Search results for: weight comparison algorithm
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 11634

Search results for: weight comparison algorithm

11514 Empirical Study for the Project and the Project Management Dimensions Comparison between SMEs and Large Companies

Authors: Amina Oukennou, Zitouni Beidouri, Otmane Bouksour

Abstract:

Small to Medium-sized enterprises are a very important component of the economy. They are present in the whole industries all over the world. They are considered as the engine for future growth in the economy. Project management is an economical international factor impacting all types of enterprises including the SMEs. This paper has the aim of measuring the weight of using projects and project management in Moroccan SMEs in comparison with the large companies. The study is based on interviews with experts: project managers, managers, directors, and consultants. They were asked questions measuring the weight of using projects, the level of using project management, and the resources employed. Eighteen Moroccan companies from a range of industries and sizes were consulted. All the companies consider projects as a key element in their strategy. Most of them affirm the great usefulness of the approach 'project', especially for the external activities. The main differences lie in the duration and the size of used projects. Despite the commonly shared idea about the importance of the project management, the interviewed persons believe that the project management knowledge has the same importance or less than the technical knowledge. All the companies affirm the need for a simpler version of project management. The content varies from one company to another.

Keywords: project dimension, project management, small to medium-sized entreprise, Morocco

Procedia PDF Downloads 283
11513 Comparison of Crossover Types to Obtain Optimal Queries Using Adaptive Genetic Algorithm

Authors: Wafa’ Alma'Aitah, Khaled Almakadmeh

Abstract:

this study presents an information retrieval system of using genetic algorithm to increase information retrieval efficiency. Using vector space model, information retrieval is based on the similarity measurement between query and documents. Documents with high similarity to query are judge more relevant to the query and should be retrieved first. Using genetic algorithms, each query is represented by a chromosome; these chromosomes are fed into genetic operator process: selection, crossover, and mutation until an optimized query chromosome is obtained for document retrieval. Results show that information retrieval with adaptive crossover probability and single point type crossover and roulette wheel as selection type give the highest recall. The proposed approach is verified using (242) proceedings abstracts collected from the Saudi Arabian national conference.

Keywords: genetic algorithm, information retrieval, optimal queries, crossover

Procedia PDF Downloads 261
11512 Performance Comparison of Different Regression Methods for a Polymerization Process with Adaptive Sampling

Authors: Florin Leon, Silvia Curteanu

Abstract:

Developing complete mechanistic models for polymerization reactors is not easy, because complex reactions occur simultaneously; there is a large number of kinetic parameters involved and sometimes the chemical and physical phenomena for mixtures involving polymers are poorly understood. To overcome these difficulties, empirical models based on sampled data can be used instead, namely regression methods typical of machine learning field. They have the ability to learn the trends of a process without any knowledge about its particular physical and chemical laws. Therefore, they are useful for modeling complex processes, such as the free radical polymerization of methyl methacrylate achieved in a batch bulk process. The goal is to generate accurate predictions of monomer conversion, numerical average molecular weight and gravimetrical average molecular weight. This process is associated with non-linear gel and glass effects. For this purpose, an adaptive sampling technique is presented, which can select more samples around the regions where the values have a higher variation. Several machine learning methods are used for the modeling and their performance is compared: support vector machines, k-nearest neighbor, k-nearest neighbor and random forest, as well as an original algorithm, large margin nearest neighbor regression. The suggested method provides very good results compared to the other well-known regression algorithms.

Keywords: batch bulk methyl methacrylate polymerization, adaptive sampling, machine learning, large margin nearest neighbor regression

Procedia PDF Downloads 270
11511 Impact of Maternal Nutrition on Newborn Anthropometry and Hemoglobin

Authors: Vinay Mishra, Meena Malkani

Abstract:

