text:
\section{Introduction}

The need to understand the dynamical and functional behavior of real-world networked systems has initiated extensive investigation of network structures over the past decade. Meanwhile, the topological analysis in the recent neuroscience studies has demonstrated that it is able to extract intrinsic information from neural networks that is practically impossible to extract using other less recent techniques of network theory~\cite{giusti2015clique,curto2017can}.

There is no universal definition of a community (a.k.a. cluster or cohesive subgroup) in network theory. A loose definition is that a community is a subgraph such that ``the number of internal edges is larger than the number of external edges"~\cite{fortunato2016community}. One pioneering work in community detection was proposed by Girvan and Newman in 2002~\cite{girvan2002community}. The authors developed an algorithm in which the communities were isolated by the successive removal of the identified inter-community edges. Since then, many new techniques, such as spin models, random walks, optimization, synchronization, as well as traditional clustering methods have been presented~\cite{reichardt2004detecting,zhou2003distance,newman2004fast,arenas2006synchronization,capocci2005detecting}.

Most of the aforementioned methods deliver standard partitions in which each vertex is assigned to a single community. However, vertices are often shared between communities in real-world networks. Therefore, detecting overlapping communities has received a lot of attention in the recent past. The first and the most popular algorithm is the clique percolation method (CPM) proposed by Palla et al.~\cite{palla2005uncovering}. It is based on the assumption that the internal edges of a community are likely to form cliques due to their high densities. Thus, a community is defined as a $k$-clique chain, i.e., a union of all the $k$-cliques that can be reached from each other through a series of adjacent $k$-cliques, where a $k$-clique refers to a maximal clique with $k$ vertices and two $k$-cliques are adjacent if they share $k-1$ vertices. In terms of implementation, the first step of this method is to find all the maximal cliques in the network. The second step is to generate the pairwise clique overlap matrix and extract the $k$-clique matrix from it. The extracted matrix represents the adjacency matrix of the cliques with size $k$. Overlapping communities are then detected by finding all the connected components in the adjacency matrix.

In the CPM, $k$ is a predefined input parameter that may render information loss by leaving a considerable fraction of vertices and edges out of the communities. Moreover, without a prior structural information of the network, it is difficult for one to choose the value of $k$ to identify meaningful communities. To preserve the structural information as much as possible, we propose to convert a network to a topological representation in the form of a $k$-clique based community tree to summarize the community structure in the network at each order. The evolutionary analysis of the community structure will then be transformed to track the topological changes of the $k$-clique based community tree over time. To this end, as opposed to the CPM for static networks, we develop an incremental algorithm that allows us to update community trees with incremental changes in a network to keep track of evolving communities.

Furthermore, we address the robustness of communities with respect to vertex and/or edge updates. In a fast-changing network, many of vertex and/or edge updates over a given time window may not lead to any significant change in the global community structure. Thus, it is unnecessary to incrementally update the evolving communities for each time window. For this reason, we adopt a metric defined from a previous study~\cite{chen2017note} to assess the topological change in community trees, and integrate it into the incremental algorithm to further improve the computational efficiency.

Following this framework, the rest of this paper is organized as follows. In Section~\ref{sec: stability_CT}, we first review the concept and stability of community trees. Section~\ref{sec: CG_and_ETT} outlines the implementation aspects for building and updating a community tree from a undirected, unweighted network. The overall algorithm, named as Dynamic CPM, is presented in Section~\ref{sec: dynamic_CPM}. Experimental results on a diverse collection of social network datasets are discussed in Section~\ref{sec: network_TDA_results} followed by a discussion of our findings in Section~\ref{sec: network_TDA_discussion}.

\section{Community Tree}
\label{sec: stability_CT}

Establishing a filtration to track the evolution of topological features across the scales lies at the core of topological data analysis (TDA). Chen et al.~\cite{chen2017note} extends this idea to the topological characterization of structural features in the form of communities in a network. Specifically, a $k$-clique community or $k$-community for short, denoted by $\mathcal{C}_k$, is adopted from the definition of a community in the CPM, and $k$ is called as its order. Note that by this definition, any arbitrary network $G$ is a 1-community. Since a $k$-clique itself is a $(k-1)$-clique chain, a $k$-community is also a $(k-1)$-community. This property allows any $k$-community $\mathcal{C}_k$ to grow a nested sequence of communities across different orders such that $\mathcal{C}_k \subseteq \mathcal{C}_{k-1} \subseteq \cdots \subseteq \mathcal{C}_1=G$, which forms a filtration of $G$.

From a topological point of view, each nested sequence of communities records the evolution of the starting community as a connected component. Thus, the birth time of the connected component is defined as the order of the starting community. We say the starting community with a higher order is born earlier. When two connected components merge at a certain order, the merging order is then defined as the death time of the connected component with a later birth time. We set the death time of the last remaining connected component, i.e., the one with the earliest birth time, to be 1. The birth and death time of each connected component in a community tree is also encoded in a persistent diagram (PD). A connected component with a longer persistence implies that its starting community behaves more robust against the changes occurring in the network.

\subsection{Stability of Community Tree}
\label{sec: stability_CT}

Chen et al.~\cite{chen2017note} also defines the bottleneck distance between two community trees as the bottleneck distance between their corresponding PDs, and proposes to use this metric to quantify how the two trees differ. To prove community trees are stable with respect to this metric, Chen et al. further introduces a quantity named {\it star number}. Mathematically, the {\it addition star number} ($ASN$) of $G_1$ and $G_2$ is given by
$$ASN(G_2,G_1) = \min\{|V_0|: \nu(e)\cap V_0\neq\emptyset\,\,\, \forall e\in E(G_2)\backslash E(G_1)\},$$
where $V_0$ is a collection of vertices and $\nu(e)$ represents the two vertices of $e$. The {\it removal star number} ($RSN$) can be defined in a similar manner. The sum of $RSN$ and $ASN$ is the {\it total star number} ($TSN$). Figure~\ref{fig_CT_stability} provides an example of computing bottleneck distance of community trees and the $TSN$\footnote{The $x$ and $y$ axes are labeled as death time and birth time, respectively, in the PDs so that all the points corresponding connected components stay above the diagonal.}.

$TSN(G_2,G_1)$ attributes the change from $G_1$ to $G_2$ to a specified number of vertices. Moreover, it has been proved that the difference between two community trees is bounded above by
their $TSN$, i.e.,
$$
d_B(\mathcal{T}(G_1),\mathcal{T}(G_2)) \leq TSN(G_2,G_1).
$$
\begin{figure}
\centering
\includegraphics[width=0.8\columnwidth]{figures/CT_stability}
\caption{The distance between two community trees. The community tree $\mathcal{T}_2$ and the corresponding PD $D_2$ are updated as $v_{11}$, $v_{12}$ and multiple edges are added (colored in brown) from $G_1$ to $G_2$. The PD in the right panel shows an optimal matching between the points in $D_1$ and $D_2$, which indicates $d_B(D_1, D_2) = 0.5$, i.e., $d_B(\mathcal{T}_1, \mathcal{T}_2) = 0.5$. On the other hand, $TSN = ASN =2$ since all the added edges are incident to $v_{11}$ and $v_{12}$.}
\label{fig_CT_stability}
\end{figure}
This result guarantees that one can infer information about the changes to a community tree from the $TSN$. Thus, rather than directly update the community tree, we compute the $TSN$ first to estimate the topological change in community structures between the two networks.

\subsubsection{Algorithm for the upper bound of TSN}
\label{subsec: TSN-upper-bound}

Although computing the $TSN$ has been proved to be NP-complete in~\cite{chen2017note}, we can circumvent this issue by calculating an upper bound for the $TSN$. Given a temporal network for a duration of time, we usually take all the vertices and edges up to a particular time $t$ and create a graph $G_t$ for evolutionary analysis. Thus, the change from $G_{t-1}$ to $G_t$ is now an incremental case where vertices and edges are only added to $G_{t-1}$. Accordingly, computing the upper bound of $TSN$ is reduced to computing the upper bound of $ASN$.
\begin{algorithm}[htbp]
\caption{Compute an upper bound on the $TSN$ in the incremental case}
\begin{algorithmic}[1]
\Procedure{TSN-upper-bound}{$G^\Delta_+$}
\State $\tau \gets |\Call{Find-VC}{G^\Delta_+}|$ \Comment{Use Bar-Yehuda and Even Algorithm to obtain $2$-OPT local ratio for minimum vertex cover.}
\State \Return $\tau$
\EndProcedure
\end{algorithmic}
\label{alg::TSN}
\end{algorithm}

Here we employ an approximation algorithm to obtain the upper bound $\tau$ of $ASN$. As shown in Algorithm~\ref{alg::TSN}, we first compute an edge-difference graph $G^\Delta_+ = (V(G_t), E(G_t)\backslash E(G_{t-1}))$\footnote{$(V(G), E(G))$ and $(V(G_t), E(G_t))$ are henceforth denoted by $(V, E)$ and $(V_t, E_t)$, respectively, for simplicity.} as the input. Bar-Yehuda and Even's greedy algorithm~\cite{bar1981linear} is then used to find a vertex cover for $G^\Delta_+$. The solution given by this algorithm is guaranteed to be within 2 times the optimum solution. Hence, we use the size of this cover as an upper bound for $ASN$. The worst-case runtime for Bar-Yehuda and Even's algorithm is $O(\max{(|E_{t-1}|,|E_t|)})$. Therefore, Algorithm~\ref{alg::TSN} also has a worst case runtime of $O(\max{(|E_{t-1}|,|E_t|)})$.
\section{Clique Graph and Euler Tour Tree}
\label{sec: CG_and_ETT}

In this framework, we transform a network $G$ into a community tree through an auxiliary structure, termed as weighted {\it clique graph} (CG). In a weighted CG, each node represents an MC found in the network and the edge weight denotes the number of vertices shared by the two corresponding MCs.
Since the presence of any single vertex in $G$ does not affect the resulting $\mathcal{T}(G)$, we ignore these MCs of size 1 when generating a weighted CG. Let $\mathcal{G}$ be a weighted CG that comprises all the MCs of size $s \geq 2$, and define $\mathcal{G}_i$ as the subgraph of $\mathcal{G}$ composed of CG nodes representing the MCs of size $s \geq i+1$ and edges with weights $w_{e_{\mathcal{G}}} \geq i$. Note that $\mathcal{G}_1 = \mathcal{G}$.

