Search results for: data center

Authors: Tae Ho Kim

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Using the center of gravity method, we intend to find the center of gravity of Eurasia and North America, focusing on the local population, and study economic development plans in Eurasia and North America. By analyzing the strengths and opportunities of an industrial location for each region, we find ways for the country to grow and develop. Through economic cooperation and support between countries, we want to reduce the cause of conflict and dispute through economic growth in countries or regions. Furthermore, we want to create conditions for peaceful and happy regions or countries. Eurasia and North America are rich in resources, have great growth potential in terms of global supply chains, and have a good position to develop further. By analyzing intimacy between countries using REM, a CRM method, we intend to transform it into a region where a hopeful future of peace and prosperity begins. The future can be transformed through positive thinking or love for humanity. Indicators of intimacy between countries or regions can also be created anew if they change how they view each other. The Earth we live on is facing great risks, such as climate change and war. In order to reduce this crisis and maintain peace and prosperity, we must cooperate with each other in new directions.

Keywords: supply chain economy, REM, Indicators of intimacy, peace and prosperity

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Authors: Jihyun Song, Kyeongjoo Kim, Minsoo Lee

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Due to the development of information technology and wireless Internet technology, various data are being generated in various fields. These data are advantageous in that they provide real-time information to the users themselves. However, when the data are accumulated and analyzed, more various information can be extracted. In addition, development and dissemination of boards such as Arduino and Raspberry Pie have made it possible to easily test various sensors, and it is possible to collect sensor data directly by using database application tools such as MySQL. These directly collected data can be used for various research and can be useful as data for data mining. However, there are many difficulties in using the board to collect data, and there are many difficulties in using it when the user is not a computer programmer, or when using it for the first time. Even if data are collected, lack of expert knowledge or experience may cause difficulties in data analysis and visualization. In this paper, we aim to construct a library for sensor data collection and analysis to overcome these problems.

Keywords: clustering, data mining, DBSCAN, k-means, k-medoids, sensor data

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Authors: Syed Iftikhar Hussain Shah, Vasilis Peristeras, Ioannis Magnisalis

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Organizations, including governments, generate (big) data that are high in volume, velocity, veracity, and come from a variety of sources. Public Administrations are using (big) data, implementing base registries, and enforcing data sharing within the entire government to deliver (big) data related integrated services, provision of insights to users, and for good governance. Government (Big) data ecosystem actors represent distinct entities that provide data, consume data, manipulate data to offer paid services, and extend data services like data storage, hosting services to other actors. In this research work, we perform a systematic literature review. The key objectives of this paper are to propose a robust definition of government (big) data ecosystem and a classification of government (big) data ecosystem actors and their roles. We showcase a graphical view of actors, roles, and their relationship in the government (big) data ecosystem. We also discuss our research findings. We did not find too much published research articles about the government (big) data ecosystem, including its definition and classification of actors and their roles. Therefore, we lent ideas for the government (big) data ecosystem from numerous areas that include scientific research data, humanitarian data, open government data, industry data, in the literature.

Keywords: big data, big data ecosystem, classification of big data actors, big data actors roles, definition of government (big) data ecosystem, data-driven government, eGovernment, gaps in data ecosystems, government (big) data, public administration, systematic literature review

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Authors: Lely A. Luengas, Pedro R. Vizcaya, Giovanni Sánchez

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In this paper, a methodology is presented to obtain the Static Alignment Model for any transtibial amputee person. The proposed methodology starts from experimental data collected on the Hospital Militar Central, Bogotá, Colombia. The effects of transtibial prosthesis malalignment on amputees were measured in terms of joint angles, center of pressure (COP) and weight distribution. Some statistical tools are used to obtain the model parameters. Mathematical predictive models of prosthetic alignment were created. The proposed models are validated in amputees and finding promising results for the prosthesis Static Alignment. Static alignment process is unique to each subject; nevertheless the proposed methodology can be used in each transtibial amputee.

Keywords: information theory, prediction model, prosthetic alignment, transtibial prosthesis

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Authors: Andrew Anis Fakhrey Mosaad

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Introduction: Sports- and physical activity-related injuries may be more likely if there is a genetic predisposition, improper coaching and/or training, and no follow-up care from sports medicine. Goal: To evaluate the frequency of injuries among athletes receiving care at a sportsfocused physical therapy clinic. Methods: The survey of injuries in athletes' treatment records over a period of eight years of activity was done to obtain data. The data collected included: the patient's features, the sport, the type of injury, the injury's characteristics, and the body portion injured. Results: The athletes were drawn from 1090 patient/athlete records, had an average age of 25, participated in 44 different sports, and were 75% men on average. Joint injuries were the most frequent type of injury, then damage to the muscles and bones. The most prevalent type of injury was chronic (47%), while the knee, ankle, and shoulder were the most frequently damaged body parts. The most injured athletes were seen in soccer, futsal, and track and field, respectively, out of all the sports. Conclusion: The most popular sport among injured players was soccer, and the most common injury type was joint damage, with the knee being the most often damaged body area. The majority of the injuries were chronic.

