Search results for: ISO/IEC 25010 quality model

Authors: A. Golmohammadi, B. Jahandideh

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One of the determinants of a firm-s prosperity is the customers- perceived service quality and satisfaction. While service quality is wide in scope, and consists of various dimensions, there may be differences in the relative importance of these dimensions in affecting customers- overall satisfaction of service quality. Identifying the relative rank of different dimensions of service quality is very important in that it can help managers to find out which service dimensions have a greater effect on customers- overall satisfaction. Such an insight will consequently lead to more effective resource allocation which will finally end in higher levels of customer satisfaction. This issue – despite its criticality- has not received enough attention so far. Therefore, using a sample of 240 bank customers in Iran, an artificial neural network is developed to address this gap in the literature. As customers- evaluation of service quality is a subjective process, artificial neural networks –as a brain metaphor- may appear to have a potentiality to model such a complicated process. Proposing a neural network which is able to predict the customers- overall satisfaction of service quality with a promising level of accuracy is the first contribution of this study. In addition, prioritizing the service quality dimensions in affecting customers- overall satisfaction –by using sensitivity analysis of neural network- is the second important finding of this paper.

Keywords: service quality, customer satisfaction, relative importance, artificial neural network.

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Authors: Odón R. Sánchez-Ccoyllo, Elizabeth Ayma-Choque, Alan Llacza

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Sulphur dioxide (SO₂) and surface-ozone (O₃) concentrations are associated with diseases. The objective of this research is to evaluate the effectiveness of the air-quality Weather Research and Forecasting model coupled to Chemistry (WRF-Chem) model with a horizontal resolution of 5 km x 5 km. For this purpose, the measurements of the hourly SO₂ and O₃ concentrations available in three air quality monitoring stations in Lima, Peru were used for the purpose of validating the simulations of the SO₂ and O₃ concentrations obtained with the WRF-Chem model in February 2018. For the quantitative evaluation of the simulations of these gases, statistical techniques were implemented, such as the average of the simulations; the average of the measurements; the Mean Bias (MeB); the Mean Error (MeE); and the Root Mean Square Error (RMSE). The results of these statistical metrics indicated that the simulated SO₂ and O₃ values over-predicted the SO₂ and O₃ measurements. For the SO₂ concentration, the MeB values varied from 0.58 to 26.35 µg/m³; the MeE values varied from 8.75 to 26.5 µg/m³; the RMSE values varied from 13.3 to 31.79 µg/m³; while for O₃ concentrations the statistical values of the MeB varied from 37.52 to 56.29 µg/m³; the MeE values varied from 37.54 to 56.70 µg/m³; the RMSE values varied from 43.05 to 69.56 µg/m³.

Keywords: Ground-ozone, Lima, Sulphur dioxide, WRF-Chem.

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Authors: Lotfi Nabli, Achraf Jabeur Telmoudi, Radhi M'hiri

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This paper proposes a modeling method of the laws controlling manufacturing systems with temporal and non temporal constraints. A methodology of robust control construction generating the margins of passive and active robustness is being elaborated. Indeed, two paramount models are presented in this paper. The first utilizes the P-time Petri Nets which is used to manage the flow type disturbances. The second, the quality model, exploits the Intervals Constrained Petri Nets (ICPN) tool which allows the system to preserve its quality specificities. The redundancy of the robustness of the elementary parameters between passive and active is also used. The final model built allows the correlation of temporal and non temporal criteria by putting two paramount models in interaction. To do so, a set of definitions and theorems are employed and affirmed by applicator examples.

Keywords: Manufacturing systems control, flow, quality, robustness, redundancy, Petri Nets.

