Search results for: multi-objective genetic algorithm

Authors: Soumitr Sanjay Dubey, Shubhajit Roy Chowdhury, Rahul Shrestha

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In this paper, we have presented a novel approach of calculating eigenvalues of any matrix for the first time on Field Programmable Gate Array (FPGA) using Triangular Systolic Arra (TSA) architecture. Conventionally, additional computation unit is required in the architecture which is compliant to the algorithm for determining the eigenvalues and this in return enhances the delay and power consumption. However, recently reported works are only dedicated for symmetric matrices or some specific case of matrix. This works presents an architecture to calculate eigenvalues of any matrix based on QR algorithm which is fully implementable on FPGA. For the implementation of QR algorithm we have used TSA architecture, which is further utilising CORDIC (CO-ordinate Rotation DIgital Computer) algorithm, to calculate various trigonometric and arithmetic functions involved in the procedure. The proposed architecture gives an error in the range of 10−4. Power consumption by the design is 0.598W. It can work at the frequency of 900 MHz.

Keywords: coordinate rotation digital computer, three angle complex rotation, triangular systolic array, QR algorithm

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Authors: Aiman Alshare, Sahar Qaadan

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A curvature dependent force correction algorithm for planning force controlled grinding process with off-line programming flexibility is designed for ABB industrial robot, in order to avoid the manual interface during the process. The machining path utilizes a spline curve fit that is constructed from the CAD data of the workpiece. The fitted spline has a continuity of the second order to assure path smoothness. The implemented algorithm computes uniform forces normal to the grinding surface of the workpiece, by constructing a curvature path in the spatial coordinates using the spline method.

Keywords: ABB industrial robot, grinding process, offline programming, CAD data extraction, force correction algorithm

Procedia PDF Downloads 362

Authors: Abejide Dorcas Ropo, , Falusi Olamide Ahmed, Daudu Oladipupo Abdulazeez Yusuf, Salihu Bolaji Zuluquri Neen, Muhammad Liman Muhammad, Gado Aishatu Adamu

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Water stress is a major factor limiting the productivity of crops in the world today. This study evaluated the morpho-agronomic response of twenty-four (24) Nigerian Bambara groundnut landraces to water stress and genetic diversity of some selected accessions using SSR markers. The studies was carried out in the Botanical garden of the Department of Plant Biology, Federal University of Technology, Minna, Niger State, Nigeria in a randomized complete block design using three replicates. Molecular analysis using SSR primers was carried out at the Centre for Bio- Science, International Institute of Tropical Agriculture (IITA) Ibadan, Nigeria in order to characterize ten selected accessions comprising of the seven most drought tolerant and the three most susceptible accessions detected from the morpho-agronomic studies. Results revealed that water stress decreased morpho-agronomic traits such as plant height, leaf area, number of leaves per plant and seed yield etc. A total of 22 alleles were detected by the SSR markers used with a mean number of 4 allelles. Simple Sequence Repeat (SSR) markers MBamCO33, Primer 65 and G358B2-D15 each detected 4 allelles while Primer 3FR and 4FR detected 5 allelles each. The study revealed significantly high polymorphisms in 10 Loci. The mean value of Polymorpic information content was 0.6997 implying the usefulness of the primers used in identifying genetic similarities and differences among the Bambara groundnut genotypes. The SSR analysis revealed a comparable pattern between genetic diversity and drought tolerance of the genotypes. The Unweighted Paired Group Method with Arithmethic Mean (UPGMA) dendrogram showed that at a genetic distance of 0.1, the accessions were grouped into three groups according to their level of tolerance to drought. The two most drought tolerant accessions were grouped together and the 5th and 6th most drought tolerant accession were also grouped together. This suggests that the genotypes grouped together may be genetically close, may possess similar genes or have a common origin. The degree of genetic variants obtained could be useful in bambara groundnut breeding for drought tolerance. The identified drought tolerant bambara groundnut landraces are important genetic resources for drought stress tolerance breeding programme of bambara groundnut. The genotypes are also useful for germplasm conservation and global implications.

Keywords: bambara groundnut, genetic diversity, germplasm, SSR markers, water stress

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Authors: E. Younsi, H. Andriamboavonjy, A. David, S. Dokou, B. Lemrabet

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Software and time optimization are very important factors in financial markets, which are competitive fields, and emergence of new computer tools further stresses the challenge. In this context, any improvement of technical indicators which generate a buy or sell signal is a major issue. Thus, many tools have been created to make them more effective. This worry about efficiency has been leading in present paper to seek best (and most innovative) way giving largest improvement in these indicators. The approach consists in attaching a signature to frequent market configurations by application of frequent patterns extraction method which is here most appropriate to optimize investment strategies. The goal of proposed trading algorithm is to find most accurate signatures using back testing procedure applied to technical indicators for improving their performance. The problem is then to determine the signatures which, combined with an indicator, outperform this indicator alone. To do this, the FP-Tree algorithm has been preferred, as it appears to be the most efficient algorithm to perform this task.

