OpenRaiser/Intern-Atlas huggingface dataset:
Study of Computer Network Issues and Improvising Drop Rate of TCP Packet Using NS-2
Venue: arXiv cs.NI 2014
Year: 2014

As the enormous use of internet increases day by day so as security concern is also raise day by day over the internet. In this paper we discuss the network security and its related threats and also study the types of protocols and few issues related to protocols in computer networks. We also simulate the design of 5 node wired network scenario, its packet drop rate analysis through TCP protocol using NS2 as a simulator. Analyzed the performance of 5-node network when the packet is drop down by graphical method also called as Xgraph when rate parameter is in mb and also analyzed the performance of same network by changing the value of rate parameter at same time so no packets would drop down at same time and also analyzed the performance by Xgraph method.
How to improve the outcome of performance evaluations in terms of percentiles for citation frequencies of my papers
Venue: arXiv cs.DL 2014
Year: 2014

Using empirical data I demonstrate that the result of performance evaluations by percentiles can be drastically influenced by the proper choice of the journal in which a manuscript is published.
Dynamic Integer Sets with Optimal Rank, Select, and Predecessor Search
Venue: arXiv cs.DS 2014
Year: 2014

We present a data structure representing a dynamic set S of w-bit integers on a w-bit word RAM. With |S|=n and w > log n and space O(n), we support the following standard operations in O(log n / log w) time: - insert(x) sets S = S + {x}. - delete(x) sets S = S - {x}. - predecessor(x) returns max{y in S | y< x}. - successor(x) returns min{y in S | y >= x}. - rank(x) returns #{y in S | y< x}. - select(i) returns y in S with rank(y)=i, if any. Our O(log n/log w) bound is optimal for dynamic rank and select, matching a lower bound of Fredman and Saks [STOC'89]. When the word length is large, our time bound is also optimal for dynamic predecessor, matching a static lower bound of Beame and Fich [STOC'99] whenever log n/log w=O(log w/loglog w). Technically, the most interesting aspect of our data structure is that it supports all the above operations in constant time for sets of size n=w^{O(1)}. This resolves a main open problem of Ajtai, Komlos, and Fredman [FOCS'83]. Ajtai et al. presented such a data structure in Yao's abstract cell-probe model with w-bit cells/words, but pointed out that the functions used could not be implemented. As a partial solution to the problem, Fredman and Willard [STOC'90] introduced a fusion node that could handle queries in constant time, but used polynomial time on the updates. We call our small set data structure a dynamic fusion node as it does both queries and updates in constant time.
A Matrix Completion Approach to Linear Index Coding Problem
Venue: arXiv cs.IT 2014
Year: 2014

In this paper, a general algorithm is proposed for rate analysis and code design of linear index coding problems. Specifically a solution for minimum rank matrix completion problem over finite fields representing the linear index coding problem is devised in order to find the optimum transmission rate given vector length and size of the field. The new approach can be applied to both scalar and vector linear index coding.
Fastfood: Approximate Kernel Expansions in Loglinear Time
Venue: arXiv cs.LG 2014
Year: 2014

Despite their successes, what makes kernel methods difficult to use in many large scale problems is the fact that storing and computing the decision function is typically expensive, especially at prediction time. In this paper, we overcome this difficulty by proposing Fastfood, an approximation that accelerates such computation significantly. Key to Fastfood is the observation that Hadamard matrices, when combined with diagonal Gaussian matrices, exhibit properties similar to dense Gaussian random matrices. Yet unlike the latter, Hadamard and diagonal matrices are inexpensive to multiply and store. These two matrices can be used in lieu of Gaussian matrices in Random Kitchen Sinks proposed by Rahimi and Recht (2009) and thereby speeding up the computation for a large range of kernel functions. Specifically, Fastfood requires O(n log d) time and O(n) storage to compute n non-linear basis functions in d dimensions, a significant improvement from O(nd) computation and storage, without sacrificing accuracy. Our method applies to any translation invariant and any dot-product kernel, such as the popular RBF kernels and polynomial kernels. We prove that the approximation is unbiased and has low variance. Experiments show that we achieve similar accuracy to full kernel expansions and Random Kitchen Sinks while being 100x faster and using 1000x less memory. These improvements, especially in terms of memory usage, make kernel methods more practical for applications that have large training sets and/or require real-time prediction.
Human Activity Learning and Segmentation using Partially Hidden Discriminative Models
Venue: arXiv cs.LG 2014
Year: 2014

