Search results for: service classification

Authors: Samah Benmerbi, Kamal Amroun, Abdelkamel Tari

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The increasing number of Web service (WS)providers throughout the globe, have produced numerous Web services providing the same or similar functionality. Therefore, there is a need of tools developing the best answer of queries by selecting and composing services with total transparency. This paper reviews various QoS based Web service selection mechanisms and architectures which facilitate qualitatively optimal selection, in other fact Web service composition is required when a request cannot be fulfilled by a single web service. In such cases, it is preferable to integrate existing web services to satisfy user’s request. We introduce an automatic Web service composition method based on hypergraph decomposition using hypertree decomposition method. The problem of selection and the composition of the web services is transformed into a resolution in a hypertree by exploring the relations of dependency between web services to get composite web service via employing an execution order of WS satisfying global request.

Keywords: web service, web service selection, web service composition, QoS, hypergraph decomposition, BE hypergraph decomposition, hypertree resolution

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Authors: Po-Jen Chen, Jian-Jiun Ding, Hung-Wei Hsu, Chien-Yao Wang, Jia-Ching Wang

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A more accurate scene classification algorithm using label relations and the hierarchy neural network was developed in this work. In many classification algorithms, it is assumed that the labels are mutually exclusive. This assumption is true in some specific problems, however, for scene classification, the assumption is not reasonable. Because there are a variety of objects with a photo image, it is more practical to assign multiple labels for an image. In this paper, two label relations, which are exclusive relation and hierarchical relation, were adopted in the classification process to achieve more accurate multiple label classification results. Moreover, the hierarchy neural network (hierarchy NN) is applied to classify the image and the directed acyclic graph structure is used for predicting a more reasonable result which obey exclusive and hierarchical relations. Simulations show that, with these techniques, a much more accurate scene classification result can be achieved.

Keywords: convolutional neural network, label relation, hierarchy neural network, scene classification

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Authors: Vimi Jham

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The banking sector has undergone tremendous change in all forms of service it provides to its customers. The efforts of the banks is to avoid customer defection and lead to customer satisfaction. The purpose of the study was to examine the linkages among the constructs such as customer perceived service quality, perceived service recovery quality and customer satisfaction in the banking industry. The moderating effect of negative brand perception due to service failure on recovery satisfaction were investigated. Random sampling methods are used to draw the sample from the population. Data was collected from 262 banking customers and were analyzed with the help of structural equation modelling approach using Smart PLS to understand the relationship among variables being studied. The results of the study contribute to the research by proving that customer service recovery satisfaction is dependent on customer perceived service quality and the moderating effect of negative brand perception due to service failure was insignificant.

Keywords: service recovery satisfaction, perceived service recovery quality, perceived service quality, structural equation modelling

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Authors: Amin Hamrahi, Niloofar Moghaddam

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Denial of Service is for denial-of-service attack, a type of attack on a network that is designed to bring the network to its knees by flooding it with useless traffic. Denial of Service (DoS) attacks have become a major threat to current computer networks. Many recent DoS attacks were launched via a large number of distributed attacking hosts in the Internet. These attacks are called distributed denial of service (DDoS) attacks. To have a better understanding on DoS attacks, this article provides an overview on existing DoS and DDoS attacks and major defense technologies in the Internet.

Keywords: denial of service, distributed denial of service, traffic, flooding

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Authors: Sanchali Das, Swapan Debbarma

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Music mood classification is developing in both the areas of music information retrieval (MIR) and natural language processing (NLP). Some of the Indian languages like Hindi English etc. have considerable exposure in MIR. But research in mood classification in regional language is very less. In this paper, powerful audio based feature for Kokborok Christian song is identified and mood classification task has been performed. Kokborok is an Indo-Burman language especially spoken in the northeastern part of India and also some other countries like Bangladesh, Myanmar etc. For performing audio-based classification task, useful audio features are taken out by jMIR software. There are some standard audio parameters are there for the audio-based task but as known to all that every language has its unique characteristics. So here, the most significant features which are the best fit for the database of Kokborok song is analysed. The regression-based model is used to find out the independent parameters that act as a predictor and predicts the dependencies of parameters and shows how it will impact on overall classification result. For classification WEKA 3.5 is used, and selected parameters create a classification model. And another model is developed by using all the standard audio features that are used by most of the researcher. In this experiment, the essential parameters that are responsible for effective audio based mood classification and parameters that do not significantly change for each of the Christian Kokborok songs are analysed, and a comparison is also shown between the two above model.