Objectives: To study the effect of physical maternal nutritional markers (viz. weight, height, gestational weight gain, BMI) and third-trimester haemoglobin concentration on anthropometry and cord blood haemoglobin of their newborn. Methods: Study area: Post-natal ward of a tertiary care hospital in an urban area. Study population: All post-partum women and their newborns. Sample size: 100. Maternal and neonatal data and anthropometric measurements were recorded in semi-structured case proforma. Data analysis: The data obtained was analysed using SPSS 20 software.The comparison between the groups was done using One-Way Analysis of Variance for two groups. For more than two groups comparisons further posthoc analysis was done using Tukey test. Pearson correlation coefficient was used for correlating the variables. A P value less than 0.05 was considered significant. Results: 1. Out of the 100 studied mothers, 52% were anaemic. 2. Cord blood haemoglobin values decreased significantly with the order of birth. 3. Cord blood haemoglobin of normal-weight newborns is significantly higher as compared to that of LBW newborns. 4. Cord blood haemoglobin has strong statistical significance with maternal anaemia. 5. Pre-pregnancy weight and gestational weight gain significantly influence the neonates anthropometry. Conclusions: 1. Birth order has a prominent inverse effect on the cord blood haemoglobin. 2. Majority of the expectant mothers are anaemic and give birth to LBW babies with reduced anthropometric markers. 3. Pre-pregnancy weight, height and gestational weight gain has a very significant impact on the neonatal anthropometry. 4. Thus, maternal nutrition during gestation and during the crucial periods of growth in the pre-child bearing age group has a very significant impact on foetal development.

Keywords: maternal nutrition, anthropometry, cord blood hemoglobin, newborn

Procedia PDF Downloads 365
11510 The Role of Thermo Priming on Improving Seedling Production Technology (ISPT) in Soybean (Glycine max (L.) Merrill) Seed's

Authors: Behzad Sani, Vida Jodaeian

Abstract:

In order to determine the impact of thermo priming on germination of soybean seeds, an experiment was conducted as a completely randomized design with three replications. The factors of studied included different time thermo priming (control, 5 and 10 minutes) through the placing seeds were exposed to oven. The results showed that the effect of thermo priming was significant on germination percentage, seedling dry weight and seedling vigour in P ≤ 0.05. Mean comparison showed that the highest germination percentage (77 %), seedling dry weight (1.39 g) and seedling vigour (107.03) were achieved by 10 minutes thermo priming.

Keywords: thermo priming, seedling, seedling production, seedling growth, soybean

Procedia PDF Downloads 294
11509 ACOPIN: An ACO Algorithm with TSP Approach for Clustering Proteins in Protein Interaction Networks

Authors: Jamaludin Sallim, Rozlina Mohamed, Roslina Abdul Hamid

Abstract:

In this paper, we proposed an Ant Colony Optimization (ACO) algorithm together with Traveling Salesman Problem (TSP) approach to investigate the clustering problem in Protein Interaction Networks (PIN). We named this combination as ACOPIN. The purpose of this work is two-fold. First, to test the efficacy of ACO in clustering PIN and second, to propose the simple generalization of the ACO algorithm that might allow its application in clustering proteins in PIN. We split this paper to three main sections. First, we describe the PIN and clustering proteins in PIN. Second, we discuss the steps involved in each phase of ACO algorithm. Finally, we present some results of the investigation with the clustering patterns.

Keywords: ant colony optimization algorithm, searching algorithm, protein functional module, protein interaction network

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11508 Text Based Shuffling Algorithm on Graphics Processing Unit for Digital Watermarking

Authors: Zayar Phyo, Ei Chaw Htoon

Abstract:

In a New-LSB based Steganography method, the Fisher-Yates algorithm is used to permute an existing array randomly. However, that algorithm performance became slower and occurred memory overflow problem while processing the large dimension of images. Therefore, the Text-Based Shuffling algorithm aimed to select only necessary pixels as hiding characters at the specific position of an image according to the length of the input text. In this paper, the enhanced text-based shuffling algorithm is presented with the powered of GPU to improve more excellent performance. The proposed algorithm employs the OpenCL Aparapi framework, along with XORShift Kernel including the Pseudo-Random Number Generator (PRNG) Kernel. PRNG is applied to produce random numbers inside the kernel of OpenCL. The experiment of the proposed algorithm is carried out by practicing GPU that it can perform faster-processing speed and better efficiency without getting the disruption of unnecessary operating system tasks.

