OpenRaiser/Intern-Atlas huggingface dataset:
A Latent Clothing Attribute Approach for Human Pose Estimation
Venue: arXiv cs.CV 2014
Year: 2014

As a fundamental technique that concerns several vision tasks such as image parsing, action recognition and clothing retrieval, human pose estimation (HPE) has been extensively investigated in recent years. To achieve accurate and reliable estimation of the human pose, it is well-recognized that the clothing attributes are useful and should be utilized properly. Most previous approaches, however, require to manually annotate the clothing attributes and are therefore very costly. In this paper, we shall propose and explore a \emph{latent} clothing attribute approach for HPE. Unlike previous approaches, our approach models the clothing attributes as latent variables and thus requires no explicit labeling for the clothing attributes. The inference of the latent variables are accomplished by utilizing the framework of latent structured support vector machines (LSSVM). We employ the strategy of \emph{alternating direction} to train the LSSVM model: In each iteration, one kind of variables (e.g., human pose or clothing attribute) are fixed and the others are optimized. Our extensive experiments on two real-world benchmarks show the state-of-the-art performance of our proposed approach.
Outlier-Robust Convex Segmentation
Venue: arXiv cs.LG 2014
Year: 2014

We derive a convex optimization problem for the task of segmenting sequential data, which explicitly treats presence of outliers. We describe two algorithms for solving this problem, one exact and one a top-down novel approach, and we derive a consistency results for the case of two segments and no outliers. Robustness to outliers is evaluated on two real-world tasks related to speech segmentation. Our algorithms outperform baseline segmentation algorithms.
Reed-Muller codes for random erasures and errors
Venue: arXiv cs.IT 2014
Year: 2014

This paper studies the parameters for which Reed-Muller (RM) codes over $GF(2)$ can correct random erasures and random errors with high probability, and in particular when can they achieve capacity for these two classical channels. Necessarily, the paper also studies properties of evaluations of multi-variate $GF(2)$ polynomials on random sets of inputs. For erasures, we prove that RM codes achieve capacity both for very high rate and very low rate regimes. For errors, we prove that RM codes achieve capacity for very low rate regimes, and for very high rates, we show that they can uniquely decode at about square root of the number of errors at capacity. The proofs of these four results are based on different techniques, which we find interesting in their own right. In particular, we study the following questions about $E(m,r)$, the matrix whose rows are truth tables of all monomials of degree $\leq r$ in $m$ variables. What is the most (resp. least) number of random columns in $E(m,r)$ that define a submatrix having full column rank (resp. full row rank) with high probability? We obtain tight bounds for very small (resp. very large) degrees $r$, which we use to show that RM codes achieve capacity for erasures in these regimes. Our decoding from random errors follows from the following novel reduction. For every linear code $C$ of sufficiently high rate we construct a new code $C'$, also of very high rate, such that for every subset $S$ of coordinates, if $C$ can recover from erasures in $S$, then $C'$ can recover from errors in $S$. Specializing this to RM codes and using our results for erasures imply our result on unique decoding of RM codes at high rate. Finally, two of our capacity achieving results require tight bounds on the weight distribution of RM codes. We obtain such bounds extending the recent \cite{KLP} bounds from constant degree to linear degree polynomials.
Joint Write-Once-Memory and Error-Control Codes
Venue: arXiv cs.IT 2014
Year: 2014

Write-Once-Memory (WOM) is a model for many modern non-volatile memories, such as flash memories. Recently, several capacity-achieving WOM coding schemes have been proposed based on polar coding. Due to the fact that practical computer memory systems always contain noises, a nature question to ask next is how may we generalize these coding schemes, such that they may also have the error-control capabilities. In this paper, we discuss a joint WOM and error-control coding scheme, which is a generalization of the capacity-achieving WOM codes based on source polarization. In this paper, we prove a sufficient and necessary condition for the noisy reading channel being less noisy than the test channel in data encoding in the polar WOM coding. Such a sufficient and necessary condition is usually satisfied in reality. As a consequence of the sufficient and necessary condition, the high entropy set related to the noisy channel is usually strictly contained in the high entropy set related to the test channel in data encoding. Therefore the low-complexity polar joint WOM and error-control codes are sufficient for most practical coding scenarios.
Security Evaluation for Mail Distribution Systems
Venue: arXiv cs.CR 2014
Year: 2014

