OpenRaiser/Intern-Atlas huggingface dataset:
Theoretical Foundation for Research in Communication using Information and Communication Technology Devices in Healthcare: An Interdisciplinary Scoping Review
Venue: arXiv cs.OH 2013
Year: 2013

Faulty communication between team members is one of the most important factors preventing substantial improvement in patient safety. Aviation, nuclear power and defense have been able to improve their safety record by adopting theory and model based solutions. In contrast, healthcare's thrust towards modern communication devices is largely devoid of theoretical foundation. The objective of this scoping review is to compile communication theories, frameworks, and models used by high risk organizations outside healthcare to study and resolve workplace communication issues. The healthcare databases searched included Medline, CINAHL, EMBASE, and PsycInfo. In addition, we searched engineering and science literature to include articles in the fields of information sciences, computer sciences, nuclear power generation, aviation, the military and other domains such as sociology that address the science and theory of communication. Comprehensive searching was also done in the communication studies literature. We also reviewed conference proceedings and grey literature and conducted citation tracking. Our initial systematic search yielded 15,365 articles. Hand searching and reviewing references resulted in a set of 181 articles. 144 full text articles were read and 40 of them were selected to be included in the review. We were able to identify 14 theories and 12 models which could be applied in hospital communication research. However, it must be noted that most of them have not yet been applied in biomedical research in hospital communication and as such their applicability can only be suggested-a gap which future research may be able to address. Formulation of a custom model representing the unique features and complexities of communication within hospitals is recommended.
Simple Bounds for Noisy Linear Inverse Problems with Exact Side Information
Venue: arXiv cs.IT 2013
Year: 2013

This paper considers the linear inverse problem where we wish to estimate a structured signal $x$ from its corrupted observations. When the problem is ill-posed, it is natural to make use of a convex function $f(\cdot)$ that exploits the structure of the signal. For example, $\ell_1$ norm can be used for sparse signals. To carry out the estimation, we consider two well-known convex programs: 1) Second order cone program (SOCP), and, 2) Lasso. Assuming Gaussian measurements, we show that, if precise information about the value $f(x)$ or the $\ell_2$-norm of the noise is available, one can do a particularly good job at estimation. In particular, the reconstruction error becomes proportional to the "sparsity" of the signal rather than the ambient dimension of the noise vector. We connect our results to existing works and provide a discussion on the relation of our results to the standard least-squares problem. Our error bounds are non-asymptotic and sharp, they apply to arbitrary convex functions and do not assume any distribution on the noise.
Dynamics of Trends and Attention in Chinese Social Media
Venue: arXiv cs.SI 2013
Year: 2013

There has been a tremendous rise in the growth of online social networks all over the world in recent years. It has facilitated users to generate a large amount of real-time content at an incessant rate, all competing with each other to attract enough attention and become popular trends. While Western online social networks such as Twitter have been well studied, the popular Chinese microblogging network Sina Weibo has had relatively lower exposure. In this paper, we analyze in detail the temporal aspect of trends and trend-setters in Sina Weibo, contrasting it with earlier observations in Twitter. We find that there is a vast difference in the content shared in China when compared to a global social network such as Twitter. In China, the trends are created almost entirely due to the retweets of media content such as jokes, images and videos, unlike Twitter where it has been shown that the trends tend to have more to do with current global events and news stories. We take a detailed look at the formation, persistence and decay of trends and examine the key topics that trend in Sina Weibo. One of our key findings is that retweets are much more common in Sina Weibo and contribute a lot to creating trends. When we look closer, we observe that most trends in Sina Weibo are due to the continuous retweets of a small percentage of fraudulent accounts. These fake accounts are set up to artificially inflate certain posts, causing them to shoot up into Sina Weibo's trending list, which are in turn displayed as the most popular topics to users.
Redundancy and Aging of Efficient Multidimensional MDS-Parity Protected Distributed Storage Systems
Venue: arXiv cs.IT 2013
Year: 2013

