Search results for: Automated solution

Authors: Christian A. Romero, Tanja Grkovic, John. R. J. French, D. İpek. Kurtböke, Ronald J. Quinn

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A high-throughput and automated 1H NMR metabolic fingerprinting dereplication approach was used to accelerate the discovery of unknown bioactive secondary metabolites. The applied dereplication strategy accelerated the discovery of new natural products, provided rapid and competent identification and quantification of the known secondary metabolites and avoided time-consuming isolation procedures. The effectiveness of the technique was demonstrated by the isolation and elucidation of arglecins B (1), C (2) and actinofuranosin A (3) from a termite-gut associated Streptomyces sp. (USC 597) grown under solid state fermentation. The structures of these compounds were elucidated by extensive interpretation of 1H, 13C and 2D NMR spectroscopic data. These represent the first report of arglecin analogues isolated from a termite gut-associated Streptomyces species.

Keywords: Actinomycetes, actinofuranosin, antibiotics, arglecins, NMR spectroscopy.

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Authors: Arun Prasad Jaganathan

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In today's rapidly evolving technological landscape, the need for efficient and proactive maintenance management solutions has become increasingly evident across various industries. Traditional approaches often suffer from drawbacks such as reactive strategies, leading to potential downtime, increased costs, and decreased operational efficiency. In response to these challenges, this paper proposes an AI-enabled approach to object-based maintenance management aimed at enhancing reliability and efficiency. The paper contributes to the growing body of research on AI-driven maintenance management systems, highlighting the transformative impact of intelligent technologies on enhancing object reliability and operational efficiency.

Keywords: AI, machine learning, predictive maintenance, object-based maintenance, expert team scheduling.

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Authors: Yongxin Yuan

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In this paper, we first give the representation of the general solution of the following inverse eigenvalue problem (IEP): Given X ∈ Rn×p and a diagonal matrix Λ ∈ Rp×p, find nontrivial real-valued symmetric arrow-head matrices A and B such that AXΛ = BX. We then consider an optimal approximation problem: Given real-valued symmetric arrow-head matrices A, ˜ B˜ ∈ Rn×n, find (A, ˆ Bˆ) ∈ SE such that Aˆ − A˜2 + Bˆ − B˜2 = min(A,B)∈SE (A−A˜2 +B −B˜2), where SE is the solution set of IEP. We show that the optimal approximation solution (A, ˆ Bˆ) is unique and derive an explicit formula for it.

Keywords: Partially prescribed spectral information, symmetric arrow-head matrix, inverse problem, optimal approximation.

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Authors: Min-Ah Woo, Min-Cheol Lim, Hyun-Joo Chang, Sung-Wook Choi

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We developed a paper-based colorimetric sensor utilizing magnetic nanoparticles conjugated with aptamers (MNP-Apts) against E. coli O157:H7. The MNP-Apts were applied to a test sample solution containing the target cells, and the solution was simply dropped onto PVDF (polyvinylidene difluoride) membrane. The membrane moves the sample radially to form the sample spots of different compounds as concentric rings, thus the MNP-Apts on the membrane enabled specific recognition of the target cells through a color ring generation by MNP-promoted colorimetric reaction of TMB (3,3',5,5'-tetramethylbenzidine) and H₂O₂. This method could be applied to rapidly and visually detect various bacterial pathogens in less than 1 h without cell culturing.

Keywords: Aptamer, colorimetric sensor, E. coli O157:H7, magnetic nanoparticle, polyvinylidene difluoride.

