Search results for: service classification

Authors: Imam Asrowardi, Septafiansyah Dwi Putra, Eko Subyantoro

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Process assessments can improve IT service management system (IT SMS) processes but the assessment method is not always transparent. This paper outlines a project to develop a solution- mediated process assessment tool to enable transparent and objective SMS process assessment. Using the international standards for SMS and process assessment, the tool is being developed following the International standard approach in collaboration and evaluate by expert judgment from committee members and ITSM practitioners.

Keywords: SMS, tools evaluation, ITIL, ISO service

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Authors: Kemal Polat

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In this study, it has been estimated whether there is skin by using RBG values obtained from the camera and k-nearest neighbor (k-NN) classifier. The dataset used in this study has an unbalanced distribution and a linearly non-separable structure. This problem can also be called a big data problem. The Skin dataset was taken from UCI machine learning repository. As the classifier, we have used the k-NN method to handle this big data problem. For k value of k-NN classifier, we have used as 1. To train and test the k-NN classifier, 50-50% training-testing partition has been used. As the performance metrics, TP rate, FP Rate, Precision, recall, f-measure and AUC values have been used to evaluate the performance of k-NN classifier. These obtained results are as follows: 0.999, 0.001, 0.999, 0.999, 0.999, and 1,00. As can be seen from the obtained results, this proposed method could be used to predict whether the image is skin or not.

Keywords: k-NN classifier, skin or non-skin classification, RGB values, classification

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Authors: Amna Khan, Zareena Kausar, Saad Malik

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Bio Mechatronics has extended applications in the field of rehabilitation. It has been contributing since World War II in improving the applicability of prosthesis and assistive devices in real life scenarios. In this paper, classification accuracies have been compared for two classifiers against five positions of elbow. Electromyography (EMG) signals analysis have been acquired directly from skeletal muscles of human forearm for each of the three defined positions and at modified extreme positions of elbow flexion and extension using 8 electrode Myo armband sensor. Features were extracted from filtered EMG signals for each position. Performance of two classifiers, support vector machine (SVM) and linear discriminant analysis (LDA) has been compared by analyzing the classification accuracies. SVM illustrated classification accuracies between 90-96%, in contrast to 84-87% depicted by LDA for five defined positions of elbow keeping the number of samples and selected feature the same for both SVM and LDA.

Keywords: classification accuracies, electromyography, linear discriminant analysis (LDA), Myo armband sensor, support vector machine (SVM)

Procedia PDF Downloads 339

Authors: Payel Datta, Abhishek Das, Abhishek Roychoudhury, Dhiman Chattopadhyay, Tanushyam Chattopadhyay

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Machine learning (ML) and deep learning (DL) is most predominantly used in image/video processing, natural language processing (NLP), audio and speech recognition but not that much used in system performance evaluation. In this paper, authors are going to describe the architecture of an abstraction layer constructed using ML/DL to detect the system failure. This proposed system is used to detect the system failure by evaluating the performance metrics of an IoT service deployment under constrained infrastructure environment. This system has been tested on the manually annotated data set containing different metrics of the system, like number of threads, throughput, average response time, CPU usage, memory usage, network input/output captured in different hardware environments like edge (atom based gateway) and cloud (AWS EC2). The main challenge of developing such system is that the accuracy of classification should be 100% as the error in the system has an impact on the degradation of the service performance and thus consequently affect the reliability and high availability which is mandatory for an IoT system. Proposed ML/DL classifiers work with 100% accuracy for the data set of nearly 4,000 samples captured within the organization.

Keywords: machine learning, system performance, performance metrics, IoT, edge

Procedia PDF Downloads 171

Authors: P. S. Jagadeesh Kumar, Tracy Lin Huan, S. Meenakshi Sundaram

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Alzheimer’s disease is one of the prevalent kind of ailment, expected for impudent reconciliation or an effectual therapy is to be accredited hitherto. Probable detonation of patients in the upcoming years, and consequently an enormous deal of apprehension in early discovery of the disorder, this will conceivably chaperon to enhanced healing outcomes. Complex impetuosity of the brain is an observant symbolic of the disease and a unique recognition of genetic sign of the disease. Machine learning alongside deep learning and decision tree reinforces the aptitude to absorb characteristics from multi-dimensional data’s and thus simplifies automatic classification of Alzheimer’s disease. Susceptible testing was prophesied and realized in training the prospect of Alzheimer’s disease classification built on machine learning advances. It was shrewd that the decision trees trained with deep neural network fashioned the excellent results parallel to related pattern classification.