Keywords: quantitative analysis, back-testing, computational models, apriori algorithm, pattern recognition, data mining, FP-tree

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Authors: Masoud Sheidaei, Mohammad-Reza Kordasti, Fahimeh Koohdar

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Calotropis procera (Aiton) W.T.Aiton, (Apocynaceae), is an economically and medicinally important plant species which is an evergreen, perennial shrub growing in arid and semi-arid climates, and can tolerate very low annual rainfall (150 mm) and a dry season. The plant can also tolerate temperature ran off 20 to30°C and is not frost tolerant. This plant species prefers free-draining sandy soils but can grow also in alkaline and saline soils.It is found at a range of altitudes from exposed coastal sites to medium elevations up to 1300 m. Due to morpho-physiological adaptations of C. procera and its ability to tolerate various abiotic stresses. This taxa can compete with desirable pasture species and forms dense thickets that interfere with stock management, particularly mustering activities. Caloteropis procera grows only in southern part of Iran where in comprises a limited number of geographical populations. We used different population genetics and r landscape analysis to produce data on geographical populations of C. procera based on molecular genetic study using SCoT molecular markers. First, we used spatial principal components (sPCA), as it can analyze data in a reduced space and can be used for co-dominant markers as well as presence / absence data as is the case in SCoT molecular markers. This method also carries out Moran I and Mantel tests to reveal spatial autocorrelation and test for the occurrence of Isolation by distance (IBD). We also performed Random Forest analysis to identify the importance of spatial and geographical variables on genetic diversity. Moreover, we used both RDA (Redundency analysis), and LFMM (Latent factor mixed model), to identify the genetic loci significantly associated with geographical variables. A niche modellng analysis was carried our to predict present potential area for distribution of these plants and also the area present by the year 2050. The results obtained will be discussed in this paper.

Keywords: population genetics, landscape genetic, Calotreropis procera, niche modeling, SCoT markers

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Authors: R. B. Knudsen, O. T. Rasmussen, R. A. Alphinas

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The reason for conducting this research is to develop an algorithm that is capable of classifying news articles from the automobile industry, according to the competitive actions that they entail, with the use of Text Mining (TM) methods. It is needed to test how to properly preprocess the data for this research by preparing pipelines which fits each algorithm the best. The pipelines are tested along with nine different classification algorithms in the realm of regression, support vector machines, and neural networks. Preliminary testing for identifying the optimal pipelines and algorithms resulted in the selection of two algorithms with two different pipelines. The two algorithms are Logistic Regression (LR) and Artificial Neural Network (ANN). These algorithms are optimized further, where several parameters of each algorithm are tested. The best result is achieved with the ANN. The final model yields an accuracy of 0.79, a precision of 0.80, a recall of 0.78, and an F1 score of 0.76. By removing three of the classes that created noise, the final algorithm is capable of reaching an accuracy of 94%.

Keywords: Artificial Neural network, Competitive dynamics, Logistic Regression, Text classification, Text mining

Procedia PDF Downloads 121

Authors: Amanda J. Burridge, Keith J. Edwards, Paul A. Wilkinson, Tom Batstone, Erik H. Murchie, Lorna McAusland, Ana Elizabete Carmo-Silva, Ivan Jauregui, Tracy Lawson, Silvere R. M. Vialet-Chabrand

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The rate of genetic progress in wheat production must be improved to meet global food security targets. However, past selection for domestication traits has reduced the genetic variation in modern wheat cultivars, a fact that could severely limit the future rate of genetic gain. The genetic variation in agronomically important traits for the wild relatives and progenitors of wheat is far greater than that of the current domesticated cultivars, but transferring these traits into modern cultivars is not straightforward. Between the elite cultivars of wheat, photosynthetic capacity is a key trait for which there is limited variation. Early screening of wheat wild relative and progenitors has shown differences in photosynthetic capacity and efficiency not only between wild relative species but marked differences between the accessions of each species. By identifying wild relative accessions with improved photosynthetic traits and characterising the genetic variation responsible, it is possible to incorporate these traits into advanced breeding programmes by wide crossing and introgression programmes. To identify the potential variety of photosynthetic capacity and efficiency available in the secondary and tertiary genepool, a wide scale survey was carried out for over 600 accessions from 80 species including those from the genus Aegilops, Triticum, Thinopyrum, Elymus, and Secale. Genotype data were generated for each accession using a ‘Wheat Wild Relative’ Single Nucleotide Polymorphism (SNP) genotyping array composed of 35,000 SNP markers polymorphic between wild relatives and elite hexaploid wheat. This genotype data was combined with phenotypic measurements such as gas exchange (CO₂, H₂O), chlorophyll fluorescence, growth, morphology, and RuBisCO activity to identify potential breeding material with enhanced photosynthetic capacity and efficiency. The data and associated analysis tools presented here will prove useful to anyone interested in increasing the genetic diversity in hexaploid wheat or the application of complex genotyping data to plant breeding.