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Authors: A. R. Rahmani, H. R. Ghaffari, M. T. Samadi

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The present work was conducted for Arsenic (III) removal, which one of the most poisonous groundwater pollutants, by synthetic nano size zerovalent iron (nZVI). Batch experiments were performed to investigate the influence of As (III), nZVI concentration, pH of solution and contact time on the efficiency of As (III) removal. nZVI was synthesized by reduction of ferric chloride by sodium borohydrid. SEM and XRD were used to determine particle size and characterization of produced nanoparticles. Up to 99.9% removal efficiency for arsenic (III) was obtained by nZVI dosage of 1 g/L at time equal to 10 min. and pH=7. It could be concluded that the removal efficiency were enhanced with increasing of ZVI dosage and reaction time, but decreased with increasing of arsenic concentration and pH for nano sized ZVI. nZVI presented an outstanding ability to remove As (III) due to not only a high surface area and low particle size but also to high inherent activity.

Keywords: Arsenic removal, aqueous solution, zero valent iron.

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Authors: Cherry Oo, Hnin Min Oo

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Software bug localization is one of the most costly tasks in program repair technique. Therefore, there is a high claim for automated bug localization techniques that can monitor programmers to the locations of bugs, with slight human arbitration. Spectrum-based bug localization aims to help software developers to discover bugs rapidly by investigating abstractions of the program traces to make a ranking list of most possible buggy modules. Using the Apache Commons Math library project, we study the diagnostic accuracy using our spectrum-based bug localization metric. Our outcomes show that the greater performance of a specific similarity coefficient, used to inspect the program spectra, is mostly effective on localizing of single line bugs.

Keywords: Software testing, fault localization, program spectra.

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Authors: Sallehan Ismail, Mahyuddin Ramli

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This paper reports on the influence of surface-treated coarse recycled concrete aggregate (RCA) on developing the compressive strength of concrete. The coarse RCA was initially treated by separately impregnating it in calcium metasilicate (CM) or wollastonite and nanosilica (NS) prepared at various concentrations. The effects of both treatment materials on concrete properties (e.g., slump, density and compressive strength) were evaluated. Scanning electron microscopy (SEM) analysis was performed to examine the microstructure of the resulting concrete. Results show that the effective use of treated coarse RCA significantly enhances the compressive strength of concrete. This result is supported by the SEM analysis, which indicates the formation of a dense interface between the treated coarse RCA and the cement matrix. Coarse RCA impregnated in CM solution results in better concrete strength than NS, and the optimum concentration of CM solution recommended for treated coarse RCA is 10%.

Keywords: Calcium metasilicate, compressive strength, nanosilica, recycled concrete aggregate.

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Authors: Benjamin Kuester, Bjoern Eilert, Malte Stonis, Ludger Overmeyer

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Increasing quality requirements make reliable and effective quality management indispensable. This includes the complaint handling in which the 8D method is widely used. The 8D report as a written documentation of the 8D method is one of the key quality documents as it internally secures the quality standards and acts as a communication medium to the customer. In practice, however, the 8D report is mostly faulty and of poor quality. There is no quality control of 8D reports today. This paper describes the use of natural language processing for the automated evaluation of 8D reports. Based on semantic analysis and text-mining algorithms the presented system is able to uncover content and formal quality deficiencies and thus increases the quality of the complaint processing in the long term.

Keywords: 8D report, complaint management, evaluation system, text-mining.

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Authors: Jihyung Kim, Taejin Kim, Sungho Park, Jun-Dong Cho

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A conventional binding method for low power in a high-level synthesis mainly focuses on finding an optimal binding for an assumed input data, and obtains only one binding table. In this paper, we show that a binding method which uses multiple binding tables gets better solution compared with the conventional methods which use a single binding table, and propose a dynamic bus binding scheme for low power using multiple binding tables. The proposed method finds multiple binding tables for the proper partitions of an input data, and switches binding tables dynamically to produce the minimum total switching activity. Experimental result shows that the proposed method obtains a binding solution having 12.6-28.9% smaller total switching activity compared with the conventional methods.

