OpenRaiser/Intern-Atlas huggingface dataset:
Establishment of Relationships between Material Design and Product Design Domains by Hybrid FEM-ANN Technique
Venue: arXiv cs.AI 2010
Year: 2010

In this paper, research on AI based modeling technique to optimize development of new alloys with necessitated improvements in properties and chemical mixture over existing alloys as per functional requirements of product is done. The current research work novels AI in lieu of predictions to establish association between material and product customary. Advanced computational simulation techniques like CFD, FEA interrogations are made viable to authenticate product dynamics in context to experimental investigations. Accordingly, the current research is focused towards binding relationships between material design and product design domains. The input to feed forward back propagation prediction network model constitutes of material design features. Parameters relevant to product design strategies are furnished as target outputs. The outcomes of ANN shows good sign of correlation between material and product design domains. The study enriches a new path to illustrate material factors at the time of new product development.
Implementation of an Innovative Bio Inspired GA and PSO Algorithm for Controller design considering Steam GT Dynamics
Venue: arXiv cs.NE 2010
Year: 2010

The Application of Bio Inspired Algorithms to complicated Power System Stability Problems has recently attracted the researchers in the field of Artificial Intelligence. Low frequency oscillations after a disturbance in a Power system, if not sufficiently damped, can drive the system unstable. This paper provides a systematic procedure to damp the low frequency oscillations based on Bio Inspired Genetic (GA) and Particle Swarm Optimization (PSO) algorithms. The proposed controller design is based on formulating a System Damping ratio enhancement based Optimization criterion to compute the optimal controller parameters for better stability. The Novel and contrasting feature of this work is the mathematical modeling and simulation of the Synchronous generator model including the Steam Governor Turbine (GT) dynamics. To show the robustness of the proposed controller, Non linear Time domain simulations have been carried out under various system operating conditions. Also, a detailed Comparative study has been done to show the superiority of the Bio inspired algorithm based controllers over the Conventional Lead lag controller.
Framework for Visualizing Model-Driven Software Evolution and its Application
Venue: arXiv cs.SE 2010
Year: 2010

Software Visualization encompasses the development and evaluation of methods for graphically representing different aspects of methods of software, including its structure, execution and evolution. Creating visualizations helps the user to better understand complex phenomena. It is also found by the software engineering community that visualization is essential and important. In order to visualize the evolution of the models in Model-Driven Software Evolution, authors have proposed a framework which consists of 7 key areas (views) and 22 key features for the assessment of Model Driven Software Evolution process and addresses a number of stakeholder concerns. The framework is derived by the application of the Goal Question Metric Paradigm. This paper aims to describe an application of the framework by considering different visualization tools/CASE tools which are used to visualize the models in different views and to capture the information of models during their evolution. Comparison of such tools is also possible by using the framework.
Stochastic Model Based Proxy Servers Architecture for VoD to Achieve Reduced Client Waiting Time
Venue: arXiv cs.MM 2010
Year: 2010

In a video on demand system, the main video repository may be far away from the user and generally has limited streaming capacities. Since a high quality video's size is huge, it requires high bandwidth for streaming over the internet. In order to achieve a higher video hit ratio, reduced client waiting time, distributed server's architecture can be used, in which multiple local servers are placed close to clients and, based on their regional demands video contents are cached dynamically from the main server. As the cost of proxy server is decreasing and demand for reduced waiting time is increasing day by day, newer architectures are explored, innovative schemes are arrived at. In this paper we present novel 3 layer architecture, includes main multimedia server, a Tracker and Proxy servers. This architecture targets to optimize the client waiting time. We also propose an efficient prefix caching and load sharing algorithm at the proxy server to allocate the cache according to regional popularity of the video. The simulation results demonstrate that it achieves significantly lower client's waiting time, when compared to the other existing algorithms.
Reliable Mining of Automatically Generated Test Cases from Software Requirements Specification (SRS)
Venue: arXiv cs.SE 2010
Year: 2010

Writing requirements is a two-way process. In this paper we use to classify Functional Requirements (FR) and Non Functional Requirements (NFR) statements from Software Requirements Specification (SRS) documents. This is systematically transformed into state charts considering all relevant information. The current paper outlines how test cases can be automatically generated from these state charts. The application of the states yields the different test cases as solutions to a planning problem. The test cases can be used for automated or manual software testing on system level. And also the paper presents a method for reduction of test suite by using mining methods thereby facilitating the mining and knowledge extraction from test cases.
Detecting Bots Based on Keylogging Activities
Venue: arXiv cs.CR 2010
Year: 2010

