Search results for: non-dominated sorting genetic algorithm
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4805

Search results for: non-dominated sorting genetic algorithm

4025 Fast and Robust Long-term Tracking with Effective Searching Model

Authors: Thang V. Kieu, Long P. Nguyen

Abstract:

Kernelized Correlation Filter (KCF) based trackers have gained a lot of attention recently because of their accuracy and fast calculation speed. However, this algorithm is not robust in cases where the object is lost by a sudden change of direction, being obscured or going out of view. In order to improve KCF performance in long-term tracking, this paper proposes an anomaly detection method for target loss warning by analyzing the response map of each frame, and a classification algorithm for reliable target re-locating mechanism by using Random fern. Being tested with Visual Tracker Benchmark and Visual Object Tracking datasets, the experimental results indicated that the precision and success rate of the proposed algorithm were 2.92 and 2.61 times higher than that of the original KCF algorithm, respectively. Moreover, the proposed tracker handles occlusion better than many state-of-the-art long-term tracking methods while running at 60 frames per second.

Keywords: correlation filter, long-term tracking, random fern, real-time tracking

Procedia PDF Downloads 125
4024 An Algorithm Based on the Nonlinear Filter Generator for Speech Encryption

Authors: A. Belmeguenai, K. Mansouri, R. Djemili

Abstract:

This work present a new algorithm based on the nonlinear filter generator for speech encryption and decryption. The proposed algorithm consists on the use a linear feedback shift register (LFSR) whose polynomial is primitive and nonlinear Boolean function. The purpose of this system is to construct Keystream with good statistical properties, but also easily computable on a machine with limited capacity calculated. This proposed speech encryption scheme is very simple, highly efficient, and fast to implement the speech encryption and decryption. We conclude the paper by showing that this system can resist certain known attacks.

Keywords: nonlinear filter generator, stream ciphers, speech encryption, security analysis

Procedia PDF Downloads 278
4023 Genetic Variability in Advanced Derivatives of Interspecific Hybrids in Brassica

Authors: Yasir Ali, Farhatullah

Abstract:

The present study was conducted to estimate the genetic variability, heritability and genetic advance in six parental lines and their 56 genotypes derived from five introgressed brassica populations on the basis of morphological and biochemical traits. The experiment was laid out in a randomized complete block design with two replications at The University of Agriculture Peshawar-Pakistan during growing season of 2015-2016. The ANOVA of all traits of F5:6 populations showed highly significant differences (P ≤ 0.01) for all morphological and biochemical traits. Among F5:6 populations, the genotype 2(526) was earlier in flowering (108.65 days), and genotype 14(485) was earlier in maturity (170 days). Tallest plants (182.5 cm), largest main raceme (91.5 cm) and maximum number of pods (80.5) on main raceme were recorded for genotype 17(34). Maximum primary branches plant-1(6.2) and longest pods (10.26 cm) were recorded for genotype 15, while genotype 16(171) had more seeds pod⁻¹ (22) and gave maximum yield plant-1 (30.22 g). The maximum 100-seed weight (0.60 g) was observed for genotype 10(506) while high protein content (22.61%) was recorded for genotype 4(99). Maximum oil content (54.08 %) and low linoleic acid (7.07 %) were produced by genotype (12(138) and low glucosinolate (59.01 µMg⁻¹) was recorded for genotype 21(113). The genotype 27(303) having high oleic acid content (51.73 %) and genotype 1(209) gave low erucic acid (35.97 %). Among the F5:6 populations moderate to high heritability observed for all morphological and biochemical traits coupled with high genetic advance. Cluster analysis grouped the 56 F5:6 populations along their parental lines into seven different groups. Each group was different from the other group on the basis of morphological and biochemical traits. Moreover all the F5:6 populations showed sufficient variability. Genotypes 10(506) and 16(171) were superior for high seed yield⁻¹, 100-seeds weight, and seed pod⁻¹ and are recommended for future breeding program.

