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This paper deals with the realization of retrieval and feature description systems for clusters by using logical rule generations based on the Genetic Programming (GP). At first, whole data is divided into several clusters and the rules are improved based the GP. The fitness of individuals is defined in proportion to the hits of corresponding logical expression to the samples in targeted cluster c, but also in inversely proportion to the hits outside the cluster c. The GP method is applied to various real world data by showing effective performance compared to conventional methods. [ABSTRACT FROM AUTHOR]

The abstract should summarize the contents of the paper and should contain at least 70 and at most 150 words. It should be set in 9-point font size and should be inset 1.0 cm from the right and left margins. There should be two blank (10-point) lines before and after the abstract. This document is in the required format. Roadmapping, as a strategic planning tool, is attracting increasing applications in industries. By applying the principles of Interactive Planning (IP), this paper puts forward a new solution for making personal academic research roadmaps. Then this paper introduces an ongoing project that is to develop a roadmapping support system based on the solution, and gives some considerations about applying the i-System Methodology for enhancing the knowledge creation in a roadmapping process. [ABSTRACT FROM AUTHOR]

This paper is about using ontologies to identify the objects from a problem domain text description. At the center of object models and ontologies are objects within a given problem domain is similar to the concept provided by ontologies. This paper addresses ontologies as a basis of a methodology for object modeling, including available tools, particularly OntoExtract, which can help the conversion process. This paper describes how the developers can implement this methodology on the base of an illustrative example. [ABSTRACT FROM AUTHOR]

Most of information has been storing and managing in relational databases and there are many researches to store OWL ontologies. In this situation, a study on efficient access control model using relational security model is required. The paper proposes a novel access control model for OWL ontologies in relational database systems. The access control is realized through evaluating queries against an OWL data view. On one hand, the OWL data view prevents the sensitive information revealed to unauthorized users. On the other hand it considers the inference ability of users. An empirical study verifies the effectiveness of our approach. [ABSTRACT FROM AUTHOR]

When we want to measure parameters of the Modulation Transfer Function (MTF) from remote sensing image directly, the sharp edges are usually used as targets. But for noise, blur and the complexity of the images, fully automatic locating the expected edge is still an unsolved problem. This paper improves the semi-auto edge extraction algorithm of live-wire [1] and introduces it into the knife-edge method [8] of MTF measuring in remote sensing image. Live-wire segmentation is a novel interactive algorithm for efficient, accurate, and reproducible boundary extraction that requires minimal user input with a mouse. The image is transformed into a weighted graph with variety restrictions. Edge searching is based on dynamic programming of Dijkstra's algorithm [5]. Optimal boundaries are computed and selected at interactive rates as the user moves the mouse starting from a manually specified seed point. In this paper, a promoted model of live-wire is proposed to measuring the on orbit Modulation Transfer Function for high spatial resolution imaging satellites. We add the no-linear diffusion filter in the local cost function to ensure the accurateness of the extraction of edges. It can both de-noise and do not affect the shape of the edges when we extracting the edges, so that the calculation of the MTF is more reasonable and precise. [ABSTRACT FROM AUTHOR]

In the recent years, classification models based on mathematical programming have been widely used in business intelligence. In this paper, a new Multi-Criteria Quadratic-Programming Linear Classification (MQLC) model is proposed and tested with VIP E-Mail dataset. This experimental study uses a variance of K-fold Cross-Validation to demonstrate the accuracy and stability of the model. Finally, we compare our model with the decision tree by using commercial software C5.0. The result indicates that the proposed MQLC model performs better than decision tree on small samples. [ABSTRACT FROM AUTHOR]

In the field of 3D model retrieval, the combination of different kinds of shape feature is a promising way to improve retrieval performance. And the efficient categorization of 3D models is critical for organizing models. The paper proposes a combination method, which automatically decides the fixed weight of different shape features. Based on the combined shape feature, the paper applies the cluster analysis technique to efficiently categorize 3D models according to their shape. The standard 3D model database, Princeton Shape Benchmark, is adopted in experiment and our method shows good performance not only in improving retrieval performance but also in categorization. [ABSTRACT FROM AUTHOR]

This paper introduces several feature selection methods on the VIP E-Mail account analysis, and then uses SVM to classify the users in order to maintain the ones who may leave in a short time. The websites hosting companies can follow the strategies, which are investigated in this paper, to reduce their labor cost and provide an attractive and simple registration for the users. The result shows that we can also reach the feasible predict accuracy. [ABSTRACT FROM AUTHOR]

