OpenRaiser/Intern-Atlas huggingface dataset:
Proactive Web Server Protocol for Complaint Assessment
Venue: arXiv cs.NI 2014
Year: 2014

Vulnerability Discovery with attack Injection security threats are increasing for the server software, when software is developed, the software tested for the functionality. Due to unawareness of software vulnerabilities most of the software before pre-Release the software should be thoroughly tested for not only functionality reliability, but should be tested for the security flows (or) vulnerabilities. The approaches such as fuzzers, Fault injection, vulnerabilities scanners, static vulnerabilities analyzers, Run time prevention mechanisms and software Rejuvenation are identifying the un-patched software which is open for security threats address to solve the problem "security testing". These techniques are useful for generating attacks but cannot be extendable for the new land of attacks. The system called proactive vulnerability attack injection tool is suitable for adding new attacks injection vectors, methods to define new protocol states (or) Specification using the interface of tool includes Network server protocol specification using GUI, Attacks generator, Attack injector, monitoring module at the victim injector, monitoring module at the victim machine and the attacks injection report generation. This tool can address most of the vulnerabilities (or) security flows.
Analysis of Hashrate-Based Double Spending
Venue: arXiv cs.CR 2014
Year: 2014

Bitcoin is the world's first decentralized digital currency. Its main technical innovation is the use of a blockchain and hash-based proof of work to synchronize transactions and prevent double-spending the currency. While the qualitative nature of this system is well understood, there is widespread confusion about its quantitative aspects and how they relate to attack vectors and their countermeasures. In this paper we take a look at the stochastic processes underlying typical attacks and their resulting probabilities of success.
Deeply Coupled Auto-encoder Networks for Cross-view Classification
Venue: arXiv cs.CV 2014
Year: 2014

The comparison of heterogeneous samples extensively exists in many applications, especially in the task of image classification. In this paper, we propose a simple but effective coupled neural network, called Deeply Coupled Autoencoder Networks (DCAN), which seeks to build two deep neural networks, coupled with each other in every corresponding layers. In DCAN, each deep structure is developed via stacking multiple discriminative coupled auto-encoders, a denoising auto-encoder trained with maximum margin criterion consisting of intra-class compactness and inter-class penalty. This single layer component makes our model simultaneously preserve the local consistency and enhance its discriminative capability. With increasing number of layers, the coupled networks can gradually narrow the gap between the two views. Extensive experiments on cross-view image classification tasks demonstrate the superiority of our method over state-of-the-art methods.
An Achievable Rate-Distortion Region for the Multiple Descriptions Problem
Venue: arXiv cs.IT 2014
Year: 2014

A multiple-descriptions (MD) coding strategy is proposed and an inner bound to the achievable rate-distortion region is derived. The scheme utilizes linear codes. It is shown in two different MD set-ups that the linear coding scheme achieves a larger rate-distortion region than previously known random coding strategies. Furthermore, it is shown via an example that the best known random coding scheme for the set-up can be improved by including additional randomly generated codebooks.
Attribute Dependencies for Data with Grades
Venue: arXiv cs.LO 2014
Year: 2014

This paper examines attribute dependencies in data that involve grades, such as a grade to which an object is red or a grade to which two objects are similar. We thus extend the classical agenda by allowing graded, or fuzzy, attributes instead of Boolean attributes in case of attribute implications, and allowing approximate match based on degrees of similarity instead of exact match in case of functional dependencies. In a sense, we move from bivalence, inherently present in the now-available theories of dependencies, to a more flexible setting that involves grades. Such a shift has far-reaching consequences. We argue that a reasonable theory of dependencies may be developed by making use of mathematical fuzzy logic. Namely, the theory of dependencies is then based on a solid logic calculus the same way the classical dependencies are based on classical logic. For instance, rather than handling degrees of similarity in an ad hoc manner, we consistently treat them as truth values, the same way as true (match) and false (mismatch) are treated in classical theories. In addition, several notions intuitively embraced in the presence of grades, such as a degree of validity of a particular dependence or a degree of entailment, naturally emerge and receive a conceptually clean treatment in the presented approach. In the paper, we discuss motivations, provide basic notions of syntax and semantics, and develop basic results which include entailment of dependencies, associated closure structures, a logic of dependencies with two versions of completeness theorem, results and algorithms regarding complete non-redundant sets of dependencies, relationship to and a possible reductionist interface to classical dependencies, and relationship to functional dependencies over domains with similarity.
Secure Routing and Data Transmission in Mobile Ad Hoc Networks
Venue: arXiv cs.NI 2014
Year: 2014