To perform the updates on the community tree efficiently as $G$ changes, we maintain a spanning forest (a spanning tree for each connected component (CC)) of $\mathcal{G}_i$, denoted by $\mathcal{F}_i$ for $i=1, \ldots, \omega(G)-1$.
We refer to the edges in $\mathcal{F}_i$ as the {\it tree edges} and maintain an adjacency list of the tree edges for every node at each level $i$. Moreover, since the birth time of a CC in $\mathcal{F}_i$ equals the size of the largest MC included in the CC, we choose this MC as the {\it representative MC} for the CC and use it as the CC's ``label". If there are multiple MCs with the same maximum size, without loss of generality, the MC with the minimum ID is selected as the representative MC. Accordingly, we record the death time of the CC as the death time of the representative MC and use the ID of the representative MC as the CC's ID. We also name the CG node corresponding to the representative MC as {\it representative CG node}. See Figure~\ref{fig::CG} for an example.

\begin{figure}[!t]
\centering
\includegraphics[width=0.75\columnwidth]{figures/CG.pdf}
\caption{An example of the sequence of weighted clique graphs $\mathcal{G}_i$ and the corresponding spanning forests $\mathcal{F}_i$, $i = \omega(G)-1, \dots, 1,$ for a given network $G$. The green, red and blue lines in $\mathcal{G}_i$ and $\mathcal{F}_i$ represent the edges with an edge weight of 1, 2 and 3, respectively. The connectivity information in $\mathcal{F}_i$ is summarized in the community tree $\mathcal{T}(G)$ at order $i+1$. For example, the representative CG nodes in $\mathcal{F}_3$ are 2 and 5, while the representative CG node in $\mathcal{F}_2$ is 2.}
\label{fig::CG}
\end{figure}

Each spanning tree in the forest is built on an underlying {\it Euler Tour (ET) Tree} data structure, introduced by Henzinger and King \cite{henzinger1995randomized}. The ET tree is constructed based on the Euler tour of the spanning tree, which is essentially a depth-first traversal of the spanning tree and ends at the node at which it starts. Each ET tree is often stored as a balanced binary search tree (BST). The data structure was later modified by Tarjan \cite{tarjan1997dynamic} to better support operations on the tree nodes such as changing node values. Therefore, we adopt Tarjan's version of the data structure here. In this version, the Euler tour of a spanning tree is a sequence of arcs (directed edges) over the spanning tree with one ``loop" arc per node visited by the tour, i.e, each edge $(u,v)$ results in two arcs $(u,v)$ and $(v,u)$, while each node $v$ corresponds to a single loop arc $(v,v)$.
See Figure~\ref{fig::ETT} for a simple illustration.

\begin{figure}[!ht]
\centering
\includegraphics[width=0.75\columnwidth]{figures/ETT.pdf}
\caption{An example of the Euler tour of a spanning tree in $\mathcal{F}_2$ (left) and one possible representation of this Euler tour as a balanced BST keyed by the index in the tour (right). In this example, the Euler tour is $(1,1)$-$(1,2)$-$(2,2)$-$(2,4)$-$(4,4)$-$(4,2)$-$(2,3)$-$(3,3)$-$(3,5)$-$(5,5)$-$(5,3)$-$(3,2)$-$(2,1)$. A spanning tree with $n$ nodes will be represented by a balanced BST with $2(n-1)+n$ nodes.}
\label{fig::ETT}
\end{figure}
\begin{figure}[!ht]
\centering
\includegraphics[width=\columnwidth]{figures/ETT_weight.pdf}
\caption{An example of an ET tree for implementing the \textproc{Add-val} operation. It is sufficient to only maintain $\Delta w(x)$ for each node $x$ to find $w(x)$ in the ET tree.}
\label{fig::ETT_weight}
\end{figure}
We implement the Euler tour of a spanning tree with a splay tree \cite{sleator1985self}, which is a self-adjusting BST where a node is always splayed to the root through a series of rotations when accessed.
Each node in the spanning tree holds a pointer to its corresponding node, referred to as {\it ET node}, in the splay tree. Particularly, the ET node corresponds to the representative CG node is referred to as {\it representative ET node}.
Meanwhile, each ET node in the splay tree also stores pointers to its parent, right and left child. With this representation, the following operations are supported in $O(\log n)$ amortized time using $O(n)$ space, where $n$ is the number of nodes in the spanning tree(s) involved in the operation \cite{tarjan1997dynamic}.

\begin{itemize}[nosep]
\item \Call{Connected}{$u,v$}: Return if $u$ and $v$ are in the same spanning tree.
\item \Call{Link}{$u, v$}: If $u$ and $v$ are in different spanning trees, insert an edge ($u, v$) connecting the trees together.
\item \Call{Cut}{$u, v$}: Delete the edge ($u, v$) from a spanning tree, splitting the tree into two trees.
\item \Call{Add-val}{$v, \alpha$}: Add $\alpha$ to the value of each node in a spanning tree containing node $v$.
\end{itemize}

\Call{Connected}{} is implemented by using the $\Call{Find-root}{}$ operation in the splay tree. Since linking two trees and cutting a tree each amounts to a fixed set of splitting and concatenation operations on Euler tours, \Call{Link}{} and \Call{Cut}{} are realized by a constant number of \Call{Split}{} and \Call{Join}{} operations of the splay tree \cite{tarjan1997dynamic}.

To handle the \Call{Add-val}{} operation efficiently, we store the value for each node of the splay tree implicitly. Specifically, let $w(x)$ be the value associated with a splay tree node $x$. Rather than storing $w(x)$ at $x$, we store the difference $\Delta w(x)$ between $w(x)$ and the value of its parent, i.e.,
\begin{equation}
\Delta w(x) =
  \begin{cases}
    w(x)       & \quad \text{if } x \text{ is the root the splay tree}\\
    w(x)-w(p(x))  & \quad \text{if } x \text{ is a nonroot, where } p(x) \text{ is the parent of } x
  \end{cases}
  \label{eq::delta-w}
\end{equation}
When $x$ is the root, then $w(x)$ itself is assigned to $\Delta w(x)$. In this manner, for each node $x$, $w(x)$ is computed by summing $\Delta w$ over all the ancestors of $x$. It also implies that adding $\alpha$ to $\Delta w(x)$ amounts to adding $\alpha$ to the values of all the descendants of $x$. Thus, \Call{Add-val}{$v, \alpha$} is realized by simply adding $\alpha$ to the node value $\Delta w$ of the root node of the splay tree that $v$'s corresponding ET node belongs to. $\Delta w(x)$ is updated in each rotation in $O(1)$ time during a splay step. One can check~\cite{sleator1985self} for details.

In our case, for a loop node, $w(x)$ is defined as the ID of the representative ET node of the ET tree that the loop node belongs to. This affiliation links each CG node in a spanning tree to the corresponding representative CG node, which facilitates the need to update the representative CG node in the new spanning tree whenever a tree edge is inserted between two CG nodes. For a nonloop node, $w(x)$ is assigned an arbitrary value of 0 since it can be simply ignored. An example is given in Figure~\ref{fig::ETT_weight} and more details can found in Algorithm~\ref{alg::update-rep}.
\section{Dynamic CPM}
\label{sec: dynamic_CPM}

We now present the overall method of our paper, which we call the Dynamic CPM. As laid out in Algorithm~\ref{alg::dynamicCPM}\footnote{The notations for Algorithm~\ref{alg::dynamicCPM} and the following algorithms are given in Table~\ref{table_symbols}.}, it essentially computes the sequence of community trees for a given sequence of complex networks that vary over time. We then directly obtain the network communities simply by scanning through each order of the computed trees one-by-one.
\begin{algorithm}[!htbp]
\caption{Calculate sequence of community trees for dynamic networks that are represented as time-varying undirected, unweighted graphs $G_0, G_1, \ldots, G_T$}
\begin{algorithmic}[1]
\Procedure{Dynamic-CPM}{$G_0, G_1, \ldots, G_T, l$}
\State $\mathscr{T}_0, \mathscr{M}_0, \mathcal{T}_0, m_0 \gets$ \Call{Build-CT}{$G_0$} \Comment{Algorithm~\ref{alg::buildCT}}
\State $Q \gets \emptyset$, $S\gets 0$, $t' \gets 0$
\For {$t = 1, \ldots, T$}
\State $G^\Delta_+ \gets (V_t, E_t\backslash E_{t-1})$
\State $\tau_t \gets \Call{TSN-upper-bound}{G^\Delta_+}$ \Comment{Algorithm~\ref{alg::TSN}}
\If {$t \leq l$}
\State \Call{Push-back}{$Q, \tau_t$}
\State $S \gets S+\tau_t$
\Else

