Search results for: Task.

Authors: Yifan Fan, Xudong Luo, Pingping Lin

Abstract:

An essential task in the field of artificial intelligence is to allow computers to interact with people through natural language. Therefore, researches such as virtual assistants and dialogue systems have received widespread attention from industry and academia. The response generation plays a crucial role in dialogue systems, so to push forward the research on this topic, this paper surveys various methods for response generation. We sort out these methods into three categories. First one includes finite state machine methods, framework methods, and instance methods. The second contains full-text indexing methods, ontology methods, vast knowledge base method, and some other methods. The third covers retrieval methods and generative methods. We also discuss some hybrid methods based knowledge and deep learning. We compare their disadvantages and advantages and point out in which ways these studies can be improved further. Our discussion covers some studies published in leading conferences such as IJCAI and AAAI in recent years.

Keywords: Retrieval, generative, deep learning, response generation, knowledge.

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Authors: A. M. Jungudo, M. A. Lasan

Abstract:

Affordable housing has long been one of the basic necessities of life to man. The ever rising prices of building materials are one of the major causes of housing shortage in many developing countries. Breaching the gap of housing needs in developing countries like Nigeria is an awaiting task longing for attention. This is due to lack of research in the development of local materials that will suit the troubled economies of these countries. The use of earth material to meet the housing needs is a sustainable option and its material is freely available universally. However, people are doubtful of using the earth material due to its modest outlook and uncertain durability. This research aims at enhancing the durability of Compressed Earth Bricks (CEBs) using stone dust as a stabilizer. The result indicates that partial replacement of lateritic soil with stone dust at 30% improves its compressive strength along with abrasive resistance.

Keywords: Laterite, stone dust, compressed earth bricks, durability.

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Authors: Mohamed A. Sullabi

Abstract:

The importance of the formal specification in the software life cycle is barely concealing to anyone. Formal specifications use mathematical notation to describe the properties of information system precisely, without unduly constraining the way in how these properties are achieved. Having a correct and quality software specification is not easy task. This study concerns with how a group of rectifiers can communicate with each other and work to prepare and produce a correct formal software specification. WBCS has been implemented based mainly in the proposed supported cooperative work model and a survey conducted on the existing Webbased collaborative writing tools. This paper aims to assess the feasibility of executing the web-based collaboration process using WBCS. The purpose of conducting this test is to test the system as a whole for functionality and fitness for use based on the evaluation test plan.

Keywords: Formal methods, Formal specifications, collaborative writing, Usability testing.

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Authors: P. Georgieva, S. Feyo de Azevedo

Abstract:

This paper is focused on issues of process modeling and two model based control strategies of a fed-batch sugar crystallization process applying the concept of artificial neural networks (ANNs). The control objective is to force the operation into following optimal supersaturation trajectory. It is achieved by manipulating the feed flow rate of sugar liquor/syrup, considered as the control input. The control task is rather challenging due to the strong nonlinearity of the process dynamics and variations in the crystallization kinetics. Two control alternatives are considered – model predictive control (MPC) and feedback linearizing control (FLC). Adequate ANN process models are first built as part of the controller structures. MPC algorithm outperforms the FLC approach with respect to satisfactory reference tracking and smooth control action. However, the MPC is computationally much more involved since it requires an online numerical optimization, while for the FLC an analytical control solution was determined.

Keywords: artificial neural networks, nonlinear model control, process identification, crystallization process

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Authors: Muhammad R. Ahmed, Xu Huang, Dharmendra Sharma

Abstract:

Despite extensive study on wireless sensor network security, defending internal attacks and finding abnormal behaviour of the sensor are still difficult and unsolved task. The conventional cryptographic technique does not give the robust security or detection process to save the network from internal attacker that cause by abnormal behavior. The insider attacker or abnormally behaved sensor identificationand location detection framework using false massage detection and Time difference of Arrival (TDoA) is presented in this paper. It has been shown that the new framework can efficiently identify and detect the insider attacker location so that the attacker can be reprogrammed or subside from the network to save from internal attack.