Keywords: Christian Kokborok song, mood classification, music information retrieval, regression

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Authors: Thanh Nguyen, Andrei Doncescu, Pierre Siegel

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Classification is an important data mining technique and could be used as data filtering in artificial intelligence. The broad application of classification for all kind of data leads to be used in nearly every field of our modern life. Classification helps us to put together different items according to the feature items decided as interesting and useful. In this paper, we compare two classification methods Naïve Bayes and ADTree use to detect spam e-mail. This choice is motivated by the fact that Naive Bayes algorithm is based on probability calculus while ADTree algorithm is based on decision tree. The parameter settings of the above classifiers use the maximization of true positive rate and minimization of false positive rate. The experiment results present classification accuracy and cost analysis in view of optimal classifier choice for Spam Detection. It is point out the number of attributes to obtain a tradeoff between number of them and the classification accuracy.

Keywords: classification, data mining, spam filtering, naive bayes, decision tree

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Authors: Mohammad Sarchami, Mohsen Zeinalkhani

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Always, financial reporting system faces some problems to win public ear. The increase in the number of fraud and representation, often combined with the bankruptcy of large companies, has raised concerns about the quality of financial statements. So, investors, legislators, managers, and auditors have focused on significant fraud detection or prevention in financial statements. This article aims to investigate the Sugeno fuzzy classification to consider fraud detection in financial reporting of accepted firms by Tehran stock exchange. The hypothesis is: Sugeno fuzzy classification may detect fraud in financial reporting by financial ratio. Hypothesis was tested using Matlab software. Accuracy average was 81/80 in Sugeno fuzzy classification; so the hypothesis was confirmed.

Keywords: fraud, financial reporting, Sugeno fuzzy classification, firm

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Authors: Hao-Hsiang Ku, Ching-Ho Chi

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Big data applications have become an imperative for many fields. Many researchers have been devoted into increasing correct rates and reducing time complexities. Hence, the study designs and proposes an Ontology-based backpropagation neural network classification and reasoning strategy for NoSQL big data applications, which is called ON4NoSQL. ON4NoSQL is responsible for enhancing the performances of classifications in NoSQL and SQL databases to build up mass behavior models. Mass behavior models are made by MapReduce techniques and Hadoop distributed file system based on Hadoop service platform. The reference engine of ON4NoSQL is the ontology-based backpropagation neural network classification and reasoning strategy. Simulation results indicate that ON4NoSQL can efficiently achieve to construct a high performance environment for data storing, searching, and retrieving.

Keywords: Hadoop, NoSQL, ontology, back propagation neural network, high distributed file system

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Authors: Vesile Evrim, Aliyu Awwal

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Today as in the other domains, there are an enormous number of political transcripts available in the Web which is waiting to be mined and used for various purposes such as statistics and recommendations. Therefore, automatically determining the political orientation on these transcripts becomes crucial. The methodologies used by machine learning algorithms to do the automatic classification are based on different features such as Linguistic. Considering the ideology differences between Liberals and Conservatives, in this paper, the effect of Personality Traits on political orientation classification is studied. This is done by considering the correlation between LIWC features and the BIG Five Personality Traits. Several experiments are conducted on Convote U.S. Congressional-Speech dataset with seven benchmark classification algorithms. The different methodologies are applied on selecting different feature sets that constituted by 8 to 64 varying number of features. While Neuroticism is obtained to be the most differentiating personality trait on classification of political polarity, when its top 10 representative features are combined with several classification algorithms, it outperformed the results presented in previous research.