Keywords: low power, bus binding, switching activity, multiplebinding tables

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Authors: Amrita Tripathi, Neeru Adlakha

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Calcium [Ca2+] dynamics is studied as a potential form of neuron excitability that can control many irregular processes like metabolism, secretion etc. Ca2+ ion enters presynaptic terminal and increases the synaptic strength and thus triggers the neurotransmitter release. The modeling and analysis of calcium dynamics in neuron cell becomes necessary for deeper understanding of the processes involved. A mathematical model has been developed for cylindrical shaped neuron cell by incorporating physiological parameters like buffer, diffusion coefficient, and association rate. Appropriate initial and boundary conditions have been framed. The closed form solution has been developed in terms of modified Bessel function. A computer program has been developed in MATLAB 7.11 for the whole approach.

Keywords: Laplace Transform, Modified Bessel function, reaction diffusion equation, diffusion coefficient, excess buffer, calcium influx

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Authors: B. Navayineya, J. Vaseghi Amiri, M. Alijani Ardeshir

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Hydrodynamic pressures acting on upstream of concrete dams during an earthquake are an important factor in designing and assessing the safety of these structures in Earthquake regions. Due to inherent complexities, assessing exact hydrodynamic pressure is only feasible for problems with simple geometry. In this research, the governing equation of concrete gravity dam reservoirs with effect of fluid viscosity in frequency domain is solved and then compared with that in which viscosity is assumed zero. The results show that viscosity influences the reservoir-s natural frequency. In excitation frequencies near the reservoir's natural frequencies, hydrodynamic pressure has a considerable difference in compare to the results of non-viscose fluid.

Keywords: Closed form solution, concrete dams reservoir, viscosity, dynamic loads, hydrodynamic pressure.

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Authors: F. Ekoue, A. Fouache d'Halloy, D. Gigon, G Plantamp, E. Zajdman

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This work focuses on analysis of classical heat transfer equation regularized with Maxwell-Cattaneo transfer law. Computer simulations are performed in MATLAB environment. Numerical experiments are first developed on classical Fourier equation, then Maxwell-Cattaneo law is considered. Corresponding equation is regularized with a balancing diffusion term to stabilize discretizing scheme with adjusted time and space numerical steps. Several cases including a convective term in model equations are discussed, and results are given. It is shown that limiting conditions on regularizing parameters have to be satisfied in convective case for Maxwell-Cattaneo regularization to give physically acceptable solutions. In all valid cases, uniform convergence to solution of initial heat equation with Fourier law is observed, even in nonlinear case.

Keywords: Maxwell-Cattaneo heat transfers equations, fourierlaw, heat conduction, numerical solution.

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Authors: Chuanjian Wang, Changfu Liu, Zhengde Dai

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In this paper, the direct AnsAz method is used for constructing the multi-wave solutions to the (2+1)-dimensional extension of the Korteweg de-Vries (shortly EKdV) equation. A new breather type of three-wave solutions including periodic breather type soliton solution, breather type of two-solitary solution are obtained. Some cases with specific values of the involved parameters are plotted for each of the three-wave solutions. Mechanical features of resonance interaction among the multi-wave are discussed. These results enrich the variety of the dynamics of higher-dimensional nonlinear wave field.

Keywords: EKdV equation, Breather, Soliton, Bilinear form, The direct AnsAz method.

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Authors: Khaled Moaddy

Abstract:

In this paper, we present a fast and accurate numerical scheme for the solution of a Laplace equation with Dirichlet boundary conditions. The non-standard finite difference scheme (NSFD) is applied to construct the numerical solutions of a Laplace equation with two different Dirichlet boundary conditions. The solutions obtained using NSFD are compared with the solutions obtained using the standard finite difference scheme (SFD). The NSFD scheme is demonstrated to be reliable and efficient.

Keywords: Standard finite difference schemes, non–standard schemes, Laplace equation, Dirichlet boundary conditions.

