Search results for: automated manufacturing system

Authors: Youngji Yoo, Cheong-Sool Park, Jun Seok Kim, Young-Hak Lee, Sung-Shick Kim, Jun-Geol Baek

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In the semiconductor manufacturing process, large amounts of data are collected from various sensors of multiple facilities. The collected data from sensors have several different characteristics due to variables such as types of products, former processes and recipes. In general, Statistical Quality Control (SQC) methods assume the normality of the data to detect out-of-control states of processes. Although the collected data have different characteristics, using the data as inputs of SQC will increase variations of data, require wide control limits, and decrease performance to detect outof- control. Therefore, it is necessary to separate similar data groups from mixed data for more accurate process control. In the paper, we propose a regression tree using split algorithm based on Pearson distribution to handle non-normal distribution in parametric method. The regression tree finds similar properties of data from different variables. The experiments using real semiconductor manufacturing process data show improved performance in fault detecting ability.

Keywords: Semiconductor, non-normal mixed process data, clustering, Statistical Quality Control (SQC), regression tree, Pearson distribution system.

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Authors: Ehsan Amid, Sina Rezaei Aghdam, Hamidreza Amindavar

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Steel surface defect detection is essentially one of pattern recognition problems. Support Vector Machines (SVMs) are known as one of the most proper classifiers in this application. In this paper, we introduce a more accurate classification method by using SVMs as our final classifier of the inspection system. In this scheme, multiclass classification task is performed based on the "one-againstone" method and different kernels are utilized for each pair of the classes in multiclass classification of the different defects. In the proposed system, a decision tree is employed in the first stage for two-class classification of the steel surfaces to "defect" and "non-defect", in order to decrease the time complexity. Based on the experimental results, generated from over one thousand images, the proposed multiclass classification scheme is more accurate than the conventional methods and the overall system yields a sufficient performance which can meet the requirements in steel manufacturing.

Keywords: Steel Surface Defect Detection, Support Vector Machines, Kernel Methods.

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Authors: Ashwag O. Maghraby, Nida N. Khan, Hosnia A. Ahmed, Ghufran N. Brohi, Hind F. Assouli, Jawaher S. Melibari

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The Arabic language is one of the most important languages. Learning it is so important for many people around the world because of its religious and economic importance and the real challenge lies in practicing it without grammatical or syntactical mistakes. This research focused on detecting and correcting the syntactic mistakes of Arabic syntax according to their position in the sentence and focused on two of the main syntactical rules in Arabic: Dual and Plural. It analyzes each sentence in the text, using Stanford CoreNLP morphological analyzer and machine-learning approach in order to detect the syntactical mistakes and then correct it. A prototype of the proposed system was implemented and evaluated. It uses support vector machine (SVM) algorithm to detect Arabic grammatical errors and correct them using the rule-based approach. The prototype system has a far accuracy 81%. In general, it shows a set of useful grammatical suggestions that the user may forget about while writing due to lack of familiarity with grammar or as a result of the speed of writing such as alerting the user when using a plural term to indicate one person.

Keywords: Arabic Language acquisition and learning, natural language processing, morphological analyzer, part-of-speech.

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Authors: Nermin Ozgulbas, Ali Serhan Koyuncugil

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One of the biggest problems of SMEs is their tendencies to financial distress because of insufficient finance background. In this study, an Early Warning System (EWS) model based on data mining for financial risk detection is presented. CHAID algorithm has been used for development of the EWS. Developed EWS can be served like a tailor made financial advisor in decision making process of the firms with its automated nature to the ones who have inadequate financial background. Besides, an application of the model implemented which covered 7,853 SMEs based on Turkish Central Bank (TCB) 2007 data. By using EWS model, 31 risk profiles, 15 risk indicators, 2 early warning signals, and 4 financial road maps has been determined for financial risk mitigation.

Keywords: Early Warning Systems, Data Mining, Financial Risk, SMEs.

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Authors: Bo Wun Huang, Pu Ping Yu, Jao-Hwa Kuang

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For smaller mechatronic device, especially for micro Electronic system, a micro machining is a must. However, most investigations on vibration of a mill have been limited to the traditional type mill. In this article, vibration and dynamic characteristics of a micro mill were investigated in this study. The trend towards higher precision manufacturing technology requires producing miniaturized components. To improve micro-milled product quality, obtain a higher production rate and avoid milling breakage, the dynamic characteristics of micro milling must be studied. A stepped pre-twisted mill is used to simulate the micro mill. The finite element analysis is employed in this work. The flute length and diameter effects of the micro mill are considered. It is clear that the effects of micro mill shape parameters on vibration in a micro mill are significant.

