Search results for: Modified artificial bee colony.

Authors: Jagabondhu Hazra, Avinash Sinha

Abstract:

Economic dispatch problem is an optimization problem where objective function is highly non linear, non-convex, non-differentiable and may have multiple local minima. Therefore, classical optimization methods may not converge or get trapped to any local minima. This paper presents a comparative study of four different evolutionary algorithms i.e. genetic algorithm, bacteria foraging optimization, ant colony optimization and particle swarm optimization for solving the economic dispatch problem. All the methods are tested on IEEE 30 bus test system. Simulation results are presented to show the comparative performance of these methods.

Keywords: Ant colony optimization, bacteria foraging optimization, economic dispatch, evolutionary algorithm, genetic algorithm, particle swarm optimization.

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Authors: Seyed Abbas Tabatabaei

Abstract:

One of the important factors of cracks on the asphalt pavements is bitumen aging that associated with the loss of volatile components and oxidation of asphalt binder. This paper is about effect of Styrene-Butadiene-Styrene (SBS) polymer on asphalt aging In order to decrease asphalt aging effects. For this purpose samples of base bitumen and SBS modified bitumen aged according to the rolling thin film oven test (RTFOT) and pressure aging vessel (PAV), respectively. Properties of each sample were evaluated using Fourier Transform Infrared (FTIR) spectroscopy, n-heptane precipitation, viscosity test, softening point test and penetration test. FT-IR Analysis, showed lower oxidation of SBS modified bitumen than base bitumen, after aging.

Keywords: SBS, Asphalt aging, modified bitumen.

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Authors: Lipeng Zhang, Limei Li, Yanming Pearl Zhang

Abstract:

This paper takes a philosophical view as axiom, and reveals the relationship between information theory and Natural Intelligence and Artificial Intelligence under real world conditions. This paper also derives the relationship between natural intelligence and nature. According to communication principle of information theory, Natural Intelligence can be divided into real part and virtual part. Based on information theory principle that Information does not increase, the restriction mechanism of Natural Intelligence creativity is conducted. The restriction mechanism of creativity reveals the limit of natural intelligence and artificial intelligence. The paper provides a new angle to observe natural intelligence and artificial intelligence.

Keywords: Natural intelligence, artificial intelligence, creativity, information theory.

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Authors: Axay J Mehta, Hema A Mehta, T.C.Manjunath, C. Ardil

Abstract:

In this paper, the modelling and design of artificial neural network architecture for load forecasting purposes is investigated. The primary pre-requisite for power system planning is to arrive at realistic estimates of future demand of power, which is known as Load Forecasting. Short Term Load Forecasting (STLF) helps in determining the economic, reliable and secure operating strategies for power system. The dependence of load on several factors makes the load forecasting a very challenging job. An over estimation of the load may cause premature investment and unnecessary blocking of the capital where as under estimation of load may result in shortage of equipment and circuits. It is always better to plan the system for the load slightly higher than expected one so that no exigency may arise. In this paper, a load-forecasting model is proposed using a multilayer neural network with an appropriately modified back propagation learning algorithm. Once the neural network model is designed and trained, it can forecast the load of the power system 24 hours ahead on daily basis and can also forecast the cumulative load on daily basis. The real load data that is used for the Artificial Neural Network training was taken from LDC, Gujarat Electricity Board, Jambuva, Gujarat, India. The results show that the load forecasting of the ANN model follows the actual load pattern more accurately throughout the forecasted period.

Keywords: Power system, Load forecasting, Neural Network, Neuron, Stabilization, Network structure, Load.

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Authors: P. Gnanasekar, A. Nagappan, S. Sharavanan, O. Saravanan, D. Vinodkumar, T. Elayabharathi, G. Karthik

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In this paper we present the deep study about the Bio- Medical Images and tag it with some basic extracting features (e.g. color, pixel value etc). The classification is done by using a nearest neighbor classifier with various distance measures as well as the automatic combination of classifier results. This process selects a subset of relevant features from a group of features of the image. It also helps to acquire better understanding about the image by describing which the important features are. The accuracy can be improved by increasing the number of features selected. Various types of classifications were evolved for the medical images like Support Vector Machine (SVM) which is used for classifying the Bacterial types. Ant Colony Optimization method is used for optimal results. It has high approximation capability and much faster convergence, Texture feature extraction method based on Gabor wavelets etc..