Classification is an important task in the fields of data mining and pattern recognition. Now there have been many algorithms for this task, while most of them do not focus on the application in databases. In this paper we extend the definition of function dependency, prove the properties of the extended function dependency, and on this basis propose an algorithm for classification. According to the two theorems in the paper, our algorithm is complete that means it can find all the classification rules from the database. At last, we demonstrate our algorithm by an example that shows the validity of our algorithm. [ABSTRACT FROM AUTHOR]

In order to give adaptive instruction to the learner, it needs to know what knowledge the learner has and what goals the learner is trying to archive. This paper proposes a method to build a model based on Bayesian networks in order to assess the learner's knowledge level. An overlay student model based on Bayesian networks is presented. This student model built on knowledge relationships with prediction ability is discussed in details. In this model, an assessing method based on Logistic model in IRT with three parameters is provided to evaluate student's performance. A case study in the course of Data Structure is illustrated in this paper. [ABSTRACT FROM AUTHOR]

OWL Web Ontology Language is a W3C recommended Language for representing machine-readable knowledge with more facilities than other knowledge representation languages. In this paper, we present a Use-Case based Fuzzy Ontology Constructing (UFOC) methodology for the building of edutainment ontology, which is encoded with OWL. Besides, a solution of representing fuzzy relation in OWL is also provided. In the edutainment ontology, two fuzzy relations, DE and AE are discovered, both playing vital roles in property calculation among online computer game. [ABSTRACT FROM AUTHOR]

In wireless sensor networks, an efficient Medium Access Control (MAC) protocol is critical, especially in terms of energy consumption and message latency. This paper introduces a novel protocol that nodes periodically sleep to conserve energy. When the source node has data packets to send, it uses a wakeup message to awake the sleeping nodes. The protocol needn't take the synchronization which must be achieved in S-MAC. It especially suits to the wireless sensor networks with narrow bandwidth. [ABSTRACT FROM AUTHOR]

The pest catastrophe prediction in ecology catastrophe is one of important part in expert system of intelligence agriculture and also the guarantee for preventing and controlling the pest catastrophe occurrence efficiently. The paper introduces the basic principles and methods of current catastrophe prediction in ecology catastrophe. According to modeling for the dynamic process of population, up-grown and amount of spawn, the paper finds out the trigger point and critical value inducing the pest catastrophe and implements the catastrophe prediction of Cnaphalocrosis Medinalis, which take measures before catastrophe to prevent big population coming into being. [ABSTRACT FROM AUTHOR]

In this paper the Vehicle Ad Hoc Network (VANET) is examined. As widely agreed VANETs must rely heavily on node-to-node communication while ease of access has to be assured at the same time. Beside the performance ensuring data authentication is another concern in VANETs. In our paper we focus on security aspects for the VANETs that aim to ensure data authentication and allow to ensure data secrecy. Ensuring data secrecy is not a standard feature of the VANETs since usually it is assumed that nodes in the network has to be able to receive all information send over the channel. However we think that it is necessary to ensure security against data eavesdrop and message forgery in some applications (e.g. police pursuits or military convoys). [ABSTRACT FROM AUTHOR]

Users are interested greatly in a user creative movie (UCM) production among various online contents. The UCM production using music and picture is the method that users make the movie easily. However, the UCM production service has the problem that any association does not exist in the music and picture. To solve this problem, we propose the UCM production method which uses a music analysis and picture analysis in the paper. A music analysis finds a picture change time according to the rhythm. This finds strong part of the sound which uses Root-Mean-Square (RMS). A picture analysis finds the association at each picture and arranges the sequence which the picture appears. This classifies the picture which uses structure simplicity of the picture (SSP) and face region detection. Therefore, if we use a music and picture analysis at the UCM production, users may make natural and efficient movie. [ABSTRACT FROM AUTHOR]

In any parallel programming language; collective communication operations involve more than one thread/process and act on multiple streams of data. The language's API provides both algorithmic and run-time system support to optimize the performance of these operations. Some developers, however, choose to play clever and start from the language's primitive operations and write their own versions of the collective operations. The question that always pops up: Are these developers wise? In this paper, we check the case of UPC (Universal Parallel C) and prove that in some circumstances, it is wiser for developers to optimize starting from UPC's primitive operations. In our testing we found out that optimization using primitive UPC operations by the developers can have better performance than readily available UPC's collective operations. In this paper, we pin point specific optimizations at both the algorithmic and the runtime support levels that developers could use to uncover missed optimization opportunities. We also propose a novel approach to implementing UPC collective operations across clusters. Under this methodology, performance-critical components are moved close to the network. We argue that this provide unique advantages for performance improvement. [ABSTRACT FROM AUTHOR]