Keywords: Brassicaceae, biochemical characterization, introgression, morphological characterization

Procedia PDF Downloads 170
4022 Optimizing Network Latency with Fast Path Assignment for Incoming Flows

Authors: Qing Lyu, Hang Zhu

Abstract:

Various flows in the network require to go through different types of middlebox. The improper placement of network middlebox and path assignment for flows could greatly increase the network latency and also decrease the performance of network. Minimizing the total end to end latency of all the ows requires to assign path for the incoming flows. In this paper, the flow path assignment problem in regard to the placement of various kinds of middlebox is studied. The flow path assignment problem is formulated to a linear programming problem, which is very time consuming. On the other hand, a naive greedy algorithm is studied. Which is very fast but causes much more latency than the linear programming algorithm. At last, the paper presents a heuristic algorithm named FPA, which takes bottleneck link information and estimated bandwidth occupancy into consideration, and achieves near optimal latency in much less time. Evaluation results validate the effectiveness of the proposed algorithm.

Keywords: flow path, latency, middlebox, network

Procedia PDF Downloads 192
4021 Genetic Counseling for Severe Mental Disorders. Integrating Innovative Services and Prophylactic Interventions in an Online Platform - MENTALICA

Authors: Ramona Moldovan, Doina Cosman, Sebastian Moldovan, Radu Popp, Victor Pop

Abstract:

MENTALICA is a project aimed at developing and evaluating a platform that can assist individuals diagnosed with severe mental disorders and their families in managing the consequences associated with severe mental disorders, recurrence risks, prevention strategies and treatment options. MENTALICA is a platform based on guidance issued by some of the most prominent scientific organizations in the world. In order to personalize the information provided, the program explores details about the personal and family history of mental disorders. MENTALICA summarizes the answers and gives respondents a personal assessment. This includes personalized information and support about schizophrenia, bipolar disorder and schizoaffective disorder. MENTALICA includes several modules: Family history tools, Risk assessment tools and Risk factor sheets, Practical guides for patients, Practical guides for families, Guidelines for clinicians. Currently, there are no available guidelines for genetic counselling for mental disorders. Respondents can print out their reports and discuss them with family members or their doctors. We will briefly present the current status of MENTALICA and its implications for patients, professionals and the community.

Keywords: genetic counseling, mental disorders, platform

Procedia PDF Downloads 475
4020 Handling Missing Data by Using Expectation-Maximization and Expectation-Maximization with Bootstrapping for Linear Functional Relationship Model

Authors: Adilah Abdul Ghapor, Yong Zulina Zubairi, A. H. M. R. Imon

Abstract:

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 two types of LFRM namely the full model of LFRM and in LFRM when the slope is estimated using a nonparametric method. 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

Procedia PDF Downloads 440
4019 An Introduction to E-Content Producing Algorithm for Screen-Recorded Videos

Authors: Jamileh Darsareh, Mohammad Nikafrooz

Abstract:

Some teachers and e-content producers, based on their experiences, try to produce educational videos using screen recording software. There are many challenges that they may encounter while producing screen-recorded videos. These are in the domains of technical and pedagogical challenges like designing the roadmap, preparing the screen, setting the recording software and recording the screen, editing, etc. This study is a descriptive study and tries to present some procedures for producing acceptable and well-made videos. These procedures are presented in the form of an algorithm for producing screen-recorded video. This algorithm presents the main producing phases, including design, pre-production, production, post-production, and distribution. These phases consist of some steps which are supported by several technical and pedagogical considerations. Following these phases and steps according to the suggested order helps the producers to produce their intended and desired video by saving time and also facing fewer technical problems. It is expected that by using this algorithm, e-content producers and teachers gain better performance in producing educational videos.

Keywords: e-content producing algorithm, screen-recorded videos, screen recording software, technical and pedagogical considerations

Procedia PDF Downloads 184
4018 Performance Comparison of Prim’s and Ant Colony Optimization Algorithm to Select Shortest Path in Case of Link Failure

Authors: Rimmy Yadav, Avtar Singh

Abstract:

—Ant Colony Optimization (ACO) is a promising modern approach to the unused combinatorial optimization. Here ACO is applied to finding the shortest during communication link failure. In this paper, the performances of the prim’s and ACO algorithm are made. By comparing the time complexity and program execution time as set of parameters, we demonstrate the pleasant performance of ACO in finding excellent solution to finding shortest path during communication link failure.

