Search results for: industry clustering

Authors: Orestis Κ. Efthymiou, Stavros T. Ponis

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In the last decade, a new industrial revolution seems to be emerging, supported -once again- by the rapid advancements of Information Technology in the areas of Machine-to-Machine (M2M) communication permitting large numbers of intelligent devices, e.g. sensors to communicate with each other and take decisions without any or minimum indirect human intervention. The advent of these technologies have triggered the emergence of a new category of hybrid (cyber-physical) manufacturing systems, combining advanced manufacturing techniques with innovative M2M applications based on the Internet of Things (IoT), under the umbrella term Industry 4.0. Even though the topic of Industry 4.0 has attracted much attention during the last few years, the attempts of providing a systematic literature review of the subject are scarce. In this paper, we present the authors’ initial study of the field with a special focus on the use and applications of Industry 4.0 principles in material handling automations and in-house logistics. Research shows that despite the vivid discussion and attractiveness of the subject, there are still many challenges and issues that have to be addressed before Industry 4.0 becomes standardized and widely applicable.

Keywords: Industry 4.0, internet of things, manufacturing systems, material handling, logistics

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Authors: Muntadher Sallal, Gareth Owenson, Mo Adda, Safa Shubbar

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Bitcoin is a digital currency based on a peer-to-peer network to propagate and verify transactions. Bitcoin is gaining wider adoption than any previous crypto-currency. However, the mechanism of peers randomly choosing logical neighbors without any knowledge about underlying physical topology can cause a delay overhead in information propagation, which makes the system vulnerable to double-spend attacks. Aiming at alleviating the propagation delay problem, this paper introduces proximity-aware extensions to the current Bitcoin protocol, named Master Node Based Clustering (MNBC). The ultimate purpose of the proposed protocol, that are based on how clusters are formulated and how nodes can define their membership, is to improve the information propagation delay in the Bitcoin network. In MNBC protocol, physical internet connectivity increases, as well as the number of hops between nodes, decreases through assigning nodes to be responsible for maintaining clusters based on physical internet proximity. We show, through simulations, that the proposed protocol defines better clustering structures that optimize the performance of the transaction propagation over the Bitcoin protocol. The evaluation of partition attacks in the MNBC protocol, as well as the Bitcoin network, was done in this paper. Evaluation results prove that even though the Bitcoin network is more resistant against the partitioning attack than the MNBC protocol, more resources are needed to be spent to split the network in the MNBC protocol, especially with a higher number of nodes.

Keywords: Bitcoin network, propagation delay, clustering, scalability

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Authors: Goksen Arik, Mihriban Korukluoglu

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Lactic acid bacteria (LAB) has been used commonly in the food industry. They can be used as natural preservatives because acidifying carried out in the medium can protect the last product against microbial spoilage. Besides, other metabolites produced by LAB during fermentation period have also an antimicrobial effect on pathogen and spoilage microorganisms in the food industry. LAB are responsible for the desirable and distinctive aroma and flavour which are observed in fermented food products such as pickle, kefir, yogurt, and cheese. Various LAB strains are able to produce B-group vitamins such as folate (B11), riboflavin (B2) and cobalamin (B12). Especially wild-type strains of LAB can produce B-group vitamins in high concentrations. These cultures may be used in food industry as a starter culture and also the microbial strains can be used in encapsulation technology for new and functional food product development. This review is based on the current applications of B-group vitamin producing LAB. Furthermore, the new technologies and innovative researches about B vitamin production in LAB have been demonstrated and discussed for determining their usage availability in various area in the food industry.

Keywords: B vitamin, food industry, lactic acid bacteria, starter culture, technology

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Authors: Rimma Dzhusupova, Jan Bosch, Helena Holmström Olsson

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Artificial Intelligence (AI) in the Engineering, Procurement, and Construction (EPC) industry has not yet a proven track record in large-scale projects. Since AI solutions for industrial applications became available only recently, deployment experience and lessons learned are still to be built up. Nevertheless, AI has become an attractive technology for organizations looking to automate repetitive tasks to reduce manual work. Meanwhile, the current AI market has started offering various solutions and services. The contribution of this research is that we explore in detail the challenges and obstacles faced in developing and deploying AI in a large-scale project in the EPC industry based on real-life use cases performed in an EPC company. Those identified challenges are not linked to a specific technology or a company's know-how and, therefore, are universal. The findings in this paper aim to provide feedback to academia to reduce the gap between research and practice experience. They also help reveal the hidden stones when implementing AI solutions in the industry.