This paper is concerned with the design and implementation of the context handlers for context-awareness in a ubiquitous computing environment. The context handlers address design issues of context handling: abstraction of context values, semantic interoperability of context information, logical and semantic interpretation of context information, and structuralization of context information for specifying various situations. To address these design issues, we define a structural context model, a context schema based on ontology, and user-friendly context value ontology. We also use ontology reasoning and rule-based reasoning. This paper focuses on context handling methods in a context-aware system. We expect that these context handling methods will help context-aware system developers to design and implement context handlers in a ubiquitous computing environment. [ABSTRACT FROM AUTHOR]

In hostile environments, the communication content and communication route need to be shielded from malicious attackers. The AnonDSR (Anonymous Dynamic Source Routing for Mobile Ad-Hoc Networks) protocol has been proposed to ensure security and anonymity in ad-hoc networks. The protocol transmits data after establishing an encryption key and communication route. One weakness of the AnonDSR is that it consists of 3 steps: security parameter establishment, route discovery, and data transmission. In this paper, we propose a variant of AnonDSR that reduces the 3 steps into 2 steps. Our protocol decreases the communication route setup time for each communication session by 31% in comparison with the AnonDSR. [ABSTRACT FROM AUTHOR]

Computational origami is the computer assisted study of origami as a branch of science of shapes. The origami construction is a countably finite sequence of fold steps, each consisting in folding along a line. In this paper, we formalize origami construction. We model origami paper by a set of faces over which we specify relations of overlay and adjacency. A fold line is determined by a specific fold method. After folding along the fold line, the structure of origami is transformed; some faces are divided and moved, new faces are created and therefore the relations over the faces change. We give a formal method to construct the model origami. The model furthermore induces a graph of layers of faces. We give two origami examples as the application of our model. They exhibit non-trivial aspects of origami which are revealed only by formal modeling. The model is the abstraction of the implemented core of the system of computational origami called Eos (E-origami system). [ABSTRACT FROM AUTHOR]

This paper proposes a mechanism to secure the mobile IPv6 networks by integrating identity based cryptosystem with cryptographically generated address. Based on an in-depth analysis of attacks and countermeasures in the CGA-based protocols, this paper gives an analysis of the so called "unauthentic key attacks", and presents a mechanism to solve this problem by integrating an IBC scheme called Combined Public Key (CPK) with CGA. Both the deployment considerations and performance analysis of this IBC-CGA scheme are present in the paper. [ABSTRACT FROM AUTHOR]

In our recent study, we have presented an approach for tracing illegal users in content distribution networks using watermarking and fingerprinting techniques [1][2]. In this paper we generalize our previous work, further the collusion robustness is supplemented by additional security and practical experiment. This includes a more efficient tree decision method, generalization of the fingerprinting system and detailed investigation of the robustness against collusion attacks. Content is distributed along a specified tree, with the seller as the root, and the buyers as the internal nodes or leaves. The fingerprinting step is achieved by the insertion of unique information in the video wavelet coefficients by temporal wavelet transform. Our system is able to detect the fingerprint even if the video content has been distorted by collusion attacks. [ABSTRACT FROM AUTHOR]

In this paper we survey a number of different social software websites and analyze their revenue models. The main revenue models that we analyzed included - advertising, premium memberships, affiliate programs, donations and merchandize sale. The survey will categorize different social software based upon the revenue model being adopted. The main aim of this paper is to highlight the need for studying revenue sharing models which attempt to reward the users in the online community for participating in a particular social software website. A total of 7 revenue sharing websites would be discussed to show the importance of revenue sharing. [ABSTRACT FROM AUTHOR]