Keywords: Alzheimer's diagnosis, decision trees, deep neural network, machine learning, pattern classification

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Authors: Wanhyun Cho, Soonja Kang, Sanggoon Kim, Soonyoung Park

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We present probabilistic multinomial Dirichlet classification model for multidimensional data and Gaussian process priors. Here, we have considered an efficient computational method that can be used to obtain the approximate posteriors for latent variables and parameters needed to define the multiclass Gaussian process classification model. We first investigated the process of inducing a posterior distribution for various parameters and latent function by using the variational Bayesian approximations and important sampling method, and next we derived a predictive distribution of latent function needed to classify new samples. The proposed model is applied to classify the synthetic multivariate dataset in order to verify the performance of our model. Experiment result shows that our model is more accurate than the other approximation methods.

Keywords: multinomial dirichlet classification model, Gaussian process priors, variational Bayesian approximation, importance sampling, approximate posterior distribution, marginal likelihood evidence

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Authors: Zhankun Wang, Timothy Makubuya

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The efficiency of public sports service of prefecture-level cities in Zhejiang from 2008 to 2012 was evaluated by applying the DEA method, then its influencing factors were also analyzed through Tobit model. Upon analysis, the results revealed the following; (i) the change in average efficiency of public sports service in Zhejiang present a smooth uptrend and at a relatively high level from 2008 to 2012 (ii) generally, the productivity of public sports service in Zhejiang improved from 2008 to 2012, the productivity efficiency varied greatly in different years, and the regional difference of production efficiency increased. (iii) The correlations for urbanization rate, aging rate, per capita GDP and the population density were significantly positive with the public sports service efficiency in Zhejiang, of which the most significant was the aging rate. However, the population density and per capita GDP had less impact on the efficiency of public sports service in Zhejiang. In addition, whether the efficiency of public sports services in different areas in Zhejiang reciprocates to overall benefits in public wellbeing in both rural and urban settings is still arguable.

Keywords: DEA model, public sports service, efficiency, Tobit model, Malmquist productivity index, Zhejiang

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Authors: Negin Mohammadrezaee Larki

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Cloud Computing is a popular solution that has been used in recent years to cooperate and collaborate among distributed applications over networks. Moving successfully into cloud computing requires an architecture that will support the new cloud capabilities. Many business leaders and analysts agree that moving to cloud requires having a solid, service-oriented architecture to provide the infrastructure needed for successful cloud implementation.

Keywords: Service Oriented Architecture (SOA), Service Oriented Cloud Computing Architecture (SOCCA), cloud computing, cloud computing architecture

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Authors: Garg Ramneesh, Uppal Sanjeev, Mittal Rajinder, Shah Sheerin, Jain Vikas, Singla Bhupinder

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Introduction: Despite advances in trauma care, a classification system for soft tissue injuries of the face still needs to be objectively defined. Aim: To develop a classification system for soft tissue injuries of the face; that is objective, easy to remember, reproducible, universally applicable, aids in surgical management and helps to develop a structured data that can be used for future use. Material and Methods: This classification system includes those patients that need surgical management of facial injuries. Associated underlying bony fractures have been intentionally excluded. Depending upon the severity of soft tissue injury, these can be graded from 0 to IV (O-Abrasions, I-lacerations, II-Avulsion injuries with no skin loss, III-Avulsion injuries with skin loss that would need graft or flap cover, and IV-complex injuries). Anatomically, the face has been divided into three zones (Zone 1/2/3), as per aesthetic subunits. Zone 1e stands for injury of eyebrows; Zones 2 a/b/c stand for nose, upper eyelid and lower eyelid respectively; Zones 3 a/b/c stand for upper lip, lower lip and cheek respectively. Suffices R and L stand for right or left involved side, B for presence of foreign body like glass or pellets, C for extensive contamination and D for depth which can be graded as D 1/2/3 if depth is still fat, muscle or bone respectively. I is for damage to facial nerve or parotid duct. Results and conclusions: This classification system is easy to remember, clinically applicable and would help in standardization of surgical management of soft tissue injuries of face. Certain inherent limitations of this classification system are inability to classify sutured wounds, hematomas and injuries along or against Langer’s lines.