Keywords: sports injuries, athletes, joint injuries, injured players

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Authors: Kiyoko Yoshimura, Yasunobu Kino

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Focusing on professional call centers where workers with expertise perform services, this study aims to clarify the relationships between emotional labor and job satisfaction and the effects of recognition of customer feedback. Since the professional call center operators consist of professional license holders (qualification holders) and those who do not (non-holders), the following three points are analyzed in the two groups by using covariance structure analysis and simultaneous multi-population analysis: 1) The relationship between emotional labor and job satisfaction, 2) customer feedback and job satisfaction, and 3) The intermediation effect between the emotional labor of customer feedback and job satisfaction. The following results are obtained: i) no direct effect is found between job satisfaction and emotional labor for qualification holders and non-holders, ii) for qualification holders and non-holders, recognition of positive feedback and recognition of negative feedback had positive and negative effects on job satisfaction, respectively, iii) for qualification and non-holders, "consideration for colleagues" influences job satisfaction by recognizing positive feedback, and iv) only for qualification holders, the factors "customer-oriented emotional expression" and "emotional disharmony" have a positive and negative effect on job satisfaction, respectively, through recognition of positive feedback and recognition of negative feedback.

Keywords: call center, emotional labor, professional service, job satisfaction, customer feedback

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Authors: Ani Demetrashvili

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The purpose of this paper is to show how students trust online tests and determine validity and reliability in the development of online testing. The pandemic situation changed every field in the world, and it changed education as well. Educational institutions moved into the online space, which was the only decision they were able to make at that time. Online assessment through online proctoring was a totally new challenge for educational institutions, and they needed to deal with it successfully. Participants were chosen from the English language center. The validity of the questionnaire was identified according to the Likert scale and Cronbach’s alpha; later, data from the participants was analyzed as well. The article summarizes literature that is available about online assessment and is interesting for people who are interested in this kind of assessment. Based on the research findings, students favor in-person testing over online assessment due to their lack of experience and skills in the latter.

Keywords: online assessment, online proctoring

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Authors: Yasemin Ilkay

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Urban spatial pattern interacts with the minds and bodies of citizens and influences their perception and attitudes, which leads to a two-folded map of the same space: physical and Psychogeographic maps. Psychogeography is a field of inquiry (rooted in literature and fiction) investigating how the environment affects the feelings and behaviors of individuals. This term was posed by Situationist International Movement in the 1950s by Guy Debord; in the course of time, the artistic framework evolved into a political issue, especially with the term Dérive, which indicates ‘deviation’ and ‘resistance’ to the existing spatial reality. The term Dérive appeared on the track of Flânéur after one hundred years; and turned out to be a political tool to transform everyday urban life. The three main concepts of psychogeography [walking, dérive, and palimpsest] construct the epistemological framework for a psychogeographic spatial analysis. Mental representations investigating this framework would provide a designer to capture the invisible layers of the gap between ‘how a space is conceived’ and ‘how the same space is perceived and experienced.’ This gap is a neglected but critical issue to discuss in the planning discipline, and psychogeography provides methodological inputs to cover the interrelation among top-down designs of urban patterning and bottom-up reproductions of ‘the soul’ of urban space at the intersection of geography and psychology. City centers and university campuses exemplify opposite poles of spatial organization and walking practice, which may result in differentiated spatial appropriation forms. There is a traditional city center in Van, located at the core of the city with a dense population and several activities, but not connected to Van Lake, which is the largest lake in the country. On the other hand, the university campus is located at the periphery, and although it has a promenade along the lake’s coast and a regional hospital, it presents a limited walking experience with ambiguous forms of spatial appropriation. The city center draws a vivid urban everyday life; however, the campus presents a relatively natural life far away from the center. This paper aims to reveal the differentiated psychogeographic maps of spatial appropriation at the city center vs. the university campus, which is located at the periphery of the city and along the coast of the largest lake in Turkey. The main question of the paper is, “how do the psychogeographic maps of spatial appropriation differentiate at the city center and university campus in Van within the walking experience with reference to the two-folded map assumption.” The experiential maps of a core group of 15 planning students will be created with the techniques of mental mapping, photographing, and narratives through attentive walks conducted together on selected routes; in addition to these attentive walks, 30 more in-depth interviews will be conducted by the core group. The narrative of psychogeographic mapping of spatial appropriation at the two spatial poles would display the conflicting soul of the city with reference to sub-behavioural regions of walking, differentiated forms of derive and layers of palimpsest.

Keywords: attentive walk, body, cognitive geography, derive, experiential maps, psychogeography, Van, Turkey

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Authors: Seini G. Kaufusi

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Background. Physician-assisted death (PAD) has and continues to be a controversial issue in the U.S. Dying with dignity statutes exists in 9 U.S. jurisdictions that permit competent adults diagnosed with a terminal illness and given a prognosis of 6 month or less to live to request medication to hasten death. Robust advocacy for and against PAD influences policy, and opinions vary. Aim. This study aims to explore the association between race and the attitudes toward physician-assisted death in the U.S. Methods. Data for this study derives from the General Social Survey (GSS) dataset, a national survey conducted by the National Opinion Research Center (NORC) that focuses on the opinions and values of American’s. A cross-sectional design and probability sample from the 2018 data set was used to randomly select respondents. Results. The results indicated that race is significantly associated with attitudes towards physician-assisted death. The level of significance suggests a strong positive association, and the direction indicated that Black and Other racial groups have higher rates of positive decision about PAD. Conclusion. Although attitudes towards PAD varied, Black and other racial groups had favorable decisions for PAD. Further research is crucial in the continuous debate on PAD and understanding the influences of predictors for or against PAD.