The security evaluation for Mail Distribution Systems focuses on certification and reliability of sensitive data between mail servers. The need to certify the information conveyed is a result of known weaknesses in the simple mail transfer protocol (SMTP). The most important consequence of these weaknesses is the possibility to mislead the recipient, which is achieved via spam (especially email spoofing). Email spoofing refers to alterations in the headers and/or the content of the message. Therefore, the authenticity of the message is compromised. Unfortunately, the broken link between certification and reliability of the information is unsolicited email (spam). Unlike the current practice of estimating the cost of spam, which prompts organizations to purchase and maintain appropriate anti-spam software, our approach offers an alternative perspective of the economic and moral consequences of unsolicited mail. The financial data provided in this paper show that spam is a major contributor to the financial and production cost of an organization, necessitating further attention. Additionally, this paper highlights the importance and severity of the weaknesses of the SMTP protocol, which can be exploited even with the use of simple applications incorporated within most commonly used Operating Systems (e.g. Telnet). As a consequence of these drawbacks Mail Distribution Systems need to be appropriate configured so as to provide the necessary security services to the users.
AlexU-Word: A New Dataset for Isolated-Word Closed-Vocabulary Offline Arabic Handwriting Recognition
Venue: arXiv cs.CV 2014
Year: 2014

In this paper, we introduce the first phase of a new dataset for offline Arabic handwriting recognition. The aim is to collect a very large dataset of isolated Arabic words that covers all letters of the alphabet in all possible shapes using a small number of simple words. The end goal is to collect a very large dataset of segmented letter images, which can be used to build and evaluate Arabic handwriting recognition systems that are based on segmented letter recognition. The current version of the dataset contains $25114$ samples of $109$ unique Arabic words that cover all possible shapes of all alphabet letters. The samples were collected from $907$ writers. In its current form, the dataset can be used for the problem of closed-vocabulary word recognition. We evaluated a number of window-based descriptors and classifiers on this task and obtained an accuracy of $92.16\%$ using a SIFT-based descriptor and ANN.
Path Sampling: A Fast and Provable Method for Estimating 4-Vertex Subgraph Counts
Venue: arXiv cs.DS 2014
Year: 2014

Counting the frequency of small subgraphs is a fundamental technique in network analysis across various domains, most notably in bioinformatics and social networks. The special case of triangle counting has received much attention. Getting results for 4-vertex patterns is highly challenging, and there are few practical results known that can scale to massive sizes. Indeed, even a highly tuned enumeration code takes more than a day on a graph with millions of edges. Most previous work that runs for truly massive graphs employ clusters and massive parallelization. We provide a sampling algorithm that provably and accurately approximates the frequencies of all 4-vertex pattern subgraphs. Our algorithm is based on a novel technique of 3-path sampling and a special pruning scheme to decrease the variance in estimates. We provide theoretical proofs for the accuracy of our algorithm, and give formal bounds for the error and confidence of our estimates. We perform a detailed empirical study and show that our algorithm provides estimates within 1% relative error for all subpatterns (over a large class of test graphs), while being orders of magnitude faster than enumeration and other sampling based algorithms. Our algorithm takes less than a minute (on a single commodity machine) to process an Orkut social network with 300 million edges.
Network Motifs Analysis of Croatian Literature
Venue: arXiv cs.CL 2014
Year: 2014