Keywords: soft tissue injuries, face, avulsion, classification

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Authors: Kwounghee Choi

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Technological convergence between the various sectors is expected to have a very large impact on future industrial and economy. This study attempts to do empirical approach between specific technologies’ classification. For technological convergence classification, it is necessary to set the target technology to be analyzed. This study selected target technology from national research and development plan. At first we found a source technology for analysis. Depending on the weight of source technology, NT-based, BT-based, IT-based, ET-based, CS-based convergence types were classified. This study aims to empirically show the concept of convergence technology and convergence types. If we use the source technology to classify convergence type, it will be useful to make practical strategies of convergence technology.

Keywords: technology convergence, source technology, convergence type, R&D strategy, technology classification

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Authors: Mariam Kutateladze

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In the twenty-first century, in the customer service settings for hospitality institution’s employee management and their well-being have become a core issue since it is linked to the customers' increased demand for high-quality service. Employees' positive attitude to customers plays an essential role in the serving process; for this reason, in the hospitality institutions service with a smile is a job requirement. This research is devoted to the issues of employee management systems improvement and its effect of the genuine smile as a positive attitude expressed by the employees to the customer. Different researchers work about the effect of the genuine smile, which is analyzed in the present paper. Based on it, the link between satisfied employees from service climate and their genuine smile is determined. An investigation in local resort hotels which are located in the regions of Georgia is conducted. In the methodology of the paper, we have used linkage research, which stated that employee satisfaction in a working place depends on the existing service climate in an organization. We have prepared questioners according to eight dimensions of good service climate by linkage research, and extra questions about the effect of the smile on customers were added. Questionnaires were distributed among employees, and the results have shown that dissatisfaction from organizations’ service climate led to employees' false smile toward customers. Demanding positive emotions from frustrated employees was the mistake of the hotel management. The false smile was easily recognized by the customers, and the frustrated employee with a false smile could not provide high-quality service. The findings of the paper will help managers to realize the importance of forming the positive service climate within the institutions since it is linked to employees' well-being who are the creators of high-quality service. The conclusion drawn from this study indicates there are core issues those managers need to take into account when planning their organizations’ profit. Managers should know their employees very well, their feelings and attitudes toward work before asking them expressing a smile since forced smile does not have a good result and quite often has bad outcomes; therefore, first of all, managers should investigate service climate in the organization. Managers should take into consideration employees’ opinions about the service climate in the organization, motivate their employees, and respect their ideas. Also, they should satisfy employees' basic needs and stress more value on extrinsic goals such as competence, relatedness, and autonomy. Managers should create a positive working environment, positive service climate, which will lead to employee satisfaction and genuine feelings, as well as improve the working environment since negative working climate will cause customers disappointment because of low-quality service provided by the unsatisfied employees.

