Search results for: cluster analyses

Authors: Insiya Kapasi, Roshni Udyavar Yehuda

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Cluster Redevelopment is a new concept in the city of Mumbai. Its regulations were laid down by the government in 2009. The concept of cluster redevelopment encompasses a group of buildings defined by a boundary as specified by the municipal authority (in this case, Mumbai), which may be dilapidated or approved for redevelopment. The study analyses the effect of cluster redevelopment in the form of renewal of old group of buildings as compared to refurbishment or restoration - on energy consumption. The methodology includes methods of assessment to determine increase or decrease in energy consumption in cluster redevelopment based on different criteria such as carpet area of the units, building envelope and its architectural elements. Results show that as the area and number of units increase the Energy consumption increases and the EPI (energy performance index) decreases as compared to the base case. The energy consumption per unit area declines by 29% in the proposed cluster redevelopment as compared to the original settlement. It is recommended that although the development is spacious and provides more light and ventilation, aspects such as glass type, traditional architectural features and consumer behavior are critical in the reduction of energy consumption.

Keywords: Cluster Redevelopment, Energy Consumption, Energy Efficiency, Typologies

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Authors: Jarunee Wonglimpiyarat

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This paper explores the innovation management strategy of Thailand in moving towards the Detroit of Asia. The study analyses Thailand’s automotive cluster based on Porter’s Diamond Model and national innovation system (NIS) framework. A qualitative methodology was carried out, using semi-structured interviews with the players in the Thai automotive industry. Thailand took a different NIS approach by pursuing an Original Equipment Manufacture (OEM) strategy to attract foreign investments in building its automotive cluster, a different path from other Asian countries that competed with Own Brand Manufacture (OBM) strategies. The findings provide useful lessons for other newly industrialized countries (NICs) in adopting the cluster policies to move up the technological ladders.

Keywords: innovation management strategy, national innovation system (NIS), Detroit of Asia, original equipment manufacturer (OEM)

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Authors: Pragya Bhawsar, Utpal Chattopadhyay

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Small and Medium Enterprises play crucial role in contributing to economic objectives of an emerging nation. To support SMEs, the idea of creation of clusters has been prevalent since past two decades. In this paper, an attempt has been done to explore the impact of being in the cluster on the competitiveness of SMEs. To meet the objective, Nasik Cluster (India) has been selected. The information was collected by means of two focus group discussions and survey of thirty SMEs. The finding generates interest revealing the fact that under the concept ‘Cluster’ a lot of ambiguity flourish. Besides the problems and opportunities of the firms in the cluster the results bring to notice that the benefits of clusterization can only reach to SMEs when the whole location can be considered/understood as a cluster, rather than many subsets (various forms of clusters) prevailing under it. Fostering such an understanding calls for harmony among the various stakeholders of the clusters. The dynamics of interaction among government, local industry associations, relevant institutions, large firms and finally SMEs which makes the most of the location based cluster, are significant in shaping the host cluster’s competitiveness and vice versa.

Keywords: SMEs, industry clusters, common facility centres, co-creation, policy

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Authors: Manverpreet Kaur, Amarpreet Singh

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The demand of Vehicular ad hoc networks is increasing day by day, due to offering the various applications and marvelous benefits to VANET users. Clustering in VANETs is most important to overcome the connectivity problems of VANETs. In this paper, we proposed a new clustering technique Enhanced cluster based connectivity maintenance in vehicular ad hoc network. Our objective is to form long living clusters. The proposed approach is grouping the vehicles, on the basis of the longest list of neighbors to form clusters. The cluster formation and cluster head selection process done by the RSU that may results it reduces the chances of overhead on to the network. The cluster head selection procedure is the vehicle which has closest speed to average speed will elect as a cluster Head by the RSU and if two vehicles have same speed which is closest to average speed then they will be calculate by one of the new parameter i.e. distance to their respective destination. The vehicle which has largest distance to their destination will be choosing as a cluster Head by the RSU. Our simulation outcomes show that our technique performs better than the existing technique.