The effect of redundancy on the aging of an efficient Maximum Distance Separable (MDS) parity--protected distributed storage system that consists of multidimensional arrays of storage units is explored. In light of the experimental evidences and survey data, this paper develops generalized expressions for the reliability of array storage systems based on more realistic time to failure distributions such as Weibull. For instance, a distributed disk array system is considered in which the array components are disseminated across the network and are subject to independent failure rates. Based on such, generalized closed form hazard rate expressions are derived. These expressions are extended to estimate the asymptotical reliability behavior of large scale storage networks equipped with MDS parity-based protection. Unlike previous studies, a generic hazard rate function is assumed, a generic MDS code for parity generation is used, and an evaluation of the implications of adjustable redundancy level for an efficient distributed storage system is presented. Results of this study are applicable to any erasure correction code as long as it is accompanied with a suitable structure and an appropriate encoding/decoding algorithm such that the MDS property is maintained.
On the DoF Region of the K-user MISO Broadcast Channel with Hybrid CSIT
Venue: arXiv cs.IT 2013
Year: 2013

An outer bound for the degrees of freedom (DoF) region of the K-user multiple-input single-output (MISO) broadcast channel (BC) is developed under the hybrid channel state information at transmitter (CSIT) model, in which the transmitter has instantaneous CSIT of channels to a subset of the receivers and delayed CSIT of channels to the rest of the receivers. For the 3-user MISO BC, when the transmitter has instantaneous CSIT of the channel to one receiver and delayed CSIT of channels to the other two, two new communication schemes are designed, which are able to achieve the DoF tuple of $\left(1,\frac{1}{3},\frac{1}{3}\right)$, with a sum DoF of $\frac{5}{3}$, that is greater than the sum DoF achievable only with delayed CSIT. Another communication scheme showing the benefit of the alternating CSIT model is also developed, to obtain the DoF tuple of $\left(1,\frac{4}{9},\frac{4}{9}\right)$ for the 3-user MISO BC.
Initial Ranging for Prioritized Network Entry in IEEE 802.16 Network
Venue: arXiv cs.NI 2013
Year: 2013

Prioritized network entry is desirable for establishing preferential network connectivity for the higher priority users when different priority users exist over a given network. In line with such desirability, we propose a simple but efficient priority differentiated initial ranging mechanism considering an Orthogonal Frequency Division Multiple Access (OFDMA) based IEEE 802.16 network. In the proposed mechanism, we introduce an approach that integrates an explicit CDMA-ranging code reservation scheme with a Ranging Slot Selection Window (RSSW) differentiation scheme. Simulation results are provided to characterize the performance of the proposed mechanism.
Towards the Framework of Information Security
Venue: arXiv cs.CR 2013
Year: 2013

Todays modern society is extremely dependent on computer based information systems. Many of the organizations would simply not be able to function properly without services provided by these systems, just like financing organizations. Although interruption might decrease the efficiency of an organization, theft or unintentional disclosure of entrusted private data could have more serious consequences, such as legal actions as well as loss of business due to lack of trust from potential users. This dependence on information systems has lead to a need for securing these systems and this in turn has created a need for knowing how secure they are. The introduction of the information society has changed how people interact with government agencies. Government agencies are now encouraged to uphold a 24-hour electronic service to the citizens. The introduction of government services on the Internet is meant to facilitate communication with agencies, decrease service times and to lessen the amount of papers that needs to be processed. The increased connectivity to the Internet results in a rising demand for information security in these systems. In this article, we have discussed about many file data breaches in the past and current history and they are going to increase day by day as the reports by DataLossDB (Open Security Foundation) organization, a non-profit organization in US.
Efficient construction of broadcast graphs
Venue: arXiv cs.DM 2013
Year: 2013