Keywords: ant colony optimization, link failure, prim’s algorithm, shortest path

Procedia PDF Downloads 381
4017 3D Reconstruction of Human Body Based on Gender Classification

Authors: Jiahe Liu, Hongyang Yu, Feng Qian, Miao Luo

Abstract:

SMPL-X was a powerful parametric human body model that included male, neutral, and female models, with significant gender differences between these three models. During the process of 3D human body reconstruction, the correct selection of standard templates was crucial for obtaining accurate results. To address this issue, we developed an efficient gender classification algorithm to automatically select the appropriate template for 3D human body reconstruction. The key to this gender classification algorithm was the precise analysis of human body features. By using the SMPL-X model, the algorithm could detect and identify gender features of the human body, thereby determining which standard template should be used. The accuracy of this algorithm made the 3D reconstruction process more accurate and reliable, as it could adjust model parameters based on individual gender differences. SMPL-X and the related gender classification algorithm have brought important advancements to the field of 3D human body reconstruction. By accurately selecting standard templates, they have improved the accuracy of reconstruction and have broad potential in various application fields. These technologies continue to drive the development of the 3D reconstruction field, providing us with more realistic and accurate human body models.

Keywords: gender classification, joint detection, SMPL-X, 3D reconstruction

Procedia PDF Downloads 53
4016 3D Human Body Reconstruction Based on Multiple Viewpoints

Authors: Jiahe Liu, HongyangYu, Feng Qian, Miao Luo

Abstract:

The aim of this study was to improve the effects of human body 3D reconstruction. The MvP algorithm was adopted to obtain key point information from multiple perspectives. This algorithm allowed the capture of human posture and joint positions from multiple angles, providing more comprehensive and accurate data. The study also incorporated the SMPL-X model, which has been widely used for human body modeling, to achieve more accurate 3D reconstruction results. The use of the MvP algorithm made it possible to observe the reconstructed object from multiple angles, thus reducing the problems of blind spots and missing information. This algorithm was able to effectively capture key point information, including the position and rotation angle of limbs, providing key data for subsequent 3D reconstruction. Compared with traditional single-view methods, the method of multi-view fusion significantly improved the accuracy and stability of reconstruction. By combining the MvP algorithm with the SMPL-X model, we successfully achieved better human body 3D reconstruction effects. The SMPL-X model is highly scalable and can generate highly realistic 3D human body models, thus providing more detail and shape information.

Keywords: 3D human reconstruction, multi-view, joint point, SMPL-X

Procedia PDF Downloads 50
4015 Genomics of Aquatic Adaptation

Authors: Agostinho Antunes

Abstract:

The completion of the human genome sequencing in 2003 opened a new perspective into the importance of whole genome sequencing projects, and currently multiple species are having their genomes completed sequenced, from simple organisms, such as bacteria, to more complex taxa, such as mammals. This voluminous sequencing data generated across multiple organisms provides also the framework to better understand the genetic makeup of such species and related ones, allowing to explore the genetic changes underlining the evolution of diverse phenotypic traits. Here, recent results from our group retrieved from comparative evolutionary genomic analyses of selected marine animal species will be considered to exemplify how gene novelty and gene enhancement by positive selection might have been determinant in the success of adaptive radiations into diverse habitats and lifestyles.

Keywords: comparative genomics, adaptive evolution, bioinformatics, phylogenetics, genome mining

Procedia PDF Downloads 516
4014 Real-Time Detection of Space Manipulator Self-Collision

Authors: Zhang Xiaodong, Tang Zixin, Liu Xin

Abstract:

In order to avoid self-collision of space manipulators during operation process, a real-time detection method is proposed in this paper. The manipulator is fitted into a cylinder enveloping surface, and then the detection algorithm of collision between cylinders is analyzed. The collision model of space manipulator self-links can be detected by using this algorithm in real-time detection during the operation process. To ensure security of the operation, a safety threshold is designed. The simulation and experiment results verify the effectiveness of the proposed algorithm for a 7-DOF space manipulator.

