Search results for: product features

Authors: Ezeni Brzovska, Durdana Ozretic-Dosen

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The purpose of this paper is to deepen the understanding of the product cues that influence purchase decision for a specific product category – chocolate, and to identify demographic differences in the buying behavior. ANOVA was employed for analyzing the significance level for nine product cues, and the survey showed statistically significant differences among different age and gender groups, and between respondents with different levels of education. From the theoretical perspective, the study adds to the existing knowledge by contributing with the research results from the new environment (Southeast Europe, Macedonia), which has been neglected so far. Establishing the level of significance for the product cues that affect buying behavior in the chocolate consumption context might help managers to improve marketing decision-making, and better meet consumer needs through identifying opportunities for packaging innovations and/or personalization toward different target groups.

Keywords: Chocolate consumption context, chocolate selection, demographic characteristics, product cues.

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Authors: Awais Adnan, Muhammad Ali, Amir Hanif Dar

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Image Searching was always a problem specially when these images are not properly managed or these are distributed over different locations. Currently different techniques are used for image search. On one end, more features of the image are captured and stored to get better results. Storing and management of such features is itself a time consuming job. While on the other extreme if fewer features are stored the accuracy rate is not satisfactory. Same image stored with different visual properties can further reduce the rate of accuracy. In this paper we present a new concept of using polynomials of sorted histogram of the image. This approach need less overhead and can cope with the difference in visual features of image.

Keywords: Sorted Histogram, Polynomial Curves, feature pointsof images, Grayscale, visual properties of image.

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Authors: Ghada A. El Khayat

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This paper argues that a product development exercise involves in addition to the conventional stages, several decisions regarding other aspects. These aspects should be addressed simultaneously in order to develop a product that responds to the customer needs and that helps realize objectives of the stakeholders in terms of profitability, market share and the like. We present a framework that encompasses these different development dimensions. The framework shows that a product development methodology such as the Quality Function Deployment (QFD) is the basic tool which allows definition of the target specifications of a new product. Creativity is the first dimension that enables the development exercise to live and end successfully. A number of group processes need to be followed by the development team in order to ensure enough creativity and innovation. Secondly, packaging is considered to be an important extension of the product. Branding strategies, quality and standardization requirements, identification technologies, design technologies, production technologies and costing and pricing are also integral parts to the development exercise. These dimensions constitute the proposed framework. The paper also presents a mathematical model used to calculate the design targets based on the target costing principle. The framework is used to study a case of a new product development in the telecommunications services sector.

Keywords: Product Development Framework, Quality FunctionDeployment, Mathematical Models, Telecommunications.

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Authors: Rasoul Abazari

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In this paper, we show that C*-tensor product of an arbitrary C*-algebra A, (not unital necessary) and C*-algebra B without ground state, have no approximately inner strongly continuous one-parameter group of *-automorphisms.

Keywords: One–parameter group, C*– tensor product, Approximately inner, Ground state.

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Authors: Zeynep Orhan, Zeynep Altan

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This paper summarizes the results of some experiments for finding the effective features for disambiguation of Turkish verbs. Word sense disambiguation is a current area of investigation in which verbs have the dominant role. Generally verbs have more senses than the other types of words in the average and detecting these features for verbs may lead to some improvements for other word types. In this paper we have considered only the syntactical features that can be obtained from the corpus and tested by using some famous machine learning algorithms.

Keywords: Word sense disambiguation, feature selection.

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Authors: Liv Gingnell, Evelina Ericsson, Joakim Lilliesköld, Robert Langerström

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In recent years, an increased competition and lower profit margins have necessitated a focus on improving the performance of the product development process, an area that traditionally have been excluded from detailed steering and evaluation. A systematic improvement requires a good understanding of the current performance, wherefore the interest for product development performance measurement has increased dramatically. This paper presents a case study that evaluates the performance of the product development performance measurement system used in a Swedish company that is a part of a global corporate group. The study is based on internal documentation and eighteen in-depth interviews with stakeholders involved in the product development process. The results from the case study includes a description of what metrics that are in use, how these are employed, and its affect on the quality of the performance measurement system. Especially, the importance of having a well-defined process proved to have a major impact on the quality of the performance measurement system in this particular case.