\If {$\tau_t \geq S/l$}
\State $V^\Delta_+ \gets V_t\backslash V_{t'}$, $E^\Delta_+ \gets E_t\backslash E_{t'}$
\State \scalebox{0.98}[1]{$\mathscr{T}_t, \mathscr{M}_t, \mathcal{T}_{t}, m_{t} \gets \Call{Update-CT}{G_{t'},V^\Delta_+, E^\Delta_+, \mathscr{T}_{t'}, \mathscr{M}_{t'}, \mathcal{T}_{t'}, m_{t'}}$} \Comment Algorithm~\ref{alg::update-CT}
\State $t' \gets t$, $\mathscr{T}_{t'} \gets \mathscr{T}_t$, $\mathscr{M}_{t'} \gets\mathscr{M}_t$, $m_{t'} \gets m_t$
\Else
\State $\mathcal{T}_t \gets \mathcal{T}_{t-1}$ \Comment{Retain previous community tree as the network has not changed substantially (from a topological perspective)}

\EndIf
\State $\tau_{t-l} \gets \Call{Pop-front}{Q}$
\State \Call{Push-back}{$Q, \tau_t$}
\State $S \gets S-\tau_{t-l}+\tau_t$
\EndIf
\EndFor
\State \Return $\mathcal{T}_0, \mathcal{T}_1, \ldots, \mathcal{T}_T$
\EndProcedure
\end{algorithmic}
\label{alg::dynamicCPM}
\end{algorithm}

There are two distinct phases in the Dynamic CPM: \textit{initialization} and \textit{update if necessary}. When a graph, corresponding to a previously non-analyzed network, is fed to the method for the first time, Algorithm~\ref{alg::buildCT} is used to yield the initial community tree. Subsequently, as new graphs, which are  modified forms of the initial graph with vertex and edge insertions, are provided as inputs, we first use our TSN bound result on the bottleneck distance between any two successive graphs to decide whether new community trees should be computed. For efficiency, we can use  Algorithm~\ref{alg::TSN} to approximate the TSN bound. If we decide to compute new community trees, then Algorithm~\ref{alg::update-CT} is used to update the trees without recomputing them from scratch. We present the initial community tree construction algorithm and the update algorithm (along with all their sub-routines) in the Appendix.

It is worth noting the importance of the update condition (line 11) in Algorithm~\ref{alg::dynamicCPM}. We are typically interested only in communities with strong (topological) persistence rather than communities that are short-lived and change even for minor modifications to the networks. In fact, we do not want to update the detected communities in such scenarios. Therefore, the choice of update condition provides a measure of control over the persistence of the communities in addition to rendering our community tracking method more efficient. Here, we update $\mathcal{T}_t$ if $\tau_t$ is no less than a moving average of length $l$. In the following experiments, the length $l$ is selected to be 3.

Figure~\ref{fig_sms_evolution} provides a realistic scenario where the Dynamic CPM works well. In this example,
we recompute the community trees at $t_4$ and $t_7$ because their respective TSN bounds are greater than the moving averages from previous windows. Indeed, the change from $G_0$ to $G_4$ is non-trivial as a new 5-community is born and a large number of lower order communities emerge. From $G_4$ to $G_7$, three more 5-communities appear along with more lower order communities being created. Thus, it makes sense to recompute the community tree. On the other hand, taking the set of 3-communities as an example, the unchanged community trees at order 3 well approximate the real 3-communities found by the CPM as is shown in Figure~\ref{fig_network_acc}.

\section{Results}
\label{sec: network_TDA_results}
We first briefly describe the network datasets that are used to evaluate our algorithm below. Although all the datasets are originally collected in the format of (sender, receiver, timestamp) tuples as directed networks, directionality is ignored in our analysis.
\begin{itemize}[nosep]
    \item Email networks [email-Enron~\cite{klimt2004enron}; email-Eu-core~\cite{paranjape2017motifs}]: Each vertex is an email address and an edge $(v_i, v_j)$ means that person $v_i$ sent or received an e-mail to or from person $v_j$. email-Enron records the communication among Enron employees mostly from November 1998 to June 2002\footnote{This dataset is downloaded from \url{http://www.cis.jhu.edu/~parky/Enron/}. The other datasets can be found from the links in \url{http://snap.stanford.edu/temporal-motifs/data.html}}, while email-Eu-core contains email data over 1 year from members of four different departments at a large European research institution.
    \item Bitcoin network [bitcoin-au~\cite{kondor2014rich}]: Each vertex is an active user ID and an edge represents a Bitcoin payment transferred between two user IDs. The bitcoin-au dataset consists of all transactions made from September 2010 to December 2013.
    \item Online social networks [college-msg~\cite{panzarasa2009patterns}; Facebook-wall~\cite{viswanath2009evolution}]: Each vertex is a user who interacts with others through an online platform. The college-msg network, spanning over 193 days, originates from an online community for students at University of California, Irvine, and an edge ($v_i, v_j$) means user $v_i$ sent or received a private message to or from user $v_j$. The Facebook-wall dataset is derived from the Facebook New Orleans networks ranging from September 2004 to January 2009, where an edge ($v_i, v_j$) indicates user $v_i$ (or $v_j$) posted on user $v_j$'s (or $v_i$'s) wall.
    \item Short message correspondence [short-msg~\cite{wu2010evidence}]: Each vertex is a mobile phone user and an edge ($v_i, v_j$) represents user $v_i$ sent or received a short message (SM) to or from user $v_j$. The short-msg dataset spans over 338 days.
\end{itemize}
\begin{table}[!htbp]
\caption{Summary statistics of datasets}
\centering
\begin{tabular}{l|c|c|c|c}
\hline
Dataset & \# vertices & \# edges & \# periods & $(V_t, E_t)$ \\
\hline
email-Enron & 182 & 2097 & 30 & (150$\pm$ 31, 1,150$\pm$ 674) \\
\hline
bitcoin-au & 1288 & 6236 & 24 & (739 $\pm$ 390, 3,164 $\pm$ 2,024)\\
\hline
college-msg & 1899& 13,838 & 23 & (1,787 $\pm$ 93, 12,847 $\pm$ 923)\\
\hline
email-Eu-core & 893 & 12,556 & 51 & (823 $\pm$ 56, 8,542 $\pm$ 2,758)\\
\hline
short-msg & 44,090 & 52,222 & 41 & (30,209 $\pm$ 9,485, 30,952 $\pm$ 12,816)\\
\hline
Facebook-wall & 45,813 & 183,412 & 37 & (16,797 $\pm$ 11,819, 59,711 $\pm$ 50,379)\\
\hline
\end{tabular}
\label{table_dataset_stats}
\end{table}

More detailed information about our datasets is summarized in Table~\ref{table_dataset_stats}. The second and third column refers to the number of vertices and edges at the end of the observation period, respectively. From $(V_t, E_t)$, we observe that the college-msg dataset is a relatively slow-growing network while the Face-wall dataset is a fast-growing one. This is consistent with the values shown in the second column from Table~\ref{table_update_stats}, as less updates are needed for the college-msg dataset while more updates are performed for the Facebook-wall one. We also notice the corresponding values for the other four datasets are about 0.5. This is because for steadily growing networks, the probably that the TSN bound is larger than the average TSN bound from the previous window is 0.5. Thus, for networks with fairly steady growth, the fraction of periods at which CT is updated should be around 0.5.
\begin{table}[!htbp]
\caption{Summary statistics relative to the evolution of networks}
\centering
\begin{tabular}{l|c|c}
\hline
Dataset & TSN bound & Fraction of periods at which CT is updated\\
\hline
email-Enron & 31 $\pm$ 16 & 0.5\\
\hline
bitcoin-au & 76 $\pm$ 27 & 0.5\\
\hline
college-msg & 75 $\pm$ 73 & 0.22\\
\hline
email-Eu-core & 106 $\pm$ 38 & 0.45\\
\hline
short-msg & 944 $\pm$ 493 & 0.56\\
\hline
Facebook-wall  & 2,981 $\pm$ 2,092 & 0.78\\
\hline
\end{tabular}
\label{table_update_stats}
\end{table}
\begin{figure}[!htbp]
\centering
\subfloat[]{\includegraphics[width=3.2in]{figures/networks_1_3_time}}
\subfloat[]{\includegraphics[width=3.2in]{figures/networks_4_6_time}}
\caption{Comparison of computation time between the original CPM and our algorithm for six network datasets. The networks are divided into two groups based on their computation time for display purposes only.}
\label{fig_network_time}
\end{figure}
Figure~\ref{fig_network_time} compares the computation time, including building and updating community trees using the Dynamic CPM to the cumulative computation time for orders above 1 using original CPM as measured on a desktop with a 2.2 GHz Intel Xeon processor and 32 GB RAM. It can be seen that our algorithm reduces the computation time significantly on the two largest datasets, short-msg and Facebook-wall, while there is no significant computation time difference between the two methods for the other four datasets.