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Authors: A.Atash J ameh

Abstract:

Sarkhoon gas plant, located in south of Iran, has been installed to removal H2S contained in a high pressure natural gas stream. The solvent used for the H2S removal from gaseous stream is 34% by weight (wt%) Di-ethanol amine (DEA) solutions. Due to increasing concentration of heat stable salt (HSS) in solvent, corrosivity of amine solution had been increased. Reports indicated that there was corrosion on the shell of regeneration column. Because source formation of HSS was unknown, we decided to control the amount of HSS at the limit less than 3% wt amine solvent. Therefore, two small columns were filled by strong anionic base and carbon active, and then polluted amine was passed through beds. Finally a temporary amine recovery package on industrial scale was made based on laboratory’s results. From economical point of view we could save $700000 beside corrosion occurrence of the stripping column has been vigorously decreased.

Keywords: Amines, corrosion, heat stable salt, resin anionic.

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Authors: Suraiya Jabin, Kamal K. Bharadwaj

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In the recent past Learning Classifier Systems have been successfully used for data mining. Learning Classifier System (LCS) is basically a machine learning technique which combines evolutionary computing, reinforcement learning, supervised or unsupervised learning and heuristics to produce adaptive systems. A LCS learns by interacting with an environment from which it receives feedback in the form of numerical reward. Learning is achieved by trying to maximize the amount of reward received. All LCSs models more or less, comprise four main components; a finite population of condition–action rules, called classifiers; the performance component, which governs the interaction with the environment; the credit assignment component, which distributes the reward received from the environment to the classifiers accountable for the rewards obtained; the discovery component, which is responsible for discovering better rules and improving existing ones through a genetic algorithm. The concatenate of the production rules in the LCS form the genotype, and therefore the GA should operate on a population of classifier systems. This approach is known as the 'Pittsburgh' Classifier Systems. Other LCS that perform their GA at the rule level within a population are known as 'Mitchigan' Classifier Systems. The most predominant representation of the discovered knowledge is the standard production rules (PRs) in the form of IF P THEN D. The PRs, however, are unable to handle exceptions and do not exhibit variable precision. The Censored Production Rules (CPRs), an extension of PRs, were proposed by Michalski and Winston that exhibit variable precision and supports an efficient mechanism for handling exceptions. A CPR is an augmented production rule of the form: IF P THEN D UNLESS C, where Censor C is an exception to the rule. Such rules are employed in situations, in which conditional statement IF P THEN D holds frequently and the assertion C holds rarely. By using a rule of this type we are free to ignore the exception conditions, when the resources needed to establish its presence are tight or there is simply no information available as to whether it holds or not. Thus, the IF P THEN D part of CPR expresses important information, while the UNLESS C part acts only as a switch and changes the polarity of D to ~D. In this paper Pittsburgh style LCSs approach is used for automated discovery of CPRs. An appropriate encoding scheme is suggested to represent a chromosome consisting of fixed size set of CPRs. Suitable genetic operators are designed for the set of CPRs and individual CPRs and also appropriate fitness function is proposed that incorporates basic constraints on CPR. Experimental results are presented to demonstrate the performance of the proposed learning classifier system.

Keywords: Censored Production Rule, Data Mining, GeneticAlgorithm, Learning Classifier System, Machine Learning, PittsburgApproach, , Reinforcement learning.

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Authors: Mohammad Ali Zazouli, Farzaneh Veisi, Amir Veisi

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Bisphenol A (BPA) is an organic synthetic compound that has many applications in various industries and is known as persistent pollutant. The aim of this research was to evaluate the efficiency of bone ash and banana peel as adsorbents for BPA adsorption from aqueous solution by using Response Surface Methodology. The effects of some variables such as sorbent dose, detention time, solution pH, and BPA concentration on the sorption efficiency was examined. All analyses were carried out according to Standard Methods. The sample size was performed using Box-Benken design and also optimization of BPA removal was done using response surface methodology (RSM). The results showed that the BPA adsorption increases with increasing of contact time and BPA concentration. However, it decreases with higher pH. More adsorption efficiency of a banana peel is very smaller than a bone ash so that BPA removal for bone ash and banana peel is 62 and 28 percent, respectively. It is concluded that a bone ash has a good ability for the BPA adsorption.