Keywords: employee management, hotel, quality of service, service climate

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Authors: Yuen Man Yan

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Peer support has been a rising prevalent mental health service in the globe. The community-based mental health services employ persons with lived experience of mental illness to be peer support workers (PSWs) to provide peer support service to those who are in the progress of recovery (PIRs). It represents the transformation of mental health service system to a recovery-oriented and person-centered care. Literatures proved the feasibility and effectiveness of the peer support service. Researchers have attempted to explore the unique good qualities of peer support service that benefit the PIRs. Empirical researches found that the strength of the relationship between those who sought for change and the change agents positively related to the outcomes in one-to-one therapies across theoretical orientations. However, there is lack of literature on investigating the relationship building between the PSWs and PIRs in the one-to-one community-based peer support service. This study aims to identify and characterise the relationship in the community-based one-to-one peer support service from the perspectives of PSWs and PIRs; and to conceptualize the components of relationship building between PSWs and PIRs in the community-based one-to-one peer support service. The study adopted the constructivist grounded theory approach. 10 pairs of the PSWs and PIRs participated in the study. Data were collected through multiple qualitative methods, including observation of the interaction and exchange of the PSWs and PIRs in the 1ₛₜ, 3ᵣ𝒹 and 9th sessions of the community-based one-to-one peer support service; and semi-structural interview with the PSWs and PIRs separately after the 3ᵣ𝒹and 9ₜₕ session of the peer support service. This presentation is going to report the preliminary findings of the study. PSWs and PIRs identified their relationship as “life alliance”. Empathy was found to be one of key components of the relationship between the PSWs and the PIRs. Unlike the empathy, as explained by Carl Roger, in which the service provider was able to put themselves into the shoes of the service recipients as if he was the service recipients, the intensity of the empathy was much greater in the relationship between PSWs and PIRs because PSWs had the lived experience of mental illness and recovery. The dimensions of the empathy in the relationship between PSWs and PIRs was found to be multiple, not only related to the mental illness but also related to various aspects in life, like family relationship, employment, interest of life, self-esteem and etc.

Keywords: person with lived experience, peer support worker, peer support service, relationship building, therapeutic alliance, community-based mental health setting

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Authors: H. Zidoum, A. AlShareedah, S. Al Sawafi, A. Al-Ansari, B. Al Lawati

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Systemic lupus erythematosus (SLE) is an autoimmune disease with genetic and environmental components. SLE is characterized by a wide variability of clinical manifestations and a course frequently subject to unpredictable flares. Despite recent progress in classification tools, the early diagnosis of SLE is still an unmet need for many patients. This study proposes an interpretable disease classification model that combines the high and efficient predictive performance of CatBoost and the model-agnostic interpretation tools of Shapley Additive exPlanations (SHAP). The CatBoost model was trained on a local cohort of 219 Omani patients with SLE as well as other control diseases. Furthermore, the SHAP library was used to generate individual explanations of the model's decisions as well as rank clinical features by contribution. Overall, we achieved an AUC score of 0.945, F1-score of 0.92 and identified four clinical features (alopecia, renal disorders, cutaneous lupus, and hemolytic anemia) along with the patient's age that was shown to have the greatest contribution on the prediction.

Keywords: feature selection, classification, systemic lupus erythematosus, model interpretation, SHAP, Catboost

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Authors: Qiu Jian-Rong, Li Qing-Hui, Zhan Dong, Zhang Lei

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Facing the problem of the demand of economic restructuring and risk of social economy stagnation due to the ageing of population, the Health Service Industry will play a very important role in the structure of industry in the future. During the process, the orient of Chinese sports medicine as well as the joint with preventive medicine, and the integration with data bank and cloud computing will be involved.

Keywords: China, the health service industry, mass sport, data bank

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Authors: Hanan Alshaher, Jinsheng Xu

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Large amounts of data on the web can provide valuable information. For example, product reviews help business owners measure customer satisfaction. Sentiment analysis classifies texts into two polarities: positive and negative. This paper examines movie reviews and tweets using a new term weighting scheme, called one-over-sigma (1/sigma), on benchmark datasets for sentiment classification. The proposed method aims to improve the performance of sentiment classification. The results show that 1/sigma is more accurate than the popular term weighting schemes. In order to verify if the entropy reflects the discriminating power of terms, we report a comparison of entropy values for different term weighting schemes.

