Search results for: scientific data mining

Authors: Jane O. Munonye

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Climate change has both negative and positive effects in agricultural production. For agriculture to be sustainable in adverse climate change condition, some natural measures are needed. The issue is to produce more food with available natural resources and reduce the contribution of agriculture to climate change. The study reviewed climate change and sustainable agriculture in southeast Nigeria. Data from the study were from secondary sources. Ten scientific papers were consulted and data for the review were collected from three. The objectives of the paper were as follows: to review the effect of climate change on one major arable crop in southeast Nigeria (yam; Dioscorea rotundata); evident of climate change impact and methods for sustainable agricultural production in adverse weather condition. Some climatic parameter as sunshine, relative humidity and rainfall have negative relationship with yam production and significant at 10% probability. Crop production was predicted to decline by 25% per hectare by 2060 while livestock production has increased the incidence of diseases and pathogens as the major effect to agriculture. Methods for sustainable agriculture and damage of natural resources by climate change were highlighted. Agriculture needs to be transformed as climate changes to enable the sector to be sustainable. There should be a policy in place to facilitate the integration of sustainability in Nigeria agriculture.

Keywords: agriculture, climate change, sustainability, yam

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Authors: Sıdıka Kaya, Gülay Sain Güven, Seda Karsavuran, Onur Toka

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This study is part of an ongoing research project supported by the Scientific and Technological Research Council of Turkey (TUBITAK) under Project Number 114K404, and participation to this conference was supported by Hacettepe University Scientific Research Coordination Unit under Project Number 10243. Evaluation of hospital readmissions is gaining importance in terms of quality and cost, and is becoming the target of national policies. In Turkey, the topic of hospital readmission is relatively new on agenda and very few studies have been conducted on this topic. The aim of this study was to determine 30-day readmission rates and risk factors for readmission. Whether readmission was planned, related to the prior admission and avoidable or not was also assessed. The study was designed as a ‘prospective cohort study.’ 472 patients hospitalized in internal medicine departments of a university hospital in Turkey between February 1, 2015 and April 30, 2015 were followed up. Analyses were conducted using IBM SPSS Statistics version 22.0 and SPSS Modeler 16.0. Average age of the patients was 56 and 56% of the patients were female. Among these patients 95 were readmitted. Overall readmission rate was calculated as 20% (95/472). However, only 31 readmissions were unplanned. Unplanned readmission rate was 6.5% (31/472). Out of 31 unplanned readmission, 24 was related to the prior admission. Only 6 related readmission was avoidable. To determine risk factors for readmission we constructed Chi-square automatic interaction detector (CHAID) decision tree algorithm. CHAID decision trees are nonparametric procedures that make no assumptions of the underlying data. This algorithm determines how independent variables best combine to predict a binary outcome based on ‘if-then’ logic by portioning each independent variable into mutually exclusive subsets based on homogeneity of the data. Independent variables we included in the analysis were: clinic of the department, occupied beds/total number of beds in the clinic at the time of discharge, age, gender, marital status, educational level, distance to residence (km), number of people living with the patient, any person to help his/her care at home after discharge (yes/no), regular source (physician) of care (yes/no), day of discharge, length of stay, ICU utilization (yes/no), total comorbidity score, means for each 3 dimensions of Readiness for Hospital Discharge Scale (patient’s personal status, patient’s knowledge, and patient’s coping ability) and number of daycare admissions within 30 days of discharge. In the analysis, we included all 95 readmitted patients (46.12%), but only 111 (53.88%) non-readmitted patients, although we had 377 non-readmitted patients, to balance data. The risk factors for readmission were found as total comorbidity score, gender, patient’s coping ability, and patient’s knowledge. The strongest identifying factor for readmission was comorbidity score. If patients’ comorbidity score was higher than 1, the risk for readmission increased. The results of this study needs to be validated by other data–sets with more patients. However, we believe that this study will guide further studies of readmission and CHAID is a useful tool for identifying risk factors for readmission.

Keywords: decision tree, hospital, internal medicine, readmission

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Authors: Fally Titikpina, Abderafi Charki, Antoine Caucheteux, David Bigaud

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The building sector is one of the largest energy consumer with about 40% of the final energy consumption in the European Union. Ensuring building energy performance is of scientific, technological and sociological matter. To assess a building energy performance, the consumption being predicted or estimated during the design stage is compared with the measured consumption when the building is operational. When valuing this performance, many buildings show significant differences between the calculated and measured consumption. In order to assess the performance accurately and ensure the thermal efficiency of the building, it is necessary to evaluate the uncertainties involved not only in measurement but also those induced by the propagation of dynamic and static input data in the model being used. The evaluation of measurement uncertainty is based on both the knowledge about the measurement process and the input quantities which influence the result of measurement. Measurement uncertainty can be evaluated within the framework of conventional statistics presented in the \textit{Guide to the Expression of Measurement Uncertainty (GUM)} as well as by Bayesian Statistical Theory (BST). Another choice is the use of numerical methods like Monte Carlo Simulation (MCS). In this paper, we proposed to evaluate the uncertainty associated to the use of a simplified model for the estimation of the energy consumption of a given building. A detailed review and discussion of these three approaches (GUM, MCS and BST) is given. Therefore, an office building has been monitored and multiple sensors have been mounted on candidate locations to get required data. The monitored zone is composed of six offices and has an overall surface of 102 $m^2$. Temperature data, electrical and heating consumption, windows opening and occupancy rate are the features for our research work.