Learning and understanding the typical patterns in the daily activities and routines of people from low-level sensory data is an important problem in many application domains such as building smart environments, or providing intelligent assistance. Traditional approaches to this problem typically rely on supervised learning and generative models such as the hidden Markov models and its extensions. While activity data can be readily acquired from pervasive sensors, e.g. in smart environments, providing manual labels to support supervised training is often extremely expensive. In this paper, we propose a new approach based on semi-supervised training of partially hidden discriminative models such as the conditional random field (CRF) and the maximum entropy Markov model (MEMM). We show that these models allow us to incorporate both labeled and unlabeled data for learning, and at the same time, provide us with the flexibility and accuracy of the discriminative framework. Our experimental results in the video surveillance domain illustrate that these models can perform better than their generative counterpart, the partially hidden Markov model, even when a substantial amount of labels are unavailable.
Indefinitely Oscillating Martingales
Venue: arXiv cs.LG 2014
Year: 2014

We construct a class of nonnegative martingale processes that oscillate indefinitely with high probability. For these processes, we state a uniform rate of the number of oscillations and show that this rate is asymptotically close to the theoretical upper bound. These bounds on probability and expectation of the number of upcrossings are compared to classical bounds from the martingale literature. We discuss two applications. First, our results imply that the limit of the minimum description length operator may not exist. Second, we give bounds on how often one can change one's belief in a given hypothesis when observing a stream of data.
Energy Efficient (EECP) Clustered Protocol for Heterogeneous Wireless Sensor Network
Venue: arXiv cs.NI 2014
Year: 2014

Energy Conservation and prolonging the life of Wireless Sensor Network is one of the major issues in the wireless sensor network as sensor nodes are highly energy constrained devices. Many routing protocols have been proposed for sensor network, especially cluster based routing protocols. Cluster based routing protocols are best known for its energy efficiency, network stability and for increasing the life time of the sensor network. Low Energy Adaptive Clustering Hierarchy (LEACH) is one of the fundamental protocols in this class. In this research paper we propose a new energy efficient cluster based protocol (EECP) for single hop heterogeneous wireless sensor network to increase the life of a sensor network. Our sensor protocol use the distance of the sensor from the sink as the major issue for the selection of a cluster in the sensor network.
Robustness of the nonlinear PI control method to ignored actuator dynamics
Venue: arXiv cs.SY 2014
Year: 2014

This note examines the robustness properties of the nonlinear PI control method to ignored actuator dynamics. It is proven that global boundedness and regulation can be achieved for sector bounded nonlinear systems with unknown control directions if the actuator dynamics are sufficiently fast and the nonlinear PI control gain is chosen from a subclass of the Nussbaum function class. Simulation examples are also presented that demonstrate the validity of our arguments.
Simulations on Consumer Tests: A Perspective for Driver Assistance Systems
Venue: arXiv cs.SE 2014
Year: 2014

This article discusses new challenges for series development regarding the vehicle safety that arise from the recently published AEB test protocol by the consumer-test-organisation EuroNCAP for driver assistance systems [6]. The tests from the test protocol are of great significance for an OEM that sells millions of cars each year, due to the fact that a positive rating of the vehicle-under-test (VUT) in safety relevant aspects is important for the reputation of a car manufacturer. The further intensification and aggravation of the test requirements for those systems is one of the challenges, that has to be mastered in order to continuously make significant contributions to safety for high-volume cars. Therefore, it is to be shown how a simulation approach may support the development process, especially with tolerance analysis. This article discusses the current stage of work, steps that are planned for the future and results that can be expected at the end of such an analysis.
Utilizing the Active and Collaborative Learning Model in the Introductory Physics Course
Venue: arXiv cs.CY 2014
Year: 2014

Model of active and collaborative learning applied in training specific subject makes clear advantage due to the goals of knowledge, skills that students got to develop successful future job. The author exploits the learning management system of Hanoi National University of Education to establish a learning environment in the Introductory Physics course Part 2, which supports to the blended learning, for the 1st year student. The method of pattern languages is taken to redesign learning content in the framework of ACLM, which focused on analysing real-life application and doing exercises, with the support of information and communication technology. Both formative and summative assessments were used to evaluate competency of students.
Formalising Surveillance and Identity
Venue: arXiv cs.CY 2014
Year: 2014

Surveillance is a social phenomenon that is general and commonplace, employed by governments, companies and communities. Its ubiquity is due to technologies for gathering and processing data; its strong and obvious effects raise difficult social questions. We give a general definition of surveillance that captures the notion in diverse situations and we illustrate it with some disparate examples.A most important, if neglected,component idea is that of the identity of the people or objects observed. We propose a general definition of identifiers as data designed to specify the identity of an entity in some context or for some purpose. We examine the ways identifiers depend upon other identifiers and show the provenance of identifiers requires reductions between identifiers and a special idea of personal identifier. The theory is formalised mathematically. Finally, we reflect on the role of formal methods to give insights in sociological contexts.
Using FLAME Toolkit for Agent-Based Simulation: Case Study Sugarscape Model
Venue: arXiv cs.MA 2014
Year: 2014