Keywords: 1/sigma, natural language processing, sentiment analysis, term weighting scheme, text classification

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Authors: Inseok Yeo, Tae-Ho Song

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To practically apply vacuum insulation panels (VIPs) to buildings or home appliances, VIPs have demanded long-term lifespan with outstanding insulation performance. Service lives of VIPs enveloped with Al-foil and three-layer Al-metallized envelope are calculated. For Al-foil envelope, the service life is longer but edge conduction is too large compared with the Al metallized envelope. To increase service life even more, the proposed double enveloping method and metal-barrier-added enveloping method are further analyzed. The service lives of the VIP to employ two enveloping methods are calculated. Also, pressure increase and thermal insulation performance characteristics are investigated. For the metal- barrier-added enveloping method, effective thermal conductivity increase with time is close to that of Al-foil envelope, especially, for getter-inserted VIPs. For the double enveloping method, if water vapor is perfectly adsorbed, the effect of service life enhancement becomes much greater. From these methods, the VIP can be guaranteed for the service life of more than 20 years.

Keywords: vacuum insulation panels, service life, double enveloping, metal-barrier-added enveloping, edge conduction

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Authors: Fuad M. Alkoot

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Different experimental technologies such as microarray sequencing have been proposed to generate high-resolution genetic data, in order to understand the complex dynamic interactions between complex diseases and the biological system components of genes and gene products. However, the generated samples have a very large dimension reaching thousands. Therefore, hindering all attempts to design a classifier system that can identify diseases based on such data. Additionally, the high overlap in the class distributions makes the task more difficult. The data we experiment with is generated for the identification of autism. It includes 142 samples, which is small compared to the large dimension of the data. The classifier systems trained on this data yield very low classification rates that are almost equivalent to a guess. We aim at reducing the data dimension and improve it for classification. Here, we experiment with applying a multistage PCA on the genetic data to reduce its dimensionality. Results show a significant improvement in the classification rates which increases the possibility of building an automated system for autism detection.

Keywords: PCA, gene expression, dimensionality reduction, classification, autism

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Authors: Daniela Stephanie Kuenstle

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Complex industries such as banking or insurance experience slow growth in mobile sales. While today’s mobile applications are sophisticated and enable location based and personalized services, consumers prefer online or even face-to-face services to complete complex transactions. A possible reason for this reluctance is that the provided service within transactional mobile applications (apps) does not adequately correspond to users’ needs. Therefore, this paper examines the impact of the user context on mobile service (m-service) in m-commerce. Motivated by the potential which context-sensitive m-services hold for the future, the impact of temporal variations as a dimension of user context, on m-service design is examined. In particular, the research question asks: Does consumer urgency function as a determinant of m-service composition in transactional apps by moderating the relation between m-service type and m-service success? Thus, the aim is to explore the moderating influence of urgency on m-service types, which includes Technology Mediated Service and Technology Generated Service. While mobile applications generally comprise features of both service types, this thesis discusses whether unexpected urgency changes customer preferences for m-service types and how this consequently impacts the overall m-service success, represented by purchase intention, loyalty intention and service quality. An online experiment with a random sample of N=1311 participants was conducted. Participants were divided into four treatment groups varying in m-service types and urgency level. They were exposed to two different urgency scenarios (high/ low) and two different app versions conveying either technology mediated or technology generated service. Subsequently, participants completed a questionnaire to measure the effectiveness of the manipulation as well as the dependent variables. The research model was tested for direct and moderating effects of m-service type and urgency on m-service success. Three two-way analyses of variance confirmed the significance of main effects, but demonstrated no significant moderation of urgency on m-service types. The analysis of the gathered data did not confirm a moderating effect of urgency between m-service type and service success. Yet, the findings propose an additive effects model with the highest purchase and loyalty intention for Technology Generated Service and high urgency, while Technology Mediated Service and low urgency demonstrate the strongest effect for service quality. The results also indicate an antagonistic relation between service quality and purchase intention depending on the level of urgency. Although a confirmation of the significance of this finding is required, it suggests that only service convenience, as one dimension of mobile service quality, delivers conditional value under high urgency. This suggests a curvilinear pattern of service quality in e-commerce. Overall, the paper illustrates the complex interplay of technology, user variables, and service design. With this, it contributes to a finer-grained understanding of the relation between m-service design and situation dependency. Moreover, the importance of delivering situational value with apps depending on user context is emphasized. Finally, the present study raises the demand to continue researching the impact of situational variables on m-service design in order to develop more sophisticated m-services.