Keywords: building energy performance, uncertainty evaluation, GUM, bayesian approach, monte carlo method

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Authors: Adawati Suhaili, Kamisah Osman, Mohd Effendi, Ewan Mohd Matore

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The global education reform has prompted Malaysia to transform the education system in Malaysia through the Malaysian Education Blueprint (MEB) 2013-2025. This transformation is aimed to achieve the top one-third rank in international assessment. The low achievement of student scientific literacy in TIMMS (Trends in International Mathematics and Science Study ) and PISA (Programme for International Student Assessment) has caused concern to the Ministry Of Education (MOE) despite various reform efforts. Therefore, an alternative action by enhancing the role of the Head of Science Panels (HoSPs) as a key change agent in catalyzing the improvement of student performance should be considered. Highlights of previous studies have shown that subject leadership is able to enhance teacher teaching quality in order to increase student learning. To lead the Science department and guide Science teachers more effectively, HoSPs need to strengthen their leadership skills. However, the issue of weaknesses in the leadership competencies of HoSPs in Malaysia has caused them to lack confidence and ability in leading the Science Department. The main objective of this study is to explore the factors that contribute to the problems faced by HoSPs at Sarawak in their leadership roles. This study used a qualitative design framework and using a semi-structured interview method for data collection. There were six informants involved in the interview consisting of lecturers, Senior Administrative Assistant Teacher and HoSPs. The findings of the study had been identified four main factors that contribute to problems in the leadership competencies of HoSPs in Sarawak, namely leadership practices, leadership structure, academic subjects and school change. The results are significant to the MOE in strengthening the leadership competencies of HoSPs in a more focus for improving the achievement of scientific literacy of students in Malaysia. This study can help improve the Hosps' leadership competencies in Malaysia.

Keywords: issues, problems, Malaysia education blueprint, leadership competencies, head of science panels

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Authors: Mathieu Hemono, Sophie Puig-Malet, Patrick Zylberman, Avner Bar-Hen, Rainer Sauerborn, Stefanie Schütte, Niamh Herlihi, Antoine Flahault et Anneliese Depoux

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Since the IPCC released its first report in 1990, an increasing number of peer-reviewed publications have reported the health risks associated with climate change. Although there is a large body of evidence supporting the association between climate change and poor health outcomes, the media is inconsistent in the attention it pays to the subject matter. This study aims to analyze the modalities and rhetoric in the media concerning the impact of climate change on health in order to better understand its role in information dissemination. A review was conducted of articles published between 1990 and 2015 in the francophone newspapers Le Monde and Jeune Afrique. A detailed search strategy including specific climate and health terminology was used to search the newspapers’ online databases. 1202 articles were identified as having referenced the terms climate change and health. Inclusion and exclusion criteria were applied to narrow the search to articles referencing the effects of climate change on human health and 160 articles were included in the final analysis. Data was extracted and categorized to create a structured database allowing for further investigation and analysis. The review indicated that although 66% of the selected newspaper articles reference scientific evidence of the impact of climate change on human health, the focus on the topic is limited major political events or is circumstances relating to public health crises. Main findings also include that among the many direct and indirect health outcomes, infectious diseases are the main health outcome highlighted in association with climate change. Lastly, the articles suggest that while developed countries have caused most of the greenhouse effect, the global south is more immediately affected. Overall, the reviewed articles reinforce the need for international cooperation in finding a solution to mitigate the effects of climate change on health. The manner in which scientific results are communicated and disseminated, impact individual and collective perceptions of the topic in the public sphere and affect political will to shape policy. The results of this analysis will underline the modalities of the rhetoric of transparency and provide the basis for a perception study of media discourses. This study is part of an interdisciplinary project called 4CHealth that confronts results of the research done on scientific, political and press literature to better understand how the knowledge on climate changes and health circulates within those different fields and whether and how it is translated to real world change.