A broadcast graph is a connected graph, $G=(V,E)$, $ |V |=n$, in which each vertex can complete broadcasting of one message within at most $t=\lceil \log n\rceil$ time units. A minimum broadcast graph on $n$ vertices is a broadcast graph with the minimum number of edges over all broadcast graphs on $n$ vertices. The cardinality of the edge set of such a graph is denoted by $B(n)$. In this paper we construct a new broadcast graph with $B(n) \le (k+1)N -(t-\frac{k}{2}+2)2^{k}+t-k+2$, for $n=N=(2^{k}-1)2^{t+1-k}$ and $B(n) \le (k+1-p)n -(t-\frac{k}{2}+p+2)2^{k}+t-k -(p-2)2^{p}$, for $2^{t} < n<(2^{k}-1)2^{t+1-k}$, where $t \geq 7$, $2 \le k \le \lfloor t/2 \rfloor -1$ for even $n$ and $2 \le k \le \lceil t/2 \rceil -1$ for odd $n$, $d=N-n$, $x= \lfloor \frac{d}{2^{t+1-k}} \rfloor$ and $ p = \lfloor \log_{2}{(x+1)} \rfloor$ if $x>0$ and $p=0$ if $x=0$. The new bound is an improvement upon the bound presented by Harutyunyan and Liestman (2012) for odd values of $n$.
Vertex Disjoint Path in Upward Planar Graphs
Venue: arXiv cs.CC 2013
Year: 2013

The $k$-vertex disjoint paths problem is one of the most studied problems in algorithmic graph theory. In 1994, Schrijver proved that the problem can be solved in polynomial time for every fixed $k$ when restricted to the class of planar digraphs and it was a long standing open question whether it is fixed-parameter tractable (with respect to parameter $k$) on this restricted class. Only recently, \cite{CMPP}.\ achieved a major breakthrough and answered the question positively. Despite the importance of this result (and the brilliance of their proof), it is of rather theoretical importance. Their proof technique is both technically extremely involved and also has at least double exponential parameter dependence. Thus, it seems unrealistic that the algorithm could actually be implemented. In this paper, therefore, we study a smaller class of planar digraphs, the class of upward planar digraphs, a well studied class of planar graphs which can be drawn in a plane such that all edges are drawn upwards. We show that on the class of upward planar digraphs the problem (i) remains NP-complete and (ii) the problem is fixed-parameter tractable. While membership in FPT follows immediately from \cite{CMPP}'s general result, our algorithm has only single exponential parameter dependency compared to the double exponential parameter dependence for general planar digraphs. Furthermore, our algorithm can easily be implemented, in contrast to the algorithm in \cite{CMPP}.
Detection and prevention of botnets and malware in an enterprise network
Venue: arXiv cs.CR 2013
Year: 2013

One of the most significant threats faced by enterprise networks today is from Bots. A Bot is a program that operates as an agent for a user and runs automated tasks over the internet, at a much higher rate than would be possible for a human alone. A collection of Bots in a network, used for malicious purposes is referred to as a Botnet. Bot attacks can range from localized attacks like key-logging to network intensive attacks like Distributed Denial of Service (DDoS). In this paper, we suggest a novel approach that can detect and combat Bots. The proposed solution adopts a two pronged strategy which we have classified into the standalone algorithm and the network algorithm. The standalone algorithm runs independently on each node of the network. It monitors the active processes on the node and tries to identify Bot processes using parameters such as response time and output to input traffic ratio. If a suspicious process has been identified the network algorithm is triggered. The network algorithm will then analyze conversations to and from the hosts of the network using the transport layer flow records. It then tries to deduce the Bot pattern as well as Bot signatures which can subsequently be used by the standalone algorithm to thwart Bot processes at their very onset.
Face Recognition using Hough Peaks extracted from the significant blocks of the Gradient Image
Venue: arXiv cs.CV 2013
Year: 2013

