OpenRaiser/Intern-Atlas huggingface dataset:
Recognition of Handwritten Textual Annotations using Tesseract Open Source OCR Engine for information Just In Time (iJIT)
Venue: arXiv cs.CV 2010
Year: 2010

Objective of the current work is to develop an Optical Character Recognition (OCR) engine for information Just In Time (iJIT) system that can be used for recognition of handwritten textual annotations of lower case Roman script. Tesseract open source OCR engine under Apache License 2.0 is used to develop user-specific handwriting recognition models, viz., the language sets, for the said system, where each user is identified by a unique identification tag associated with the digital pen. To generate the language set for any user, Tesseract is trained with labeled handwritten data samples of isolated and free-flow texts of Roman script, collected exclusively from that user. The designed system is tested on five different language sets with free- flow handwritten annotations as test samples. The system could successfully segment and subsequently recognize 87.92%, 81.53%, 92.88%, 86.75% and 90.80% handwritten characters in the test samples of five different users.
Development of a Multi-User Recognition Engine for Handwritten Bangla Basic Characters and Digits
Venue: arXiv cs.CV 2010
Year: 2010

The objective of the paper is to recognize handwritten samples of basic Bangla characters using Tesseract open source Optical Character Recognition (OCR) engine under Apache License 2.0. Handwritten data samples containing isolated Bangla basic characters and digits were collected from different users. Tesseract is trained with user-specific data samples of document pages to generate separate user-models representing a unique language-set. Each such language-set recognizes isolated basic Bangla handwritten test samples collected from the designated users. On a three user model, the system is trained with 919, 928 and 648 isolated handwritten character and digit samples and the performance is tested on 1527, 14116 and 1279 character and digit samples, collected form the test datasets of the three users respectively. The user specific character/digit recognition accuracies were obtained as 90.66%, 91.66% and 96.87% respectively. The overall basic character-level and digit level accuracy of the system is observed as 92.15% and 97.37%. The system fails to segment 12.33% characters and 15.96% digits and also erroneously classifies 7.85% characters and 2.63% on the overall dataset.
Faster Approximation Schemes for Fractional Multicommodity Flow Problems via Dynamic Graph Algorithms
Venue: arXiv cs.DS 2010
Year: 2010

We combine the work of Garg and Konemann, and Fleischer with ideas from dynamic graph algorithms to obtain faster (1-eps)-approximation schemes for various versions of the multicommodity flow problem. In particular, if eps is moderately small and the size of every number used in the input instance is polynomially bounded, the running times of our algorithms match - up to poly-logarithmic factors and some provably optimal terms - the Omega(mn) flow-decomposition barrier for single-commodity flow.
Variable Threshold MOSFET Approach (Through Dynamic Threshold MOSFET) For Universal Logic Gates
Venue: arXiv cs.OH 2010
Year: 2010

In this article, we proposed a Variable threshold MOSFET(VTMOS)approach which is realized from Dynamic Threshold MOSFET(DTMOS), suitable for sub-threshold digital circuit operation. Basically the principle of sub- threshold logics is operating MOSFET in sub-threshold region and using the leakage current in that region for switching action, there by drastically decreasing power. To reduce the power consumption of sub-threshold circuits further, a novel body biasing technique termed VTMOS is introduced .VTMOS approach is realized from DTMOS approach. Dynamic threshold MOS (DTMOS) circuits provide low leakage and high current drive, compared to CMOS circuits, operated at lower voltages. The VTMOS is based on operating the MOS devices with an appropriate substrate bias which varies with gate voltage, by connecting a positive bias voltage between gate and substrate for NMOS and negative bias voltage between gate and substrate for PMOS. With VTMOS, there is a considerable reduction in operating current and power dissipation, while the remaining characteristics are almost the same as those of DTMOS. Results of our investigations show that VTMOS circuits improves the power up to 50% when compared to CMOS and DTMOS circuits, in sub- threshold region.. The performance analysis and comparison of VTMOS, DTMOS and CMOS is made and test results of Power dissipation, Propagation delay and Power delay product are presented to justify the superiority of VTMOS logic over conventional sub-threshold logics using Hspice Tool. The dependency of these parameters on frequency of operation has also been investigated.
Expressiveness of Generic Process Shape Types
Venue: arXiv cs.LO 2010
Year: 2010