In this paper, we present an identity (ID) based protocol that secures AODV and TCP so that it can be used in dynamic and attack prone environments of mobile ad hoc networks. The proposed protocol protects AODV using Sequential Aggregate Signatures (SAS) based on RSA. It also generates a session key for each pair of source-destination nodes of a MANET for securing the end-to-end transmitted data. Here each node has an ID which is evaluated from its public key and the messages that are sent are authenticated with a signature/ MAC. The proposed scheme does not allow a node to change its ID throughout the network lifetime. Thus it makes the network secure against attacks that target AODV and TCP in MANET. We present performance analysis to validate our claim.
Humanitarian Algorithms : A Codified Key Safety Switch Protocol for Lethal Autonomy
Venue: arXiv cs.CR 2014
Year: 2014

With the deployment of lethal autonomous weapons, there is the requirement that any such platform complies with the precepts of International Humanitarian Law. Humanitarian Algorithms[9: p. 9] ensure that lethal autonomous weapon systems perform military/security operations, within the confines of International Humanitarian Law. Unlike other existing techniques of regulating lethal autonomy this scheme advocates for an approach that enables Machine Learning. Lethal autonomous weapons must be equipped with appropriate fail-safe mechanisms that locks them if they malfunction.
Performance Analysis of AODV, DSDV and DSR in MANETs
Venue: arXiv cs.NI 2014
Year: 2014

Mobile Ad hoc Networks (MANETs) are considered as a new paradigm of infrastructure-less mobile wireless communication systems. MANETs are being widely studied and it is the technology that is attracting a large variety of applications. Routing in MANETs is considered a challenging task due to the unpredictable changes in the network topology, resulting from the random and frequent movement of the nodes and due to the absence of any centralized control [1][2]. In this paper, we evaluate the performance of reactive routing protocols, Ad hoc On demand Distance Vector (AODV) and Dynamic Source Routing (DSR) and proactive routing protocol Destination Sequenced Distance Vector (DSDV). The major goal of this study is to analyze the performance of well known MANETs routing protocol in high mobility case under low, medium and high density scenario. Unlike military applications, most of the other applications of MANETs require moderate to high mobility. Hence it becomes important to study the impact of high mobility on the performance of these routing protocols. The performance is analyzed with respect to Average End-to-End Delay, Normalized Routing Load (NRL), Packet Delivery Fraction (PDF) and Throughput. Simulation results verify that AODV gives better performance as compared to DSR and DSDV.
An Optimized Semantic Web Service Composition Method Based on Clustering and Ant Colony Algorithm
Venue: arXiv cs.SE 2014
Year: 2014

In today's Web, Web Services are created and updated on the fly. For answering complex needs of users, the construction of new web services based on existing ones is required. It has received a great attention from different communities. This problem is known as web services composition. However, it is one of big challenge problems of recent years in a distributed and dynamic environment. Web services can be composed manually but it is a time consuming task. The automatic web service composition is one of the key features for future the semantic web. The various approaches in field of web service compositions proposed by the researchers. In this paper, we propose a novel architecture for semantic web service composition using clustering and Ant colony algorithm.
Factors Modulating Software Design Quality
Venue: arXiv cs.SE 2014
Year: 2014