Keywords: ACO Ant Colony Optimization, Correlogram, CCM Co-Occurrence Matrix, RTS Rough-Set theory

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Authors: Artur Matuck, Guilherme F. Nobre

Abstract:

Machines can be either tool, media, or social agents. Advances in technology have been delivering machines capable of autonomous expression, both through communication and art. This paper deals with models (theoretical approach) and experiments (applied approach) related to artificial agents. On one hand it traces how social sciences' scholars have worked with topics such as text automatization, man-machine writing cooperation, and communication. On the other hand it covers how computer sciences' scholars have built communicative and artistic machines, including the programming of creativity. The aim is to present a brief survey on artificially intelligent communicators and artificially creative writers, and provide the basis to understand the meta-authorship and also to new and further man-machine co-authorship.

Keywords: Artificial communication, artificial creativity, artificial writers, meta-authorship, robotic art.

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Authors: A. López–Vásquez, D. Santamaría, M. Tibatá, C. Gómez

Abstract:

A study concerning the photocatalytic decolourization of Congo red (CR) dye, over artificial UV irradiation is presented. Photocatalysts based on a commercial titanium dioxide (TiO2) modified with transition metals (Ni, Cu and Zn) were used. The dopage method used was wet impregnation. A TiO2 sample without salt was subjected to the same hydrothermal treatment to be used as reference. Congo red solutions to several pH conditions (natural and basic) were used to evaluate photocatalytic performance of each doped catalysts. Photodecolourization percentage was measured spectrofotrometically after 3 h of treatment to 499 nm as response variable. Kinetics investigations of photodegradation indicated that reactions obey to Langmuir-Hinshelwood model and pseudo–first order law. The rate constant studies of photocatalytic decolourization reactions for Zn–TiO2 and Cu–TiO2 photocatalysts indicated that in all cases the rate constant of the reaction was higher than that of TiO2 undoped. These results show that nature of the metal modifying the TiO2 influence on the efficiency of the photocatalyst evaluated in process. Ni does not present an additional effect compared with TiO2, while Zn enhances the photoactivity due to its electronic properties.

Keywords: Congo red, Dopage, Photodecolourization, Titanium dioxide.

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Authors: A. Buasri, N. Chaiyut, K. Borvornchettanuwat, N. Chantanachai, K. Thonglor

Abstract:

Inorganic nanoparticles filled polymer composites have extended their multiple functionalities to various applications, including mechanical reinforcement, gas barrier, dimensional stability, heat distortion temperature, flame-retardant, and thermal conductivity. Sodium stearate-modified calcium carbonate (CaCO3) nanoparticles were prepared using surface modification method. The results showed that sodium stearate attached to the surface of CaCO3 nanoparticles with the chemical bond. The effect of modified CaCO3 nanoparticles on thermal properties of polypropylene (PP) was studied by means of differential scanning calorimetry (DSC) and Thermogravimetric analysis (TGA). It was found that CaCO3 significantly affected the crystallization temperature and crystallization degree of PP. Effect of the modified CaCO3 content on mechanical properties of PP/CaCO3 nanocomposites was also studied. The results showed that the modified CaCO3 can effectively improve the mechanical properties of PP. In comparison with PP, the impact strength of PP/CaCO3 nanocomposites increased by about 65% and the hardness increased by about 5%.

Keywords: Polypropylene Nanocomposites, Modified Calcium Carbonate, Sodium Stearate, Surface Treatment

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Authors: Mohammed Benbrahim, Adil Daoudi, Khalid Benjelloun, Aomar Ibenbrahim

Abstract:

The automatic discrimination of seismic signals is an important practical goal for earth-science observatories due to the large amount of information that they receive continuously. An essential discrimination task is to allocate the incoming signal to a group associated with the kind of physical phenomena producing it. In this paper, two classes of seismic signals recorded routinely in geophysical laboratory of the National Center for Scientific and Technical Research in Morocco are considered. They correspond to signals associated to local earthquakes and chemical explosions. The approach adopted for the development of an automatic discrimination system is a modular system composed by three blocs: 1) Representation, 2) Dimensionality reduction and 3) Classification. The originality of our work consists in the use of a new wavelet called "modified Mexican hat wavelet" in the representation stage. For the dimensionality reduction, we propose a new algorithm based on the random projection and the principal component analysis.