Keywords: LSB based steganography, Fisher-Yates algorithm, text-based shuffling algorithm, OpenCL, XORShiftKernel

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11507 Development of a General Purpose Computer Programme Based on Differential Evolution Algorithm: An Application towards Predicting Elastic Properties of Pavement

Authors: Sai Sankalp Vemavarapu

Abstract:

This paper discusses the application of machine learning in the field of transportation engineering for predicting engineering properties of pavement more accurately and efficiently. Predicting the elastic properties aid us in assessing the current road conditions and taking appropriate measures to avoid any inconvenience to commuters. This improves the longevity and sustainability of the pavement layer while reducing its overall life-cycle cost. As an example, we have implemented differential evolution (DE) in the back-calculation of the elastic modulus of multi-layered pavement. The proposed DE global optimization back-calculation approach is integrated with a forward response model. This approach treats back-calculation as a global optimization problem where the cost function to be minimized is defined as the root mean square error in measured and computed deflections. The optimal solution which is elastic modulus, in this case, is searched for in the solution space by the DE algorithm. The best DE parameter combinations and the most optimum value is predicted so that the results are reproducible whenever the need arises. The algorithm’s performance in varied scenarios was analyzed by changing the input parameters. The prediction was well within the permissible error, establishing the supremacy of DE.

Keywords: cost function, differential evolution, falling weight deflectometer, genetic algorithm, global optimization, metaheuristic algorithm, multilayered pavement, pavement condition assessment, pavement layer moduli back calculation

Procedia PDF Downloads 138
11506 An Algorithm for the Map Labeling Problem with Two Kinds of Priorities

Authors: Noboru Abe, Yoshinori Amai, Toshinori Nakatake, Sumio Masuda, Kazuaki Yamaguchi

Abstract:

We consider the problem of placing labels of the points on a plane. For each point, its position, the size of its label and a priority are given. Moreover, several candidates of its label positions are prespecified, and each of such label positions is assigned a priority. The objective of our problem is to maximize the total sum of priorities of placed labels and their points. By refining a labeling algorithm that can use these priorities, we propose a new heuristic algorithm which is more suitable for treating the assigned priorities.

Keywords: map labeling, greedy algorithm, heuristic algorithm, priority

Procedia PDF Downloads 402
11505 Framework for Detecting External Plagiarism from Monolingual Documents: Use of Shallow NLP and N-Gram Frequency Comparison

Authors: Saugata Bose, Ritambhra Korpal

Abstract:

The internet has increased the copy-paste scenarios amongst students as well as amongst researchers leading to different levels of plagiarized documents. For this reason, much of research is focused on for detecting plagiarism automatically. In this paper, an initiative is discussed where Natural Language Processing (NLP) techniques as well as supervised machine learning algorithms have been combined to detect plagiarized texts. Here, the major emphasis is on to construct a framework which detects external plagiarism from monolingual texts successfully. For successfully detecting the plagiarism, n-gram frequency comparison approach has been implemented to construct the model framework. The framework is based on 120 characteristics which have been extracted during pre-processing the documents using NLP approach. Afterwards, filter metrics has been applied to select most relevant characteristics and then supervised classification learning algorithm has been used to classify the documents in four levels of plagiarism. Confusion matrix was built to estimate the false positives and false negatives. Our plagiarism framework achieved a very high the accuracy score.

Keywords: lexical matching, shallow NLP, supervised machine learning algorithm, word n-gram

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11504 A Hybrid Distributed Algorithm for Multi-Objective Dynamic Flexible Job Shop Scheduling Problem

Authors: Aydin Teymourifar, Gurkan Ozturk

Abstract:

In this paper, a hybrid distributed algorithm has been suggested for multi-objective dynamic flexible job shop scheduling problem. The proposed algorithm is high level, in which several algorithms search the space on different machines simultaneously also it is a hybrid algorithm that takes advantages of the artificial intelligence, evolutionary and optimization methods. Distribution is done at different levels and new approaches are used for design of the algorithm. Apache spark and Hadoop frameworks have been used for the distribution of the algorithm. The Pareto optimality approach is used for solving the multi-objective benchmarks. The suggested algorithm that is able to solve large-size problems in short times has been compared with the successful algorithms of the literature. The results prove high speed and efficiency of the algorithm.