Keywords: climate change, health, health impacts, communication, media, rhetoric, awareness, Global South, Africa

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Authors: Aya Salama

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Digital Twin is an emerging research topic that attracted researchers in the last decade. It is used in many fields, such as smart manufacturing and smart healthcare because it saves time and money. It is usually related to other technologies such as Data Mining, Artificial Intelligence, and Machine Learning. However, Human digital twin (HDT), in specific, is still a novel idea that still needs to prove its feasibility. HDT expands the idea of Digital Twin to human beings, which are living beings and different from the inanimate physical entities. The goal of this research was to create a Human digital twin that is responsible for real-time human replies automation by simulating human behavior. For this reason, clustering, supervised classification, topic extraction, and sentiment analysis were studied in this paper. The feasibility of the HDT for personal replies generation on social messaging applications was proved in this work. The overall accuracy of the proposed approach in this paper was 63% which is a very promising result that can open the way for researchers to expand the idea of HDT. This was achieved by using Random Forest for clustering the question data base and matching new questions. K-nearest neighbor was also applied for sentiment analysis.

Keywords: human digital twin, sentiment analysis, topic extraction, supervised machine learning, unsupervised machine learning, classification, clustering

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Authors: Prashant Shrivastava

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The purpose of this study is to explore re3dat.org registry to identify research data repositories registration workflow process. Further objective is to depict a graph for present development of research data repositories in India. Preliminarily with an approach to understand re3data.org registry framework and schema design then further proceed to explore the status of research data repositories of India in re3data.org registry. Research data repositories are getting wider relevance due to e-research concepts. Now available registry re3data.org is a good tool for users and researchers to identify appropriate research data repositories as per their research requirements. In Indian environment, a compatible National Research Data Policy is the need of the time to boost the management of research data. Registry for Research Data Repositories is a crucial tool to discover specific information in specific domain. Also, Research Data Repositories in India have not been studied. Re3data.org registry and status of Indian research data repositories both discussed in this study.

Keywords: research data, research data repositories, research data registry, re3data.org

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Authors: Alua Massalimova

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Situation analysis of Blood Service revealed that the strengths dominated over the weak 1.4 times. The possibilities dominate over the threats by 1.1 times. It follows that by using timely the possibility the Service, it is possible to strengthen its strengths and avoid threats. Priority directions of the resulting analysis are the use of subjective factors, such as personal management capacity managers of the Blood Center in the field of possibilities of legal activity of administrative decisions and the mobilization of stable staff in general market conditions. We have studied for the period 2011-2015 retrospectively indicators of Blood Service of Kazakhstan. Strengths of Blood Service of RK(Ps4,5): 1) indicators of donations for 1000 people is higher than in some countries of the CIS (in Russia 14, Kazakhstan - 17); 2) the functioning science centre of transfusiology; 3) the legal possibility of additional financing blood centers in the form of paid services; 4) the absence of competitors; 5) training on specialty Transfusiology; 6) the stable management staff of blood centers, a high level of competence; 7) increase in the incidence requiring transfusion therapy (oncohematology); 8) equipment upgrades; 9) the opening of a reference laboratory; 10) growth of the proportion of issued high-quality blood components; 11) governmental organization 'Drop of Life'; 12) the functioning bone marrow register; 13) equipped with modern equipment HLA-laboratory; 14) High categorization of average medical workers; 15) availability of own specialized scientific journal; 16) vivarium. The weaknesses (Ps = 3.5): 1) the incomplete equipping of blood centers and blood transfusion cabinets according to standards; 2) low specific weight of paid services of the CC; 3) low categorization of doctors; 4) high staff turnover; 5) the low scientific potential of industrial and clinical of transfusiology; 6) the low wages paid; 7) slight growth of harvested donor blood; 8) the weak continuity with offices blood transfusion; 9) lack of agitation work; 10) the formally functioning of Transfusion Association; 11) the absence of scientific laboratories; 12) high standard deviation from the average for donations in the republic. The possibilities (Ps = 2,7): 1): international grants; 2) organization of international seminars on clinical of transfusiology; 3) cross-sectoral cooperation; 4) to increase scientific research in the field of clinical of transfusiology; 5) reduce the share of donation unsuitable for transfusion and processing; 6) strengthening marketing management in the development of fee-based services; 7) advertising paid services; 8) strengthening the publishing of teaching aids; 9) team-building staff. The threats (Ps = 2.1): 1) an increase of staff turnover; 2) the risk of litigation; 3) reduction gemoprodukts based on evidence-based medicine; 4) regression of scientific capacity; 5) organization of marketing; 6) transfusiologist marketing; 7) reduction in the quality of the evidence base transfusions.