Keywords: attitudes, euthanasia, physician-assisted death, race

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Authors: Hotlan Siagian, Hatane Semuel, Wilma Laura Sahetapy

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This study aims at examining the effect of market orientation on marketing performance through product adaptation strategy. The population of the research is domestic leather craft companies located in five regions, the center of the leather craft industry in Indonesia, i.e., Central Java, East Java, South Sulawesi, Bali, and West Kalimantan. The respondent consists of a manager level from each company. Data collection used a questionnaire designed with five-item Likert scale. Collected data were analyzed using structural equation modeling (SEM) technique with SmartPLS software version 3.0 to examine the hypotheses. The result of the study shows that all hypotheses are supported. Market orientation affects marketing performance. Market orientation affects product adaptation strategy. Product adaptation strategy influences the marketing performance. The research also has revealed the main finding that product adaptation strategy contributes to a mediating role in the market orientation strategy and marketing performance relationship. The leather craft companies in Indonesia, therefore, may refer to this result in improving their marketing performance.

Keywords: leather craft industry, market orientation, marketing performance, product adaptation strategy

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Authors: Napasri Suwanajote

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The purposes of this research were to analyze and evaluate successful factors in OTOP production process for the developing of learning center on OTOP production process based on Sufficiency Economic Philosophy for sustainable life quality. The research has been designed as a qualitative study to gather information from 30 OTOP producers in Bangkontee District, Samudsongkram Province. They were all interviewed on 3 main parts. Part 1 was about the production process including 1) production, 2) product development, 3) the community strength, 4) marketing possibility, and 5) product quality. Part 2 evaluated appropriate successful factors including 1) the analysis of the successful factors, 2) evaluate the strategy based on Sufficiency Economic Philosophy, and 3) the model of learning center on OTOP production process based on Sufficiency Economic Philosophy for sustainable life quality. The results showed that the production did not affect the environment with potential in continuing standard quality production. They used the raw materials in the country. On the aspect of product and community strength in the past 1 year, it was found that there was no appropriate packaging showing product identity according to global market standard. They needed the training on packaging especially for food and drink products. On the aspect of product quality and product specification, it was found that the products were certified by the local OTOP standard. There should be a responsible organization to help the uncertified producers pass the standard. However, there was a problem on food contamination which was hazardous to the consumers. The producers should cooperate with the government sector or educational institutes involving with food processing to reach FDA standard. The results from small group discussion showed that the community expected high education and better standard living. Some problems reported by the community included informal debt and drugs in the community. There were 8 steps in developing the model of learning center on OTOP production process based on Sufficiency Economic Philosophy for sustainable life quality.

Keywords: production process, OTOP, sufficiency economic philosophy, language choice

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Authors: Ilirian Laçi, Alketa Spahiu

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Big strums of thyroid glandule observed by a simple viewing can be witnessed in everyday life. Medical cabinets evidence patients withpalpablenodes of thyroid glandule, mainly nodes of the size of 10 millimeters. Further, more cases which have resulted in negative under palpation have resulted in positive at ultrasound examination. Therefore, the use of ultrasound for diagnosing has increased the number of patients with nodes of thyroid glandule in the last couple of decades in all countries, Albania included. Thus, there has been evidence of an increased number of patients affected by this pathology, where female patients dominate. Demographically, the capital shows high numbers due to the high population, but of interest is the high incidence of those areas distanced from the sea. While regarding related pathologies, no significant link was evidenced, an element of ancestry was evident in the nodes of the thyroid glandule. When we talk of nodes of the thyroid glandule, we should consider hyperplasia, neoplasia, and inflammatory diseases that cause nodes of the thyroid glandule. This increase parallels the world’s increase of the incidence of thyroid glandule, with malign cases, which are at about 5% and are not depended on size. Given the numbers, with most thyroid glandule nodes being benign, the main objective of the examination of the nodes was the determination of benign and malign cases to avoid undue surgery. Subject of this study were 212 patients that underwent fine-needle aspiration (FNA) under ultrasound guidance at the Medical University Center of Tirana. All the patients came to the Mother Teresa University Hospital from public and private hospitals and other polyclinics. These patients had an ultrasound examination before visiting the Center of Nuclear Medicine for a scintigraph of thyroid glandule in the period September 2016 and September 2017. To correlate, all patients had been examined via ultrasound of the thyroid glandule prior to the scintigraph. The ultrasound included evaluation of the number of nodes, their size, their solid, cystic, or solid-cystic structure, echogenicity according to the gray scale, the presence of calcification, the presence of lymph nodes, the presence of adenopathy, and the correlation of the cytology results from the Laboratory of Pathological Anatomy of Medical University Center of Tirana.

Keywords: thyroid nodes, fine needle aspiration, ultrasound, scintigraphy

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Authors: Andrew Shugyo Daijo Bonnici