Object oriented approach is one of the popular software development approach for managing complex systems with massive set of requirements. Unlike procedural approach, this approach captures the requirements as set of data rather than services. Further, class is considered as a key unit of the solution-domain with data and services wrapped together, representing architectural design of a basic module. Thus, system complexity is directly related to the number of modules and the degree of interaction between them. This could be mapped as a functional diagram with cardinalities between the modules. However, complexity is always a threat to quality at each stage of software development. Design phase is therefore one of the core influencing phases during development that selects the right architecture based on the problem statement which is bound to be measured for quality. Hence, software industries adapts several organization- specific principles, domain-specific patterns, metric standards and best practices to improve and measure the quality of both process and product. The paper highlights the factors which influence the overall design quality and metrics implication in improving the quality of final product. It also presents the solution domain as an interdependent layered architecture which has a greater impact on concluding the quality of the end product. This approach of design is a unique contribution to the domain of Object Oriented approach of software development. It also focuses on design metrics which ensures the implementation of right choice of design towards the retention of quality of the product.
Virtual Learning Environments-A Survey
Venue: arXiv cs.CY 2014
Year: 2014

This paper is based on the study of existing literature, highlights the current state of the work proposed to implement technically enhanced learning. Technology developments and network infrastructure improvements, specifically the world wide web) are providing exciting opportunities for the use of computers in all areas. These developments have fit together with an evolving role for education as more students wish to study at a distance, part time, or wish to integrate their education with their professional career. With the market becoming increasingly mature, e learning has almost become a major plank in both national and institutional strategies. At the same time, virtual learning system is also gaining its popularity among its users. It has brought in a great revolution in itself. In the advanced learning strategy, virtual learning systems depends on level and sector of working, usage of functions, purpose of usage, required online resources to perform computationally intensive operations such as information sharing and collaborative work. Often the institutions prefer the latest and the best technology which is cost effective and provide the best features which meet up all requirements. Virtual learning environment enables operator professional to bring together in one place a variety of prevailing resources, suchlike tasks and formative feedback, and links to law reports, statutes and journal articles, all intended at summing up value to student learning managing learning experience without the burden of communication and providing successful delivery of education and training with flexibility. In spite of the hype achieved by organizations in technically enhanced learning, the growth of the virtual learning systems users is still below expectations due to the risks associated with the implementation strategy and provision of technical support.
Triple Patterning Lithography (TPL) Layout Decomposition using End-Cutting
Venue: arXiv cs.AR 2014
Year: 2014

Triple patterning lithography (TPL) is one of the most promising techniques in the 14nm logic node and beyond. However, traditional LELELE type TPL technology suffers from native conflict and overlapping problems. Recently LELEEC process was proposed to overcome the limitations, where the third mask is used to generate the end-cuts. In this paper we propose the first study for LELEEC layout decomposition. Conflict graphs and end-cut graphs are constructed to extract all the geometrical relationships of input layout and end-cut candidates. Based on these graphs, integer linear programming (ILP) is formulated to minimize the conflict number and the stitch number.
Imaging with Rays: Microscopy, Medical Imaging, and Computer Vision
Venue: arXiv cs.CV 2014
Year: 2014

In this paper we broadly consider techniques which utilize projections on rays for data collection, with particular emphasis on optical techniques. We formulate a variety of imaging techniques as either special cases or extensions of tomographic reconstruction. We then consider how the techniques must be extended to describe objects containing occlusion, as with a self-occluding opaque object. We formulate the reconstruction problem as a regularized nonlinear optimization problem to simultaneously solve for object brightness and attenuation, where the attenuation can become infinite. We demonstrate various simulated examples for imaging opaque objects, including sparse point sources, a conventional multiview reconstruction technique, and a super-resolving technique which exploits occlusion to resolve an image.
The Fair Distribution of Power to Electric Vehicles: An Alternative to Pricing
Venue: arXiv cs.NI 2014
Year: 2014