Keywords: distributed algorithms, apache-spark, Hadoop, flexible dynamic job shop scheduling, multi-objective optimization

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11503 Sweepline Algorithm for Voronoi Diagram of Polygonal Sites

Authors: Dmitry A. Koptelov, Leonid M. Mestetskiy

Abstract:

Voronoi Diagram (VD) of finite set of disjoint simple polygons, called sites, is a partition of plane into loci (for each site at the locus) – regions, consisting of points that are closer to a given site than to all other. Set of polygons is a universal model for many applications in engineering, geoinformatics, design, computer vision, and graphics. VD of polygons construction usually done with a reduction to task of constructing VD of segments, for which there are effective O(n log n) algorithms for n segments. Preprocessing – constructing segments from polygons’ sides, and postprocessing – polygon’s loci construction by merging the loci of the sides of each polygon are also included in reduction. This approach doesn’t take into account two specific properties of the resulting segment sites. Firstly, all this segments are connected in pairs in the vertices of the polygons. Secondly, on the one side of each segment lies the interior of the polygon. The polygon is obviously included in its locus. Using this properties in the algorithm for VD construction is a resource to reduce computations. The article proposes an algorithm for the direct construction of VD of polygonal sites. Algorithm is based on sweepline paradigm, allowing to effectively take into account these properties. The solution is performed based on reduction. Preprocessing is the constructing of set of sites from vertices and edges of polygons. Each site has an orientation such that the interior of the polygon lies to the left of it. Proposed algorithm constructs VD for set of oriented sites with sweepline paradigm. Postprocessing is a selecting of edges of this VD formed by the centers of empty circles touching different polygons. Improving the efficiency of the proposed sweepline algorithm in comparison with the general Fortune algorithm is achieved due to the following fundamental solutions: 1. Algorithm constructs only such VD edges, which are on the outside of polygons. Concept of oriented sites allowed to avoid construction of VD edges located inside the polygons. 2. The list of events in sweepline algorithm has a special property: the majority of events are connected with “medium” polygon vertices, where one incident polygon side lies behind the sweepline and the other in front of it. The proposed algorithm processes such events in constant time and not in logarithmic time, as in the general Fortune algorithm. The proposed algorithm is fully implemented and tested on a large number of examples. The high reliability and efficiency of the algorithm is also confirmed by computational experiments with complex sets of several thousand polygons. It should be noted that, despite the considerable time that has passed since the publication of Fortune's algorithm in 1986, a full-scale implementation of this algorithm for an arbitrary set of segment sites has not been made. The proposed algorithm fills this gap for an important special case - a set of sites formed by polygons.

Keywords: voronoi diagram, sweepline, polygon sites, fortunes' algorithm, segment sites

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11502 A Variant of a Double Structure-Preserving QR Algorithm for Symmetric and Hamiltonian Matrices

Authors: Ahmed Salam, Haithem Benkahla

Abstract:

Recently, an efficient backward-stable algorithm for computing eigenvalues and vectors of a symmetric and Hamiltonian matrix has been proposed. The method preserves the symmetric and Hamiltonian structures of the original matrix, during the whole process. In this paper, we revisit the method. We derive a way for implementing the reduction of the matrix to the appropriate condensed form. Then, we construct a novel version of the implicit QR-algorithm for computing the eigenvalues and vectors.

Keywords: block implicit QR algorithm, preservation of a double structure, QR algorithm, symmetric and Hamiltonian structures

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11501 A New Tool for Global Optimization Problems: Cuttlefish Algorithm

Authors: Adel Sabry Eesa, Adnan Mohsin Abdulazeez Brifcani, Zeynep Orman

Abstract:

This paper presents a new meta-heuristic bio-inspired optimization algorithm which is called Cuttlefish Algorithm (CFA). The algorithm mimics the mechanism of color changing behavior of the cuttlefish to solve numerical global optimization problems. The colors and patterns of the cuttlefish are produced by reflected light from three different layers of cells. The proposed algorithm considers mainly two processes: reflection and visibility. Reflection process simulates light reflection mechanism used by these layers, while visibility process simulates visibility of matching patterns of the cuttlefish. To show the effectiveness of the algorithm, it is tested with some other popular bio-inspired optimization algorithms such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO) and Bees Algorithm (BA) that have been previously proposed in the literature. Simulations and obtained results indicate that the proposed CFA is superior when compared with these algorithms.