The Reference Model for Open Distributed Processing (RM-ODP) defines a framework within which support of distribution, interoperability and portability can be integrated. However other ODP standards have to be defined. We treat in this paper the need of formal notation for structural concepts in the enterprise language. Indeed, the ODP viewpoint languages are abstract in the sense that they define what concepts should be supported not how these concepts should be represented. One approach to define formal semantics of a language is denotational elaborating the instance denoted by a sentence of the language in a particular context. Using the denotational semantics in the context of UML/OCL meta-modelling approach and the denotational semantics we define in this paper syntax and semantics for a fragment of ODP structural concepts defined in the RM-ODP foundations part and in the enterprise language. These specification concepts are suitable for describing and constraining ODP enterprise viewpoint specifications. [ABSTRACT FROM AUTHOR]

This paper is a position paper on the nature of dynamic systems. While there is an agreement on the definition of what a static distributed system is, there is no agreed definition on what a dynamic distributed system is. This paper is a first step in that direction. To that end, it emphasizes two orthogonal dimensions that are present in any dynamic distributed system, namely the varying and possibly very large number of entities that currently define the system, and the fact that each of these entities knows only a few other entities (its neighbors) and possibly will never be able to know the whole system it is a member of. To illustrate the kind of issues one has to cope with in dynamic systems, the paper considers, as a "canonical" problem, a simple data aggregation problem. It shows the type of dynamic systems in which that problem can be solved and the ones in which it cannot be solved. The aim of the paper is to give the reader an idea of the subtleties and difficulties encountered when one wants to understand the nature of dynamic distributed systems. [ABSTRACT FROM AUTHOR]

This paper proposes an implementation of the data structure called bag or multiset used by descriptive programming languages (e.g. Gamma, Linda) over an open system. In this model, a succession of "chemical reactions" consumes the elements of the bag and produces new elements according to specific rules. This approach is particularly interesting as it suppresses all unneeded synchronization and reveals all the potential parallelism of a program. An efficient implementation of a bag provides an efficient implementation of the subsequent program. This paper defines a new communication and synchronization model adapted from workqueues used in parallel computing. The proposed model allows to benefit from the potential parallelism offered by this style of programming when only an approximate solution is needed. [ABSTRACT FROM AUTHOR]

In this paper, a speech emotion recognition system and its application for call-center system is proposed. In general, a speech captured by cellular-phone contains noises due to the mobile network and speaker environment. In order to minimize the effect of these noises and so improve the system performance, we employ a simple MA filter at the feature domain. Two pattern classification methods, k-NN and SVM with probability estimate, are compared to distinguish two emotional states- neutral and anger- for call-center application. The experimental results indicate that the proposed method provides very stable and successful emotional classification performance and it promises the feasibility of the agent for mobile communication services. [ABSTRACT FROM AUTHOR]

In this paper, we obtain the main term of the average stochastic complexity for certain complete bipartite graph-type spin models in Bayesian estimation. We study the Kullback function of the spin model by using a new method of eigenvalue analysis first and use a recursive blowing up process for obtaining the maximum pole of the zeta function which is defined by using the Kullback function. The papers [1,2] showed that the maximum pole of the zeta function gives the main term of the average stochastic complexity of the hierarchical learning model. [ABSTRACT FROM AUTHOR]

Microarray is a fascinating technology that provides us with accurate predictions of the state of biological tissue samples simply based on the expression levels of genes available from it. Of particular interest in the use of microarray technology is the classification of normal and tumor tissues which is vital for accurate diagnosis of the disease of interest. In this paper, we shall make use of geometric representation from graph theory for the classification of normal and tumor tissues of colon and ovary. The accuracy of our geometric representation-based classification algorithm will be shown to be comparable to that of the currently known best classification algorithms for the two datasets. In particular, the presented algorithm will be shown to have the highest classification accuracy when the number of genes used for classification is small. [ABSTRACT FROM AUTHOR]

Fault Tolerance is an increasing challenge for integrated circuits due to semiconductor technology scaling. This paper looks at how artificial evolution may be tuned to the creation of novel redundancy structures which may be applied to meet this challenge. An experimental setup and results for creating "useful" redundant structures is presented. [ABSTRACT FROM AUTHOR]

The precision and power consumption of pipelined FFT processors are highly affected by the wordlengths in fixed-point application systems. Due to nonconvex space, wordlength optimization under multiple competing objectives is a complex, time-consuming task. This paper proposes a new approach to solving the multi-objective evolutionary optimization design of pipelined FFT processors for wireless OFDM receivers. In our new approach, the number of design variables can be significantly reduced. We also fully investigate how the internal wordlength configuration affects the precision and power consumption of the FFT by setting the wordlengths of input and FFT coefficients to be 12 and 16 bits in fixed-point number type. A new system-level model for representing power consumption of the pipelined FFT is also developed and utilized in this paper. Finally, simulation results are provided to validate the effectiveness of applying the nondominated sorting genetic algorithm to the multi-objective evolutionary design of a 1024-point pipelined FFT processor for wireless OFDM receivers. [ABSTRACT FROM AUTHOR]