Keywords: mobile consumer behavior, mobile service design, mobile service success, self-service technology, situation dependency, user-context sensitivity

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Authors: Abobaker Mohammed Qasem Farhan, Shangming Yang, Mohammed Al-Nehari

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Pneumonia is a kind of lung disease that creates congestion in the chest. Such pneumonic conditions lead to loss of life of the severity of high congestion. Pneumonic lung disease is caused by viral pneumonia, bacterial pneumonia, or Covidi-19 induced pneumonia. The early prediction and classification of such lung diseases help to reduce the mortality rate. We propose the automatic Computer-Aided Diagnosis (CAD) system in this paper using the deep learning approach. The proposed CAD system takes input from raw computerized tomography (CT) scans of the patient's chest and automatically predicts disease classification. We designed the Hybrid Deep Learning Algorithm (HDLA) to improve accuracy and reduce processing requirements. The raw CT scans have pre-processed first to enhance their quality for further analysis. We then applied a hybrid model that consists of automatic feature extraction and classification. We propose the robust 2D Convolutional Neural Network (CNN) model to extract the automatic features from the pre-processed CT image. This CNN model assures feature learning with extremely effective 1D feature extraction for each input CT image. The outcome of the 2D CNN model is then normalized using the Min-Max technique. The second step of the proposed hybrid model is related to training and classification using different classifiers. The simulation outcomes using the publically available dataset prove the robustness and efficiency of the proposed model compared to state-of-art algorithms.

Keywords: CT scan, Covid-19, deep learning, image processing, lung disease classification

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Authors: M. Pramila Devi, J. Praveena

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In today’s industrial scenario, the expectations and demand of customers are reaching great heights. In order to satisfy the customer requirements the users are increasingly turning towards fourth party logistics (4PL) service providers to manage their total supply chain operations. In this present research, initially, the criteria for the selection of integrated service providers have been identified and an integrated modal based on their inter-relationship has been developed with help of shippers, with this idea of what factors to be considered and their inter-relationships while selecting integrated service provider. Later, various methods deriving the priority weights viz. Analytical Hierarchy Process (AHP) have been employed for 4PL service provider selection. The derived priorities of 4PL alternatives using methods have been critically analyzed and compared for effective selection. The use of the modal indicates that the computed quantitative evaluation can be applied to improve the precision of the selection.

Keywords: analytical hierarchy process, fourth party logistics, priority weight, criteria selection

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Authors: Hassan Baji, Chun-Qing Li, Wei Yang

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Water seepage is one of the most common causes of damage in tunnel structures, which can cause direct and indirect e.g. reinforcement corrosion and calcium leaching damages. Estimation of water seepage or inflow is one of the main challenges in probabilistic assessment of tunnels. The methodology proposed in this study is an attempt for mathematically modeling the water seepage in tunnel structures and further predicting its service life. Using the time-dependent reliability, water seepage is formulated as a failure mode, which can be used for prediction of service life. Application of the formulated seepage failure mode to a case study tunnel is presented.

Keywords: water seepage, tunnels, time-dependent reliability, service life

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Authors: Sakapas Saengchai

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This research has objective to study and analysis, expending linkage of trading border of Thai-Myanmar and the way of development trading of Thai-Myanmar border. There are advantage of competition in ASEAN Community on collection data and observation, in-depth interview, group conversation and exchange opinion of public agency, entrepreneur and people. Result of study found that main development of border trade is 1) Cross-border service should be development infrastructure of land telecommunication, sea has support economics of cross-border trade, 2) International consumption service should be expand service with Myanmar and India for linkage with entrepreneur and trading from international to Thailand, 3) Establish business for provide service has development cooperation of logistics via Andaman of Thailand, and 4) Mobility personnel, exchange personnel including labor for development potential of border trade has competition advantage.