This observation is further verified by the statistical test in Table~\ref{table_comp_time_stats_test}. We further evaluate three quantities that are often used to measure small world effect on these networks. As shown in Table~\ref{table_comp_time_stats_test}, the average clustering coefficients of the short-msg and Facebook-wall datasets are considerately smaller than other datasets, and their average shortest path lengths and effective diameters~\cite{leskovec2007graph} are noticeable larger than the others. All these values reflect that the communities in short-msg and Facebook-wall networks are less close-knit than the other networks over time. In fact, the short-msg and Facebook-wall networks can be classified as small world networks, as their average shortest path lengths scale with $\ln V_t$. Meanwhile, the other networks are regarded as ultra-small world since they have smaller average shortest path lengths that scale with $\ln \ln V_t$~\cite{barabasi2016network}. The corresponding community trees for small world networks tend to have more branches, especially at lower orders. The highest order of these trees are also much smaller than their counterparts for the ultra-small networks. This structural characteristics implies that the \Call{Link}{} and/or \Call{Cut}{} operations during the insertion and/or deletion of CG edges are more often performed between splay trees of small sizes, as opposed to the scenario for ultra-small networks where large splay trees are more frequently involved during these operations. This explains why our algorithm shows more strength for small world networks than ultra-small ones.
\begin{table}[!htbp]
\caption{Wilcoxon rank-sum test for computation time difference between the original CPM and our algorithm, and measures for the degree of clustering in networks}
\centering
\begin{tabular}{l|c|c|c|c}
\hline
\multirow{2}{*}{Dataset} & \multirow{2}{*}{$p$-value} & Average clustering & Average shortest & Effective diameter \\
& & coefficient & path length & (90th percentile) \\
\hline
email-Enron & 0.39 &0.44 $\pm$ 0.08 & 2.49 $\pm$ 0.38 & 3.12 $\pm$ 0.56 \\
\hline
bitcoin-au & 0.16 & 0.34 $\pm$ 0.02 & 2.82 $\pm$ 0.15 & 3.40 $\pm$ 0.23\\
\hline
college-msg & 0.84 & 0.11 $\pm$ 0.002 & 3.05 $\pm$ 0.12 & 3.61 $\pm$ 0.15\\
\hline
email-Eu-core & 0.61 & 0.36 $\pm$ 0.03 & 2.89 $\pm$ 0.29 & 3.44 $\pm$ 0.46\\
\hline
short-msg & \bf 3.9e-9 & \bf 0.045 $\pm$ 0.011 & \bf 9.70 $\pm$ 1.66 & \bf 13.2 $\pm$ 2.25\\
\hline
Facebook-wall & \bf 0.02 & \bf 0.097 $\pm$ 0.025 & \bf 6.20 $\pm$ 1.44 & \bf 7.68 $\pm$ 2.05\\
\hline
\end{tabular}
\label{table_comp_time_stats_test}
\end{table}

\begin{figure}[!htbp]
\centering
\includegraphics[width=5.8in]{figures/networks_acc.pdf}
\caption{Distribution of similarities measure by NMI between a set of 3-communities found in a network up to a particular time and the cover found by the previous update of the network for our datasets.}
\label{fig_network_acc}
\end{figure}
Figure~\ref{fig_network_acc} evaluate the similarities between the network cover\footnote{A set of communities is often referred to as a cover in the literature} from an unchanged community tree at order 3 and the real set of 3-communities by $t_i$ for all the datasets. The evaluation metric is chosen to be normalized mutual information (NMI), which is a measure of similarities between the partitions based on information theory. This metric is proven to be reliable for comparing the real communities and the found ones when evaluating community detection algorithms~\cite{danon2005comparing}. Here we adopt a widely-used version, proposed by Lancichinetti et al.~\cite{lancichinetti2009detecting}, for comparative analysis of overlapping communities. It can be seen that the mean values of the cover similarity for small-world networks are roughly above 0.85, while those vary from around 0.65 to 0.9 among ultra-small world networks.
\begin{figure}[!bp]
\centering
\includegraphics[width=\columnwidth]{figures/sms_evolution}
\caption{Network evolution for the short-msg dataset. The PDs correspond to the community trees at $t_0$, $t_4$, $t_7$, respectively. The number attached above to a point represents the multiplicity of this point in the PDs. The graphs shown at the bottom are a collection of CCs (subgraphs) where the set of 4-communities (blue) and 5-communities (red) belong to.}
\label{fig_sms_evolution}
\end{figure}

In Figure~\ref{fig_sms_evolution}, the short-msg dataset serves an example to demonstrate the evolutionary network analysis using our algorithm. The community tree is initially built at $t_0$ and updated at $t_4$ and $t_7$ base on the rule in our algorithm. The corresponding PDs indicate that the community tree is featured with a large number of lower order branches throughout the duration. The generated community tree by our algorithm is able to track communities over time and identify their appearance and disappearance by their labels. In this example, the highest order of $\mathcal{T}_0$ is 4 and there are four CCs at $t_0$. From $t_0$ to $t_4$, a newborn 5-community CC$_4$ appears, and it is not evolved from any of the 4-communities at $t_0$. CC$_1$ and CC$_3$ stay isolated from others, but CC$_2$ has been merged to the central CC at $t_4$. From $t_4$ to $t_7$, three more 5-communities are born, where one of them is CC$_3$ and the other two, CC$_5$ and CC$_6$ are evolved from newly 4-communities at $t_4$. Interestingly, CC$_1$ still remains disconnected to any other CCs.

\section{Discussion and Future Work}
\label{sec: network_TDA_discussion}
In this paper, we develop an algorithm called the Dynamic CPM that can efficiently detect communities in large-scale dynamic networks. The experiments show that our algorithm reduces the computation time significantly compared to the original CPM, especially for small world networks. The network cover of 3-communities from unchanged community trees also maintain relatively high similarities to the real covers. Furthermore, since the community tree encodes the evolutionary information of communities, our algorithm can naturally track similar communities over time, which often helps to determine fundamental structures of dynamic networks. In addition, the concise tree structure also records when communities appear, disappear, split or merge, which allows us to identify the occurrence of critical events.

The framework in this paper is expected to lay the basis for a TDA route to the study of multilayer networks, particularly in fragility analysis.
Multilayer networks exhibit a more realistic fashion to characterize a wide variety of real-world networks~\cite{jeub2017local}, where intra-layer edges encode different or related types of interactions, and dynamical processes traverse along both intra-layer and inter-layer edges.
In fact, a temporal network is a special type of multilayer network where each time instant is mapped into a different layer. Since
random failures or targeted attacks tend to cause cascading effects (the failure of one node will recursively provoke the failure of connected nodes) on the network functionality and the magnitude of such effects is directly related to the topology of the network, investigating community-based topological structures and the resilience of multilayer networks will help to improve infrastructural design in relevant applications so as to make them more robust to critical failure modes.

\bibliographystyle{unsrt}

redpajama_set_name: RedPajamaArXiv


text:
Q: Eclipse Project > Configure I just happened to disable Maven Nature. Now to re-enable it again I was trying to do Right Click Project: Configure > Convert To Maven Project.
However I do not see Configure option anymore. How do I convert it back to maven project again? I deleted the project and re-checked it back from the truck but to no avail!

A: Never mind, I fixed the problem just by restarting eclipse. Looks like lot of inconsistencies arise if you operate Eclipse for too long. I guess its good practice to save work and restart eclipse every now and then.

