OpenRaiser/Intern-Atlas huggingface dataset:
Extensionality of lambda-*
Venue: arXiv cs.LO 2014
Year: 2014

We prove an extensionality theorem for the "type-in-type" dependent type theory with Sigma-types. We suggest that the extensional equality type be identified with the logical equivalence relation on the free term model of type theory.
Bangla Text Recognition from Video Sequence: A New Focus
Venue: arXiv cs.CV 2014
Year: 2014

Extraction and recognition of Bangla text from video frame images is challenging due to complex color background, low-resolution etc. In this paper, we propose an algorithm for extraction and recognition of Bangla text form such video frames with complex background. Here, a two-step approach has been proposed. First, the text line is segmented into words using information based on line contours. First order gradient value of the text blocks are used to find the word gap. Next, a local binarization technique is applied on each word and text line is reconstructed using those words. Secondly, this binarized text block is sent to OCR for recognition purpose.
A Fast Decodable Full-Rate STBC with High Coding Gain for 4x2 MIMO Systems
Venue: arXiv cs.IT 2014
Year: 2014

In this work, a new fast-decodable space-time block code (STBC) is proposed. The code is full-rate and full-diversity for 4x2 multiple-input multiple-output (MIMO) transmission. Due to the unique structure of the codeword, the proposed code requires a much lower computational complexity to provide maximum-likelihood (ML) decoding performance. It is shown that the ML decoding complexity is only O(M^{4.5}) when M-ary square QAM constellation is used. Finally, the proposed code has highest minimum determinant among the fast-decodable STBCs known in the literature. Simulation results prove that the proposed code provides the best bit error rate (BER) performance among the state-of-the-art STBCs.
A Cryptographic Scheme Of Mellin Transform
Venue: arXiv cs.CR 2014
Year: 2014

In this paper it has been developed an algorithm for cryptography, using the Mellin's transform. Cryptography is very important to protect data to ensure that two people, using an insecure channel, may communicate in a secure way. In the present age, ensure the communications will essential to shared data that have to be protected. The original message is a plain text, and the encrypted form as cipher text. The cipher text message contains all the information of the plain text, but is cannot be read from a human without a key and a method to decrypt it.
Analysis and Optimization of Random Sensing Order in Cognitive Radio Networks
Venue: arXiv cs.IT 2014
Year: 2014

Developing an efficient spectrum access policy enables cognitive radios to dramatically increase spectrum utilization while ensuring predetermined quality of service levels for primary users. In this paper, modeling, performance analysis, and optimization of a distributed secondary network with random sensing order policy are studied. Specifically, the secondary users create a random order of available channels upon primary users return, and then find optimal transmission and handoff opportunities in a distributed manner. By a Markov chain analysis, the average throughputs of the secondary users and average interference level among the secondary and primary users are investigated. A maximization of the secondary network performance in terms of the throughput while keeping under control the average interference is proposed. It is shown that despite of traditional view, non-zero false alarm in the channel sensing can increase channel utilization, especially in a dense secondary network where the contention is too high. Then, two simple and practical adaptive algorithms are established to optimize the network. The second algorithm follows the variations of the wireless channels in non-stationary conditions and outperforms even static brute force optimization, while demanding few computations. The convergence of the distributed algorithms are theoretically investigated based on the analytical performance indicators established by the Markov chain analysis. Finally, numerical results validate the analytical derivations and demonstrate the efficiency of the proposed schemes. It is concluded that fully distributed sensing order algorithms can lead to substantial performance improvements in cognitive radio networks without the need of centralized management or message passing among the users.
A Robust Biometric-Based Three-factor Remote User Authentication Scheme
Venue: arXiv cs.CR 2014
Year: 2014

The rapid development of Internet of Things (IoT) technology, which is an inter connection of networks through an insecure public channel i.e. Internet demands for authenticating the remote user trying to access the secure network resources. In 2013, Ankita et al. proposed an improved three factor remote user authentication scheme. In this poster we will show that Ankita et al scheme is vulnerable to known session specific temporary information attack, on successfully performing the attack, the adversary can perform all other major cryptographic attacks. As a part of our contribution, we will propose an improved scheme which is resistance to all major cryptographic attacks and overcomes the defects in Ankita et al. scheme.
Transparent Combination of Expert and Measurement Data for Defect Prediction: An Industrial Case Study
Venue: arXiv cs.SE 2014
Year: 2014

