Search results for: stochastic programming problem with recourse

Authors: M. Rodionov, Z. Dedovets

Abstract:

This article discusses plausible reasoning use for solution to practical problems. Such reasoning is the major driver of motivation and implementation of mathematical, scientific and educational research activity. A general, practical problem solving algorithm is presented which includes an analysis of specific problem content to build, solve and interpret the underlying mathematical model. The author explores the role of practical problems such as the stimulation of students' interest, the development of their world outlook and their orientation in the modern world at the different stages of learning mathematics in secondary school. Particular attention is paid to the characteristics of those problems which were systematized and presented in the conclusions.

Keywords: Mathematics, motivation, secondary school, student, practical problem.

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Authors: Ahmed Elrewainy

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Mixing in the hyperspectral imaging occurs due to the low spatial resolutions of the used cameras. The existing pure materials “endmembers” in the scene share the spectra pixels with different amounts called “abundances”. Unmixing of the data cube is an important task to know the present endmembers in the cube for the analysis of these images. Unsupervised unmixing is done with no information about the given data cube. Sparsity is one of the recent approaches used in the source recovery or unmixing techniques. The l₁-norm optimization problem “basis pursuit” could be used as a sparsity-based approach to solve this unmixing problem where the endmembers is assumed to be sparse in an appropriate domain known as dictionary. This optimization problem is solved using proximal method “iterative thresholding”. The l₁-norm basis pursuit optimization problem as a sparsity-based unmixing technique was used to unmix real and synthetic hyperspectral data cubes.

Keywords: Basis pursuit, blind source separation, hyperspectral imaging, spectral unmixing, wavelets.

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Authors: Gionata Carmignani, Mario G. C. A. Cimino, Franco Failli

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Business Processes (BPs) are the key instrument to understand how companies operate at an organizational level, taking an as-is view of the workflow, and how to address their issues by identifying a to-be model. In last year’s, the BP Model and Notation (BPMN) has become a de-facto standard for modeling processes. However, this standard does not incorporate explicitly the Problem- Solving (PS) knowledge in the Process Modeling (PM) results. Thus, such knowledge cannot be shared or reused. To narrow this gap is today a challenging research area. In this paper we present a framework able to capture the PS knowledge and to improve a workflow. This framework extends the BPMN specification by incorporating new general-purpose elements. A pilot scenario is also presented and discussed.

Keywords: Business Process Management, BPMN, Problem Solving, Process mapping.

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Authors: Yousef Abu Nahleh, Alhasan Hakami, Arun Kumar, Fugen Daver

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This study considers the problem of calculating safety stocks in disaster situations inventory systems that face demand uncertainties. Safety stocks are essential to make the supply chain, which is controlled by forecasts of customer needs, in response to demand uncertainties and to reach predefined goal service levels. To solve the problem of uncertainties due to the disaster situations affecting the industry sector, the concept of Emergency Safety Stock (ESS) was proposed. While there exists a huge body of literature on determining safety stock levels, this literature does not address the problem arising due to the disaster and dealing with the situations. In this paper, the problem of improving the Order Quantity Model to deal with uncertainty of demand due to disasters is managed by incorporating a new idea called ESS which is based on the probability of disaster occurrence and uses probability matrix calculated from the historical data. 

Keywords: Emergency Safety Stocks, Safety stocks, Order Quantity Model, Supply chain.

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Authors: Pham Luu Trung Duong, Moonyong Lee

Abstract:

To increase precision and reliability of automatic control systems, we have to take into account of random factors affecting the control system. Thus, operational matrix technique is used for statistical analysis of first order plus time delay system with uniform random parameter. Examples with deterministic and stochastic disturbance are considered to demonstrate the validity of the method. Comparison with Monte Carlo method is made to show the computational effectiveness of the method.

Keywords: First order plus dead-time, Operational matrix, Statistical analysis, Walsh function.