Keywords: wheat, wild relatives, pre-breeding, genomics, photosynthesis

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Authors: Chieh-Chun Chang, Cheng-Ting Shih, Yan-Lin Liu, Shu-Jun Chang, Jay Wu

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With the widespread use of digital mammography (DM), radiation dose evaluation of breasts has become important. X-ray spectra are one of the key factors that influence the absorbed dose of glandular tissue. In this study, we estimated the X-ray spectrum of DM using the expectation maximization (EM) algorithm with the transmission measurement data. The interpolating polynomial model proposed by Boone was applied to generate the initial guess of the DM spectrum with the target/filter combination of Mo/Mo and the tube voltage of 26 kVp. The Monte Carlo N-particle code (MCNP5) was used to tally the transmission data through aluminum sheets of 0.2 to 3 mm. The X-ray spectrum was reconstructed by using the EM algorithm iteratively. The influence of the initial guess for EM reconstruction was evaluated. The percentage error of the average energy between the reference spectrum inputted for Monte Carlo simulation and the spectrum estimated by the EM algorithm was -0.14%. The normalized root mean square error (NRMSE) and the normalized root max square error (NRMaSE) between both spectra were 0.6% and 2.3%, respectively. We conclude that the EM algorithm with transmission measurement data is a convenient and useful tool for estimating x-ray spectra for DM in clinical practice.

Keywords: digital mammography, expectation maximization algorithm, X-Ray spectrum, X-Ray

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Authors: P. M. Sreekanth

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Teak (Tectona grandis L. f.) is a tree species indigenous to India and other Southeastern countries. It produces high-value timber and is easily established in plantations. Reforestation requires a constant supply of high quality seeds. Seed Production Areas (SPA) of teak are improved stands used for collection of open-pollinated quality seeds in large quantities. Information on the genetic diversity of major teak SPAs in India is scanty. The genetic structure of four important seed production areas of Kerala State in Southern India was analyzed employing amplified fragment length polymorphism markers using ten selective primer combinations on 80 samples (4 populations X 20 trees). The study revealed that the gene diversity of the SPAs varied from 0.169 (Konni SPA) to 0.203 (Wayanad SPA). The percentage of polymorphic loci ranged from 74.42 (Parambikulam SPA) to 84.06 (Konni SPA). The mean total gene diversity index (HT) of all the four SPAs was 0.2296 ±0.02. A high proportion of genetic diversity was observed within the populations (83%) while diversity between populations was lower (17%) (GST = 0.17). Principal coordinate analysis and STRUCTURE analysis of the genotypes indicated that the pattern of clustering was in accordance with the origin and geographic location of SPAs, indicating specific identity of each population. A UPGMA dendrogram was prepared and showed that all the twenty samples from each of Konni and Parambikulam SPAs clustered into two separate groups, respectively. However, five Nilambur genotypes and one Wayanad genotype intruded into the Konni cluster. The higher gene flow estimated (Nm = 2.4) reflected the inclusion of Konni origin planting stock in the Nilambur and Wayanad plantations. Evidence for population structure investigated using 3D Principal Coordinate Analysis of FAMD software 1.30 indicated that the pattern of clustering was in accordance with the origin of SPAs. The present study showed that assessment of genetic diversity in seed production plantations can be achieved using AFLP markers. The AFLP fingerprinting was also capable of identifying the geographical origin of planting stock and there by revealing the occurrence of the errors in genotype labeling. Molecular marker-based selective culling of genetically similar trees from a stand so as to increase the genetic base of seed production areas could be a new proposition to improve quality of seeds required for raising commercial plantations of teak. The technique can also be used to assess the genetic diversity status of plus trees within provenances during their selection for raising clonal seed orchards for assuring the quality of seeds available for raising future plantations.

Keywords: AFLP, genetic structure, spa, teak

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Authors: Heng Chia Ying, Charmaine Tan Chai Nie, Burra Venkata Durga Kumar

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Process scheduling is the method of process management that determines which process the CPU will proceed with for the next task and how long it takes. Some issues were found in process management, particularly for Priority Scheduling (PS) and Round Robin Scheduling (RR). The proposed recommendations made for IPRRS are to combine the strengths of both into a combining algorithm while they draw on others to compensate for each weakness. A significant improvement on the combining technique of scheduler, Incorporating Priority Round-Robin Scheduler (IPRRS) address an algorithm for both high and low priority task to sustain the indefinite blocking issue faced in the priority scheduling algorithm and minimize the average turnaround time (ATT) and average waiting time (AWT) in RR scheduling algorithm. This paper will delve into the simple rules introduced by IPRRS and enhancements that both PS and RR bring to the execution of processes in the operating system. Furthermore, it incorporates the best aspects of each algorithm to build the optimum algorithm for a certain case in terms of prioritized processes, ATT, and AWT.

Keywords: round Robin scheduling, priority scheduling, indefinite blocking, process management, sustain, turnaround time

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Authors: Semeh Ben Salem, Sami Naouali, Moetez Sallami

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The increasing amount of collected data has limited the performance of the current analyzing algorithms. Thus, developing new cost-effective algorithms in terms of complexity, scalability, and accuracy raised significant interests. In this paper, a modified effective k-means based algorithm is developed and experimented. The new algorithm aims to reduce the computational load without significantly affecting the quality of the clusterings. The algorithm uses the City Block distance and a new stop criterion to guarantee the convergence. Conducted experiments on a real data set show its high performance when compared with the original k-means version.