Defining strategies on how to perform quality assurance (QA) and how to control such activities is a challenging task for organizations developing or maintaining software and software-intensive systems. Planning and adjusting QA activities could benefit from accurate estimations of the expected defect content of relevant artifacts and the effectiveness of important quality assurance activities. Combining expert opinion with commonly available measurement data in a hybrid way promises to overcome the weaknesses of purely data-driven or purely expert-based estimation methods. This article presents a case study of the hybrid estimation method HyDEEP for estimating defect content and QA effectiveness in the telecommunication domain. The specific focus of this case study is the use of the method for gaining quantitative predictions. This aspect has not been empirically analyzed in previous work. Among other things, the results show that for defect content estimation, the method performs significantly better statistically than purely data-based methods, with a relative error of 0.3 on average (MMRE).
MANIAC Challenge: The Wolf-pack strategy
Venue: arXiv cs.NI 2014
Year: 2014

MANIAC Challenge raises a problem of game theory, different players strategies intertwine and the success of any player is dependent on the actions of all players in the system. A truly fair scenario is when all the strategies are identical, all the nodes co-operate and they all equally share the rewards and risks that come with every transfer. A successful strategy is one that tries to diverge from the equilibrium to maximize its own gains and it manages to do so. We propose the wolf-pack strategy. Unlike standard game-theory based strategies, our strategy does not penalize the nodes that diverge from fairness or from equilibrium, as we believe most nodes will do so in an attempt to get an advantage over the other nodes. The wolf-pack strategy will try to always find the most successful node or nodes and penalize them. We believe that just like in nature, a number of small predators can take down the bigger, more profitable ones. Furthermore during the Challenge we test two different strategies that provide completely opposite results. These offer a clear picture of what the best strategy is and the problems of the current system.
BigDataBench: a Big Data Benchmark Suite from Internet Services
Venue: arXiv cs.DB 2014
Year: 2014

As architecture, systems, and data management communities pay greater attention to innovative big data systems and architectures, the pressure of benchmarking and evaluating these systems rises. Considering the broad use of big data systems, big data benchmarks must include diversity of data and workloads. Most of the state-of-the-art big data benchmarking efforts target evaluating specific types of applications or system software stacks, and hence they are not qualified for serving the purposes mentioned above. This paper presents our joint research efforts on this issue with several industrial partners. Our big data benchmark suite BigDataBench not only covers broad application scenarios, but also includes diverse and representative data sets. BigDataBench is publicly available from http://prof.ict.ac.cn/BigDataBench . Also, we comprehensively characterize 19 big data workloads included in BigDataBench with varying data inputs. On a typical state-of-practice processor, Intel Xeon E5645, we have the following observations: First, in comparison with the traditional benchmarks: including PARSEC, HPCC, and SPECCPU, big data applications have very low operation intensity; Second, the volume of data input has non-negligible impact on micro-architecture characteristics, which may impose challenges for simulation-based big data architecture research; Last but not least, corroborating the observations in CloudSuite and DCBench (which use smaller data inputs), we find that the numbers of L1 instruction cache misses per 1000 instructions of the big data applications are higher than in the traditional benchmarks; also, we find that L3 caches are effective for the big data applications, corroborating the observation in DCBench.
B-Maniac
Venue: arXiv cs.NI 2014
Year: 2014

Mobile Data Offloading permits users to use cheap communication media, whenever feasible, for delivering their personal data instead of using the infrastructure which is more expensive. Having good procedures to assess and compare the different possibilities a device has to send his data is crucial. In the following paper, we propose an evaluating approach that takes into consideration the topology changes history in order to provide an efficient way to calculate the quality of a specific medium. In particular \textit{Bayesian Networks} are used as basis to provide our solution to the Maniac Challenge 2013. Bayesian Networks is a statistical model for the generation of inferences starting with very little information. In the next sections we will give a definition of the Bayesian Networks focusing on the simplest and computationally efficient of the Bayesian Networks versions, named \textit{\naive Bayes}. Finally, we will show our method for the challenge to evaluate the medium and the bid strategy.
Smart Grid Demand Monitoring Model
Venue: arXiv cs.OH 2014
Year: 2014

This paper is in related to the demand genrated by the consumer for a time for the power which is being viewed by taking some measures to solve the demand need.
Using temporal IDF for efficient novelty detection in text streams
Venue: arXiv cs.IR 2014
Year: 2014

Novelty detection in text streams is a challenging task that emerges in quite a few different scenarios, ranging from email thread filtering to RSS news feed recommendation on a smartphone. An efficient novelty detection algorithm can save the user a great deal of time and resources when browsing through relevant yet usually previously-seen content. Most of the recent research on detection of novel documents in text streams has been building upon either geometric distances or distributional similarities, with the former typically performing better but being much slower due to the need of comparing an incoming document with all the previously-seen ones. In this paper, we propose a new approach to novelty detection in text streams. We describe a resource-aware mechanism that is able to handle massive text streams such as the ones present today thanks to the burst of social media and the emergence of the Web as the main source of information. We capitalize on the historical Inverse Document Frequency (IDF) that was known for capturing well term specificity and we show that it can be used successfully at the document level as a measure of document novelty. This enables us to avoid similarity comparisons with previous documents in the text stream, thus scaling better and leading to faster execution times. Moreover, as the collection of documents evolves over time, we use a temporal variant of IDF not only to maintain an efficient representation of what has already been seen but also to decay the document frequencies as the time goes by. We evaluate the performance of the proposed approach on a real-world news articles dataset created for this task. The results show that the proposed method outperforms all of the baselines while managing to operate efficiently in terms of time complexity and memory usage, which are of great importance in a mobile setting scenario.
Generalized friendship paradox in complex networks: The case of scientific collaboration
Venue: arXiv cs.SI 2014
Year: 2014