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Authors: Mohammed I. Abouheaf, Sofie Haesaert, Wei-Jen Lee, Frank L. Lewis

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Economic Dispatch is one of the most important power system management tools. It is used to allocate an amount of power generation to the generating units to meet the load demand. The Economic Dispatch problem is a large scale nonlinear constrained optimization problem. In general, heuristic optimization techniques are used to solve non-convex Economic Dispatch problem. In this paper, ideas from Reinforcement Learning are proposed to solve the non-convex Economic Dispatch problem. Q-Learning is a reinforcement learning techniques where each generating unit learn the optimal schedule of the generated power that minimizes the generation cost function. The eligibility traces are used to speed up the Q-Learning process. Q-Learning with eligibility traces is used to solve Economic Dispatch problems with valve point loading effect, multiple fuel options, and power transmission losses.

Keywords: Economic Dispatch, Non-Convex Cost Functions, Valve Point Loading Effect, Q-Learning, Eligibility Traces.

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Authors: T. O. Olwal, K. Djouani, B. J. van Wyk, Y. Hamam, P. Siarry

Abstract:

Multi-Radio Multi-Channel Wireless Mesh Networks (MRMC-WMNs) operate at the backbone to access and route high volumes of traffic simultaneously. Such roles demand high network capacity, and long “online" time at the expense of accelerated transmission energy depletion and poor connectivity. This is the problem of transmission power control. Numerous power control methods for wireless networks are in literature. However, contributions towards MRMC configurations still face many challenges worth considering. In this paper, an energy-efficient power selection protocol called PMMUP is suggested at the Link-Layer. This protocol first divides the MRMC-WMN into a set of unified channel graphs (UCGs). A UCG consists of multiple radios interconnected to each other via a common wireless channel. In each UCG, a stochastic linear quadratic cost function is formulated. Each user minimizes this cost function consisting of trade-off between the size of unification states and the control action. Unification state variables come from independent UCGs and higher layers of the protocol stack. The PMMUP coordinates power optimizations at the network interface cards (NICs) of wireless mesh routers. The proposed PMMUP based algorithm converges fast analytically with a linear rate. Performance evaluations through simulations confirm the efficacy of the proposed dynamic power control.

Keywords: Effective band inference based power control algorithm (EBIA), Power Selection MRMC Unification Protocol (PMMUP), MRMC State unification Variable Prediction (MRSUP), Wireless Mesh Networks (WMNs).

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Authors: Lynne Chester

Abstract:

Governments around the world are expending considerable time and resources framing strategies and policies to deliver energy security. The term 'energy security' has quietly slipped into the energy lexicon without any meaningful discourse about its meaning or assumptions. An examination of explicit and inferred definitions finds that the concept is inherently slippery because it is polysemic in nature having multiple dimensions and taking on different specificities depending on the country (or continent), timeframe or energy source to which it is applied. But what does this mean for policymakers? Can traditional policy approaches be used to address the problem of energy security or does its- polysemic qualities mean that it should be treated as a 'wicked' problem? To answer this question, the paper assesses energy security against nine commonly cited characteristics of wicked policy problems and finds strong evidence of 'wickedness'.

Keywords: Energy security, policy making, wicked problems.

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Authors: Young-Seok Choi

Abstract:

This work presents a new type of the affine projection (AP) algorithms which incorporate the sparsity condition of a system. To exploit the sparsity of the system, a weighted l1-norm regularization is imposed on the cost function of the AP algorithm. Minimizing the cost function with a subgradient calculus and choosing two distinct weighting for l1-norm, two stochastic gradient based sparsity regularized AP (SR-AP) algorithms are developed. Experimental results exhibit that the SR-AP algorithms outperform the typical AP counterparts for identifying sparse systems.

Keywords: System identification, adaptive filter, affine projection, sparsity, sparse system.

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Authors: Nai-Chieh Wei, I-Ming Chao, Chin-Jung Liuand, Hong Long Chen

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This paper combines the branch-and-bound method and the petri net to solve the two-sided assembly line balancing problem, thus facilitating effective branching and pruning of tasks. By integrating features of the petri net, such as reachability graph and incidence matrix, the propose method can support the branch-and-bound to effectively reduce poor branches with systematic graphs. Test results suggest that using petri net in the branching process can effectively guide the system trigger process, and thus, lead to consistent results.