A bot is a piece of software that is usually installed on an infected machine without the user's knowledge. A bot is controlled remotely by the attacker under a Command and Control structure. Recent statistics show that bots represent one of the fastest growing threats to our network by performing malicious activities such as email spamming or keylogging. However, few bot detection techniques have been developed to date. In this paper, we investigate a behavioural algorithm to detect a single bot that uses keylogging activity. Our approach involves the use of function calls analysis for the detection of the bot with a keylogging component. Correlation of the frequency of a specified time-window is performed to enhance he detection scheme. We perform a range of experiments with the spybot. Our results show that there is a high correlation between some function calls executed by this bot which indicates abnormal activity in our system.
Bounds on Threshold of Regular Random $k$-SAT
Venue: arXiv cs.IT 2010
Year: 2010

We consider the regular model of formula generation in conjunctive normal form (CNF) introduced by Boufkhad et. al. We derive an upper bound on the satisfiability threshold and NAE-satisfiability threshold for regular random $k$-SAT for any $k \geq 3$. We show that these bounds matches with the corresponding bound for the uniform model of formula generation. We derive lower bound on the threshold by applying the second moment method to the number of satisfying assignments. For large $k$, we note that the obtained lower bounds on the threshold of a regular random formula converges to the lower bound obtained for the uniform model. Thus, we answer the question posed in \cite{AcM06} regarding the performance of the second moment method for regular random formulas.
Half-Duplex Active Eavesdropping in Fast Fading Channels: A Block-Markov Wyner Secrecy Encoding Scheme
Venue: arXiv cs.IT 2010
Year: 2010

In this paper we study the problem of half-duplex active eavesdropping in fast fading channels. The active eavesdropper is a more powerful adversary than the classical eavesdropper. It can choose between two functional modes: eavesdropping the transmission between the legitimate parties (Ex mode), and jamming it (Jx mode) -- the active eavesdropper cannot function in full duplex mode. We consider a conservative scenario, when the active eavesdropper can choose its strategy based on the legitimate transmitter-receiver pair's strategy -- and thus the transmitter and legitimate receiver have to plan for the worst. We show that conventional physical-layer secrecy approaches perform poorly (if at all), and we introduce a novel encoding scheme, based on very limited and unsecured feedback -- the Block-Markov Wyner (BMW) encoding scheme -- which outperforms any schemes currently available.
New Insights from an Analysis of Social Influence Networks under the Linear Threshold Model
Venue: arXiv cs.OH 2010
Year: 2010

We study the spread of influence in a social network based on the Linear Threshold model. We derive an analytical expression for evaluating the expected size of the eventual influenced set for a given initial set, using the probability of activation for each node in the social network. We then provide an equivalent interpretation for the influence spread, in terms of acyclic path probabilities in the Markov chain obtained by reversing the edges in the social network influence graph. We use some properties of such acyclic path probabilities to provide an alternate proof for the submodularity of the influence function. We illustrate the usefulness of the analytical expression in estimating the most influential set, in special cases such as the UILT(Uniform Influence Linear Threshold), USLT(Uniform Susceptance Linear Threshold) and node-degree based influence models. We show that the PageRank heuristic is either provably optimal or performs very well in the above models, and explore its limitations in more general cases. Finally, based on the insights obtained from the analytical expressions, we provide an efficient algorithm which approximates the greedy algorithm for the influence maximization problem.
A Large-System Analysis of the Imperfect-CSIT Gaussian Broadcast Channel with a DPC-based Transmission Strategy
Venue: arXiv cs.IT 2010
Year: 2010

The Gaussian broadcast channel (GBC) with $K$ transmit antennas and $K$ single-antenna users is considered for the case in which the channel state information is obtained at the transmitter via a finite-rate feedback link of capacity $r$ bits per user. The throughput (i.e., the sum-rate normalized by $K$) of the GBC is analyzed in the limit as $K \to \infty$ with $\frac{r}{K} \to \bar{r}$. Considering the transmission strategy of zeroforcing dirty paper coding (ZFDPC), a closed-form expression for the asymptotic throughput is derived. It is observed that, even under the finite-rate feedback setting, ZFDPC achieves a significantly higher throughput than zeroforcing beamforming. Using the asymptotic throughput expression, the problem of obtaining the number of users to be selected in order to maximize the throughput is solved.
Estimating and Sampling Graphs with Multidimensional Random Walks
Venue: arXiv cs.DS 2010
Year: 2010

Estimating characteristics of large graphs via sampling is a vital part of the study of complex networks. Current sampling methods such as (independent) random vertex and random walks are useful but have drawbacks. Random vertex sampling may require too many resources (time, bandwidth, or money). Random walks, which normally require fewer resources per sample, can suffer from large estimation errors in the presence of disconnected or loosely connected graphs. In this work we propose a new $m$-dimensional random walk that uses $m$ dependent random walkers. We show that the proposed sampling method, which we call Frontier sampling, exhibits all of the nice sampling properties of a regular random walk. At the same time, our simulations over large real world graphs show that, in the presence of disconnected or loosely connected components, Frontier sampling exhibits lower estimation errors than regular random walks. We also show that Frontier sampling is more suitable than random vertex sampling to sample the tail of the degree distribution of the graph.
Position Analysis of the RRP-3(SS) Multi-Loop Spatial Structure
Venue: arXiv cs.RO 2010
Year: 2010