Keywords: space manipulator, collision detection, self-collision, the real-time collision detection

Procedia PDF Downloads 449
4013 Incorporating Information Gain in Regular Expressions Based Classifiers

Authors: Rosa L. Figueroa, Christopher A. Flores, Qing Zeng-Treitler

Abstract:

A regular expression consists of sequence characters which allow describing a text path. Usually, in clinical research, regular expressions are manually created by programmers together with domain experts. Lately, there have been several efforts to investigate how to generate them automatically. This article presents a text classification algorithm based on regexes. The algorithm named REX was designed, and then, implemented as a simplified method to create regexes to classify Spanish text automatically. In order to classify ambiguous cases, such as, when multiple labels are assigned to a testing example, REX includes an information gain method Two sets of data were used to evaluate the algorithm’s effectiveness in clinical text classification tasks. The results indicate that the regular expression based classifier proposed in this work performs statically better regarding accuracy and F-measure than Support Vector Machine and Naïve Bayes for both datasets.

Keywords: information gain, regular expressions, smith-waterman algorithm, text classification

Procedia PDF Downloads 303
4012 Hybridized Simulated Annealing with Chemical Reaction Optimization for Solving to Sequence Alignment Problem

Authors: Ernesto Linan, Linda Cruz, Lucero Becerra

Abstract:

In this paper, a new hybridized algorithm based on Chemical Reaction Optimization and Simulated Annealing is proposed to solve the alignment sequence Problem. The Chemical Reaction Optimization is a population-based meta-heuristic algorithm based on the principles of a chemical reaction. Simulated Annealing is applied to solve a large number of combinatorial optimization problems of general-purpose. In this paper, we propose hybridization between Chemical Reaction Optimization algorithm and Simulated Annealing in order to solve the Sequence Alignment Problem. An initial population of molecules is defined at beginning of the proposed algorithm, where each molecule represents a sequence alignment problem. In order to simulate inter-molecule collisions, the process of Chemical Reaction is placed inside the Metropolis Cycle at certain values of temperature. Inside this cycle, change of molecules is done due to collisions; some molecules are accepted by applying Boltzmann probability. The results with the hybrid scheme are better than the results obtained separately.

Keywords: chemical reaction optimization, sequence alignment problem, simulated annealing algorithm, metaheuristics

Procedia PDF Downloads 197
4011 LEDs Based Indoor Positioning by Distances Derivation from Lambertian Illumination Model

Authors: Yan-Ren Chen, Jenn-Kaie Lain

Abstract:

This paper proposes a novel indoor positioning algorithm based on visible light communications, implemented by light-emitting diode fixtures. In the proposed positioning algorithm, distances between light-emitting diode fixtures and mobile terminal are derived from the assumption of ideal Lambertian optic radiation model, and Trilateration positioning method is proceeded immediately to get the coordinates of mobile terminal. The proposed positioning algorithm directly obtains distance information from the optical signal modeling, and therefore, statistical distribution of received signal strength at different positions in interior space has no need to be pre-established. Numerically, simulation results have shown that the proposed indoor positioning algorithm can provide accurate location coordinates estimation.

Keywords: indoor positioning, received signal strength, trilateration, visible light communications

Procedia PDF Downloads 400
4010 CanVis: Towards a Web Platform for Cancer Progression Tree Analysis

Authors: Michael Aupetit, Mahmoud Al-ismail, Khaled Mohamed

Abstract:

Cancer is a major public health problem all over the world. Breast cancer has the highest incidence rate over all cancers for women in Qatar making its study a top priority of the country. Human cancer is a dynamic disease that develops over an extended period through the accumulation of a series of genetic alterations. A Darwinian process drives the tumor cells toward higher malignancy growing the branches of a progression tree in the space of genes expression. Although it is not possible to track these genetic alterations dynamically for one patient, it is possible to reconstruct the progression tree from the aggregation of thousands of tumor cells’ genetic profiles from thousands of different patients at different stages of the disease. Analyzing the progression tree is a way to detect pivotal molecular events that drive the malignant evolution and to provide a guide for the development of cancer diagnostics, prognostics and targeted therapeutics. In this work we present the development of a Visual Analytic web platform CanVis enabling users to upload gene-expression data and analyze their progression tree. The server computes the progression tree based on state-of-the-art techniques and allows an interactive visual exploration of this tree and the gene-expression data along its branching structure helping to discover potential driver genes.