redpajama_set_name: RedPajamaStackExchange


text:
Next Article in Exclusives
Beyond 3G Networks: An Interview with Lucent Mobility CTO Paul Mankiewich
By Kirk L. Kroeker
February 18, 2004 5:30 AM PT
Lucent's Mobility Solutions Group has been working to meet the needs of the world's mobile service providers, including traditional wireless carriers and emerging third-generation (3G) mobile operators. The group believes that 3G spread-spectrum technology is the ideal way to address the future of wireless technology and help mobile operators create a sustainable 3G business.
In spread-spectrum networks, signals are distributed over a broad area within the available frequency band, providing tremendous capacity at high quality while minimizing interference. By its nature, spread-spectrum technology also is more secure than earlier technologies, which is a benefit to mobile operators that face a growing array of security and privacy challenges.
When it comes to 3G, Lucent remains a leader in deploying spread-spectrum mobile networks. The company has deployed more than 90,000 spread-spectrum base stations and has enabled more than 50,000 base stations in networks worldwide to support 3G CDMA2000 services, far more than any other equipment vendor. Lucent also has deployed commercial 3G networks for more than 25 mobile operators in North and South America, Europe, Asia and the Australia and New Zealand region.
Paul Mankiewich is chief architect and chief technical officer for Lucent's Mobility Solutions Group and senior vice president of Networking and Services Research for Bell Labs. To find out what's next for Lucent and for the mobile industry, TechNewsWorld turned to Mankiewich for an exclusive interview.
TechNewsWorld: Can you tell us a little about what you do at Lucent?
Paul Mankiewich: As CTO of Lucent's Mobility Solutions Group, my team is responsible for developing the network vision and architecture for Lucent's Mobility business and serves as the key technical interface to our mobile operator customers. I also supervise a team that works with wireless standards bodies worldwide; Lucent has long had a leading role in defining global standards for mobile networking technologies.
As a senior vice president of Bell Labs, I am responsible for overseeing the networking and services research labs. The mission of the Networking Research Laboratory is to provide technological breakthroughs and innovations that lead to superior next-generation IP-based wireless and data networking systems for telecommunications service providers. This work involves creating new algorithms, protocols, network architectures and building prototype systems and network elements.
The Converged Networks and Services Research Center is developing innovative technologies and systems to differentiate Lucent's switching products and the services they enable. A key focus of the center is to develop new architectures, call processors, media servers, gateways and personalization technologies to provide the simple creation and delivery of call management functions and enhanced services.
My dual role in the Mobility business and Bell Labs is beneficial because it gives me the opportunity to drive the innovation of Bell Labs research into the development of products that will continue to differentiate Lucent's Mobility business. It also allows me to ensure that the research we're doing in these labs aligns with the real-world needs of our mobility customers.
TNW: How has the Lucent Mobility Solutions Group evolved over the past several years?
Mankiewich: Over the past several years, our mobility business has been aligned to focus on key strategic areas, which are now proving themselves out in the marketplace. For example, we chose to focus our development work on spread-spectrum CDMA technology, which is the underlying technology of the two dominant 3G standards — W-CDMA and CDMA2000. Now we are seeing that investment pay off, as mobile operators around the world are deploying 3G CDMA2000 and W-CDMA networks.
We also placed an emphasis on mobile high-speed data. With 3G technology, mobile operators increase their voice capacity and also — for the first time — have the capability to offer truly high-speed mobile data services. We made sure we had an end-to-end offer in place to help mobile operators deliver mobile high-speed data services to their subscribers. And our efforts went beyond providing the technology that makes these services possible. We conducted primary market research to identify the applications and the most likely segments to sign up for mobile high-speed data services.
We developed marketing programs to help our customers sell to enterprises — the segment we found that would be the early adopters of mobile high-speed data. We worked with individual enterprises on market pilots and trials of the technology to help our customers better understand what it takes to integrate 3G and corporate applications, firewalls and security. And we worked with device manufacturers to make sure end-user products — such as wireless PC modem cards — were available and well tested to support mobile high-speed data services.
TNW: The Mobility group has a reputation for pushing toward convergence. From your perspective, why is convergence important?
Mankiewich: We place a strategic emphasis on convergence. As more and more data traffic begins to be carried on mobile networks, which have been mostly used for voice, we see a need to help our mobile operator customers marry data and voice networks to reduce their overall cost of operations and increase network efficiency. A transition from circuit-switched networks to packet- or IP-based networks makes this possible. An all-IP network enables both VoIP and data services. These IP networks can support any wireline or wireless access technology.
With the transition to all-IP networks, there is an opportunity for mobile operators to become the primary provider of all of a consumer's voice, data and multimedia services, taking advantage of the convergence of multiple network types. We've started calling this a "grand slam" services bundle opportunity for mobile operators — because they are the only service providers today that can offer subscribers voice, data and multimedia services along with the added convenience of mobility.
TNW: Why can't a mobile operator's IP network carry all of the traffic generated by a user's mobile phone, home phone, home computer or any other communications device?
Mankiewich: To make this happen, smart devices will be available that know when a user is at home (using his or her WiFi network) or on the move (using the mobile network). Mobile operators can help deliver the service capability with smart devices because a mobile network is the only type of network today that can provide information regarding a person's whereabouts, specifically their location (where a user is at a given point in time) and presence (whether a user is on or off a network), and also the type of device they are using at any given time.
We are focused on providing mobile operators a seamless end-to-end network solution to help them become a converged network services provider — from the infrastructure equipment all the way to the device a consumer utilizes. As part of this effort, in November 2003, we unveiled our Accelerate VoIP portfolio of solutions — a cost-effective way for our customers to evolve their networks to provide IP-based voice, data and multimedia services.
TNW: Lucent is a driver in the 3G space, so can you say a little about what's happening in that space in the United States and abroad?
Mankiewich: Lucent is definitely leading in the 3G space, as we've deployed more than 25 commercial 3G networks and more than 50,000 3G base stations worldwide. 3G technology is ushering in a new era of mobile communications, as it enables the introduction of mobile high-speed data services on networks that have been mostly used for voice services.
The United States is clearly one of the leaders in this new era of mobile 3G communications. Here in the U.S., commercial nationwide CDMA2000 1X networks are available from Verizon Wireless and Sprint PCS. Lucent was a major supplier for both of these networks. AT&T Wireless also has deployed EDGE technology nationwide. We are also working with AT&T Wireless to trial W-CDMA/UMTS services in the Miami area. And, we helped Verizon Wireless deploy a commercial CDMA2000 1xEV-DO network in Washington, D.C., which provides average data speeds of 300 to 500 Kbps — comparable to the fastest wireline connections. Verizon Wireless has recently announced plans to deploy a national 1xEV-DO network.
TNW: And on the international side?
Mankiewich: Internationally, Korea is clearly leading the way in 3G, having deployed commercial CDMA2000 1X and 1xEV-DO networks that are generating substantial revenue with millions of subscribers. We are helping KTF in Korea expand their 1xEV-DO network. Japan is also advanced, with commercial CDMA2000 1X and W-CDMA networks deployed by KDDI and NTT DoCoMo, respectively. KDDI has introduced CDMA2000 1xEV-DO services. In other countries like India, we helped Reliance build its 3G network, which is now one of the fastest-growing networks in the world.
In Europe, we are seeing limited deployments of UMTS/W-CDMA. For example, Hutchinson has a commercial UMTS network but very few UMTS subscribers. The mobile operators in Europe seem to be taking a wait-and-see approach with regard to rolling out UMTS, but we believe the first operators to deploy the technology and target enterprises with mobile high-speed data services can begin generating significant revenues today.
Because of 3G's mass deployment, we are beginning to witness the transition from circuit-switched networks to packet- or IP-based networks, which I mentioned earlier. An all-IP network enables operators to start rolling out VoIP services that generate new, profitable revenue.
TNW: What about Lucent's technology right now? What's the most exciting thing happening in your group in the year ahead?
Mankiewich: There are several exciting technology developments my team is working on. These include enhancements to CDMA2000 1xEV-DO, 1xEV-DV and UMTS/W-CDMA — both high-speed downlink packet access (HSDPA) and enhanced uplink data channel (EUDCH). These enhancements will increase the uplink (the speed at which data can be sent from a user back to the network) and downlink (the speed at which data can be delivered to users) speeds on these networks. Uplink speeds are becoming increasingly important because people are creating content on their devices and sending it back through the network. Think of pictures and video content that are now being sent over 3G networks. Also, these enhancements will make efficient and high-quality VoIP services over mobile technologies a reality. The world is moving rapidly to VoIP, and wireless should lead the way.
TNW: Anything else you're working on?
Mankiewich: We are also working on other technologies than can further increase the data rates on these 3G networks. For example, Bell Labs has developed an innovation called Bell Labs Layered Space/Time (BLAST), which is a multiple-input multiple-output (MIMO) technology that uses multiple antennas at the base station to send and receive wireless signals to mobile devices with multiple antennas. BLAST can greatly increase capacity, coverage and the speed at which data is transmitted.
We also plan to take one of our Bell Labs innovations, called OCELOT, another step further. OCELOT is a network design and planning tool developed by Bell Labs that helps mobile operators optimize their networks — for example, tilting antennas a certain way — helping increase network coverage and capacity. We are currently working on embedding OCELOT functionality into the network itself, making dynamic network optimization possible. A "smart" software enhancement, if you will, which would enable networks to intelligently optimize themselves in real-time. This would result in significant efficiency, capacity and coverage gains for mobile operators.
You also can expect to see new products and solutions introduced as part of our Accelerate VoIP portfolio. Enhancements to Lucent's Softswitch, for example, were made so that the product supports both wireless and wireline networks and provides a single platform for all applications. For customers with our existing switching products, we will be introducing solutions that will protect the investments they have made and help them gracefully migrate to IP networks.
TNW: At this point, what would you say are the biggest challenges for Lucent? For example, would it be wireless interoperability, your competitors' technology or even wireless security?
Mankiewich: I believe our biggest challenge is how fast the market for mobile high-speed data services and VoIP services will become widespread. We are seeing some traction in the marketplace already, and we do expect both to take off. We have a very solid technology vision through 2010, but the question is, how fast does the technology evolve? And when do certain technologies become deployed?
TNW: With all that is happening in the computer world in terms of viruses wreaking massive havoc across the Internet and — at the same time — with mobile devices becoming increasingly sophisticated to the point where the most advanced phones can be better characterized as computers, where do you see the wireless world headed in terms of security?
Mankiewich: When speaking about wireless security, we need to look at two areas — WiFi (802.11) and 3G. In the 802.11 WiFi space, security was not considered at the very beginning when this standard was being developed because the technology was originally designed for use in the home. Now, service providers want to offer services using WiFi networks, and the service needs to be reliable and secure. So the industry is now going back to address security issues, which were not addressed initially when the standard was developed. And I'm confident they will be resolved.
On the 3G side, security was rigorously addressed from day one — when the standards were being put together. As an industry, we made it a priority from the outset. And for this reason, I'm not worried about any major security issue related to 3G.
TNW: And what about Lucent's role in security?
Mankiewich: Lucent has a large group dedicated to security. We have groups working on fundamental algorithms for encryption and encryption more generally. Much of our Bell Labs research work is also focused on security. Bell Labs has long been a leader in network security — whether it's defining standards or building firewalls that are impervious to attack — and networks are safer today thanks to our pioneering efforts. Our researchers are intensely focused on enabling end-to-end security of networks, and we're developing the algorithms, protocols, best practices and services to ensure the security and reliability of networks.
One timely example is Bell Labs' Network Security Model, which recently became the basis for the International Telecommunications Union's (ITU) newest global security standard — Recommendation X.805. Recommendation X.805 can be used by network operators and individuals to detect, predict and correct security vulnerabilities across wireless, optical and wire-line voice, data and converged networks before hackers or crackers can exploit them.
TNW: In your opinion, what's the single most important technology of the 20th century?
Mankiewich: There are two — the transistor, invented by Bell Labs, and the integrated circuit (or silicon), invented by Texas Instruments. These two technologies followed a Moore's Law-type curve, and without them and the pace of their development, the advanced mobile devices and computers of today could not exist. Moore's Law in silicon will probably run out at a scale of a bit below 50 nanometers. Bell Labs is already looking at new ways to develop higher-density circuits — an area called nanotechnology research.
Bell Labs is already a well-established leader in nanotechnology. The New Jersey Nanotechnology Consortium, located at our headquarters in Murray Hill, has some of the world's most sophisticated equipment for the fabrication of nanotechnology devices and materials. The work being done here is focused on commercialization, with several contracts already in place with customers in fields such as defense, biotech, aerospace and more.
TNW: Do you think there is a parallel to Moore's Law in the telecommunications industry — or in wireless technology?
Mankiewich: In technology, we depend on Moore's Law. It has treated us well in the technologies available in the modems that enable us to deliver higher data rates and the processing power available to mobile devices. Mobile devices are now beginning to rival laptops with their processing power for high-speed communications and applications. But there are some who would argue that the pace of technology innovation has actually accelerated to the point where Moore's Law can't keep up.
Even though there has been a lull in the telecom industry, the amount of information on the Internet continues to grow. We are seeing this increase exceeding the rate of Moore's Law, which means we will need to get more and more creative in how we design networks. We are moving more and more functionality to the edge of the network, and in the core of the network we are developing very novel combinations of electronic and optical processing. Also, the need for security, as I mentioned earlier, has greatly increased our need for processing power embedded all over the network.
TNW: What will the telecommunications market look like in 10 years?
Mankiewich: We will see the full integration and convergence of all access technologies, meaning end-users will be provided services across multiple network types in a seamless way. A consumer won't know if they're on a WiFi or 3G network, for example, and will receive continuous service. Sets of services will be delivered based on where a user is located, and presence across the whole network will be intelligent and intuitive relative to the user's needs. A user will have one mobile phone or device to use at the home, office and at work. When users are at home, they will be charged on their personal bill, if they're making a personal call, and they will have access to a set of services designated as home services. When they get to the office, the user's device will automatically load the office phone directory onto the phone, for example, and all calls will automatically be charged to the company bill.
We also believe that managing your personal information and preferences will be the key to making these ubiquitous services useful while preventing them from becoming too intrusive. Recently, we introduced Bell Labs' Privacy-Conscious Personalization (PCP) framework, which lets users specify what location information is shared, when, with whom, how and under what circumstances. It relies on user preferences to intelligently infer context — such as working or shopping — and then determines with whom location information should be shared. We've always believed people should be able to communicate on their own terms and wishes, and we are making sure the next generation of networks reflects this conviction.
You also can expect the emergence of embedded-sensory networks that interact with each other. Machines will be sharing data wirelessly with other machines, and we, as consumers, won't even know it. As you're approaching your home, your mobile device will wirelessly interact with your home's embedded-sensory network and let it know you're a block away, and your home's lights will automatically be turned on for you. At home, your washing machine will be able to call its manufacturer when it is malfunctioning, and the manufacturer will be able to run diagnostics remotely. In fact, the majority of network traffic might be machine-to-machine communication — and I expect this machine-to-machine communication to become more pervasive than normal, everyday phone conversations driving today's network traffic.
TNW: How about 20 years from now? What will the telecommunications industry look like?
Mankiewich: In 20 years, it's hard to say or even imagine. Mobile data speeds will have increased exponentially, so one possible thing we might see is the virtual reality concept really taking off. For example, when a mother is on the road traveling for business and wants to speak with her children back home or even tuck them into bed at night, an image of the mother could appear to the child at home, and the two people could have a "virtual reality" conversation over the mobile network. Or if a student is surfing the Internet and looking for information on the Parthenon ruins in Greece, they can actually choose to embed themselves in a "virtual reality tour" and check out the temple in 450 B.C. and experience it with the people of that time.
TNW: Where will Lucent be in that future?
Mankiewich: With Bell Labs as our innovations engine, Lucent will continuously be at the forefront. Throughout all of the turmoil in the telecom industry, we believe we have been able to keep Bell Labs very strong and diverse. Our ability to address a very diverse set of topics and technologies enables us to be ready for any turn the telecom industry could take. We will continue to deliver the equipment, software and services that will support the new sets of mobile services I mentioned earlier and network convergence. Bell Labs will continue to be the leading source of new communications technologies.
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redpajama_set_name: RedPajamaCommonCrawl