Keywords: VANETs, clustering, connectivity, cluster head, intelligent transportation system (ITS)

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Authors: Mohammad Reza Shojaei, Mahdeih Mirzaeinia

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We have studied the cluster structure of even-even stable isotopes of Ge and Sr. The Schrodinger equation has been solved using the generalized parametric Nikiforov-Uvarov method with a phenomenological potential. This potential is the sum of the attractive Yukawa-like potential, a Manning-Rosen-type potential, and the repulsive Yukawa potential for interaction between the cluster and the core. We have shown that the available experimental data of the first rotational band energies can be well described by assuming a binary system of the α cluster and the core and using an analytical solution. Our results were consistent with experimental values. Hence, this model can be applied to study the other even-even isotopes

Keywords: cluser model, NU method, ge and Sr, potential central

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Authors: Philna Coetzee, Clara Msiza

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In modern society, audit committees are seen as the custodians of accountability and the conscience of management and the board. But who holds the audit committee accountable for their actions or non-actions and how do we know what they are supposed to be doing and what they are doing? The purpose of this article is to provide greater insight into the latter part of this problem, namely, determine what best practises for audit committees and the disclosure of what is the realities are. In countries where governance is well established, the roles and responsibilities of the audit committee are mostly clearly guided by legislation and/or guidance documents, with countries increasingly providing guidance on this topic. With high cost involved to adhere to governance guidelines, the public (for public organisations) and shareholders (for private organisations) expect to see the value of their ‘investment’. For audit committees, the dividends on the investment should reflect in less fraudulent activities, less corruption, higher efficiency and effectiveness, improved social and environmental impact, and increased profits, to name a few. If this is not the case (which is reflected in the number of fraudulent activities in both the private and the public sector), stakeholders have the right to ask: where was the audit committee? Therefore, the objective of this article is to contribute to the body of knowledge by comparing the adherence of audit committee to best practices guidelines as stipulated in the King Report across public listed companies, national and provincial government departments, state-owned enterprises and local municipalities. After constructs were formed, based on the literature, factor analyses were conducted to reduce the number of variables in each construct. Thereafter, cluster analyses, which is an explorative analysis technique that classifies a set of objects in such a way that objects that are more similar are grouped into the same group, were conducted. The SPSS TwoStep Clustering Component was used, being capable of handling both continuous and categorical variables. In the first step, a pre-clustering procedure clusters the objects into small sub-clusters, after which it clusters these sub-clusters into the desired number of clusters. The cluster analyses were conducted for each construct and the measure, namely the audit opinion as listed in the external audit report, were included. Analysing 228 organisations' information, the results indicate that there is a clear distinction between the four spheres of business that has been included in the analyses, indicating certain strengths and certain weaknesses within each sphere. The results may provide the overseers of audit committees’ insight into where a specific sector’s strengths and weaknesses lie. Audit committee chairs will be able to improve the areas where their audit committee is lacking behind. The strengthening of audit committees should result in an improvement of the accountability of boards, leading to less fraud and corruption.

Keywords: audit committee disclosure, cluster analyses, governance best practices, strengths and weaknesses

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Authors: Christopher Lama, Alix Rieser, Aleksandra Molchanova, Charles Thangaraj

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New technologies like Tesla’s Dojo have made high-performance embedded computing more available. Although automobile computing has developed and benefited enormously from these more recent technologies, the costs are still high, prohibitively high in some cases for broader adaptation, particularly for the after-market and enthusiast markets. This project aims to implement a Raspberry Pi-based low-power (under one hundred Watts) highly mobile computing cluster for a neural network. The computing cluster built from off-the-shelf components is more affordable and, therefore, makes wider adoption possible. The paper describes the design of the neural network, Raspberry Pi-based cluster, and applications the cluster will run. The neural network will use input data from sensors and cameras to project a live view of the road state as the user drives. The neural network will be trained to predict traffic behavior and generate warnings when potentially dangerous situations are predicted. The significant outcomes of this study will be two folds, firstly, to implement and test the low-cost cluster, and secondly, to ascertain the effectiveness of the predictive AI implemented on the cluster.

Keywords: CS pedagogy, student research, cluster computing, machine learning

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Authors: Purevdolgor Luvsantseren, Ajnai Luvsan-Ish, Oyuntsetseg Sandag, Javzmaa Tsend, Akhit Tileubai, Baasandorj Chilhaasuren, Jargalbat Puntsagdash, Galbadrakh Chuluunbaatar