Keywords: blood service, healthcare, Kazakhstan, quantative swot analysis

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Authors: Yumei Han, Ling Li, Naiqing Song, Xiaoping Yang, Yuping Han

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Educational think tank is agreeably regarded as significant part of a nation’s soft power to promote the scientific and democratic level of educational policy making, and it plays critical role of bridging educational research in higher institutions and educational policy making. This study explores the concept, functions and significance of educational think tank in China, and conceptualizes a three dimensional framework to analyze the approaches of transforming research-based higher institutions into effective educational think tanks to serve educational policy making in the nation wide. Since 2014, the Ministry of Education P.R. China has been promoting the strategy of developing new type of educational think tanks in higher institutions, and such a strategy has been put into the agenda for the 13th Five Year Plan for National Education Development released in 2017.In such context, increasing scholars conduct studies to put forth strategies of promoting the development and transformation of new educational think tanks to serve educational policy making process. Based on literature synthesis, policy text analysis, and analysis of theories about policy making process and relationship between educational research and policy-making, this study constructed a three dimensional conceptual framework to address the following questions: (a) what are the new features of educational think tanks in the new era comparing traditional think tanks, (b) what are the functional objectives of the new educational think tanks, (c) what are the organizational patterns and mechanism of the new educational think tanks, (d) in what approaches traditional research-based higher institutions can be developed or transformed into think tanks to effectively serve the educational policy making process. The authors adopted case study approach on five influential education policy study centers affiliated with top higher institutions in China and applied the three dimensional conceptual framework to analyze their functional objectives, organizational patterns as well as their academic pathways that researchers use to contribute to the development of think tanks to serve education policy making process.Data was mainly collected through interviews with center administrators, leading researchers and academic leaders in the institutions. Findings show that: (a) higher institution based think tanks mainly function for multi-level objectives, providing evidence, theoretical foundations, strategies, or evaluation feedbacks for critical problem solving or policy-making on the national, provincial, and city/county level; (b) higher institution based think tanks organize various types of research programs for different time spans to serve different phases of policy planning, decision making, and policy implementation; (c) in order to transform research-based higher institutions into educational think tanks, the institutions must promote paradigm shift that promotes issue-oriented field studies, large data mining and analysis, empirical studies, and trans-disciplinary research collaborations; and (d) the five cases showed distinguished features in their way of constructing think tanks, and yet they also exposed obstacles and challenges such as independency of the think tanks, the discourse shift from academic papers to consultancy report for policy makers, weakness in empirical research methods, lack of experience in trans-disciplinary collaboration. The authors finally put forth implications for think tank construction in China and abroad.

Keywords: education policy-making, educational research, educational think tank, higher institution

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Authors: Dalin Si, Azizan Aziz, Bertrand Lasternas

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To encourage building owners to purchase electricity at the wholesale market and reduce building peak demand, this study aims to develop models that predict day-ahead hourly electricity consumption and demand using artificial neural network (ANN) and support vector machine (SVM). All prediction models are built in Python, with tool Scikit-learn and Pybrain. The input data for both consumption and demand prediction are time stamp, outdoor dry bulb temperature, relative humidity, air handling unit (AHU), supply air temperature and solar radiation. Solar radiation, which is unavailable a day-ahead, is predicted at first, and then this estimation is used as an input to predict consumption and demand. Models to predict consumption and demand are trained in both SVM and ANN, and depend on cooling or heating, weekdays or weekends. The results show that ANN is the better option for both consumption and demand prediction. It can achieve 15.50% to 20.03% coefficient of variance of root mean square error (CVRMSE) for consumption prediction and 22.89% to 32.42% CVRMSE for demand prediction, respectively. To conclude, the presented models have potential to help building owners to purchase electricity at the wholesale market, but they are not robust when used in demand response control.

Keywords: building energy prediction, data mining, demand response, electricity market

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Authors: Ilgin Gökaşar, Saman Ghaffarian

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The need for fast processed big data of transportation ridership (eg., smartcard data) and traffic operation (e.g., traffic detectors data) which requires a lot of computational power is incontrovertible in Intelligent Transportation Systems. Nowadays cloud computing is one of the important subjects and popular information technology solution for data processing. It enables users to process enormous measure of data without having their own particular computing power. Thus, it can also be a good selection for transportation big data processing as well. This paper intends to examine how the cloud computing can enhance transportation big data process with contrasting its advantages and disadvantages, and discussing cloud computing features.

Keywords: big data, cloud computing, Intelligent Transportation Systems, ITS, traffic data processing

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Authors: Jeff Chak-Fu Wong, Tony Chun Yin Yip

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The transition from secondary school to university seems exciting for many first-year students but can be more challenging than expected. Enabling instructors to know students’ learning habits and styles enhances their understanding of the students’ learning backgrounds, allows teachers to provide better support for their students, and has therefore high potential to improve teaching quality and learning, especially in any mathematics-related courses. The aim of this research is to collect students’ data using online surveys, to analyze students’ factors using learning analytics and educational data mining and to discover the characteristics of the students at risk of falling behind in their studies based on students’ previous academic backgrounds and collected data. In this paper, we use correlation-based distance methods and mutual information for measuring student factor relationships. We then develop a factor network using the Minimum Spanning Tree method and consider further study for analyzing the topological properties of these networks using social network analysis tools. Under the framework of mutual information, two graph-based feature filtering methods, i.e., unsupervised and supervised infinite feature selection algorithms, are used to analyze the results for students’ data to rank and select the appropriate subsets of features and yield effective results in identifying the factors affecting students at risk of failing. This discovered knowledge may help students as well as instructors enhance educational quality by finding out possible under-performers at the beginning of the first semester and applying more special attention to them in order to help in their learning process and improve their learning outcomes.