This paper proposes a new technique for automatic face recognition using integrated peaks of the Hough transformed significant blocks of the binary gradient image. In this approach firstly the gradient of an image is calculated and a threshold is set to obtain a binary gradient image, which is less sensitive to noise and illumination changes. Secondly, significant blocks are extracted from the absolute gradient image, to extract pertinent information with the idea of dimension reduction. Finally the best fitted Hough peaks are extracted from the Hough transformed significant blocks for efficient face recognition. Then these Hough peaks are concatenated together, which are used as feature in classification process. The efficiency of the proposed method is demonstrated by the experiment on 1100 images from the FRAV2D face database, 2200 images from the FERET database, where the images vary in pose, expression, illumination and scale and 400 images from the ORL face database, where the images slightly vary in pose. Our method has shown 93.3%, 88.5% and 99% recognition accuracy for the FRAV2D, FERET and the ORL database respectively.
Human Face Recognition using Gabor based Kernel Entropy Component Analysis
Venue: arXiv cs.CV 2013
Year: 2013

In this paper, we present a novel Gabor wavelet based Kernel Entropy Component Analysis (KECA) method by integrating the Gabor wavelet transformation (GWT) of facial images with the KECA method for enhanced face recognition performance. Firstly, from the Gabor wavelet transformed images the most important discriminative desirable facial features characterized by spatial frequency, spatial locality and orientation selectivity to cope with the variations due to illumination and facial expression changes were derived. After that KECA, relating to the Renyi entropy is extended to include cosine kernel function. The KECA with the cosine kernels is then applied on the extracted most important discriminating feature vectors of facial images to obtain only those real kernel ECA eigenvectors that are associated with eigenvalues having positive entropy contribution. Finally, these real KECA features are used for image classification using the L1, L2 distance measures; the Mahalanobis distance measure and the cosine similarity measure. The feasibility of the Gabor based KECA method with the cosine kernel has been successfully tested on both frontal and pose-angled face recognition, using datasets from the ORL, FRAV2D and the FERET database.
File System - A Component of Operating System
Venue: arXiv cs.OS 2013
Year: 2013

The file system provides the mechanism for online storage and access to file contents, including data and programs. This paper covers the high-level details of file systems, as well as related topics such as the disk cache, the file system interface to the kernel, and the user-level APIs that use the features of the file system. It will give you a thorough understanding of how a file system works in general. The main component of the operating system is the file system. It is used to create, manipulate, store, and retrieve data. At the highest level, a file system is a way to manage information on a secondary storage medium. There are so many layers under and above the file system. All the layers are to be fully described here. This paper will give the explanatory knowledge of the file system designers and the researchers in the area. The complete path from the user process to secondary storage device is to be mentioned. File system is the area where the researchers are doing lot of job and there is always a need to do more work. The work is going on for the efficient, secure, energy saving techniques for the file systems. As we know that the hardware is going to be fast in performance and low-priced day by day. The software is not built to comeback with the hardware technology. So there is a need to do research in this area to bridge the technology gap.
Quantization and Greed are Good: One bit Phase Retrieval, Robustness and Greedy Refinements
Venue: arXiv cs.IT 2013
Year: 2013

In this paper, we study the problem of robust phase recovery. We investigate a novel approach based on extremely quantized (one-bit) phase-less measurements and a corresponding recovery scheme. The proposed approach has surprising robustness and stability properties and, unlike currently available methods, allows to efficiently perform phase recovery from measurements affected by severe (possibly unknown) non-linear perturbations, such as distortions (e.g. clipping). Beyond robustness, we show how our approach can be used within greedy approaches based on alternating minimization. In particular, we propose novel initialization schemes for the alternating minimization achieving favorable convergence properties with improved sample complexity.
Shannon Sampling and Parseval Frames on Compact Manifolds
Venue: arXiv cs.IT 2013
Year: 2013

Our article is a summary of some results for Riemannian manifolds that were obtained in \cite{gpes}-\cite{Pesssubm}. To the best of our knowledge these are the pioneering papers which contain the most general results about frames, Shannon sampling, and cubature formulas on compact and non-compact Riemannian manifolds. In particular, the paper \cite{gpes} gives an "end point" construction of tight localized frames on homogeneous compact manifolds. The paper \cite{Pessubm} is the first systematic development of localized frames on compact domains in Euclidean spaces.
Bootstrapped Grouping of Results to Ambiguous Person Name Queries
Venue: arXiv cs.IR 2013
Year: 2013

