Computer Science Algorithms Research Articles

An Efficient Technique for Finding Longest Common Subsequence of DNA Sequences

Molecular biologists rely very heavily on computer science algorithms as research tools. The process of finding the longest common subsequence of two DNA sequences has a wide range of applications in modern bioinformatics. Genetics databases can hold enormous amounts of raw data, for example the human genome consists of approximately three billion DNA base pairs. The processing of this gigantic volume of data necessitates the use of extremely efficient string algorithms. This paper introduces a space and time effective technique for retrieving the longest common subsequence of DNA sequences.

Convex Geometry and its Applications

The geometry of convex domains in Euclidean space plays a central role in several branches of mathematics: functional and harmonic analysis, the theory of PDE, linear programming and, increasingly, in the study of algorithms in computer science. The purpose of this meeting was to bring together researchers from the analytic, geometric and probabilistic groups who have contributed to these developments.

THE VIRTUAL LABORATORY IN THE ANALYSIS OF ALGORITHMS AS DIDACTIC STRATEGY

The objective of the present work was to apply a methodology in the teaching of the Techniques of Design and Analysis of Computational Algorithms, for the construction of optimal algorithms in the solution of problems. The methodology followed in the investigation began with the construction and selection of measurement tools. The subject of the Techniques of Design and Analysis of Computational Algorithms in Computer Science is very important, since they are a tool for the optimal and effective solution in the solution of problems through the design of computer algorithms, being necessary to investigate what ideas students have or preconceived ideas through diagnostic tests. This document first describes the methodology followed and the results obtained when applied through the virtual material implemented with Gowin's UVE and the conceptual maps (MMCC) to achieve significant learning in the topic of algorithm analysis. The data recorded at the beginning, during and at the end of the course were analyzed qualitatively and quantitatively in a comparative manner. This research was carried out in the School of Mechanical and Electrical Engineering of the Culhuacán Unit of the National Polytechnic Institute of Mexico in the course of the analysis of algorithms of the fifth semester of.

The Evolution of an Industrial Sector with a Varying Degree of Roundaboutness of Production

The evolutionary model presented in this paper depicts an industrial sector with a varying degree of economic roundaboutness, i.e., vertical division of labor between producers and users of different types of intermediate products that are ultimately used for the production of a single final product. To include this vertical aspect of industrial dynamics, the model adds the concept of production trees to the evolutionary models of Schumpeterian competition. The specification of this concept suggests the use of the notions of graph theory and the related algorithms of computer science in the treatment of industrial novelty, including structural innovations. Although the model is developed within the Nelson and Winter tradition, the introduction of the Austrian issue of roundaboutness implies a major extension of the research agenda, including production-structure innovations, the emergence and functioning of markets for intermediate products, ways of coping with the instability of upstream markets, the spread of the effects of an upstream innovation, and the measurement of the degree of roundaboutness and of overall productivity. The model reflects a Schumpeterian version of the Boehm-Bawerkian vision of the emergence of increased long-term roundaboutness of production. The Schumpeterian approach implies an innovation- and entrepreneur-driven process of vertical disintegration and reintegration.

Fusing non-conservative kinetic market models and evolutionary computing

This research establishes an identity between kinetic market models of econophysics and evolutionary algorithms of computer science. The fusion between the two approaches motivated a new market model with two basic operations: sampling and selection of states. The result is a non-conservative market that depends on the size of the sample set and the approach used to approximate the principle of energy conservation. This market exhibits complex dynamics with random walks for the sum of all the agents’ money and a scaling behavior for the money distribution in the population. Moreover, the fusion demonstrates how to add an evolutionary context to the kinetic market models and suggests a quasi-equilibrium version of those models. As a by-product, the work reveals a practical application as a new replacement rule for family competition evolutionary algorithms, which outperforms traditional ones in challenging combinatorial optimization problems.

On the Construction of Substitutes

Gross substitutability is a central concept in economics and is connected to important notions in discrete convex analysis, number theory, and the analysis of greedy algorithms in computer science. Many different characterizations are known for this class, but providing a constructive description remains a major open problem. The construction problem asks how to construct all gross substitutes from a class of simpler functions using a set of operations. Because gross substitutes are a natural generalization of matroids to real-valued functions, matroid rank functions form a desirable such class of simpler functions. Shioura proved that a rich class of gross substitutes can be expressed as sums of matroid rank functions, but it is open whether all gross substitutes can be constructed this way. Our main result is a negative answer showing that some gross substitutes cannot be expressed as positive linear combinations of matroid rank functions. En route, we provide necessary and sufficient conditions for the sum to preserve substitutability, uncover a new operation preserving substitutability, and fully describe all substitutes with at most four items.