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One of the indicators of the quality of university services is student satisfaction. Aim: We aimed to study the level of satisfaction of students in the first year of premedical courses in the course of Medical Physics using the cluster method. Materials and Methods: In the framework of this goal, a questionnaire was collected from a total of 324 students who studied the medical physics course of the 1st course of the premedical course at the Mongolian National University of Medical Sciences. When determining the level of satisfaction, the answers were obtained on five levels of satisfaction: "excellent", "good", "medium", "bad" and "very bad". A total of 39 questionnaires were collected from students: 8 for course evaluation, 19 for teacher evaluation, and 12 for student evaluation. From the research, a database with 39 fields and 324 records was created. Results: In this database, cluster analysis was performed in MATLAB and R programs using the k-means method of data mining. Calculated the Hopkins statistic in the created database, the values are 0.88, 0.87, and 0.97. This shows that cluster analysis methods can be used. The course evaluation sub-fund is divided into three clusters. Among them, cluster I has 150 objects with a "good" rating of 46.2%, cluster II has 119 objects with a "medium" rating of 36.7%, and Cluster III has 54 objects with a "good" rating of 16.6%. The teacher evaluation sub-base into three clusters, there are 179 objects with a "good" rating of 55.2% in cluster II, 108 objects with an "average" rating of 33.3% in cluster III, and 36 objects with an "excellent" rating in cluster I of 11.1%. The sub-base of student evaluations is divided into two clusters: cluster II has 215 objects with an "excellent" rating of 66.3%, and cluster I has 108 objects with an "excellent" rating of 33.3%. Evaluating the resulting clusters with the Silhouette coefficient, 0.32 for the course evaluation cluster, 0.31 for the teacher evaluation cluster, and 0.30 for student evaluation show statistical significance. Conclusion: Finally, to conclude, cluster analysis in the model of the medical physics lesson “good” - 46.2%, “middle” - 36.7%, “bad” - 16.6%; 55.2% - “good”, 33.3% - “middle”, 11.1% - “bad” in the teacher evaluation model; 66.3% - “good” and 33.3% of “bad” in the student evaluation model.

Keywords: questionnaire, data mining, k-means method, silhouette coefficient

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Authors: Wen-Hsiang Lai

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Except for the internal aspects of entrepreneurship (i.e. motivation, opportunity perspective and alertness), there are external aspects that affecting entrepreneurship (i.e. the industrial cluster). By comparing the machinery companies located inside and outside the industrial district, this study aims to explore the cluster effects on the entrepreneurship of companies in Taiwan machinery clusters (TMC). In this study, three factors affecting the entrepreneurship in TMC are conducted as “competition”, “embedded-ness” and “specialized knowledge”. The “competition” in the industrial cluster is defined as the competitive advantages that companies gain in form of demand effects and diversified strategies; the “embedded-ness” refers to the quality of company relations (relational embedded-ness) and ranges (structural embedded-ness) with the industry components (universities, customers and complementary) that affecting knowledge transfer and knowledge generations; the “specialized knowledge” shares the internal knowledge within industrial clusters. This study finds that when comparing to the companies which are outside the cluster, the industrial cluster has positive influence on the entrepreneurship. Additionally, the factor of “relational embedded-ness” has significant impact on the entrepreneurship and affects the adaptation ability of companies in TMC. Finally, the factor of “competition” reveals partial influence on the entrepreneurship.

Keywords: entrepreneurship, industrial cluster, industrial district, economies of agglomerations, Taiwan Machinery Cluster (TMC)

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Authors: Tariq Abbas, Younus Muhammad, Sayyad Aun Muhammad

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Background : Crimean Congo hemorrhagic fever (CCHF) is a tick born viral zoonotic disease that has been notified from almost all regions of Pakistan. The aim of this study was to investigate spatial distribution of CCHF cases reported to National Institue of Health , Islamabad during year 2013. Methods : Spatial statistics tools were applied to detect extent spatial auto-correlation and clusters of the disease based on adjusted cumulative incidence per million population for each district. Results : The data analyses revealed a large multi-district cluster of high values in the uplands of Balochistan province near Afghanistan border. Conclusion : The cluster included following districts: Pishin; Qilla Abdullah; Qilla Saifullah; Quetta, Sibi; Zhob; and Ziarat. These districts may be given priority in CCHF surveillance, control programs, and further epidemiological research . The location of the cluster close to border of Afghanistan and Iran highlight importance of the findings for organizations dealing with disease at national, regional and global levels.

Keywords: Crimean Congo hemorrhagic fever, Pakistan, spatial autocorrelation, clusters , adjusted cumulative incidence

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Authors: A. Akın, H. Çoban

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This study was carried out to determine the effects of Control (C), 1/3 Cluster Tip Reduction (1/3 CTR), 1/6 Cluster Tip Reduction (1/6 CTR), 1/9 Cluster Tip Reduction (1/9 CTR), 1/3 CTR + Boric Acid (BA), 1/6 CTR + BA, 1/9 CTR + BA applications on yield and yield components of four years old Alphonse Lavallee grape variety (Vitis vinifera L.) grown on grafted 110 Paulsen rootstock in Konya province in Turkey in the vegetation period in 2015. According to the results, the highest maturity index 21.46 with 1/9 CTR application; the highest grape juice yields 736.67 ml with 1/3 CTR + BA application; the highest L* color value 32.07 with 1/9 CTR application; the highest a* color value 1.74 with 1/9 CTR application; the highest b* color value 3.72 with 1/9 CTR application were obtained. The effects of applications on grape fresh yield, cluster weight and berry weight were not found statistically significant.