Keywords: Insider Attaker identification, Abnormal Behaviour, Location detection, Time difference of Arrival (TDoA), Wireless sensor network

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Authors: Hoong C. Chin, Soon H. Chew, Zhaoxia Wang

Abstract:

Work on sustainable developments and the call for action in education for sustainable development have been ongoing for a number of years. Training engineering students with the relevant competencies, particularly in sustainable development literacy, has been identified as an urgent task in universities. This requires not only a holistic, multi-disciplinary approach to education but also a suitable training environment to develop the needed skills and to inculcate the appropriate attitudes in students towards sustainable development. To demonstrate how this can be done, a module involving an overseas field trip was introduced in 2013 at the National University of Singapore. This paper provides details of the module and describes its training philosophy and methods. Measured against the student learning outcomes, stipulated by the Engineering Accreditation Board, the module scored well on all of them, particularly those related to complex problem solving, environmental and sustainability awareness, multi-disciplinary team work and varied-level communications.

Keywords: Civil engineering education, student learning outcomes, sustainable development.

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Authors: Q. Niu, X. H. Zhou, W. Liu

Abstract:

The cooling channels of injection mould play a crucial role in determining the productivity of moulding process and the product quality. It’s not a simple task to design high quality cooling channels. In this paper, an intelligent cooling channels design system including automatic layout of cooling channels, interference checking and assembly of accessories is studied. Automatic layout of cooling channels using genetic algorithm is analyzed. Through integrating experience criteria of designing cooling channels, considering the factors such as the mould temperature and interference checking, the automatic layout of cooling channels is implemented. The method of checking interference based on distance constraint algorithm and the function of automatic and continuous assembly of accessories are developed and integrated into the system. Case studies demonstrate the feasibility and practicality of the intelligent design system.

Keywords: Injection mould, cooling channel, automatic layout, interference checking.

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Authors: Soe Winn, May Thwe Oo

Abstract:

Business process automation is an important task in an enterprise business environment software development. The requirements of processing acceleration and automation level of enterprises are inherently different from one organization to another. We present a methodology and system for automation of business process management system architecture by multi-agent collaboration based on SOA. Design layer processes are modeled in semantic markup language for web services application. At the core of our system is considering certain types of human tasks to their further automation across over multiple platform environments. An improved abnormality processing with model for automation of BPMS architecture by multi-agent collaboration based on SOA is introduced. Validating system for efficiency of process automation, an application for educational knowledge base instance would also be described.

Keywords: Business process management system, businessprocess automation, multi-agent collaboration, Service OrientedArchitecture, extensible service application

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Authors: Nittaya Kerdprasop, Kittisak Kerdprasop

Abstract:

Frequent patterns are patterns such as sets of features or items that appear in data frequently. Finding such frequent patterns has become an important data mining task because it reveals associations, correlations, and many other interesting relationships hidden in a dataset. Most of the proposed frequent pattern mining algorithms have been implemented with imperative programming languages such as C, Cµ, Java. The imperative paradigm is significantly inefficient when itemset is large and the frequent pattern is long. We suggest a high-level declarative style of programming using a functional language. Our supposition is that the problem of frequent pattern discovery can be efficiently and concisely implemented via a functional paradigm since pattern matching is a fundamental feature supported by most functional languages. Our frequent pattern mining implementation using the Haskell language confirms our hypothesis about conciseness of the program. The performance studies on speed and memory usage support our intuition on efficiency of functional language.

Keywords: Association, frequent pattern mining, functionalprogramming, pattern matching.

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Authors: Junaid Rashid, Waqar Mehmood, Muhammad Wasif Nisar

Abstract:

This survey paper shows the recent state of model comparison as it’s applies to Model Driven engineering. In Model Driven Engineering to calculate the difference between the models is a very important and challenging task. There are number of tasks involved in model differencing that firstly starts with identifying and matching the elements of the model. In this paper, we discuss how model matching is accomplished, the strategies, techniques and the types of the model. We also discuss the future direction. We found out that many of the latest model comparison strategies are geared near enabling Meta model and similarity based matching. Therefore model versioning is the most dominant application of the model comparison. Recently to work on comparison for versioning has begun to deteriorate, giving way to different applications. Ultimately there is wide change among the tools in the measure of client exertion needed to perform model comparisons, as some require more push to encourage more sweeping statement and expressive force.

Keywords: Model comparison, model clone detection, model versioning, EMF Model, model diff.