Keywords: politics, personality traits, LIWC, machine learning

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Authors: Byeongju Choi, Sanggil Lee, Kyung-Eun Lee

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Introduction: In the republic of Korea, the number of workers in the beauty industry has been increasing. Because the prevalence of hepatitis B carriers in Korea is higher than in other countries, the risk of blood-borne infection including viral hepatitis B and C, among the workers by using the sharp and contaminated instruments during procedure can be expected among beauty salon workers. However, the health care policies for the workers to prevent the blood-borne infection are not established due to the lack of evidences. Moreover, the workers in hair and nail salon were mostly employed at small businesses, where national mandatory systems or policies for workers’ health management are not applied. In this study, the risk of the viral hepatitis B and C from the job experiencing the hair and nail procedures in the mortality was assessed. Method: We conducted a retrospective review of the job histories and causes of death in the female deaths from 2006-2016. 132,744 of female deaths who had one more job experiences during their lifetime were included in this study. Job histories were assessed using the employment insurance database in Korea Employment Information Service (KEIS) and the causes of death were in death statistics produced by Statistics Korea. Case group (n= 666) who died from viral hepatitis was classified the death having record involved in ‘B15-B19’ as a cause of deaths based on Korean Standard Classification of Diseases(KCD) with the deaths from other causes, control group (n=132,078). The group of the workers in the beauty service industry were defined as the employees who had ever worked in the industry coded as ‘9611’ based on Korea Standard Industry Classification (KSIC) and others were others. Other than job histories, birth year, marital status, education level were investigated from the death statistics. Multiple logistic regression analysis were used to assess the risk of deaths from viral hepatitis in the case and control group. Result: The number of the deaths having ever job experiences at the hair and nail salon was 255. After adjusting confounders of age, marital status and education, the odds ratio(OR) for deaths from viral hepatitis was quite high in the group having experiences with working in the beauty service industry with 3.14(95% confidence interval(CI) 1.00-9.87). Other associated factors with increasing the risk of deaths from viral hepatitis were low education level(OR=1.34, 95% CI 1.04-1.73), married women (OR=1.42, 95% CI 1.02-1.97). Conclusion: The risk of deaths from viral hepatitis were high in the workers in the beauty service industry but not statistically significant, which might attributed from the small number of workers in beauty service industry. It was likely that the number of workers in beauty service industry could be underestimated due to their temporary job position. Further studies evaluating the status and the incidence of viral infection among the workers with consideration of the vertical transmission would be required.

Keywords: beauty service, viral hepatitis, blood-borne infection, viral infection

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Authors: Kazeem Oluwakemi Oseni, Kate Dingley

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E-Service has moved from the usual manual and traditional way of rendering services to electronic service provision for the public and there are several reasons for implementing these services, Airline ticketing have gone from its manual traditional way to an intelligent web-driven service of purchasing. Many companies have seen their profits doubled through the use of online services in their operation and a typical example is Hewlett Packard (HP) which is rapidly transforming their after sales business into a profit generating e-service business unit. This paper will examine the various challenges confronting e-Service adoption and implementation in Nigeria and also analyse lessons learnt from e-Service adoption and implementation in Asia to see how it could be useful in Nigeria which is a lower middle income country. Based on the analysis of the online survey data. It has been identified that the public in Nigeria are much aware of e-Services but successful adoption and implementation have been the problems faced.

Keywords: e-government service, adoption, implementation, Nigeria, Asia

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Authors: M.R Asghari Bejestani, Gh. R. Mohammad Khani, V.R. Nafisi

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Imagined speech recognition is one of the most interesting approaches to BCI development and a lot of works have been done in this area. Many different experiments have been designed and hundreds of combinations of feature extraction methods and classifiers have been examined. Reported classification accuracies range from the chance level to more than 90%. Based on non-stationary nature of brain signals, we have introduced 3 classification modes according to time difference in inter and intra-class samples. The modes can explain the diversity of reported results and predict the range of expected classification accuracies from the brain signal accusation procedure. In this paper, a few samples are illustrated by inspecting results of some previous works.

