Search results for: matrix minimization algorithm

Authors: P.-W. Tsai, C.-Y. Chen, C.-W. Chen

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In this paper, the stability analysis of a GA-Based adaptive fuzzy sliding model controller for a nonlinear system is discussed. First, a nonlinear plant is well-approximated and described with a reference model and a fuzzy model, both involving FLC rules. Then, FLC rules and the consequent parameter are decided on via an Evolved Bat Algorithm (EBA). After this, we guarantee a new tracking performance inequality for the control system. The tracking problem is characterized to solve an eigenvalue problem (EVP). Next, an adaptive fuzzy sliding model controller (AFSMC) is proposed to stabilize the system so as to achieve good control performance. Lyapunov’s direct method can be used to ensure the stability of the nonlinear system. It is shown that the stability analysis can reduce nonlinear systems into a linear matrix inequality (LMI) problem. Finally, a numerical simulation is provided to demonstrate the control methodology.

Keywords: adaptive fuzzy sliding mode control, Lyapunov direct method, swarm intelligence, evolved bat algorithm

Procedia PDF Downloads 445

Authors: Uswah Khairuddin, Rubiyah Yusof, Nenny Ruthfalydia Rosli

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This paper presents a comparative study between k-Nearest Neighbour (k-NN) and Multi-Layer Perceptron Neural Network (MLP-NN) classifier using Genetic Algorithm (GA) as feature selector for wood recognition system. The features have been extracted from the images using Grey Level Co-Occurrence Matrix (GLCM). The use of GA based feature selection is mainly to ensure that the database used for training the features for the wood species pattern classifier consists of only optimized features. The feature selection process is aimed at selecting only the most discriminating features of the wood species to reduce the confusion for the pattern classifier. This feature selection approach maintains the ‘good’ features that minimizes the inter-class distance and maximizes the intra-class distance. Wrapper GA is used with k-NN classifier as fitness evaluator (GA-kNN). The results shows that k-NN is the best choice of classifier because it uses a very simple distance calculation algorithm and classification tasks can be done in a short time with good classification accuracy.

Keywords: feature selection, genetic algorithm, optimization, wood recognition system

Procedia PDF Downloads 545

Authors: Kerim Emre Öksüz, Mehmet Çevik, A. Enbiya Bozdağ, Ali Özer, Mehmet Şimşir

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Metal matrix composites (MMCs) have gained a considerable interest in the last three decades. Conventional powder metallurgy production route often involves the addition of reinforcing phases into the metal matrix directly, which leads to poor wetting behavior between ceramic phase and metal matrix and the segregation of reinforcements. The commonly used elements for ceramic phase formation in iron based MMCs are Ti, Nb, Mo, W, V and C, B. The aim of the present paper is to investigate the effect of sintering temperature and V-B addition on densification, phase development, microstructure, and hardness of Fe–V-B composites (Fe-(5-10) wt. %B – 25 wt. %V alloys) prepared by powder metallurgy process. Metal powder mixes were pressed uniaxial and sintered at different temperatures (ranging from 1300 to 1400ºC) for 1h. The microstructure of the (V, B) Fe composites was studied with the help of high magnification optical microscope and XRD. Experimental results show that (V, B) Fe composites can be produced by conventional powder metallurgy route.

Keywords: hardness, metal matrix composite (MMC), microstructure, powder metallurgy

Procedia PDF Downloads 798

Authors: Ruitao Li, Zhili Dong, Nay Win Khun, Khiam Aik Khor

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In this study, microstructure and sintering mechanism as well as wear resistance properties of Ti/Al-Cr-Fe metal matrix composites (MMCs) fabricated by spark plasma sintering (SPS) with Ti as matrix and Al-Cr-Fe as reinforcement were investigated. Phases and microstructure of the sintered samples were analyzed using X-ray diffractometry (XRD), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS) and transmission electron microscopy (TEM). Wear resistance properties were tested by ball-on-disk method. An Al3Ti ring forms around each Al-Cr-Fe particle as the bonding layer between Ti and Al-Cr-Fe particles. The Al content in Al-Cr-Fe particles experiences a decrease from 70 at.% to 60 at.% in the sintering process. And these particles consist of quasicrystalline icosahedral AlCrFe and quasicrystal approximants γ-brass Al8(Cr,Fe)5 and Al9(Cr,Fe)4 in the sintered compact. The addition of Al-Cr-Fe particles into the Ti matrix can improve the microhardness by about 40% and the wear resistance is improved by more than 50% due to the increase in the microhardness and the change of wear mechanism.