Keywords: artificial intelligence, machine learning, deep learning, innovation, engineering, procurement and construction industry, AI in the EPC industry

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Authors: Pawit Mongkolprasit, Proud Arunrangsiwed

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Lately, many media organizations in Thailand have started to produce 3D animation, so the quality of personnel should be identified. As an instructor in the school of Animation and Multimedia, the researchers have to prepare the students, suitable for the need of industry. The current study used exploratory research design to establish the knowledge of about this issue, including the required qualification of employees and the potential of animation industry in Thailand. The interview sessions involved three key informants from three well-known organizations. The interview data was used to design a questionnaire for the confirmation phase. The overall results showed that the industry needed an individual with 3D animation skill, computer graphic skills, good communication skills, a high responsibility, and an ability to finish the project on time. Moreover, it is also found that there were currently various kinds of media where 3D animation has been involved, such as films, TV variety, TV advertising, online advertising, and application on mobile device.

Keywords: 3D animation, animation industry, marketing trend, Thailand animation

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Authors: Sudawan Somjai

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The purpose of this paper was to find an appropriate outsourcing system model for the Thai electrical appliances industry. The objective was to increase competitive capability of the industry with an outsourcing system. The population for this study was the staff in the selected 10 companies in Thai electrical appliances industry located in Bangkok and the eastern part of Thailand. Data collecting techniques included in-depth interviews, focus group and storytelling techniques. The data was collected from 5 key informants from each company, making a total of 50 informants. The findings revealed that an outsourcing model would consist of important factors including outsourcing system, labor flexibility, capability of business process, manpower management efficiency, cost reduction, business risk elimination, core competency and competitiveness. Different suggestions were made as well in this research paper.

Keywords: outsourcing system, model, Thailand, electrical appliances industry

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Authors: Kayode O. Afolabi, Benson C. Iweriebor, Anthony I. Okoh, Larry C. Obi

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Porcine circovirus type 2 (PCV2) is the major etiological viral agent of porcine multisystemic wasting syndrome (PWMS) and other porcine circovirus-associated diseases (PCVAD) of great economic importance in pig industry globally. In an effort to determine the status of swine herds in the Province as regarding the ‘small but powerful’ viral pathogen; a total of 375 blood, faecal and nasal swab samples were obtained from seven pig farms (commercial and communal) in Amathole, O.R. Tambo and Chris-Hani District Municipalities of Eastern Cape Province between the year 2015 and 2016. Three hundred and thirty nine (339) samples out of the total sample were subjected to molecular screening using PCV2 specific primers by conventional polymerase chain reaction (PCR). Selected sequences were further analyzed and confirmed through genome sequencing and phylogenetic analyses. The data obtained revealed that 15.93% of the screened samples (54/339) from the swine herds of the studied areas were positive for PCV2; while the severity of occurrence of the viral pathogen as observed at farm level ranges from approximately 5.6% to 60% in the studied farms. The Majority, precisely 15 out of 17 (88%) analyzed sequences were found clustering with other PCV2b reference strains in the phylogenetic analysis. More interestingly, two other sequences obtained were also found clustering within PCV2d genogroup, which is presently another fast-spreading genotype with observable higher virulence in global swine herds. This finding confirmed the presence of this all-important viral pathogen in pigs of the region; which could result in a serious outbreak of PCVAD and huge economic loss at the instances of triggering factors if no appropriate measures are taken to curb its spread effectively.