Keywords: Outcome metric, Performance driver, Performance measurement, Product development process.

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Authors: Alemu Moges Belay

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In the 1980s, companies began to feel the effect of three major influences on their product development: newer and innovative technologies, increasing product complexity and larger organizations. And therefore companies were forced to look for new product development methods. This paper tries to focus on the two of new product development methods (DFM and CE). The aim of this paper is to see and analyze different product development methods specifically on Design for Manufacturability and Concurrent Engineering. Companies can achieve and be benefited by minimizing product life cycle, cost and meeting delivery schedule. This paper also presents simplified models that can be modified and used by different companies based on the companies- objective and requirements. Methodologies that are followed to do this research are case studies. Two companies were taken and analysed on the product development process. Historical data, interview were conducted on these companies in addition to that, Survey of literatures and previous research works on similar topics has been done during this research. This paper also tries to show the implementation cost benefit analysis and tries to calculate the implementation time. From this research, it has been found that the two companies did not achieve the delivery time to the customer. Some of most frequently coming products are analyzed and 50% to 80 % of their products are not delivered on time to the customers. The companies are following the traditional way of product development that is sequentially design and production method, which highly affect time to market. In the case study it is found that by implementing these new methods and by forming multi disciplinary team in designing and quality inspection; the company can reduce the workflow steps from 40 to 30.

Keywords: Design for manufacturability, Concurrent Engineering, Time-to-Market, Product development

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Authors: Yuan-Jye Tseng, Yen-Jung Wang

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A product development for green logistics model using the fuzzy analytic network process method is presented for evaluating the relationships among the product design, the manufacturing activities, and the green supply chain. In the product development stage, there can be alternative ways to design the detailed components to satisfy the design concept and product requirement. In different design alternative cases, the manufacturing activities can be different. In addition, the manufacturing activities can affect the green supply chain of the components and product. In this research, a fuzzy analytic network process evaluation model is presented for evaluating the criteria in product design, manufacturing activities, and green supply chain. The comparison matrices for evaluating the criteria among the three groups are established. The total relational values between the three groups represent the relationships and effects. In application, the total relational values can be used to evaluate the design alternative cases for decision-making to select a suitable design case and the green supply chain. In this presentation, an example product is illustrated. It shows that the model is useful for integrated evaluation of design and manufacturing and green supply chain for the purpose of product development for green logistics.

Keywords: Supply chain management, green supply chain, product development for logistics, fuzzy analytic network process.

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Authors: Chin Tangtarntana

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The main purpose of this study was to investigate the effects of animation in offensive product advertising. Experiment was conducted to collect consumer responses toward animated and static ads of offensive and non-offensive products. The study was conducted by distributing questionnaires to the target respondents. According to statistics from Innovative Internet Research Center, Thailand, majority of internet users are 18 – 44 years old. The results revealed an interaction between ad design and offensive product. Specifically, when used in offensive product advertisements, animated ads were not effective for consumer attention, but yielded positive response in terms of attitude toward product. The findings support that information processing model is accurate in predicting consumer cognitive response toward cartoon ads, whereas U&G, arousal, and distinctive theory is more accurate in predicting consumer affective response. In practical, these findings can also be used to guide ad designers and marketers that are suitable for offensive products.

Keywords: Animation, banner ad design, consumer responses, offensive product advertising, stock exchange of Thailand.

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Authors: J. C. T. Benavente, J. C. E. Ferreira

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The rapid development of manufacturing and information systems has caused significant changes in manufacturing environments in recent decades. Mass production has given way to flexible manufacturing systems, in which an important characteristic is customized or "on demand" production. In this scenario, the seamless and without gaps information flow becomes a key factor for success of enterprises. In this paper we present a framework to support the mapping of features into machining workingsteps compliant with the ISO 14649 standard (known as STEP-NC). The system determines how the features can be made with the available manufacturing resources. Examples of the mapping method are presented for features such as a pocket with a general surface.