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Authors: Bingchun Liu, Pei-Chann Chang, Natasha Huang, Dun Li

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Machine Learning and Data Mining are the two important tools for extracting useful information and knowledge from large datasets. In machine learning, classification is a wildly used technique to predict qualitative variables and is generally preferred over regression from an operational point of view. Due to the enormous increase in air pollution in various countries especially China, Air Quality Classification has become one of the most important topics in air quality research and modelling. This study aims at introducing a hybrid classification model based on information theory and Support Vector Machine (SVM) using the air quality data of four cities in China namely Beijing, Guangzhou, Shanghai and Tianjin from Jan 1, 2014 to April 30, 2016. China's Ministry of Environmental Protection has classified the daily air quality into 6 levels namely Serious Pollution, Severe Pollution, Moderate Pollution, Light Pollution, Good and Excellent based on their respective Air Quality Index (AQI) values. Using the information theory, information gain (IG) is calculated and feature selection is done for both categorical features and continuous numeric features. Then SVM Machine Learning algorithm is implemented on the selected features with cross-validation. The final evaluation reveals that the IG and SVM hybrid model performs better than SVM (alone), Artificial Neural Network (ANN) and K-Nearest Neighbours (KNN) models in terms of accuracy as well as complexity.

Keywords: Machine learning, air quality classification, air quality index, information gain, support vector machine, cross-validation.

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Authors: Chuang-Chun Chiou, Chien-Ju Liu, Jenteng Tsai

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Due to the rise of aging population, effective utilization of healthcare resources has become an important issue. With the advance of ICT technology, the application of tele-healthcare service has received more attention than ever. The main purpose of this research is to investigate how to conduct innovative design for tele-healthcare service based on user-s perspectives. First, the healthcare service blueprint was used to describe the processes of tele-healthcare service delivery, and then construct PZB service quality gap model based on the literature and practitioners- interviews. Next, TRIZ theory is applied to implement service innovation. We found the proposed service innovation procedures can effectively improve the quality of service design.

Keywords: Tele-homecare, Service blueprint, TRIZ, PZB model

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Authors: Michal Mardiak, Jaroslav Polec

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In this paper we proposed comparison of four content based objective metrics with results of subjective tests from 80 video sequences. We also include two objective metrics VQM and SSIM to our comparison to serve as “reference” objective metrics because their pros and cons have already been published. Each of the video sequence was preprocessed by the region recognition algorithm and then the particular objective video quality metric were calculated i.e. mutual information, angular distance, moment of angle and normalized cross-correlation measure. The Pearson coefficient was calculated to express metrics relationship to accuracy of the model and the Spearman rank order correlation coefficient to represent the metrics relationship to monotonicity. The results show that model with the mutual information as objective metric provides best result and it is suitable for evaluating quality of video sequences.

Keywords: Objective quality metrics, mutual information, region recognition, content based metrics

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Authors: Shinpei Ogata, Yoshitaka Aoki, Hirotaka Okuda, Saeko Matsuura

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A key to success of high quality software development is to define valid and feasible requirements specification. We have proposed a method of model-driven requirements analysis using Unified Modeling Language (UML). The main feature of our method is to automatically generate a Web user interface mock-up from UML requirements analysis model so that we can confirm validity of input/output data for each page and page transition on the system by directly operating the mock-up. This paper proposes a support method to check the validity of a data life cycle by using a model checking tool “UPPAAL" focusing on CRUD (Create, Read, Update and Delete). Exhaustive checking improves the quality of requirements analysis model which are validated by the customers through automatically generated mock-up. The effectiveness of our method is discussed by a case study of requirements modeling of two small projects which are a library management system and a supportive sales system for text books in a university.

Keywords: CRUD, Model Checking, Model Driven Development, Requirements Analysis, Unified Modeling Language, UPPAAL.

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Authors: María Fernández-Ropero, Ricardo Pérez-Castillo, Ismael Caballero, Mario Piattini

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Appropriate description of business processes through standard notations has become one of the most important assets for organizations. Organizations must therefore deal with quality faults in business process models such as the lack of understandability and modifiability. These quality faults may be exacerbated if business process models are mined by reverse engineering, e.g., from existing information systems that support those business processes. Hence, business process refactoring is often used, which change the internal structure of business processes whilst its external behavior is preserved. This paper aims to choose the most appropriate set of refactoring operators through the quality assessment concerning understandability and modifiability. These quality features are assessed through well-proven measures proposed in the literature. Additionally, a set of measure thresholds are heuristically established for applying the most promising refactoring operators, i.e., those that achieve the highest quality improvement according to the selected measures in each case.