Keywords: micro system, micro mill, vibration.

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Authors: Liubov Magerramova, Eugene Kratt, Pavel Presniakov

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A detailed analysis has been performed for several schemes of Gas Turbine Wheels production based on additive and powder technologies including metal, ceramic, and stereolithography 3-D printing. During the process of development and debugging of gas turbine engine components, different versions of these components must be manufactured and tested. Cooled blades of the turbine are among of these components. They are usually produced by traditional casting methods. This method requires long and costly design and manufacture of casting molds. Moreover, traditional manufacturing methods limit the design possibilities of complex critical parts of engine, so capabilities of Powder Metallurgy Techniques (PMT) were analyzed to manufacture the turbine wheel with air-cooled blades. PMT dramatically reduce time needed for such production and allow creating new complex design solutions aimed at improving the technical characteristics of the engine: improving fuel efficiency and environmental performance, increasing reliability, and reducing weight. To accelerate and simplify the blades manufacturing process, several options based on additive technologies were used. The options were implemented in the form of various casting equipment for the manufacturing of blades. Methods of powder metallurgy were applied for connecting the blades with the disc. The optimal production scheme and a set of technologies for the manufacturing of blades and turbine wheel and other parts of the engine can be selected on the basis of the options considered.

Keywords: Additive technologies, gas turbine engine, powder technology, turbine wheel.

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Authors: Rahil Garnavi, Mohammad Aldeen, M. Emre Celebi, Alauddin Bhuiyan, Constantinos Dolianitis, George Varigos

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Automatic segmentation of skin lesions is the first step towards the automated analysis of malignant melanoma. Although numerous segmentation methods have been developed, few studies have focused on determining the most effective color space for melanoma application. This paper proposes an automatic segmentation algorithm based on color space analysis and clustering-based histogram thresholding, a process which is able to determine the optimal color channel for detecting the borders in dermoscopy images. The algorithm is tested on a set of 30 high resolution dermoscopy images. A comprehensive evaluation of the results is provided, where borders manually drawn by four dermatologists, are compared to automated borders detected by the proposed algorithm, applying three previously used metrics of accuracy, sensitivity, and specificity and a new metric of similarity. By performing ROC analysis and ranking the metrics, it is demonstrated that the best results are obtained with the X and XoYoR color channels, resulting in an accuracy of approximately 97%. The proposed method is also compared with two state-of-theart skin lesion segmentation methods.

Keywords: Border detection, Color space analysis, Dermoscopy, Histogram thresholding, Melanoma, Segmentation.

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Authors: A. Lauvray, F. Poulhaon, P. Michaud, P. Joyot, E. Duc

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Additive Friction Stir Manufacturing, or AFSM, is a new industrial process that follows the emergence of friction-based processes. The AFSM process is a solid-state additive process using the energy produced by the friction at the interface between a rotating non-consumable tool and a substrate. Friction depends on various parameters like axial force, rotation speed or friction coefficient. The feeder material is a metallic rod that flows through a hole in the tool. There is still a lack in understanding of the physical phenomena taking place during the process. This research aims at a better AFSM process understanding and implementation, thanks to numerical simulation and experimental validation performed on a prototype effector. Such an approach is considered a promising way for studying the influence of the process parameters and to finally identify a process window that seems relevant. The deposition of material through the AFSM process takes place in several phases. In chronological order these phases are the docking phase, the dwell time phase, the deposition phase, and the removal phase. The present work focuses on the dwell time phase that enables the temperature rise of the system due to pure friction. An analytic modeling of heat generation based on friction considers as main parameters the rotational speed and the contact pressure. Another parameter considered influential is the friction coefficient assumed to be variable, due to the self-lubrication of the system with the rise in temperature or the materials in contact roughness smoothing over time. This study proposes through a numerical modeling followed by an experimental validation to question the influence of the various input parameters on the dwell time phase. Rotation speed, temperature, spindle torque and axial force are the main monitored parameters during experimentations and serve as reference data for the calibration of the numerical model. This research shows that the geometry of the tool as well as fluctuations of the input parameters like axial force and rotational speed are very influential on the temperature reached and/or the time required to reach the targeted temperature. The main outcome is the prediction of a process window which is a key result for a more efficient process implementation.