Keywords: brain computer interface, silent talk, imagined speech, classification, signal processing

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Authors: Ren Moses, Jaqueline Masaki

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This paper addresses the need for accurate and updated vehicle classification system through a thorough evaluation of vehicle class categories to identify errors arising from the existing system and proposing modifications. The data collected from two permanent traffic monitoring sites in Florida were used to evaluate the performance of the existing vehicle classification table. The vehicle data were collected and classified by the automatic vehicle classifier (AVC), and a video camera was used to obtain ground truth data. The Federal Highway Administration (FHWA) vehicle classification definitions were used to define vehicle classes from the video and compare them to the data generated by AVC in order to identify the sources of misclassification. Six types of errors were identified. Modifications were made in the classification table to improve the classification accuracy. The results of this study include the development of updated vehicle classification table with a reduction in total error by 5.1%, a step by step procedure to use for evaluation of vehicle classification studies and recommendations to improve FHWA 13-category rule set. The recommendations for the FHWA 13-category rule set indicate the need for the vehicle classification definitions in this scheme to be updated to reflect the distribution of current traffic. The presented results will be of interest to States’ transportation departments and consultants, researchers, engineers, designers, and planners who require accurate vehicle classification information for planning, designing and maintenance of transportation infrastructures.

Keywords: vehicle classification, traffic monitoring, pavement design, highway traffic

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Authors: Siri-Orn Champatong

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The objectives of this research were to study the attitude of service marketing mix that affected the decision making behavior to use fitness service in case of the fitness in Thailand. This study employed by survey research and questionnaire was used to collect the data from 400 of consumers who have used the service and interested in using the service in the future. The descriptive statistics and multiple regression analysis were used to analyze data. The results revealed that the attitude toward overall marketing mix was at moderate level. For particulars, attitude toward product and service aspects were at good level, however, attitude toward price, place, promotion, people, physical evidence and service quality aspects were at moderate level. The hypothesis testing results showed that attitude toward each aspect affected word of mouth, however, attitude toward product and service, place, promotion, people and physical evidence affected tendency to use fitness service at .05 statistically significant level.

Keywords: decision making behavior, fitness, marketing mix, marketing service

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Authors: Pranee Tridhoskul

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This research paper is aimed to examine a relationship between the service marketing mix and customers’ frequency of use of service at Mercedes Benz Auto Repair Centres under Thonburi Group, Thailand. Based on 2,267 customers who used the service of Thonburi Group’s Auto Repair Centres as the population, the sampling of this research was a total of 340 samples, by use of Probability Sampling Technique. Systematic Random Sampling was applied by use of questionnaire in collecting the data at Thonburi Group’s Auto Repair Centres. Mean and Pearson’s basic statistical correlations were utilized in analyzing the data. The study discovered a medium level of customers’ perception towards product and service of Thonburi Group’s Auto Repair Centres, price, place or distribution channel and promotion. People who provided service were perceived also at a medium level, whereas the physical evidence and service process were perceived at a high level. Furthermore, there appeared a correlation between the physical evidence and service process, and customers’ frequency of use of automobile service per year.

Keywords: service marketing mix, behavior, Mercedes Auto Service Centre, frequency of use

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Authors: Dewi Juliah Ratnaningsih, Imas Sukaesih Sitanggang

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Classification is one of data mining techniques that aims to discover a model from training data that distinguishes records into the appropriate category or class. Data mining classification methods can be applied in education, for example, to determine the classification of non-active students in Indonesia Open University. This paper presents a comparison of three methods of classification: Naïve Bayes, Bagging, and C.45. The criteria used to evaluate the performance of three methods of classification are stratified cross-validation, confusion matrix, the value of the area under the ROC Curve (AUC), Recall, Precision, and F-measure. The data used for this paper are from the non-active Indonesia Open University students in registration period of 2004.1 to 2012.2. Target analysis requires that non-active students were divided into 3 groups: C1, C2, and C3. Data analyzed are as many as 4173 students. Results of the study show: (1) Bagging method gave a high degree of classification accuracy than Naïve Bayes and C.45, (2) the Bagging classification accuracy rate is 82.99 %, while the Naïve Bayes and C.45 are 80.04 % and 82.74 % respectively, (3) the result of Bagging classification tree method has a large number of nodes, so it is quite difficult in decision making, (4) classification of non-active Indonesia Open University student characteristics uses algorithms C.45, (5) based on the algorithm C.45, there are 5 interesting rules which can describe the characteristics of non-active Indonesia Open University students.