In this paper we analyse network motifs in the co-occurrence directed networks constructed from five different texts (four books and one portal) in the Croatian language. After preparing the data and network construction, we perform the network motif analysis. We analyse the motif frequencies and Z-scores in the five networks. We present the triad significance profile for five datasets. Furthermore, we compare our results with the existing results for the linguistic networks. Firstly, we show that the triad significance profile for the Croatian language is very similar with the other languages and all the networks belong to the same family of networks. However, there are certain differences between the Croatian language and other analysed languages. We conclude that this is due to the free word-order of the Croatian language.
Music Data Analysis: A State-of-the-art Survey
Venue: arXiv cs.DB 2014
Year: 2014

Music accounts for a significant chunk of interest among various online activities. This is reflected by wide array of alternatives offered in music related web/mobile apps, information portals, featuring millions of artists, songs and events attracting user activity at similar scale. Availability of large scale structured and unstructured data has attracted similar level of attention by data science community. This paper attempts to offer current state-of-the-art in music related analysis. Various approaches involving machine learning, information theory, social network analysis, semantic web and linked open data are represented in the form of taxonomy along with data sources and use cases addressed by the research community.
Model of Interaction between Learning and Evolution
Venue: arXiv cs.NE 2014
Year: 2014

The model of interaction between learning and evolutionary optimization is designed and investigated. The evolving population of modeled organisms is considered. The mechanism of the genetic assimilation of the acquired features during a number of generations of Darwinian evolution is studied. It is shown that the genetic assimilation takes place as follows: phenotypes of modeled organisms move towards the optimum at learning; then the selection takes place; genotypes of selected organisms also move towards the optimum. The hiding effect is also studied; this effect means that strong learning can inhibit the evolutionary search for the optimal genotype. The mechanism of influence of the learning load on the interaction between learning and evolution is analyzed. It is shown that the learning load can lead to a significant acceleration of evolution.
CBM: A Crypto-Coded Modulation Scheme for Rate Information Concealing and Robustness Boosting
Venue: arXiv cs.CR 2014
Year: 2014

Exposing the rate information of wireless transmission enables highly efficient attacks that can severely degrade the performance of a network at very low cost. In this paper, we introduce an integrated solution to conceal the rate information of wireless transmissions while simultaneously boosting the resiliency against interference. The proposed solution is based on a generalization of Trellis Coded Modulation combined with Cryptographic Interleaving. We develop algorithms for discovering explicit codes for concealing any modulation in {BPSK, QPSK, 8-PSK, 16-QAM, 64-QAM}. We demonstrate that in most cases this modulation hiding scheme has the side effect of boosting resiliency by up to 8.5dB.
Developing a SAAS-Cloud Integrated Development Environment (IDE) for C, C++, and Java
Venue: arXiv cs.SE 2014
Year: 2014

Cloud era brought revolution of computerization world. People could access their data from anywhere and anytime with different devices. One of the cloud's model is Software as a Service, which capable to provide applications that run on a cloud infrastructure.An IDE (Integrated Development Environment) is the most popular tool to develop application in the network or single computer development. By installing IDE in each computer of the network could causes the lot of time and budget spending. The objective of the research is developing an efficient cloud based IDE. The IDE could compile the code which sent from client browser through SaaS IDE to the server and send it back to the client. The method that used in the research is the System Development Life-Cycle: Waterfall and Unified Model Language as system designing tool. The research successfully produced the cloud-based SaaS IDE with excellent result from several testing in local network and internet.
Analytical Performance Model for Poisson Wireless Networks with Pathloss and Shadowing Propagation
Venue: arXiv cs.NI 2014
Year: 2014