Keywords: pattern recognition, global terrorism database, Manhattan distance, k-means clustering, terrorism data analysis

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Authors: Micheale Yifter Weldemichael

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Sesame (Sesamum indicum L.) is among the most important oilseed crops for its high edible oil quality and quantity. Sesame is grown for food, medicinal, pharmaceutical, and industrial uses. Sesame is also cultivated as a main cash crop in Asia and Africa by smallholder farmers. Despite the global exponential increase in sesame cultivation area, its production and productivity remain low, mainly due to biotic and abiotic constraints. Notwithstanding the efforts to solve these problems, a low level of genetic variation and inadequate genomic resources hinder the progress of sesame improvement. The objective of this paper is, therefore, to review recent advances in the area of molecular breeding and transformation to overcome major production constraints and could result in enhanced and sustained sesame production. This paper reviews various researches conducted to date on molecular breeding and genetic transformation in sesame focusing on molecular markers used in assessing the available online database resources, genes responsible for key agronomic traits as well as transgenic technology and genome editing. The review concentrates on quantitative and semi-quantitative studies on molecular breeding for key agronomic traits such as improvement of yield components, oil and oil-related traits, disease and insect/pest resistance, and drought, waterlogging and salt tolerance, as well as sesame genetic transformation and genome editing techniques. Pitfalls and limitations of existing studies and methodologies used so far are identified and some priorities for future research directions in sesame genetic improvement are identified in this review.

Keywords: abiotic stress, biotic stress, improvement, molecular breeding, oil, sesame, shattering

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Authors: Sven Tackenberg, Sönke Duckwitz, Andreas Petz, Christopher M. Schlick

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This paper introduces an extension to the well-established Resource-Constrained Project Scheduling Problem (RCPSP) to apply it to complex maintenance problems. The problem is to assign technicians to a team which has to process several tasks with multi-level skill requirements during a work shift. Here, several alternative activities for a task allow both, the temporal shift of activities or the reallocation of technicians and tools. As a result, switches from one valid work process variant to another can be considered and may be selected by the developed evolutionary algorithm based on the present skill level of technicians or the available tools. An additional complication of the observed scheduling problem is that the locations of the construction sites are only temporarily accessible during a day. Due to intensive rail traffic, the available time slots for maintenance and repair works are extremely short and are often distributed throughout the day. To identify efficient working periods, a first concept of a Bayesian network is introduced and is integrated into the extended RCPSP with pre-emptive and non-pre-emptive tasks. Thereby, the Bayesian network is used to calculate the probability of a maintenance task to be processed during a specific period of the shift. Focusing on the domain of maintenance of the railway infrastructure in metropolitan areas as the most unproductive implementation process at construction site, the paper illustrates how the extended RCPSP can be applied for maintenance planning support. A multi-criteria evolutionary algorithm with a problem representation is introduced which is capable of revising technician-task allocations, whereas the duration of the task may be stochastic. The approach uses a novel activity list representation to ensure easily describable and modifiable elements which can be converted into detailed shift schedules. Thereby, the main objective is to develop a shift plan which maximizes the utilization of each technician due to a minimization of the waiting times caused by rail traffic. The results of the already implemented core algorithm illustrate a fast convergence towards an optimal team composition for a shift, an efficient sequence of tasks and a high probability of the subsequent implementation due to the stochastic durations of the tasks. In the paper, the algorithm for the extended RCPSP is analyzed in experimental evaluation using real-world example problems with various size, resource complexity, tightness and so forth.

Keywords: maintenance management, scheduling, resource constrained project scheduling problem, genetic algorithms

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Authors: Sonia Bedhiaf-Romdhani

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The sheep (Ovis aries) was domesticated, approximately 11,000 years ago (YBP), in the Fertile Crescent from Asian Mouflon (Ovis Orientalis). The Northern African (NA) sheep is 7,000 years old, represents a remarkable diversity of sheep populations reared under traditional and low input farming systems (LIFS) over millennia. The majority of small ruminants in developing countries are encountered in low input production systems and the resilience of local communities in rural areas is often linked to the wellbeing of small ruminants. Regardless of the rich biodiversity encountered in sheep ecotypes there are four main sheep breeds in the country with 61,6 and 35.4 percents of Barbarine (fat tail breed) and Queue Fine de l’Ouest (thin tail breed), respectively. Phoenicians introduced the Barbarine sheep from the steppes of Central Asia in the Carthaginian period, 3000 years ago. The Queue Fine de l’Ouest is a thin-tailed meat breed heavily concentrated in the Western and the central semi-arid regions. The Noire de Thibar breed, involving mutton-fine wool producing animals, has been on the verge of extinction, it’s a composite black coated sheep breed found in the northern sub-humid region because of its higher nutritional requirements and non-tolerance of the prevailing harsher condition. The D'Man breed, originated from Morocco, is mainly located in the southern oases of the extreme arid ecosystem. A genetic investigation of Tunisian sheep breeds using a genome-wide scan of approximately 50,000 SNPs was performed. Genetic analysis of relationship between breeds highlighted the genetic differentiation of Noire de Thibar breed from the other local breeds, reflecting the effect of past events of introgression of European gene pool. The Queue Fine de l’Ouest breed showed a genetic heterogeneity and was close to Barbarine. The D'Man breed shared a considerable gene flow with the thin-tailed Queue Fine de l'Ouest breed. Native small ruminants breeds, are capable to be efficiently productive if essential ingredients and coherent breeding schemes are implemented and followed. Assessing the status of genetic variability of native sheep breeds could provide important clues for research and policy makers to devise better strategies for the conservation and management of genetic resources.