Keywords: Adsorbent, banana peel, bisphenol A (BPA), bone ash, wastewater treatment.

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Authors: Adam Sobey, James Blake, Ajit Shenoi

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The leisure boatbuilding industry has tight profit margins that demand that boats are created to a high quality but with low cost. This requirement means reduced design times combined with increased use of design for production can lead to large benefits. The evolutionary nature of the boatbuilding industry can lead to a large usage of previous vessels in new designs. With the increase in automated tools for concurrent engineering within structural design it is important that these tools can reuse this information while subsequently feeding this to designers. The ability to accurately gather this materials and parts data is also a key component to these tools. This paper therefore aims to develop an architecture made up of neural networks and databases to feed information effectively to the designers based on previous design experience.

Keywords:

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Authors: R. Simutis, V. Galvanauskas, D. Levisauskas, J. Repsyte

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This paper proposes a bioprocess optimization procedure based on Relevance Vector Regression models and evolutionary programming technique. Relevance Vector Regression scheme allows developing a compact and stable data-based process model avoiding time-consuming modeling expenses. The model building and process optimization procedure could be done in a half-automated way and repeated after every new cultivation run. The proposed technique was tested in a simulated mammalian cell cultivation process. The obtained results are promising and could be attractive for optimization of industrial bioprocesses.

Keywords: Bioprocess optimization, Evolutionary programming, Relevance Vector Regression.

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Authors: S. Adhirai, R. P. Mahapatra, Paramjit Singh

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Optimization is an important tool in making decisions and in analysing physical systems. In mathematical terms, an optimization problem is the problem of finding the best solution from among the set of all feasible solutions. The paper discusses the Whale Optimization Algorithm (WOA), and its applications in different fields. The algorithm is tested using MATLAB because of its unique and powerful features. The benchmark functions used in WOA algorithm are grouped as: unimodal (F1-F7), multimodal (F8-F13), and fixed-dimension multimodal (F14-F23). Out of these benchmark functions, we show the experimental results for F7, F11, and F19 for different number of iterations. The search space and objective space for the selected function are drawn, and finally, the best solution as well as the best optimal value of the objective function found by WOA is presented. The algorithmic results demonstrate that the WOA performs better than the state-of-the-art meta-heuristic and conventional algorithms.

Keywords: Optimization, optimal value, objective function, optimization problems, meta-heuristic optimization algorithms, Whale Optimization Algorithm, Implementation, MATLAB.

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Authors: A. Javed, K. Djidjeli, J. T. Xing

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The concept of adaptive shape parameters (ASP) has been presented for solution of incompressible Navier Strokes equations using mesh-free local Radial Basis Functions (RBF). The aim is to avoid ill-conditioning of coefficient matrices of RBF weights and inaccuracies in RBF interpolation resulting from non-optimized shape of basis functions for the cases where data points (or nodes) are not distributed uniformly throughout the domain. Unlike conventional approaches which assume globally similar values of RBF shape parameters, the presented ASP technique suggests that shape parameter be calculated exclusively for each data point (or node) based on the distribution of data points within its own influence domain. This will ensure interpolation accuracy while still maintaining well conditioned system of equations for RBF weights. Performance and accuracy of ASP technique has been tested by evaluating derivatives and laplacian of a known function using RBF in Finite difference mode (RBFFD), with and without the use of adaptivity in shape parameters. Application of adaptive shape parameters (ASP) for solution of incompressible Navier Strokes equations has been presented by solving lid driven cavity flow problem on mesh-free domain using RBF-FD. The results have been compared for fixed and adaptive shape parameters. Improved accuracy has been achieved with the use of ASP in RBF-FD especially at regions where larger gradients of field variables exist.