Keywords: business process model, modifiability, refactoring, understandability

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Authors: Oktay Nusratov, Ramin Rzaev, Aydin Goyushov

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Fuzzy inference method based approach to the forming of modular intellectual system of assessment the quality of communication services is proposed. Developed under this approach the basic fuzzy estimation model takes into account the recommendations of the International Telecommunication Union in respect of the operation of packet switching networks based on IPprotocol. To implement the main features and functions of the fuzzy control system of quality telecommunication services it is used multilayer feedforward neural network.

Keywords: Quality of communication, IP-telephony, Fuzzy set, Fuzzy implication, Neural network.

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Authors: Pei-Ju Chao, Tsair-Fwu Lee, Wei-Luen Huang, Long-Chang Chen, Te-Jen Su, Wen-Ping Chen

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The main goal in this paper is to quantify the quality of different techniques for radiation treatment plans, a back-propagation artificial neural network (ANN) combined with biomedicine theory was used to model thirteen dosimetric parameters and to calculate two dosimetric indices. The correlations between dosimetric indices and quality of life were extracted as the features and used in the ANN model to make decisions in the clinic. The simulation results show that a trained multilayer back-propagation neural network model can help a doctor accept or reject a plan efficiently. In addition, the models are flexible and whenever a new treatment technique enters the market, the feature variables simply need to be imported and the model re-trained for it to be ready for use.

Keywords: neural network, dosimetric index, radiation treatment, tumor

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Authors: Eunji Choi, Borang Park, Youngjae Choi, Jinwoo Moon

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In this study, a predictive model for estimating the metabolism (MET) of human body was developed for the optimal control of indoor thermal environment. Human body images for indoor activities and human body joint coordinated values were collected as data sets, which are used in predictive model. A deep learning algorithm was used in an initial model, and its number of hidden layers and hidden neurons were optimized. Lastly, the model prediction performance was analyzed after the model being trained through collected data. In conclusion, the possibility of MET prediction was confirmed, and the direction of the future study was proposed as developing various data and the predictive model.

Keywords: Deep learning, indoor quality, metabolism, predictive model.

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Authors: Mohamed Asaad Abdelrazek, Amir Taher El-Sheikh, M. Zayan, A.M. Elhady

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The successful realization of complex systems is dependent not only on the technology issues and the process for implementing them, but on the management issues as well. Managing the systems development lifecycle requires technical management. Systems engineering management is the technical management. Systems engineering management is accomplished by incorporating many activities. The three major activities are development phasing, systems engineering process and lifecycle integration. Systems engineering management activities are performed across the system development lifecycle. Due to the ever-increasing complexity of systems as well the difficulty of managing and tracking the development activities, new ways to achieve systems engineering management activities are required. This paper presents a systematic approach used as a design management tool applied across systems engineering management roles. In this approach, Transdisciplinary System Development Lifecycle (TSDL) Model has been modified and integrated with Quality Function Deployment. Hereinafter, the name of the systematic approach is the Transdisciplinary Quality System Development Lifecycle (TQSDL) Model. The QFD translates the voice of customers (VOC) into measurable technical characteristics. The modified TSDL model is based on Axiomatic Design developed by Suh which is applicable to all designs: products, processes, systems and organizations. The TQSDL model aims to provide a robust structure and systematic thinking to support the implementation of systems engineering management roles. This approach ensures that the customer requirements are fulfilled as well as satisfies all the systems engineering manager roles and activities.

Keywords: Axiomatic design, quality function deployment, systems engineering management, system development lifecycle.

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Authors: Mohamed Idris S. Abozaed, Suliman Mohamed Elrajoubi

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Researches and concerns in power quality gained significant momentum in the field of power electronics systems over the last two decades globally. This sudden increase in the number of concerns over power quality problems is a result of the huge increase in the use of non-linear loads. In this paper, power quality evaluation of some distribution networks at Misurata - Libya has been done using a power quality and energy analyzer (Fluke 437 Series II). The results of this evaluation are used to minimize the problems of power quality. The analysis shows the main power quality problems that exist and the level of awareness of power quality issues with the aim of generating a start point which can be used as guidelines for researchers and end users in the field of power systems.