Keywords: Seismic signals, Wavelets, Dimensionality reduction, Artificial neural networks, Classification.

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Authors: Jolly Shah, S.S.Rattan, B.C.Nakra

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Automatic control of the robotic manipulator involves study of kinematics and dynamics as a major issue. This paper involves the forward and inverse kinematics of 2-DOF robotic manipulator with revolute joints. In this study the Denavit- Hartenberg (D-H) model is used to model robot links and joints. Also forward and inverse kinematics solution has been achieved using Artificial Neural Networks for 2-DOF robotic manipulator. It shows that by using artificial neural network the solution we get is faster, acceptable and has zero error.

Keywords: Artificial Neural Network, Forward Kinematics, Inverse Kinematics, Robotic Manipulator

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Authors: M. Seneewong-Na-Ayuttaya, T. Pongprayoon

Abstract:

The nanofiber sheet of Multiwall Cabon Nanotube (MWCNTs)/Polyacylonitile (PAN) composites was fabricated from electrospun nanofiber. Firstly the surface of MWCNTs was chemically modified, comparing two different techniques consisting of admicellar polymerization and functionalization to improve the dispersion and prevent the aggregation in the PAN matrix. The modified MWCNTs were characterized by the dispersion in dimethylformamide (DMF) solvent, Laser particle size, and FTRaman. Lastly, DSC, SEM and mechanical properties of the nanofiber sheet were examined. The results show that the mechanical properties of the nanofiber sheet prepared from admicellar polymerization-modified MWCNTs were higher than those of the others.

Keywords: Multiwall carbon nanotube, admicellar polymerization, functionalization, nanofiber sheet.

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Authors: U. Bottigli, M.Carpinelli, P.L. Fiori, B. Golosio, A. Marras, G. L. Masala, P. Oliva

Abstract:

The counting process of cell colonies is always a long and laborious process that is dependent on the judgment and ability of the operator. The judgment of the operator in counting can vary in relation to fatigue. Moreover, since this activity is time consuming it can limit the usable number of dishes for each experiment. For these purposes, it is necessary that an automatic system of cell colony counting is used. This article introduces a new automatic system of counting based on the elaboration of the digital images of cellular colonies grown on petri dishes. This system is mainly based on the algorithms of region-growing for the recognition of the regions of interest (ROI) in the image and a Sanger neural net for the characterization of such regions. The better final classification is supplied from a Feed-Forward Neural Net (FF-NN) and confronted with the K-Nearest Neighbour (K-NN) and a Linear Discriminative Function (LDF). The preliminary results are shown.

Keywords: Automatic cell counting, neural network, region growing, Sanger net.

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Authors: Khaled M. Alhawiti

Abstract:

This research study aims to present a retrospective study about speech recognition systems and artificial intelligence. Speech recognition has become one of the widely used technologies, as it offers great opportunity to interact and communicate with automated machines. Precisely, it can be affirmed that speech recognition facilitates its users and helps them to perform their daily routine tasks, in a more convenient and effective manner. This research intends to present the illustration of recent technological advancements, which are associated with artificial intelligence. Recent researches have revealed the fact that speech recognition is found to be the utmost issue, which affects the decoding of speech. In order to overcome these issues, different statistical models were developed by the researchers. Some of the most prominent statistical models include acoustic model (AM), language model (LM), lexicon model, and hidden Markov models (HMM). The research will help in understanding all of these statistical models of speech recognition. Researchers have also formulated different decoding methods, which are being utilized for realistic decoding tasks and constrained artificial languages. These decoding methods include pattern recognition, acoustic phonetic, and artificial intelligence. It has been recognized that artificial intelligence is the most efficient and reliable methods, which are being used in speech recognition.

Keywords: Speech recognition, acoustic phonetic, artificial intelligence, Hidden Markov Models (HMM), statistical models of speech recognition, human machine performance.

