OpenRaiser/Intern-Atlas huggingface dataset:
Optimal Bangla Keyboard Layout using Association Rule of Data Mining
Venue: arXiv cs.AI 2010
Year: 2010

In this paper we present an optimal Bangla Keyboard Layout, which distributes the load equally on both hands so that maximizing the ease and minimizing the effort. Bangla alphabet has a large number of letters, for this it is difficult to type faster using Bangla keyboard. Our proposed keyboard will maximize the speed of operator as they can type with both hands parallel. Here we use the association rule of data mining to distribute the Bangla characters in the keyboard. First, we analyze the frequencies of data consisting of monograph, digraph and trigraph, which are derived from data wire-house, and then used association rule of data mining to distribute the Bangla characters in the layout. Finally, we propose a Bangla Keyboard Layout. Experimental results on several keyboard layout shows the effectiveness of the proposed approach with better performance.
A Unique 10 Segment Display for Bengali Numerals
Venue: arXiv cs.AR 2010
Year: 2010

Segmented display is widely used for efficient display of alphanumeric characters. English numerals are displayed by 7 segment and 16 segment display. The segment size is uniform in this two display architecture. Display architecture using 8, 10, 11, 18 segments have been proposed for Bengali numerals 0...9 yet no display architecture is designed using segments of uniform size and uniform power consumption. In this paper we have proposed a uniform 10 segment architecture for Bengali numerals. This segment architecture uses segments of uniform size and no bent segment is used.
Geoglyphs of Titicaca as an ancient example of graphic design
Venue: arXiv cs.GR 2010
Year: 2010

The paper proposes an ancient landscape design as an example of graphic design for an age and place where no written documents existed. It is created by a network of earthworks, which constitute the remains of an extensive ancient agricultural system. It can be seen by means of the Google satellite imagery on the Peruvian region near the Titicaca Lake, as a texture superimposed to the background landform. In this texture, many drawings (geoglyphs) can be observed.
A Gossip-based optimistic replication for efficient delay-sensitive streaming using an interactive middleware support system
Venue: arXiv cs.DC 2010
Year: 2010

While sharing resources the efficiency is substantially degraded as a result of the scarceness of availability of the requested resources in a multiclient support manner. These resources are often aggravated by many factors like the temporal constraints for availability or node flooding by the requested replicated file chunks. Thus replicated file chunks should be efficiently disseminated in order to enable resource availability on-demand by the mobile users. This work considers a cross layered middleware support system for efficient delay-sensitive streaming by using each device's connectivity and social interactions in a cross layered manner. The collaborative streaming is achieved through the epidemically replicated file chunk policy which uses a transition-based approach of a chained model of an infectious disease with susceptible, infected, recovered and death states. The Gossip-based stateful model enforces the mobile nodes whether to host a file chunk or not or, when no longer a chunk is needed, to purge it. The proposed model is thoroughly evaluated through experimental simulation taking measures for the effective throughput Eff as a function of the packet loss parameter in contrast with the effectiveness of the replication Gossip-based policy.
A Fast Audio Clustering Using Vector Quantization and Second Order Statistics
Venue: arXiv cs.SD 2010
Year: 2010

This paper describes an effective unsupervised speaker indexing approach. We suggest a two stage algorithm to speed-up the state-of-the-art algorithm based on the Bayesian Information Criterion (BIC). In the first stage of the merging process a computationally cheap method based on the vector quantization (VQ) is used. Then in the second stage a more computational expensive technique based on the BIC is applied. In the speaker indexing task a turning parameter or a threshold is used. We suggest an on-line procedure to define the value of a turning parameter without using development data. The results are evaluated using 10 hours of audio data.
Extended Range Profiling in Stepped-Frequency Radar with Sparse Recovery
Venue: arXiv cs.IT 2010
Year: 2010

The newly emerging theory of compressed sensing (CS) enables restoring a sparse signal from inadequate number of linear projections. Based on compressed sensing theory, a new algorithm of high-resolution range profiling for stepped-frequency (SF) radar suffering from missing pulses is proposed. The new algorithm recovers target range profile over multiple coarse-range-bins, providing a wide range profiling capability. MATLAB simulation results are presented to verify the proposed method. Furthermore, we use collected data from real SF radar to generate extended target high-resolution range (HRR) profile. Results are compared with `stretch' based least square method to prove its applicability.
Doubly Exponential Solution for Randomized Load Balancing Models with Markovian Arrival Processes and PH Service Times
Venue: arXiv cs.DM 2010
Year: 2010