Keywords: comparative analysis, data mining, clasiffication, Bagging, Naïve Bayes, C.45, non-active students, Indonesia Open University

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Authors: Anu Paul, Varghese Paul

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The focal aspire of e-Government (eGovt) is to offer citizen-centered service delivery. Accordingly, the citizenry consumes services from multiple government agencies through national portal. Thus, eGovt is an enterprise with the primary business motive of transparent, efficient and effective public services to its citizenry and its logical structure is the eGovernment Enterprise Architecture (eGEA). Since eGovt is IT oriented multifaceted service-centric system, EA doesn’t do much on an automated enterprise other than the business artifacts. Service-Oriented Architecture (SOA) manifestation led some governments to pertain this in their eGovts, but it limits the source of business artifacts. The concurrent use of EA and SOA in eGovt executes interoperability and integration and leads to Service-Oriented e-Government Enterprise (SOeGE). Consequently, agile eGovt system becomes a reality. As an IT perspective eGovt comprises of centralized public service artifacts with the existing application logics belong to various departments at central, state and local level. The eGovt is renovating to SOeGE by apply the Service-Orientation (SO) principles in the entire system. This paper explores IT perspective of SOeGE in India which encompasses the public service models and illustrated with a case study the Passport service of India.

Keywords: enterprise architecture, service-oriented e-Government enterprise, service interface layer, service model

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Authors: R. L. Ujjwal, Abhishek Jain

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In the field of computer vision, most facial variations such as identity, expression, emotions and gender have been extensively studied. Automatic age estimation has been rarely explored. With age progression of a human, the features of the face changes. This paper is providing a new comparable study of different type of algorithm to feature extraction [Hybrid features using HAAR cascade & HOG features] & classification [KNN & SVM] training dataset. By using these algorithms we are trying to find out one of the best classification algorithms. Same thing we have done on the feature selection part, we extract the feature by using HAAR cascade and HOG. This work will be done in context of age group classification model.

Keywords: computer vision, age group, face detection

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Authors: Halit Arslan, Ismail Sahin, Ahmet Oguz Akturk, Ismail Celik

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Today, the means of following the developments in the area of science and technology is to keep up with the pace of the advancements in this area. As is in every profession, apart from their personal efforts, the training of teachers in the period after they start their careers is only possible through in-service training. The aim of the present study is to determine the views of Information Technologies (IT) teachers regarding the in-service training courses organized by the Ministry of National Education. In this study, in which quantitative research methods and techniques were employed, the views of 196 IT teachers were collected by using the “Views on In-service Training” questionnaire developed by the authors of the paper. Independent groups t-test was used to determine whether the views of IT teachers regarding in-service training differed depending on gender, age and professional seniority. One-way analysis of variance (ANOVA) was used to investigate whether the views of IT teachers regarding in-service training differed depending on the number of in-service training courses they joined and the type of in-service training course they wanted to take. According to the findings obtained in the study, the views of IT teachers on in-service training did not show a significant difference depending on gender and age, whereas those views differed depending on professional seniority, the number of in-service training courses they joined and the type of in-service training course they wanted to take.

Keywords: in-service training, IT teachers, professional development, personal development

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Authors: Khunsa Fatima, Umar K. Khattak, Allah Bakhsh Kausar

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Satellite images interpretation and analysis assist geologists by providing valuable information about geology and minerals of an area to be surveyed. A test site in Fatejang of district Attock has been studied using Landsat ETM+ and ASTER satellite images for lithological mapping. Five different supervised image classification techniques namely maximum likelihood, parallelepiped, minimum distance to mean, mahalanobis distance and spectral angle mapper have been performed on both satellite data images to find out the suitable classification technique for lithological mapping in the study area. Results of these five image classification techniques were compared with the geological map produced by Geological Survey of Pakistan. The result of maximum likelihood classification technique applied on ASTER satellite image has the highest correlation of 0.66 with the geological map. Field observations and XRD spectra of field samples also verified the results. A lithological map was then prepared based on the maximum likelihood classification of ASTER satellite image.

Keywords: ASTER, Landsat-ETM+, satellite, image classification

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Authors: Hamid Reza Nikkhah, Abbas Toloei Eshlaghi, Hossein Ali Momeni

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One of the most important services of Knowledge Management Systems (KMS) is collaboration service which plays a decisive role in organization efficiency. Cloud computing as one of the latest IT technologies has brought a new paradigm in delivering services and communications. In this research, we evaluate the impact of cloud computing on the collaboration service of KMS and for doing so, four variables of cloud computing and three variables of the collaboration service were detected to be assessed.It was found that cloud computing has a far-fetching direct impact on the collaboration service.