text:
Corporate Lessons To Learn From Wells Fargo
When a hunger for success didn't lead to it
BankingCorporate FinanceFinancial Performance
Anastasia Anokhina
When discussing corporate culture, leadership teams and strategists always try to emphasize the importance of the right environment, and that it's people who drive the company forward. However, there are also cases where competitive advantage as a goal can turn into a disaster, where poor management can further escalate dreadful results.
In the banking industry, September started with a shock, with one of the world's leading banks Wells Fargo revealed to be involved in dodgy affairs. The bank has now become a case study of how corporate culture shouldn't look. Reports have been confirmed that bank's employees had been opening and applying more than 2 million bank accounts and credit cards without customers' permission or knowledge between 2011-2015. After the revelation, the case instantly caught the attention of the various governmental bodies, including the CFPB, Los Angeles City Attorney, the Office of the Comptroller of the Currency, FBI - to name a few.
With such rapid escalation of the scandal, Wells Fargo's reputation and customers' trust nosedived at the same speed as its stock prices - down 8.16%, since September 9. What has this got to do with corporate culture? The whole situation could have been prevented, if only the right management was in place, and different methods would have been chosen to drive a competitive advantage of the bank.
What lessons can be learned from Wells Fargo?
Firstly, corporate culture is a very sensitive and reactive ecosystem. With too much pressure it will collapse, and the same outcome should be expected if it's poorly managed. The latter is what happened to Wells Fargo. When John G. Stumpf, the bank's Chief Executive Officer appears at the various hearings as a process of the fraud investigation, he tends to stick to the same reason the disaster occurred. He blames 5,300 employees, claiming that they unlawfully acted behind the managers' backs: 'If they're not going to do the thing that we ask them to do — put customers first, honor our vision and values — I don't want them here,' stressing that the situation is by no means a result of the leadership failure but solely a misconduct of 'low-level bankers' and 'tellers'. When Stumpf was called to resigned, he accepted responsibility but denied it was his failure.
Misconducts in the workplace happen frequently. Each case is individual, and, most of the time, malicious actions against the company are performed by individuals. However, when the situation is out of control for years and leadership teams fail to identify the problem, the blame goes further than just employees. Setting competitive sales programs was the first indication that Wells Fargo put itself in a vulnerable position. Misconducts happen if the opportunity is created - in Wells Fargo there were plenty.
The management success in the organization is strongly linked to the size of it - the bigger it is, the more supervision and connection is needed. With Wells Fargo, considering its sizes and spread in activities, employees were simply scattered, lacking critical support but still faced with extreme pressure driven by sales targets - former employees have been actively revealing the details of their work life in the bank on social media.
One mistake leads to another, and all the ingredients for a huge failure are there. The real lesson is, when someone talks about the importance of healthy corporate culture, listen.
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OilGas News
Moderate investment in big data, despite potential for operational efficiencies in oil and gas
Industry caught in Catch 22, says DNV GL
Only one in five oil and gas companies see themselves as highly digitalized today. However, close to half of senior oil and gas professionals [1] (45%) already see solid or high potential for big data and analytics to transform the operating efficiency of the industry in 2016, according to research by DNV GL, the leading technical advisor to the oil and gas industry.
Nada Ahmed, Senior Engineer at DNV GL – Oil & Gas
Elisabeth Tørstad, CEO of DNV GL – Oil & Gas
The research among over 900 senior oil and professionals reveals that despite it's potential, only 36% plan significant or moderate investment in big data and analytics in 2016. The IT related technology expected to by most respondents to have significant or high investment is cyber security attack/prevention (44%), followed by automation/remote operation (43%).
"Early adopters are emerging, but many in the industry are still at early stages of maturity in data analytics and data-based decision making. The industry is in something of a 'Catch 22' situation; close to half of seniors in our industry see solid or high potential for big data and analytics to transform the industry's operating efficiency in 2016. However, investment seems to be lagging just when we need it most. Our in-depth interviews point to cost constraints and uncertainty about the cost-saving potential of digital technologies as the key reasons," says Nada Ahmed, Senior Engineer at DNV GL – Oil & Gas.
"As for other areas of innovation, collaboration could prove essential to bridge this digital gap and ensure experience transfer in the conservation of data, efficiency drivers and ways to ultimately leverage the opportunities big data represent for the industry," adds Ahmed.
DNV GL has identified key opportunities to reduce costs by optimizing day-to-day operations [2]:
Condition monitoring for more effective maintenance and inspection regimes, dictated by specific, industry, historical and real-time data. Replacing planned maintenance with preventive maintenance, driven by early warnings from sensor data, can significantly reduce downtime.
Instant information from wells can provide timely decisions on underperforming wells and other potential issues that, if not dealt with, could lead to enormous costs.
Detecting anomalies while drilling and during operation can also lead to more effective decisions for cost savings.
Elisabeth Tørstad, CEO of DNV GL – Oil & Gas, says: "Our customers say that a number of challenges need to be addressed to capitalize on the opportunities within Big Data; robust strategies to capture, manage and utilize critical data, access to reliable, trustworthy data, and stringent security to minimize security breaches. We are working with the industry to help it manage the risks and leverage the opportunities associated with digitalization.
"Cyber-attacks on in the oil and gas industry have grown in stature and sophistication in recent years, making them more difficult to detect and defend against, and costing companies increasing sums of money to recover from," adds Tørstad.
1. A New Reality: the outlook for the oil and gas industry in 2016 is an industry benchmark study from DNV GL, the leading technical advisor to the industry. Now in its sixth year, the programme builds on the findings of five prior annual outlook reports, first launched in early 2011. During October and November 2015, we surveyed 921 senior professionals and executives across the global oil and gas industry. More than a third (35%) of respondents work for oil and gas operators, while 60% are employed by suppliers and service companies across the industry. The remaining respondents come from regulators and trade associations. The companies surveyed vary in size: 40% had annual revenue of USD 500m or less, while 14% had annual revenue in excess of USD 10bn. Respondents were drawn from publicly-listed companies and privately-held firms. They also represent a range of functions within the industry, from board-level executives to senior engineers.
2. Digitalization in the Oil & Gas Sector is published by DNV GL and based on in-depth interviews with 25 key stakeholders (operators, rig owners, IT suppliers and consultants).
Una breve historia de la DNV GL (Global)
Las marcas registradas DNV GL®, DNV®, Horizon Graphic y Det Norske Veritas® son propiedad de las empresas del grupo Det Norske Veritas. Todos los derechos reservados.
SAFER SMARTER GREENER


The Georgia Municipal Association recently presented the City of Douglasville with a Safety and Liability Management Grant of $20,000.
HR Director Teaa Allston-Bing said, "the grant application included the need for police department bullet proof vests, city-wide ergonomic safety belts and information technology storage arrays for the PD and City Hall that will hold video from the surveillance camera system. The grant funds will be used to cover those items."