Keywords: metal matrix composites, spark plasma sintering, phase transformation, wear

Procedia PDF Downloads 421

Authors: Jamaludin Sallim, Rozlina Mohamed, Roslina Abdul Hamid

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

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

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Authors: Shengbiao Wu, Weihua Cao, Min Wu, Can Liu

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This paper presents an intelligent tuning method of microwave filter based on complex neural network and improved space mapping. The tuning process consists of two stages: the initial tuning and the fine tuning. At the beginning of the tuning, the return loss of the filter is transferred to the passband via the error of phase. During the fine tuning, the phase shift caused by the transmission line and the higher order mode is removed by the curve fitting. Then, an Cauchy method based on the admittance parameter (Y-parameter) is used to extract the coupling matrix. The influence of the resonant cavity loss is eliminated during the parameter extraction process. By using processed data pairs (the amount of screw variation and the variation of the coupling matrix), a tuning model is established by the complex neural network. In view of the improved space mapping algorithm, the mapping relationship between the actual model and the ideal model is established, and the amplitude and direction of the tuning is constantly updated. Finally, the tuning experiment of the eight order coaxial cavity filter shows that the proposed method has a good effect in tuning time and tuning precision.

Keywords: microwave filter, scattering parameter, coupling matrix, intelligent tuning

Procedia PDF Downloads 311

Authors: Zayar Phyo, Ei Chaw Htoon

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

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

Procedia PDF Downloads 149

Authors: Olusegun A. Afolabi, Ndivhuwo Ndou

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Composite material is an important area that has gained global visibility in many research fields in recent years. Composite material is the combination of separate materials with different properties to form a single material having different properties from the parent materials. Material composition and combination is an important aspect of composite material. The focus of this study is to provide insight into an easy way of calculating the compositions and formulations of constituent materials that make up any composite material. The compositions of the matrix and filler used for fabricating composite materials are taken into consideration. From the composite fabricated, data can be collected and analyzed based on the test and characterizations such as tensile, flexural, compression, impact, hardness, etc. Also, the densities of the matrix and the filler with regard to their constituent materials are discussed.

Keywords: composite material, density, filler, matrix, percentage weight, volume fraction

Procedia PDF Downloads 67

Authors: Benny Alexander, Ikhlashia N. Fadhilah, Muhammad R. Pasha, Michelle Julia, Anne Z. Syahrial

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Brake shoe is a component that serves to reduce speed or stop the train's speed by utilizing the friction force. Generally, the material used as a brake shoe is cast iron, where cast iron itself is a heavy, expensive, and easily worn material. Aluminum matrix composites are one of candidates for the cast iron replacement material as the basic material for brake shoe. The matrix in the composite used is Aluminum AC4B. Reinforcement used in aluminum matrix composites is nano-alumina, where the use of nano-alumina of 0.25%, 0.3%, 0.35%, 0.4%, and 0.5% volume fraction will be tested. The sample is made using the stir casting method; then, it will be tested mechanically. The use of nano-alumina as a reinforcement will increase the strength of the matrix. SEM (scanning electron microscopy) testing is used to test the distribution of reinforcing particles due to stirring. Therefore, the addition of nano-alumina will improve AC4B aluminum matrix composites.

Keywords: aluminium matrix composites, brake shoe application, stir casting, nano-alumina

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Authors: Abraham Castellanos, Christophe Durville, Sophie Echenim

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In this article, a portfolio optimization problem is performed in a Solvency II context: it illustrates how advanced optimization techniques can help to tackle complex operational pain points around the monitoring, control, and stability of Solvency Capital Requirement (SCR). The market SCR of a portfolio is calculated as a combination of SCR sub-modules. These sub-modules are the results of stress-tests on interest rate, equity, property, credit and FX factors, as well as concentration on counter-parties. The market SCR is non convex and non differentiable, which does not make it a natural optimization criteria candidate. In the SCR formulation, correlations between sub-modules are fixed, whereas risk-driven portfolio allocation is usually driven by the dynamics of the actual correlations. Implementing a portfolio construction approach that is efficient on both a regulatory and economic standpoint is not straightforward. Moreover, the challenge for insurance portfolio managers is not only to achieve a minimal SCR to reduce non-invested capital but also to ensure stability of the SCR. Some optimizations have already been performed in the literature, simplifying the standard formula into a quadratic function. But to our knowledge, it is the first time that the standard formula of the market SCR is used in an optimization problem. Two solvers are combined: a bundle algorithm for convex non- differentiable problems, and a BFGS (Broyden-Fletcher-Goldfarb- Shanno)-SQP (Sequential Quadratic Programming) algorithm, to cope with non-convex cases. A market SCR minimization is then performed with historical data. This approach results in significant reduction of the capital requirement, compared to a classical Markowitz approach based on the historical volatility. A comparative analysis of different optimization models (equi-risk-contribution portfolio, minimizing volatility portfolio and minimizing value-at-risk portfolio) is performed and the impact of these strategies on risk measures including market SCR and its sub-modules is evaluated. A lack of diversification of market SCR is observed, specially for equities. This was expected since the market SCR strongly penalizes this type of financial instrument. It was shown that this direct effect of the regulation can be attenuated by implementing constraints in the optimization process or minimizing the market SCR together with the historical volatility, proving the interest of having a portfolio construction approach that can incorporate such features. The present results are further explained by the Market SCR modelling.