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Authors: Latha Parthiban, R. Subramanian

Abstract:

Heart disease (HD) is a major cause of morbidity and mortality in the modern society. Medical diagnosis is an important but complicated task that should be performed accurately and efficiently and its automation would be very useful. All doctors are unfortunately not equally skilled in every sub specialty and they are in many places a scarce resource. A system for automated medical diagnosis would enhance medical care and reduce costs. In this paper, a new approach based on coactive neuro-fuzzy inference system (CANFIS) was presented for prediction of heart disease. The proposed CANFIS model combined the neural network adaptive capabilities and the fuzzy logic qualitative approach which is then integrated with genetic algorithm to diagnose the presence of the disease. The performances of the CANFIS model were evaluated in terms of training performances and classification accuracies and the results showed that the proposed CANFIS model has great potential in predicting the heart disease.

Keywords: CANFIS, genetic algorithms, heart disease, membership function.

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Authors: Dr.K.Sri Rama Krishna, J.Lakshmi Narayana, Dr.L.Pratap Reddy

Abstract:

Microstrip lines, widely used for good reason, are broadband in frequency and provide circuits that are compact and light in weight. They are generally economical to produce since they are readily adaptable to hybrid and monolithic integrated circuit (IC) fabrication technologies at RF and microwave frequencies. Although, the existing EM simulation models used for the synthesis and analysis of microstrip lines are reasonably accurate, they are computationally intensive and time consuming. Neural networks recently gained attention as fast and flexible vehicles to microwave modeling, simulation and optimization. After learning and abstracting from microwave data, through a process called training, neural network models are used during microwave design to provide instant answers to the task learned.This paper presents simple and accurate ANN models for the synthesis and analysis of Microstrip lines to more accurately compute the characteristic parameters and the physical dimensions respectively for the required design specifications.

Keywords: Neural Models, Algorithms, Microstrip Lines, Analysis, Synthesis

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Authors: Nina Robson, Kenneth John Faller II, Vishalkumar Ahir, Mustafa Mhawesh, Reza Langari

Abstract:

This paper describes the development of a model of an impaired human arm performing a reaching motion, which will be used to predict hand path trajectories for people with reduced arm joint mobility. Assuming that the arm was in contact with a surface during the entire movement, the contact conditions at the initial and final task locations were determined and used to generate the entire trajectory. The model was validated by comparing it to experimental data, which simulated an arm joint impairment by physically constraining the joint motion with a brace. Future research will include using the model in the development of physical training protocols that avoid early recruitment of “healthy” Degrees-Of-Freedom (DOF) for reaching motions, thus facilitating an Active Range-Of-Motion Recovery (AROM) for a particular impaired joint.

Keywords: Higher order kinematic specifications, human motor coordination, impaired movement, kinematic synthesis.

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Authors: Petra Hurbišová, Monika Davidová

Abstract:

The article deals with the readiness of military professionals for challenging situations. It discusses higher requirements on the psychical endurance of military professionals arising from the specific nature of the military occupation, which is typical for being very difficult to maintain regularity, which is in accordance with the hygiene of work alternated by relaxation. The soldier must be able to serve in the long term and constantly intense performance that goes beyond human tolerance to stress situations. A challenging situation is always associated with overcoming difficulties, obstacles and complicated circumstances or using unusual methods, ways and means to achieve the desired (expected) objectives, performing a given task or satisfying an important need. This paper describes the categories of challenging situations, their classification and characteristics. Attention is also paid to the formation of personality in challenging situations, coping with stress in challenging situations, Phases of solutions of stressful situations, resistance to challenging life situations and its factors. Finally, the article is focused on increasing the readiness of military professionals for challenging situations.

Keywords: Coping, challenging situations, stress, stressful situations, military professionals, resilience.

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Authors: Barath Kumar, Oliver Niggemann, Juergen Jasperneite

Abstract:

Model-based approaches have been applied successfully to a wide range of tasks such as specification, simulation, testing, and diagnosis. But one bottleneck often prevents the introduction of these ideas: Manual modeling is a non-trivial, time-consuming task. Automatically deriving models by observing and analyzing running systems is one possible way to amend this bottleneck. To derive a model automatically, some a-priori knowledge about the model structure–i.e. about the system–must exist. Such a model formalism would be used as follows: (i) By observing the network traffic, a model of the long-term system behavior could be generated automatically, (ii) Test vectors can be generated from the model, (iii) While the system is running, the model could be used to diagnose non-normal system behavior. The main contribution of this paper is the introduction of a model formalism called 'probabilistic regression automaton' suitable for the tasks mentioned above.

Keywords: Model-based approach, Probabilistic regression automata, Statistical models and Timed automata.