 

Keywords: Branch-and-Bound Method, Petri Net, Two-Sided Assembly Line Balancing Problem.

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Authors: Mohammed A. Hajeeh

Abstract:

This paper examines the behavior of a system, which upon failure is either replaced with certain probability p or imperfectly repaired with probability q. The system is analyzed using Kolmogorov's forward equations method; the analytical expression for the steady state availability is derived as an indicator of the system’s performance. It is found that the analysis becomes more complex as the number of imperfect repairs increases. It is also observed that the availability increases as the number of states and replacement probability increases. Using such an approach in more complex configurations and in dynamic systems is cumbersome; therefore, it is advisable to resort to simulation or heuristics. In this paper, an example is provided for demonstration.

Keywords: Repairable models, imperfect, availability, exponential distribution.

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Authors: Oon-Seng Tan

Abstract:

Human Computer Interaction (HCI) has been an emerging field that draws in the experts from various fields to enhance the application of computer programs and the ease of computer users. HCI has much to do with learning and cognition and an emerging approach to learning and problem-solving is problembased learning (PBL). The processes of PBL involve important cognitive functions in the various stages. This paper will illustrate how closely related fields to HCI, PBL and cognitive psychology can benefit from informing each other through analysing various cognitive functions. Several cognitive functions from cognitive function disc (CFD) would be presented and discussed in relation to human-computer interface. This paper concludes with the implications of bridging the gaps amongst these disciplines.

Keywords: problem-based learning, human computerinteraction, cognitive psychology, Cognitive Function Disc (CFD)

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Authors: Tomoaki Hashimoto

Abstract:

Recently, optimal control problems subject to probabilistic constraints have attracted much attention in many research field. Although probabilistic constraints are generally intractable in optimization problems, several methods haven been proposed to deal with probabilistic constraints. In most methods, probabilistic constraints are transformed to deterministic constraints that are tractable in optimization problems. This paper examines a method for transforming probabilistic constraints into deterministic constraints for a class of probabilistic constrained optimal control problems.

Keywords: Optimal control, stochastic systems, discrete-time systems, probabilistic constraints.

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Authors: Mimi N. A. Mohamed

Abstract:

The complexity of teaching English in higher institutions by non-native speakers within a second/foreign language setting has created continuous discussions and research about teaching approaches and teaching practises, professional identities and challenges. In addition, there is a growing awareness that teaching English within discipline-specific contexts adds up to the existing complexity. This awareness leads to reassessments, discussions and suggestions on course design and content and teaching approaches and techniques. In meeting expectations teaching at a university specified in a particular discipline such as engineering, English language educators are not only required to teach students to be able to communicate in English effectively but also to teach soft skills such as problem solving skills. This paper is part of a research conducted to investigate how English language educators negotiate with the complexities of teaching problem solving skills through English language teaching at a technical university. This paper reports the way an English language educator identified himself and the way he approached his teaching in this institutional context.

Keywords: English Language Teaching, Teacher Agency, Problem Solving Skills, Professional Identities.

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Authors: Masaru Fujieda, Takahiro Murakami, Yoshihisa Ishida

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Independent component analysis (ICA) in the frequency domain is used for solving the problem of blind source separation (BSS). However, this method has some problems. For example, a general ICA algorithm cannot determine the permutation of signals which is important in the frequency domain ICA. In this paper, we propose an approach to the solution for a permutation problem. The idea is to effectively combine two conventional approaches. This approach improves the signal separation performance by exploiting features of the conventional approaches. We show the simulation results using artificial data.

Keywords: Blind source separation, Independent componentanalysis, Frequency domain, Permutation ambiguity.

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Authors: Bilal Saeed Raja, M. Ali Iqbal, Imran Ihsan

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Extracting and elaborating software requirements and transforming them into viable software architecture are still an intricate task. This paper defines a solution architecture which is based on the blurred amalgamation of problem space and solution space. The dependencies between domain constraints, requirements and architecture and their importance are described that are to be considered collectively while evolving from problem space to solution space. This paper proposes a revised version of Twin Peaks Model named Win Peaks Model that reconciles software requirements and architecture in more consistent and adaptable manner. Further the conflict between stakeholders- win-requirements is resolved by proposed Voting methodology that is simple adaptation of win-win requirements negotiation model and QARCC.