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Core-Self Intelligence (CSI) is an absolutely still, non-verbal, non-cerebral intelligence. Our still core-self intelligence is felt at our body's center point of gravity, just an inch below our navel, deep within our lower abdomen. The still sub-quantum depth of core-Self remains untouched by the conditioning influences of family, society, culture, religion, and spiritual views that shape our personalities and ego-self identities. As core-Self intelligence is inborn and unconditioned, it exists within all human beings regardless of age, race, color, creed, mental acuity, or national origin. Our core-self intelligence functions as a wise and compassionate guide that advances our health and well-being, our mental clarity and emotional resiliency, our fearless peace and behavioral wisdom, and our ever-deepening compassion for self and others. Although our core-Self, with its absolutely still non-judgmental intelligence, operates far beneath the functioning of our ego-self identity and our thinking mind, it effectively coexists with our passing thoughts, all of our figuring and thinking, our logical and rational way of knowing, the ebb and flow of our feelings, and the natural or triggered emergence of our emotions. When we allow our whole inner somatic awareness to gently sink into the intelligent center point of gravity within our lower abdomen, the felt arising of our core- Self’s inborn stillness has a serene and relaxing effect on our ego-self and thinking mind. It naturally slows down the speedy passage of our involuntary thoughts, diminishes our ego-self's defensive and reactive functioning, and decreases narcissistic reflections on I, me, and mine. All of these healthy cognitive benefits advance our innate wisdom and compassion, facilitate our personal and interpersonal growth, and liberate the ever-fresh wonder and curiosity of our beginner's heartmind. In conclusion, by studying, exploring, and researching our core-Self intelligence, psychologists and psychotherapists can unlock new avenues for advancing the farther reaches of our mental, emotional, and spiritual health and well-being, our innate behavioral wisdom and boundless empathy, our lucid compassion for self and others, and our unwavering confidence in the still guiding light of our core-Self that exists at the abdominal center point of all human beings.

Keywords: intelligence, transpersonal, beginner’s heartmind, compassionate wisdom

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Authors: Syed Iftikhar Hussain Shah, Vasilis Peristeras, Ioannis Magnisalis

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Data that is high in volume, velocity, veracity and comes from a variety of sources is usually generated in all sectors including the government sector. Globally public administrations are pursuing (big) data as new technology and trying to adopt a data-centric architecture for hosting and sharing data. Properly executed, big data and data analytics in the government (big) data ecosystem can be led to data-driven government and have a direct impact on the way policymakers work and citizens interact with governments. In this research paper, we conduct a systematic literature review. The main aims of this paper are to highlight essential aspects of the government (big) data ecosystem and to explore the most critical socio-technical factors that contribute to the successful implementation of government (big) data ecosystem. The essential aspects of government (big) data ecosystem include definition, data types, data lifecycle models, and actors and their roles. We also discuss the potential impact of (big) data in public administration and gaps in the government data ecosystems literature. As this is a new topic, we did not find specific articles on government (big) data ecosystem and therefore focused our research on various relevant areas like humanitarian data, open government data, scientific research data, industry data, etc.

Keywords: applications of big data, big data, big data types. big data ecosystem, critical success factors, data-driven government, egovernment, gaps in data ecosystems, government (big) data, literature review, public administration, systematic review

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Authors: Anli Du Preez, James Bekker

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Data is currently one of the most critical and influential emerging technologies. However, the true potential of data is yet to be exploited since, currently, about 1% of generated data are ever actually analyzed for value creation. There is a data gap where data is not explored due to the lack of data analytics infrastructure and the required data analytics skills. This study developed a decision support framework for data analytics by following Jabareen’s framework development methodology. The study focused on machine learning algorithms, which is a subset of data analytics. The developed framework is designed to assist data analysts with little experience, in choosing the appropriate machine learning algorithm given the purpose of their application.

Keywords: Data analytics, Industrial engineering, Machine learning, Value creation

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Authors: N. Smaoui, B. Chentouf

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The boundary stabilization problem of the rotating disk-beam system is a topic of interest in research studies. This system involves a flexible beam attached to the center of a disk, and the control and stabilization of this system have been extensively studied. This research focuses on the case where the center of mass is fixed in an inertial frame, and the rotation of the center is non-uniform. The system is represented by a set of nonlinear coupled partial differential equations and ordinary differential equations. The boundary stabilization problem of this system via a delayed boundary control is considered. We assume that the boundary control is either of a force type control or a moment type control and is subject to the presence of a constant time-delay. The aim of this research is threefold: First, we demonstrate that the rotating disk-beam system is well-posed in an appropriate functional space. Then, we establish the exponential stability property of the system. Finally, we provide numerical simulations that illustrate the theoretical findings. The research utilizes the semigroup theory to establish the well-posedness of the system. The resolvent method is then employed to prove the exponential stability property. Finally, the finite element method is used to demonstrate the theoretical results through numerical simulations. The research findings indicate that the rotating disk-beam system can be stabilized using a boundary control with a time delay. The proof of stability is based on the resolvent method and a variation of constants formula. The numerical simulations further illustrate the theoretical results. The findings have potential implications for the design and implementation of control strategies in similar systems. In conclusion, this research demonstrates that the rotating disk-beam system can be stabilized using a boundary control with time delay. The well-posedness and exponential stability properties are established through theoretical analysis, and these findings are further supported by numerical simulations. The research contributes to the understanding and practical application of control strategies for flexible structures, providing insights into the stability of rotating disk-beam systems.

Keywords: rotating disk-beam, delayed force control, delayed moment control, torque control, exponential stability

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Authors: Jaleh Shoshtarian Malak, Niloofar Mohamadzadeh

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Managing pre-hospital emergency patients requires real-time practices and efficient resource utilization. Since we are facing a distributed Network of healthcare providers, services and applications choosing the right resources and treatment protocol considering patient situation is a critical task. Delivering care to emergency patients at right time and with the suitable treatment settings can save ones live and prevent further complication. In recent years Multi Agent Systems (MAS) introduced great solutions to deal with real-time, distributed and complicated problems. In this paper we propose a multi agent based pre-hospital emergency management architecture in order to manage coordination, collaboration, treatment protocol and healthcare provider selection between different parties in pre-hospital emergency in a self-organizing manner. We used AnyLogic Agent Based Modeling (ABM) tool in order to simulate our proposed architecture. We have analyzed and described the functionality of EMS center, Ambulance, Consultation Center, EHR Repository and Quality of Care Monitoring as main collaborating agents. Future work includes implementation of the proposed architecture and evaluation of its impact on patient quality of care improvement.