Keywords: pigs, polymerase chain reaction, porcine circovirus type 2, South Africa

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Authors: Malmi Amadoru, Chandana Gamage

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Sri Lanka is emerging as a global IT-BPO hub topping up among the 20 global outsourcing destinations. When setting up a new venture in Sri Lanka, talent sourcing plays one of the key functions due to the rapid growth of workforce. Getting competent people with right skills for right positions leads organizations achieving its vision, mission and objectives. It also drives in earning competitive advantage over industry competitors. Thus it is crucial to scan and recruit the best employees to an organization. However there is no published information available on recruitment methods utilized in Sri Lankan software industry, as a study of this nature had not being conducted previously in Sri Lanka. The main objective of this study was to explore various talent sourcing practices exploited in Sri Lankan software industry. Also this study analyses the extent which Sri Lanka has adopted different recruitment strategies utilized in worldwide and its deviations. The research outcome is beneficial for HR professionals to identify the current trends in recruitment practices. Moreover investors who are interested in IT-BPO engagements can gain a thorough knowledge about talent sourcing techniques in Sri Lankan software industry. Finally, this research clues trending areas which can be further investigated in future.

Keywords: IT-BPO, recruitment, Sri Lanka, software industry, talent

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Authors: E. Kissi, V. K. Acheamfour, J. J. Gyimah, T. Adjei-Kumi

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Factoring accounts receivable is widely accepted as an alternative financing source and utilized in almost every industry that sells business-to-business or business-to-government. However, its patronage in the construction industry is very limited as some barriers hinder its application in the construction industry. This study aims at assessing the barriers to the use of factoring accounts receivables in the Ghanaian construction industry. The study adopted the sequential exploratory research method where structured and unstructured questionnaires were conveniently distributed to D1K1 and D2K2 construction firms in Ghana. Using the one-sample t-test and Kendall’s Coefficient of concordance data was analyzed. The most severe challenge concluded is the high cost of factoring patronage. Other critical challenges identified were low knowledge on factoring processes, inadequate access to information on factoring, and high risks involved in factoring. Hence, it is recommended that contractors should be made aware of the prospects of factoring of accounts receivables in the construction industry. This study serves as basis for further rigorous research into factoring of accounts receivables in the industry.

Keywords: barriers, contractors, factoring accounts receivables, Ghanaian, perception

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Authors: Saou Mohamed Amine

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The construction industry has been identified as a user of substantial amount of materials and energy resources that has an enormous impact on environment. The energy efficient in refurbishment project is being considered as one of the approaches to achieve sustainability in construction industry. The increasing concern for environment has made building owners and designers to incorporate the energy efficiency features into their building projects.

Keywords: construction industry, design team attributes, energy efficient performance, refurbishment projects characteristics

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Authors: Ashok V. Sutagundar, Sunilkumar S. Manvi

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Energy, delay and bandwidth are the prime issues of wireless sensor network (WSN). Energy usage optimization and efficient bandwidth utilization are important issues in WSN. Event triggered data aggregation facilitates such optimal tasks for event affected area in WSN. Reliable delivery of the critical information to sink node is also a major challenge of WSN. To tackle these issues, we propose an event driven dynamic clustering and data aggregation scheme for WSN that enhances the life time of the network by minimizing redundant data transmission. The proposed scheme operates as follows: (1) Whenever the event is triggered, event triggered node selects the cluster head. (2) Cluster head gathers data from sensor nodes within the cluster. (3) Cluster head node identifies and classifies the events out of the collected data using Bayesian classifier. (4) Aggregation of data is done using statistical method. (5) Cluster head discovers the paths to the sink node using residual energy, path distance and bandwidth. (6) If the aggregated data is critical, cluster head sends the aggregated data over the multipath for reliable data communication. (7) Otherwise aggregated data is transmitted towards sink node over the single path which is having the more bandwidth and residual energy. The performance of the scheme is validated for various WSN scenarios to evaluate the effectiveness of the proposed approach in terms of aggregation time, cluster formation time and energy consumed for aggregation.