Keywords: numerical model, additive manufacturing, frictional heat generation, process

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Authors: Qiong Huang, Satish Chand

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This paper uses a primary data from 670 Chinese manufacturing firms, together with the newly introduced regressionbased inequality decomposition method, to study the effect of openness on wage inequality. We find that openness leads to a positive industry wage premium, but its contribution to firm-level wage inequality is relatively small, only 4.69%. The major contributor to wage inequality is human capital, which could explain 14.3% of wage inequality across sample firms.  

Keywords: Openness, human capital, wage inequality, decomposition; China.

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Authors: İlke Bereketli, Müjde Erol Genevois, H. Ziya Ulukan

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Nowadays, manufacturers are facing great challenges with regard to the production of green products due to the emerging issue of hazardous substance management (HSM). In particular, environmental legislation pressures have yielded to increased risk, manufacturing complexity and green components demands. The green principles were expanded to many departments within organization, including supply chain. Green supply chain management (GSCM) was emerging in the last few years. This idea covers every stage in manufacturing from the first to the last stage of life cycle. From product lifecycle concept, the cycle starts at the design of a product. QFD is a customer-driven product development tool, considered as a structured management approach for efficiently translating customer needs into design requirements and parts deployment, as well as manufacturing plans and controls in order to achieve higher customer satisfaction. This paper develops an Eco- QFD to provide a framework for designing Eco-mobile phone by integrating the life cycle analysis LCA into QFD throughout the entire product development process.

Keywords: Eco-design, Eco-QFD, EEE, Environmental New Product Development, Mobile Phone.

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Authors: Mazila Md-Yusuf, Fauziah Mohamad Yunus, Nur Zahraatul Lail Md Supaat

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Capital structure is one of the most important financial decisions in corporate financing strategy. It involves the choice of debt and equity level in financing a company-s operations. This study aims to investigate whether the capital structure choice of Malaysian electrical and electronic manufacturing companies that are listed in the Bursa Malaysia can be explained by factors that have been found by most studies as dominant determinants of capital structure (company size, profitability, asset tangibility, liquidity and growth). Using debt ratio as the proxy for capital structure and applying pooled ordinary least square multiple regression estimation, the results showed that on average, Malaysian electrical and electronic manufacturing companies used less debt in funding their business operations. The findings also showed that size and asset tangibility has a significant positive relationship with debt level, while liquidity has a negative significant relationship with leverage.

Keywords: Capital structure, capital structure theories, leverage, manufacturing companies.

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Authors: Peng Hao Wang, Garam Kim, Ronald Sterkenburg

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The applications of composite materials within the aviation industry has been increasing at a rapid pace.  However, the growing applications of composite materials have also led to growing demand for more tooling to support its manufacturing processes. Tooling and tooling maintenance represents a large portion of the composite manufacturing process and cost. Therefore, the industry’s adaptability to new techniques for fabricating high quality tools quickly and inexpensively will play a crucial role in composite material’s growing popularity in the aviation industry. One popular tool fabrication technique currently being developed involves additive manufacturing such as 3D printing. Although additive manufacturing and 3D printing are not entirely new concepts, the technique has been gaining popularity due to its ability to quickly fabricate components, maintain low material waste, and low cost. In this study, a team of Purdue University School of Aviation and Transportation Technology (SATT) faculty and students investigated the effectiveness of a 3D printed composite compression mold. A 3D printed composite compression mold was fabricated by 3D scanning a steel valve cover of an aircraft reciprocating engine. The 3D printed composite compression mold was used to fabricate carbon fiber versions of the aircraft reciprocating engine valve cover. The 3D printed composite compression mold was evaluated for its performance, durability, and dimensional stability while the fabricated carbon fiber valve covers were evaluated for its accuracy and quality. The results and data gathered from this study will determine the effectiveness of the 3D printed composite compression mold in a mass production environment and provide valuable information for future understanding, improvements, and design considerations of 3D printed composite molds.

Keywords: Additive manufacturing, carbon fiber, composite tooling, molds.