Keywords: multi agent systems, pre-hospital emergency, simulation, software architecture

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Authors: Sharon Hovav, Ilya Levner, Oren Nahum, Istvan Szabo

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In modern large-scale logistic centers (e.g., big automated warehouses), complex logistic operations performed by human staff (pickers) need to be coordinated with the operations of automated facilities (robots, conveyors, cranes, lifts, flow racks, etc.). The efficiency of advanced logistic centers strongly depends on optimizing picking technologies in synch with the facility/product layout, as well as on optimal distribution of material flows (products) in the system. The challenge is to develop a mathematical operations research (OR) tool that will optimize system cost-effectiveness. In this work, we propose a model that describes an automatic logistic center consisting of a set of workstations located at several galleries (floors), with each station containing a known number of flow racks. The requirements of each product and the working capacity of stations served by a given set of workers (pickers) are assumed as predetermined. The goal of the model is to maximize system efficiency. The proposed model includes two echelons. The first is the setting of the (optimal) number of workstations needed to create the total processing/logistic system, subject to picker capacities. The second echelon deals with the assignment of the products to the workstations and flow racks, aimed to achieve maximal throughputs of picked products over the entire system given picker capacities and budget constraints. The solutions to the problems at the two echelons interact to balance the overall load in the flow racks and maximize overall efficiency. We have developed an operations research model within each echelon. In the first echelon, the problem of calculating the optimal number of workstations is formulated as a non-standard bin-packing problem with capacity constraints for each bin. The problem arising in the second echelon is presented as a constrained product-workstation-flow rack assignment problem with non-standard mini-max criteria in which the workload maximum is calculated across all workstations in the center and the exterior minimum is calculated across all possible product-workstation-flow rack assignments. The OR problems arising in each echelon are proved to be NP-hard. Consequently, we find and develop heuristic and approximation solution algorithms based on exploiting and improving local optimums. The LC model considered in this work is highly dynamic and is recalculated periodically based on updated demand forecasts that reflect market trends, technological changes, seasonality, and the introduction of new items. The suggested two-echelon approach and the min-max balancing scheme are shown to work effectively on illustrative examples and real-life logistic data.

Keywords: logistics center, product-workstation, assignment, maximum performance, load balancing, fast algorithm

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Authors: Pennapa Palapin

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This study aimed to examine the management and development of forest tourism Kamchanoad. Ban Dung, Udon Thani sustainability. Data were collected by means of qualitative research including in-depth interviews, semi-structured, and then the data were summarized and discussed in accordance with the objectives. And make a presentation in the form of lectures. The target population for the study consisted of 16 people, including representatives from government agencies, community leaders and the community. The results showed that Guidelines for the Management and Development of Forest Tourism Kamchanoad include management of buildings and infrastructure such as roads, water, electricity, toilets. Other developments are the establishment of a service center that provides information and resources to facilitate tourists.; nature trails and informative signage to educate visitors on the path to the jungle Kamchanoad; forest activities for tourists who are interested only in occasional educational activities such as vegetation, etc.; disseminating information on various aspects of tourism through various channels in both Thailand and English, as well as a website to encourage community involvement in the planning and management of tourism together with the care and preservation of natural resources and preserving the local cultural tourist area of Kamchanoad.

Keywords: guidelines for the management and development, forest tourism, Kamchanoad, sustainability

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Authors: Annapureddy Srikant Reddy, Atthanti Mahendra, Samala Chinni Krishna, N. Neelima

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In our present world, we are generating a lot of data and we, need a specific device to store all these data. Generally, we store data in pen drives, hard drives, etc. Sometimes we may loss the data due to the corruption of devices. To overcome all these issues, we implemented a cloud space for storing the data, and it provides more security to the data. We can access the data with just using the internet from anywhere in the world. We implemented all these with the java using Net beans IDE. Once user uploads the data, he does not have any rights to change the data. Users uploaded files are stored in the cloud with the file name as system time and the directory will be created with some random words. Cloud accepts the data only if the size of the file is less than 2MB.

Keywords: cloud space, AES, FTP, NetBeans IDE

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Authors: Jamileh Vasheghani Farahani

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The main purpose of this research is to show the current active faults and active tectonic of the area by three seismic networks in Tehran region: 1-Tehran Disaster Mitigation and Management Organization (TDMMO), 2-Broadband Iranian National Seismic Network Center (BIN), 3-Iranian Seismological Center (IRSC). In this study, we analyzed microearthquakes happened in Tehran city and its surroundings using the Tehran networks from 1996 to 2015. We found some active faults and trends in the region. There is a 200-year history of historical earthquakes in Tehran. Historical and instrumental seismicity show that the east of Tehran is more active than the west. The Mosha fault in the North of Tehran is one of the active faults of the central Alborz. Moreover, other major faults in the region are Kahrizak, Eyvanakey, Parchin and North Tehran faults. An important seismicity region is an intersection of the Mosha and North Tehran fault systems (Kalan village in Lavasan). This region shows a cluster of microearthquakes. According to the historical and microseismic events analyzed in this research, there is a seismic gap in SE of Tehran. The empirical relationship is used to assess the Mmax based on the rupture length. There is a probability of occurrence of a strong motion of 7.0 to 7.5 magnitudes in the region (based on the assessed capability of the major faults such as Parchin and Eyvanekey faults and historical earthquakes).