Keywords: Cuttlefish Algorithm, bio-inspired algorithms, optimization, global optimization problems

Procedia PDF Downloads 532
11500 Using Genetic Algorithms and Rough Set Based Fuzzy K-Modes to Improve Centroid Model Clustering Performance on Categorical Data

Authors: Rishabh Srivastav, Divyam Sharma

Abstract:

We propose an algorithm to cluster categorical data named as ‘Genetic algorithm initialized rough set based fuzzy K-Modes for categorical data’. We propose an amalgamation of the simple K-modes algorithm, the Rough and Fuzzy set based K-modes and the Genetic Algorithm to form a new algorithm,which we hypothesise, will provide better Centroid Model clustering results, than existing standard algorithms. In the proposed algorithm, the initialization and updation of modes is done by the use of genetic algorithms while the membership values are calculated using the rough set and fuzzy logic.

Keywords: categorical data, fuzzy logic, genetic algorithm, K modes clustering, rough sets

Procedia PDF Downloads 212
11499 An Improved Ant Colony Algorithm for Genome Rearrangements

Authors: Essam Al Daoud

Abstract:

Genome rearrangement is an important area in computational biology and bioinformatics. The basic problem in genome rearrangements is to compute the edit distance, i.e., the minimum number of operations needed to transform one genome into another. Unfortunately, unsigned genome rearrangement problem is NP-hard. In this study an improved ant colony optimization algorithm to approximate the edit distance is proposed. The main idea is to convert the unsigned permutation to signed permutation and evaluate the ants by using Kaplan algorithm. Two new operations are added to the standard ant colony algorithm: Replacing the worst ants by re-sampling the ants from a new probability distribution and applying the crossover operations on the best ants. The proposed algorithm is tested and compared with the improved breakpoint reversal sort algorithm by using three datasets. The results indicate that the proposed algorithm achieves better accuracy ratio than the previous methods.

Keywords: ant colony algorithm, edit distance, genome breakpoint, genome rearrangement, reversal sort

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11498 Developing New Algorithm and Its Application on Optimal Control of Pumps in Water Distribution Network

Authors: R. Rajabpour, N. Talebbeydokhti, M. H. Ahmadi

Abstract:

In recent years, new techniques for solving complex problems in engineering are proposed. One of these techniques is JPSO algorithm. With innovative changes in the nature of the jump algorithm JPSO, it is possible to construct a graph-based solution with a new algorithm called G-JPSO. In this paper, a new algorithm to solve the optimal control problem Fletcher-Powell and optimal control of pumps in water distribution network was evaluated. Optimal control of pumps comprise of optimum timetable operation (status on and off) for each of the pumps at the desired time interval. Maximum number of status on and off for each pumps imposed to the objective function as another constraint. To determine the optimal operation of pumps, a model-based optimization-simulation algorithm was developed based on G-JPSO and JPSO algorithms. The proposed algorithm results were compared well with the ant colony algorithm, genetic and JPSO results. This shows the robustness of proposed algorithm in finding near optimum solutions with reasonable computational cost.

Keywords: G-JPSO, operation, optimization, pumping station, water distribution networks

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11497 Support Vector Regression with Weighted Least Absolute Deviations

Authors: Kang-Mo Jung

Abstract:

Least squares support vector machine (LS-SVM) is a penalized regression which considers both fitting and generalization ability of a model. However, the squared loss function is very sensitive to even single outlier. We proposed a weighted absolute deviation loss function for the robustness of the estimates in least absolute deviation support vector machine. The proposed estimates can be obtained by a quadratic programming algorithm. Numerical experiments on simulated datasets show that the proposed algorithm is competitive in view of robustness to outliers.

Keywords: least absolute deviation, quadratic programming, robustness, support vector machine, weight

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11496 Comparison Constructions in the Language of the Qur'an

Authors: Safiah Ahmed Yahya Madkhali

Abstract:

The aim of the present paper is to provide a characterization of the expression of comparison in the language of the Qur’an, the language of the Divine Book of the Muslim nation. It focuses on quantitative as well as qualitative comparisons. While works on comparison constructions in Arabic focus on a type(s) of the comparison construction and exclude another and investigate its behaviour in Standard Arabic, the paper aims to be inclusive of the varied instances that are scalar comparison constructions and describe its aspects in the language of the Qur’an. To the best of my knowledge, comparative constructions in the language of the Qur’an has not been tackled before and hence the characterization provided in the paper would be the contribution of the present work. The paper highlights the several rhetorical features of the construction as present in the different verses in the Qur’an which set them distinct from the ordinary use of the construction in the different verities of the Arabic language.