Keywords: border trade, development, service, ASEAN

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Authors: Ayadi Aya, Ghorbel Oussama, M. Obeid Abdulfattah, Abid Mohamed

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Nowadays, many wireless sensor networks have been distributed in the real world to collect valuable raw sensed data. The challenge is to extract high-level knowledge from this huge amount of data. However, the identification of outliers can lead to the discovery of useful and meaningful knowledge. In the field of wireless sensor networks, an outlier is defined as a measurement that deviates from the normal behavior of sensed data. Many detection techniques of outliers in WSNs have been extensively studied in the past decade and have focused on classic based algorithms. These techniques identify outlier in the real transaction dataset. This survey aims at providing a structured and comprehensive overview of the existing researches on classification based outlier detection techniques as applicable to WSNs. Thus, we have identified key hypotheses, which are used by these approaches to differentiate between normal and outlier behavior. In addition, this paper tries to provide an easier and a succinct understanding of the classification based techniques. Furthermore, we identified the advantages and disadvantages of different classification based techniques and we presented a comparative guide with useful paradigms for promoting outliers detection research in various WSN applications and suggested further opportunities for future research.

Keywords: bayesian networks, classification-based approaches, KPCA, neural networks, one-class SVM, outlier detection, wireless sensor networks

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Authors: H. Emari, Z. Emari

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The main objective of this research was to determine the dimensions of service quality in the banking industry of Iran. For this purpose, the study empirically examined the European perspective suggesting that service quality consists of three dimensions, technical, functional and image. This research is an applied research and its strategy is casual strategy. A standard questionnaire was used for collecting the data. 287 customers of Melli Bank of Northwest were selected through cluster sampling and were studied. The results from a banking service sample revealed that the overall service quality is influenced more by a consumer’s perception of technical quality than functional quality. Accordingly, the Gronroos model is a more appropriate representation of service quality than the American perspective with its limited concentration on the dimension of functional quality in the banking industry of Iran. So, knowing the key dimensions of the quality of services in this industry and planning for their improvement can increase the satisfaction of customers and productivity of this industry.

Keywords: technical quality, functional quality, banking, image, mediating role

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Authors: Wajeeh Daher, Nimer Baya'a

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High Order Thinking Skills (HOTS) are suggested today as essential for the cognitive development of students and as preparing them for real life skills. Teachers are encouraged to use HOTS activities in the classroom to help their students develop higher order skills and deep thinking. So it is essential to prepare pre-service teachers to write and use HOTS activities for their students. This paper describes a model for integrating HOTS activities with GeoGebra in pre-service teachers’ preparation. This model describes four aspects of HOTS activities and working with them: Activity components, preparation procedure, strategies and processes used in writing a HOTS activity and types of the HOTS activities. In addition, the paper describes the pre-service teachers' difficulties in preparing and working with HOTS activities, as well as their perceptions regarding the use of these activities and GeoGebra in the mathematics classroom. The paper also describes the contribution of a HOTS activity to pupils' learning of mathematics, where this HOTS activity was prepared and taught by one pre-service teacher.

Keywords: high order thinking skills, HOTS activities, pre-service teachers, professional development

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Authors: Ahmad Mohsin, Syda Fatima, Falak Nawaz, Aman Ullah Khan

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Selection of an appropriate architectural style is vital to the success of target web service under development. The nature of architecture design and selection for service-oriented computing applications is quite different as compared to traditional software. Web Services have complex and rigorous architectural styles to choose. Due to this, selection for accurate architectural style for web services development has become a more complex decision to be made by architects. Architectural style selection is a multi-criteria decision and demands lots of experience in service oriented computing. Decision support systems are good solutions to simplify the selection process of a particular architectural style. Our research suggests a new approach using DSS for selection of architectural styles while developing a web service to cater FRs and NFRs. Our proposed DSS helps architects to select right web service architectural pattern according to the domain and non-functional requirements. In this paper, a rule base DSS has been developed using CLIPS (C Language Integrated Production System) to support decisions using multi-criteria requirements. This DSS takes architectural characteristics, domain requirements and software architect preferences for NFRs as input for different architectural styles in use today in service-oriented computing. Weighted sum model has been applied to prioritize quality attributes and domain requirements. Scores are calculated using multiple criterions to choose the final architecture style.