Keywords: Functional Requirements, Non Functional Requirements, Twin Peaks Model, QARCC.

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Authors: George Cristian Gruia, Michal Kavan

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The article describes a case study on one of Czech Republic-s manufacturing middle size enterprises (ME), where due to the European financial crisis, production lines had to be redesigned and optimized in order to minimize the total costs of the production of goods. It is considered an optimization problem of minimizing the total cost of the work load, according to the costs of the possible locations of the workplaces, with an application of the Greedy algorithm and a partial analogy to a Set Packing Problem. The displacement of working tables in a company should be as a one-toone monotone increasing function in order for the total costs of production of the goods to be at minimum. We use a heuristic approach with greedy algorithm for solving this linear optimization problem, regardless the possible greediness which may appear and we apply it in a Czech ME.

Keywords: Czech, greedy algorithm, minimize, total costs.

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Authors: C. Porkodi, R. Arumuganathan

Abstract:

In this paper a Public Key Cryptosystem is proposed using the number theoretic transforms (NTT) over a ring of integer modulo a composite number. The key agreement is similar to ElGamal public key algorithm. The security of the system is based on solution of multivariate linear congruence equations and discrete logarithm problem. In the proposed cryptosystem only fixed numbers of multiplications are carried out (constant complexity) and hence the encryption and decryption can be done easily. At the same time, it is very difficult to attack the cryptosystem, since the cipher text is a sequence of integers which are interrelated. The system provides authentication also. Using Mathematica version 5.0 the proposed algorithm is justified with a numerical example.

Keywords: Cryptography, decryption, discrete logarithm problem encryption, Integer Factorization problem, Key agreement, Number Theoretic Transform.

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Authors: Saman M. Siddiqui, Fang Jiancheng

Abstract:

Robust nonlinear integrated navigation of GPS and low cost MEMS is a hot topic of research these days. A robust filter is required to cope up with the problem of unpredictable discontinuities and colored noises associated with low cost sensors. H∞ filter is previously used in Extended Kalman filter and Unscented Kalman filter frame. Unscented Kalman filter has a problem of Cholesky matrix factorization at each step which is a very unstable operation. To avoid this problem in this research H∞ filter is designed in Square root Unscented filter framework and found 50% more robust towards increased level of colored noises.

Keywords: H∞ filter, MEMS, GPS, Nonlinear system, robust system, Square root unscented filter.

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Authors: Tamanna Siddiqui, M. Afshar Alam

Abstract:

Automated discovery of Rule is, due to its applicability, one of the most fundamental and important method in KDD. It has been an active research area in the recent past. Hierarchical representation allows us to easily manage the complexity of knowledge, to view the knowledge at different levels of details, and to focus our attention on the interesting aspects only. One of such efficient and easy to understand systems is Hierarchical Production rule (HPRs) system. A HPR, a standard production rule augmented with generality and specificity information, is of the following form: Decision If < condition> Generality Specificity . HPRs systems are capable of handling taxonomical structures inherent in the knowledge about the real world. This paper focuses on the issue of mining Quantified rules with crisp hierarchical structure using Genetic Programming (GP) approach to knowledge discovery. The post-processing scheme presented in this work uses Quantified production rules as initial individuals of GP and discovers hierarchical structure. In proposed approach rules are quantified by using Dempster Shafer theory. Suitable genetic operators are proposed for the suggested encoding. Based on the Subsumption Matrix(SM), an appropriate fitness function is suggested. Finally, Quantified Hierarchical Production Rules (HPRs) are generated from the discovered hierarchy, using Dempster Shafer theory. Experimental results are presented to demonstrate the performance of the proposed algorithm.

Keywords: Knowledge discovery in database, quantification, dempster shafer theory, genetic programming, hierarchy, subsumption matrix.