The SINR (signal to interference plus noise ratio) is a key factor for wireless networks analysis. Indeed, the SINR distribution allows the derivation of performance and quality of service (QoS) evaluation. Moreover, it also enables the analysis of radio resources allocation and scheduling policies, since they depend on the SINR reached by a UE (User Equipment). Therefore, it is particularly interesting to develop an analytical method which allows to evaluate the SINR, in a simple and quick way, for a realistic environment. Considering a stochastic Poisson network model, we establish the CDF (cumulative distributed function) of the SINR. We show that the shadowing can be neglected, in many cases, as long as mobiles are connected to their best serving base station (BS), i.e. the BS which offers them the most powerful useful signal. As a consequence, the analysis of performance and quality of service, directly derived from the CDF of SINR, can be established by using a propagation model which takes into account only the pathloss. Moreover, we establish that the Fluid network model we have proposed can be used to analyze stochastic Poisson distributed network. Therefore, the analysis of stochastic Poisson network can be done in an easy and quick way, by using the analytical expression of the SINR established thanks to the Fluid network model.
Sparse distributed localized gradient fused features of objects
Venue: arXiv cs.CV 2014
Year: 2014

The sparse, hierarchical, and modular processing of natural signals is related to the ability of humans to recognize objects with high accuracy. In this study, we report a sparse feature processing and encoding method, which improved the recognition performance of an automated object recognition system. Randomly distributed localized gradient enhanced features were selected before employing aggregate functions for representation, where we used a modular and hierarchical approach to detect the object features. These object features were combined with a minimum distance classifier, thereby obtaining object recognition system accuracies of 93% using the Amsterdam library of object images (ALOI) database, 92% using the Columbia object image library (COIL)-100 database, and 69% using the PASCAL visual object challenge 2007 database. The object recognition performance was shown to be robust to variations in noise, object scaling, and object shifts. Finally, a comparison with eight existing object recognition methods indicated that our new method improved the recognition accuracy by 10% with ALOI, 8% with the COIL-100 database, and 10% with the PASCAL visual object challenge 2007 database.
Efficient Media Retrieval from Non-Cooperative Queries
Venue: arXiv cs.IR 2014
Year: 2014

Text is ubiquitous in the artificial world and easily attainable when it comes to book title and author names. Using the images from the book cover set from the Stanford Mobile Visual Search dataset and additional book covers and metadata from openlibrary.org, we construct a large scale book cover retrieval dataset, complete with 100K distractor covers and title and author strings for each. Because our query images are poorly conditioned for clean text extraction, we propose a method for extracting a matching noisy and erroneous OCR readings and matching it against clean author and book title strings in a standard document look-up problem setup. Finally, we demonstrate how to use this text-matching as a feature in conjunction with popular retrieval features such as VLAD using a simple learning setup to achieve significant improvements in retrieval accuracy over that of either VLAD or the text alone.
End-to-End Integration of a Convolutional Network, Deformable Parts Model and Non-Maximum Suppression
Venue: arXiv cs.CV 2014
Year: 2014

Deformable Parts Models and Convolutional Networks each have achieved notable performance in object detection. Yet these two approaches find their strengths in complementary areas: DPMs are well-versed in object composition, modeling fine-grained spatial relationships between parts; likewise, ConvNets are adept at producing powerful image features, having been discriminatively trained directly on the pixels. In this paper, we propose a new model that combines these two approaches, obtaining the advantages of each. We train this model using a new structured loss function that considers all bounding boxes within an image, rather than isolated object instances. This enables the non-maximal suppression (NMS) operation, previously treated as a separate post-processing stage, to be integrated into the model. This allows for discriminative training of our combined Convnet + DPM + NMS model in end-to-end fashion. We evaluate our system on PASCAL VOC 2007 and 2011 datasets, achieving competitive results on both benchmarks.
Optimization of Hybrid PV/Wind Power System for Remote Telecom Station
Venue: arXiv cs.SY 2014
Year: 2014