Keywords: cloud computing, collaboration service, knowledge management systems, cloud computing

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Authors: Chaoren Lu

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Public policy is playing as one driving force that influencing service innovation implementation in public sector. However, public policy implications cannot be automatically derived from the analyses of innovation issues, and there lacks of researches about the influences of public policy onto innovation. Moreover, innovation in service system is hard to predictable and whether policy encourages or hidden innovation is still lack of study. Especially, by given the context that multiple actors are active involving within the service delivery process in public transport sector, the complex driving forces and challenges are emerged towards the service operation. This study is aim to analysis the service innovation practices within service operating organizations to understand the drivers and challenges of service operation based on policy requirements, and where the innovation idea generating from. The case studies of Changzhou Transit Group and Nanjing Jiangnan Public Transit Group will be launched. This paper reveals the ambidexterity between top-down and bottom-up demands within the public transport service operating organizations contribute to the innovation ideas. Meanwhile, it contributes to the understanding of fundamental elements of service innovation is the new relationship creation and new way of sharing knowledge. The policy contributes to the trigger of creation of such relationship. The research question is: what are the sources of service innovation practices in local public transport system in China in in facing the policy implementation?

Keywords: public value, service innovation, public transport service, China

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Authors: Saed Khawaldeh, Mohamed Elsharnouby, Alaa Eddin Alchalabi, Usama Pervaiz, Tajwar Aleef, Vu Hoang Minh

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Taxonomic classification has a wide-range of applications such as finding out more about the evolutionary history of organisms that can be done by making a comparison between species living now and species that lived in the past. This comparison can be made using different kinds of extracted species’ data which include DNA sequences. Compared to the estimated number of the organisms that nature harbours, humanity does not have a thorough comprehension of which specific species they all belong to, in spite of the significant development of science and scientific knowledge over many years. One of the methods that can be applied to extract information out of the study of organisms in this regard is to use the DNA sequence of a living organism as a marker, thus making it available to classify it into a taxonomy. The classification of living organisms can be done in many machine learning techniques including Neural Networks (NNs). In this study, DNA sequences classification is performed using Convolutional Neural Networks (CNNs) which is a special type of NNs.

Keywords: deep networks, convolutional neural networks, taxonomic classification, DNA sequences classification

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Authors: E. Vazquez-Santacruz, M. Gamboa-Zuniga

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In this paper, we show a methodology for bodies classification in lying state using HOG descriptors and pressures sensors positioned in a matrix form (14 x 32 sensors) on the surface where bodies lie down. it will be done in real time. Our system is embedded in a care robot that can assist the elderly patient and medical staff around to get a better quality of life in and out of hospitals. Due to current technology a limited number of sensors is used, wich results in low-resolution data array, that will be used as image of 14 x 32 pixels. Our work considers the problem of human posture classification with few information (sensors), applying digital process to expand the original data of the sensors and so get more significant data for the classification, however, this is done with low-cost algorithms to ensure the real-time execution.

Keywords: real-time classification, sensors, robots, health care, elderly patients, artificial intelligence

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Authors: Vahid Bairami Rad

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With the rapid growth of the Internet and the globalization of the market, most enterprises are trying to attract and win customers in the highly competitive electronic market. Better e-service quality will enhance the relationship with customers and their satisfaction. So the measurement of eservice quality is very important but it is a complex process due to the complex nature of services. Literature predicts that there is a lack of universal definition of e-service quality. The e-service quality measures in banking have great importance in achieving high customer base. This paper proposes a conceptual model for measuring e-service quality in Iranian Banking Iran. Nine dimensions reliability, ease of use, personalization, security and trust, website aesthetic, responsiveness, contact and speed of delivery had been identified. The results of this paper may help to develop a proper scale to measure the e-service quality in Iranian Banking Industry, which may assist to maintain and improve the performance and effectiveness of e-service quality to retain customers.