The Human Rights Project helps the Bard community examine the theory and practice of human rights through teaching, research, and public programs.
The Human Rights Project is an exploratory research and action initiative at Bard College, Annandale-on-Hudson, NY. Through teaching, public programs, research, and engagement with communities in the region and globally, the Project aims at once to foster critical discussions of human rights theory and practice, and to engage with practitioners on the leading edges of human rights research. Founded in 1999, the Project developed the first interdisciplinary undergraduate degree (B.A.) program in Human Rights in the United States in 2003.


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Before you ask me to take back my words, consider this; someone will walk into a club or some other entertainment joint, buy two bottles of beer (whatever the brand), probably for Kshs 200 each, and enjoy one match in the upcoming FIFA 2018 World Cup. That's Kshs 400. On top of that, the same person shall have driven miles, or taken a matatu, to take him to the joint. So when Safaricom says its subscribers will enjoy the FIFA 2018 World Cup affordably by spending Kshs 99 ONLY on data bundles and Kwese iflix access, then you're better off celebrating.
Through a press statement sent to news rooms, Safaricom announced the launch of data bundles dubbed Giga Football Passes, to enable customers stream all the FIFA 2018 World Cup matches on Kwesé iflix on-the-go on their smartphones. With these passes, customers can stream any of the 64 matches of the FIFA 2018 World Cup live games on Kwesé iflix at KES 99 for 24 hours, inclusive of all data charges.


At 77 Arts Academy, our music faculty are mindful of the need to engage students in the learning process by providing an enjoyable experience that is supportive while challenging them to live up to their potential. Our faculty is experienced in utilizing creative teaching techniques that individualize the learning style of each student and are sensitive to the unique challenges each child may have when learning.
Other instrument lessons can be provided as desired.
We also rent a wide variety of woodwinds, brass, and string instruments. Please contact us for more information.
Our music faculty can be found on the faculty webpage.


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The new antibiotic was discovered in a sample of soil.
The research is "ingenious," Dr. William Schaffner, an infectious disease specialist at Vanderbilt University, told The New York Times.
Researchers said the antibiotic, which has yet to be tested in humans, could one day be used to treat drug-resistant infections caused by the superbug MRSA, as well as tuberculosis, which normally requires a combination of drugs that can have adverse side effects.
Antibiotic-resistant infections already kill 700,000 people each year, with those numbers expected to rise.
"The discovery of this novel compound challenges long-held scientific beliefs and holds great promise for treating an array of menacing infections," said Kim Lewis, a professor at Northeastern University and co-founder of the NovoBiotic Pharmaceuticals, which has patented teixobactin.
Still, experts urged caution. Though the researchers said they didn't see signs of poisoning in the mice treated with teixobactin, antibiotics that show promise in mice are often toxic to humans.
"It's at the test-tube and the mouse level, and mice are not men or women," Schaffner told The Times. "Moving beyond that is a large step, and many compounds have failed."
Lewis worked with researchers at Germany's University of Bonn and with Britain's Selcia Limited, and the finding was published in the journal Nature on Wednesday.
The problem of infections developing drug resistance — a feature of medicine since Alexander Fleming's discovery of the first antibiotic, penicillin, in 1928 — has worsened in recent years as multi-drug-resistant bugs have developed and drug companies have cut investment.
The World Health Organization warned last year that a post-antibiotic era, where even basic healthcare becomes dangerous due to risk of infection during routine operations, could come this century unless something drastic is done.
Lewis and his NovoBiotic colleagues sought to address the problem by tapping into new potential sources of antibiotics.
"The new research is based on the premise that everything on earth — plants, soil, people, animals — is teeming with microbes that compete fiercely to survive," Denise Grady explained in The Times. "Trying to keep one another in check, the microbes secrete biological weapons: antibiotics."
The team behind the new discovery developed a way of growing such microbes in their natural environment using a miniature device called an iChip that can isolate and help grow single cells.
Researchers have had trouble growing most bacteria outside of their natural environment, which makes it hard to study potential new antibiotics. The iChip, which bring the natural environment into the lab, may end up being a more important innovation than teixobactin itself.
"The method has the potential to be truly transformative, giving us access to a much greater diversity of environmental bacteria than previously imagined," Gautam Dantas, a Washington University scientist who specializes in antibiotic resistance, told science writer Ed Yong.
The development of the iChip method means that Lewis and his team are well-positioned to discover even more good candidates for future antibiotics. "Teixobactin is a fish; the iChip is the rod," Yong explained. "Having the rod guarantees that we'll get more fish — and we desperately need more."
NovoBiotic has so far collected about 50,000 strains of uncultured bacteria and discovered 25 new antibiotics, of which teixobactin is the latest and most interesting, Lewis said. "The rule of thumb in antibiotic discovery is if you have 50 good leads, from those you will get one drug," Lewis explained. "That's just the reality."
One recent discovery, for example, proved to be too toxic to be used as an antibiotic, and is now being tested as a potential anticancer agent.
"The discovery of a potential new class of antibiotics is good news," said Richard Seabrook of Britain's Wellcome Trust medical charity. "Screening previously unculturable soil bacteria is a new twist in the search ... and it is encouraging to see this approach yielding results. However, we will not know whether teixobactin will be effective in humans until this research is taken ... to clinical trials."
Lewis hopes to begin those trials in about two years, and noted that even though the research has not been especially costly so far, they will need significant funding to bring the drug to market.
Even if all goes perfectly — and researchers could still discover problems that halt development — teixobactin won't be available in hospitals for at least five years. It will be more expensive than generic antibiotics, and would likely take the form of an injection, not a pill.


text:
Articles on Police officers
Antwon Rose Jr. was fatally shot by a police officer in East Pittsburgh. AP Photo/Gene J. Puskar
When some police feel misunderstood, it can impact their performance
Shefali V. Patil, University of Texas at Austin
Scholarship in organizational psychology has shown that when employee morale is low, it can result in poorer performance. A new study finds this may be true for some police officers.
How thinking about murderers as hunters could help the police
Jessica Leigh Thornton, Nelson Mandela University
Insights and approaches drawn from anthropology could be a useful part of the toolkit for a cop trying to catch a killer.
Victoria has the lowest youth crime rate of any of the states, despite being the only one that does not have a police in schools program. Dean Lewins/AAP
Why police in schools won't reduce youth crime in Victoria
Diana Johns, University of Melbourne
The police in schools model abolished in Victoria in 2006 represents an outdated, paternalistic approach to youth crime and would not likely reduce youth crime rates if we brought it back now.
Research has found police in schools programs can work, where the focus is on the safety and education of young people. Aap/Tracey Nearmy
Police in schools: helpful or harmful? It depends on the model
Katherine J. McLachlan, University of South Australia
Tough-on-crime models of policing students don't reduce youth crime, but community engagement programs for at-risk youth can be beneficial.
from www.shutterstock.com
Police prefer to carry tasers – but would that make anyone safer?
Peter Squires, University of Brighton
A review of international research shows that police may well be better off without weapons.
Many South Africans fear and mistrust the police. Kim Ludbrook/EPA
Responding to student protests: should the law be a tool of justice or violence?
Jameelah Omar, University of Cape Town
Clashes between student protesters and armed security (whether public or private) compel South Africans to consider the role of use of force in the context of protests.
Protesters call for the arrest of an officer who shot dead unarmed motorist Terence Crutcher. REUTERS/Nick Oxford
Police shootings and race in America: Five essential reads
Danielle Douez, The Conversation
Protests erupted against the killing of black men by police in Tulsa and Charlotte. This roundup looks at research on racial violence and explains where there might be potential solutions.
Are police being asked to do too much? North Charleston
Why are police inside public schools?
Aaron Kupchik, University of Delaware
Police in schools are being asked to deal with a range of issues, such as being a mental health counselor for a traumatized child. It is unfair to the police and can be harmful for children.
Police shootings
US police
Peter Squires
Professor of Criminology & Public Policy, University of Brighton
Rosabelle Boswell
Professor of Anthropology and Executive Dean of Arts, Nelson Mandela University
Aaron Kupchik
Professor of Sociology & Criminal Justice, University of Delaware
Jameelah Omar
Lecturer in Criminal Justice, Department of Public Law, University of Cape Town
Katherine J. McLachlan
Lecturer in Law & Criminal Justice, University of South Australia
Jessica Leigh Thornton
Anthropologist- Researcher, Nelson Mandela University
Diana Johns
Senior Lecturer in Criminology, University of Melbourne
Shefali V. Patil
Assistant Professor of Management, University of Texas at Austin