Keywords: financial risk, numerical optimization, portfolio management, solvency capital requirement

Procedia PDF Downloads 117

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

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

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

Procedia PDF Downloads 433

Authors: Amandeep Singh, Niraj Bala

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In the last decades, light-weight materials such as magnesium matrix composites have become hot topic for material research due to their excellent mechanical and physical properties. However, relatively very less work has been done related to the wear behavior of these composites. Magnesium matrix composites have wide applications in automobile and aerospace sector. In this review, attempt has been done to collect the literature related to wear behavior of magnesium matrix composites fabricated through various processing techniques such as stir casting, powder metallurgy, friction stir processing etc. Effect of different reinforcements, reinforcement content, reinforcement size, wear load, sliding speed and time have been studied by different researchers in detail. Wear mechanism under different experimental condition has been reviewed in detail. The wear resistance of magnesium and its alloys can be enhanced with the addition of different reinforcements. Wear resistance can further be enhanced by increasing the percentage of added reinforcements. Increase in applied load during wear test leads to increase in wear rate of magnesium composites.

Keywords: hardness, magnesium matrix composites, reinforcement, wear

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Authors: Bidzina Matsaberidze

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It is known that, in emergency situations, multi-attribute group decision-making (MAGDM) models are characterized by insufficient objective data and a lack of time to respond to the task. Evidence theory is an effective tool for describing such incomplete information in decision-making models when the expert and his knowledge are involved in the estimations of the MAGDM parameters. We consider an emergency decision-making model, where expert assessments on humanitarian aid from distribution centers (HADC) are represented in q-rung ortho-pair fuzzy numbers, and the data structure is described within the data body theory. Based on focal probability construction and experts’ evaluations, an objective function-distribution centers’ selection ranking index is constructed. Our approach for solving the constructed bicriteria partitioning problem consists of two phases. In the first phase, based on the covering’s matrix, we generate a matrix, the columns of which allow us to find all possible partitionings of the HADCs with the service centers. Some constraints are also taken into consideration while generating the matrix. In the second phase, based on the matrix and using our exact algorithm, we find the partitionings -allocations of the HADCs to the centers- which correspond to the Pareto-optimal solutions. For an illustration of the obtained results, a numerical example is given for the facility location-selection problem.

Keywords: emergency MAGDM, q-rung orthopair fuzzy sets, evidence theory, HADC, facility location problem, multi-objective combinatorial optimization problem, Pareto-optimal solutions

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Authors: Aydin Teymourifar, Gurkan Ozturk

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

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

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Authors: R. Buntem, K. Samkongngam

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The silicate glass was prepared using rice husk as the source of silica. The base composition of glass sample is composed of SiO2 (from rice husk ash), Na2CO3, K2CO3, ZnO, H3BO3, CaO, Al2O3 or Al, and CuO. Aluminum is used in place of Al2O3 in order to reduce Cu2+ to Cu+. The red color of Cu2O in the glass matrix was observed when the Al was added into the glass mixture. The expansion coefficients of the copper doped glass are in the range of 1.2 x 10-5-1.4x10-5 (ºC -1) which is common for the silicate glass. The finger prints of the bond vibrations were studied using IR spectroscopy. While the oxidation state and the coordination information of the copper ion in the glass matrix were investigated using X-ray absorption spectroscopy. From the data, Cu+ and Cu2+ exist in the glass matrix. The red particles of Cu2O can be formed in the glass matrix when enough aluminum was added.