Keywords: Features, ISO 14649 standard, STEP-NC, mapping, machining workingsteps.

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Authors: Andrzej Przemyslaw Kusnierczak

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Advances in technology (e.g. the internet, telecommunication) and political changes (fewer trade barriers and an enlarged European Union, ASEAN, NAFTA and other organizations) have led to develop international competition and expand into new markets. Companies in Thailand, Asia and around the globe are increasingly being pressured on price and for faster time to enter the market. At the same time, new markets are appearing and many companies are looking for changes and shifts in their domestic markets. These factors have enabled the rapid growth for companies and globalizing many different business activities during the product development process from research and development (R&D) to production. This research will show and clarify methods how to develop global product. Also, it will show how important is a global product impact into Thai Economy development.

Keywords: Development, global, management, product.

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Authors: Wan-Ting Lin, Chuen-Horng Lin, Tsung-Ho Wu, Yung-Kuan Chan

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This study aims to segment objects using the K-means algorithm for texture features. Firstly, the algorithm transforms color images into gray images. This paper describes a novel technique for the extraction of texture features in an image. Then, in a group of similar features, objects and backgrounds are differentiated by using the K-means algorithm. Finally, this paper proposes a new object segmentation algorithm using the morphological technique. The experiments described include the segmentation of single and multiple objects featured in this paper. The region of an object can be accurately segmented out. The results can help to perform image retrieval and analyze features of an object, as are shown in this paper.

Keywords: k-mean, multiple objects, segmentation, texturefeatures.

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Authors: J.L. Castro, K. Benghazi, M.V. Hurtado, M. Navarro, J.M. Zurita

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Nowadays, quick technological changes force companies to develop innovative products in an increasingly competitive environment. Therefore, how to enhance the time of new product development is very important. This design problem often lacks the exact formula for getting it, and highly depends upon human designers- past experiences. For these reasons, in this work, a Casebased reasoning (CBR) system to assist in new product development is proposed. When a case is recovered from the case base, the system will take into account not only the attribute-s specific value and how important it is. It will also take into account if the attribute has a positive influence over the product development. Hence the manufacturing time will be improved. This information will be introduced as a new concept called “adaptability". An application to this method for hearing instrument new design illustrates the proposed approach.

Keywords: Case based reasoning, Fuzzy logic, New product development, Retrieval stage, Similarity.

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Authors: Chi Jung Kim, Mincheol Whang, Eui Chul Lee

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In this paper, we propose a new method to distinguish between arousal and relaxation states by using multiple features acquired from a photoplethysmogram (PPG) and support vector machine (SVM). To induce arousal and relaxation states in subjects, 2 kinds of sound stimuli are used, and their corresponding biosignals are obtained using the PPG sensor. Two features–pulse to pulse interval (PPI) and pulse amplitude (PA)–are extracted from acquired PPG data, and a nonlinear classification between arousal and relaxation is performed using SVM. This methodology has several advantages when compared with previous similar studies. Firstly, we extracted 2 separate features from PPG, i.e., PPI and PA. Secondly, in order to improve the classification accuracy, SVM-based nonlinear classification was performed. Thirdly, to solve classification problems caused by generalized features of whole subjects, we defined each threshold according to individual features. Experimental results showed that the average classification accuracy was 74.67%. Also, the proposed method showed the better identification performance than the single feature based methods. From this result, we confirmed that arousal and relaxation can be classified using SVM and PPG features.

Keywords: Support Vector Machine, PPG, Emotion Recognition, Arousal, Relaxation

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Authors: Essam Al Daoud

Abstract:

Gradient boosting methods have been proven to be a very important strategy. Many successful machine learning solutions were developed using the XGBoost and its derivatives. The aim of this study is to investigate and compare the efficiency of three gradient methods. Home credit dataset is used in this work which contains 219 features and 356251 records. However, new features are generated and several techniques are used to rank and select the best features. The implementation indicates that the LightGBM is faster and more accurate than CatBoost and XGBoost using variant number of features and records.