Cryptanalysis with genetic algorithm has attracted much interest in recent years. This paper presents an approach for the cryptanalysis of two-round DES based on genetic algorithm. However, cryptanalysis of two-round DES using genetic algorithm is usually a difficult task. In this paper, we adopt known plaintext attack and produce a variety of optimum keys based on fitness function. Furthermore, we count every bit of optimal keys one by one, and find some valuable bits, which generate a significant deviation from the other observed bits. Finally, the 56-bit key is successfully gained without searching the whole search space. The experimental result indicates that this is a promising method and can be adopted to handle other complex block ciphers. [ABSTRACT FROM AUTHOR]

This paper mainly discusses the genetic algorithms in optimization of network planning project. It focuses on the study of multi-task scheduling (Resource-constrained project scheduling problem, RCPSP). For the problem of the resource-constrained task scheduling problem, the paper proposes a method to improve the genetic algorithms optimization of multi-task scheduling problem. From the aspects of the establishment of the optimized algorithms models, the algorithms design, the accomplishment of algorithms as well as the analysis of the result, we conducts this study in detail, and makes a comparison analysis with the other 11 heuristic methods. In this way, we testify our method and get the good results. [ABSTRACT FROM AUTHOR]

Different constraint handling techniques have been incorporated with genetic algorithms (GAs), however most of current studies are based on computer experiments. The paper makes an theoretical analysis of GAs using penalizing infeasible solutions and repairing infeasible solutions on average knapsack problem. It is shown that GAs using the repair method is more efficient than GAs using the penalty method on average capacity knapsack problems. [ABSTRACT FROM AUTHOR]

This paper focuses on the limit behaviors of evolutionary algorithms based on finite search space by using the properties of Markov chains and Perron-Frobenius Theorem. Some convergence results of general square matrices are given, and some useful properties of homogeneous Markov chains with finite states are investigated. The geometric convergence rates of the transition operators, which is determined by the revised spectral of the corresponding transition matrix of a Markov chain associated with the EA considered here, are estimated. Some applications of the theoretical results in this paper are also discussed. [ABSTRACT FROM AUTHOR]

This paper introduces a novel wrapper-mediator based semantic data grid service mechanism to solve the problem of Semantic heterogeneity and few compatible data sources. It uses ontology based semantic information to wrap the heterogeneous data source, and employs mediator structure to supply accessing interface for the data sources, and it extends semantic query, mapping and fusion languages to support semantic grid communication mechanism. The extension of XML algebra with semantic query enhanced is discussed to enable semantic querying on data gird environment. [ABSTRACT FROM AUTHOR]

This paper discusses and compares several policies to place replicas in tree networks, subject to server capacity and QoS constraints. The client requests are known beforehand, while the number and location of the servers are to be determined. We study three strategies. The first two strategies assign each client to a unique server while the third allows requests of a client to be processed by multiple servers. The main contribution of this paper is to assess the impact of QoS constraints on the total replication cost. In this paper, we establish the NP-completeness of the problem on homogeneous networks when the requests of a given client can be processed by multiple servers. We provide several efficient polynomial heuristic algorithms for NP-complete instances of the problem. [ABSTRACT FROM AUTHOR]

This paper is concerned with the problem of finding a representative sample of Pareto-optimal points in multi-objective optimization. The Normal Boundary Intersection algorithm is a scalarization scheme for generating a set of evenly spaced Efficient solutions. A drawback of this algorithm is that Pareto-optimality of solutions is not guaranteed. The contributions of this paper are two-fold. First, it presents alternate formulation of this algorithms, such that (weak) Pareto-optimality of solutions is guaranteed. This improvement makes these algorithm theoretically equivalent to other classical algorithms (like weighted-sum or ε-constraint methods), without losing its ability to generate a set of evenly spaced Efficient solutions. Second, an algorithm is presented so as to know beforehand about certain sub-problems whose solutions are not Pareto-optimal and thus not wasting computational effort to solve them. The relationship of the new algorithm with weighted-sum and goal programming method is also presented. [ABSTRACT FROM AUTHOR]