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Authors: K. A. Laptinskiy, S. A. Burikov, A. M. Vervald, S. A. Dolenko, T. A. Dolenko

Abstract:

The article presents the results of the application of artificial neural networks to separate the fluorescent contribution of nanodiamonds used as biomarkers, adsorbents and carriers of drugs in biomedicine, from a fluorescent background of own biological fluorophores. The principal possibility of solving this problem is shown. Use of neural network architecture let to detect fluorescence of nanodiamonds against the background autofluorescence of egg white with high accuracy - better than 3 ug/ml.

Keywords: Artificial neural networks, fluorescence, data aggregation.

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Authors: Nikol Žižková

Abstract:

The aim of this study was to observe the behavior of polymer-modified cement mortars with regard to the use of a pozzolanic admixture. Polymer-modified mortars (PMMs) containing various types of waste glass (waste packing glass and fluorescent tube glass) were produced always with 20% of cement substituted with a pozzolanic-active material. Ethylene/vinyl acetate copolymer (EVA) was used for polymeric modification. The findings confirm the possibility of using the waste glass examined herein as a partial substitute for cement in the production of PMM, which contributes to the preservation of non-renewable raw material resources and to the efficiency of waste glass material reuse.

Keywords: Recycled waste glass, polymer-modified mortars, pozzolanic admixture.

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Authors: Mohsen Soori, Fooad Karimi Ghaleh Jough

Abstract:

The integration of Artificial Intelligence (AI) techniques in the optimization of steel moment frame structures represents a transformative approach to enhance the design, analysis, and performance of these critical engineering systems. The review encompasses a wide spectrum of AI methods, including machine learning algorithms, evolutionary algorithms, neural networks, and optimization techniques, applied to address various challenges in the field. The synthesis of research findings highlights the interdisciplinary nature of AI applications in structural engineering, emphasizing the synergy between domain expertise and advanced computational methodologies. This synthesis aims to serve as a valuable resource for researchers, practitioners, and policymakers seeking a comprehensive understanding of the state-of-the-art in AI-driven optimization for steel moment frame structures. The paper commences with an overview of the fundamental principles governing steel moment frame structures and identifies the key optimization objectives, such as efficiency of structures. Subsequently, it delves into the application of AI in the conceptual design phase, where algorithms aid in generating innovative structural configurations and optimizing material utilization. The review also explores the use of AI for real-time structural health monitoring and predictive maintenance, contributing to the long-term sustainability and reliability of steel moment frame structures. Furthermore, the paper investigates how AI-driven algorithms facilitate the calibration of structural models, enabling accurate prediction of dynamic responses and seismic performance. Thus, by reviewing and analyzing the recent achievements in applications artificial intelligent in optimization of steel moment frame structures, the process of designing, analysis, and performance of the structures can be analyzed and modified.

Keywords: Artificial Intelligent, optimization process, steel moment frame, structural engineering.

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Authors: Kongsheng Zhang, Li Ge

Abstract:

It is a one-sided hypothesis testing process for assessing bioequivalence. Bootstrap and modified large-sample(MLS) methods are considered to study individual bioequivalence(IBE), type I error and power of hypothesis tests are simulated and compared with FDA(2001). The results show that modified large-sample method is equivalent to the method of FDA(2001) .

Keywords: Individual bioequivalence, bootstrap, Bayesian bootstrap, modified large-sample.

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Authors: Meng-Hui Chen, Pei-Chann Chang, Wei-Hsiu Huang

Abstract:

Artificial Immune System is adopted as a Heuristic Algorithm to solve the combinatorial problems for decades. Nevertheless, many of these applications took advantage of the benefit for applications but seldom proposed approaches for enhancing the efficiency. In this paper, we continue the previous research to develop a Self-evolving Artificial Immune System II via coordinating the T and B cell in Immune System and built a block-based artificial chromosome for speeding up the computation time and better performance for different complexities of problems. Through the design of Plasma cell and clonal selection which are relative the function of the Immune Response. The Immune Response will help the AIS have the global and local searching ability and preventing trapped in local optima. From the experimental result, the significant performance validates the SEAIS II is effective when solving the permutation flows-hop problems.