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The Epson T0423 magenta cartridge contains 16ml of ink, which is a large size cartridge and makes the T0423 ideal for both home and office usage, as you should be able to get a fair amount of use from the T0423 Cartridge. The T0423 magenta cartridge contains Epson DURABrite Ultra ink, making it perfect for high quality printing. The DURABrite ink in the magenta Epson T0423 cartridge contains a resin as an extra layer of protection from sun damage as well as numerous other benefits. This makes the Epson C13T04234010 cartridge a great choice for any of the printers listed above.
Our original Epson T0423 magenta cartridges for this range of Epson printers are amongst the lowest priced on the Internet. All our prices include VAT and delivery so the price you see is the price you pay.


text:
Eagles start new year with win over Harcum College
Stefan Nakic scores in Polk State's 80-75 win over Harcum College. (Photo by Tom Hagerty, Polk State.)
Trailing 68-64 in the second half, Polk State rallied to beat Harcum College 80-75 tonight in Winter Haven.
"I'm pleased with our team's effort tonight," said Head Coach Brandon Giles.
"It really feels good to get the win tonight before we start conference play on Saturday.
"We've been talking all along over the holiday break that it's a new season for us now, and we put a huge emphasis on winning this first game after the break. It's always good to go into conference play with a little bit of momentum.
"I would definitely like to point out Stefan Nakic for responding tonight. I was on him pretty hard there early in the second half but had a great response and was our MVP of this game."
Nakic finished with 14 points and shot eight-for-eight from the free-throw line.
Kadeem Webb led the Eagles with 23 points. He shot five-for-10 from three-point range.
Bryan Polanco scored 17 points and grabbed six rebounds.
Walt Covington had 11 points while Broderick Oliver had seven rebounds and two blocked shots.
Milz Tatum recorded seven points, five assists, and two rebounds.
The Eagles (3-14) begin Suncoast Conference play Saturday against Hillsborough Community College at 4 p.m. in Winter haven.


Comfortable, lightweight and easy-to-use, the new and improved Kegel8 Biofeedback Pelvic Trainer Vaginal Probe is an ideal spare to use with your new style Kegel8 Trainer.
The new and improved Kegel8 Trainer Vaginal Probe is designed especially for use with our new style Kegel8 Biofeedback Pelvic Trainer, available from October 2014. The special inflatable design works with your Kegel8 Biofeedback Trainer to help with your Kegel8 exercises. In Test Mode you will squeeze against the probe to discover your Squeeze Scale and in Train Mode, by squeezing against the probe, you can ensure that you are carrying out your Kegels perfectly, every time.
Please check you have chosen the correct replacement probe for your Kegel8 Trainer unit. This probe is for the new and improved Kegel8 Trainer unit, available from October 2014, that inflates the probe automatically. Another way to check, is by looking at the connector that fits in to your Kegel8 Trainer unit, shown in the product image.
If you bought your Kegel8 Trainer before October 2014 and need a replacement probe, you can find the correct one here.
It is a delicate measuring instrument - please do not squeeze and test it with your hand, otherwise it will not be able to read the strength of your pelvic floor muscles! The new and improved Kegel8 Trainer Vaginal Probe comes complete with air-line tubing ready for use.
Your Kegel8 Trainer Vaginal Probe is a sensitive measuring device, so it's important to take good care of it. After every use, you should clean your probe with Kegel8 Klean and store it safely in the original packaging.


text:
Consumer Financial Protection Bureau Settles Claims of Illegal Billing Practices with Cellular Providers
Benjamin R. Cox
CFPA, CFPB, Telecommunications
On May 12, the Consumer Financial Protection Bureau ("CFPB") announced that it is seeking to settle claims against two cellular providers who have agreed to return $120 million in funds to wireless customers. The Bureau filed proposed orders in the United States District Courts for the District of New Jersey and Southern District of New York which, if approved, would settle enforcement actions alleging unfair acts and practices under the Consumer Financial Protection Act ("CFPA") brought by the Bureau in coordination with the state attorneys general and Federal Communications Commission ("FCC"). The civil complaint filed against one of the providers alleged that it allowed merchants unfettered access to "cram[] . . . fabricated charges" onto customers' bills for goods known in the industry as "premium text messages" or "premium short messaging services." These digital products consist of "one-time purchases or monthly subscriptions to ringtones, wallpaper, and text messages providing flirting tips, horoscopes, and other digital content" for which the cellular provider retained 30% of the charge. The Bureau alleged that the cellular providers outsourced payment processing for these services to third-party vendors, but then failed to properly monitor them, resulting in millions of dollars of illicit charges to consumers. If approved by the courts, the parties' proposed consent orders would require the cellular providers to provide $120 million in redress to affected customers, implement new billing practices with increased transparency, obtain informed consent from consumers before allowing third-party billing, improve dispute resolution procedures, and enhance customer service training programs. The cellular providers would also be required to pay $38 million in federal and state fines.


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text:
New Native Kitchen
Celebrating Modern Recipes of the American Indian
By Freddie Bitsoie, and James O. Fraioli
Photographer	Quentin Bacon
Illustrator	Gabriella Trujillo
Imprint: Abrams Books
Illustrations: 150 color
Modern Indigenous cuisine from the renowned Native foods educator and former chef of Mitsitam Native Foods Café at the Smithsonian's National Museum of the American Indian
From Freddie Bitsoie, the former executive chef at Mitsitam Native Foods Café at the Smithsonian's National Museum of the American Indian, and James Beard Award–winning author James O. Fraioli, New Native Kitchen is a celebration of Indigenous cuisine. Accompanied by original artwork by Gabriella Trujillo and offering delicious dishes like Cherrystone Clam Soup from the Northeastern Wampanoag and Spice-Rubbed Pork Tenderloin from the Pueblo peoples, Bitsoie showcases the variety of flavor and culinary history on offer from coast to coast, providing modern interpretations of 100 recipes that have long fed this country.
Recipes like Chocolate Bison Chili, Prickly Pear Sweet Pork Chops, and Sumac Seared Trout with Onion and Bacon Sauce combine the old with the new, holding fast to traditions while also experimenting with modern methods. In this essential cookbook, Bitsoie shares his expertise and culinary insights into Native American cooking and suggests new approaches for every home cook. With recipes as varied as the peoples that inspired them, New Native Kitchen celebrates the Indigenous heritage of American cuisine.
"This book is a glorious celebration of Native American cuisine filled with pride and love."
author of The Flavor Equation, Nik Sharma —
"Thanks to Chef Freddie Bitsoie and this artful, inspiring book, it is easy to see how we can incorporate Indigenous foods into our kitchens and how the simple act of cooking can also be a celebration of Indigenous people, their rich cultural traditions, and connection to the land that has inspired so many delicious recipes."
Robert Redford —
"Freddie Bitsoie has taken Native American cuisine to a new level."
Tewa/Hopi, artist, Dan Namingha —
"Freddie Bitsoie is one of our continent's very best chefs and storytellers. This is required reading for anyone who really cares about cooking."
James Beard Award-winning journalist and author of American Food, Rachel Wharton —
"I am fascinated with Freddie's knowledge of Indigenous foods. He always brings love and understanding to the experience of ancestral food culture. Meegwetch (thank you)."
Anishinaabe, actor, Adam Beach —
"I have always used food as my entry point to learning more about cultures both outside of and within my own—and in New Native Kitchen, Freddie Bitsoie is an exceptional guide, showing off the vibrant, regional native cooking of what is now the United States, giving context to the people who created it while showing off the beautiful ingredients of a truly exciting and diverse cuisine."
chef and author of forthcoming The Don't Panic Pantry Cookbook, Noah Galuten —
"I love this book, which is both a practical, modern cookbook filled with recipes that center on the local and the seasonal, and a generous, sweeping testament to the scope, ingenuity, and enduring importance of Indigenous culinary traditions throughout the Americas."
author of Start Simple, Lukas Volger —
"To seek and understand Indigenous foods is to dwell in the lands of our ancestors, to taste the earth and all that grows, from roots to leaf, from field and stream, to even the birds of the sky. Freddie not only has been immersed in this knowledge but has been a true, joyous steward of Native culture through food. This is going to be a staple in my house and will be a great gift for friends, family, and colleagues! I love Freddie!"
Iñupiat, Yupik, Métis-Cree, actor, activist, storyteller, Irene Bedard —
Freddie Bitsoie is a proud Navajo and an award-winning chef. He is the former executive chef of Mitsitam Native Foods Café, located inside Washington, D.C.'s Smithsonian National Museum of the American Indian. Bitsoie was previously the executive chef of Fire Rock Casino and is the winner of the Smithsonian's Native Chef Competition. He has contributed to a number of Native American cookbooks, including America: The Cookbook (Phaidon, 2017) and James Beard Award–winner Sioux Chef's Indigenous Kitchen (University of Minnesota Press, 2017). He lives in Washington, D.C. James O. Fraioli is a James Beard Award–winning author with nearly 40 books to his credit. He lives in Seattle, Washington.
More Food & Drink


What's the first thing that comes to mind when u read the word nautical? If you are like me it would be distance. As a style for decoration, it would represent the coastal based theme that one would use for their home.
Some tips to guide you towards attaining this goal. First getting the right color that resembles the real thing is very important. This should be applied to the home itself as well as furniture and accessories. Nothing brings out more the nautical feel than furniture and accessories that have been designed to fit the cool, breezy disposition of the beachside.
Such small things as miniature boats, animation of organisms found in the seas like seashells and oysters and rugs and carpets that appear sandy in color and texture would go along way in making the home look original. The accessories should be spread throughout the home to cover all the rooms.