Keywords: students' academic performance, correlation-based distance method, social network analysis, feature selection, graph-based feature filtering method

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Authors: Sri Suryaningsum

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The achievement ‘Best Practice Model’ holds by the government on behalf of the success implementation corporate social responsibility program that held on PT. Kaltim Prima Coal which had operation located in the isolated district in Sanggata, it could be the reference for the other companies to improve the social welfare in surrounding area, especially for the companies that have operated in the isolated area in Indonesia. The rule of Kaltim Prima Coal as the catalyst in the development progress to push up the independence of district especially for the district which has located in surrounding mining operation from village level to the regency level, those programs had written in the 7 field program in Corporate Social Responsibility, it was doing by stakeholders. The stakeholders are village government, sub-district government, Regency and citizen. One of the best programs that implement at PT. Kaltim Prima Coal is Regarding Resettlement that was completed based on Asian Development Bank Resettlement Best Practice and International Financial Corporation Resettlement Action Plan. This program contributed on the resettlement residences to develop the isolated and the neglected district.

Keywords: CSR, isolated, neglected, poverty, mining industry

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Authors: M. Kebisek, L. Spendla, M. Kopcek, T. Skulavik

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In our paper we describe the security capabilities of data collection. Data are collected with probes located in the near and distant surroundings of the company. Considering the numerous obstacles e.g. forests, hills, urban areas, the data collection is realized in several ways. The collection of data uses connection via wireless communication, LAN network, GSM network and in certain areas data are collected by using vehicles. In order to ensure the connection to the server most of the probes have ability to communicate in several ways. Collected data are archived and subsequently used in supervisory applications. To ensure the collection of the required data, it is necessary to propose algorithms that will allow the probes to select suitable communication channel.

Keywords: communication, computer network, data collection, probe

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Authors: Jinhui Bak, Bumjin Kim

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The purpose of this study is to analyze how the scientific and mathematical fields (STEM) and liberal arts (A) work together in the STEAM program. In the future STEAM programs that have been designed and developed, the humanities will act not just as a 'tool' for science technology and mathematics, but as a 'core' content to have an equivalent status. STEAM was first introduced to the Republic of Korea in 2011 when the Ministry of Education emphasized fostering creative convergence talent. Many programs have since been developed under the name STEAM, but with the majority of programs focusing on technology education, arts and humanities are considered secondary. As a result, arts is most likely to be accepted as an option that can be excluded from the teachers who run the STEAM program. If what we ultimately pursue through STEAM education is in fostering STEAM literacy, we should no longer turn arts into a tooling area for STEM. Based on this consciousness, this study analyzed over 160 STEAM programs in middle and high schools, which were produced and distributed by the Ministry of Education and the Korea Science and Technology Foundation from 2012 to 2017. The framework of analyses referenced two criteria presented in the related prior studies: normative convergence and technological convergence. In addition, we divide Arts into fine arts and liberal arts and focused on Korean Language Course which is in liberal arts and analyzed what kind of curriculum standards were selected, and what kind of process the Korean language department participated in teaching and learning. In this study, to ensure the reliability of the analysis results, we have chosen to cross-check the individual analysis results of the two researchers and only if they are consistent. We also conducted a reliability check on the analysis results of three middle and high school teachers involved in the STEAM education program. Analyzing 10 programs selected randomly from the analyzed programs, Cronbach's α .853 showed a reliable level. The results of this study are summarized as follows. First, the convergence ratio of the liberal arts was lowest in the department of moral at 14.58%. Second, the normative convergence is 28.19%, which is lower than that of the technological convergence. Third, the language and achievement criteria selected for the program were limited to functional areas such as listening, talking, reading and writing. This means that the convergence of Korean language departments is made only by the necessary tools to communicate opinions or promote scientific products. In this study, we intend to compare these results with the STEAM programs in the United States and abroad to explore what elements or key concepts are required for the achievement criteria for Korean language and curriculum. This is meaningful in that the humanities field (A), including Korean, provides basic data that can be fused into 'equivalent qualifications' with science (S), technical engineering (TE) and mathematics (M).