Keywords: Artificial Immune System, Clonal Selection, Immune Response, Permutation Flow-shop Scheduling Problems

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Authors: M. Ghasemi-Varnamkhasti, S. H. Yoosefian, A. Mohammad-Razdari

Abstract:

This study investigated the effects of Ag nanoparticle polyethylene film and active modified atmosphere on the postharvest quality of tomatoes stored at 6 ºC. The atmosphere composition used in the packaging was 7% O₂ + 7% CO₂ + 86% N₂, and synthetic air (control). The variables measured were weight loss, firmness, color and respiration rate over 21 days. The results showed that the combination of Ag nanoparticle polyethylene film and modified atmosphere could extend the shelf life of tomatoes to 21 days and could influence the postharvest quality of tomatoes. Also, existence of Ag nanoparticles caused preventing from increasing weight loss, a*, b*, Chroma, Hue angle and reducing firmness and L*. As well as, tomatoes at Ag nanoparticle polyethylene films had lower respiration rate than Polyethylene and paper bags to 13.27% and 23.50%, respectively. The combination of Ag nanoparticle polyethylene film and active modified atmosphere was effective with regard to delaying maturity during the storage period, and preserving the quality of tomatoes.

Keywords: Ag nanoparticles, modified atmosphere, polyethylene film, tomato.

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Authors: M. Mohagheghian, A. M. Ghaedi, A. Vafaei

Abstract:

An artificial neural network (ANN) model is presented for the prediction of kinematic viscosity of binary mixtures of poly (ethylene glycol) (PEG) in water as a function of temperature, number-average molecular weight and mass fraction. Kinematic viscosities data of aqueous solutions for PEG (0.55419×10-6 – 9.875×10-6 m2/s) were obtained from the literature for a wide range of temperatures (277.15 - 338.15 K), number-average molecular weight (200 -10000), and mass fraction (0.0 – 1.0). A three layer feed-forward artificial neural network was employed. This model predicts the kinematic viscosity with a mean square error (MSE) of 0.281 and the coefficient of determination (R2) of 0.983. The results show that the kinematic viscosity of binary mixture of PEG in water could be successfully predicted using an artificial neural network model.

Keywords: Artificial neural network, kinematic viscosity, poly ethylene glycol (PEG)

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Authors: Zhouji Chen

Abstract:

In this paper, the modified Gauss-Seidel method with the new preconditioner for solving the linear system Ax = b, where A is a nonsingular M-matrix with unit diagonal, is considered. The convergence property and the comparison theorems of the proposed method are established. Two examples are given to show the efficiency and effectiveness of the modified Gauss-Seidel method with the presented new preconditioner.

Keywords: Preconditioned linear system, M-matrix, Convergence, Comparison theorem.

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Authors: Shahram Naghizadeh Raeisi, Ali Alghooneh

Abstract:

Using membrane technology and modification of milk protein structural properties, a lactose free yogurt was developed. The functional, textural and structural properties of the sample were evaluated and compared with the commercial ones. Results showed that the modification of protein in high fat set yogurt resulted in 11.55%, 18%, 20.21% and 7.08% higher hardness, consistency, water holding capacity, and shininess values compared with the control one. Furthermore, these indices of modified low fat set yogurt were 21.40%, 25.41%, 28.15% & 10.58% higher than the control one, which could be related to the gel network microstructural properties in yogurt formulated with modified protein. In this way, in comparison with the control one, the index of linkage strength (A), the number of linkages (z), and time scale of linkages (λrel) of the high fat modified yogurt were 22.10%, 50.68%, 21.82% higher than the control one; whereas, the average linear distance between two adjacent crosslinks (ξ), was 16.77% lower than the control one. For low fat modified yogurt, A, z, λrel, and ξ indices were 34.30%, 61.70% and 42.60% higher and 19.20% lower than the control one, respectively. The shelf life of modified yogurt was extended to 10 weeks in the refrigerator, while, the control set yogurt had a 3 weeks shelf life. The acidity of high fat and low fat modified yogurts increased from 76 to 84 and 72 to 80 Dornic degrees during 10 weeks of storage, respectively, whereas for control high fat and low fat yogurts they increased from 82 to 122 and 77 to 112 Dornic degrees, respectively. This behavior could be due to the elimination of microorganism’s source of energy in modified yogurt. Furthermore, the calories of high fat and low fat lactose free yogurts were 25% and 40% lower than their control samples, respectively. Generally, results showed that the lactose free yogurt with modified protein, despite of 1% lower protein content than the control one, showed better functional properties, nutritional properties, network parameters, and shelf stability, which could be promising in the set yogurt industry.