Keywords: copper in glass, coordination information, silicate glass, XANES spectrum

Procedia PDF Downloads 263

Authors: Vibha Sinha, Sumedha Chakma

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Arsenic (As) contamination in drinking water is a serious concern worldwide resulting in severe health maladies. To tackle this problem, several hydrogel based matrix which selectively uptake toxic metals from contaminated water has increasingly been examined as a potential practical method for metal removal. The major concern in hydrogels is low stability of matrix, resulting in poor performance. In this study, the potential of hybrid hydrogel-biochar matrix synthesized from natural plant polymers, specific for As removal was explored. Various compositional and functional group changes of the elements contained in the matrix due to the adsorption of As were identified. Moreover, to resolve the stability issue in hydrogel matrix, optimum and effective mixing of hydrogel with biochar was studied. Mixing varied proportions of matrix components at the time of digestion process was tested. Preliminary results suggest that partial premixing methods may increase the stability and reduce cost. Addition of nanoparticles and specific catalysts with different concentrations of As(III) and As(V) under batch conditions was performed to study their role in performance enhancement of the hydrogel matrix. Further, effect of process parameters, optimal uptake conditions and detailed mechanism derived from experimental studies were suitably conducted. This study provides an efficient, specific and a low-cost As removal method that offers excellent regeneration abilities which can be reused for value.

Keywords: arsenic, catalysts, hybrid hydrogel-biochar, water purification

Procedia PDF Downloads 188

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

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

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

Procedia PDF Downloads 563

Authors: Rishabh Srivastav, Divyam Sharma

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

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

Procedia PDF Downloads 246

Authors: Essam Al Daoud

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

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

Procedia PDF Downloads 344

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

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

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

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Authors: Israa Sh. Tawfic, Sema Koc Kayhan

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Given a large sparse signal, great wishes are to reconstruct the signal precisely and accurately from lease number of measurements as possible as it could. Although this seems possible by theory, the difficulty is in built an algorithm to perform the accuracy and efficiency of reconstructing. This paper proposes a new proved method to reconstruct sparse signal depend on using new method called Least Support Matching Pursuit (LS-OMP) merge it with the theory of Partial Knowing Support (PSK) given new method called Partially Knowing of Least Support Orthogonal Matching Pursuit (PKLS-OMP). The new methods depend on the greedy algorithm to compute the support which depends on the number of iterations. So to make it faster, the PKLS-OMP adds the idea of partial knowing support of its algorithm. It shows the efficiency, simplicity, and accuracy to get back the original signal if the sampling matrix satisfies the Restricted Isometry Property (RIP). Simulation results also show that it outperforms many algorithms especially for compressible signals.

Keywords: compressed sensing, lest support orthogonal matching pursuit, partial knowing support, restricted isometry property, signal reconstruction

Procedia PDF Downloads 240

Authors: Hoshang Kolivand, Mahyar Kolivand, Mohd Shahrizal Sunar, Mohd Azhar M. Arsad

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Real-time shadow generation in virtual environments and Augmented Reality (AR) was always a hot topic in the last three decades. Lots of calculation for shadow generation among AR needs a fast algorithm to overcome this issue and to be capable of implementing in any real-time rendering. In this paper, a silhouette detection algorithm is presented to generate shadows for AR systems. Δ+ algorithm is presented based on extending edges of occluders to recognize which edges are silhouettes in the case of real-time rendering. An accurate comparison between the proposed algorithm and current algorithms in silhouette detection is done to show the reduction calculation by presented algorithm. The algorithm is tested in both virtual environments and AR systems. We think that this algorithm has the potential to be a fundamental algorithm for shadow generation in all complex environments.

Keywords: silhouette detection, shadow volumes, real-time shadows, rendering, augmented reality

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Authors: Mohamed Lotfy, Ghada Soliman

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Recognizing Arabic dot-matrix digits is a challenging problem due to the unique characteristics of dot-matrix fonts, such as irregular dot spacing and varying dot sizes. This paper presents an approach for recognizing Arabic digits printed in dot matrix format. The proposed model is based on Convolutional Neural Networks (CNN) that take the dot matrix as input and generate embeddings that are rounded to generate binary representations of the digits. The binary embeddings are then used to perform Optical Character Recognition (OCR) on the digit images. To overcome the challenge of the limited availability of dotted Arabic expiration date images, we developed a True Type Font (TTF) for generating synthetic images of Arabic dot-matrix characters. The model was trained on a synthetic dataset of 3287 images and 658 synthetic images for testing, representing realistic expiration dates from 2019 to 2027 in the format of yyyy/mm/dd. Our model achieved an accuracy of 98.94% on the expiry date recognition with Arabic dot matrix format using fewer parameters and less computational resources than traditional CNN-based models. By investigating and presenting our findings comprehensively, we aim to contribute substantially to the field of OCR and pave the way for advancements in Arabic dot-matrix character recognition. Our proposed approach is not limited to Arabic dot matrix digit recognition but can also be extended to text recognition tasks, such as text classification and sentiment analysis.