Keywords: comparison constructions, inequality, comparative, superlative, equality

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11495 Building Bricks Made of Fly-Ash Mixed with Sand or Ceramic Dust: Synthesis and a Comparative Study

Authors: Md. R. Shattique, Md. T. Zaki, Md. G. Kibria

Abstract:

Fly-ash bricks give a comprehensive solution towards recycling of fly-ash and since there is no requirement of firing to produce them, they are also eco-friendly bricks; little or no carbon-dioxide is emitted during their entire production cycle. As bricks are the most essential and widely utilized building materials in the construction industry, the significance of developing an alternate eco-friendly brick is substantial in modern times. In this paper, manufacturing and potential utilization of Fly-ash made building bricks have been studied and was found to be a prospective substitute for fired clay bricks that contribute greatly to polluting the environment. Also, a comparison between sand made and ceramic dust made Fly-ash bricks have been carried out experimentally. The ceramic dust made bricks seem to show higher compressive strength at lower unit volume weight compared to sand made Fly-ash bricks. Moreover, the water absorption capacity of ceramic dust Fly-ash bricks was lower than sand made bricks. Then finally a statistical comparison between fired clay bricks and fly-ash bricks were carried out. All the requirements for good quality building bricks are matched by the fly-ash bricks. All the facts from this study pointed out that these bricks give a new opportunity for being an alternate building material.

Keywords: coal fly-ash, ceramic dust, burnt clay bricks, sand, gypsum, absorption capacity, unit volume weight, compressive strength

Procedia PDF Downloads 389
11494 An Enhanced Harmony Search (ENHS) Algorithm for Solving Optimization Problems

Authors: Talha A. Taj, Talha A. Khan, M. Imran Khalid

Abstract:

Optimization techniques attract researchers to formulate a problem and determine its optimum solution. This paper presents an Enhanced Harmony Search (ENHS) algorithm for solving optimization problems. The proposed algorithm increases the convergence and is more efficient than the standard Harmony Search (HS) algorithm. The paper discusses the novel techniques in detail and also provides the strategy for tuning the decisive parameters that affects the efficiency of the ENHS algorithm. The algorithm is tested on various benchmark functions, a real world optimization problem and a constrained objective function. Also, the results of ENHS are compared to standard HS, and various other optimization algorithms. The ENHS algorithms prove to be significantly better and more efficient than other algorithms. The simulation and testing of the algorithms is performed in MATLAB.

Keywords: optimization, harmony search algorithm, MATLAB, electronic

Procedia PDF Downloads 428
11493 Downscaling Daily Temperature with Neuroevolutionary Algorithm

Authors: Min Shi

Abstract:

State of the art research with Artificial Neural Networks for the downscaling of General Circulation Models (GCMs) mainly uses back-propagation algorithm as a training approach. This paper introduces another training approach of ANNs, Evolutionary Algorithm. The combined algorithm names neuroevolutionary (NE) algorithm. We investigate and evaluate the use of the NE algorithms in statistical downscaling by generating temperature estimates at interior points given information from a lattice of surrounding locations. The results of our experiments indicate that NE algorithms can be efficient alternative downscaling methods for daily temperatures.

Keywords: temperature, downscaling, artificial neural networks, evolutionary algorithms

Procedia PDF Downloads 320
11492 An Experimental Investigation of the Effect of Control Algorithm on the Energy Consumption and Temperature Distribution of a Household Refrigerator

Authors: G. Peker, Tolga N. Aynur, E. Tinar

Abstract:

In order to determine the energy consumption level and cooling characteristics of a domestic refrigerator controlled with various cooling system algorithms, a side by side type (SBS) refrigerator was tested in temperature and humidity controlled chamber conditions. Two different control algorithms; so-called drop-in and frequency controlled variable capacity compressor algorithms, were tested on the same refrigerator. Refrigerator cooling characteristics were investigated for both cases and results were compared with each other. The most important comparison parameters between the two algorithms were taken as; temperature distribution, energy consumption, evaporation and condensation temperatures, and refrigerator run times. Standard energy consumption tests were carried out on the same appliance and resulted in almost the same energy consumption levels, with a difference of %1,5. By using these two different control algorithms, the power consumptions character/profile of the refrigerator was found to be similar. By following the associated energy measurement standard, the temperature values of the test packages were measured to be slightly higher for the frequency controlled algorithm compared to the drop-in algorithm. This paper contains the details of this experimental study conducted with different cooling control algorithms and compares the findings based on the same standard conditions.