In this paper, we provide a novel matrix-analytic approach for studying doubly exponential solutions of randomized load balancing models (also known as supermarket models) with Markovian arrival processes (MAPs) and phase-type (PH) service times. We describe the supermarket model as a system of differential vector equations by means of density dependent jump Markov processes, and obtain a closed-form solution with a doubly exponential structure to the fixed point of the system of differential vector equations. Based on this, we show that the fixed point can be decomposed into the product of two factors inflecting arrival information and service information, and further find that the doubly exponential solution to the fixed point is not always unique for more general supermarket models. Furthermore, we analyze the exponential convergence of the current location of the supermarket model to its fixed point, and apply the Kurtz Theorem to study density dependent jump Markov process given in the supermarket model with MAPs and PH service times, which leads to the Lipschitz condition under which the fraction measure of the supermarket model weakly converges the system of differential vector equations. This paper gains a new understanding of how workload probing can help in load balancing jobs with non-Poisson arrivals and non-exponential service times.
Rotation Invariant Face Detection Using Wavelet, PCA and Radial Basis Function Networks
Venue: arXiv cs.CV 2010
Year: 2010

This paper introduces a novel method for human face detection with its orientation by using wavelet, principle component analysis (PCA) and redial basis networks. The input image is analyzed by two-dimensional wavelet and a two-dimensional stationary wavelet. The common goals concern are the image clearance and simplification, which are parts of de-noising or compression. We applied an effective procedure to reduce the dimension of the input vectors using PCA. Radial Basis Function (RBF) neural network is then used as a function approximation network to detect where either the input image is contained a face or not and if there is a face exists then tell about its orientation. We will show how RBF can perform well then back-propagation algorithm and give some solution for better regularization of the RBF (GRNN) network. Compared with traditional RBF networks, the proposed network demonstrates better capability of approximation to underlying functions, faster learning speed, better size of network, and high robustness to outliers.
Text Classification using Association Rule with a Hybrid Concept of Naive Bayes Classifier and Genetic Algorithm
Venue: arXiv cs.IR 2010
Year: 2010

Text classification is the automated assignment of natural language texts to predefined categories based on their content. Text classification is the primary requirement of text retrieval systems, which retrieve texts in response to a user query, and text understanding systems, which transform text in some way such as producing summaries, answering questions or extracting data. Now a day the demand of text classification is increasing tremendously. Keeping this demand into consideration, new and updated techniques are being developed for the purpose of automated text classification. This paper presents a new algorithm for text classification. Instead of using words, word relation i.e. association rules is used to derive feature set from pre-classified text documents. The concept of Naive Bayes Classifier is then used on derived features and finally a concept of Genetic Algorithm has been added for final classification. A system based on the proposed algorithm has been implemented and tested. The experimental results show that the proposed system works as a successful text classifier.
Smart Bengali Cell Phone Keypad Layout
Venue: arXiv cs.HC 2010
Year: 2010

Nowadays cell phone is the most common communicating used by mass people. SMS based communication is a cheap and popular communication method. It is human tendency to have the opportunity to write SMS in their mother language. Text input in mother language is more flexible when the alphabets of that language are printed on the keypad. Bangla mobile keypad based on phonetics has been proposed earlier. But the keypad is not scientific from frequency and flexibility point of view. Since it is not a feasible solution in this paper we have proposed an efficient Bengali keypad for cell phone and other cellular device. The proposed keypad is based on the frequency of the alphabets in Bengali language and also with the view of structure of human finger movements. We took the two points in count to provide a flexible and fast cell phone keypad.
Completely Enhanced Cell Phone Keypad
Venue: arXiv cs.HC 2010
Year: 2010

The enhanced frequency based keypad is designed to speed up the typing process. This paper will show that the proposed layout will increase the typing speed and be flexible for thumb. Traditional cell phone keypad is not a scientific keypad from the frequency point of view. Approaches have been explored to speed up the typing process. We found that no manufacturer has considered the frequency of the alphabet. The current architecture does not provide flexibility although the users are accustomed to the currently available multi-tapping keypad. Since the currently available keypad layouts are not best suited for users, this paper will suggest a keypad for cell phone and other cellular device based on the frequency of the alphabet in English language and also with the view of structure of human finger movements to provide a flexible and fast cell phone keypad. It also takes into consideration the key jamming problem that was available in typewriter. At first we identified those keys of cell phone, which are easily reachable and create less pressure on the thumb. Thus the key frequency order is calculated from anatomical point of view. In our proposed layout we arranged the alphabet in the frequent keys based on the frequency of the alphabet.
Optimal Bangla Keyboard Layout using Data Mining Technique
Venue: arXiv cs.AI 2010
Year: 2010

This paper presents an optimal Bangla Keyboard Layout, which distributes the load equally on both hands so that maximizing the ease and minimizing the effort. Bangla alphabet has a large number of letters, for this it is difficult to type faster using Bangla keyboard. Our proposed keyboard will maximize the speed of operator as they can type with both hands parallel. Here we use the association rule of data mining to distribute the Bangla characters in the keyboard. First, we analyze the frequencies of data consisting of monograph, digraph and trigraph, which are derived from data wire-house, and then used association rule of data mining to distribute the Bangla characters in the layout. Experimental results on several data show the effectiveness of the proposed approach with better performance.
Rule Extraction using Artificial Neural Networks
Venue: arXiv cs.NE 2010
Year: 2010