Keywords: Gradient boosting, XGBoost, LightGBM, CatBoost, home credit.

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Authors: Ayse Gecer, Nihal Erginel

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Quality control is the crucial step for ISO 9001 Quality System Management Standard for companies. While measuring the quality level of both raw material and semi product/product, the calibration of the measuring device is an essential requirement. Calibration suppliers are in the service sector and therefore the calibration supplier selection is becoming a worthy topic for improving service quality. This study presents the results of a questionnaire about the selection criteria of a calibration supplier. The questionnaire was applied to 103 companies and the results are discussed in this paper. The analysis was made with MINITAB 14.0 statistical programs. “Competence of documentations" and “technical capability" are defined as the prerequisites because of the ISO/IEC17025:2005 standard. Also “warranties and complaint policy", “communication", “service features", “quality" and “performance history" are defined as very important criteria for calibration supplier selection.

Keywords: Calibration, criteria of calibration supplier selection, calibration supplier selection, questionnaire

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Authors: Erika Yamaguchi, Sirawadee Arunyanrt, Shunichi Ohmori, Kazuho Yoshimoto

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In this paper, we suggest a simulation tool to make a decision of monthly production planning for maximizing a profit of Specialty store retailer of Private label Apparel (SPA) firms. Most of SPA firms are fabless and make outsourcing deals for productions with factories of their subcontractors. Every month, SPA firms make a booking for production lines and manpower in the factories. The booking is conducted a few months in advance based on a demand prediction and a monthly production planning at that time. However, the demand prediction is updated month by month, and the monthly production planning would change to meet the latest demand prediction. Then, SPA firms have to change the capacities initially booked within a certain range to suit to the monthly production planning. The booking system is called “capacity-booking”. These days, though it is an issue for SPA firms to make precise monthly production planning, many firms are still conducting the production planning by empirical rules. In addition, it is also a challenge for SPA firms to match their products and factories with considering their demand predictabilities and regulation abilities. In this paper, we suggest a model for considering these two issues. An objective is to maximize a total profit of certain periods, which is sales minus costs of production, inventory, and capacity-booking penalty. To make a better monthly production planning at SPA firms, these points should be considered: demand predictabilities by random trends, previous and next month’s production planning of the target month, and regulation abilities of the capacity-booking. To decide matching products and factories for outsourcing, it is important to consider seasonality, volume, and predictability of each product, production possibility, size, and regulation ability of each factory. SPA firms have to consider these constructions and decide orders with several factories per one product. We modeled these issues as a linear programming. To validate the model, an example of several computational experiments with a SPA firm is presented. We suppose four typical product groups: basic, seasonal (Spring / Summer), seasonal (Fall / Winter), and spot product. As a result of the experiments, a monthly production planning was provided. In the planning, demand predictabilities from random trend are reduced by producing products which are different product types. Moreover, priorities to produce are given to high-margin products. In conclusion, we developed a simulation tool to make a decision of monthly production planning which is useful when the production planning is set every month. We considered the features of capacity-booking, and matching of products and factories which have different features and conditions.

Keywords: Capacity-booking, SPA, monthly production planning, linear programming.

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Authors: Shuki Dror

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This work discusses an innovative methodology for deployment of service quality characteristics. Four groups of organizational features that may influence the quality of services are identified: human resource, technology, planning, and organizational relationships. A House of Service Quality (HOSQ) matrix is built to extract the desired improvement in the service quality characteristics and to translate them into a hierarchy of important organizational features. The Mean Square Error (MSE) criterion enables the pinpointing of the few essential service quality characteristics to be improved as well as selection of the vital organizational features. The method was implemented in an engineering supply enterprise and provides useful information on its vital service dimensions.

Keywords: HOQ, organizational features, service quality.