Keywords: wireless sensor network, dynamic clustering, data aggregation, wireless communication

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Authors: Syed Sohaib Bin Hasib, Hiyam Al-Kilidar

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Meeting project deadlines is a major challenge for most construction projects. In this study, perceptions of contractors, clients, and consultants are compared relative to a list of factors derived from the review of the extant literature on project delay. 59 causes (categorized into 8 groups) of project delays were identified from the literature. A survey was devised to get insights and ranking of these factors from clients, consultants & contractors in the Australian construction industry. Findings showed that project delays in the Australian construction industry are mainly the result of skill shortages, interference in execution, and poor coordination and communication between the project stakeholders.

Keywords: construction, delay factors, time delay, australian construction industry

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Authors: Zelalem Fantahun

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Part-of-speech tagging is the process of assigning a part-of-speech or other lexical class marker to each word into naturally occurring text. Part-of-speech tagging is the most fundamental and basic task almost in all natural language processing. In natural language processing, the problem of providing large amount of manually annotated data is a knowledge acquisition bottleneck. Since, Amharic is one of under-resourced language, the availability of tagged corpus is the bottleneck problem for natural language processing especially for POS tagging. A promising direction to tackle this problem is to provide a system that does not require manually tagged data. In unsupervised learning, the learner is not provided with classifications. Unsupervised algorithms seek out similarity between pieces of data in order to determine whether they can be characterized as forming a group. This paper explicates the development of unsupervised part-of-speech tagger using K-Means clustering for Amharic language since large amount of data is produced in day-to-day activities. In the development of the tagger, the following procedures are followed. First, the unlabeled data (raw text) is divided into 10 folds and tokenization phase takes place; at this level, the raw text is chunked at sentence level and then into words. The second phase is feature extraction which includes word frequency, syntactic and morphological features of a word. The third phase is clustering. Among different clustering algorithms, K-means is selected and implemented in this study that brings group of similar words together. The fourth phase is mapping, which deals with looking at each cluster carefully and the most common tag is assigned to a group. This study finds out two features that are capable of distinguishing one part-of-speech from others these are morphological feature and positional information and show that it is possible to use unsupervised learning for Amharic POS tagging. In order to increase performance of the unsupervised part-of-speech tagger, there is a need to incorporate other features that are not included in this study, such as semantic related information. Finally, based on experimental result, the performance of the system achieves a maximum of 81% accuracy.

Keywords: POS tagging, Amharic, unsupervised learning, k-means

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Authors: Diego Saqui, José H. Saito, José R. Campos, Lúcio A. de C. Jorge

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Hyperspectral images and remote sensing are important for many applications. A problem in the use of these images is the high volume of data to be processed, stored and transferred. Dimensionality reduction techniques can be used to reduce the volume of data. In this paper, an approach to band selection based on clustering algorithms is presented. This approach allows to reduce the volume of data. The proposed structure is based on Fuzzy C-Means (or K-Means) and NWHFC algorithms. New attributes in relation to other studies in the literature, such as kurtosis and low correlation, are also considered. A comparison of the results of the approach using the Fuzzy C-Means and K-Means with different attributes is performed. The use of both algorithms show similar good results but, particularly when used attributes variance and kurtosis in the clustering process, however applicable in hyperspectral images.

Keywords: band selection, fuzzy c-means, k-means, hyperspectral image

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Authors: Rym Ghariani, Ghada Soltane, Younes Boujelbene

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Industry 4.0, a set of emerging smart and digital technologies, has been the main focus of operations management researchers and practitioners in recent years. The objective of this research paper is to study the impact of Industry 4.0 on the integration of the supply chain (SCI) in Tunisian industrial companies. A conceptual model to study the relationship between Industry 4.0 technologies and supply chain integration was designed. This model contains three explained variables (Big data, Internet of Things, and Robotics) and one variable to be explained (supply chain integration). In order to answer our research questions and investigate the research hypotheses, principal component analysis and discriminant analysis were used using SPSS26 software. The results reveal that there is a statistically positive impact significant impact of Industry 4.0 (Big data, Internet of Things and Robotics) on the integration of the supply chain. Interestingly, big data has a greater positive impact on supply chain integration than the Internet of Things and robotics.