Keywords: control algorithm, cooling, energy consumption, refrigerator

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11491 An Optimization Algorithm Based on Dynamic Schema with Dissimilarities and Similarities of Chromosomes

Authors: Radhwan Yousif Sedik Al-Jawadi

Abstract:

Optimization is necessary for finding appropriate solutions to a range of real-life problems. In particular, genetic (or more generally, evolutionary) algorithms have proved very useful in solving many problems for which analytical solutions are not available. In this paper, we present an optimization algorithm called Dynamic Schema with Dissimilarity and Similarity of Chromosomes (DSDSC) which is a variant of the classical genetic algorithm. This approach constructs new chromosomes from a schema and pairs of existing ones by exploring their dissimilarities and similarities. To show the effectiveness of the algorithm, it is tested and compared with the classical GA, on 15 two-dimensional optimization problems taken from literature. We have found that, in most cases, our method is better than the classical genetic algorithm.

Keywords: chromosome injection, dynamic schema, genetic algorithm, similarity and dissimilarity

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11490 Genetic Analysis of Growth Traits in White Boni Sheep under the Central Highlands Region of Yemen

Authors: Abed Al-Bial, S. Alazazie, A. Shami

Abstract:

The data were collected from 1992 to 2009 of White Boni sheep maintained at the Regional Research Station in the Central Highlands of Yemen. Data were analyzed to study the growth related traits and their genetic control. The least square means for body weights were 2.26±0.67, 11.14±0.46 and 19.21±1.25 kg for birth weight (BW), weaning weight (WW), six-month weight (WM6), respectively. The pre- and post-weaning average daily weight gains (ADG1 and ADG2) were 106.04±4.98g and 46.21±8.36 g/ day. Significant differences associated with the year of lambing were observed in body weight and weight gain at different stages of growth. Males were heavier and had a higher weight gain than females at almost all stages of growth and differences tended to increase with age. Single-born lambs had a distinct advantage over those born in twin births at all stages of growth. The lambs in the dam’s second to fourth parities were generally of heavier weight and higher daily weight gain than those in other parities. The heritabilities of all body weights, weight gains at different stages of growth were moderate (0.11-0.43). The phenotypic and genetic correlation among the different body weights were positive and high. The genetic correlations of the pre- and post-weaning average daily gains with body weights were hight to moderate, except BW with ADG2.

Keywords: breed, genetics, growth traits, heritability, sheep

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11489 Role of Zinc in Catch-Up Growth of Low-Birth Weight Neonates

Authors: M. A. Abdel-Wahed, Nayera Elmorsi Hassan, Safaa Shafik Imam, Ola G. El-Farghali, Khadija M. Alian

Abstract:

Low-birth-weight is a challenging public health problem. Aim: to clarify role of zinc on enhancing catch-up growth of low-birth-weight and find out a proposed relationship between zinc effect on growth and the main growth hormone mediator, IGF-1. Methods: Study is a double-blind-randomized-placebo-controlled trial conducted on low-birth-weight-neonates delivered at Ain Shams University Maternity Hospital. It comprised 200 Low-birth-weight-neonates selected from those admitted to NICU. Neonates were randomly allocated into one of the following two groups: group I: low-birth-weight; AGA or SGA on oral zinc therapy at dose of 10 mg/day; group II: Low-birth-weight; AGA or SGA on placebo. Anthropometric measurements were taken including birth weight, length; head, waist, chest, mid-upper arm circumferences, triceps and sub-scapular skin-fold thicknesses. Results: At 12-month-old follow-up visit, mean weight, length; head (HC), waist, chest, mid-upper arm circumferences and triceps; also, infant’s proportions had values ≥ 10th percentile for weight, length and HC were significantly higher among infants of group I when compared to those of group II. Oral zinc therapy was associated with 24.88%, 25.98% and 19.6% higher proportion of values ≥ 10th percentile regarding weight, length and HC at 12-month-old visit, respectively [NNT = 4, 4 and 5, respectively]. Median IGF-1 levels measured at 6 months were significantly higher in group I compared to group II (median (range): 90 (19 – 130) ng/ml vs. 74 (21 – 130) ng/ml, respectively, p=0.023). Conclusion: Oral zinc therapy in low-birth-weight neonates was associated with significantly more catch-up growth at 12-months-old and significantly higher serum IGF-1 at 6-month-old.