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Authors: G. Van Dijck, M. M. Van Hulle, M. Wevers

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A genetic algorithm (GA) based feature subset selection algorithm is proposed in which the correlation structure of the features is exploited. The subset of features is validated according to the classification performance. Features derived from the continuous wavelet transform are potentially strongly correlated. GA-s that do not take the correlation structure of features into account are inefficient. The proposed algorithm forms clusters of correlated features and searches for a good candidate set of clusters. Secondly a search within the clusters is performed. Different simulations of the algorithm on a real-case data set with strong correlations between features show the increased classification performance. Comparison is performed with a standard GA without use of the correlation structure.

Keywords: Classification, genetic algorithm, hierarchicalagglomerative clustering, wavelet transform.

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Authors: Yasmeen Bassas, Sandra Kuebler, Allen Riddell

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Native Language Identification is one of the growing subfields in Natural Language Processing (NLP). The task of Native Language Identification (NLI) is mainly concerned with predicting the native language of an author’s writing in a second language. In this paper, we investigate the performance of two types of features; content-based features vs. content independent features when they are evaluated on a different corpus (using social media data “Reddit”). In this NLI task, the predefined models are trained on one corpus (TOEFL) and then the trained models are evaluated on a different data using an external corpus (Reddit). Three classifiers are used in this task; the baseline, linear SVM, and Logistic Regression. Results show that content-based features are more accurate and robust than content independent ones when tested within corpus and across corpus.

Keywords: NLI, NLP, content-based features, content independent features, social media corpus, ML.

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Authors: Fernando Miguel Campos, Fernando Jesus Aguiar, Pedro Campos

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A large amount of software products offer a wide range and number of features. This is called featuritis or creeping featurism and tends to rise with each release of the product. Feautiris often adds unnecessary complexity to software, leading to longer learning curves and overall confusing the users and degrading their experience. We take a look to a new design approach tendency that has been coming up, the so-called “What You Get is What You Need” concept that argues that products should be very focused, simple and with minimalistic interfaces in order to help users conduct their tasks in distraction-free ambiences. This isn’t as simple to implement as it might sound and the developers need to cut down features. Our contribution illustrates and evaluates this design method through a novel distraction-free diagramming tool named Delineato Pro for Mac OS X in which the user is confronted with an empty canvas when launching the software and where tools only show up when really needed.

Keywords: Diagramming, HCI, usability, user interface.

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Authors: Emre Alptekin, Damla Yalçınyiğit, Gülfem Alptekin

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In highly competitive environments, a growing number of companies must regularly launch new products speedily and successfully. A company-s success is based on the systematic, conscious product designing method which meets the market requirements and takes risks as well as resources into consideration. Research has found that developing and launching new products are inherently risky endeavors. Hence in this research, we aim at introducing a risk evaluation framework for the new product innovation process. Our framework is based on the fuzzy analytical hierarchy process (FAHP) methodology. We have applied all the stages of the framework on the risk evaluation process of a pharmaceuticals company.

Keywords: Evaluation, risks, product innovation.

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Authors: Hui Hui Wang, Dzulkifli Mohamad, N.A Ismail

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This paper attempts to discuss the evolution of the retrieval techniques focusing on development, challenges and trends of the image retrieval. It highlights both the already addressed and outstanding issues. The explosive growth of image data leads to the need of research and development of Image Retrieval. However, Image retrieval researches are moving from keyword, to low level features and to semantic features. Drive towards semantic features is due to the problem of the keywords which can be very subjective and time consuming while low level features cannot always describe high level concepts in the users- mind.

Keywords: content based image retrieval, keyword based imageretrieval, semantic gap, semantic image retrieval.

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Authors: Elham Serkani, Hossein Gharaee Garakani, Naser Mohammadzadeh, Elaheh Vaezpour

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Intrusion detection systems (IDS) are the main components of network security. These systems analyze the network events for intrusion detection. The design of an IDS is through the training of normal traffic data or attack. The methods of machine learning are the best ways to design IDSs. In the method presented in this article, the pruning algorithm of C5.0 decision tree is being used to reduce the features of traffic data used and training IDS by the least square vector algorithm (LS-SVM). Then, the remaining features are arranged according to the predictor importance criterion. The least important features are eliminated in the order. The remaining features of this stage, which have created the highest level of accuracy in LS-SVM, are selected as the final features. The features obtained, compared to other similar articles which have examined the selected features in the least squared support vector machine model, are better in the accuracy, true positive rate, and false positive. The results are tested by the UNSW-NB15 dataset.