Keywords: industry 4.0 (I4.0), big data, internet of things, robotics, supply chain integration

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Authors: P. Srinivasa Rao, K. Venkatesh Sharma, G. Sadhya Devi, V. Nagesh

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Privacy Preserving Data Publication is the main concern in present days because the data being published through the internet has been increasing day by day. This huge amount of data was named as Big Data by its size. This project deals the privacy preservation in the context of Big Data using a data warehousing solution called hive. We implemented Nearest Similarity Based Clustering (NSB) with Bottom-up generalization to achieve (v,l)-anonymity. (v,l)-Anonymity deals with the sensitivity vulnerabilities and ensures the individual privacy. We also calculate the sensitivity levels by simple comparison method using the index values, by classifying the different levels of sensitivity. The experiments were carried out on the hive environment to verify the efficiency of algorithms with Big Data. This framework also supports the execution of existing algorithms without any changes. The model in the paper outperforms than existing models.

Keywords: sensitivity, sensitive level, clustering, Privacy Preserving Data Publication (PPDP), bottom-up generalization, Big Data

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Authors: Rahul Paul, Peter Mctaggart, Luke Skinner

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Maintaining public safety and network reliability are the core objectives of all electricity distributors globally. For many electricity distributors, managing vegetation clearances from their above ground assets (poles and conductors) is the most important and costly risk mitigation control employed to meet these objectives. Light Detection And Ranging (LiDAR) is widely used by utilities as a cost-effective method to inspect their spatially-distributed assets at scale, often captured using high powered LiDAR scanners attached to fixed wing or rotary aircraft. The resulting 3D point cloud model is used by these utilities to perform engineering grade measurements that guide the prioritisation of vegetation cutting programs. Advances in computer vision and machine-learning approaches are increasingly applied to increase automation and reduce inspection costs and time; however, real-world LiDAR capture variables (e.g., aircraft speed and height) create complexity, noise, and missing data, reducing the effectiveness of these approaches. This paper proposes a method for identifying each conductor from LiDAR data via clustering methods that can precisely reconstruct conductors in complex real-world configurations in the presence of high levels of noise. It proposes 3D catenary models for individual clusters fitted to the captured LiDAR data points using a least square method. An iterative learning process is used to identify potential conductor models between pole pairs. The proposed method identifies the optimum parameters of the catenary function and then fits the LiDAR points to reconstruct the conductors.

Keywords: point cloud, LİDAR data, machine learning, computer vision, catenary curve, vegetation management, utility industry

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Authors: Azadeh Shahbazi

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This study tries to find out the determinants of capital structure in hotel industry in 7 important hotel chains in USA within the period of 12 years of 2000 to 2012. The study is used a panel pooled regression to realize the relation among different variables. Results show that the variables which could make changes in the capital structure of firms are Non-Debt Tax Shield and Tangibility.

Keywords: capital structure, service industry, hospitality, finance

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Authors: C. Pislaru, A. Shebani

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This paper uses the radial basis function neural network (RBFNN) for system identification of nonlinear systems. Five nonlinear systems are used to examine the activity of RBFNN in system modeling of nonlinear systems; the five nonlinear systems are dual tank system, single tank system, DC motor system, and two academic models. The feed forward method is considered in this work for modelling the non-linear dynamic models, where the K-Means clustering algorithm used in this paper to select the centers of radial basis function network, because it is reliable, offers fast convergence and can handle large data sets. The least mean square method is used to adjust the weights to the output layer, and Euclidean distance method used to measure the width of the Gaussian function.