This paper describes efficient word meaning acquisition for infant agents (IAs) based on learning biases that are observed in children's language development. An IA acquires word meanings through learning the relations among visual features of objects and acoustic features of human speech. In this task, the IA has to find out which visual features are indicated by the speech. Previous works introduced stochastic approaches to do this, however, such approaches need many examples to achieve high accuracy. In this paper, firstly, we propose a word meaning acquisition method for the IA based on an Online-EM algorithm without learning biases. Then, we implement two types of biases into it to accelerate the word meaning acquisition. Experimental results show that the proposed method with biases can efficiently acquire word meanings. [ABSTRACT FROM AUTHOR]

Gene selection is usually the crucial first step in microarray data analysis. One class of typical approaches is to calculate some discriminative scores using data associated with a single gene. Such discriminative scores are then sorted and top ranked genes are selected for further analysis. However, such an approach will result in redundant gene set since it ignores the complex relationships between genes. Recent researches in feature subset selection began to tackle this problem by limiting the correlations of the selected feature set. In this paper, we propose a novel general framework BFSS: Boost Feature Subset Selection to improve the performance of single-gene based discriminative scores using bootstrapping techniques. Features are selected from dynamically adjusted bootstraps of the training dataset. We tested our algorithm on three well-known publicly available microarray data sets in the bioinformatics community. Encouraging results are reported in this paper. [ABSTRACT FROM AUTHOR]

The paper proposes meta-ontology of the user modeling field. Ontology is meant to structure the state-of-the-art in the field and serve as a central reference point and as a tool to index systems, papers and learning media. Such ontology is beneficial for both the user modeling research community and the students as it creates a shared conceptualization of the known approaches to building user models and their implementations. [ABSTRACT FROM AUTHOR]

This paper presents active contours based method for hand tracking using color information. The main problem in active contours based approach is that results are very sensitive to location of the initial curve. Initial curve far form the object induces more heavy computational cost, low accuracy of results, as well as missing the object that has a large movement. Therefore, this paper presents a hand tracking method using a mean shift algorithm and active contours. The proposed method consists of two steps: hand localization and hand extraction. In the first step, the hand location is estimated using mean shift. And the second step, at the location, evolves the initial curve using an active contour model. To assess the effectiveness of the proposed method, it is applied to real image sequences which include moving hand. [ABSTRACT FROM AUTHOR]

This paper will present a new approach to the interpretation of semantic information retrieved from complex X-ray images. The tasks of the analysis and the interpretation of cognitive meaning of selected medical diagnostic images are made possible owing to the application of graph image languages based on tree grammars. One of the main problems in the fast accessing and analysis of information collected in various medical examinations is the way to transform efficiently the visual information into a form enabling intelligent recognition and understanding of semantic meaning of selected patterns. Another problem in accessing for useful information in multimedia databases is the creation of a method of representation and indexing of important objects constituting the data contents. In the paper we describe some examples presenting ways of applying picture languages techniques in the creation of intelligent cognitive multimedia systems for selected classes of medical images showing especially wrist structures. [ABSTRACT FROM AUTHOR]

We consider the problem of determining the disassembly schedule (quantity and timing) of products in order to satisfy the demand of their parts or components over a finite planning horizon. This paper focuses on the capacitated version of the problem for the objective of minimizing the sum of setup, disassembly operation, and inventory holding costs. The problem is formulated as an integer program, and to solve the problem, a Lagrangean heuristic algorithm is developed after reformulating the integer program. To show the performance of the heuristic algorithm, computational experiments are done on randomly generated test problems, and the test results show that the algorithm suggested in this paper works well. [ABSTRACT FROM AUTHOR]

Disassembly scheduling is the problem of determining the timing and quantity of disassembling used products to satisfy the demands of their parts or components over the planning horizon. This paper focuses on the case of single product type without parts commonality while the resource capacity restrictions are explicitly considered. The problem is formulated as an integer program for the objective of minimizing the number of products to be disassembled, and an optimal algorithm, after deriving the properties of the problem, is suggested. Computational experiments are done on randomly generated test problems, and the results are reported. [ABSTRACT FROM AUTHOR]