Shape types are a general concept of process types which work for many process calculi. We extend the previously published Poly* system of shape types to support name restriction. We evaluate the expressiveness of the extended system by showing that shape types are more expressive than an implicitly typed pi-calculus and an explicitly typed Mobile Ambients. We demonstrate that the extended system makes it easier to enjoy advantages of shape types which include polymorphism, principal typings, and a type inference implementation.
Interference in Lattice Networks
Venue: arXiv cs.IT 2010
Year: 2010

Lattices are important as models for the node locations in wireless networks for two main reasons: (1) When network designers have control over the placement of the nodes, they often prefer a regular arrangement in a lattice for coverage and interference reasons. (2) If nodes are randomly distributed or mobile, good channel access schemes ensure that concurrent transmitters are regularly spaced, hence the locations of the transmitting nodes are well approximated by a lattice. In this paper, we introduce general interference bounding techniques that permit the derivation of tight closed-form upper and lower bounds for all lattice networks, and we present and analyze optimum or near-optimum channel access schemes for one-dimensional, square, and triangular lattices.
Precoded Turbo Equalizer for Power Line Communication Systems
Venue: arXiv cs.IT 2010
Year: 2010

Power line communication continues to draw increasing interest by promising a wide range of applications including cost-free last-mile communication solution. However, signal transmitted through the power lines deteriorates badly due to the presence of severe inter-symbol interference (ISI) and harsh random pulse noise. This work proposes a new precoded turbo equalization scheme specifically designed for the PLC channels. By introducing useful precoding to reshape ISI, optimizing maximum {\it a posteriori} (MAP) detection to address the non-Gaussian pulse noise, and performing soft iterative decision refinement, the new equalizer demonstrates a gain significantly better than the existing turbo equalizers.
Gameplay experience in a gaze interaction game
Venue: arXiv cs.HC 2010
Year: 2010

Assessing gameplay experience for gaze interaction games is a challenging task. For this study, a gaze interaction Half-Life 2 game modification was created that allowed eye tracking control. The mod was deployed during an experiment at Dreamhack 2007, where participants had to play with gaze navigation and afterwards rate their gameplay experience. The results show low tension and negative affects scores on the gameplay experience questionnaire as well as high positive challenge, immersion and flow ratings. The correlation between spatial presence and immersion for gaze interaction was high and yields further investigation. It is concluded that gameplay experience can be correctly assessed with the methodology presented in this paper.
Dense Error-Correcting Codes in the Lee Metric
Venue: arXiv cs.IT 2010
Year: 2010

Several new applications and a number of new mathematical techniques have increased the research on error-correcting codes in the Lee metric in the last decade. In this work we consider several coding problems and constructions of error-correcting codes in the Lee metric. First, we consider constructions of dense error-correcting codes in relatively small dimensions over small alphabets. The second problem we solve is construction of diametric perfect codes with minimum distance four. We will construct such codes over various lengths and alphabet sizes. The third problem is to transfer an n-dimensional Lee sphere with large radius into a shape, with the same volume, located in a relatively small box. Hadamard matrices play an essential role in the solutions for all three problems. A construction of codes based on Hadamard matrices will start our discussion. These codes approach the sphere packing bound for very high rate range and appear to be the best known codes over some sets of parameters.
A Faster Routing Scheme for Stationary Wireless Sensor Networks - A Hybrid Approach
Venue: arXiv cs.NI 2010
Year: 2010