The friendship paradox states that your friends have on average more friends than you have. Does the paradox "hold" for other individual characteristics like income or happiness? To address this question, we generalize the friendship paradox for arbitrary node characteristics in complex networks. By analyzing two coauthorship networks of Physical Review journals and Google Scholar profiles, we find that the generalized friendship paradox (GFP) holds at the individual and network levels for various characteristics, including the number of coauthors, the number of citations, and the number of publications. The origin of the GFP is shown to be rooted in positive correlations between degree and characteristics. As a fruitful application of the GFP, we suggest effective and efficient sampling methods for identifying high characteristic nodes in large-scale networks. Our study on the GFP can shed lights on understanding the interplay between network structure and node characteristics in complex networks.
Maximal Sharing in the Lambda Calculus with letrec
Venue: arXiv cs.PL 2014
Year: 2014

Increasing sharing in programs is desirable to compactify the code, and to avoid duplication of reduction work at run-time, thereby speeding up execution. We show how a maximal degree of sharing can be obtained for programs expressed as terms in the lambda calculus with letrec. We introduce a notion of `maximal compactness' for lambda-letrec-terms among all terms with the same infinite unfolding. Instead of defined purely syntactically, this notion is based on a graph semantics. lambda-letrec-terms are interpreted as first-order term graphs so that unfolding equivalence between terms is preserved and reflected through bisimilarity of the term graph interpretations. Compactness of the term graphs can then be compared via functional bisimulation. We describe practical and efficient methods for the following two problems: transforming a lambda-letrec-term into a maximally compact form; and deciding whether two lambda-letrec-terms are unfolding-equivalent. The transformation of a lambda-letrec-term $L$ into maximally compact form $L_0$ proceeds in three steps: (i) translate L into its term graph $G = [[ L ]]$; (ii) compute the maximally shared form of $G$ as its bisimulation collapse $G_0$; (iii) read back a lambda-letrec-term $L_0$ from the term graph $G_0$ with the property $[[ L_0 ]] = G_0$. This guarantees that $L_0$ and $L$ have the same unfolding, and that $L_0$ exhibits maximal sharing. The procedure for deciding whether two given lambda-letrec-terms $L_1$ and $L_2$ are unfolding-equivalent computes their term graph interpretations $[[ L_1 ]]$ and $[[ L_2 ]]$, and checks whether these term graphs are bisimilar. For illustration, we also provide a readily usable implementation.
Lower Bounds and Approximations for the Information Rate of the ISI Channel
Venue: arXiv cs.IT 2014
Year: 2014

We consider the discrete-time intersymbol interference (ISI) channel model, with additive Gaussian noise and fixed i.i.d. inputs. In this setting, we investigate the expression put forth by Shamai and Laroia as a conjectured lower bound for the input-output mutual information after application of a MMSE-DFE receiver. A low-SNR expansion is used to prove that the conjectured bound does not hold under general conditions, and to characterize inputs for which it is particularly ill-suited. One such input is used to construct a counterexample, indicating that the Shamai-Laroia expression does not always bound even the achievable rate of the channel, thus excluding a natural relaxation of the original conjectured bound. However, this relaxed bound is then shown to hold for any finite entropy input and ISI channel, when the SNR is sufficiently high. Finally, new simple bounds for the achievable rate are proven, and compared to other known bounds. Information-Estimation relations and estimation-theoretic bounds play a key role in establishing our results.
Discrete-Time Output-Feedback Robust Repetitive Control for a Class of Nonlinear Systems by Additive State Decomposition
Venue: arXiv cs.SY 2014
Year: 2014

The discrete-time robust repetitive control (RC, or repetitive controller, also designated RC) problem for nonlinear systems is both challenging and practical. This paper proposes a discrete-time output-feedback RC design for a class of systems subject to measurable nonlinearities to track reference robustly with respect to the period variation. The design relies on additive state decomposition, by which the output-feedback RC problem is decomposed into an output-feedback RC problem for a linear time-invariant system and a state-feedback stabilization problem for a nonlinear system. Thanks to the decomposition, existing controller design methods in both the frequency domain and time domain can be employed to make the robustness and discretization for a nonlinear system tractable. To demonstrate the effectiveness, an illustrative example is given.
Fast nonparametric clustering of structured time-series
Venue: arXiv cs.LG 2014
Year: 2014