Keywords: electronic banking, Dimensions, customer service quality, electronic, communication

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Authors: Kat Jingjing Luo

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The development of theme parks in China has been through a rapid growth in the past decades. Increasing competition within service quality has forced theme park managers concerned the relationship between service quality and visitors’ satisfaction. Even though those existing service quality measurements such as SERVQUAL and THEMEQUAL have been applied in related researches, none of them is exclusive for Chinese theme park service quality. This study aims to investigate the service quality of the most popular theme park in China currently and develop a unique, reliable and valid scale. The reliability and validity analysis results from a survey of over 200 tourists in Chimelong ocean kingdom in Zhuhai city, south of China, indicate that the dimension of waiting time is a discover factor in the measurement of Chinese theme park service quality excluding in the THEMEQUAL instrument (i.e., tangibles, reliability, responsiveness and access, assurance, empathy and courtesy). The newly developed scale gives a better understand service quality in Chinese theme park industry, and the managerial implications in regard to the research, how to improve theme park service quality are discussed.

Keywords: theme park, scale development, China, service quality

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Authors: Taghreed Abu-Salim

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This paper develops and investigates a framework for the assessment of customer involvement in the service design process of result oriented product-service systems in order to improve the service offering in a business to business (B2B) context. The framework comprises five main criteria and fifteen sub-criteria that contribute to customer involvement in a hierarchy using a maturity grid to highlight the strengths and weaknesses for each criterion. To develop the customer involvement framework, an extensive literature review related to service design, result oriented product-service system (PSS) and customer involvement in service design was carried out. Key factors that significantly influence customer involvement from industry and literature were identified to develop an initial framework. This framework was tested in six companies from four different sectors of industry: district cooling, medical equipment, transportation and oil storage. Validation of the framework was carried out using expert opinions and industrial case studies. A major contribution of the developed framework includes a hierarchy of appropriate criteria for assessing customer involvement in the service design process within results oriented PSS; the definition of four maturity levels which are suitable to describe the whole spectrum of customer involvement in the service design process; and finally, The paper concludes by enabling service providers to: take proactive decisions; screen and evaluate new services; improve perceived service quality; and provide barriers against imitation.

Keywords: customer involvement, maturity grid, new service development, result oriented product-service system, service design

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Authors: Shuge Lei, Haonan Hu, Dasheng Sun, Huabin Zhang, Kehong Yuan, Jian Dai, Yan Tong

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It remains challenging to measure reliability from classification results from different machine learning models. This paper proposes a reliable soup optimization algorithm based on the model weight fusion algorithm Model Soup, aiming to improve reliability by using dual-channel reliability as the objective function to fuse a series of weights in the breast ultrasound classification models. Experimental results on breast ultrasound clinical datasets demonstrate that reliable soup significantly enhances the reliability of breast ultrasound image classification tasks. The effectiveness of the proposed approach was verified via multicenter trials. The results from five centers indicate that the reliability optimization algorithm can enhance the reliability of the breast ultrasound image classification model and exhibit low multicenter correlation.

Keywords: breast ultrasound image classification, feature attribution, reliability assessment, reliability optimization

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Authors: Fahd Sabry Esmail, M. Badr Senousy, Mohamed Ragaie

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In recent years, there has been an explosion in the rate of using technology that help discovering the diseases. For example, DNA microarrays allow us for the first time to obtain a "global" view of the cell. It has great potential to provide accurate medical diagnosis, to help in finding the right treatment and cure for many diseases. Various classification algorithms can be applied on such micro-array datasets to devise methods that can predict the occurrence of Leukemia disease. In this study, we compared the classification accuracy and response time among eleven decision tree methods and six rule classifier methods using five performance criteria. The experiment results show that the performance of Random Tree is producing better result. Also it takes lowest time to build model in tree classifier. The classification rules algorithms such as nearest- neighbor-like algorithm (NNge) is the best algorithm due to the high accuracy and it takes lowest time to build model in classification.

Keywords: data mining, classification techniques, decision tree, classification rule, leukemia diseases, microarray data

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Authors: Yutae Lee

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This paper considers a discrete-time bulk-arrival bulkservice queueing system, where service capacity varies depending on the previous service time. By using the generating function technique and the supplementary variable method, we compute the distributions of the queue length at an arbitrary slot boundary and a departure time.

Keywords: discrete-time queue, bulk queue, variable service capacity, queue length distribution

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