The rapid depletion of fossil fuel resources and environmental concerns has given awareness on generation of renewable energy resources. Among the various renewable resources, hybrid solar and wind energy seems to be promising solutions to provide reliable power supply with improved system efficiency and reduced storage requirements for stand-alone applications. This paper presents a feasibility assessment and optimum size of photovoltaic (PV) array, wind turbine and battery bank for a standalone hybrid Solar/Wind Power system (HSWPS) at remote telecom station of Nepal at Latitude (27°23'50") and Longitude (86°44'23") consisting a telecommunication load of Very Small Aperture Terminal (VSAT), Repeater station and Code Division Multiple Access Base Transceiver Station (CDMA 2C10 BTS). In any RES based system, the feasibility assessment is considered as the first step analysis. In this work, feasibility analysis is carried through hybrid optimization model for electric renewables (HOMER) and mathematical models were implemented in the MATLAB environment to perform the optimal configuration for a given load and a desired loss of power supply probability (LPSP) from a set of systems components with the lowest value of cost function defined in terms of reliability and levelized unit electricity cost (LUCE). The simulation results for the existing and the proposed models are compared. The simulation results shows that existing architecture consisting of 6.12 kW KC85T photovoltaic modules, 1kW H3.1 wind turbine and 1600 Ah GFM-800 battery bank have a 36.6% of unmet load during a year. On the other hand, the proposed system includes 1kW *2 H3.1 Wind turbine, 8.05 kW TSM-175DA01 photovoltaic modules and 1125 Ah T-105 battery bank with system reliability of 99.99% with a significant cost reduction as well as reliable energy production.
Stable Model Counting and Its Application in Probabilistic Logic Programming
Venue: arXiv cs.AI 2014
Year: 2014

Model counting is the problem of computing the number of models that satisfy a given propositional theory. It has recently been applied to solving inference tasks in probabilistic logic programming, where the goal is to compute the probability of given queries being true provided a set of mutually independent random variables, a model (a logic program) and some evidence. The core of solving this inference task involves translating the logic program to a propositional theory and using a model counter. In this paper, we show that for some problems that involve inductive definitions like reachability in a graph, the translation of logic programs to SAT can be expensive for the purpose of solving inference tasks. For such problems, direct implementation of stable model semantics allows for more efficient solving. We present two implementation techniques, based on unfounded set detection, that extend a propositional model counter to a stable model counter. Our experiments show that for particular problems, our approach can outperform a state-of-the-art probabilistic logic programming solver by several orders of magnitude in terms of running time and space requirements, and can solve instances of significantly larger sizes on which the current solver runs out of time or memory.
Network motifs emerge from interconnections that favor stability
Venue: arXiv cs.SY 2014
Year: 2014

Network motifs are overrepresented interconnection patterns found in real-world networks. What functional advantages may they offer for building complex systems? We show that most network motifs emerge from interconnections patterns that best exploit the intrinsic stability characteristics of individual nodes. This feature is observed at different scales in a network, from nodes to modules, suggesting an efficient mechanism to stably build complex systems.
Fast Matrix Multiplication: Limitations of the Laser Method
Venue: arXiv cs.CC 2014
Year: 2014

Until a few years ago, the fastest known matrix multiplication algorithm, due to Coppersmith and Winograd (1990), ran in time $O(n^{2.3755})$. Recently, a surge of activity by Stothers, Vassilevska-Williams, and Le Gall has led to an improved algorithm running in time $O(n^{2.3729})$. These algorithms are obtained by analyzing higher and higher tensor powers of a certain identity of Coppersmith and Winograd. We show that this exact approach cannot result in an algorithm with running time $O(n^{2.3725})$, and identify a wide class of variants of this approach which cannot result in an algorithm with running time $O(n^{2.3078})$; in particular, this approach cannot prove the conjecture that for every $ε> 0$, two $n\times n$ matrices can be multiplied in time $O(n^{2+ε})$. We describe a new framework extending the original laser method, which is the method underlying the previously mentioned algorithms. Our framework accommodates the algorithms by Coppersmith and Winograd, Stothers, Vassilevska-Williams and Le Gall. We obtain our main result by analyzing this framework. The framework is also the first to explain why taking tensor powers of the Coppersmith-Winograd identity results in faster algorithms.