Keywords: sheep, farming systems, diversity, SNPs.

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Authors: A. Mohammadi, S. Asghari, M. Aien, M. Rashidinejad

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After emergent of alternative current networks and their popularity, asynchronous motors became more widespread than other kinds of industrial motors. In order to control and run these motors efficiently, an accurate estimation of motor parameters is needed. There are different methods to obtain these parameters such as rotor locked test, no load test, DC test, analytical methods, and so on. The most common drawback of these methods is their inaccuracy in estimation of some motor parameters. In order to remove this concern, a novel method for parameter estimation of induction motors using particle swarm optimization (PSO) algorithm is proposed. In the proposed method, transient state of motor is used for parameter estimation. Comparison of the simulation results purtuined to the PSO algorithm with other available methods justifies the effectiveness of the proposed method.

Keywords: induction motor, motor parameter estimation, PSO algorithm, analytical method

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Authors: Ramin Javadzadeh

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The particle swarm optimization are Meta heuristic optimization method, which are used for clustering and pattern recognition applications are abundantly. These algorithms in multimodal optimization problems are more efficient than genetic algorithms. A major drawback in these algorithms is their slow convergence to global optimum and their weak stability can be considered in various running of these algorithms. In this paper, improved Particle swarm optimization is introduced for the first time to overcome its problems. The fuzzy cellular automata is used for improving the algorithm efficiently. The credibility of the proposed approach is evaluated by simulations, and it is shown that the proposed approach achieves better results can be achieved compared to the Particle swarm optimization algorithms.

Keywords: cellular automata, cellular learning automata, local search, optimization, particle swarm optimization

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Authors: Ahlem Abid, Farah Jemili

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Intrusion detection has been the subject of numerous studies in industry and academia, but cyber security analysts always want greater precision and global threat analysis to secure their systems in cyberspace. To improve intrusion detection system, the visualisation of the security events in form of graphs and diagrams is important to improve the accuracy of alerts. In this paper, we propose an approach of an IDS based on cloud computing, big data technique and using a machine learning graph algorithm which can detect in real time different attacks as early as possible. We use the MAWILab intrusion detection dataset . We choose Microsoft Azure as a unified cloud environment to load our dataset on. We implement the k2 algorithm which is a graphical machine learning algorithm to classify attacks. Our system showed a good performance due to the graphical machine learning algorithm and spark structured streaming engine.

Keywords: Apache Spark Streaming, Graph, Intrusion detection, k2 algorithm, Machine Learning, MAWILab, Microsoft Azure Cloud

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Authors: Syed Romat Ali Shah, Bilal Shoaib, Saleem Akhtar, Munib Ahmad, Shahan Sadiqui

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Classification is a data mining technique, which is recognizedon Machine Learning (ML) algorithm. It is used to classifythe individual articlein a knownofinformation into a set of predefinemodules or group. Web mining is also a portion of that sympathetic of data mining methods. The main purpose of this paper to analysis and compare the performance of Naïve Bayse Algorithm, Decision Tree, K-Nearest Neighbor (KNN), Artificial Neural Network (ANN)and Support Vector Machine (SVM). This paper consists of different ML algorithm and their advantages and disadvantages and also define research issues.

Keywords: Data Mining, Web Mining, classification, ML Algorithms

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Authors: Hong Nguyen Thi Hai, Ryota Konda, Dat Kieu Tuan, Cao Tran Thanh, Khang Phung Van, Hau Tran Tin, Harry Wu

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Melaleuca cajuputi is a moderately fast-growing species and considered as a multi-purpose tree as it provides fuelwood, piles and frame poles in construction, leaf essential oil and honey. It occurs in Australia, Papua New Guinea, and South-East Asia. M. cajuputi plantation can be harvested on 6-7 year rotations for wood products. Its timber can also be used for pulp and paper, fiber and particle board, producing quality charcoal and potentially sawn timber. However, most reported M. cajuputi breeding programs have been focused on oil production rather than wood production. In this study, breeding program of M. cajuputi aimed to improve wood production was examined by estimating genetic parameters for growth (tree height, diameter at breast height (DBH), and volume), stem form, stiffness (modulus of elasticity (MOE)), bark thickness and bark ratio in a half-sib family progeny trial including 80 families in the Mekong Delta of Vietnam. MOE is one of the key wood properties of interest to the wood industry. Non-destructive wood stiffness was measured indirectly by acoustic velocity using FAKOPP Microsecond Timer and especially unaffected by bark mass. Narrow-sense heritability for the seven traits ranged from 0.13 to 0.27 at age 7 years. MOE and stem form had positive genetic correlations with growth while the negative correlation between bark ratio and growth was also favorable. Breeding for simultaneous improvement of multiple traits, faster growth with higher MOE and reduction of bark ratio should be possible in M. cajuputi. Index selection based on volume and MOE showed genetic gains of 31 % in volume, 6 % in MOE and 13 % in stem form. In addition, heritability and age-age genetic correlations for growth traits increased with time and optimal early selection age for growth of M. cajuputi based on DBH alone was 4 years. Selected thinning resulted in an increase of heritability due to considerable reduction of phenotypic variation but little effect on genetic variation.