The paper presents the position analysis of a spatial structure composed of two platforms mutually connected by one RRP and three SS serial kinematic chains, where R, P, and S stand for revolute, prismatic, and spherical kinematic pair respectively. A set of three compatibility equations is laid down that, following algebraic elimination, results in a 28th-order univariate algebraic equation, which in turn provides the addressed problem with 28 solutions in the complex domain. Among the applications of the results presented in this paper is the solution to the forward kinematics of the Tricept, a well-known in-parallel-actuated spatial manipulator. Numerical examples show adoption of the proposed method in dealing with two case studies.
The median of the distance between two leaves in a phylogenetic tree
Venue: arXiv cs.DM 2010
Year: 2010

We establish a limit formula for the median of the distance between two leaves in a fully resolved unrooted phylogenetic tree with n leaves. More precisely, we prove that this median is equal, in the limit, to the square root of 4*ln(2)*n.
Recursive tilings and space-filling curves with little fragmentation
Venue: arXiv cs.CG 2010
Year: 2010

This paper defines the Arrwwid number of a recursive tiling (or space-filling curve) as the smallest number w such that any ball Q can be covered by w tiles (or curve sections) with total volume O(vol(Q)). Recursive tilings and space-filling curves with low Arrwwid numbers can be applied to optimise disk, memory or server access patterns when processing sets of points in d-dimensional space. This paper presents recursive tilings and space-filling curves with optimal Arrwwid numbers. For d >= 3, we see that regular cube tilings and space-filling curves cannot have optimal Arrwwid number, and we see how to construct alternatives with better Arrwwid numbers.
Mobility Impact on Performance of Mobile Grids
Venue: arXiv cs.NI 2010
Year: 2010

Wireless mobile grids are one of the emerging grid types, which help to pool the resources of several willing and cooperative mobile devices to resolve a computationally intensive task. The mobile grids exhibit stronger challenges like mobility management of devices, providing transparent access to grid resources, task management and handling of limited resources so that resources are shared efficiently. Task execution on these devices should not be affected by their mobility. The proposed work presents performance evaluation of wireless mobile grid using normal walk mobility model. The normal walk model represents daily motion of users and the direction of motion is mostly symmetric in a real life environment, thus it is effective in location updating of a mobile station and in turn helps task distribution among these available mobile stations. Some of the performance parameters such as Task Execution Time, task failure rate, communication overhead on Brokering Server and Monitoring Cost are discussed.
Assisted Common Information with Applications to Secure Two-Party Computation
Venue: arXiv cs.IT 2010
Year: 2010

Secure multi-party computation is a central problem in modern cryptography. An important sub-class of this are problems of the following form: Alice and Bob desire to produce sample(s) of a pair of jointly distributed random variables. Each party must learn nothing more about the other party's output than what its own output reveals. To aid in this, they have available a set up - correlated random variables whose distribution is different from the desired distribution - as well as unlimited noiseless communication. In this paper we present an upperbound on how efficiently a given set up can be used to produce samples from a desired distribution. The key tool we develop is a generalization of the concept of common information of two dependent random variables [Gacs-Korner, 1973]. Our generalization - a three-dimensional region - remedies some of the limitations of the original definition which captured only a limited form of dependence. It also includes as a special case Wyner's common information [Wyner, 1975]. To derive the cryptographic bounds, we rely on a monotonicity property of this region: the region of the "views" of Alice and Bob engaged in any protocol can only monotonically expand and not shrink. Thus, by comparing the regions for the target random variables and the given random variables, we obtain our upperbound.
Making Sense of the Evolution of a Scientific Domain: A Visual Analytic Study of the Sloan Digital Sky Survey Research
Venue: arXiv cs.GL 2010
Year: 2010

We introduce a new visual analytic approach to the study of scientific discoveries and knowledge diffusion. Our approach enhances contemporary co-citation network analysis by enabling analysts to identify co-citation clusters of cited references intuitively, synthesize thematic contexts in which these clusters are cited, and trace how research focus evolves over time. The new approach integrates and streamlines a few previously isolated techniques such as spectral clustering and feature selection algorithms. The integrative procedure is expected to empower and strengthen analytical and sense making capabilities of scientists, learners, and researchers to understand the dynamics of the evolution of scientific domains in a wide range of scientific fields, science studies, and science policy evaluation and planning. We demonstrate the potential of our approach through a visual analysis of the evolution of astronomical research associated with the Sloan Digital Sky Survey (SDSS) using bibliographic data between 1994 and 2008. In addition, we also demonstrate that the approach can be consistently applied to a set of heterogeneous data sources such as e-prints on arXiv, publications on ADS, and NSF awards related to the same topic of SDSS.
Performance Modeling and Evaluation of Traffic management for Mobile Networks by SINR Prediction
Venue: arXiv cs.NI 2010
Year: 2010