Keywords: Iran, major faults, microseismicity, Tehran

Procedia PDF Downloads 365

Authors: Elham A. Kwildi, Yahia S. Abugnah, Nuri S. Madi

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This study was designed to evaluate the microbiological quality and safety of two types of salads prepared at a catering center affiliated with Libyan Airlines in Tripoli, Libya. Two hundred and twenty-one (221) samples (132 economy-class and 89 first- class) were used in this project which lasted for ten months. Biweekly, microbiological tests were performed which included total plate count (TPC) and total coliforms (TCF), in addition to enumeration and/or detection of some pathogenic bacteria mainly Escherichia coli, Staphylococcus aureus, Bacillus cereus, Salmonella sp, Listeria sp and Vibrio parahaemolyticus parahaemolyticus, By using conventional as well as compact dry methods. Results indicated that TPC of type 1 salad ranged between (<10 – 62 x 103 cfu/gm) and (<10 to 36 x103 cfu/g), while TCF were (<10 – 41 x 103 cfu/gm) and (< 10 to 66 x102 cfu/g) using both methods of detection respectively. On the other hand, TPC of type 2 salad were: (1 × 10 – 52 x 103) and (<10 – 55 x 103 cfu/gm) and in the range of (1 x10 to 45x103 cfu/g), and the (TCF) counts were between (< 10 to 55x103 cfu/g) and (< 10 to 34 x103 cfu/g) using the 1st and the 2nd methods of detection respectively. Also, the pathogens mentioned above were detected in both types of salads, but their levels varied according to the type of salad and the method of detection. The level of Staphylococcus aureus, for instance, was 17.4% using conventional method versus 14.4% using the compact dry method. Similarly, E. coli was 7.6% and 9.8%, while Salmonella sp. recorded the least percentage i.e. 3% and 3.8% with the two mentioned methods respectively. First class salads were also found to contain the same pathogens, but the level of E. coli was relatively higher in this case (14.6% and 16.9%) using conventional and compact dry methods respectively. The second rank came Staphylococcus aureus (13.5%) and (11.2%), followed by Salmonella (6.74%) and 6.70%). The least percentage was for Vibrio parahaemolyticus (4.9%) which was detected in the first class salads only. The other two pathogens Bacillus cereus and Listeria sp. were not detected in either one of the salads. Finally, it is worth mentioning that there was a significant decline in TPC and TCF counts in addition to the disappearance of pathogenic bacteria after the 6-7th month of the study which coincided with the first trial of the HACCP system at the center. The ups and downs in the counts along the early stages of the study reveal that there is a need for some important correction measures including more emphasis on training of the personnel in applying the HACCP system effectively.

Keywords: air travel, vegetable salads, foodborne outbreaks, Libya

Procedia PDF Downloads 326

Authors: Jennifer Sturgeon

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Stable relationships provide a predictable and trusting environment and are essential for early development, but high teacher turnover rates in childcare settings make it challenging for infants and toddlers to form stable relationships with their teachers. This can have an adverse effect on development and learning. The qualitative study discussed in this article draws from the experiences of early Head Start teachers and administrators to describe both the impact of teacher turnover and the motivational factors that contribute to teacher retention. A case study approach was used and included classroom observations, a review of exit interviews, and perceptions from focus groups of early Head Start staff in an urban early Head Start childcare center. Emerging from the case study was the discovery that teacher turnover has an impact on the social-emotional development of toddlers, particularly in self-regulation. Additional key findings that emerged include teacher turnover leading to negative effects on learning, a decrease in preschool preparation, and increased chaos in the classroom and center. Motivational factors that contributed to teacher retention included positive leadership, the mission to make a difference, and fair compensation.

Keywords: early childhood, teacher turnover, continuity of care, early head start

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Authors: Linus O. Asuquo

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Mining in Nigeria and development effort of metallurgical technologies at National Metallurgical Development Centre Jos has been addressed in this paper. The paper has looked at the history of mining in Nigeria, the impact of mining on social and industrial development, and the contribution of the mining sector to Nigeria’s Gross Domestic Product (GDP). The paper clearly stated that Nigeria’s mining sector only contributes 0.5% to the nation’s GDP unlike Botswana that the mining sector contributes 38% to the nation’s GDP. Nigeria Bureau of Statistics has it on record that Nigeria has about 44 solid minerals awaiting to be exploited. Clearly highlighted by this paper is the abundant potentials that exist in the mining sector for investment. The paper made an exposition on the extensive efforts made at National Metallurgical Development Center (NMDC) to develop metallurgical technologies in various areas of the metals sector; like mineral processing, foundry development, nonferrous metals extraction, materials testing, lime calcination, ANO (Trade name for powder lubricant) wire drawing lubricant, refractories and many others. The paper went ahead to draw a conclusion that there is a need to develop the mining sector in Nigeria and to give a sustainable support to the efforts currently made at NMDC to develop metallurgical technologies which are capable of transforming the metals sector in Nigeria, which will lead to industrialization. Finally the paper made some recommendations which traverse the topic for the best expectation.