Keywords: alphonse lavallee grape cultivar, different cluster tip reduction (1/3, 1/6, 1/9), foliar boric acid application, yield, quality

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Authors: Pil Seong Park

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Homemade HPC clusters are widely used in many small labs, because they are easy to build and cost-effective. Even though incremental growth is an advantage of clusters, it results in heterogeneous systems anyhow. Instead of adding new nodes to the cluster, we can extend clusters to include some other Internet servers working independently on the same LAN, so that we can make use of their idle times, especially during the night. However extension across a firewall raises some security problems with NFS. In this paper, we propose a method to solve such a problem using SSH tunneling, and suggest a modified structure of the cluster that implements it.

Keywords: extension of HPC clusters, security, NFS, SSH tunneling

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Authors: Ritu Vashistha, Jitender Kumar

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Clustering using the K-means algorithm is a very common way to understand and analyze the obtained output data. When a similar object is grouped, this is called the basis of Clustering. There is K number of objects and C number of cluster in to single cluster in which k is always supposed to be less than C having each cluster to be its own centroid but the major problem is how is identify the cluster is correct based on the data. Formulation of the cluster is not a regular task for every tuple of row record or entity but it is done by an iterative process. Each and every record, tuple, entity is checked and examined and similarity dissimilarity is examined. So this iterative process seems to be very lengthy and unable to give optimal output for the cluster and time taken to find the cluster. To overcome the drawback challenge, we are proposing a formula to find the clusters at the run time, so this approach can give us optimal results. The proposed approach uses the Euclidian distance formula as well melanosis to find the minimum distance between slots as technically we called clusters and the same approach we have also applied to Ant Colony Optimization(ACO) algorithm, which results in the production of two and multi-dimensional matrix.

Keywords: ant colony optimization, data clustering, centroids, data mining, k-means

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Authors: Shahed Vahedi, Mohd Salmi Md Noorani

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This paper investigates cluster synchronization phenomena between community networks. We focus on the situation where a variety of dynamics occur in the clusters. In particular, we show that different synchronization states simultaneously occur between the networks. The controller is designed having an adaptive control gain, and theoretical results are derived via Lyapunov stability. Simulations on well-known dynamical systems are provided to elucidate our results.

Keywords: cluster synchronization, adaptive control, community network, simulation

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Authors: Ishtiaq Wahid, Masood Ahmad, Nighat Ayub, Sajad Ali

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Lifetime of a wireless sensor network (WSN) is directly proportional to the energy consumption of its constituent nodes. Routing in wireless sensor network is very challenging due its inherit characteristics. In hierarchal routing the sensor filed is divided into clusters. The cluster-heads are selected from each cluster, which forms a hierarchy of nodes. The cluster-heads are used to transmit the data to the base station while other nodes perform the sensing task. In this way the lifetime of the network is increased. In this paper a comparative study of hierarchal routing protocols are conducted. The simulation is done in NS-2 for validation.

Keywords: WSN, cluster, routing, sensor networks

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Authors: Sahar Elsaleh, Ghada Farhat, Shaikha Al-Derham, Fasih Alam

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Background: Cesarean section (CS) delivery is one of the major concerns both in developing and developed countries. The rate of CS deliveries are on the rise globally, and especially in Qatar. Many socio-economic, demographic, clinical and institutional factors play an important role for cesarean sections. This study aims to investigate factors affecting the prevalence of CS among women in Qatar using the UNICEF’s Multiple Indicator Cluster Survey (MICS) 2012 database. Methods: The study has focused on the women’s questionnaire of the MICS, which was successfully distributed to 5699 participants. Following study inclusion and exclusion criteria, a final sample of 761 women aged 19- 49 years who had at least one delivery of giving birth in their lifetime before the survey were included. A number of socio-economic, demographic, clinical and institutional factors, identified through literature review and available in the data, were considered for the analyses. Bivariate and multivariate logistic regression models, along with a multi-level modeling to investigate clustering effect, were undertaken to identify the factors that affect CS prevalence in Qatar. Results: From the bivariate analyses the study has shown that, a number of categorical factors are statistically significantly associated with the dependent variable (CS). When identifying the factors from a multivariate logistic regression, the study found that only three categorical factors -‘age of women’, ‘place at delivery’ and ‘baby weight’ appeared to be significantly affecting the CS among women in Qatar. Although the MICS dataset is based on a cluster survey, an exploratory multi-level analysis did not show any clustering effect, i.e. no significant variation in results at higher level (households), suggesting that all analyses at lower level (individual respondent) are valid without any significant bias in results. Conclusion: The study found a statistically significant association between the dependent variable (CS delivery) and age of women, frequency of TV watching, assistance at birth and place of birth. These results need to be interpreted cautiously; however, it can be used as evidence-base for further research on cesarean section delivery in Qatar.