Keywords: system identification, nonlinear systems, neural networks, radial basis function, K-means clustering algorithm

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Authors: Abdulkadir Adamu Shehu

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Company’s reputation is an elusive asset. The reputation gained by companies must be preserved for sustainability of the company. However, the construction project is still suffering from declination of character due to the factors that affect their reputation. The problem led to the loss of projects, abandoning of the projects and many more. This contributed to negative impact on the contractors in the construction industry. As for today, previous studies have not investigated in this regards yet. For that reason, this paper examines the factors which could promote contractor’s reputation in the construction industry in Nigeria. To achieve this aim, 140 questionnaires were distributed to the Nigerian contractors. Based on the 67% response rate, descriptive analysis and analysis of variance (ANOVA) were the tools applied for the data obtained to be analysed. The result shows that, good communication system and improve quality of output of products are the most significant variables that can promote contractor’s reputation. The homogenous analyses indicate that there are significant different perceptions of respondents in term of the significant effects. The research concluded that contractor’s reputation in construction industry must be maintained and further research was suggested to focus on the qualitative method to have in-depth knowledge on contractor’s reputation in the construction industry.

Keywords: construction industry, contractor’s reputation, effects of delay, Nigeria

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Authors: Robert Cazar, Nathaly Maza

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Energy drinks and sports drinks are quite popular among young adults and teenagers worldwide. Some concerns regarding their health effects – particularly those of the energy drinks - have been raised based on scientific findings. Differentiating between these two types of drinks by means of their chemical properties seems to be an instructive task. Chemometrics provides the most appropriate strategy to do so. In this study, a discrimination analysis of the energy and sports drinks has been carried out applying chemometric methods. A set of eleven samples of available commercial brands of drinks – seven energy drinks and four sports drinks – were collected. Each sample was characterized by eight chemical variables (carbohydrates, energy, sugar, sodium, pH, degrees Brix, density, and citric acid). The data set was standardized and examined by exploratory chemometric techniques such as clustering and principal component analysis. As a preliminary step, a variable selection was carried out by inspecting the variable correlation matrix. It was detected that some variables are redundant, so they can be safely removed, leaving only five variables that are sufficient for this analysis. They are sugar, sodium, pH, density, and citric acid. Then, a hierarchical clustering `employing the average – linkage criterion and using the Euclidian distance metrics was performed. It perfectly separates the two types of drinks since the resultant dendogram, cut at the 25% similarity level, assorts the samples in two well defined groups, one of them containing the energy drinks and the other one the sports drinks. Further assurance of the complete discrimination is provided by the principal component analysis. The projection of the data set on the first two principal components – which retain the 71% of the data information – permits to visualize the distribution of the samples in the two groups identified in the clustering stage. Since the first principal component is the discriminating one, the inspection of its loadings consents to characterize such groups. The energy drinks group possesses medium to high values of density, citric acid, and sugar. The sports drinks group, on the other hand, exhibits low values of those variables. In conclusion, the application of chemometric methods on a data set that features some chemical properties of a number of energy and sports drinks provides an accurate, dependable way to discriminate between these two types of beverages.

Keywords: chemometrics, clustering, energy drinks, principal component analysis, sports drinks

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Authors: Walid Moudani, Ahmad Shahin

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This research presents a study to handle the recruitment services system. It aims to enhance a business intelligence system by embedding data mining in its core engine and to facilitate the link between job searchers and recruiters companies. The purpose of this study is to present an intelligent management system for supporting recruitment services based on data mining methods. It consists to apply segmentation on the extracted job postings offered by the different recruiters. The details of the job postings are associated to a set of relevant features that are extracted from the web and which are based on critical criterion in order to define consistent clusters. Thereafter, we assign the job searchers to the best cluster while providing a ranking according to the job postings of the selected cluster. The performance of the proposed model used is analyzed, based on a real case study, with the clustered job postings dataset and classified job searchers dataset by using some metrics.

Keywords: job postings, job searchers, clustering, genetic algorithms, business intelligence

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Authors: Khalifa Al Baloushi, Hongwei Zhang, Terrence Perera

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Over the last few decades, the government of the UAE has been taking actions to consolidate defense manufacturing entities with the view to build a coherent and modern defense manufacturing base. Whilst these actions have significantly improved the overall capabilities of defense manufacturing; further opportunities exist to radically transform the sector. A comprehensive literature review and data collected from a survey identified three potential areas of improvements, (a) integration of Industry 4.0 technologies and other smart technologies, (b) stronger engagement of small and Medium-sized defense manufacturing companies and (c) Enhancing the national defense policies by embedding best practices from other nations. This research paper presents the design and development of a conceptual framework for the UAE defense industrial ecosystem.