Sex: The power of randomization

In evolutionary biology, randomness has been perceived as a force that, in and of itself, is capable of inventing: mutation creates new genetic information at random across the genome which leads to phenotypic change, which is then subject to selection. However, in science in general and in computer science in particular, the widespread use of randomness takes a different form. Here, randomization allows for the breaking of pattern, as seen for example in its removal of biases (patterns) by random sampling or random assignment to conditions. Combined with various forms of evaluation, this breaking of pattern becomes an extraordinarily powerful tool, as also seen in many randomized algorithms in computer science. Here we show that this power of randomness is harnessed in nature by sex and recombination. In a finite population, and under the assumption of interactions between genetic variants, sex and recombination allow selection to test how well an allele will perform in a sample of combinations of interacting genetic partners drawn at random from all possible such combinations; consequently, even a small number of tests of genotypes such as takes place in a finite population favors alleles that will most likely perform well in a vast number of yet unrealized genetic combinations. This power of randomization is not manifest in asexual populations.

Knowledge and use of Information Technology in the Diagnosis and Treatment of Diseases by the Ayurvedic Practitioners in Kerala

We are now living in a world where computers are everywhere and are invading our lives in ways we can't even imagine. In this paper study how information and communication technologies (ICT), modern engineering, and computer science techniques, devices, and algorithms can be used in the diagnosis and treatment of diseases by Ayurvedic Practitioners and expand the reach of the wisdom of Ayurveda, the traditional Indian medicine system globally. The Ayurveda and its allied system focus on Universal applicability. So Information and communications technology (ICT) is increasingly being used in management of diagnosis and treatment of diseases by Ayurvedic medical practitioners.

A sample implementation for parallelizing Divide-and-Conquer algorithms on the GPU

The strategy of Divide-and-Conquer (D&C) is one of the frequently used programming patterns to design efficient algorithms in computer science, which has been parallelized on shared memory systems and distributed memory systems. Tzeng and Owens specifically developed a generic paradigm for parallelizing D&C algorithms on modern Graphics Processing Units (GPUs). In this paper, by following the generic paradigm proposed by Tzeng and Owens, we provide a new and publicly available GPU implementation of the famous D&C algorithm, QuickHull, to give a sample and guide for parallelizing D&C algorithms on the GPU. The experimental results demonstrate the practicality of our sample GPU implementation. Our research objective in this paper is to present a sample GPU implementation of a classical D&C algorithm to help interested readers to develop their own efficient GPU implementations with fewer efforts.

Application for AI-OCR Module: Auto Detection of Emails/Letter Images

The purpose of this project is to provide instructions for teaching the Artificial Intelligence topic of supervised machine learning for the task of Optical Character Recognition (OCR) at various levels of a student’s undergraduate curriculum, such as basic knowledge, novice, and intermediate. The levels vary from beginner with a slight background in computing and computer science to intermediate with a better understanding of computer science fundamentals and algorithms.

Convex Geometry and its Applications

The past 30 years have not only seen substantial progress and lively activity in various areas within convex geometry, e.g., in asymptotic geometric analysis, valuation theory, the L_p -Brunn-Minkowski theory and stochastic geometry, but also an increasing amount and variety of applications of convex geometry to other branches of mathematics (and beyond), e.g. to PDEs, statistics, discrete geometry, optimization, or geometric algorithms in computer science. Thus convex geometry is a flourishing and attractive field, which is also reflected by the considerable number of talented young mathematicians at this meeting.

Summation Formulas Involving Binomial Coefficients, Harmonic Numbers, and Generalized Harmonic Numbers

A variety of identities involving harmonic numbers and generalized harmonic numbers have been investigated since the distant past and involved in a wide range of diverse fields such as analysis of algorithms in computer science, various branches of number theory, elementary particle physics, and theoretical physics. Here we show how one can obtain further interesting and (almost) serendipitous identities about certain finite or infinite series involving binomial coefficients, harmonic numbers, and generalized harmonic numbers by simply applying the usual differential operator to well-known Gauss’s summation formula for2F1(1).

Evaluation of computer methods for biomarker discovery on computational grids

Background: Discovering biomarkers is a fundamental step to understand and deal with genetic diseases. Methods using classic Computer Science algorithms have been adapted in order to support processing large biological data sets, aiming to find useful information to understand causing conditions of diseases such as cancer. Results: This paper describes some promising biomarker discovery methods based on several grid architectures. Each technique has some features that make it more suitable for a particular grid architecture. This matching depends on the parallelizing capabilities of the method and the resource availability in each processing/storage node. Conclusion: The study described in this paper analyzed the performance of biomarker discovery methods in different grid architectures. We find that some methods are more suited for certain grid architectures, resulting in significant performance improvement and producing more accurate results.