Keywords: Power Quality Disturbances, Power Quality Evaluation, Statistical Analysis.

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Authors: Abdoullah Fath-Allah, Laila Cheikhi, Rafa E. Al-Qutaish, Ali Idri

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The e-government emerging concept transforms the way in which the citizens are dealing with their governments. Thus, the citizens can execute the intended services online anytime and anywhere. This results in great benefits for both the governments (reduces the number of officers) and the citizens (more flexibility and time saving). Therefore, building a maturity model to assess the egovernment portals becomes desired to help in the improvement process of such portals. This paper aims at proposing an egovernment maturity model based on the measurement of the best practices’ presence. The main benefit of such maturity model is to provide a way to rank an e-government portal based on the used best practices, and also giving a set of recommendations to go to the higher stage in the maturity model.

Keywords: Best practices, e-government portal, maturity model, quality model.

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Authors: Çiğdem Bakır, Mecit Yüzkat

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With the increasing emphasis on water quality worldwide, the search for and expanding the market for new and intelligent monitoring systems has increased. The current method is the laboratory process, where samples are taken from bodies of water, and tests are carried out in laboratories. This method is time-consuming, a waste of manpower and uneconomical. To solve this problem, we used machine learning methods to detect water pollution in our study. We created decision trees with the Orange3 software used in the study and tried to determine all the factors that cause water pollution. An automatic prediction model based on water quality was developed by taking many model inputs such as water temperature, pH, transparency, conductivity, dissolved oxygen, and ammonia nitrogen with machine learning methods. The proposed approach consists of three stages: Preprocessing of the data used, feature detection and classification. We tried to determine the success of our study with different accuracy metrics and the results were presented comparatively. In addition, we achieved approximately 98% success with the decision tree.

Keywords: Decision tree, water quality, water pollution, machine learning.

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Authors: Guangzhuang Yu, Chun-Chu Liu

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With the advent of the Internet era in recent years, social music education has gradually shifted from the original entity education mode to the mode of entity plus network teaching. No matter for school music education, professional music education or social music education, the teaching quality is the most important evaluation index. Regarding the research on teaching quality evaluation, scholars at home and abroad have contributed a lot of research results on the basis of multiple methods and evaluation subjects. However, to our best knowledge the complete evaluation model for the virtual teaching interaction mode of the emerging network music education Application (APP) has not been established. This research firstly found out the basic dimensions that accord with the teaching quality required by the three parties, constructing the quality evaluation index system; and then, on the basis of expounding the connotation of each index, it determined the weight of each index by using method of fuzzy analytic hierarchy process, providing ideas and methods for scientific, objective and comprehensive evaluation of the teaching quality of network education APP.

Keywords: Network music education APP, teaching quality evaluation, index, connotation.

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Authors: A. Bajit, M. Nahid, A. Tamtaoui, E. H. Bouyakhf

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In this paper, we propose a Perceptually Optimized Foveation based Embedded ZeroTree Image Coder (POEFIC) that introduces a perceptual weighting to wavelet coefficients prior to control SPIHT encoding algorithm in order to reach a targeted bit rate with a perceptual quality improvement with respect to a given bit rate a fixation point which determines the region of interest ROI. The paper also, introduces a new objective quality metric based on a Psychovisual model that integrates the properties of the HVS that plays an important role in our POEFIC quality assessment. Our POEFIC coder is based on a vision model that incorporates various masking effects of human visual system HVS perception. Thus, our coder weights the wavelet coefficients based on that model and attempts to increase the perceptual quality for a given bit rate and observation distance. The perceptual weights for all wavelet subbands are computed based on 1) foveation masking to remove or reduce considerable high frequencies from peripheral regions 2) luminance and Contrast masking, 3) the contrast sensitivity function CSF to achieve the perceptual decomposition weighting. The new perceptually optimized codec has the same complexity as the original SPIHT techniques. However, the experiments results show that our coder demonstrates very good performance in terms of quality measurement.