Keywords: cesarean section, factors, multiple indicator cluster survey, MICS database, Qatar

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Authors: A. E. Emam, M. Abd Elghany

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The change in orbit evolution between collocated satellites (X, Y) inside +/-0.09 ° E/W and +/- 0.07 ° N/S cluster, after one of these satellites is placed in an inclined orbit (satellite X) and the effect of this change in the collocation safety inside the cluster window has been studied and evaluated. Several collocation scenarios had been studied in order to adjust the location of both satellites inside their cluster to maximize the separation between them and safe the mission.

Keywords: satellite, GEO, collocation, risk assessment

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Authors: Naim Karasekreter, Ugur Fidan, Fatih Basciftci

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Wireless sensor networks are networks in which more than one sensor node is organized among themselves. The working principle is based on the transfer of the sensed data over the other nodes in the network to the central station. Wireless sensor networks concentrate on routing algorithms, energy efficiency and clustering algorithms. In the clustering method, the nodes in the network are divided into clusters using different parameters and the most suitable cluster head is selected from among them. The data to be sent to the center is sent per cluster, and the cluster head is transmitted to the center. With this method, the network traffic is reduced and the energy efficiency of the nodes is increased. In this study, clustering algorithms were examined in terms of clustering performances and cluster head selection characteristics to try to identify weak and strong sides. This work is supported by the Project 17.Kariyer.123 of Afyon Kocatepe University BAP Commission.

Keywords: wireless sensor networks (WSN), clustering algorithm, cluster head, clustering

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Authors: A. Akin

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This study was carried out on Italia grape variety (Vitis vinifera L.) in Konya province, Turkey in 2016. The cultivar is five years old and grown on 1103 Paulsen rootstock. It was determined the effects of applications of the Control (C), 1/3 Cluster Tip Reduction (1/3 CTR), 1/6 Cluster Tip Reduction (1/6 CTR), 1/9 Cluster Tip Reduction (1/9 CTR), 1/3 CTR+Boric Acid (BA), 1/6 CTR+BA, 1/9 CTR+BA, on yield and yield components of the Italia grape variety. The results were obtained as the highest fresh grape yield (4.74 g) with 1/9 CTR+BA application; the highest cluster weight (220.08 g) with 1/3 CTR application; the highest 100 berry weight (565.85 g) with 1/9 CTR+BA application; as the highest maturity index (49.28) with 1/9 CTR+BA application; as the highest must yield (685.33 ml/kg) with 1/3 CTR+BA and (685.33 ml/kg) with 1/9 CTR+BA applications. To increase the fresh grape yield, 100 berry weight and maturity index in the Italia grape variety, the 1/9 CTR+BA application can be recommended.

Keywords: boric acid, cluster tip reduction, Italia grape variety, yield, yield components

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Authors: Murat Yazici

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Anomalies are irregularities found in data that do not adhere to a well-defined standard of normal behavior. The identification of outliers or anomalies in data has been a subject of study within the statistics field since the 1800s. Over time, a variety of anomaly detection techniques have been developed in several research communities. The cluster analysis can be used to detect anomalies. It is the process of associating data with clusters that are as similar as possible while dissimilar clusters are associated with each other. Many of the traditional cluster algorithms have limitations in dealing with data sets containing categorical properties. To detect anomalies in categorical data, fuzzy clustering approach can be used with its advantages. The fuzzy k-Mode (FKM) clustering algorithm, which is one of the fuzzy clustering approaches, by extension to the k-means algorithm, is reported for clustering datasets with categorical values. It is a form of clustering: each point can be associated with more than one cluster. In this paper, anomaly detection is performed on two simulated data by using the FKM cluster algorithm. As a significance of the study, the FKM cluster algorithm allows to determine anomalies with their abnormality degree in contrast to numerous anomaly detection algorithms. According to the results, the FKM cluster algorithm illustrated good performance in the anomaly detection of data, including both one anomaly and more than one anomaly.