Keywords: industry 4.0, defense manufacturing, eco-systems, integration

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Authors: Radhia Toujani, Jalel Akaichi

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In recent years, the study of community detection in social networks has received great attention. The hierarchical structure of the network leads to the emergence of the convergence to a locally optimal community structure. In this paper, we aim to avoid this local optimum in the introduced hybrid hierarchical method. To achieve this purpose, we present an objective function where we incorporate the value of structural and semantic similarity based modularity and a metaheuristic namely bees colonies algorithm to optimize our objective function on both hierarchical level divisive and agglomerative. In order to assess the efficiency and the accuracy of the introduced hybrid bee colony model, we perform an extensive experimental evaluation on both synthetic and real networks.

Keywords: social network, community detection, agglomerative hierarchical clustering, divisive hierarchical clustering, similarity, modularity, metaheuristic, bee colony

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Authors: Jirarat Teeravaraprug, Usawadee Inklay

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This paper gave an attempt in prioritizing information technologies that organizations should give concentration. The case study was organizations in the automotive assembly industry in Thailand. Data were first collected to gather all information technologies known and used in the automotive assembly industry in Thailand. Five experts from the industries were surveyed based on the concept of fuzzy DEMATEL. The information technologies were categorized into six groups, which were communication, transaction, planning, organization management, warehouse management, and transportation. The cause groups of information technologies for each group were analysed and presented. Moreover, the relationship between the used and the significant information technologies was given. Discussions based on the used information technologies and the research results are given.

Keywords: information technology, automotive assembly industry, fuzzy DEMATEL

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Authors: Tiantian Ma

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The district of Doumen, Zhuhai has a sophisticated seabass value chain. However, unlike typical Global Value Chain (GVC) industries, the seabass value chain in Doumen is highly domestic both in terms of production and consumption. Still, since the highly-industrialized and capital-intensive industry involves many off-farm segments in both upstream and downstream, this paper will be utilizing the method of value chain analysis. To be specific, the paper will concentrate on two research goals: 1) the value chain mapping of the seabass industry, such as identifying actors in the hatchery, fish feed, fishponds, processing, logistics, and distribution, 2) the SWOT analysis of the seabass industry in Doumen, including incompetence of the waste disposal, the strategy of marketing, and the supportive role of the government, etc. In general, the seabass industry in Doumen is a sophisticated but not yet comprehensive value chain. It has achieved a lot in industrializing aqua-food products and fostering development, but there are still improvements that could be carried out, such as upholding environmental sustainability and promoting the brand better.

Keywords: agricultural value chain, fish farming, regional development, SWOT analysis, value chain mapping

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Authors: Efe Çukur

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This study aims to discuss and compare i) widespread and generic design, particularly industrial design education in relation to the specific needs of the automotive/transportation industry, and ii) an automotive/transportation design education model within and under to provide the conditions of design education and automotive industry, especially in Turkey and T.R.N.C. The automotive industry is the 11th largest in the world ($1.51 trillion). One of the most important departments in this industry, along with sales, marketing and engineering, is the design department. The automotive industry is known as the locomotive industry, but there is a non-automotive design department on the academic side of Turkey. This suggestion; includes the presentation of a program proposal that meets the needs of the industry for Turkey and T.R.N.C., the second largest automobile manufacturing country in Europe. On the education side, industrial design education has become a generic title. Automotive design studios are divided into several subgroups. Even in the higher graduate education, the automotive design departments get their subgroups like exterior design and interior design. Transportation design, which is a subfield of industrial design, is offered as higher education in transportation design departments, particularly in America and Europe. In these departments, the curriculum is shaped to the needs of the sectors. Higher education transportation design programs began in the mid-20th century. Until those high education programs...Until these high education programs, the industry has adapted architectures and engineers for designer workloads. Still today transportation design graduates are not the majority of the design studios. The content of the study is an in-depth comparison of these institutions and how the requirements, demands of the industry are met in this regard and revealed. Some of the institutions are selected from Europe and US. To be analyzed under the headings of staff, courses, syllabus, University-Industry collaboration, and location selection. The study includes short, mid, and long term proposals and a hypothesis for discussion. In short, the study will not only provide a wide comparative scope of information on generic and specialized aspects of design education in different countries but also propose a higher education model for automotive / transportation design with solid data of requirements, methodology, and structure regarding learning outcomes, and especially industry cooperation.