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Authors: Bhim Singh

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Due to increased pressure from global competitors, manufacturing organizations are switching over to lean philosophies from traditional mass production. Lean manufacturing is a manufacturing philosophy which focuses on elimination of various types of wastes and creates maximum value for the end customers. Lean thinking aims to produce high quality products and services at the lowest possible cost with maximum customer responsiveness. Indian Industry is facing lot of problems in this transformation from traditional mass production to lean production. Through this paper an attempt has been made to identify various lean implementation hurdles in Indian industries with the help of a structured survey. Identified hurdles are grouped with the help of factor analysis and rated by calculating descriptive statistics. To show the effect of lean implementation hurdles a hypothesis “Organizations having higher level of lean implementation hurdles will have poor (negative) performance” has been postulated and tested using correlation matrix between performance parameters of the organizations and identified hurdles. The findings of the paper will be helpful to prepare road map to identify and eradicate the lean implementation hurdles.

Keywords: Factor analysis, global competition, lean implementation and lean hurdles.

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Authors: Syahril Ridzuan Ab Rahim, Ibrahim Ahmad, Mohd Azizi Chik, Ahmad Zafir Md. Rejab, and U. Hashim

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This research presents the development of simulation modeling for WIP management in semiconductor fabrication. Manufacturing simulation modeling is needed for productivity optimization analysis due to the complex process flows involved more than 35 percent re-entrance processing steps more than 15 times at same equipment. Furthermore, semiconductor fabrication required to produce high product mixed with total processing steps varies from 300 to 800 steps and cycle time between 30 to 70 days. Besides the complexity, expansive wafer cost that potentially impact the company profits margin once miss due date is another motivation to explore options to experiment any analysis using simulation modeling. In this paper, the simulation model is developed using existing commercial software platform AutoSched AP, with customized integration with Manufacturing Execution Systems (MES) and Advanced Productivity Family (APF) for data collections used to configure the model parameters and data source. Model parameters such as processing steps cycle time, equipment performance, handling time, efficiency of operator are collected through this customization. Once the parameters are validated, few customizations are made to ensure the prior model is executed. The accuracy for the simulation model is validated with the actual output per day for all equipments. The comparison analysis from result of the simulation model compared to actual for achieved 95 percent accuracy for 30 days. This model later was used to perform various what if analysis to understand impacts on cycle time and overall output. By using this simulation model, complex manufacturing environment like semiconductor fabrication (fab) now have alternative source of validation for any new requirements impact analysis.

Keywords: Advanced Productivity Family (APF), Complementary Metal Oxide Semiconductor (CMOS), Manufacturing Execution Systems (MES), Work In Progress (WIP).

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Authors: Zuzana Crhova, Karel Kolman, Drahomíra Pavelkova

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Knowledge is considered as an important asset which can help organizations to create competitive advantage. The necessity of taking care of these assets is more important in these days – in days of turbulent changes in business environment. Knowledge could facilitate adaption to constant changes. The aim of this paper is to describe how the knowledge sharing can be supported in the manufacturing companies. The methods of case studies and grounded theory were used to present information gained by carrying out semistructured interviews. Results show that knowledge sharing is supported in very similar ways in respondent companies.

Keywords: Case Study, Human Resource Management, Knowledge, Knowledge Sharing.

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Authors: N. Ahmed, A.J. Day, J.L. Victory L. Zeall, B. Young

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The manufacture of large-scale precision aerospace components using CNC requires a highly effective maintenance strategy to ensure that the required accuracy can be achieved over many hours of production. This paper reviews a strategy for a maintenance management system based on Failure Mode Avoidance, which uses advanced techniques and technologies to underpin a predictive maintenance strategy. It is shown how condition monitoring (CM) is important to predict potential failures in high precision machining facilities and achieve intelligent and integrated maintenance management. There are two distinct ways in which CM can be applied. One is to monitor key process parameters and observe trends which may indicate a gradual deterioration of accuracy in the product. The other is the use of CM techniques to monitor high status machine parameters enables trends to be observed which can be corrected before machine failure and downtime occurs. It is concluded that the key to developing a flexible and intelligent maintenance framework in any precision manufacturing operation is the ability to evaluate reliably and routinely machine tool condition using condition monitoring techniques within a framework of Failure Mode Avoidance.