Artificial neural networks have been successfully applied to a variety of business application problems involving classification and regression. Although backpropagation neural networks generally predict better than decision trees do for pattern classification problems, they are often regarded as black boxes, i.e., their predictions are not as interpretable as those of decision trees. In many applications, it is desirable to extract knowledge from trained neural networks so that the users can gain a better understanding of the solution. This paper presents an efficient algorithm to extract rules from artificial neural networks. We use two-phase training algorithm for backpropagation learning. In the first phase, the number of hidden nodes of the network is determined automatically in a constructive fashion by adding nodes one after another based on the performance of the network on training data. In the second phase, the number of relevant input units of the network is determined using pruning algorithm. The pruning process attempts to eliminate as many connections as possible from the network. Relevant and irrelevant attributes of the data are distinguished during the training process. Those that are relevant will be kept and others will be automatically discarded. From the simplified networks having small number of connections and nodes we may easily able to extract symbolic rules using the proposed algorithm. Extensive experimental results on several benchmarks problems in neural networks demonstrate the effectiveness of the proposed approach with good generalization ability.
The Complexity of Counting Eulerian Tours in 4-Regular Graphs
Venue: arXiv cs.CC 2010
Year: 2010

We investigate the complexity of counting Eulerian tours ({\sc #ET}) and its variations from two perspectives---the complexity of exact counting and the complexity w.r.t. approximation-preserving reductions (AP-reductions \cite{MR2044886}). We prove that {\sc #ET} is #P-complete even for planar 4-regular graphs. A closely related problem is that of counting A-trails ({\sc #A-trails}) in graphs with rotational embedding schemes (so called maps). Kotzig \cite{MR0248043} showed that {\sc #A-trails} can be computed in polynomial time for 4-regular plane graphs (embedding in the plane is equivalent to giving a rotational embedding scheme). We show that for 4-regular maps the problem is #P-hard. Moreover, we show that from the approximation viewpoint {\sc #A-trails} in 4-regular maps captures the essence of {\sc #ET}, that is, we give an AP-reduction from {\sc #ET} in general graphs to {\sc #A-trails} in 4-regular maps. The reduction uses a fast mixing result for a card shuffling problem \cite{MR2023023}. In order to understand whether #{\sc A-trails} in 4-regular maps can AP-reduce to #{\sc ET} in 4-regular graphs, we investigate a problem in which transitions in vertices are weighted (this generalizes both #{\sc A-trails} and #{\sc ET}). In the 4-regular case we show that {\sc A-trails} can be used to simulate any vertex weights and provide evidence that {\sc ET} can simulate only a limited set of vertex weights.
Modelling Variability for System Families
Venue: arXiv cs.SE 2010
Year: 2010

In this paper, an approach to facilitate the treatment with variabilities in system families is presented by explicitly modelling variants. The proposed method of managing variability consists of a variant part, which models variants and a decision table to depict the customisation decision regarding each variant. We have found that it is easy to implement and has advantage over other methods. We present this model as an integral part of modelling system families.
The complexity of linear-time temporal logic over the class of ordinals
Venue: arXiv cs.LO 2010
Year: 2010

We consider the temporal logic with since and until modalities. This temporal logic is expressively equivalent over the class of ordinals to first-order logic by Kamp's theorem. We show that it has a PSPACE-complete satisfiability problem over the class of ordinals. Among the consequences of our proof, we show that given the code of some countable ordinal alpha and a formula, we can decide in PSPACE whether the formula has a model over alpha. In order to show these results, we introduce a class of simple ordinal automata, as expressive as Büchi ordinal automata. The PSPACE upper bound for the satisfiability problem of the temporal logic is obtained through a reduction to the nonemptiness problem for the simple ordinal automata.
Measuring Similarity of Graphs and their Nodes by Neighbor Matching
Venue: arXiv cs.AI 2010
Year: 2010

The problem of measuring similarity of graphs and their nodes is important in a range of practical problems. There is a number of proposed measures, some of them being based on iterative calculation of similarity between two graphs and the principle that two nodes are as similar as their neighbors are. In our work, we propose one novel method of that sort, with a refined concept of similarity of two nodes that involves matching of their neighbors. We prove convergence of the proposed method and show that it has some additional desirable properties that, to our knowledge, the existing methods lack. We illustrate the method on two specific problems and empirically compare it to other methods.
Testing Closeness of Discrete Distributions
Venue: arXiv cs.DS 2010
Year: 2010