In this publication, we combine two Bayesian non-parametric models: the Gaussian Process (GP) and the Dirichlet Process (DP). Our innovation in the GP model is to introduce a variation on the GP prior which enables us to model structured time-series data, i.e. data containing groups where we wish to model inter- and intra-group variability. Our innovation in the DP model is an implementation of a new fast collapsed variational inference procedure which enables us to optimize our variationala pproximation significantly faster than standard VB approaches. In a biological time series application we show how our model better captures salient features of the data, leading to better consistency with existing biological classifications, while the associated inference algorithm provides a twofold speed-up over EM-based variational inference.
Tendencies, Dead-ends, and Promising Ways. From Interface Ideas to New Programs
Venue: arXiv cs.HC 2014
Year: 2014

The mechanism of communication between users and devices is called interface. From time to time changes in interface significantly improve our work with computers even without any serious changes in programs themselves. Main ideas in PCs interface were introduced many years ago and since then there are no significant changes, while new devices show promising ways by using direct manipulation of screen objects. Users' direct action with all the screen objects of our ordinary PCs turns standard screens into touch screens of very high resolution and not only changes the interface of familiar programs but creates the new type of programs: user-driven applications.
Exploiting Capture Effect in Frameless ALOHA for Massive Wireless Random Access
Venue: arXiv cs.IT 2014
Year: 2014

The analogies between successive interference cancellation (SIC) in slotted ALOHA framework and iterative belief-propagation erasure-decoding, established recently, enabled the application of the erasure-coding theory and tools to design random access schemes. This approach leads to throughput substantially higher than the one offered by the traditional slotted ALOHA. In the simplest setting, SIC progresses when a successful decoding occurs for a single user transmission. In this paper we consider a more general setting of a channel with capture and explore how such physical model affects the design of the coded random access protocol. Specifically, we assess the impact of capture effect in Rayleigh fading scenario on the design of SIC-enabled slotted ALOHA schemes. We provide analytical treatment of frameless ALOHA, which is a special case of SIC-enabled ALOHA scheme. We demonstrate both through analytical and simulation results that the capture effect can be very beneficial in terms of achieved throughput.
Wireless Scheduling Algorithms in Complex Environments
Venue: arXiv cs.NI 2014
Year: 2014

Efficient spectrum use in wireless sensor networks through spatial reuse requires effective models of packet reception at the physical layer in the presence of interference. Despite recent progress in analytic and simulations research into worst-case behavior from interference effects, these efforts generally assume geometric path loss and isotropic transmission, assumptions which have not been borne out in experiments. Our paper aims to provide a methodology for grounding theoretical results into wireless interference in experimental reality. We develop a new framework for wireless algorithms in which distance-based path loss is replaced by an arbitrary gain matrix, typically obtained by measurements of received signal strength (RSS). Gain matrices allow for the modeling of complex environments, e.g., with obstacles and walls. We experimentally evaluate the framework in two indoors testbeds with 20 and 60 motes, and confirm superior predictive performance in packet reception rate for a gain matrix model over a geometric distance-based model. At the heart of our approach is a new parameter $ζ$ called metricity which indicates how close the gain matrix is to a distance metric, effectively measuring the complexity of the environment. A powerful theoretical feature of this parameter is that all known SINR scheduling algorithms that work in general metric spaces carry over to arbitrary gain matrices and achieve equivalent performance guarantees in terms of $ζ$ as previously obtained in terms of the path loss constant. Our experiments confirm the sensitivity of $ζ$ to the nature of the environment. Finally, we show analytically and empirically how multiple channels can be leveraged to improve metricity and thereby performance. We believe our contributions will facilitate experimental validation for recent advances in algorithms for physical wireless interference models.
Visualization of Software and Systems as Support Mechanism for Integrated Software Project Control
Venue: arXiv cs.SE 2014
Year: 2014

Many software development organizations still lack support for obtaining intellectual control over their software development processes and for determining the performance of their processes and the quality of the produced products. Systematic support for detecting and reacting to critical process and product states in order to achieve planned goals is usually missing. One means to institutionalize measurement on the basis of explicit models is the development and establishment of a so-called Software Project Control Center (SPCC) for systematic quality assurance and management support. An SPCC is comparable to a control room, which is a well known term in the mechanical production domain. One crucial task of an SPCC is the systematic visualization of measurement data in order to provide context-, purpose-, and role-oriented information for all stakeholders (e.g., project managers, quality assurance managers, developers) during the execution of a software development project. The article will present an overview of SPCC concepts, a concrete instantiation that supports goal-oriented data visualization, as well as examples and experiences from practical applications.