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Authors: Prashanth C.M., K. Chandrashekar Shet

Abstract:

In recent past, the Unified Modeling Language (UML) has become the de facto industry standard for object-oriented modeling of the software systems. The syntax and semantics rich UML has encouraged industry to develop several supporting tools including those capable of generating deployable product (code) from the UML models. As a consequence, ensuring the correctness of the model/design has become challenging and extremely important task. In this paper, we present an approach for automatic verification of protocol model/design. As a case study, Session Initiation Protocol (SIP) design is verified for the property, “the CALLER will not converse with the CALLEE before the connection is established between them ". The SIP is modeled using UML statechart diagrams and the desired properties are expressed in temporal logic. Our prototype verifier “UML-SMV" is used to carry out the verification. We subjected an erroneous SIP model to the UML-SMV, the verifier could successfully detect the error (in 76.26ms) and generate the error trace.

Keywords: Unified Modeling Language, Statechart, Verification, Protocol Design, Model Checking.

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Authors: G.A.C.P. Ganegoda, D.M.A. Samaranayake, L.S. Bandara, K.A.D.N.K. Wimalawarne

Abstract:

With the popularity of the multi-core and many-core architectures there is a great requirement for software frameworks which can support parallel programming methodologies. In this paper we introduce an Eclipse toolkit, JConqurr which is easy to use and provides robust support for flexible parallel progrmaming. JConqurr is a multi-core and many-core programming toolkit for Java which is capable of providing support for common parallel programming patterns which include task, data, divide and conquer and pipeline parallelism. The toolkit uses an annotation and a directive mechanism to convert the sequential code into parallel code. In addition to that we have proposed a novel mechanism to achieve the parallelism using graphical processing units (GPU). Experiments with common parallelizable algorithms have shown that our toolkit can be easily and efficiently used to convert sequential code to parallel code and significant performance gains can be achieved.

Keywords: Multi-core, parallel programming patterns, GPU, Java, Eclipse plugin, toolkit,

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Authors: Viet-Hoang Vu, Nhan Le-Thanh

Abstract:

Recently the usefulness of Concept Abduction, a novel non-monotonic inference service for Description Logics (DLs), has been argued in the context of ontology-based applications such as semantic matchmaking and resource retrieval. Based on tableau calculus, a method has been proposed to realize this reasoning task in ALN, a description logic that supports simple cardinality restrictions as well as other basic constructors. However, in many ontology-based systems, the representation of ontology would require expressive formalisms for capturing domain-specific constraints, this language is not sufficient. In order to increase the applicability of the abductive reasoning method in such contexts, we would like to present in the scope of this paper an extension of the tableaux-based algorithm for dealing with concepts represented inALCQ, the description logic that extends ALN with full concept negation and quantified number restrictions.

Keywords: Abductive reasoning, description logics, semantic matchmaking, non-monotonic inference, tableaux-based method.

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Authors: Darren Zou

Abstract:

Forecasting the stock market is a very challenging task. Various economic indicators such as GDP, exchange rates, interest rates, and unemployment have a substantial impact on the stock market. Time series models are the traditional methods used to predict stock market changes. In this paper, a machine learning method, Bayesian Additive Regression Tree (BART) is used in predicting stock market indexes based on multiple economic indicators. BART can be used to model heterogeneous treatment effects, and thereby works well when models are misspecified. It also has the capability to handle non-linear main effects and multi-way interactions without much input from financial analysts. In this research, BART is proposed to provide a reliable prediction on day-to-day stock market activities. By comparing the analysis results from BART and with time series method, BART can perform well and has better prediction capability than the traditional methods.

Keywords: Bayesian, Forecast, Stock, BART.

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Authors: Razib M. Othman, Safaai Deris, Rosli M. Illias

Abstract:

Gene Ontology terms have been actively used to annotate various protein sets. SWISS-PROT, TrEMBL, and InterPro are protein databases that are annotated according to the Gene Ontology terms. However, direct implementation of the Gene Ontology terms for annotation of anonymous protein sequences is not easy, especially for species not commonly represented in biological databases. UTMGO is developed as a tool that allows the user to quickly and easily search for a group of semantically related Gene Ontology terms. The applicability of the UTMGO is demonstrated by applying it to annotation of anonymous protein sequence. The extended UTMGO uses the Gene Ontology terms together with protein sequences associated with the terms to perform the annotation task. GOPET, GOtcha, GoFigure, and JAFA are used to compare the performance of the extended UTMGO.