Keywords: fuzzy k-mode clustering, anomaly detection, noise, categorical data

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Authors: L. Belkhiri, L. Mouni, A. Tiri, T.S. Narany

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In the present study, the self-organizing map (SOM) clustering technique was applied to identify homogeneous clusters of hydrochemical parameters in El Milia plain, Algeria, to assess the quality of groundwater for potable and agricultural purposes. The visualization of SOM-analysis indicated that 35 groundwater samples collected in the study area were classified into three clusters, which showed progressive increase in electrical conductivity from cluster one to cluster three. Samples belonging to cluster one are mostly located in the recharge zone showing hard fresh water type, however, water type gradually changed to hard-brackish type in the discharge zone, including clusters two and three. Ionic ratio studies indicated the role of carbonate rock dissolution in increases on groundwater hardness, especially in cluster one. However, evaporation and evapotranspiration are the main processes increasing salinity in cluster two and three.

Keywords: groundwater quality, self-organizing maps, drinking water, irrigation water

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Authors: Nandini Mohan, Thiruvengadam R. B.

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Mahatma Gandhi advocated that the true indicator of modern India lay in the development of its villages. This has been proven with the recent outbreak of the Coronavirus pandemic and the surfacing predicament of our urban centers. Developed on the Industrialization model, the current state of the metropolis is of rampant overcrowding, high rates of unemployment, inadequate infrastructure, and resources to cater to the growing population. A majority of each city’s strength composes of the migrant population, demonstrated through the migrant crisis, a direct repercussion of COVID-19. This paper explores the ideology of how rural development can act as a tactic to counter the high rates of rural-urban migration. It establishes the need for a rural push, as India is predominantly an agrarian economy, with a vast disparity between the urban and rural centers due to its urban bias. It seeks to define development in holistic terms. It studies the models of ‘cluster’ as conceptualized by V.K.R.V. Rao, and detailed by Architect Charles Correa in his book, The New Landscape. The paper reexamines the theory of cluster development through existing models proposed by the government of India. Namely, PURA (Provision of Urban Amenities in Rural Areas), DRI (Deendayal Research Institute), and Rurban under Shyama Prasad Mukharjee Rurban Mission. It analyses the models, their strengths, weaknesses, and reasons for their failure and success to derive parameters for the ideation of an archetype model. A model of rural development that talks of the simultaneous development of existing adjacent villages, by the introduction of set unique functions, that may turn into self-sustaining clusters or agglomerations in the future, which could serve as the next step for Indian village development based on the cluster ideology.

Keywords: counter migration, models of rural development, cluster development theory, India

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Authors: Wassim Jerbi, Abderrahmen Guermazi, Hafedh Trabelsi

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The optimum use of coverage in wireless sensor networks (WSNs) is very important. LEACH protocol called Low Energy Adaptive Clustering Hierarchy, presents a hierarchical clustering algorithm for wireless sensor networks. LEACH is a protocol that allows the formation of distributed cluster. In each cluster, LEACH randomly selects some sensor nodes called cluster heads (CHs). The selection of CHs is made with a probabilistic calculation. It is supposed that each non-CH node joins a cluster and becomes a cluster member. Nevertheless, some CHs can be concentrated in a specific part of the network. Thus, several sensor nodes cannot reach any CH. to solve this problem. We created an O-LEACH Orphan nodes protocol, its role is to reduce the sensor nodes which do not belong the cluster. The cluster member called Gateway receives messages from neighboring orphan nodes. The gateway informs CH having the neighboring nodes that not belong to any group. However, Gateway called (CH') attaches the orphaned nodes to the cluster and then collected the data. O-Leach enables the formation of a new method of cluster, leads to a long life and minimal energy consumption. Orphan nodes possess enough energy and seeks to be covered by the network. The principal novel contribution of the proposed work is O-LEACH protocol which provides coverage of the whole network with a minimum number of orphaned nodes and has a very high connectivity rates.As a result, the WSN application receives data from the entire network including orphan nodes. The proper functioning of the Application requires, therefore, management of intelligent resources present within each the network sensor. The simulation results show that O-LEACH performs better than LEACH in terms of coverage, connectivity rate, energy and scalability.

Keywords: WSNs; routing; LEACH; O-LEACH; Orphan nodes; sub-cluster; gateway; CH’

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Authors: Abbas Al-Refaie

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The research examines the factors that affect customer churn (CC) in the Jordanian telecom industry. A total of 700 surveys were distributed. Cluster analysis revealed three main clusters. Results showed that CC and customer satisfaction (CS) were the key determinants in forming the three clusters. In two clusters, the center values of CC were high, indicating that the customers were loyal and SC was expensive and time- and energy-consuming. Still, the mobile service provider (MSP) should enhance its communication (COM), and value added services (VASs), as well as customer complaint management systems (CCMS). Finally, for the third cluster the center of the CC indicates a poor level of loyalty, which facilitates customers churn to another MSP. The results of this study provide valuable feedback for MSP decision makers regarding approaches to improving their performance and reducing CC.