As the popularity of electric vehicles increases, the demand for more power can increase more rapidly than our ability to install additional generating capacity. In the long term we expect that the supply and demand will become balanced. However, in the interim the rate at which electric vehicles can be deployed will depend on our ability to charge these vehicles without inconveniencing their owners. In this paper, we investigate using fairness mechanisms to distribute power to electric vehicles on a smart grid. We assume that during peak demand there is insufficient power to charge all the vehicles simultaneously. In each five minute interval of time we select a subset of the vehicles to charge, based upon information about the vehicles. We evaluate the selection mechanisms using published data on the current demand for electric power as a function of time of day, current driving habits for commuting, and the current rates at which electric vehicles can be charged on home outlets. We found that conventional selection strategies, such as first-come-first-served or round robin, may delay a significant fraction of the vehicles by more than two hours, even when the total available power over the course of a day is two or three times the power required by the vehicles. However, a selection mechanism that minimizes the maximum delay can reduce the delays to a few minutes, even when the capacity available for charging electric vehicles exceeds their requirements by as little as 5%.
Design and Synthesis of Ultra Low Energy Spin-Memristor Threshold Logic
Venue: arXiv cs.ET 2014
Year: 2014

A threshold logic gate (TLG) performs weighted sum of multiple inputs and compares the sum with a threshold. We propose Spin-Memeristor Threshold Logic (SMTL) gates, which employ memristive cross-bar array (MCA) to perform current-mode summation of binary inputs, whereas, the low-voltage fast-switching spintronic threshold devices (STD) carry out the threshold operation in an energy efficient manner. Field programmable SMTL gate arrays can operate at a small terminal voltage of ~50mV, resulting in ultra-low power consumption in gates as well as programmable interconnect networks. We evaluate the performance of SMTL using threshold logic synthesis. Results for common benchmarks show that SMTL based programmable logic hardware can be more than 100x energy efficient than state of the art CMOS FPGA.
On Zeroth-Order Stochastic Convex Optimization via Random Walks
Venue: arXiv cs.LG 2014
Year: 2014

We propose a method for zeroth order stochastic convex optimization that attains the suboptimality rate of $\tilde{\mathcal{O}}(n^{7}T^{-1/2})$ after $T$ queries for a convex bounded function $f:{\mathbb R}^n\to{\mathbb R}$. The method is based on a random walk (the \emph{Ball Walk}) on the epigraph of the function. The randomized approach circumvents the problem of gradient estimation, and appears to be less sensitive to noisy function evaluations compared to noiseless zeroth order methods.
Acoustic Space Learning for Sound Source Separation and Localization on Binaural Manifolds
Venue: arXiv cs.SD 2014
Year: 2014

In this paper we address the problems of modeling the acoustic space generated by a full-spectrum sound source and of using the learned model for the localization and separation of multiple sources that simultaneously emit sparse-spectrum sounds. We lay theoretical and methodological grounds in order to introduce the binaural manifold paradigm. We perform an in-depth study of the latent low-dimensional structure of the high-dimensional interaural spectral data, based on a corpus recorded with a human-like audiomotor robot head. A non-linear dimensionality reduction technique is used to show that these data lie on a two-dimensional (2D) smooth manifold parameterized by the motor states of the listener, or equivalently, the sound source directions. We propose a probabilistic piecewise affine mapping model (PPAM) specifically designed to deal with high-dimensional data exhibiting an intrinsic piecewise linear structure. We derive a closed-form expectation-maximization (EM) procedure for estimating the model parameters, followed by Bayes inversion for obtaining the full posterior density function of a sound source direction. We extend this solution to deal with missing data and redundancy in real world spectrograms, and hence for 2D localization of natural sound sources such as speech. We further generalize the model to the challenging case of multiple sound sources and we propose a variational EM framework. The associated algorithm, referred to as variational EM for source separation and localization (VESSL) yields a Bayesian estimation of the 2D locations and time-frequency masks of all the sources. Comparisons of the proposed approach with several existing methods reveal that the combination of acoustic-space learning with Bayesian inference enables our method to outperform state-of-the-art methods.
Dynamic Partial Sorting
Venue: arXiv cs.DS 2014
Year: 2014