Keywords: Anonymous protein sequence, Gene Ontology, Protein sequence annotation, Protein sequence alignment

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Authors: L. H. Chong, Y. Y. Chen

Abstract:

Information is increasing in volumes; companies are overloaded with information that they may lose track in getting the intended information. It is a time consuming task to scan through each of the lengthy document. A shorter version of the document which contains only the gist information is more favourable for most information seekers. Therefore, in this paper, we implement a text summarization system to produce a summary that contains gist information of oil and gas news articles. The summarization is intended to provide important information for oil and gas companies to monitor their competitor-s behaviour in enhancing them in formulating business strategies. The system integrated statistical approach with three underlying concepts: keyword occurrences, title of the news article and location of the sentence. The generated summaries were compared with human generated summaries from an oil and gas company. Precision and recall ratio are used to evaluate the accuracy of the generated summary. Based on the experimental results, the system is able to produce an effective summary with the average recall value of 83% at the compression rate of 25%.

Keywords: Information retrieval, text summarization, statistical approach.

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Authors: P. Ahern, D. Collery

Abstract:

The implementation of lean thinking in the manufacturing industry revolutionized the traditional approach to large-scale production through the process of identifying the waste in each task and putting in place mitigation measures to eliminate the waste in all its forms. The Irish construction industry, however, has been much slower to adopt the principles of lean, opting instead to stick with the traditional approach to construction project delivery which is inherently wasteful. Lean thinking holds the potential to revolutionize the construction industry in a similar manner to the adoption of lean manufacturing. Lean principles present opportunities for reduced project duration, reduced project cost, improved quality, and elimination of re-works and non-value-added activities. This research has been designed to accumulate research data through available literature, electronic surveys, and interviews. The results show an industry reluctant to accept change and an undefined path to successful lean construction implementation.

Keywords: Barriers, lean construction, lean implementation, lean manufacturing, lean philosophy.

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Authors: Sylvain Devie, Pierre-Philippe Robet, Yannick Aoustin, Maxime Gautier

Abstract:

The aim of this paper is to show that the observation of the external effort and the sensor-less control of a system is limited by the mechanical system. First, the model of a one-joint robot with a prismatic joint is presented. Based on this model, two different procedures were performed in order to identify the mechanical parameters of the system and observe the external effort applied on it. Experiments have proven that the accuracy of the force observer, based on the DC motor current, is limited by the mechanics of the robot. The sensor-less control will be limited by the accuracy in estimation of the mechanical parameters and by the maximum static friction force, that is the minimum force which can be observed in this case. The consequence of this limitation is that industrial robots without specific design are not well adapted to perform sensor-less precision tasks. Finally, an efficient control law is presented for high effort applications.

Keywords: Control, Identification, Robot, Co-manipulation, Sensor-less.

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Authors: T. Chandrasekhar, K. Thangavel, E. N. Sathishkumar

Abstract:

Microarrays are made it possible to simultaneously monitor the expression profiles of thousands of genes under various experimental conditions. It is used to identify the co-expressed genes in specific cells or tissues that are actively used to make proteins. This method is used to analysis the gene expression, an important task in bioinformatics research. Cluster analysis of gene expression data has proved to be a useful tool for identifying co-expressed genes, biologically relevant groupings of genes and samples. In this work K-Means algorithms has been applied for clustering of Gene Expression Data. Further, rough set based Quick reduct algorithm has been applied for each cluster in order to select the most similar genes having high correlation. Then the ACV measure is used to evaluate the refined clusters and classification is used to evaluate the proposed method. They could identify compact clusters with feature selection method used to genes are selected.

Keywords: Clustering, Feature selection, Gene expression data, Quick reduct.

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Authors: K. S. Jasmine, R. Vasantha

Abstract:

The overriding goal of software engineering is to provide a high quality system, application or a product. To achieve this goal, software engineers must apply effective methods coupled with modern tools within the context of a mature software process [2]. In addition, it is also must to assure that high quality is realized. Although many quality measures can be collected at the project levels, the important measures are errors and defects. Deriving a quality measure for reusable components has proven to be challenging task now a days. The results obtained from the study are based on the empirical evidence of reuse practices, as emerged from the analysis of industrial projects. Both large and small companies, working in a variety of business domains, and using object-oriented and procedural development approaches contributed towards this study. This paper proposes a quality metric that provides benefit at both project and process level, namely defect removal efficiency (DRE).