Keywords: DWT, linear-phase 9/7 filter, Foveation Filtering, CSF implementation approaches, 9/7 Wavelet JND Thresholds and Wavelet Error Sensitivity WES, Luminance and Contrast masking, standard SPIHT, Objective Quality Measure, Probability Score PS.

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Authors: Pham Thanh Trung, Huynh Quyet Thang

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Reliability is one of the most important quality attributes of software. Based on the approach of Reussner and the approach of Cheung, we proposed the reliability prediction model of component-based software architectures. Also, the value of the model is shown through the experimental evaluation on a web server system.

Keywords: component-based architecture, reliability prediction model, software reliability engineering.

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Authors: Cheng-Che Tsai, Huang-Ming Chuang

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The purpose of this paper is to explore the role of cognitive decision effort in recommendation system, combined with indicators "information quality" and "service quality" from IS success model to exam the awareness of the user for the "recommended system performance". A total of 411 internet user answered a questionnaire assessing their attention of use and satisfaction of recommendation system in internet book store. Quantitative result indicates following research results. First, information quality of recommended system has obvious influence in consumer shopping decision-making process, and the attitude to use the system. Second, in the process of consumer's shopping decision-making, the recommendation system has no significant influence for consumers to pay lower cognitive decision-making effort. Third, e-commerce platform provides recommendations and information is necessary, but the quality of information on user needs must be considered, or they will be other competitors offer homogeneous services replaced.

Keywords: Recommender system, Cognitive decision-making efforts, IS success model, Internet bookstore.

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Authors: S. Areerachakul

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Nowadays, several techniques such as; Fuzzy Inference System (FIS) and Neural Network (NN) are employed for developing of the predictive models to estimate parameters of water quality. The main objective of this study is to compare between the predictive ability of the Adaptive Neuro-Fuzzy Inference System (ANFIS) model and Artificial Neural Network (ANN) model to estimate the Biochemical Oxygen Demand (BOD) on data from 11 sampling sites of Saen Saep canal in Bangkok, Thailand. The data is obtained from the Department of Drainage and Sewerage, Bangkok Metropolitan Administration, during 2004-2011. The five parameters of water quality namely Dissolved Oxygen (DO), Chemical Oxygen Demand (COD), Ammonia Nitrogen (NH3N), Nitrate Nitrogen (NO3N), and Total Coliform bacteria (T-coliform) are used as the input of the models. These water quality indices affect the biochemical oxygen demand. The experimental results indicate that the ANN model provides a higher correlation coefficient (R=0.73) and a lower root mean square error (RMSE=4.53) than the corresponding ANFIS model.

Keywords: adaptive neuro-fuzzy inference system, artificial neural network, biochemical oxygen demand, surface water.

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Authors: S. Aberkane, N. Djabali, S. Fafi, A. Baghezza

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Chronic illnesses affect many Algerians. It is possible to investigate the impact of illness representations and coping on quality of life and whether illness representations are indirectly associated with quality of life through their influence on coping. This study aims at investigating the relationship between illness perception, coping strategies and quality of life with chronic illness. Illness perceptions are indirectly associated with the quality of life through their influence on coping mediation. A sample of 316 participants with chronic illness living in the region of Batna, Algeria, has been adopted in this study. A correlation statistical analysis is used to determine the relationship between illness perception, coping strategies, and quality of life. Multiple regression analysis was employed to highlight the predictive ability of the dimensions of illness perception and coping strategies on the dependent variables of quality of life, where mediation analysis is considered in the exploration of the indirect effect significance of the mediator. This study provides insights about the relationship between illness perception, coping strategies and quality of life in the considered sample (r = 0.39, p < 0.01). Therefore, it proves that there is an effect of illness identity perception, external and medical attributions related to emotional role, physical functioning, and mental health perceived, and these were fully mediated by the asking for assistance (c’= 0.04, p < 0.05), the guarding (c’= 0.00, p < 0.05), and the task persistence strategy (c’= 0.05, p < 0.05). The findings imply partial support for the common-sense model of illness representations in a chronic illness population. Directions for future research are highlighted, as well as implications for psychotherapeutic interventions which target unhelpful beliefs and maladaptive coping strategies (e.g., cognitive behavioral therapy).