Keywords: Korean STEAM Programme, liberal arts, STEAM curriculum, STEAM Literacy, STEM

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Authors: Thodoris Tsagkaris, Marios Stavropoulos, Panagiotis Theodosis-Nobelos, Charalampos Triantis

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Isotretinoin is a widely used therapeutic for the treatment of acne vulgaris and various other skin disorders. However, since its approval, many side effects and contraindications have been described, particularly important, such as teratogenicity as well as liver disease and dermal deterioration. In a very important allegation, isotretinoin has been linked with psychiatric symptoms like depression, suicidal ideation, schizophrenia, and hypervitaminosis A syndrome characteristics. These adverse effects have raised significant concerns regarding the safety of isotretinoin. Numerous studies and research have associated isotretinoin with side effects on the mental health of patients and have proposed plausible mechanisms regarding this suspected causative relationship. However, the evidence is still contradicting, and the data disperse, making their validity less valuable. Thus, in the present study, we aim to analyze further the available literature and present a complete analysis of the side effects of isotretinoin, with particular emphasis on the effects it may have on the mental health of patients. The review is based on international articles from broad scientific electronic databases like PubMed and Scopus. This review concludes that although many studies have associated isotretinoin with mental effects like depression, bipolar disorder, schizophrenia, and suicidal ideation, the data are still insufficient and often contradictory. In fact, additional studies with accurate data and larger double-blinded samples, and more analytic systematic reviews are required. It is especially important to monitor the dose and the intervals that isotretinoin has to be administered in order to potentially cause mental health problems, as well as the duration of treatment and the role that the patient's medical and pharmaceutical history may play.

Keywords: acne, depression, isotretinoin, mental health

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Authors: Kisik Song, Sungjoo Lee

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Recent years have seen an increasing number of patent disputes due to excessive competition in the global market and a reduced technology life-cycle; this has increased the risk of investment in technology development. While many global companies have started developing a methodology to identify promising technologies and assess for decisions, the existing methodology still has some limitations. Post hoc assessments of the new technology are not being performed, especially to determine whether the suggested technologies turned out to be promising. For example, in existing quantitative patent analysis, a patent’s citation information has served as an important metric for quality assessment, but this analysis cannot be applied to recently registered patents because such information accumulates over time. Therefore, we propose a new technology assessment model that can replace citation information and positively affect technological development based on post hoc analysis of the patents for promising technologies. Additionally, we collect customer reviews on a target technology to extract keywords that show the customers’ needs, and we determine how many keywords are covered in the new technology. Finally, we construct a portfolio (based on a technology assessment from patent information) and a customer-based marketability assessment (based on review data), and we use them to visualize the characteristics of the new technologies.

Keywords: technology assessment, patents, citation information, opinion mining

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Authors: B. S. Choudri

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Introduction: Climate change is a major threat to rural livelihoods and to food security in the developing world, including Oman. The aim of this study is to provide a basis for policymakers and researchers in order to understand the impacts of climate change on agriculture and developing adaptation strategies in Oman. Methodology: The data was collected from different agricultural areas across the country with the help of a questionnaire survey among farmers, discussion with community, and observations at the field level. Results: The analysis of data collected from different areas within the country shows a shift in the sowing period of major crops and increased temperatures over recent years. Farmer community is adopting through diversification of crops, use of heat-tolerant species, and improved measures of soil and water conservation. Agriculture has been the main livelihood for most of the farmer communities in rural areas in the country. Conclusions: In order to reduce the effects of climate change at the local and farmer communities, risk reduction would be important along with an in-depth analysis of the vulnerability. Therefore, capacity building of local farmers and providing them with scientific knowledge, mainstreaming adaptation into development activities would be essential with additional funding and subsidies.

Keywords: agriculture, climate change, vulnerability, adaptation

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Authors: Corinne Kowalski, Lea de Jong, Rainer Sauerborn, Niamh Herlihy, Anneliese Depoux, Jale Tosun

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Climate change is considered one of the biggest threats to human health of the 21st century. The link between climate change and health has received relatively little attention in the media, in research and in policy-making. A long term and broad overview of how health is represented in the legislation on climate change is missing in the legislative literature. It is unknown if or how the argument for health is referred in legal clauses addressing climate change, in national and European legislation. Integrating scientific based evidence into policies regarding the impacts of climate change on health could be a key step to inciting the political and societal changes necessary to decelerate global warming. This may also drive the implementation of new strategies to mitigate the consequences on health systems. To provide an overview of this issue, we are analyzing the Global Climate Legislation Database provided by the Grantham Research Institute on Climate Change and the Environment. This institution was established in 2008 at the London School of Economics and Political Science. The database consists of (updated as of 1st January 2015) legislations on climate change in 99 countries around the world. This tool offers relevant information about the state of climate related policies. We will use the database to systematically analyze the 829 identified legislations to identify how health is represented as a relevant aspect of climate change legislation. We are conducting explorative research of national and supranational legislations and anticipate health to be addressed in various forms. The goal is to highlight how often, in what specific terms, which aspects of health or health risks of climate change are mentioned in various legislations. The position and recurrence of the mention of health is also of importance. Data will be extracted with complete quotation of the sentence which mentions health, which will allow for second qualitative stage to analyze which aspects of health are represented and in what context. This study is part of an interdisciplinary project called 4CHealth that confronts results of the research done on scientific, political and press literature to better understand how the knowledge on climate change and health circulates within those different fields and whether and how it is translated to real world change.