Keywords: software architecture, web-service, rule-based, DSS, multi-criteria requirements, quality attributes

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Authors: Siti Aisyah binti Jumpaan

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21ˢᵗ century skills (PAK-21) integration has made its way into Malaysian curriculum when Ministry of Education introduce its implementation since 2016. This study was conducted to explore pre-service teachers’ readiness in integrating 21st century skills in the classroom via the digital storytelling (DST) method and to find gaps between theory and practice that can be integral towards pre-service teachers’ professional growth. Qualitative research method was used in this research involving six respondents who were selected using a purposive sampling method. Their response from interviews and lesson plan analysis were analysed using narrative analysis. The findings showed that pre-service teachers showed a moderate level of readiness in integrating 21st century skills using DST. Pre-service teachers demonstrated high level of preparedness in writing their lesson plan, but their interview revealed that they faced struggles in implementation due to several factors, such as lack of technology and failure to obtain students’ participation. This study further strengthens the need for specialised curriculum for pre-service teachers in teaching 21st century skills via DST.

Keywords: digital storytelling, 21ˢᵗ century skills, preservice teachers, teacher training

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Authors: Alexander Hudson, Shaogang Gong

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Structure determination is key to understanding protein function at a molecular level. Whilst significant advances have been made in predicting structure and function from amino acid sequence, researchers must still rely on expensive, time-consuming analytical methods to visualise detailed protein conformation. In this study, we demonstrate that it is possible to make accurate (≥80%) predictions of protein class and architecture from structures determined at low (>3A) resolution, using a deep convolutional neural network trained on high-resolution (≤3A) structures represented as 2D matrices. Thus, we provide proof of concept for high-speed, low-cost protein structure classification at low resolution, and a basis for extension to prediction of function. We investigate the impact of the input representation on classification performance, showing that side-chain information may not be necessary for fine-grained structure predictions. Finally, we confirm that high resolution, low-resolution and NMR-determined structures inhabit a common feature space, and thus provide a theoretical foundation for boosting with single-image super-resolution.

Keywords: transfer learning, protein distance maps, protein structure classification, neural networks

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Authors: T. M. Al Muhareb

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Any organization should take into consideration the customers’ satisfaction while providing any service to their customers. The quality of services is always considered as the main aspect that attracts the customers’ attention and helps the airports to develop their services and operations. King Khalid International Airport is considered as the gateway of the Kingdom of Saudi Arabia. Therefore, the aim of this paper was to identify the quality service in the departure area at in King Khalid Airport. The SERVQUAL questionnaire was distributed among the passengers in King Khalid International Airport and the respondents have reached to 500 passengers. The results that are obtained from the SERVQUAL questionnaire showed that the quality of airport’s services is low.

Keywords: service quality, SERVQUAL methodology, King Khalid International Airport (KKIA), customers’ satisfaction

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Authors: Liya Shan, Qing Liao, Qinyue Hu, Shantao Jiang, Tao Wang

Abstract:

In this paper, a Quality of Experience (QoE)-driven cross-layer resource allocation scheme for high traffic service over Open Wireless Network (OWN) downlink is proposed, and the related problem about the users in the whole cell including the users in overlap region of different cells has been solved.A method, in which assess models of the BestEffort service and the no-reference assess algorithm for video service are adopted, to calculate the Mean Opinion Score (MOS) value for high traffic service has been introduced. The cross-layer architecture considers the parameters in application layer, media access control layer and physical layer jointly. Based on this architecture and the MOS value, the Binary Constrained Particle Swarm Optimization (B_CPSO) algorithm is used to solve the cross-layer resource allocation problem. In addition,simulationresults show that the proposed scheme significantly outperforms other schemes in terms of maximizing average users’ MOS value for the whole system as well as maintaining fairness among users.

Keywords: high traffic service, cross-layer resource allocation, QoE, B_CPSO, OWN

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