Keywords: mining, minerals, technologies, value addition

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Authors: Imbesat Daudi

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Islamophobia, which is a billion-dollar industry, is widespread, especially in the United States, Europe, India, Israel, and countries that have Muslim minorities at odds with their governmental policies. Hatred of Islam in the West did not evolve spontaneously; it was methodically created. Islamophobia's current format has been designed to spread on its own, find a space in the Western psyche, and resist its eradication. Hatred has been sustained by neoconservative ideologues and their allies, which are supported by the mainstream media. Social scientists have evaluated how ideas spread, why any idea can go viral, and where new ideas find space in our brains. This was possible because of the advances in the computational power of software and computers. Spreading of ideas, including Islamophobia, follows a sine curve; it has three phases: An initial exploratory phase with a long lag period, an explosive phase if ideas go viral, and the final phase when ideas find space in the human psyche. In the initial phase, the ideas are quickly examined in a center in the prefrontal lobe. When it is deemed relevant, it is sent for evaluation to another center of the prefrontal lobe; there, it is critically examined. Once it takes a final shape, the idea is sent as a final product to a center in the occipital lobe. This center cannot critically evaluate ideas; it can only defend them from its critics. Counterarguments, no matter how scientific, are automatically rejected. Therefore, arguments that could be highly effective in the early phases are counterproductive once they are stored in the occipital lobe. Anti-Islamophobic intellectuals have done a very good job of countering Islamophobic arguments. However, they have not been as effective as neoconservative ideologues who have promoted anti-Muslim rhetoric that was based on half-truths, misinformation, or outright lies. The failure is partly due to the support pro-war activists receive from the mainstream media, state institutions, mega-corporations engaged in violent conflicts, and think tanks that provide Islamophobic arguments. However, there are also scientific reasons why anti-Islamophobic thinkers have been less effective. There are different dynamics of spreading ideas once they are stored in the occipital lobe. The human brain is incapable of evaluating further once it accepts ideas as its own; therefore, a different strategy is required to be effective. This paper examines 1) why anti-Islamophobic intellectuals have failed in changing the minds of non-Muslims and 2) the steps of countering hatred. Simply put, a new strategy is needed that can effectively counteract hatred of Islam and Muslims. Islamophobia is a disease that requires strong measures. Fighting hatred is always a challenge, but if we understand why Islamophobia is taking root in the twenty-first century, one can succeed in challenging Islamophobic arguments. That will need a coordinated effort of Intellectuals, writers and the media.

Keywords: islamophobia, Islam and violence, anti-islamophobia, demonization of Islam

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Authors: Rokhmatul Insani, Hira Laksmiwati Soemitro

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Business Intelligence is a methodology that exploits the data to produce information and knowledge systematically, business intelligence can support the decision-making process. Some methods in business intelligence are data warehouse and data mining. A data warehouse can store historical data from transactional data. For data modelling in data warehouse, we apply dimensional modelling by Kimball. While data mining is used to extracting patterns from the data and get insight from the data. Data mining has many techniques, one of which is segmentation. For profiling of telecommunication customer, we use customer segmentation according to customer’s usage of services, customer invoice and customer payment. Customers can be grouped according to their characteristics and can be identified the profitable customers. We apply K-Means Clustering Algorithm for segmentation. The input variable for that algorithm we use RFM (Recency, Frequency and Monetary) model. All process in data mining, we use tools IBM SPSS modeller.

Keywords: business intelligence, customer segmentation, data warehouse, data mining

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Authors: George Charkoftakis, Panagiotis Liosatos, Nicolas-Alexander Tatlas, Dimitrios Goustouridis, Stelios M. Potirakis

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E-maintenance is a relatively new concept, generally referring to maintenance management by monitoring assets over the Internet. One of the key links in the chain of an e-maintenance system is data acquisition and transmission. Specifically for the case of a fleet of heavy-duty vehicles, where the main challenge is the diversity of the vehicles and vehicle-embedded self-diagnostic/reporting technologies, the design of the data acquisition and transmission unit is a demanding task. This clear if one takes into account that a heavy-vehicles fleet assortment may range from vehicles with only a limited number of analog sensors monitored by dashboard light indicators and gauges to vehicles with plethora of sensors monitored by a vehicle computer producing digital reporting. The present work proposes an adaptable internet of things (IoT) sensor node that is capable of addressing this challenge. The proposed sensor node architecture is based on the increasingly popular single-board computer – expansion boards approach. In the proposed solution, the expansion boards undertake the tasks of position identification by means of a global navigation satellite system (GNSS), cellular connectivity by means of 3G/long-term evolution (LTE) modem, connectivity to on-board diagnostics (OBD), and connectivity to analog and digital sensors by means of a novel design of expansion board. Specifically, the later provides eight analog plus three digital sensor channels, as well as one on-board temperature / relative humidity sensor. The specific device offers a number of adaptability features based on appropriate zero-ohm resistor placement and appropriate value selection for limited number of passive components. For example, although in the standard configuration four voltage analog channels with constant voltage sources for the power supply of the corresponding sensors are available, up to two of these voltage channels can be converted to provide power to the connected sensors by means of corresponding constant current source circuits, whereas all parameters of analog sensor power supply and matching circuits are fully configurable offering the advantage of covering a wide variety of industrial sensors. Note that a key feature of the proposed sensor node, ensuring the reliable operation of the connected sensors, is the appropriate supply of external power to the connected sensors and their proper matching to the IoT sensor node. In standard mode, the IoT sensor node communicates to the data center through 3G/LTE, transmitting all digital/digitized sensor data, IoT device identity, and position. Moreover, the proposed IoT sensor node offers WiFi connectivity to mobile devices (smartphones, tablets) equipped with an appropriate application for the manual registration of vehicle- and driver-specific information, and these data are also forwarded to the data center. All control and communication tasks of the IoT sensor node are performed by dedicated firmware. It is programmed with a high-level language (Python) on top of a modern operating system (Linux). Acknowledgment: This research has been co-financed by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship, and Innovation, under the call RESEARCH—CREATE—INNOVATE (project code: T1EDK- 01359, IntelligentLogger).