Keywords: Lactose free, low calorie, network properties, protein modification.

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Authors: Howaidi M. Al-Otaibi, Abdulrahman S. Al-Suhaibani, Hamad A. Alsoliman

Abstract:

Fibers are extensively used in civil engineering applications for many years. In this study, empty fruit bunch of date palm trees were used to produce cellulose fiber that were used as additives in the asphalt binder. Two sizes (coarse and fine) of cellulose fibers were pre-blended in PG64-22 binder with various contents of 1.5%, 3%, 4.5%, 6%, and 7.5% by weight of asphalt binder. The physical and rheological properties of fiber modified asphalt binders were tested by using conventional tests such as penetration, softening point and viscosity; and SHRP test such as dynamic shear rheometer. The results indicated that the fiber modified asphalt binders were higher in softening point, viscosity, and complex shear modulus, and lower in penetration compared to pure asphalt. The fiber modified binders showed an improvement in rheological properties since it was possible to raise the control binder (pure asphalt) PG from 64 to 70 by adding 6% (by weight) of either fine or coarse fibers. Such improvement in stiffness of fiber modified binder is expected to improve pavement resistance to rutting.

Keywords: Cellulose date palm fiber, fiber modified asphalt, physical properties, rheological properties.

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Authors: A. Naceri, M. Chikouche Hamina, P. Grosseau

Abstract:

The effect of artificial pozzolan (waste brick) on the physico-chemical properties of cement manufactured was investigated. The waste brick is generated by the manufacture of bricks. It was used in the proportions of 0%, 5%, 10%, 15% and 20% by mass of cement to study its effect on the physico-chemical properties of cement incorporating artificial pozzolan. The physicochemical properties of cement at anhydrous state and the hydrated state (chemical composition, specific weight, fineness, consistency of the cement paste and setting times) were studied. The experimental results obtained show that the quantity of pozzolanic admixture (waste brick) of cement manufactured is the principal parameter who influences on the variation of the physico-chemical properties of the cement tested.

Keywords: Artificial pozzolan, waste brick, cement, physicochemicalcharacteristics.

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Authors: Hiba Basim Alwan, Ku Ruhana Ku-Mahamud

Abstract:

A direction for ACO is to optimize continuous and mixed (discrete and continuous) variables in solving problems with various types of data. Support Vector Machine (SVM), which originates from the statistical approach, is a present day classification technique. The main problems of SVM are selecting feature subset and tuning the parameters. Discretizing the continuous value of the parameters is the most common approach in tuning SVM parameters. This process will result in loss of information which affects the classification accuracy. This paper presents two algorithms that can simultaneously tune SVM parameters and select the feature subset. The first algorithm, ACO_R-SVM, will tune SVM parameters, while the second IACO_MV-R-SVM algorithm will simultaneously tune SVM parameters and select the feature subset. Three benchmark UCI datasets were used in the experiments to validate the performance of the proposed algorithms. The results show that the proposed algorithms have good performances as compared to other approaches.

Keywords: Continuous ant colony optimization, incremental continuous ant colony, simultaneous optimization, support vector machine.

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Authors: Noor Zainab Habib, Ibrahim Kamaruddin, Madzalan Napiah, Isa Mohd Tan

Abstract:

This paper presents a part of research on the rheological properties of bitumen modified by thermoplastic namely linear low density polyethylene (LLDPE), high density polyethylene (HDPE) and polypropylene (PP) and its interaction with 80 pen base bitumen. As it is known that the modification of bitumen by the use of polymers enhances its performance characteristics but at the same time significantly alters its rheological properties. The rheological study of polymer modified bitumen (PMB) was made through penetration, ring & ball softening point and viscosity test. The results were then related to the changes in the rheological properties of polymer modified bitumen. It was observed that thermoplastic copolymer shows profound effect on penetration rather than softening point. The viscoelastic behavior of polymer modified bitumen depend on the concentration of polymer, mixing temperature, mixing technique, solvating power of base bitumen and molecular structure of polymer used. PP offer better blend in comparison to HDPE and LLDPE. The viscosity of base bitumen was also enhanced with the addition of polymer. The pseudoplastic behavior was more prominent for HDPE and LLDPE than PP. Best results were obtained when polymer concentration was kept below 3%

Keywords: Polymer modified bitumen, Linear low densitypolyethylene, High density polyethylene, Polypropylene.