Keywords: Maintenance, Condition Monitoring, CNC, Machining, Accuracy, Capability, Key Process Parameters, Critical Parameters

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Authors: V. Geetha, K. S. Aprameya

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Early diagnosis of dental caries is essential for maintaining dental health. In this paper, method for diagnosis of dental caries is proposed using Laplacian filter, adaptive thresholding, texture analysis and Support Vector Machine (SVM) classifier. Analysis of the proposed method is compared with Otsu thresholding, watershed segmentation and active contouring method. Adaptive thresholding has comparatively better performance with 96.9% accuracy and 96.1% precision. The results are validated using statistical method, two-way ANOVA, at significant level of 5%, that shows the interaction of proposed method on performance parameter measures are significant. Hence the proposed technique could be used for detection of dental caries in automated computer assisted diagnosis system.

Keywords: Computer assisted diagnosis, dental caries, dental radiography, image segmentation.

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Authors: A. Suleng, T. Jelstad Olsen, J. Šindler, P. Bárta

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A dead leg is a typical subsea production system component. CFD is required to model heat transfer within the dead leg. Unfortunately its solution is time demanding and thus not suitable for fast prediction or repeated simulations. Therefore there is a need to create a thermal FEA model, mimicking the heat flows and temperatures seen in CFD cool down simulations. This paper describes the conventional way of tuning and a new automated way using parametric model order reduction (PMOR) together with an optimization algorithm. The tuned FE analyses replicate the steady state CFD parameters within a maximum error in heat flow of 6 % and 3 % using manual and PMOR method respectively. During cool down, the relative error of the tuned FEA models with respect to temperature is below 5% comparing to the CFD. In addition, the PMOR method obtained the correct FEA setup five times faster than the manually tuned FEA.

Keywords: CFD, convective heat, FEA, model tuning, subseaproduction

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Authors: Abhimanyu Pati, Prabir K. Bandyopadhyay

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The paper intends to highlight the significance of Digital Manufacturing (DM) strategy in support and achievement of business strategy and goals of any manufacturing organization. Towards this end, DM initiatives have been given a process perspective, while not undermining its technological significance, with a view to link its benefits directly with fulfilment of customer needs and expectations in a responsive and cost-effective manner. A digital process model has been proposed to categorize digitally enabled organizational processes with a view to create synergistic groups, which adopt and use digital tools having similar characteristics and functionalities. This will throw future opportunities for researchers and developers to create a unified technology environment for integration and orchestration of processes. Secondly, an effort has been made to apply “what” and “how” features of Quality Function Deployment (QFD) framework to establish the relationship between customers’ needs – both for external and internal customers, and the features of various digital processes, which support for the achievement of these customer expectations. The paper finally concludes that in the present highly competitive environment, business organizations cannot thrive to sustain unless they understand the significance of digital strategy and integrate it with their business strategy with a clearly defined implementation roadmap. A process-oriented approach to DM strategy will help business executives and leaders to appreciate its value propositions and its direct link to organization’s competitiveness.

Keywords: Digital manufacturing, digital process model, quality function deployment, business strategy.

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Authors: Siobhan O’Shea, Sangeetha Vijaysri Nair, Hee Cheol Kim, Charles Thomas Nugent, Cheuk Yan William Tong, Sam Douthwaite, Andrew Worlock

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The Aptima® HIV-1 Quant Dx Assay is a fully automated assay on the Panther system. It is based on Transcription- Mediated Amplification and real time detection technologies. This assay is intended for monitoring HIV-1 viral load in plasma specimens and for the detection of HIV-1 in plasma and serum specimens. Nine-hundred and seventy nine specimens selected at random from routine testing at St Thomas’ Hospital, London were anonymised and used to compare the performance of the Aptima HIV-1 Quant Dx assay and Roche COBAS® AmpliPrep/COBAS® TaqMan® HIV-1 Test, v2.0. Two-hundred and thirty four specimens gave quantitative HIV-1 viral load results in both assays. The quantitative results reported by the Aptima Assay were comparable to those reported by the Roche COBAS AmpliPrep/COBAS TaqMan HIV-1 Test, v2.0 with a linear regression slope of 1.04 and an intercept on -0.097. The Aptima assay detected HIV-1 in more samples than the COBAS assay. This was not due to lack of specificity of the Aptima assay because this assay gave 99.83% specificity on testing plasma specimens from 600 HIV-1 negative individuals. To understand the reason for this higher detection rate a side-by-side comparison of low level panels made from the HIV-1 3rd international standard (NIBSC10/152) and clinical samples of various subtypes were tested in both assays. The Aptima assay was more sensitive than the COBAS assay. The good sensitivity, specificity and agreement with other commercial assays make the HIV-1 Quant Dx Assay appropriate for both viral load monitoring and detection of HIV-1 infections.