Keywords: Chronic illness, coping, illness perception, quality of life, self-regulation model.

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Authors: M. Stoklasa, H. Starzyczna, K. Matusinska

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This article deals with the perceived quality of regional products in the Moravian-Silesian region in the Czech Republic. Research was focused on finding out what do consumers perceive as a quality product and what characteristics make a quality product. The data were obtained by questionnaire survey andanalysed by IBM SPSS. From the thousands of respondents the representative sample of 719 for MS region was created based on demographic factors of gender, age, education and income. The research analysis disclosed that consumers in MS region are still price oriented and that the preference of quality over price does not depend on regional brand knowledge.

Keywords: Regional brands, quality products, characteristics of quality, quality over price.

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Authors: Abdul H, Jamil A, Imran U

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Conflicts identification among non-functional requirements is often identified intuitively which impairs conflict analysis practices. This paper proposes a new model to identify conflicts among non-functional requirements. The proposed model uses the matrix mechanism to identify the quality based conflicts among non-functional requirements. The potential conflicts are identified through the mapping of low level conflicting quality attributes to low level functionalities using the matrices. The proposed model achieves the identification of conflicts among product and process requirements, identifies false conflicts, decreases the documentation overhead, and maintains transparency of identified conflicts. The attributes are not concomitantly taken into account by current models in practice.

Keywords: Conflict Identification, Matrix Maps, Non-functional Requirements, Requirements Analysis, Software Engineering

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Authors: B. E. Narkhede, S. K. Mahajan, B. T. Patil, R. D. Raut

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Information quality is a major performance measure for an Enterprise Resource Planning (ERP) system of any firm. This study identifies various critical success factors of information quality. The effect of various critical success factors like project management, reengineering efforts and interdepartmental communications on information quality is analyzed using a multiple regression model. Here quantitative data are collected from respondents from various firms through structured questionnaire for assessment of the information quality, project management, reengineering efforts and interdepartmental communications. The validity and reliability of the data are ensured using techniques like factor analysis, computing of Cronbach’s alpha. This study gives relative importance of each of the critical success factors. The findings suggest that among the various factors influencing information quality careful reengineering efforts are the most influencing factor. This paper gives clear insight to managers and practitioners regarding the relative importance of critical success factors influencing information quality so that they can formulate a strategy at the beginning of ERP system implementation.

Keywords: Enterprise resource planning, information systems, multiple regression, information quality.

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Authors: Andrés Carrión García, Aura López de Murillo, José Jabaloyes Vivas, Angela Grisales del Río

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Some quality control tools use non metric subjective information coming from experts, who qualify the intensity of relations existing inside processes, but without quantifying them. In this paper we have developed a quality control analytic tool, measuring the impact or strength of the relationship between process operations and product characteristics. The tool includes two models: a qualitative model, allowing relationships description and analysis; and a formal quantitative model, by means of which relationship quantification is achieved. In the first one, concepts from the Graphs Theory were applied to identify those process elements which can be sources of variation, that is, those quality characteristics or operations that have some sort of prelacy over the others and that should become control items. Also the most dependent elements can be identified, that is those elements receiving the effects of elements identified as variation sources. If controls are focused in those dependent elements, efficiency of control is compromised by the fact that we are controlling effects, not causes. The second model applied adapts the multivariate statistical technique of Covariance Structural Analysis. This approach allowed us to quantify the relationships. The computer package LISREL was used to obtain statistics and to validate the model.

Keywords: Characteristics matrix, covariance structure analysis, LISREL.