Keywords: breast cancer, progression tree, visual analytics, web platform

Procedia PDF Downloads 398
4009 Finite Element Method for Solving the Generalized RLW Equation

Authors: Abdel-Maksoud Abdel-Kader Soliman

Abstract:

The General Regularized Long Wave (GRLW) equation is solved numerically by giving a new algorithm based on collocation method using quartic B-splines at the mid-knot points as element shape. Also, we use the Fourth Runge-Kutta method for solving the system of first order ordinary differential equations instead of finite difference method. Our test problems, including the migration and interaction of solitary waves, are used to validate the algorithm which is found to be accurate and efficient. The three invariants of the motion are evaluated to determine the conservation properties of the algorithm.

Keywords: generalized RLW equation, solitons, quartic b-spline, nonlinear partial differential equations, difference equations

Procedia PDF Downloads 479
4008 A Statistical-Algorithmic Approach for the Design and Evaluation of a Fresnel Solar Concentrator-Receiver System

Authors: Hassan Qandil

Abstract:

Using a statistical algorithm incorporated in MATLAB, four types of non-imaging Fresnel lenses are designed; spot-flat, linear-flat, dome-shaped and semi-cylindrical-shaped. The optimization employs a statistical ray-tracing methodology of the incident light, mainly considering effects of chromatic aberration, varying focal lengths, solar inclination and azimuth angles, lens and receiver apertures, and the optimum number of prism grooves. While adopting an equal-groove-width assumption of the Poly-methyl-methacrylate (PMMA) prisms, the main target is to maximize the ray intensity on the receiver’s aperture and therefore achieving higher values of heat flux. The algorithm outputs prism angles and 2D sketches. 3D drawings are then generated via AutoCAD and linked to COMSOL Multiphysics software to simulate the lenses under solar ray conditions, which provides optical and thermal analysis at both the lens’ and the receiver’s apertures while setting conditions as per the Dallas-TX weather data. Once the lenses’ characterization is finalized, receivers are designed based on its optimized aperture size. Several cavity shapes; including triangular, arc-shaped and trapezoidal, are tested while coupled with a variety of receiver materials, working fluids, heat transfer mechanisms, and enclosure designs. A vacuum-reflective enclosure is also simulated for an enhanced thermal absorption efficiency. Each receiver type is simulated via COMSOL while coupled with the optimized lens. A lab-scale prototype for the optimum lens-receiver configuration is then fabricated for experimental evaluation. Application-based testing is also performed for the selected configuration, including that of a photovoltaic-thermal cogeneration system and solar furnace system. Finally, some future research work is pointed out, including the coupling of the collector-receiver system with an end-user power generator, and the use of a multi-layered genetic algorithm for comparative studies.

Keywords: COMSOL, concentrator, energy, fresnel, optics, renewable, solar

Procedia PDF Downloads 137
4007 K-Means Clustering-Based Infinite Feature Selection Method

Authors: Seyyedeh Faezeh Hassani Ziabari, Sadegh Eskandari, Maziar Salahi

Abstract:

Infinite Feature Selection (IFS) algorithm is an efficient feature selection algorithm that selects a subset of features of all sizes (including infinity). In this paper, we present an improved version of it, called clustering IFS (CIFS), by clustering the dataset in advance. To do so, first, we apply the K-means algorithm to cluster the dataset, then we apply IFS. In the CIFS method, the spatial and temporal complexities are reduced compared to the IFS method. Experimental results on 6 datasets show the superiority of CIFS compared to IFS in terms of accuracy, running time, and memory consumption.

Keywords: feature selection, infinite feature selection, clustering, graph

Procedia PDF Downloads 109
4006 An Observer-Based Direct Adaptive Fuzzy Sliding Control with Adjustable Membership Functions

Authors: Alireza Gholami, Amir H. D. Markazi

Abstract:

In this paper, an observer-based direct adaptive fuzzy sliding mode (OAFSM) algorithm is proposed. In the proposed algorithm, the zero-input dynamics of the plant could be unknown. The input connection matrix is used to combine the sliding surfaces of individual subsystems, and an adaptive fuzzy algorithm is used to estimate an equivalent sliding mode control input directly. The fuzzy membership functions, which were determined by time consuming try and error processes in previous works, are adjusted by adaptive algorithms. The other advantage of the proposed controller is that the input gain matrix is not limited to be diagonal, i.e. the plant could be over/under actuated provided that controllability and observability are preserved. An observer is constructed to directly estimate the state tracking error, and the nonlinear part of the observer is constructed by an adaptive fuzzy algorithm. The main advantage of the proposed observer is that, the measured outputs is not limited to the first entry of a canonical-form state vector. The closed-loop stability of the proposed method is proved using a Lyapunov-based approach. The proposed method is applied numerically on a multi-link robot manipulator, which verifies the performance of the closed-loop control. Moreover, the performance of the proposed algorithm is compared with some conventional control algorithms.