Keywords: HIV viral load, Aptima, Roche, Panther system.

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Authors: Jehad Al Dallal

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An application framework provides a reusable design and implementation for a family of software systems. Frameworks are introduced to reduce the cost of a product line (i.e., a family of products that shares the common features). Software testing is a timeconsuming and costly ongoing activity during the application software development process. Generating reusable test cases for the framework applications during the framework development stage, and providing and using the test cases to test part of the framework application whenever the framework is used reduces the application development time and cost considerably. This paper introduces the Framework Interface State Transition Tester (FIST2), a tool for automated unit testing of Java framework applications. During the framework development stage, given the formal descriptions of the framework hooks, the specifications of the methods of the framework-s extensible classes, and the illegal behavior description of the Framework Interface Classes (FICs), FIST2 generates unitlevel test cases for the classes. At the framework application development stage, given the customized method specifications of the implemented FICs, FIST2 automates the use, execution, and evaluation of the already generated test cases to test the implemented FICs. The paper illustrates the use of the FIST2 tool for testing several applications that use the SalesPoint framework.

Keywords: Automated testing, class testing, FICs, FIST2, object-oriented framework, object-oriented testing.

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Authors: S. Madhavi, S. Abirami, C. Bharathi, B. Ekambaram, T. Krishna Sankar, A. Nattudurai, N. Vijayarangan

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The high utilization rate of Automated Teller Machine (ATM) has inevitably caused the phenomena of waiting for a long time in the queue. This in turn has increased the out of stock situations. The ATM utilization helps to determine the usage level and states the necessity of the ATM based on the utilization of the ATM system. The time in which the ATM used more frequently (peak time) and based on the predicted solution the necessary actions are taken by the bank management. The analysis can be done by using the concept of Data Mining and the major part are analyzed based on the predictive data mining. The results are predicted from the historical data (past data) and track the relevant solution which is required. Weka tool is used for the analysis of data based on predictive data mining.

Keywords: ATM, Bank Management, Data Mining, Historical data, Predictive Data Mining, Weka tool.

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Authors: Djalal Eddine Khodja, Aissa Kheldoun

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In this work we present the modelling of the induction machine, taking into consideration the stator defects of the induction machine. It is based on the theory of electromagnetic coupling of electrical circuits. In fact, for the modelling of stationary defects such as short circuit between turns in the same phase, we introduce only in the matrix the coefficients of resistance and inductance of stator and in the mutual inductance stator-rotor. These coefficients take account the number of turns in short-circuit deducted from the total number of turns in the same phase; in this way we obtain the number of useful turns. In addition, all these faults involved, will be used for the creation of the database that will be used to develop an automated system failures of the induction machine.

Keywords: Asynchronous machine, Indicatory Values Statorfaults, Multi-turns Model, Three-phases Model.

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Authors: Kazeem A. Adebiyi

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Despite many success stories of manufacturing safety, many organizations are still reluctant, perceiving it as cost increasing and time consuming. The clear contributor may be due to the use of lagging indicators rather than leading indicator measures. The study therefore proposes a combinatorial model for determining the best safety strategy. A combination theory and cost benefit analysis was employed to develop a monetary saving / loss function in terms value of preventions and cost of prevention strategy. Documentations, interviews and structured questionnaire were employed to collect information on Before-And-After safety programme records from a Tobacco company between periods of 1993-2001(for pre-safety) and 2002-2008 (safety period) for the model application. Three combinatorial alternatives A, B, C were obtained resulting into 4, 6 and 4 strategies respectively with PPE and Training being predominant. A total of 728 accidents were recorded for a 9 year period of pre-safety programme and 163 accidents were recorded for 7 years period of safety programme. Six preventions activities (alternative B) yielded the best results. However, all the years of operation experienced except year 2004. The study provides a leading resources for planning successful safety programme

Keywords: Combination, Manufacturing Safety, Monetary Savings, Prevention Strategies.