Convex Geometry and its Applications

The geometry of convex domains in Euclidean space plays a central role in several branches of mathematics: functional and harmonic analysis, the theory of PDE, linear programming and, increasingly, in the study of other algorithms in computer science. High-dimensional geometry is an extremely active area of research: the participation of a considerable number of talented young mathematicians at this meeting is testament to the fact that the field is flourishing.

Finite summation formulas involving binomial coefficients, harmonic numbers and generalized harmonic numbers

A variety of identities involving harmonic numbers and generalized harmonic numbers have been investigated since the distant past and involved in a wide range of diverse fields such as analysis of algorithms in computer science, various branches of number theory, elementary particle physics and theoretical physics. Here we show how one can obtain further interesting identities about certain finite series involving binomial coefficients, harmonic numbers and generalized harmonic numbers by applying the usual differential operator to a known identity. MSC:11M06, 33B15, 33E20, 11M35, 11M41, 40C15.

Soundspace partitioning to increase communication efficiency in bird communities

Birds do not always vocalize at random, but may rather divide up soundspace in such a manner that they avoid overlap with the songs of other bird species. In effect, a high degree of communication efficiency can be achieved by many simultaneously active vocalists that finely integrate songs with minimal overlap. We describe this phenomenon from several recordings at our principal study location, near Volcano, California. The most-studied models for conceptualizing and studying such de-synchronized systems come from scheduling algorithms in computer science, where internet protocols involve packets of information that are broadcast widely; any collisions between them will corrupt the colliding packets so that they need to be resent. We have simulated some of these methods that might be appropriate for the soundspace of bird communities. Some features of these de-synchronized depend on specifics of the algorithms used.

Optimal distributed linear averaging

A new optimal distributed linear averaging (ODLA) problem is presented in this paper. This problem is motivated by the distributed averaging problem which arises in the context of distributed algorithms in computer science and coordination of groups of autonomous agents in engineering. The aim of the ODLA problem is to compute the average of the initial values at nodes of a graph through an optimal distributed algorithm in which the nodes in the graph can only communicate with their neighbors. Optimality is given by a minimization problem of a quadratic cost functional under infinite horizon. We show that this problem has a very close relationship with the notion of semistability. By developing new necessary and sufficient conditions for semistability of linear discrete-time systems, we convert the proposed ODLA problem into an equivalent, constrained optimization problem and then derive a solvable, fixed-structure convex optimization problem.

Gradient-Type Methods: A Unified Perspective in Computer Science and Numerical Analysis

This paper presents a general and comprehensive description of Optimization Methods, and Algorithms from a novel viewpoint. It is shown, in particular, that Direct Methods, Iterative Methods, and Computer Science Algorithms belong to a well-defined general class of both Finite and Infinite Procedures, characterized by suitable descent directions.

Some summation formulas involving harmonic numbers and generalized harmonic numbers

Harmonic numbers and generalized harmonic numbers have been studied since the distant past and are involved in a wide range of diverse fields such as analysis of algorithms in computer science, various branches of number theory, elementary particle physics and theoretical physics. Here we aim at presenting further interesting identities about certain finite or infinite series involving harmonic numbers and generalized harmonic numbers. We also give a brief eclectic review on some known properties associated with the harmonic and generalized harmonic numbers.

Characterizing complex particle morphologies through shape matching: Descriptors, applications, and algorithms

Many standard structural quantities, such as order parameters and correlation functions, exist for common condensed matter systems, such as spherical and rod-like particles. However, these structural quantities are often insufficient for characterizing the unique and highly complex structures often encountered in the emerging field of nano and microscale self-assembly, or other disciplines involving complex structures such as computational biology. Computer science algorithms known as “shape matching” methods pose a unique solution to this problem by providing robust metrics for quantifying the similarity between pairs of arbitrarily complex structures. This pairwise matching operation, either implicitly or explicitly, lies at the heart of most standard structural characterization schemes for particle systems. By substituting more robust “shape descriptors” into these schemes we extend their applicability to structures formed from more complex building blocks. Here, we describe several structural characterization schemes and shape descriptors that can be used to obtain various types of structural information about particle systems. We demonstrate the application of shape matching algorithms to a variety of example problems, for topics including local and global structure identification and classification, automated phase diagram mapping, and the construction of spatial and temporal correlation functions. The methods are applicable to a wide range of systems, both simulated and experimental, provided particle positions are known or can be accurately imaged.