Keywords: IoT sensor nodes, e-maintenance, single-board computers, sensor expansion boards, on-board diagnostics

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Authors: Arindam Chaudhuri

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Classification of data has been actively used for most effective and efficient means of conveying knowledge and information to users. The prima face has always been upon techniques for extracting useful knowledge from data such that returns are maximized. With emergence of huge datasets the existing classification techniques often fail to produce desirable results. The challenge lies in analyzing and understanding characteristics of massive data sets by retrieving useful geometric and statistical patterns. We propose a supervised parallel fuzzy rough support vector machine (PFRSVM) for data classification in cloud environment. The classification is performed by PFRSVM using hyperbolic tangent kernel. The fuzzy rough set model takes care of sensitiveness of noisy samples and handles impreciseness in training samples bringing robustness to results. The membership function is function of center and radius of each class in feature space and is represented with kernel. It plays an important role towards sampling the decision surface. The success of PFRSVM is governed by choosing appropriate parameter values. The training samples are either linear or nonlinear separable. The different input points make unique contributions to decision surface. The algorithm is parallelized with a view to reduce training times. The system is built on support vector machine library using Hadoop implementation of MapReduce. The algorithm is tested on large data sets to check its feasibility and convergence. The performance of classifier is also assessed in terms of number of support vectors. The challenges encountered towards implementing big data classification in machine learning frameworks are also discussed. The experiments are done on the cloud environment available at University of Technology and Management, India. The results are illustrated for Gaussian RBF and Bayesian kernels. The effect of variability in prediction and generalization of PFRSVM is examined with respect to values of parameter C. It effectively resolves outliers’ effects, imbalance and overlapping class problems, normalizes to unseen data and relaxes dependency between features and labels. The average classification accuracy for PFRSVM is better than other classifiers for both Gaussian RBF and Bayesian kernels. The experimental results on both synthetic and real data sets clearly demonstrate the superiority of the proposed technique.

Keywords: FRSVM, Hadoop, MapReduce, PFRSVM

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Authors: Esra Danaci, Tugba Kavalali Erdogan, Sevil Masat, Selin Keskin Kiziltepe, Tugba Cinarli, Zeliha Koc

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This study was conducted in a descriptive and cross-sectional manner to determine that factors that influence the self-efficacy and self-sufficiency levels among oncology patients. The research was conducted between January 24, 2017 and September 24, 2017 in the oncology and hematology departments of a university hospital in Turkey with 179 voluntary inpatients. The data were collected through the Self-Sufficiency/Self-Efficacy Scale and a 29-question survey, which was prepared in order to determine the sociodemographic and clinical properties of the patients. The Self-Sufficiency/Self-Efficacy Scale is a Likert-type scale with 23 articles. The scale scores range between 23 and 115. A high final score indicates a good self-sufficiency/self-efficacy perception for the individual. The data were analyzed using percentage analysis, one-way ANOVA, Mann Whitney U-test, Kruskal Wallis test and Tukey test. The demographic data of the subjects were as follows: 57.5% were male and 42.5% were female, 82.7% were married, 46.4% were primary school graduate, 36.3% were housewives, 19% were employed, 93.3% had social security, 52.5% had matching expenses and incomes, 49.2% lived in the center of the city. The mean age was 57.1±14.6. It was determined that 22.3% of the patients had lung cancer, 19.6% had leukemia, and 43.6% had a good overall condition. The mean self-sufficiency/self-efficacy score was 83,00 (41-115). It was determined that the patients' self-sufficiency/self-efficacy scores were influenced by some of their socio-demographic and clinical properties. This study has found that the patients had high self-sufficiency/self-efficacy scores. It is recommended that the nursing care plans should be developed to improve their self-sufficiency/self-efficacy levels in the light of the patients' sociodemographic and clinical properties.

Keywords: oncology, patient, self-efficacy, self-sufficiency

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Authors: F. Calderón-Vega, A. D. García-Soto, C. Mösso

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Recorded significant wave heights sometimes exhibit large uncommon values (outliers) that can be associated with extreme phenomena such as hurricanes and cold fronts. In this study, some extremely large wave heights recorded in NOAA buoys (National Data Buoy Center, noaa.gov) are used to investigate their effect in the prediction of future wave heights associated with given return periods. Extreme waves are predicted through a time-dependent model based on the so-called generalized extreme value distribution. It is found that the outliers do affect the estimated wave heights. It is concluded that a detailed inspection of outliers is envisaged to determine whether they are real recorded values since this will impact defining design wave heights for coastal protection purposes.

Keywords: GEV model, non-stationary, seasonality, outliers

Procedia PDF Downloads 195