A wireless sensor network consists of light-weight, low power, small size sensor nodes. Routing in wireless sensor networks is a demanding task. This demand has led to a number of routing protocols which efficiently utilize the limited resources available at the sensor nodes. Most of these protocols are either based on single hop routing or multi hop routing and typically find the minimum energy path without addressing other issues such as time delay in delivering a packet, load balancing, and redundancy of data. Response time is very critical in environment monitoring sensor networks where typically the sensors are stationary and transmit data to a base station or a sink node. In this paper a faster load balancing routing protocol based on location with a hybrid approach is proposed.
Analysis, Interpretation, and Recognition of Facial Action Units and Expressions Using Neuro-Fuzzy Modeling
Venue: arXiv cs.CV 2010
Year: 2010

In this paper an accurate real-time sequence-based system for representation, recognition, interpretation, and analysis of the facial action units (AUs) and expressions is presented. Our system has the following characteristics: 1) employing adaptive-network-based fuzzy inference systems (ANFIS) and temporal information, we developed a classification scheme based on neuro-fuzzy modeling of the AU intensity, which is robust to intensity variations, 2) using both geometric and appearance-based features, and applying efficient dimension reduction techniques, our system is robust to illumination changes and it can represent the subtle changes as well as temporal information involved in formation of the facial expressions, and 3) by continuous values of intensity and employing top-down hierarchical rule-based classifiers, we can develop accurate human-interpretable AU-to-expression converters. Extensive experiments on Cohn-Kanade database show the superiority of the proposed method, in comparison with support vector machines, hidden Markov models, and neural network classifiers. Keywords: biased discriminant analysis (BDA), classifier design and evaluation, facial action units (AUs), hybrid learning, neuro-fuzzy modeling.
Superior Exploration-Exploitation Balance with Quantum-Inspired Hadamard Walks
Venue: arXiv cs.NE 2010
Year: 2010

This paper extends the analogies employed in the development of quantum-inspired evolutionary algorithms by proposing quantum-inspired Hadamard walks, called QHW. A novel quantum-inspired evolutionary algorithm, called HQEA, for solving combinatorial optimization problems, is also proposed. The novelty of HQEA lies in it's incorporation of QHW Remote Search and QHW Local Search - the quantum equivalents of classical mutation and local search, that this paper defines. The intuitive reasoning behind this approach, and the exploration-exploitation balance thus occurring is explained. From the results of the experiments carried out on the 0,1-knapsack problem, HQEA performs significantly better than a conventional genetic algorithm, CGA, and two quantum-inspired evolutionary algorithms - QEA and NQEA, in terms of convergence speed and accuracy.
Recognizing Combinations of Facial Action Units with Different Intensity Using a Mixture of Hidden Markov Models and Neural Network
Venue: arXiv cs.CV 2010
Year: 2010

Facial Action Coding System consists of 44 action units (AUs) and more than 7000 combinations. Hidden Markov models (HMMs) classifier has been used successfully to recognize facial action units (AUs) and expressions due to its ability to deal with AU dynamics. However, a separate HMM is necessary for each single AU and each AU combination. Since combinations of AU numbering in thousands, a more efficient method will be needed. In this paper an accurate real-time sequence-based system for representation and recognition of facial AUs is presented. Our system has the following characteristics: 1) employing a mixture of HMMs and neural network, we develop a novel accurate classifier, which can deal with AU dynamics, recognize subtle changes, and it is also robust to intensity variations, 2) although we use an HMM for each single AU only, by employing a neural network we can recognize each single and combination AU, and 3) using both geometric and appearance-based features, and applying efficient dimension reduction techniques, our system is robust to illumination changes and it can represent the temporal information involved in formation of the facial expressions. Extensive experiments on Cohn-Kanade database show the superiority of the proposed method, in comparison with other classifiers. Keywords: classifier design and evaluation, data fusion, facial action units (AUs), hidden Markov models (HMMs), neural network (NN).
Using Rough Set and Support Vector Machine for Network Intrusion Detection
Venue: arXiv cs.LG 2010
Year: 2010