Some of the main ranking features of today's search engines reflect result popularity and are based on ranking models, such as PageRank, implicit feedback aggregation, and more. While such features yield satisfactory results for a wide range of queries, they aggravate the problem of search for ambiguous entities: Searching for a person yields satisfactory results only if the person we are looking for is represented by a high-ranked Web page and all required information are contained in this page. Otherwise, the user has to either reformulate/refine the query or manually inspect low-ranked results to find the person in question. A possible approach to solve this problem is to cluster the results, so that each cluster represents one of the persons occurring in the answer set. However clustering search results has proven to be a difficult endeavor by itself, where the clusters are typically of moderate quality. A wealth of useful information about persons occurs in Web 2.0 platforms, such as LinkedIn, Wikipedia, Facebook, etc. Being human-generated, the information on these platforms is clean, focused, and already disambiguated. We show that when searching for ambiguous person names the information from such platforms can be bootstrapped to group the results according to the individuals occurring in them. We have evaluated our methods on a hand-labeled dataset of around 5,000 Web pages retrieved from Google queries on 50 ambiguous person names.
Optimal Provision-After-Wait in Healthcare
Venue: arXiv cs.GT 2013
Year: 2013

We investigate computational and mechanism design aspects of scarce resource allocation, where the primary rationing mechanism is through waiting times. Specifically we consider allocating medical treatments to a population of patients. Each patient needs exactly one treatment, and can choose from $k$ hospitals. Hospitals have different costs, which are fully paid by a third party ---the "payer". The payer has a fixed budget $B$, and each hospital will have its own waiting time. At equilibrium, each patient will choose his most preferred hospital given his intrinsic preferences and the waiting times. The payer thus computes the waiting times so that at equilibrium the budget constraint is satisfied and the social welfare is maximized. We first show that the optimization problem is NP-hard, yet if the budget can be relaxed to $(1+ε)B$ for an arbitrarily small $ε$, then the optimum under budget $B$ can be approximated efficiently. Next, we study the endogenous emergence of waiting time from the dynamics between hospitals and patients, and show that there is no need for the payer to explicitly enforce the optimal waiting times. Under certain conditions, all he need is to enforce the amount of money he wants to pay to each hospital. The dynamics will always converge to the desired waiting times in finite time. We then go beyond equilibrium solutions and investigate the optimization problem over a much larger class of mechanisms containing the equilibrium ones as special cases. With two hospitals, we show that under a natural assumption on the patients' preference profiles, optimal welfare is in fact attained by the randomized assignment mechanism, which allocates patients to hospitals at random subject to the budget constraint, but avoids waiting times. Finally, we discuss potential policy implications of our results, as well as follow-up directions and open problems.
On Cell Association and Scheduling Policies in Femtocell Networks
Venue: arXiv cs.NI 2013
Year: 2013

Femtocells are recognized effective for improving network coverage and capacity, and reducing power consumption due to the reduced range of wireless transmissions. Although highly appealing, a plethora of challenging problems need to be addressed for fully harvesting its potential. In this paper, we investigate the problem of cell association and service scheduling in femtocell networks. In addition to the general goal of offloading macro base station (MBS) traffic, we also aim to minimize the latency of service requested by users, while considering both open and closed access strategies. We show the cell association problem is NP-hard, and propose several near-optimal solution algorithms for assigning users to base stations (BS), including a sequential fixing algorithm, a rounding approximation algorithm, a greedy approximation algorithm, and a randomized algorithm. For the service scheduling problem, we develop an optimal algorithm to minimize the average waiting time for the users associated with the same BS. The proposed algorithms are analyzed with respect to performance bounds, approximation ratios, and optimality, and are evaluated with simulations.