Social scientists have used agent-based models to understand how individuals interact and behave in various political, ecological and economic scenarios. Agent-based models are ideal for understanding such models involving interacting individuals producing emergent phenomenon. Sugarscape is one of the most famous examples of a social agent-based model which has been used to show how societies grow in the real world. This paper builds on the Sugarscape model, using the Flexible Large scale Agent-based modelling Environment (FLAME) to simulate three different scenarios of the experiment, which are based on the Sugar and Citizen locations. FLAME is an agent-based modelling framework which has previously been used to model biological and economic models. The paper includes details on how the model was written and the various parameters set for the simulation. The results of the model simulated are processed for three scenarios and analysed to see what affect the initial starting states of the agents had on the overall result obtained through the model and the variance in simulation time of processing the model on multicore architectures. The experiments highlight that there are limitations of the FLAME framework and writing simulation models in general which are highly dependent on initial starting states of a model, also raising further potential work which can be built into the Sugarscape model to study other interesting phenomenon in social and economic laws.
Differential Modulation and Non-Coherent Detection in Wireless Relay Networks
Venue: arXiv cs.IT 2014
Year: 2014

The technique of cooperative communications is finding its way in the next generations of many wireless communication applications. Due to the distributed nature of cooperative networks, acquiring fading channels information for coherent detection is more challenging than in the traditional point-to-point communications. To bypass the requirement of channel information, differential modulation together with non-coherent detection can be deployed. This thesis is concerned with various issues related to differential modulation and non-coherent detection in cooperative networks. Specifically, the thesis examines the behaviour and robustness of non-coherent detection in mobile environments (i.e., time-varying channels). The amount of channel variation is related to the normalized Doppler shift which is a function of user's mobility. The Doppler shift is used to distinguish between slow time-varying (slow-fading) and rapid time-varying (fast-fading) channels. The performance of several important relay topologies, including single-branch and multi-branch dual-hop relaying with/without a direct link that employ amplify-and-forward relaying and two-symbol non-coherent detection, is analyzed. For this purpose, a time-series model is developed for characterizing the time-varying nature of the cascaded channel encountered in amplify-and-forward relaying.
Faster FPT Algorithm for Graph Isomorphism Parameterized by Eigenvalue Multiplicity
Venue: arXiv cs.CC 2014
Year: 2014

We give a $O^*(k^{O(k)})$ time isomorphism testing algorithm for graphs of eigenvalue multiplicity bounded by $k$ which improves on the previous best running time bound of $O^*(2^{O(k^2/\log k)})$.
Digital Image Data Hiding Techniques: A Comparative Study
Venue: arXiv cs.MM 2014
Year: 2014

With the advancements in the field of digital image processing during the last decade, digital image data hiding techniques such as watermarking, Steganography have gained wide popularity. Digital image watermarking techniques hide a small amount of data into a digital image which, later can be retrieved using some specific retrieval algorithms to prove the copyright of a piece of digital information whereas, Steganographic techniques are used to hide a large amount of data secretly into some innocuous looking digital medium. In this paper we are providing an up-to-date review of these data hiding techniques.
Embedding of Large Boolean Functions for Reversible Logic
Venue: arXiv cs.ET 2014
Year: 2014

Reversible logic represents the basis for many emerging technologies and has recently been intensively studied. However, most of the Boolean functions of practical interest are irreversible and must be embedded into a reversible function before they can be synthesized. Thus far, an optimal embedding is guaranteed only for small functions, whereas a significant overhead results when large functions are considered. In this paper, we study this issue. We prove that determining an optimal embedding is coNP-hard already for restricted cases. Then, we propose heuristic and exact methods for determining both the number of additional lines as well as a corresponding embedding. For the approaches we considered sums of products and binary decision diagrams as function representations. Experimental evaluations show the applicability of the approaches for large functions. Consequently, the reversible embedding of large functions is enabled as a precursor to subsequent synthesis.
BCK-algebras arising from block codes
Venue: arXiv cs.IT 2014
Year: 2014

In this paper, we will provide an algorithm which allows us to find a BCK-algebra starting from a given block code.
Application of approximate matrix factorization to high order linearly implicit Runge-Kutta methods
Venue: arXiv cs.NA 2014
Year: 2014