The dynamic partial sorting problem asks for an algorithm that maintains lists of numbers under the link, cut and change value operations, and queries the sorted sequence of the $k$ least numbers in one of the lists. We first solve the problem in $O(k\log (n))$ time for queries and $O(\log (n))$ time for updates using the tournament tree data structure, where $n$ is the number of elements in the lists. We then introduce a layered tournament tree data structure and solve the same problem in $O(\log_φ^* (n) k\log (k))$ time for queries and $O\left(\log (n)\cdot\log^2\log (n)\right)$ for updates, where $φ$ is the golden ratio and $\log_φ^*(n)$ is the iterated logarithmic function with base $φ$.
PR2: A Language Independent Unsupervised Tool for Personality Recognition from Text
Venue: arXiv cs.CL 2014
Year: 2014

We present PR2, a personality recognition system available online, that performs instance-based classification of Big5 personality types from unstructured text, using language-independent features. It has been tested on English and Italian, achieving performances up to f=.68.
Hierarchical Temporal Memory Based on Spin-Neurons and Resistive Memory for Energy-Efficient Brain-Inspired Computing
Venue: arXiv cs.ET 2014
Year: 2014

Hierarchical temporal memory (HTM) tries to mimic the computing in cerebral-neocortex. It identifies spatial and temporal patterns in the input for making inferences. This may require large number of computationally expensive tasks like, dot-product evaluations. Nano-devices that can provide direct mapping for such primitives are of great interest. In this work we show that the computing blocks for HTM can be mapped using low-voltage, fast-switching, magneto-metallic spin-neurons combined with emerging resistive cross-bar network (RCN). Results show possibility of more than 200x lower energy as compared to 45nm CMOS ASIC design
Computing Unique Maximum Matchings in O(m) time for Konig-Egervary Graphs and Unicyclic Graphs
Venue: arXiv cs.DM 2014
Year: 2014

Let alpha(G) denote the maximum size of an independent set of vertices and mu(G) be the cardinality of a maximum matching in a graph G. A matching saturating all the vertices is perfect. If alpha(G) + mu(G) equals the number of vertices of G, then it is called a Konig-Egervary graph. A graph is unicyclic if it has a unique cycle. In 2010, Bartha conjectured that a unique perfect matching, if it exists, can be found in O(m) time, where m is the number of edges. In this paper we validate this conjecture for Konig-Egervary graphs and unicylic graphs. We propose a variation of Karp-Sipser leaf-removal algorithm (Karp and Spiser, 1981), which ends with an empty graph if and only if the original graph is a Konig-Egervary graph with a unique perfect matching obtained as an output as well. We also show that a unicyclic non-bipartite graph G may have at most one perfect matching, and this is the case where G is a Konig-Egervary graph.
EPIC: Efficient prediction of IC manufacturing hotspots with a unified meta-classification formulation
Venue: arXiv cs.AR 2014
Year: 2014

In this paper we present EPIC, an efficient and effective predictor for IC manufacturing hotspots in deep sub-wavelength lithography. EPIC proposes a unified framework to combine different hotspot detection methods together, such as machine learning and pattern matching, using mathematical programming/optimization. EPIC algorithm has been tested on a number of industry benchmarks under advanced manufacturing conditions. It demonstrates so far the best capability in selectively combining the desirable features of various hotspot detection methods (3.5-8.2% accuracy improvement) as well as significant suppression of the detection noise (e.g., 80% false-alarm reduction). These characteristics make EPIC very suitable for conducting high performance physical verification and guiding efficient manufacturability friendly physical design.