Given samples from two distributions over an $n$-element set, we wish to test whether these distributions are statistically close. We present an algorithm which uses sublinear in $n$, specifically, $O(n^{2/3}ε^{-8/3}\log n)$, independent samples from each distribution, runs in time linear in the sample size, makes no assumptions about the structure of the distributions, and distinguishes the cases when the distance between the distributions is small (less than $\max\{ε^{4/3}n^{-1/3}/32, εn^{-1/2}/4\}$) or large (more than $ε$) in $\ell_1$ distance. This result can be compared to the lower bound of $Ω(n^{2/3}ε^{-2/3})$ for this problem given by Valiant. Our algorithm has applications to the problem of testing whether a given Markov process is rapidly mixing. We present sublinear for several variants of this problem as well.
One-Counter Stochastic Games
Venue: arXiv cs.GT 2010
Year: 2010

We study the computational complexity of basic decision problems for one-counter simple stochastic games (OC-SSGs), under various objectives. OC-SSGs are 2-player turn-based stochastic games played on the transition graph of classic one-counter automata. We study primarily the termination objective, where the goal of one player is to maximize the probability of reaching counter value 0, while the other player wishes to avoid this. Partly motivated by the goal of understanding termination objectives, we also study certain "limit" and "long run average" reward objectives that are closely related to some well-studied objectives for stochastic games with rewards. Examples of problems we address include: does player 1 have a strategy to ensure that the counter eventually hits 0, i.e., terminates, almost surely, regardless of what player 2 does? Or that the liminf (or limsup) counter value equals infinity with a desired probability? Or that the long run average reward is >0 with desired probability? We show that the qualitative termination problem for OC-SSGs is in NP intersection coNP, and is in P-time for 1-player OC-SSGs, or equivalently for one-counter Markov Decision Processes (OC-MDPs). Moreover, we show that quantitative limit problems for OC-SSGs are in NP intersection coNP, and are in P-time for 1-player OC-MDPs. Both qualitative limit problems and qualitative termination problems for OC-SSGs are already at least as hard as Condon's quantitative decision problem for finite-state SSGs.
Approximate Maximum A Posteriori Inference with Entropic Priors
Venue: arXiv cs.SD 2010
Year: 2010

In certain applications it is useful to fit multinomial distributions to observed data with a penalty term that encourages sparsity. For example, in probabilistic latent audio source decomposition one may wish to encode the assumption that only a few latent sources are active at any given time. The standard heuristic of applying an L1 penalty is not an option when fitting the parameters to a multinomial distribution, which are constrained to sum to 1. An alternative is to use a penalty term that encourages low-entropy solutions, which corresponds to maximum a posteriori (MAP) parameter estimation with an entropic prior. The lack of conjugacy between the entropic prior and the multinomial distribution complicates this approach. In this report I propose a simple iterative algorithm for MAP estimation of multinomial distributions with sparsity-inducing entropic priors.
Capacity Results for Relay Channels with Confidential Messages
Venue: arXiv cs.IT 2010
Year: 2010

We consider a communication system where a relay helps transmission of messages from {a} sender to {a} receiver. The relay is considered not only as a helper but as a wire-tapper who can obtain some knowledge about transmitted messages. In this paper we study a relay channel with confidential messages(RCC), where a sender attempts to transmit common information to both a receiver and a relay and also has private information intended for the receiver and confidential to the relay. The level of secrecy of private information confidential to the relay is measured by the equivocation rate, i.e., the entropy rate of private information conditioned on channel outputs at the relay. The performance measure of interest for the RCC is the rate triple that includes the common rate, the private rate, and the equivocation rate as components. The rate-equivocation region is defined by the set that consists of all these achievable rate triples. In this paper we give two definitions of the rate-equivocation region. We first define the rate-equivocation region in the case of deterministic encoder and call it the deterministic rate-equivocation region. Next, we define the rate-equivocation region in the case of stochastic encoder and call it the stochastic rate-equivocation region. We derive explicit inner and outer bounds for the above two regions. On the deterministic/stochastic rate-equivocation region we present two classes of relay channels where inner and outer bounds match. We also evaluate the deterministic and stochastic rate-equivocation regions of the Gaussian RCC.
LRM-Trees: Compressed Indices, Adaptive Sorting, and Compressed Permutations
Venue: arXiv cs.DS 2010
Year: 2010

LRM-Trees are an elegant way to partition a sequence of values into sorted consecutive blocks, and to express the relative position of the first element of each block within a previous block. They were used to encode ordinal trees and to index integer arrays in order to support range minimum queries on them. We describe how they yield many other convenient results in a variety of areas, from data structures to algorithms: some compressed succinct indices for range minimum queries; a new adaptive sorting algorithm; and a compressed succinct data structure for permutations supporting direct and indirect application in time all the shortest as the permutation is compressible.