Keywords: adaptive algorithm, fuzzy systems, membership functions, observer

Procedia PDF Downloads 189
4005 Performance Evaluation of Using Genetic Programming Based Surrogate Models for Approximating Simulation Complex Geochemical Transport Processes

Authors: Hamed K. Esfahani, Bithin Datta

Abstract:

Transport of reactive chemical contaminant species in groundwater aquifers is a complex and highly non-linear physical and geochemical process especially for real life scenarios. Simulating this transport process involves solving complex nonlinear equations and generally requires huge computational time for a given aquifer study area. Development of optimal remediation strategies in aquifers may require repeated solution of such complex numerical simulation models. To overcome this computational limitation and improve the computational feasibility of large number of repeated simulations, Genetic Programming based trained surrogate models are developed to approximately simulate such complex transport processes. Transport process of acid mine drainage, a hazardous pollutant is first simulated using a numerical simulated model: HYDROGEOCHEM 5.0 for a contaminated aquifer in a historic mine site. Simulation model solution results for an illustrative contaminated aquifer site is then approximated by training and testing a Genetic Programming (GP) based surrogate model. Performance evaluation of the ensemble GP models as surrogate models for the reactive species transport in groundwater demonstrates the feasibility of its use and the associated computational advantages. The results show the efficiency and feasibility of using ensemble GP surrogate models as approximate simulators of complex hydrogeologic and geochemical processes in a contaminated groundwater aquifer incorporating uncertainties in historic mine site.

Keywords: geochemical transport simulation, acid mine drainage, surrogate models, ensemble genetic programming, contaminated aquifers, mine sites

Procedia PDF Downloads 262
4004 An Improved VM Allocation Algorithm by Utilizing Combined Resource Allocation Mechanism and Released Resources in Cloud Environment

Authors: Md Habibul Ansary, Chandan Garai, Ranjan Dasgupta

Abstract:

Utilization of resources is always a great challenge for any allocation problem, particularly when resource availability is dynamic in nature. In this work VM allocation mechanism has been augmented by providing resources in a combined manner. This approach has some inherent advantages in terms of reduction of wait state for the pending jobs of some users and better utilization of unused resources from the service providers’ point of view. Moreover the algorithm takes care of released resources from the finished jobs as soon as those become available. The proposed algorithm has been explained by suitable example to make the work complete.

Keywords: Bid ratio, cloud service, virtualization, VM allocation problem

Procedia PDF Downloads 383
4003 Exploring an Exome Target Capture Method for Cross-Species Population Genetic Studies

Authors: Benjamin A. Ha, Marco Morselli, Xinhui Paige Zhang, Elizabeth A. C. Heath-Heckman, Jonathan B. Puritz, David K. Jacobs

Abstract:

Next-generation sequencing has enhanced the ability to acquire massive amounts of sequence data to address classic population genetic questions for non-model organisms. Targeted approaches allow for cost effective or more precise analyses of relevant sequences; although, many such techniques require a known genome and it can be costly to purchase probes from a company. This is challenging for non-model organisms with no published genome and can be expensive for large population genetic studies. Expressed exome capture sequencing (EecSeq) synthesizes probes in the lab from expressed mRNA, which is used to capture and sequence the coding regions of genomic DNA from a pooled suite of samples. A normalization step produces probes to recover transcripts from a wide range of expression levels. This approach offers low cost recovery of a broad range of genes in the genome. This research project expands on EecSeq to investigate if mRNA from one taxon may be used to capture relevant sequences from a series of increasingly less closely related taxa. For this purpose, we propose to use the endangered Northern Tidewater goby, Eucyclogobius newberryi, a non-model organism that inhabits California coastal lagoons. mRNA will be extracted from E. newberryi to create probes and capture exomes from eight other taxa, including the more at-risk Southern Tidewater goby, E. kristinae, and more divergent species. Captured exomes will be sequenced, analyzed bioinformatically and phylogenetically, then compared to previously generated phylogenies across this group of gobies. This will provide an assessment of the utility of the technique in cross-species studies and for analyzing low genetic variation within species as is the case for E. kristinae. This method has potential applications to provide economical ways to expand population genetic and evolutionary biology studies for non-model organisms.

