have a favourite riding route that you would like to share please send us a link here.
Remember, ride to arrive and enjoy yourself safely!