Keywords: computer vision, pattern recognition, optical character recognition, deep learning

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

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

Keywords: optimization, harmony search algorithm, MATLAB, electronic

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Authors: Tanvir Ahmed, Musfira Rahman, Rumpa Chowdhury

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We performed laboratory experiments to assess the suitability of using medical waste incineration fly ash in cement as a construction material based on the engineering properties of fly ash-cement matrix and the leaching potential of toxic heavy metals from the stabilized mix. Fly ash-cement samples were prepared with different proportions of fly ash (0%, 5%, 10%, 15% and 20% by weight) in the laboratory controlled conditions. The solidified matrix exhibited a compressive strength from 3950 to 4980 psi when fly ash is mixed in varying proportions. The 28-day compressive strength has been found to decrease with the increase in fly ash content, but it meets the minimum requirement of compressive strength for cement-mortar. Soundness test results for cement-mortar mixes having up to 15% fly ash. Final and initial setting times of cement have been found to generally increase with fly ash content. Water requirement (for normal consistency) also increased with the increase in fly ash content in cement. Based on physical properties of the cement-mortar matrix it is recommended that up to 10% (by weight) medical waste incineration fly ash can be incorporated for producing cement-mortar of optimum quality. Leaching behaviours of several targeted heavy metals (As, Cu, Ni, Cd, Pb, Hg and Zn) were analyzed using Toxicity Characteristics Leaching Procedure (TCLP) on fly ash and solidified fly ash-cement matrix. It was found that the leached concentrations of As, Cu, Cd, Pb and Zn were reduced by 80.13%, 89.47%, 33.33% and 23.9% respectively for 10% fly ash incorporated cement-mortar matrix compared to that of original fly ash. The leached concentrations of heavy metals were from the matrix were far below the EPA land disposal limits. These results suggest that the solidified fly ash incorporated cement-mortar matrix can effectively confine and immobilize the heavy metals contained in the fly ash.

Keywords: cement-mortar, fly ash, leaching, waste management

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Authors: Isil Kerti, Onur Okur, Sibel Daglilar, Recep Calin

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Particulate reinforced aluminium matrix composites have gained more importance in automotive, aeronautical and defense industries due to their specific properties like as low density, high strength and stiffness, good fatigue strength, dimensional stability at high temperature and acceptable tribological properties. In this study, 2014 Aluminium alloy used as a matrix material and B₄C and SiC were selected as reinforcements components. For production of composites materials, vacuum infiltration method was used. In the experimental studies, the reinforcement volume ratios were defined by mixing as totally 10% B₄C and SiC. Aging treatment (T6) was applied to the specimens. The effect of T6 treatment on hardness was determined by using Brinell hardness test method. The effects of the aging treatment on microstructure and chemical structure were analysed by making XRD, SEM and EDS analysis on the specimens.

Keywords: metal matrix composite, vacumm infiltration method, aluminum metal matrix, mechanical feature

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Authors: César Garza

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In supervised binary classification and regression problems, it is well-known that learnability is equivalent to a uniform convergence of the hypothesis class, and if a problem is learnable, it is learnable by empirical risk minimization. For the general learning setting of unsupervised learning tasks, there are non-trivial learning problems where uniform convergence does not hold. We present here the task of learning centers of mass with an extra feature that “activates” some of the coordinates over the unit ball in a Hilbert space. We show that the learning problem is learnable under a stable RLM rule. We introduce a family of distributions over the domain space with some mild restrictions for which the sample complexity of uniform convergence for these problems must grow logarithmically with the dimension of the Hilbert space. If we take this dimension to infinity, we obtain a learnable problem for which the uniform convergence property fails for a vast family of distributions.

Keywords: statistical learning theory, learnability, uniform convergence, stability, regularized loss minimization

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Authors: Ali Mohammadi Bolban Abad, Fariborz Ahmadi

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Optimization in manufacture is a method to use limited resources to obtain the best performance and reduce waste. In this paper a new algorithm based on eurygaster life is introduced to obtain a plane in which task order and completion time of resources are defined. Evaluation results show our approach has less make span when the resources are allocated with some products in comparison to genetic algorithm.

Keywords: evolutionary computation, genetic algorithm, particle swarm optimization, NP-Hard problems, production scheduling

Procedia PDF Downloads 378

Authors: Min Shi

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

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

Procedia PDF Downloads 349

Authors: Radhwan Yousif Sedik Al-Jawadi

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

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

Procedia PDF Downloads 346