Over the recent years a considerable amount of effort has been devoted towards the performance evaluation and prediction of Mobile Networks. Performance modeling and evaluation of mobile networks are very important in view of their ever expending usage and the multiplicity of their component parts together with the complexity of their functioning. The present paper addresses current issues in traffic management and congestion control by (signal to interference plus noise ratio) SINR prediction congestion control, routing and optimization of cellular mobile networks.
Dire n'est pas concevoir
Venue: arXiv cs.AI 2010
Year: 2010

The conceptual modelling built from text is rarely an ontology. As a matter of fact, such a conceptualization is corpus-dependent and does not offer the main properties we expect from ontology. Furthermore, ontology extracted from text in general does not match ontology defined by expert using a formal language. It is not surprising since ontology is an extra-linguistic conceptualization whereas knowledge extracted from text is the concern of textual linguistics. Incompleteness of text and using rhetorical figures, like ellipsis, modify the perception of the conceptualization we may have. Ontological knowledge, which is necessary for text understanding, is not in general embedded into documents.
Genetic Algorithm Based Optimization of Clustering in Ad Hoc Networks
Venue: arXiv cs.NI 2010
Year: 2010

In this paper, we have to concentrate on implementation of Weighted Clustering Algorithm with the help of Genetic Algorithm (GA).Here we have developed new algorithm for the implementation of GA-based approach with the help of Weighted Clustering Algorithm (WCA) (4). ClusterHead chosen is a important thing for clustering in adhoc networks. So, we have shown the optimization technique for the minimization of ClusterHeads(CH) based on some parameter such as degree difference, Battery power (Pv), degree of mobility, and sum of the distances of a node in adhoc networks. ClusterHeads selection of adhoc networks is an important thing for clustering. Here, we have discussed the performance comparison between deterministic approach and GA based approach. In this performance comparison, we have seen that GA does not always give the good result compare to deterministic WCA algorithm. Here we have seen connectivity (connectivity can be measured by the probability that a node is reachable to any other node.) is better than the deterministic WCA algorithm (4).
Test Case Generation using Mutation Operators and Fault Classification
Venue: arXiv cs.SE 2010
Year: 2010

Software testing is the important phase of software development process. But, this phase can be easily missed by software developers because of their limited time to complete the project. Since, software developers finish their software nearer to the delivery time; they dont get enough time to test their program by creating effective test cases. . One of the major difficulties in software testing is the generation of test cases that satisfy the given adequacy criterion Moreover, creating manual test cases is a tedious work for software developers in the final rush hours. A new approach which generates test cases can help the software developers to create test cases from software specifications in early stage of software development (before coding) and as well as from program execution traces from after software development (after coding). Heuristic techniques can be applied for creating quality test cases. Mutation testing is a technique for testing software units that has great potential for improving the quality of testing, and to assure the high reliability of software. In this paper, a mutation testing based test cases generation technique has been proposed to generate test cases from program execution trace, so that the test cases can be generated after coding. The paper details about the mutation testing implementation to generate test cases. The proposed algorithm has been demonstrated for an example.
An Intelligent System For Effective Forest Fire Detection Using Spatial Data
Venue: arXiv cs.OH 2010
Year: 2010

The explosive growth of spatial data and extensive utilization of spatial databases emphasize the necessity for the automated discovery of spatial knowledge. In modern times, spatial data mining has emerged as an area of voluminous research. Forest fires are a chief environmental concern, causing economical and ecological damage while endangering human lives across the world. The fast or early detection of forest fires is a vital element for controlling such phenomenon. The application of remote sensing is at present a significant method for forest fires monitoring, particularly in vast and remote areas. Different methods have been presented by researchers for forest fire detection. The motivation behind this research is to obtain beneficial information from images in the forest spatial data and use the same in the determination of regions at the risk of fires by utilizing Image Processing and Artificial Intelligence techniques. This paper presents an intelligent system to detect the presence of forest fires in the forest spatial data using Artificial Neural Networks. The digital images in the forest spatial data are converted from RGB to XYZ color space and then segmented by employing anisotropic diffusion to identify the fire regions. Subsequently, Radial Basis Function Neural Network is employed in the design of the intelligent system, which is trained with the color space values of the segmented fire regions. Extensive experimental assessments on publicly available spatial data illustrated the efficiency of the proposed system in effectively detecting forest fires.