Keywords: CFD, Meshless Particle Method, Radial Basis Functions, Shape Parameters

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Authors: H. Elbehiery, A. Hefnawy, M. Elewa

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Quality control in ceramic tile manufacturing is hard, labor intensive and it is performed in a harsh industrial environment with noise, extreme temperature and humidity. It can be divided into color analysis, dimension verification, and surface defect detection, which is the main purpose of our work. Defects detection is still based on the judgment of human operators while most of the other manufacturing activities are automated so, our work is a quality control enhancement by integrating a visual control stage using image processing and morphological operation techniques before the packing operation to improve the homogeneity of batches received by final users.

Keywords: Quality control, Defects detection, Visual control, Image processing, Morphological operation

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Authors: R. Maier, S. Thalmann, A. Sandow

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Organizations face challenges supporting knowledge workers due to their particular requirements for an environment supportive of their self-guided learning activities which are important to increase their productivity and to develop creative solutions to non-routine problems. Face-to-face knowledge sharing remains crucial in spite of a large number of knowledge management instruments that aim at supporting a more impersonal transfer of knowledge. This paper first describes the main criteria for a conceptual and technical solution targeted at flexible management of office space that aims at assigning those knowledge workers to the same room that are most likely to thrive when being brought together thus enhancing their knowledge work productivity. The paper reflects on lessons learned from the implementation and operation of such a solution in a project-focused organization and derives several implications for future extensions that target to foster problem solving, informal learning and personal development.

Keywords: informal learning, knowledge work, officemanagement.

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Authors: Rosshairy Abd Rahman, Chooi-Leng Ang, Razamin Ramli

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Feed is one of the factors which play an important role in determining a successful development of an aquaculture industry. It is always critical to produce the best aquaculture diet at a minimum cost in order to trim down the operational cost and gain more profit. However, the feed mix problem becomes increasingly difficult since many issues need to be considered simultaneously. Thus, the purpose of this paper is to review the current techniques used by nutritionist and researchers to tackle the issues. Additionally, this paper introduce an enhance algorithm which is deemed suitable to deal with all the issues arise. The proposed technique refers to Hybrid Genetic Algorithm which is expected to obtain the minimum cost diet for farmed animal, while satisfying nutritional requirements. Hybrid GA technique with artificial bee algorithm is expected to reduce the penalty function and provide a better solution for the feed mix problem.

Keywords: Artificial bee algorithm, feed mix problem, hybrid genetic algorithm.

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Authors: Divyanka Sontakke, Arpit Thakre, D. K Shinde, Sujata Parmeshwaran

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Electrospinning is the most widely utilized method to create nanofibers because of the direct setup, the capacity to mass-deliver consistent nanofibers from different polymers, and the ability to produce ultrathin fibers with controllable diameters. Smooth and much arranged ultrafine Polyacrylonitrile (PAN) nanofibers with diameters going from submicron to nanometer were delivered utilizing Electrospinning technique. PAN powder was used as a precursor to prepare the solution utilized as a part of this process. At the point when the electrostatic repulsion contradicted surface tension, a charged stream of polymer solution was shot out from the head of the spinneret and along these lines ultrathin nonwoven fibers were created. The effect of electrospinning parameter such as applied voltage, feed rate, concentration of polymer solution and tip to collector distance on the morphology of electrospun PAN nanofibers were investigated. The nanofibers were heat treated for carbonization to examine the changes in properties and composition to make for electrical application. Scanning Electron Microscopy (SEM) was performed before and after carbonization to study electrical conductivity and morphological characterization. The SEM images have shown the uniform fiber diameter and no beads formation. The average diameter of the PAN fiber observed 365nm and 280nm for flat plat and rotating drum collector respectively. The four probe strategy was utilized to inspect the electrical conductivity of the nanofibers and the electrical conductivity is significantly improved with increase in oxidation temperature exposed.

Keywords: Electrospinning, polyacrylonitrile carbon nanofibres, heat treatment, electrical conductivity.