Keywords: coastal lagoons, endangered species, non-model organism, target capture method

Procedia PDF Downloads 173
4002 Association of Major Histocompatibility Complex Alleles with Antibody Response to Newcastle Vaccine in Chicken

Authors: Atefeh Esmailnejad, Gholam Reza Nikbakht Brujeni

Abstract:

The major histocompatibility complex (MHC) is the best-characterized genetic region associated with susceptibility and/or resistance to a wide range of infectious diseases, autoimmune diseases and immune responses to vaccines. It has been demonstrated that there is an association between the MHC and resistance to Marek disease, Newcastle disease, Rous sarcoma tumor, Avian leucosis, Fowl cholera, Salmonellosis and Pasteurellosis in chicken. The present study evaluated the MHC polymorphism and its association with antibody response to Newcastle (ND) vaccine in Iranian native chickens. The MHC polymorphism was investigated using LEI0258 microsatellite locus by PCR-based fragment analysis. LEI0258 microsatellite marker is a genetic indicator for MHC, which is located on microchromosome 16 and strongly associated with serologically defined MHC haplotypes. Antibody titer against ND vaccine was measured by Haemaglutination Inhibition (HI) assay. Statistical analysis was performed using SPSS software (version 21). Total of 13 LEI0258 microsatellite alleles were identified in 72 samples which indicated a high genetic diversity in the population. The association study revealed a significant influence of MHC alleles on immune responses to Newcastle vaccine. 311 and 313 bp alleles were significantly associated with elevated immune responses to Newcastle vaccine (p<0.05). These results would be applicable in designing and improving the populations under selective breeding.

Keywords: chicken, LEI0258, MHC, Newcastle vaccine

Procedia PDF Downloads 419
4001 Genomics of Adaptation in the Sea

Authors: Agostinho Antunes

Abstract:

The completion of the human genome sequencing in 2003 opened a new perspective into the importance of whole genome sequencing projects, and currently multiple species are having their genomes completed sequenced, from simple organisms, such as bacteria, to more complex taxa, such as mammals. This voluminous sequencing data generated across multiple organisms provides also the framework to better understand the genetic makeup of such species and related ones, allowing to explore the genetic changes underlining the evolution of diverse phenotypic traits. Here, recent results from our group retrieved from comparative evolutionary genomic analyses of selected marine animal species will be considered to exemplify how gene novelty and gene enhancement by positive selection might have been determinant in the success of adaptive radiations into diverse habitats and lifestyles.

Keywords: marine genomics, evolutionary bioinformatics, human genome sequencing, genomic analyses

Procedia PDF Downloads 596
4000 Microwave Imaging by Application of Information Theory Criteria in MUSIC Algorithm

Authors: Majid Pourahmadi

Abstract:

The performance of time-reversal MUSIC algorithm will be dramatically degrades in presence of strong noise and multiple scattering (i.e. when scatterers are close to each other). This is due to error in determining the number of scatterers. The present paper provides a new approach to alleviate such a problem using an information theoretic criterion referred as minimum description length (MDL). The merits of the novel approach are confirmed by the numerical examples. The results indicate the time-reversal MUSIC yields accurate estimate of the target locations with considerable noise and multiple scattering in the received signals.

Keywords: microwave imaging, time reversal, MUSIC algorithm, minimum description length (MDL)

Procedia PDF Downloads 318
3999 The Quotation-Based Algorithm for Distributed Decision Making

Authors: Gennady P. Ginkul, Sergey Yu. Soloviov

Abstract:

The article proposes to use so-called "quotation-based algorithm" for simulation of decision making process in distributed expert systems and multi-agent systems. The idea was adopted from the techniques for group decision-making. It is based on the assumption that one expert system to perform its logical inference may use rules from another expert system. The application of the algorithm was demonstrated on the example in which the consolidated decision is the decision that requires minimal quotation.