Keywords: acoustic velocity, age-age correlation, bark thickness, heritability, Melaleuca cajuputi, stiffness, thinning effect

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Authors: Fumiko Kojima, Shuji Fujimoto

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Anisakiasis is a disease caused by infection with an anisakid larvae, mostly Anisakis simplex. The larvae commonly infect in marine fish and the disease is frequently reported in areas of the world where fish is consumed raw, lightly pickled or salted. In Japan, people have the habit of eating raw fish such as ‘sushi’ or ‘sashimi’, so they have more chance of infection with larvae of anisakid nematodes. There are three sibling species in A. simplex larvae, namely, A. simplex sensu stricto (Asss), A. pegreffii (Ap) and A. simplex C. It was revealed that Ap is dominant among the larvae from fish (Scomber japonics) in the Japan Sea side and Asss is dominant among those of the Pacific Ocean side conversely. Although anisakiasis has happened in Japan among both the Japan Sea side area and the Pacific Ocean side area. The aim of this study was to investigate genetic variations between the siblings (Asss and Ap) and within the same sibling species by random amplified polymorphic DNA (RAPD) technique. In order to investigate the genetic difference among the each A. simplex larvae, we used RAPD technique to differentiate individuals of A. simplex obtained from Scomber japonics fish those were caught in the Japan sea (Goto Islands in Nagasaki Prefecture) and the cost of Pacific Ocean (Kanagawa Prefecture). The RAPD patterns of the control DNA (Genus Raphidascaris) were markedly different from those of the A. simplex. There were differences in amplification patterns between Asss and Ap. The RAPD patterns for larvae obtained from fish of the same sea were somewhat different and variations were detected even among larvae from the same fish. These results suggest the considerable high genetic variability between Asss and Ap and the possible existence of genetic variation within the sibling species.

Keywords: Anisakiasis in Japan, Anisakis simplex, genomic identification, PCR-RAPD

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Authors: Adilah Abdul Ghapor, Yong Zulina Zubairi, Rahmatullah Imon

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Missing value problem is common in statistics and has been of interest for years. This article considers two modern techniques in handling missing data for linear functional relationship model (LFRM) namely the Expectation-Maximization (EM) algorithm and Expectation-Maximization with Bootstrapping (EMB) algorithm using three performance indicators; namely the mean absolute error (MAE), root mean square error (RMSE) and estimated biased (EB). In this study, we applied the methods of imputing missing values in the LFRM. Results of the simulation study suggest that EMB algorithm performs much better than EM algorithm in both models. We also illustrate the applicability of the approach in a real data set.

Keywords: expectation-maximization, expectation-maximization with bootstrapping, linear functional relationship model, performance indicators

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Authors: Nkwa Agbor Etobi Arreneke

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A well-designed earthing/grounding system will not only provide an effective path for direct dissipation of faulty currents into the earth/soil, but also ensure the safety of personnels withing and around its immediate surrounding perimeter is free from the possibility of fatal electric shock. In order to achieve the latter, it is of paramount importance to ensuring that both the step and touch potentials are kept within the allowable tolerance set by standards IEEE Std-80-2000. In this article, the step and touch potentials of an earthing system are simulated and conformity verified using the Finite Element Method (FEM), and has been found to be 242.4V and 194.80V respectively. The effect of injection current position is also analyzed to observe its effect on a person within or in contact with any active part of the earthing system of the substation. The values obtained closely matches those of other published works which made using different numerical methods and/or simulations Genetic Algorithm (GA). This current study is aimed at throwing more light to the dangers of step and touch potential of earthing systems of substation and electrical facilities as a whole, and the need for further in-dept analysis of these parameters. Observations made on this current paper shows that, the position of contact with an energize earthing system is of paramount important in determining its effect on living organisms in contact with any energized part of the earthing systems.

Keywords: earthing/grounding systems, finite element method (fem), ground/earth resistance, safety, touch and step potentials, generic algorithm

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Authors: Yun-Hsiang Wang, Huai-Yi Chen, Kin Fong Lei

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Deoxyribonucleic acid (DNA) hybridization is a common technique used in genetic assay widely. However, the hybridization ratio and rate are usually limited by the diffusion effect. Here, microfluidic electrode platform producing electroosmosis generated by alternating current signal has been proposed to enhance the hybridization ratio and rate. The electrode was made of aurum fabricated by microfabrication technique. Thiol-modified oligo probe was immobilized on the electrode for specific capture of target, which is modified by fluorescent tag. Alternative electroosmosis can induce local microfluidic vortexes to accelerate DNA hybridization. This study provides a strategy to enhance the rate of DNA hybridization in the genetic assay.