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Authors: Z. Ulukan, E. Demircioğlu

Abstract:

Facility location is a complex real-world problem which needs a strategic management decision. This paper provides a general review on studies, efforts and developments in Facility Location Problems which are classical optimization problems having a wide-spread applications in various areas such as transportation, distribution, production, supply chain decisions and telecommunication. Our goal is not to review all variants of different studies in FLPs or to describe very detailed computational techniques and solution approaches, but rather to provide a broad overview of major location problems that have been studied, indicating how they are formulated and what are proposed by researchers to tackle the problem. A brief, elucidative table based on a grouping according to “General Problem Type” and “Methods Proposed” used in the studies is also presented at the end of the work.

Keywords: Discrete location problems, exact methods, heuristic algorithms, single source capacitated facility location problems.

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Authors: Peerapong Uthansakul, Monthippa Uthansakul

Abstract:

The rapid growth of e-Commerce services is significantly observed in the past decade. However, the method to verify the authenticated users still widely depends on numeric approaches. A new search on other verification methods suitable for online e-Commerce is an interesting issue. In this paper, a new online signature-verification method using angular transformation is presented. Delay shifts existing in online signatures are estimated by the estimation method relying on angle representation. In the proposed signature-verification algorithm, all components of input signature are extracted by considering the discontinuous break points on the stream of angular values. Then the estimated delay shift is captured by comparing with the selected reference signature and the error matching can be computed as a main feature used for verifying process. The threshold offsets are calculated by two types of error characteristics of the signature verification problem, False Rejection Rate (FRR) and False Acceptance Rate (FAR). The level of these two error rates depends on the decision threshold chosen whose value is such as to realize the Equal Error Rate (EER; FAR = FRR). The experimental results show that through the simple programming, employed on Internet for demonstrating e-Commerce services, the proposed method can provide 95.39% correct verifications and 7% better than DP matching based signature-verification method. In addition, the signature verification with extracting components provides more reliable results than using a whole decision making.

Keywords: Online signature verification, e-Commerce services, Angular transformation.

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Authors: T. S. Ozsahin, V. Kahya, A. Birinci, A. O. Cakiroglu

Abstract:

In this study, the contact problem of a layered composite which consists of two materials with different elastic constants and heights resting on two rigid flat supports with sharp edges is considered. The effect of gravity is neglected. While friction between the layers is taken into account, it is assumed that there is no friction between the supports and the layered composite so that only compressive tractions can be transmitted across the interface. The layered composite is subjected to a uniform clamping pressure over a finite portion of its top surface. The problem is reduced to a singular integral equation in which the contact pressure is the unknown function. The singular integral equation is evaluated numerically and the results for various dimensionless quantities are presented in graphical forms.

Keywords: Frictionless contact, Layered composite, Singularintegral equation, The theory of elasticity.

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Authors: Wayan F. Mahmudy, Romeo M. Marian, Lee H. S. Luong

Abstract:

This paper presents modeling and optimization of two NP-hard problems in flexible manufacturing system (FMS), part type selection problem and loading problem. Due to the complexity and extent of the problems, the paper was split into two parts. The first part of the papers has discussed the modeling of the problems and showed how the real coded genetic algorithms (RCGA) can be applied to solve the problems. This second part discusses the effectiveness of the RCGA which uses an array of real numbers as chromosome representation. The novel proposed chromosome representation produces only feasible solutions which minimize a computational time needed by GA to push its population toward feasible search space or repair infeasible chromosomes. The proposed RCGA improves the FMS performance by considering two objectives, maximizing system throughput and maintaining the balance of the system (minimizing system unbalance). The resulted objective values are compared to the optimum values produced by branch-and-bound method. The experiments show that the proposed RCGA could reach near optimum solutions in a reasonable amount of time.