Keywords: climate change, explorative research, health, policies

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Authors: Nay Myo Sandar

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With the growth of technologies and applications, a large amount of data has been producing at increasing rate from various resources such as social media networks, sensor devices, and other information serving devices. This large collection of massive, complex and exponential growth of dataset is called big data. The traditional database systems cannot store and process such data due to large and complexity. Consequently, cloud computing is a potential solution for data storage and processing since it can provide a pool of resources for servers and storage. However, moving large amount of data to and from is a challenging issue since it can encounter a high latency due to large data size. With respect to big data movement problem, this paper reviews the literature of previous works, discusses about research issues, finds out approaches for dealing with big data movement problem.

Keywords: Big Data, Cloud Computing, Big Data Movement, Network Techniques

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Authors: Ole Michael Spaten

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This article presents similarities and differences between psychotherapy, coaching psychology and coaching, and hence discusses boundaries between these diverse fields of practice. The point of departure will be prevailing arguments and descriptions in the scientific community, and it shows both commonalities and major differences in relation to the application in daily practice. The results (the similarities and differences) are presented and discussed in the light of scientific research and different theoretical perspectives, including both classic and recent scholars. Some of the main differences presented are; the clinical/non-clinical perspective and the educational differences, including the different criteria and demands which professionals working in these three different professions, should undergo to obtain their certification. Further, one of the main similarities is presented: the importance of the relationship between the therapist/coach and the client/coachee. The goal and task oriented focus are also presented as a similarity between the three intervention forms – at least to some extent. Finally, some central concepts from the fields are presented in a table for a proposal of distinctions and interfaces. It is concluded that a comprehensive education in combination with an understanding of the differences and similarities between the three intervention forms is of significant importance for the professional working in either of the fields. Future studies should, however, include additional research on the similarities and differences and how to continue the educational progress in all three disciplines.

Keywords: boundaries, coaching, coaching psychology, interface, psychotherapy

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Authors: Ahmed Mateen, Zhu Qingsheng, Ahmad Bilal

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In the current age of technology, information is the most precious asset of a company. Today, companies have a large amount of data. As the data become larger, access to data for some particular information is becoming slower day by day. Faster data processing to shape it in the form of information is the biggest issue. The major problems in distributed databases are the efficiency of data distribution and response time of data distribution. The security of data distribution is also a big issue. For these problems, we proposed a strategy that can maximize the efficiency of data distribution and also increase its response time. This technique gives better results for secure data distribution from multiple heterogeneous sources. The newly proposed technique facilitates the companies for secure data sharing efficiently and quickly.

Keywords: ER-schema, electronic record, P2P framework, API, query formulation

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Authors: Ghaleb Y. Abbasi, Israa Abu Rumman

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This paper modeled sales history archived from 2012 to 2015 bulked in monthly bins for five products for a medical supply company in Jordan. The sales forecasts and extracted consistent patterns in the sales demand history from the Enterprise Resource Planning (ERP) system were used to predict future forecasting and generate sales demand forecasting using time series analysis statistical technique called Auto Regressive Integrated Moving Average (ARIMA). This was used to model and estimate realistic sales demand patterns and predict future forecasting to decide the best models for five products. Analysis revealed that the current replenishment system indicated inventory overstocking.

Keywords: ARIMA models, sales demand forecasting, time series, R code

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Authors: Han-Qin Zheng, Yi-Fan Chiang-Hsieh, Chia-Hung Chien, Wen-Chi Chang

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As the most important non-vascular plants, algae have many research applications, including high species diversity, biofuel sources, adsorption of heavy metals and, following processing, health supplements. With the increasing availability of next-generation sequencing (NGS) data for algae genomes and transcriptomes, an integrated resource for retrieving gene expression data and metabolic pathway is essential for functional analysis and systems biology in algae. However, gene expression profiles and biological pathways are displayed separately in current resources, and making it impossible to search current databases directly to identify the cellular response mechanisms. Therefore, this work develops a novel AlgaePath database to retrieve gene expression profiles efficiently under various conditions in numerous metabolic pathways. AlgaePath, a web-based database, integrates gene information, biological pathways, and next-generation sequencing (NGS) datasets in Chlamydomonasreinhardtii and Neodesmus sp. UTEX 2219-4. Users can identify gene expression profiles and pathway information by using five query pages (i.e. Gene Search, Pathway Search, Differentially Expressed Genes (DEGs) Search, Gene Group Analysis, and Co-Expression Analysis). The gene expression data of 45 and 4 samples can be obtained directly on pathway maps in C. reinhardtii and Neodesmus sp. UTEX 2219-4, respectively. Genes that are differentially expressed between two conditions can be identified in Folds Search. Furthermore, the Gene Group Analysis of AlgaePath includes pathway enrichment analysis, and can easily compare the gene expression profiles of functionally related genes in a map. Finally, Co-Expression Analysis provides co-expressed transcripts of a target gene. The analysis results provide a valuable reference for designing further experiments and elucidating critical mechanisms from high-throughput data. More than an effective interface to clarify the transcript response mechanisms in different metabolic pathways under various conditions, AlgaePath is also a data mining system to identify critical mechanisms based on high-throughput sequencing.