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Authors: Zanariah Abdul Majid, Mohamed Suleiman

Abstract:

The aim of this paper is to investigate the performance of the developed two point block method designed for two processors for solving directly non stiff large systems of higher order ordinary differential equations (ODEs). The method calculates the numerical solution at two points simultaneously and produces two new equally spaced solution values within a block and it is possible to assign the computational tasks at each time step to a single processor. The algorithm of the method was developed in C language and the parallel computation was done on a parallel shared memory environment. Numerical results are given to compare the efficiency of the developed method to the sequential timing. For large problems, the parallel implementation produced 1.95 speed-up and 98% efficiency for the two processors.

Keywords: Numerical methods, parallel method, block method, higher order ODEs.

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Authors: R. Xu, X. Zhao, X. Li, C. Kwan, C.-I Chang

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An image texture analysis and target recognition approach of using an improved image texture feature coding method (TFCM) and Support Vector Machine (SVM) for target detection is presented. With our proposed target detection framework, targets of interest can be detected accurately. Cascade-Sliding-Window technique was also developed for automated target localization. Application to mammogram showed that over 88% of normal mammograms and 80% of abnormal mammograms can be correctly identified. The approach was also successfully applied to Synthetic Aperture Radar (SAR) and Ground Penetrating Radar (GPR) images for target detection.

Keywords: Image texture analysis, feature extraction, target detection, pattern classification.

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Authors: Qasim M. Kriri

Abstract:

Few Saudi Arabia production companies face financial profit issues until this moment. This work presents a linear integer programming model that solves a production problem of a Saudi Food Company in Saudi Arabia. An optimal solution to the above-mentioned problem is a Linear Programming solution. In this regard, the main purpose of this project is to maximize profit. Linear Programming Technique has been used to derive the maximum profit from production of natural juice at Saudi Food Co. The operations of production of the company were formulated and optimal results are found out by using Lindo Software that employed Sensitivity Analysis and Parametric linear programming in order develop Linear Programming. In addition, the parameter values are increased, then the values of the objective function will be increased.

Keywords: Parameter linear programming, objective function, sensitivity analysis, optimize profit.

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Authors: R. Amooaghaie

Abstract:

Principally, plants grown in soilless culture may be attacked by the same pests and diseases as cultivated traditionally in soil. The most destructive phytopathogens are fungi, such as Phythium, Phytophthora and Fusarium, followed by viruses, bacteria and nematodes. We investigated effect of carbon nanotube filters on disease management of soilless culture. Tomato seedlings transplant in plastic pots filled with a soilless media of vermiculite. The crop irrigated and fertilized using a hydroponic nutrient solution. We used carbon nanotube filters for nutrient solution disinfection. Our results show that carbon nanotube filtration significantly reduces pathogens on tomato plants. Fungal elimination (Fusarium oxysporum and Pythium spp.) was usually successful at about 96 to 99.9% all over the cultural season. It is seem that in tomato soilless culture, nanofiltration constitutes a reliable method that allows control of the development of diseases caused by pathogenic fungi

Keywords: Fusarium oxysporum, Nanofilteration, Pythium spp., Soilless culture, Tomato

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Authors: M. F. Omar, R. A. Salam, R. Abdullah, N. A. Rashid

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Proteins or genes that have similar sequences are likely to perform the same function. One of the most widely used techniques for sequence comparison is sequence alignment. Sequence alignment allows mismatches and insertion/deletion, which represents biological mutations. Sequence alignment is usually performed only on two sequences. Multiple sequence alignment, is a natural extension of two-sequence alignment. In multiple sequence alignment, the emphasis is to find optimal alignment for a group of sequences. Several applicable techniques were observed in this research, from traditional method such as dynamic programming to the extend of widely used stochastic optimization method such as Genetic Algorithms (GAs) and Simulated Annealing. A framework with combination of Genetic Algorithm and Simulated Annealing is presented to solve Multiple Sequence Alignment problem. The Genetic Algorithm phase will try to find new region of solution while Simulated Annealing can be considered as an alignment improver for any near optimal solution produced by GAs.

Keywords: Simulated annealing, genetic algorithm, sequence alignment, multiple sequence alignment.

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