Keywords: Software Reuse, Defect density, Reuse metrics, Defect Removal efficiency.

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Authors: Andrey V. Timofeev, Dmitry Egorov

Abstract:

This paper describes an effective solution to the task of a remote monitoring of super-extended objects (oil and gas pipeline, railways, national frontier). The suggested solution is based on the principle of simultaneously monitoring of seismoacoustic and optical/infrared physical fields. The principle of simultaneous monitoring of those fields is not new but in contrast to the known solutions the suggested approach allows to control super-extended objects with very limited operational costs. So-called C-OTDR (Coherent Optical Time Domain Reflectometer) systems are used to monitor the seismoacoustic field. Far-CCTV systems are used to monitor the optical/infrared field. A simultaneous data processing provided by both systems allows effectively detecting and classifying target activities, which appear in the monitored objects vicinity. The results of practical usage had shown high effectiveness of the suggested approach.

Keywords: Bimodal processing, C-OTDR monitoring system, LPboost, SVM.

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Authors: Qian Wang, Sylvain Lassalle, Antony R. Mileham, Geraint W. Owen

Abstract:

This paper mathematically analyses the varying magnitude of production loss, which may occur due to idle time (inprocess waiting time and traveling time) on a linear walking worker assembly line. Within this flexible and reconfigurable assembly system, each worker travels down the line carrying out each assembly task at each station; and each worker accomplishes the assembly of a unit from start to finish and then travels back to the first station to start the assembly of a new product. This strategy of system design attempts to combine the flexibility of the U-shaped moving worker assembly cell with the efficiency of the conventional fixed worker assembly line. The paper aims to evaluate the effect of idle time that may offset the labor efficiency of each walking worker providing an insight into the mechanism of such a flexible and reconfigurable assembly system.

Keywords: Production lines, manufacturing systems, assemblysystems, walking workers.

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Authors: Chih Chin Yang, Chung Shan Sun

Abstract:

In this paper the relationships between professional competences and school curriculain IC design industry are explored. The semi-structured questionnaire survey and focus group interview is the research method. Study participants are graduates of microelectronics engineering professional departments who are currently employed in the IC industry. The IC industries are defined as the electronic component manufacturing industry and optical-electronic component manufacturing industry in the semiconductor industry and optical-electronic material devices, respectively. Study participants selected from IC design industry include IC engineering and electronic & semiconductor engineering. The human training with IC design professional competence in microelectronics engineering professional departments is explored in this research. IC professional competences of human resources in the IC design industry include general intelligence and professional intelligence.

Keywords: IC design, curricula, competence, task, duty.

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Authors: Chetneti Srisa-an

Abstract:

In Knowledge and Data Engineering field, relational database is the best repository to store data in a real world. It has been using around the world more than eight decades. Normalization is the most important process for the analysis and design of relational databases. It aims at creating a set of relational tables with minimum data redundancy that preserve consistency and facilitate correct insertion, deletion, and modification. Normalization is a major task in the design of relational databases. Despite its importance, very few algorithms have been developed to be used in the design of commercial automatic normalization tools. It is also rare technique to do it automatically rather manually. Moreover, for a large and complex database as of now, it make even harder to do it manually. This paper presents a new complete automated relational database normalization method. It produces the directed graph and spanning tree, first. It then proceeds with generating the 2NF, 3NF and also BCNF normal forms. The benefit of this new algorithm is that it can cope with a large set of complex function dependencies.

Keywords: Relational Database, Functional Dependency, Automatic Normalization, Primary Key, Spanning tree.

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Authors: A. Faro, D. Giordano, F. Maiorana

Abstract:

Data mining uses a variety of techniques each of which is useful for some particular task. It is important to have a deep understanding of each technique and be able to perform sophisticated analysis. In this article we describe a tool built to simulate a variation of the Kohonen network to perform unsupervised clustering and support the entire data mining process up to results visualization. A graphical representation helps the user to find out a strategy to optmize classification by adding, moving or delete a neuron in order to change the number of classes. The tool is also able to automatically suggest a strategy for number of classes optimization.The tool is used to classify macroeconomic data that report the most developed countries? import and export. It is possible to classify the countries based on their economic behaviour and use an ad hoc tool to characterize the commercial behaviour of a country in a selected class from the analysis of positive and negative features that contribute to classes formation.

Keywords: Unsupervised classification, Kohonen networks, macroeconomics, Visual data mining, cluster interpretation.

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