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Authors: F. Matusek, G. Pujolle, R. Reda

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Shadow detection is still considered as one of the potential challenges for intelligent automated video surveillance systems. A pre requisite for reliable and accurate detection and tracking is the correct shadow detection and classification. In such a landscape of conditions, privacy issues add more and more complexity and require reliable shadow detection. In this work the intertwining between security, accuracy, reliability and privacy is analyzed and, accordingly, a novel architecture for Privacy Enhancing Video Surveillance (PEVS) is introduced. Shadow detection and masking are dealt with through the combination of two different approaches simultaneously. This results in a unique privacy enhancement, without affecting security. Subsequently, the methodology was employed successfully in a large-scale wireless video surveillance system; privacy relevant information was stored and encrypted on the unit, without transferring it over an un-trusted network.

Keywords: Video Surveillance, Intelligent Video Surveillance, Physical Security, WSSU, Privacy, Shadow Detection.

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Authors: Marcin Ciura, Damian Grund, S

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This paper describes a system, in which various methods of text summarizing can be adapted to Polish. A structure of the system is presented. A modular construction of the system and access to the system via the Internet are signaled.

Keywords: Automatic summary generation, linguistic analysis, text generation.

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Authors: A. Won-Yong Chae, B. Hyung-Nam Kim, C. Kyoung-Jun Lee, D. Hee-Je Kim

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The renewable energy has been attracting attention as a new alternative energy due to the problem of environmental pollution and resource depletion. In particular, daylighting and PV system are regarded as the solutions. In this paper, the hybrid dimming control system supplied by solar cell and daylighting system was designed. Daylighting system is main source and PV system is spare source. PV system operates the LED lamp which supports daylighting system because daylighting system is unstable due to the variation of irradiance. In addition, PV system has a role charging batteries. Battery charging has a benefit that PV system operate LED lamp in the bad weather. However, LED lamp always can`t turn on that-s why dimming control system was designed. In particular, the solar charging robot was designed to check the interior irradiance intensity. These systems and the application of the solar charging robot are expected to contribute developing alternative energy in the near future.

Keywords: Daylighting system, PV system, LED lamp, Suntracking robot.

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Authors: Hussein Alahmer, Amr Ahmed

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Liver cancer is one of the common diseases that cause the death. Early detection is important to diagnose and reduce the incidence of death. Improvements in medical imaging and image processing techniques have significantly enhanced interpretation of medical images. Computer-Aided Diagnosis (CAD) systems based on these techniques play a vital role in the early detection of liver disease and hence reduce liver cancer death rate.  This paper presents an automated CAD system consists of three stages; firstly, automatic liver segmentation and lesion’s detection. Secondly, extracting features. Finally, classifying liver lesions into benign and malignant by using the novel contrasting feature-difference approach. Several types of intensity, texture features are extracted from both; the lesion area and its surrounding normal liver tissue. The difference between the features of both areas is then used as the new lesion descriptors. Machine learning classifiers are then trained on the new descriptors to automatically classify liver lesions into benign or malignant. The experimental results show promising improvements. Moreover, the proposed approach can overcome the problems of varying ranges of intensity and textures between patients, demographics, and imaging devices and settings.

Keywords: CAD system, difference of feature, Fuzzy c means, Liver segmentation.

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Authors: Ashot Navasardian, Mariam Vardanian, Vladik Vardanian

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The photovoltaic and the semiconductor industries are in growth and it is necessary to supply a large amount of silicon to maintain this growth. Since silicon is still the best material for the manufacturing of solar cells and semiconductor components so the pure silicon like solar grade and semiconductor grade materials are demanded. There are two main routes for silicon production: metallurgical and chemical. In this article, we reviewed the electrotecnological installations and systems for semiconductor manufacturing. The main task is to design the installation which can produce SOG Silicon from river sand by one work unit.

Keywords: Metallurgical grade silicon, solar grade silicon, impurity, refining, plasma.

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Authors: Viktorie Janečková, Petr Šnapka, Marie Mikušová

Abstract:

This paper aims to initiate an analytical account of the issues of compliance with economy condition for incentive pay system application in an enterprise. Economy is considered one of the conditions for effective incentive pay system application another condition being the achievement of desired efficiency level of the incentive pay system application. Bonus pay system is discussed as an example.

Keywords: Cost analysis, economy, incentive pay system.

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