Keywords: DNA hybridization, electroosmosis, electrical enhancement, hybridization ratio

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Authors: Wathig Hashim Mohamed Ibrahim

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Twenty Five polymorphic microsatellite out of 50 Loci were used to genotype some camel (Camelus dromedarius) types and subtypes in Sudan (Naylawi, Shanapla, Lahawi, Kinani, Rashaydi, Bani-Aamir, Annafi, Bishari Shallagyai and Bishari Arririt) and that from Qatar (OmmaniHJ, OmmaniKH, Majaheem, Pakistani Sindi, Pakistani Punjabi and Pakistani) and for comparative; one type from Somalia (Aarhou) and another from Chad (Spotted) were investigated. The highest number of alleles were 23 in Locus CVRL 01, and lowest were 2 in YWLL 59. The observed heterozygosity (Hobs) were 0.950 and 0.049 for VOLP08 and YWLL09, respectively, while the expected heterozygosity (HExp) were 0.915 and 0.362 for Locus VOLP67 and YWLL58, respectively, and the HExp mean was 0.7378. Polymorphic Information Content (PIC) ranged between 0.907 - 0.345 in Locus VOLP67 and YWLL58, and the PIC mean was 0.7002. The genetic distance ranged between 0.545 – 0.098 for Shallagyai (Bishari subtype) – Pakistani Sindi subtype and between Annafi - Rashaydi, respectively. The genetic distance between spotted and all types ranged between 0.223 with Arririt (Bishari subtype) and 0.463 with Punjabi (Pakistani subtype) that found in Qatar, while all types with Aarhou ranged between 0.215 for Arririt and 0.469 with Punjabi (Pakistani subtype). The dondrogram shows that there is a relationship between the genetic makeup and geographical distributions and also between the genetic makeup and phenotypic characteristic. Individual assignment was calculated, 46.62% correctly assigned and 46.87% quality index. Hardy Weinberg Equivalent (HWE) was also calculated. Key words: Camel, genotype, polymorphic microsatellite

Keywords: camel, genotype, polymorphic microsatellite, types and subtypes

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Authors: Tomáš Dyk, Stanislav Procházka, Martin Drahanský

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The article proposes a new algorithm for detecting damaged areas of the tank barrel based on the image of the inner surface of the tank barrel. Damage position is calculated using image processing techniques such as edge detection, discrete wavelet transformation and image segmentation for accurate contour detection. The algorithm can detect surface damage in smoothbore and even in rifled tank barrels. The algorithm also calculates the volume of the detected damage from the depth map generated, for example, from the distance measurement unit. The proposed method was tested on data obtained by a tank barrel scanning device, which generates both surface image data and depth map. The article also discusses tank barrel scanning devices and how damaged surface impacts material resistance.

Keywords: barrel, barrel diagnostic, image processing, surface damage detection, tank

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Authors: Riffat Iqbal, Sidra Ihsan, Andleeb Batool, Maryam Mukhtar

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Glaucoma is a gathering of optic neuropathies described by dynamic degeneration of retinal ganglionic cells. It is clinically and innately heterogenous illness containing a couple of particular forms each with various causes and severities. Primary open-angle glaucoma (POAG) is the most generally perceived kind of glaucoma. This study investigated the genetic association of single nucleotide polymorphisms (SNPs; rs10483727 and rs33912345) at the SIX1/SIX6 locus with primary open-angle glaucoma (POAG) in the Pakistani population. The SIX6 gene plays an important role in ocular development and has been associated with morphology of the optic nerve. A total of 100 patients clinically diagnosed with glaucoma and 100 control individuals of age over 40 were enrolled in the study. Genomic DNA was extracted by organic extraction method. The SNP genotyping was done by (i) PCR based restriction fragment length polymorphism (RFLP) and sequencing method. Significant genetic associations were observed for rs10483727 (risk allele T) and rs33912345 (risk allele C) with POAG. Hence, it was concluded that Six6 gene is genetically associated with pathogenesis of Glaucoma in Pakistan.

Keywords: genotyping, Pakistani population, primary open-angle glaucoma, SIX6 gene

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Authors: T. R. Sharika, Ashwini Kumar, Kamal Bijlani

Abstract:

Encryption is the process of converting crucial information’s unreadable to unauthorized persons. Image security is an important type of encryption that secures all type of images from cryptanalysis. A stream cipher is a fast symmetric key algorithm which is used to convert plaintext to cipher text. In this paper we are proposing an image encryption algorithm with Discrete Cosine Transform and Stream Ciphers that can improve compression of images and enhanced security. The paper also explains the use of a shuffling algorithm for enhancing securing.