Keywords: design education, automotive - transportation design programs, transportation design, automotive industry in Turkey /T.R.N.C., automotive design education in Turkey /T.R.N.C.

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Authors: Joseph Reylan Viray, Kriztine R. Viray

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Call center conversations, more than the business dimensions that they normally manifest, are interactions between human beings. These are communication exchanges that are packed with psychological, cultural and social dimensions that affect the specific experience of the parties. The increasing development of information and communication technology over the past decades brought about important advantages and corresponding disadvantages in the process of communicational transactions in call center industry. It has been established that the technology is so powerful that it strongly affects, among others, call center business. In the present study, the author explores the interplay between the technology being utilized by the industry and the cultural orientations of both the call center agents and their customers in the process of communication exchanges. Specifically, the paper seeks to (1) describe the interplay between culture and technology in inbound call center industry as it affects the communication exchange of the agents and customers; (2) understand the nature and the dynamics of the call center industry as regards the cultural dimensions of Hofstede; and (3) come up with a simple study where the cross-cultural aspect of the call center industry could be highlighted and could provide necessary knowledge to the stakeholders. Cognizant of the complexity of the topic, the researchers employed Hofstede's cultural dimensions. Likewise, another theory that was used in this study is the Computer Mediated Communication Theory.

Keywords: call center industry, culture, Hofstede, CMT, technology

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Authors: Lisandy A. Suryana, Lidia Mayangsari, Santi Novani

Abstract:

Creative industry in Indonesia become an important aspect of the economy. One of the sectors of creative industry which give the highest contribution toward Indonesia’s GDP is fashion sector. In line with the target of Indonesia in 2020 to be the qibla’ of moeslem fashion of the world, all of the stakeholders of the business ecosystem should collaborate. Rather than focus on the internal aspects of producer, external aspects such as customers, government, community, etc. become important to be involved in the ecosystem to support the development and sustainability of those fashion sector. Unfortunately, although Indonesia has the biggest moeslem population, the number of hijab business penetration only 10%. Therefore, this research aims to analyze and develop the virtual co-creation platform for hijab creative industry as the strategy to achieve sustainability and increase the market share. This preliminary research describes the main stakeholders in the hijab creative industry based on business model approach. This business model is adapted by considering the service science context, and the data is collected by using the qualitative approach especially in-depth interview. This business model shows the relationship between resource integration, value co-creation, the value proposition of the company, and also the financial aspect of the business.

Keywords: value co-creation, Hijab Fashion Industry, creative industry, service business model, business model canvas

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Authors: Albert Gyamfi

Abstract:

Cocoa plays critical role in the socio-economic development of Ghana. Meanwhile, smallholder farmers most of whom are illiterate dominate the industry. According to the cocoa-based agricultural knowledge and information system (AKIS) model knowledge is created and transferred to the industry between three key actors: cocoa researchers, extension experts, and cocoa farmers. Dwelling on the SECI model, the media richness theory (MRT), and the AKIS model, a conceptual model of web 2.0-based AKIS model (AKIS 2.0) is developed and used to assess the possible effects of social media usage for knowledge creation in the Ghanaian cocoa industry. A mixed method approach with a survey questionnaire was employed, and a second-order multi-group structural equation model (SEM) was used to analyze the data. The study concludes that the use of web 2.0 applications for knowledge creation would lead to sustainable interactions among the key knowledge actors for effective knowledge creation in the cocoa industry in Ghana.

Keywords: agriculture, cocoa, knowledge, media, web 2.0

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