The main function of IDS (Intrusion Detection System) is to protect the system, analyze and predict the behaviors of users. Then these behaviors will be considered an attack or a normal behavior. Though IDS has been developed for many years, the large number of return alert messages makes managers maintain system inefficiently. In this paper, we use RST (Rough Set Theory) and SVM (Support Vector Machine) to detect intrusions. First, RST is used to preprocess the data and reduce the dimensions. Next, the features were selected by RST will be sent to SVM model to learn and test respectively. The method is effective to decrease the space density of data. The experiments will compare the results with different methods and show RST and SVM schema could improve the false positive rate and accuracy.
A Comparison between Memetic algorithm and Genetic algorithm for the cryptanalysis of Simplified Data Encryption Standard algorithm
Venue: arXiv cs.CR 2010
Year: 2010

Genetic algorithms are a population-based Meta heuristics. They have been successfully applied to many optimization problems. However, premature convergence is an inherent characteristic of such classical genetic algorithms that makes them incapable of searching numerous solutions of the problem domain. A memetic algorithm is an extension of the traditional genetic algorithm. It uses a local search technique to reduce the likelihood of the premature convergence. The cryptanalysis of simplified data encryption standard can be formulated as NP-Hard combinatorial problem. In this paper, a comparison between memetic algorithm and genetic algorithm were made in order to investigate the performance for the cryptanalysis on simplified data encryption standard problems(SDES). The methods were tested and various experimental results show that memetic algorithm performs better than the genetic algorithms for such type of NP-Hard combinatorial problem. This paper represents our first effort toward efficient memetic algorithm for the cryptanalysis of SDES.
Exact Ramsey Theory: Green-Tao numbers and SAT
Venue: arXiv cs.DM 2010
Year: 2010

We consider the links between Ramsey theory in the integers, based on van der Waerden's theorem, and (boolean, CNF) SAT solving. We aim at using the problems from exact Ramsey theory, concerned with computing Ramsey-type numbers, as a rich source of test problems, where especially methods for solving hard problems can be developed. In order to control the growth of the problem instances, we introduce "transversal extensions" as a natural way of constructing mixed parameter tuples (k_1, ..., k_m) for van-der-Waerden-like numbers N(k_1, ..., k_m), such that the growth of these numbers is guaranteed to be linear. Based on Green-Tao's theorem we introduce the "Green-Tao numbers" grt(k_1, ..., k_m), which in a sense combine the strict structure of van der Waerden problems with the (pseudo-)randomness of the distribution of prime numbers. Using standard SAT solvers (look-ahead, conflict-driven, and local search) we determine the basic values. It turns out that already for this single form of Ramsey-type problems, when considering the best-performing solvers a wide variety of solver types is covered. For m > 2 the problems are non-boolean, and we introduce the "generic translation scheme", which offers an infinite variety of translations ("encodings") and covers the known methods. In most cases the special instance called "nested translation" proved to be far superior.
Scalar-linear Solvability of Matroidal Networks Associated with Representable Matroids
Venue: arXiv cs.IT 2010
Year: 2010

We study matroidal networks introduced by Dougherty et al. We prove the converse of the following theorem: If a network is scalar-linearly solvable over some finite field, then the network is a matroidal network associated with a representable matroid over a finite field. It follows that a network is scalar-linearly solvable if and only if the network is a matroidal network associated with a representable matroid over a finite field. We note that this result combined with the construction method due to Dougherty et al. gives a method for generating scalar-linearly solvable networks. Using the converse implicitly, we demonstrate scalar-linear solvability of two classes of matroidal networks: networks constructed from uniform matroids and those constructed from graphic matroids.
Patrolling a Street Network is Strongly NP-Complete but in P for Tree Structures
Venue: arXiv cs.CG 2010
Year: 2010