Keywords: decryption, DCT, encryption, RC4 cipher, stream cipher

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Authors: Othman Elmahdy Othman, Agnés Germot, Daniel Petit, Muhammad Khodary, Abderrahman Maftah

Abstract:

Recently, the control (D-loop) and cytochrome b (Cyt b) regions of mtDNA have received more attention due to their role in the genetic diversity and phylogenetic studies in different livestock which give important knowledge towards the genetic resource conservation. Studies based on sequencing of sheep mitochondrial DNA showed that there are five maternal lineages in the world for domestic sheep breeds; A, B, C, D and E. By using cytochrome B sequencing, we aimed to clarify the genetic affinities and phylogeny of six Egyptian sheep breeds. Blood samples were collected from 111 animals belonging to six Egyptian sheep breeds; Barki, Rahmani, Ossimi, Saidi, Sohagi and Fallahi. The total DNA was extracted and the specific primers were used for conventional PCR amplification of the cytochrome B region of mtDNA. PCR amplified products were purified and sequenced. The alignment of sequences was done using BioEdit software and DnaSP 5.00 software was used to identify the sequence variation and polymorphic sites in the aligned sequences. The result showed that the presence of 39 polymorphic sites leading to the formation of 29 haplotypes. The haplotype diversity in six tested breeds ranged from 0.643 in Rahmani breed to 0.871 in Barki breed. The lowest genetic distance was observed between Rahmani and Saidi (D: 1.436 and Dxy: 0.00127) while the highest distance was observed between Ossimi and Sohagi (D: 6.050 and Dxy: 0.00534). Neighbour-joining (Phylogeny) tree was constructed using Mega 5.0 software. The sequences of 111 analyzed samples were aligned with references sequences of different haplogroups; A, B, C, D and E. The phylogeny result showed the presence of four haplogroups; HapA, HapB, HapC and HapE in the examined samples whereas the haplogroup D was not found. The result showed that 88 out of 111 tested animals cluster with haplogroup B (79.28%), whereas 12 tested animals cluster with haplogroup A (10.81%), 10 animals cluster with haplogroup C (9.01%) and one animal belongs to haplogroup E (0.90%).

Keywords: phylogeny, genetic biodiversity, MtDNA, cytochrome B, Egyptian sheep

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Authors: Mudrika Singhal

Abstract:

The research paper is basically about how the genetically modified organisms evolved and their significance in today’s world. It also highlights about the various pros and cons of the genetically modified organisms and the progress of India in this field. A genetically modified organism is the one whose genetic material has been altered using genetic engineering techniques. They have a wide range of uses such as transgenic plants, genetically modified mammals such as mouse and also in insects and aquatic life. Their use is rooted back to the time around 12,000 B.C. when humans domesticated plants and animals. At that humans used genetically modified organisms produced by the procedure of selective breeding and not by genetic engineering techniques. Selective breeding is the procedure in which selective traits are bred in plants and animals and then are domesticated. Domestication of wild plants into a suitable cultigen is a well known example of this technique. GMOs have uses in varied fields ranging from biological and medical research, production of pharmaceutical drugs to agricultural fields. The first organisms to be genetically modified were the microbes because of their simpler genetics. At present the genetically modified protein insulin is used to treat diabetes. In the case of plants transgenic plants, genetically modified crops and cisgenic plants are the examples of genetic modification. In the case of mammals, transgenic animals such as mice, rats etc. serve various purposes such as researching human diseases, improvement in animal health etc. Now coming upon the pros and cons related to the genetically modified organisms, pros include crops with higher yield, less growth time and more predictable in comparison to traditional breeding. Cons include that they are dangerous to mammals such as rats, these products contain protein which would trigger allergic reactions. In India presently, group of GMOs include GM microorganisms, transgenic crops and animals. There are varied applications in the field of healthcare and agriculture. In the nutshell, the research paper is about the progress in the field of genetic modification, taking along the effects in today’s world.

Keywords: applications, mammals, transgenic, engineering and technology

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Authors: Fathi Kallel, Ahmed Ben Hamida, Christian Berger-Vachon

Abstract:

In this paper, a Speech Enhancement Algorithm based on Multi-Band Spectral Subtraction (MBSS) principle is evaluated for Bilateral Cochlear Implant (BCI) users. Specifically, dual-channel noise power spectral estimation algorithm using Power Spectral Densities (PSD) and Cross Power Spectral Densities (CPSD) of the observed signals is studied. The enhanced speech signal is obtained using Dual-Channel Multi-Band Spectral Subtraction ‘DC-MBSS’ algorithm. For performance evaluation, objective speech assessment test relying on Perceptual Evaluation of Speech Quality (PESQ) score is performed to fix the optimal number of frequency bands needed in DC-MBSS algorithm. In order to evaluate the speech intelligibility, subjective listening tests are assessed with 3 deafened BCI patients. Experimental results obtained using French Lafon database corrupted by an additive babble noise at different Signal-to-Noise Ratios (SNR) showed that DC-MBSS algorithm improves speech understanding for single and multiple interfering noise sources.

Keywords: speech enhancement, spectral substracion, noise estimation, cochlear impalnt

Procedia PDF Downloads 549