Keywords: cluster analysis, telecom industry, switching cost, customer churn

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Authors: D. Supaporn, B. Julaluk

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The purposes of this study were to study symptom cluster, functional status and quality of life of patients with chronic obstructive pulmonary disease (COPD), and to examine factors related to and predicting symptom cluster, functional status and quality of life of COPD patients. The sample was 180 COPD patients multi-stage random sampling from 4 hospitals in the eastern region, Thailand. The research instruments were 8 questionnaires and recorded forms measuring personal and illness data, co-morbidity, physical and psychological symptom, health status perception, social support, and regimen adherence, functional status and quality of life. Spearman rank and Pearson correlation coefficient, exploratory factors analysis and standard multiple regression were used to analyzed data. The findings revealed that two symptom clusters were generated: physical symptom cluster including dyspnea, fatigue and insomnia; and, psychological symptom cluster including anxiety and depression. Scores of physical symptom cluster was at moderate level while that of psychological symptom cluster was at low level. Scores on functional status, social support and overall regimen adherence were at good level whereas scores on quality of life and health status perception were at moderate level. Disease severity was positively related to physical symptom cluster, psychological symptom cluster and quality of life, and was negatively related to functional status at a moderate level (rs = .512, .509, .588 and -.611, respectively). Co-morbidity was positively related to physical symptom cluster and psychological symptom cluster at a low level (r = .179 and .176, respectively). Regimen adherence was negatively related to quality of life and psychological symptom cluster at a low level (r=-.277 and -.309, respectively), and was positively related to functional status at a moderate level (r=.331). Health status perception was negatively related to physical symptom cluster, psychological symptom cluster and quality of life at a moderate to high level (r = -.567, -.640 and -.721, respectively) and was positively related to functional status at a high level (r = .732). Social support was positively related to functional status (r=.235) and was negatively related to quality of life at a low level (r=-.178). Physical symptom cluster was negatively related to functional status (r= -.490) and was positively related to quality of life at a moderate level (r=.566). Psychological symptom cluster was negatively related to functional status and was positively related to quality of life at a moderate level (r= -.566 and .559, respectively). Disease severity, co-morbidity and health status perception could predict 40.2% of the variance of physical symptom cluster. Disease severity, co-morbidity, regimen adherence and health status perception could predict 49.8% of the variance of psychological symptom cluster. Co-morbidity, regimen adherence and health status perception could predict 65.0% of the variance of functional status. Disease severity, health status perception and physical symptom cluster could predict 60.0% of the variance of quality of life in COPD patients. The results of this study can be used for enhancing quality of life of COPD patients.

Keywords: chronic obstructive pulmonary disease, functional status, quality of life, symptom cluster

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Authors: Alexander Sharashenidze

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This article discusses the role of tourism in the economics of Georgia, justifies the necessity of several governmental supporting tools for diversification of tourism product and increasing competitiveness. Tourism directions are characterized through discovering Georgian tourism potential, considering cultural and geographical features; tools of formating supplemental products and development opportunities of Tbilisi and, also regions are asserted in the case of conducting appropriate government policy. There are presented tools of suggesting innovative tourism products, improvement of service, decreasing taxes, also providing availability to them. The role of tourism cluster in improvement of national competitiveness is substantiated. Based on the analysis of competitive factors influencing the development of tourism cluster, conclusions are made, and recommendations are suggested.

Keywords: economic competitivness, enhancing competitiveness, Georgian economic, tourism cluster, tourism product

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Authors: Kanogkan Leerojanaprapa

Abstract:

Textile and garment industry is used to a major exporting industry of Thailand. According to lacking of the nation's price-competitiveness by stopping the EU's GSP (Generalised Scheme of Preferences) and ‘Nationwide Minimum Wage Policy’ that Thailand’s employers must pay all employees at least 300 baht (about $10) a day, the supply chains of the Thai textile and garment industry is affected and need to be reformed. Therefore, either Thai textile or garment industry will be existed or not would be concerned. This is also challenged for the government to decide which industries should be promoted the future industries of Thailand. Recently Thai government launch The Cluster-based Special Economic Development Zones Policy for promoting business cluster (effect on September 16, 2015). They define a cluster as the concentration of interconnected businesses and related institutions that operate within the same geographic areas and textiles and garment is one of target industrial clusters and 9 provinces are targeted (Bangkok, Kanchanaburi, Nakhon Pathom, Ratchaburi, Samut Sakhon, Chonburi, Chachoengsao, Prachinburi, and Sa Kaeo). The cluster zone are defined to link west-east corridor connected to manufacturing source in Cambodia and Mynmar to Bangkok where are promoted to be design, sourcing, and trading hub. The Thai government will provide tax and non-tax incentives for targeted industries within the clusters and expects these businesses are scattered to where they can get the most benefit which will identify future industrial cluster. This research will show the difference between the current cluster and future cluster following the target provinces of the textile and garment. The current cluster is analysed from secondary data. The four characteristics of the numbers of plants in Spinning, weaving and finishing of textiles, Manufacture of made-up textile articles, except apparel, Manufacture of knitted and crocheted fabrics, and Manufacture of other textiles, not elsewhere classified in particular 77 provinces (in total) are clustered by K-means cluster analysis and Hierarchical Cluster Analysis. In addition, the cluster can be confirmed and showed which variables contribute the most to defined cluster solution with ANOVA test. The results of analysis can identify 22 provinces (which the textile or garment plants are located) into 3 clusters. Plants in cluster 1 tend to be large numbers of plants which is only Bangkok, Next plants in cluster 2 tend to be moderate numbers of plants which are Samut Prakan, Samut Sakhon and Nakhon Pathom. Finally plants in cluster 3 tend to be little numbers of plants which are other 18 provinces. The same methodology can be implemented in other industries for future study.

Keywords: ANOVA, hierarchical cluster analysis, industrial clusters, K -means cluster analysis, textile and garment industry

Procedia PDF Downloads 212

Authors: Wided Abidi, Tahar Ezzedine

Abstract:

Low-Energy Adaptive Clustering Hierarchy (LEACH) has been considered as one of the effective hierarchical routing algorithms that optimize energy and prolong the lifetime of network. Since the selection of Cluster Head (CH) in LEACH is carried out randomly, in this paper, we propose an approach of electing CH based on LEACH protocol. In other words, we present a formula for calculating the threshold responsible for CH election. In fact, we adopt three principle criteria: the remaining energy of node, the number of neighbors within cluster range and the distance between node and CH. Simulation results show that our proposed approach beats LEACH protocol in regards of prolonging the lifetime of network and saving residual energy.

Keywords: wireless sensors networks, LEACH protocol, cluster head election, energy efficiency

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Authors: Ameen Jameel Alawneh

Abstract:

A Mobile ad-hoc network (MANET) is a collection of wireless mobile hosts that dynamically form a temporary network without the aid of a system administrator. It has neither fixed infrastructure nor wireless ad hoc sessions. It inherently reaches several nodes with a single transmission, and each node functions as both a host and a router. The network maybe represented as a set of clusters each managed by clusterhead. The cluster size is not fixed and it depends on the movement of nodes. We proposed a clusterhead size algorithm (CHSize). This clustering algorithm can be used by several routing algorithms for ad hoc networks. An elected clusterhead is assigned for communication with all other clusters. Analysis and simulation of the algorithm has been implemented using GloMoSim networks simulator, MATLAB and MAPL11 proved that the proposed algorithm achieves the goals.

Keywords: simulation, MANET, Ad-hoc, cluster head size, linked cluster algorithm, loss and dropped packets

Procedia PDF Downloads 390

Authors: Hassan S. Hussein, Rania A. Abul Seoud, Amr M. Refaat

Abstract:

Scientific researchers face in the analysis of very large data sets that is increasing noticeable rate in today’s and tomorrow’s technologies. Hadoop and Spark are types of software that developed frameworks. Hadoop framework is suitable for many Different hardware platforms. In this research, a scientific Linux cluster for Big Data analysis (SLBD) is presented. SLBD runs open source software with large computational capacity and high performance cluster infrastructure. SLBD composed of one cluster contains identical, commodity-grade computers interconnected via a small LAN. SLBD consists of a fast switch and Gigabit-Ethernet card which connect four (nodes). Cloudera Manager is used to configure and manage an Apache Hadoop stack. Hadoop is a framework allows storing and processing big data across the cluster by using MapReduce algorithm. MapReduce algorithm divides the task into smaller tasks which to be assigned to the network nodes. Algorithm then collects the results and form the final result dataset. SLBD clustering system allows fast and efficient processing of large amount of data resulting from different applications. SLBD also provides high performance, high throughput, high availability, expandability and cluster scalability.

Keywords: big data platforms, cloudera manager, Hadoop, MapReduce

Procedia PDF Downloads 357