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Authors: Ratchakit Sakuldee, Somkait Udomhunsakul

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Measurement of the quality of image compression is important for image processing application. In this paper, we propose an objective image quality assessment to measure the quality of gray scale compressed image, which is correlation well with subjective quality measurement (MOS) and least time taken. The new objective image quality measurement is developed from a few fundamental of objective measurements to evaluate the compressed image quality based on JPEG and JPEG2000. The reliability between each fundamental objective measurement and subjective measurement (MOS) is found. From the experimental results, we found that the Maximum Difference measurement (MD) and a new proposed measurement, Structural Content Laplacian Mean Square Error (SCLMSE), are the suitable measurements that can be used to evaluate the quality of JPEG200 and JPEG compressed image, respectively. In addition, MD and SCLMSE measurements are scaled to make them equivalent to MOS, given the rate of compressed image quality from 1 to 5 (unacceptable to excellent quality).

Keywords: JPEG, JPEG2000, objective image quality measurement, subjective image quality measurement, correlation coefficients.

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Authors: K. Petcharaporn, S. Kumchoo

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The acidity (citric acid) is the one of chemical content that can be refer to the internal quality and it’s a maturity index of tomato, The titratable acidity (%TA) can be predicted by a non-destructive method prediction by using the transmittance short wavelength (SW-NIR) spectroscopy in the wavelength range between 665-955 nm. The set of 167 tomato samples divided into groups of 117 tomatoes sample for training set and 50 tomatoes sample for test set were used to establish the calibration model to predict and measure %TA by partial least squares regression (PLSR) technique. The spectra were pretreated with MSC pretreatment and it gave the optimal result for calibration model as (R = 0.92, RMSEC = 0.03%) and this model obtained high accuracy result to use for %TA prediction in test set as (R = 0.81, RMSEP = 0.05%). From the result of prediction in test set shown that the transmittance SW-NIR spectroscopy technique can be used for a non-destructive method for %TA prediction of tomato.

Keywords: Tomato, quality, prediction, transmittance, titratable acidity, citric acid.

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Authors: L. Tao, T. J. Sun, Z. H. Li

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The knowledge base of welding defect recognition is essentially incomplete. This characteristic determines that the recognition results do not reflect the actual situation. It also has a further influence on the classification of welding quality. This paper is concerned with the study of a rough set based method to reduce the influence and improve the classification accuracy. At first, a rough set model of welding quality intelligent classification has been built. Both condition and decision attributes have been specified. Later on, groups of the representative multiple compound defects have been chosen from the defect library and then classified correctly to form the decision table. Finally, the redundant information of the decision table has been reducted and the optimal decision rules have been reached. By this method, we are able to reclassify the misclassified defects to the right quality level. Compared with the ordinary ones, this method has higher accuracy and better robustness.

Keywords: intelligent decision, rough set, welding defects, welding quality level

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Authors: Mihails Kulikovs, Ernests Petersons

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Network management techniques have long been of interest to the networking research community. The queue size plays a critical role for the network performance. The adequate size of the queue maintains Quality of Service (QoS) requirements within limited network capacity for as many users as possible. The appropriate estimation of the queuing model parameters is crucial for both initial size estimation and during the process of resource allocation. The accurate resource allocation model for the management system increases the network utilization. The present paper demonstrates the results of empirical observation of memory allocation for packet-based services.

Keywords: Queuing System, Packet Loss Probability, Measurement-Based Admission Control (MBAC), Performanceevaluation, Quality of Service (QoS).

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Authors: Sadaf Sahar, Usman Qamar, Sadaf Ayaz

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In the software development lifecycle, the quality prediction techniques hold a prime importance in order to minimize future design errors and expensive maintenance. There are many techniques proposed by various researchers, but with the increasing complexity of the software lifecycle model, it is crucial to develop a flexible system which can cater for the factors which in result have an impact on the quality of the end product. These factors include properties of the software development process and the product along with its operation conditions. In this paper, a neural network (perceptron) based software quality prediction technique is proposed. Using this technique, the stakeholders can predict the quality of the resulting software during the early phases of the lifecycle saving time and resources on future elimination of design errors and costly maintenance. This technique can be brought into practical use using successful training.

Keywords: Software quality, fuzzy logic, perceptron, prediction.

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