We consider the following problem: Given a finite set of straight line segments in the plane, determine the positions of a minimal number of points on the segments, from which guards can see all segments. This problem can be interpreted as looking for a minimal number of locations of policemen, guards, cameras or other sensors, that can observe a network of streets, corridors, tunnels, tubes, etc. We show that the problem is strongly NP-complete even for a set of segments with a cubic graph structure, but in P for tree structures.
Cost-Bandwidth Tradeoff In Distributed Storage Systems
Venue: arXiv cs.IT 2010
Year: 2010

Distributed storage systems are mainly justified due to the limited amount of storage capacity and improving the reliability through distributing data over multiple storage nodes. On the other hand, it may happen the data is stored in unreliable nodes, while it is desired the end user to have a reliable access to the stored data. So, in an event that a node is damaged, to prevent the system reliability to regress, it is necessary to regenerate a new node with the same amount of stored data as the damaged node to retain the number of storage nodes, thereby having the previous reliability. This requires the new node to connect to some of existing nodes and downloads the required information, thereby occupying some bandwidth, called the repair bandwidth. On the other hand, it is more likely the cost of downloading varies across different nodes. This paper aims at investigating the theoretical cost-bandwidth tradeoff, and more importantly, it is demonstrated that any point on this curve can be achieved through the use of the so called generalized regenerating codes which is an enhancement of the regeneration codes introduced by Dimakis et al. in [1].
Energy Efficiency Analysis in Amplify-and-Forward and Decode-and-Forward Cooperative Networks
Venue: arXiv cs.IT 2010
Year: 2010

In this paper, we have studied the energy efficiency of cooperative networks operating in either the fixed Amplifyand- Forward (AF) or the selective Decode-and-Forward (DF) mode. We consider the optimization of the M-ary quadrature amplitude modulation (MQAM) constellation size to minimize the bit energy consumption under given bit error rate (BER) constraints. In the computation of the energy expenditure, the circuit, transmission, and retransmission energies are taken into account. The link reliabilities and retransmission probabilities are determined through the outage probabilities under the Rayleigh fading assumption. Several interesting observations with practical implications are made. It is seen that while large constellations are preferred at small transmission distances, constellation size should be decreased as the distance increases; the cooperative gain is computed to compare direct transmission and cooperative transmission.
Relay Beamforming Strategies for Physical-Layer Security
Venue: arXiv cs.IT 2010
Year: 2010

In this paper, collaborative use of relays to form a beamforming system and provide physical-layer security is investigated. In particular, amplify-and-forward (AF) relay beamforming designs under total and individual relay power constraints are studied with the goal of maximizing the secrecy rates when perfect channel state information (CSI) is available. In the AF scheme, not having analytical solutions for the optimal beamforming design under both total and individual power constraints, an iterative algorithm is proposed to numerically obtain the optimal beamforming structure and maximize the secrecy rates. Robust beamforming designs in the presence of imperfect CSI are investigated for decode-and-forward (DF) based relay beamforming, and optimization frameworks are provided.
QoS Analysis of Cognitive Radio Channels with Perfect CSI at both Receiver and Transmitter
Venue: arXiv cs.IT 2010
Year: 2010

In this paper, cognitive transmission under quality of service (QoS) constraints is studied. In the cognitive radio channel model, it is assumed that both the secondary receiver and the secondary transmitter know the channel fading coefficients perfectly and optimize the power adaptation policy under given constraints, depending on the channel activity of the primary users, which is determined by channel sensing performed by the secondary users. The transmission rates are equal to the instantaneous channel capacity values. A state transition model with four states is constructed to model this cognitive transmission channel. Statistical limitations on the buffer lengths are imposed to take into account the QoS constraints. The maximum throughput under these statistical QoS constraints is identified by finding the effective capacity of the cognitive radio channel. The impact upon the effective capacity of several system parameters, including the channel sensing duration, detection threshold, detection and false alarm probabilities, and QoS parameters, is investigated.