Keywords: low-birth-weight, zinc, catch-up growth, neonates

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11488 Modified Active (MA) Algorithm to Generate Semantic Web Related Clustered Hierarchy for Keyword Search

Authors: G. Leena Giri, Archana Mathur, S. H. Manjula, K. R. Venugopal, L. M. Patnaik

Abstract:

Keyword search in XML documents is based on the notion of lowest common ancestors in the labelled trees model of XML documents and has recently gained a lot of research interest in the database community. In this paper, we propose the Modified Active (MA) algorithm which is an improvement over the active clustering algorithm by taking into consideration the entity aspect of the nodes to find the level of the node pertaining to a particular keyword input by the user. A portion of the bibliography database is used to experimentally evaluate the modified active algorithm and results show that it performs better than the active algorithm. Our modification improves the response time of the system and thereby increases the efficiency of the system.

Keywords: keyword matching patterns, MA algorithm, semantic search, knowledge management

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11487 Left to Right-Right Most Parsing Algorithm with Lookahead

Authors: Jamil Ahmed

Abstract:

Left to Right-Right Most (LR) parsing algorithm is a widely used algorithm of syntax analysis. It is contingent on a parsing table, whereas the parsing tables are extracted from the grammar. The parsing table specifies the actions to be taken during parsing. It requires that the parsing table should have no action conflicts for the same input symbol. This requirement imposes a condition on the class of grammars over which the LR algorithms work. However, there are grammars for which the parsing tables hold action conflicts. In such cases, the algorithm needs a capability of scanning (looking-ahead) next input symbols ahead of the current input symbol. In this paper, a ‘Left to Right’-‘Right Most’ parsing algorithm with lookahead capability is introduced. The 'look-ahead' capability in the LR parsing algorithm is the major contribution of this paper. The practicality of the proposed algorithm is substantiated by the parser implementation of the Context Free Grammar (CFG) of an already proposed programming language 'State Controlled Object Oriented Programming' (SCOOP). SCOOP’s Context Free Grammar has 125 productions and 192 item sets. This algorithm parses SCOOP while the grammar requires to ‘look ahead’ the input symbols due to action conflicts in its parsing table. Proposed LR parsing algorithm with lookahead capability can be viewed as an optimization of ‘Simple Left to Right’-‘Right Most’ (SLR) parsing algorithm.

Keywords: left to right-right most parsing, syntax analysis, bottom-up parsing algorithm

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11486 Performance Analysis of Proprietary and Non-Proprietary Tools for Regression Testing Using Genetic Algorithm

Authors: K. Hema Shankari, R. Thirumalaiselvi, N. V. Balasubramanian

Abstract:

The present paper addresses to the research in the area of regression testing with emphasis on automated tools as well as prioritization of test cases. The uniqueness of regression testing and its cyclic nature is pointed out. The difference in approach between industry, with business model as basis, and academia, with focus on data mining, is highlighted. Test Metrics are discussed as a prelude to our formula for prioritization; a case study is further discussed to illustrate this methodology. An industrial case study is also described in the paper, where the number of test cases is so large that they have to be grouped as Test Suites. In such situations, a genetic algorithm proposed by us can be used to reconfigure these Test Suites in each cycle of regression testing. The comparison is made between a proprietary tool and an open source tool using the above-mentioned metrics. Our approach is clarified through several tables.

Keywords: APFD metric, genetic algorithm, regression testing, RFT tool, test case prioritization, selenium tool

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11485 Parallel Version of Reinhard’s Color Transfer Algorithm

Authors: Abhishek Bhardwaj, Manish Kumar Bajpai

Abstract:

An image with its content and schema of colors presents an effective mode of information sharing and processing. By changing its color schema different visions and prospect are discovered by the users. This phenomenon of color transfer is being used by Social media and other channel of entertainment. Reinhard et al’s algorithm was the first one to solve this problem of color transfer. In this paper, we make this algorithm efficient by introducing domain parallelism among different processors. We also comment on the factors that affect the speedup of this problem. In the end by analyzing the experimental data we claim to propose a novel and efficient parallel Reinhard’s algorithm.

Keywords: Reinhard et al’s algorithm, color transferring, parallelism, speedup

Procedia PDF Downloads 583