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Authors: Mohammad Taghi Darvishi, Maliheh Najafi, Mohammad Najafi

Abstract:

In this paper, using (G/G )-expansion method and modified F-expansion method, we give some explicit formulas of exact traveling wave solutions for the (3+1)-dimensional breaking soliton equation. A modified F-expansion method is proposed by taking full advantages of F-expansion method and Riccati equation in seeking exact solutions of the equation.

Keywords: Exact solution, The (3+1)-dimensional breaking soliton equation, ( G G )-expansion method, Riccati equation, Modified Fexpansion method.

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Authors: Thiang, Handry Khoswanto, Rendy Pangaldus

Abstract:

Inverse kinematics analysis plays an important role in developing a robot manipulator. But it is not too easy to derive the inverse kinematic equation of a robot manipulator especially robot manipulator which has numerous degree of freedom. This paper describes an application of Artificial Neural Network for modeling the inverse kinematics equation of a robot manipulator. In this case, the robot has three degree of freedoms and the robot was implemented for drilling a printed circuit board. The artificial neural network architecture used for modeling is a multilayer perceptron networks with steepest descent backpropagation training algorithm. The designed artificial neural network has 2 inputs, 2 outputs and varies in number of hidden layer. Experiments were done in variation of number of hidden layer and learning rate. Experimental results show that the best architecture of artificial neural network used for modeling inverse kinematics of is multilayer perceptron with 1 hidden layer and 38 neurons per hidden layer. This network resulted a RMSE value of 0.01474.

Keywords: Artificial neural network, back propagation, inverse kinematics, manipulator, robot.

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Authors: Hossein Ali Akbarpour, Fatemeh Dadkhah

Abstract:

This paper considers a multi criteria cell formation problem in Cellular Manufacturing System (CMS). Minimizing the number of voids and exceptional elements in cells simultaneously are two proposed objective functions. This problem is an Np-hard problem according to the literature, and therefore, we can-t find the optimal solution by an exact method. In this paper we developed two ant algorithms, Ant Colony Optimization (ACO) and Max-Min Ant System (MMAS), based on Data Envelopment Analysis (DEA). Both of them try to find the efficient solutions based on efficiency concept in DEA. Each artificial ant is considered as a Decision Making Unit (DMU). For each DMU we considered two inputs, the values of objective functions, and one output, the value of one for all of them. In order to evaluate performance of proposed methods we provided an experimental design with some empirical problem in three different sizes, small, medium and large. We defined three different criteria that show which algorithm has the best performance.

Keywords: Ant algorithm, Cellular manufacturing system, Data envelopment analysis, Efficiency

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Authors: Piyush Pal, Rahul Dev

Abstract:

Water is essential for life and fresh water is a finite resource that is becoming scarce day by day even though it is recycled by hydrological cycle. The fresh water reserves are being polluted due to expanding irrigation, industries, urban population and its development. Contaminated water leads to several health problems. With the increasing demand of fresh water, solar distillation is an alternate solution which uses solar energy to evaporate water and then to condense it, thereby collecting distilled water within or outside the same system to use it as potable water. The structure that houses the process is known as a 'solar still'. In this paper, ‘Modified double slope solar still (MDSSS)’ & 'Modified double slope basin type multiwick solar still (MDSBMSS)' have been designed to convert saline, brackish water into drinking water. In this work two different modified solar stills are fabricated to study the performance of these solar stills. For modification of solar stills, Fibre Reinforced Plastic (FRP) and Acrylic sheets are used. The experiments in MDSBMSS and MDSSS was carried on 10 September 2015 & 5 November 2015 respectively. Performances of the stills were investigated. The amount of distillate has been found 3624 Ml/day in MDSBMSS on 10 September 2015 and 2400 Ml/day in MDSSS on 5 November 2015.

Keywords: Contaminated water, Conventional solar still, Modified solar still, Wick.

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