Keywords: Flexible manufacturing system, production planning, part type selection problem, loading problem, real-coded genetic algorithm

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Authors: Salma El Hajjami, Jamal Malki, Alain Bouju, Mohammed Berrada

Abstract:

With the expansion of machine learning and data mining in the context of Big Data analytics, the common problem that affects data is class imbalance. It refers to an imbalanced distribution of instances belonging to each class. This problem is present in many real world applications such as fraud detection, network intrusion detection, medical diagnostics, etc. In these cases, data instances labeled negatively are significantly more numerous than the instances labeled positively. When this difference is too large, the learning system may face difficulty when tackling this problem, since it is initially designed to work in relatively balanced class distribution scenarios. Another important problem, which usually accompanies these imbalanced data, is the overlapping instances between the two classes. It is commonly referred to as noise or overlapping data. In this article, we propose an approach called: One Side Behavioral Noise Reduction (OSBNR). This approach presents a way to deal with the problem of class imbalance in the presence of a high noise level. OSBNR is based on two steps. Firstly, a cluster analysis is applied to groups similar instances from the minority class into several behavior clusters. Secondly, we select and eliminate the instances of the majority class, considered as behavioral noise, which overlap with behavior clusters of the minority class. The results of experiments carried out on a representative public dataset confirm that the proposed approach is efficient for the treatment of class imbalances in the presence of noise.

Keywords: Machine learning, Imbalanced data, Data mining, Big data.

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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: Alireza Rezaei, Fatemeh Baharifard, Kourosh Parand

Abstract:

In this paper we improve the quasilinearization method by barycentric Lagrange interpolation because of its numerical stability and computation speed to achieve a stable semi analytical solution. Then we applied the improved method for solving the Fin problem which is a nonlinear equation that occurs in the heat transferring. In the quasilinearization approach the nonlinear differential equation is treated by approximating the nonlinear terms by a sequence of linear expressions. The modified QLM is iterative but not perturbative and gives stable semi analytical solutions to nonlinear problems without depending on the existence of a smallness parameter. Comparison with some numerical solutions shows that the present solution is applicable.

Keywords: Quasilinearization method, Barycentric lagrange interpolation, nonlinear ODE, fin problem, heat transfer.

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Authors: Hiroshi Yamaguchi, Phillip C.-Y. Sheu, Ryo Fujita, Shigeo Tsujii

Abstract:

In this paper, the secure BioSemantic Scheme is presented to bridge biological/biomedical research problems and computational solutions via semantic computing. Due to the diversity of problems in various research fields, the semantic capability description language (SCDL) plays and important role as a common language and generic form for problem formalization. SCDL is expected the essential for future semantic and logical computing in Biosemantic field. We show several example to Biomedical problems in this paper. Moreover, in the coming age of cloud computing, the security problem is considered to be crucial issue and we presented a practical scheme to cope with this problem.

Keywords: Biomedical applications, private information retrieval (PIR), semantic capability description language (SCDL), semantic computing.

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Authors: Jieer Wu, Zheshu Ma

Abstract:

Nondestructive testing in engineering is an inverse Cauchy problem for Laplace equation. In this paper the problem of nondestructive testing is expressed by a Laplace-s equation with third-kind boundary conditions. In order to find unknown values on the boundary, the method of fundamental solution is introduced and realized. Because of the ill-posedness of studied problems, the TSVD regularization technique in combination with L-curve criteria and Generalized Cross Validation criteria is employed. Numerical results are shown that the TSVD method combined with L-curve criteria is more efficient than the TSVD method combined with GCV criteria. The abstract goes here.

Keywords: ill-posed, TSVD, Laplace's equation, inverse problem, L-curve, Generalized Cross Validation.

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Authors: Tai-Hsi Wu, Jinn-Yi Yeh, Chin-Chih Chang

Abstract:

Cell formation is the first step in the design of cellular manufacturing systems. In this study, a general purpose computational scheme employing a hybrid tabu search algorithm as the core is proposed to solve the cell formation problem and its variants. In the proposed scheme, great flexibilities are left to the users. The core solution searching algorithm embedded in the scheme can be easily changed to any other meta-heuristic algorithms, such as the simulated annealing, genetic algorithm, etc., based on the characteristics of the problems to be solved or the preferences the users might have. In addition, several counters are designed to control the timing of conducting intensified solution searching and diversified solution searching strategies interactively.

Keywords: Cell formation problem, Tabu search

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