Keywords: Intrusion detection system, decision tree, support vector machine, feature selection.

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Authors: Orhan Feyzioğlu, Gülçin Büyüközkan

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As a vital activity for companies, new product development (NPD) is also a very risky process due to the high uncertainty degree encountered at every development stage and the inevitable dependence on how previous steps are successfully accomplished. Hence, there is an apparent need to evaluate new product initiatives systematically and make accurate decisions under uncertainty. Another major concern is the time pressure to launch a significant number of new products to preserve and increase the competitive power of the company. In this work, we propose an integrated decision-making framework based on neural networks and fuzzy logic to make appropriate decisions and accelerate the evaluation process. We are especially interested in the two initial stages where new product ideas are selected (go/no go decision) and the implementation order of the corresponding projects are determined. We show that this two-staged intelligent approach allows practitioners to roughly and quickly separate good and bad product ideas by making use of previous experiences, and then, analyze a more shortened list rigorously.

Keywords: Decision Making, Neural Networks, Fuzzy Theory and Systems, Choquet Integral, New Product Development.

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Authors: Hong Choon Ong

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Naïve Bayes classifiers are simple probabilistic classifiers. Classification extracts patterns by using data file with a set of labeled training examples and is currently one of the most significant areas in data mining. However, Naïve Bayes assumes the independence among the features. Structural learning among the features thus helps in the classification problem. In this study, the use of structural learning in Bayesian Network is proposed to be applied where there are relationships between the features when using the Naïve Bayes. The improvement in the classification using structural learning is shown if there exist relationship between the features or when they are not independent.

Keywords: Bayesian Network, Classification, Naïve Bayes, Structural Learning.

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Authors: Jayaletchumi T. Sambantha Moorthy, Suhaimi bin Ibrahim, Mohd Naz’ri Mahrin

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Most quality models have defined usability as a significant factor that leads to improving product acceptability, increasing user satisfaction, improving product reliability, and also financially benefitting companies. Usability is also the best factor that balances both the technical and human aspects of a software product, which is an important aspect in defining quality during software development process. A usability risk consist risk factors that could impact the usability of a software product thereby contributing to negative user experiences and causing a possible software product failure. Hence, it is important to mitigate and reduce usability risks in the software development process itself. By managing possible usability risks in software development process, failure of software product could be reduced. Therefore, this research uses the Delphi method to identify mitigation plans for reducing potential usability risks. The Delphi method is conducted with seven experts from the field of risk management and software development.

Keywords: Usability, Usability Risk, Risk Management, Risk Mitigation, Delphi Method.

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Authors: M. Sumana, K. S. Hareesha

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Secure computations are essential while performing privacy preserving data mining. Distributed privacy preserving data mining involve two to more sites that cannot pool in their data to a third party due to the violation of law regarding the individual. Hence in order to model the private data without compromising privacy and information loss, secure multiparty computations are used. Secure computations of product, mean, variance, dot product, sigmoid function using the additive and multiplicative homomorphic property is discussed. The computations are performed on vertically partitioned data with a single site holding the class value.

Keywords: Homomorphic property, secure product, secure mean and variance, secure dot product, vertically partitioned data.

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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: Zhengyong Liu, Huiqing Ying

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GFRG(Glass Fiber Reinforced Gypsum) wall is a green product which can erect a building fast in prefabricated method, but its application to high-rise residential buildings is limited for its poor lateral stiffness. This paper has proposed a modification to GFRG walls structure to increase its lateral stiffness, which aiming to erect small high-rise residential buildings as load-bearing walls. The elastic finite element analysis to it has shown the lateral deformation feature and the distributions of the axial force and the shear force. The analysis results show that the new GFRG reinforced concrete wall can be used for small high-rise residential buildings.

Keywords: GFRG wall, lateral features, elastic analysis, residential building.

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