Keywords: backward chaining inference, distributed expert systems, group decision making, multi-agent systems

Procedia PDF Downloads 362
3998 On the Absence of BLAD, CVM, DUMPS and BC Autosomal Recessive Mutations in Stud Bulls of the Local Alatau Cattle Breed of the Republic of Kazakhstan

Authors: Yessengali Ussenbekov, Valery Terletskiy, Orik Zhanserkenova, Shynar Kasymbekova, Indira Beyshova, Aitkali Imanbayev, Almas Serikov

Abstract:

Currently, there are 46 hereditary diseases afflicting cattle with known molecular genetic diagnostic methods developed for them. Genetic anomalies frequently occur in the Holstein cattle breeds from American and Canadian bloodlines. The data on the incidence of BLAD, CVM, DUMPS and BC autosomal recessive lethal mutations in pedigree animals are discordant, the detrimental allele incidence rates are high for the Holstein cattle breed, whereas the incidence rates of these mutations are low in some breeds or they are completely absent. Data were obtained on the basis of frozen semen of stud bulls. DNA was extracted from the semen with the DNA-Sorb-B extraction kit. The lethal mutation in the genes CD18, SLC35A3, UMP and ASS of Alatau stud bulls (N=124) was detected by polymerase chain reaction and RFLP analysis. It was established that stud bulls of the local Alatau breed were not carriers of the BLAD, CVM, DUMPS, and BC detrimental mutations. However, with a view to preventing the dissemination of hereditary diseases it is recommended to monitor the pedigree stock using molecular genetic methods.

Keywords: PCR, autosomal recessive point mutation, BLAD, CVM, DUMPS, BC, stud bulls

Procedia PDF Downloads 428
3997 A Highly Efficient Broadcast Algorithm for Computer Networks

Authors: Ganesh Nandakumaran, Mehmet Karaata

Abstract:

A wave is a distributed execution, often made up of a broadcast phase followed by a feedback phase, requiring the participation of all the system processes before a particular event called decision is taken. Wave algorithms with one initiator such as the 1-wave algorithm have been shown to be very efficient for broadcasting messages in tree networks. Extensions of this algorithm broadcasting a sequence of waves using a single initiator have been implemented in algorithms such as the m-wave algorithm. However as the network size increases, having a single initiator adversely affects the message delivery times to nodes further away from the initiator. As a remedy, broadcast waves can be allowed to be initiated by multiple initiator nodes distributed across the network to reduce the completion time of broadcasts. These waves initiated by one or more initiator processes form a collection of waves covering the entire network. Solutions to global-snapshots, distributed broadcast and various synchronization problems can be solved efficiently using waves with multiple concurrent initiators. In this paper, we propose the first stabilizing multi-wave sequence algorithm implementing waves started by multiple initiator processes such that every process in the network receives at least one sequence of broadcasts. Due to being stabilizing, the proposed algorithm can withstand transient faults and do not require initialization. We view a fault as a transient fault if it perturbs the configuration of the system but not its program.

Keywords: distributed computing, multi-node broadcast, propagation of information with feedback and cleaning (PFC), stabilization, wave algorithms

Procedia PDF Downloads 488
3996 Analysis of ECGs Survey Data by Applying Clustering Algorithm

Authors: Irum Matloob, Shoab Ahmad Khan, Fahim Arif

Abstract:

As Indo-pak has been the victim of heart diseases since many decades. Many surveys showed that percentage of cardiac patients is increasing in Pakistan day by day, and special attention is needed to pay on this issue. The framework is proposed for performing detailed analysis of ECG survey data which is conducted for measuring the prevalence of heart diseases statistics in Pakistan. The ECG survey data is evaluated or filtered by using automated Minnesota codes and only those ECGs are used for further analysis which is fulfilling the standardized conditions mentioned in the Minnesota codes. Then feature selection is performed by applying proposed algorithm based on discernibility matrix, for selecting relevant features from the database. Clustering is performed for exposing natural clusters from the ECG survey data by applying spectral clustering algorithm using fuzzy c means algorithm. The hidden patterns and interesting relationships which have been exposed after this analysis are useful for further detailed analysis and for many other multiple purposes.

Keywords: arrhythmias, centroids, ECG, clustering, discernibility matrix

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