Linearly implicit Runge-Kutta methods with approximate matrix factorization can solve efficiently large systems of differential equations that have a stiff linear part, e.g. reaction-diffusion systems. However, the use of approximate factorization usually leads to loss of accuracy, which makes it attractive only for low order time integration schemes. This paper discusses the application of approximate matrix factorization with high order methods; an inexpensive correction procedure applied to each stage allows to retain the high order of the underlying linearly implicit Runge-Kutta scheme. The accuracy and stability of the methods are studied. Numerical experiments on reaction-diffusion type problems of different sizes and with different degrees of stiffness illustrate the efficiency of the proposed approach.
Conservative constraint satisfaction re-revisited
Venue: arXiv cs.CC 2014
Year: 2014

Conservative constraint satisfaction problems (CSPs) constitute an important particular case of the general CSP, in which the allowed values of each variable can be restricted in an arbitrary way. Problems of this type are well studied for graph homomorphisms. A dichotomy theorem characterizing conservative CSPs solvable in polynomial time and proving that the remaining ones are NP-complete was proved by Bulatov in 2003. Its proof, however, is quite long and technical. A shorter proof of this result based on the absorbing subuniverses technique was suggested by Barto in 2011. In this paper we give a short elementary prove of the dichotomy theorem for the conservative CSP.
FFT Interpolation from Nonuniform Samples Lying in a Regular Grid
Venue: arXiv cs.IT 2014
Year: 2014

This paper presents a method to interpolate a periodic band-limited signal from its samples lying at nonuniform positions in a regular grid, which is based on the FFT and has the same complexity order as this last algorithm. This kind of interpolation is usually termed "the missing samples problem" in the literature, and there exists a wide variety of iterative and direct methods for its solution. The one presented in this paper is a direct method that exploits the properties of the so-called erasure polynomial, and it provides a significant improvement on the most efficient method in the literature, which seems to be the burst error recovery (BER) technique of Marvasti's et al. The numerical stability and complexity of the method are evaluated numerically and compared with the pseudo-inverse and BER solutions.
Unsupervised Keyword Extraction from Polish Legal Texts
Venue: arXiv cs.CL 2014
Year: 2014

In this work, we present an application of the recently proposed unsupervised keyword extraction algorithm RAKE to a corpus of Polish legal texts from the field of public procurement. RAKE is essentially a language and domain independent method. Its only language-specific input is a stoplist containing a set of non-content words. The performance of the method heavily depends on the choice of such a stoplist, which should be domain adopted. Therefore, we complement RAKE algorithm with an automatic approach to selecting non-content words, which is based on the statistical properties of term distribution.
Multi-Sensor Event Detection using Shape Histograms
Venue: arXiv cs.LG 2014
Year: 2014

Vehicular sensor data consists of multiple time-series arising from a number of sensors. Using such multi-sensor data we would like to detect occurrences of specific events that vehicles encounter, e.g., corresponding to particular maneuvers that a vehicle makes or conditions that it encounters. Events are characterized by similar waveform patterns re-appearing within one or more sensors. Further such patterns can be of variable duration. In this work, we propose a method for detecting such events in time-series data using a novel feature descriptor motivated by similar ideas in image processing. We define the shape histogram: a constant dimension descriptor that nevertheless captures patterns of variable duration. We demonstrate the efficacy of using shape histograms as features to detect events in an SVM-based, multi-sensor, supervised learning scenario, i.e., multiple time-series are used to detect an event. We present results on real-life vehicular sensor data and show that our technique performs better than available pattern detection implementations on our data, and that it can also be used to combine features from multiple sensors resulting in better accuracy than using any single sensor. Since previous work on pattern detection in time-series has been in the single series context, we also present results using our technique on multiple standard time-series datasets and show that it is the most versatile in terms of how it ranks compared to other published results.
Analysis of a chaotic spiking neural model: The NDS neuron
Venue: arXiv cs.NE 2014
Year: 2014

Further analysis and experimentation is carried out in this paper for a chaotic dynamic model, viz. the Nonlinear Dynamic State neuron (NDS). The analysis and experimentations are performed to further understand the underlying dynamics of the model and enhance it as well. Chaos provides many interesting properties that can be exploited to achieve computational tasks. Such properties are sensitivity to initial conditions, space filling, control and synchronization.Chaos might play an important role in information processing tasks in human brain as suggested by biologists. If artificial neural networks (ANNs) is equipped with chaos then it will enrich the dynamic behaviours of such networks. The NDS model has some limitations and can be overcome in different ways. In this paper different approaches are followed to push the boundaries of the NDS model in order to enhance it. One way is to study the effects of scaling the parameters of the chaotic equations of the NDS model and study the resulted dynamics. Another way is to study the method that is used in discretization of the original Rössler that the NDS model is based on. These approaches have revealed some facts about the NDS attractor and suggest why such a model can be stabilized to large number of unstable periodic orbits (UPOs) which might correspond to memories in phase space.