Many companies are beginning to change the way they develop products due to increasing awareness of environmentally conscious product development. To copy with these trends, designers are being asked to incorporate environmental criteria into the design process. Recently Life Cycle Assessment (LCA) is used to support the decision-making for product design and the best alternative can be selected based on its estimated environmental impacts and benefits. Both the lack of detailed information and time for a full LCA for a various range of design concepts need the new approach for the environmental analysis. This paper presents an artificial neural network (ANN) based approximate LCA model of product concepts for product groups using a product classification method. A product classification method is developed to support the specialization of ANN based LCA model for different classes of products. Hierarchical clustering is used to guide a systematic identification of product groups based upon environmental categories using the C4.5 decision tree algorithm. Then, an artificial neural network approach is used to estimate an approximate LCA for classified products with product attributes and environmental impact drivers identified in this paper. [ABSTRACT FROM AUTHOR]

Determining product mix under the theory of constraints (TOC) has been widely considered by many researchers. The product mix problem in a multi-bottleneck environment is much more complicated than a single-bottleneck system. In all researches, which have been done in this field, only one criterion has been considered and it is the profit resulted from allocating one unit of bottleneck capacity to each product. In this paper, another criterion is considered together with the first one. The new criterion, which is very important in decision-making, is late delivery cost. Another contribution of the paper is that it assumes each bottleneck as a decision-maker and applies group decision-making techniques. The new approach benefits from the advantage of reaching optimum solution. This will be shown through an example and the results of the new approach will be used in the objective function of an integer linear programming (ILP) model in order to reach optimum solution. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive and successful application of data mining methodologies to improve wafer yield in a semiconductor wafer fabrication system. To begin with, this paper applies a clustering method to automatically identify AUF (Area Uniform Failure) phenomenon from data instead of visual inspection that bad chips occurs in a specific area of wafer. Next, sequential pattern analysis and classification methods are applied to find out machines and parameters that are cause of low yield, respectively. Finally, this paper demonstrates an information system, Y2R-PLUS (Yield Rapid Ramp-up, Prediction, analysis & Up Support) that is developed in order to analyze wafer yield in a Korea semiconductor manufacturer. [ABSTRACT FROM AUTHOR]

Many industries are using damage control inputs to control the unpredictable damages to yield. For example, chemical production processes are using catalysts to promote reactions. However, use of these inputs can generate the pollutions and the efficient use of them can contribute to the protection of environment. This paper uses a famous nonparametric method (Data Envelopment Analysis: DEA) to estimate the efficiency in the use of polluting inputs such as damage control inputs and uses a regression analysis to identify factors which affect the efficiency. The results from application to an agricultural field show the existence of substantial inefficiency and heterogeneity across farms. This implies that uniform standards or incentives such as Pigouvian taxes are not useful to regulate the use of polluting inputs. Moreover, technical efficiency was determined by some farm-level characteristics. [ABSTRACT FROM AUTHOR]

Security has been more crucial issue as targets of attacker are wide ranges from personal information to various things in ubiquitous computing environments. Portable computing devices such as cellular phone, PDA, and smart phone in such conditions have been exposured under security threats, which cause attacker to exploit malicious code and modification of storied data. In this paper we present security threats and their countermeasures in technical, manageable, and physical aspect of mobile portable computing devices. We believe that this paper will contributes on initiating a research on security issues of mobile portable computing devices and provide users with guidance to keep their information safe in mobile communication environments. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new learning process (or experience) model, which is called SCO Control Net, to be possibly applicable to the SCORMSharable Content Object Reference Model by the Advance Distributed Learning (ADL) Initiative that aims to foster the e-Learning specifications and standards. content aggregation model for e-Learning management systems. In terms of the representation of the learning process model, the current SCORM content aggregation model supports a rule-based model for defining a set of rules that describe the intended sequence and ordering of learning activities in a tree-structured content organization. On the other hand, the SCO Control Net aims to support a process-based model for explicitly defining the rules. That is, it is intended to realize the concept of process-driven content organization by separating the learning process from the SCORM's content organization. We would call that the former is content-driven aggregation model, and the later is process-driven aggregation model. This paper formalizes a theoretical basis of the process-driven aggregation model by representing the sequence of learning activities through the SCO control net. We strongly believe that the process-driven aggregation model delivers a way of much more convenient content aggregating work and system, in terms of not only defining the intended sequence and ordering of learning activities, but also building the runtime environment for sequencing and navigation of learning activities and experiences. Keywords: SCORM Content Aggregation Model, Sharable Content Object, e-Learning Management System, SCO Control Net, Process-driven Content Aggregation Model, Sequencing and Navigation of Learning Process and Experience. [ABSTRACT FROM AUTHOR]