Keywords: next-generation sequencing (NGS), algae, transcriptome, metabolic pathway, co-expression

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Authors: T. H. Derdzyan, K. A. Ghazaryan, G. A. Gevorgyan

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Beta-glucosidase, chitinase, leucine-aminopeptidase, acid phosphomonoestearse and acetate-esterase enzyme activities in the soils under the impact of metallurgical industrial activity in Lori marz (district) were investigated. The results of the study showed that the activities of the investigated enzymes in the soils decreased with increasing distance from the Shamlugh copper mine, the Chochkan tailings storage facility and the ore transportation road. Statistical analysis revealed that the activities of the enzymes were positively correlated (significant) to each other according to the observation sites which indicated that enzyme activities were affected by the same anthropogenic factor. The investigations showed that the soils were polluted with heavy metals (Cu, Pb, As, Co, Ni, Zn) due to copper mining activity in this territory. The results of Pearson correlation analysis revealed a significant negative correlation between heavy metal pollution degree (Nemerow integrated pollution index) and soil enzyme activity. All of this indicated that copper mining activity in this territory causing the heavy metal pollution of the soils resulted in the inhabitation of the activities of the enzymes which are considered as biological catalysts to decompose organic materials and facilitate the cycling of nutrients.

Keywords: Armenia, metallurgical industrial activity, heavy metal pollutionl, soil enzyme activity

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Authors: Wanderson Goncalves e Goncalves, José Alberto Silva de Sá

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Human actions are a threat to the balance and conservation of the Amazon forest. Therefore the environmental monitoring services play an important role as the preservation and maintenance of this environment. This study classified forest types using data from a forest inventory provided by the 'Florestal e da Biodiversidade do Estado do Pará' (IDEFLOR-BIO), located between the municipalities of Santarém, Juruti and Aveiro, in the state of Pará, Brazil, covering an area approximately of 600,000 hectares, Bands 3, 4 and 5 of the TM-Landsat satellite image, and Self - Organizing Maps. The information from the satellite images was extracted using QGIS software 2.8.1 Wien and was used as a database for training the neural network. The midpoints of each sample of forest inventory have been linked to images. Later the Digital Numbers of the pixels have been extracted, composing the database that fed the training process and testing of the classifier. The neural network was trained to classify two forest types: Rain Forest of Lowland Emerging Canopy (Dbe) and Rain Forest of Lowland Emerging Canopy plus Open with palm trees (Dbe + Abp) in the Mamuru Arapiuns glebes of Pará State, and the number of examples in the training data set was 400, 200 examples for each class (Dbe and Dbe + Abp), and the size of the test data set was 100, with 50 examples for each class (Dbe and Dbe + Abp). Therefore, total mass of data consisted of 500 examples. The classifier was compiled in Orange Data Mining 2.7 Software and was evaluated in terms of the confusion matrix indicators. The results of the classifier were considered satisfactory, and being obtained values of the global accuracy equal to 89% and Kappa coefficient equal to 78% and F1 score equal to 0,88. It evaluated also the efficiency of the classifier by the ROC plot (receiver operating characteristics), obtaining results close to ideal ratings, showing it to be a very good classifier, and demonstrating the potential of this methodology to provide ecosystem services, particularly in anthropogenic areas in the Amazon.

Keywords: artificial neural network, computational intelligence, pattern recognition, unsupervised learning

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Authors: Michael Brave, Mark Kroll, Steven Karch, Charles Wetli, Michael Graham, Sebastian Kunz, Dorin Panescu

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Background: Conducted electrical weapons (CEW) are now used in 107 countries and are a common law enforcement less-lethal force practice in the United Kingdom (UK), United States of America (USA), Canada, Australia, New Zealand, and others. Use of these devices is rarely temporally associated with the occurrence of sudden arrest-related deaths (ARD). Because such deaths are uncommon, few Medical Examiners (MEs) ever encounter one, and even fewer offices have established comprehensive investigative protocols. Without sufficient scientific data, the role, if any, played by a CEW in a given case is largely supplanted by conjecture often defaulting to a CEW-induced fatal cardiac arrhythmia. In addition to the difficulty in investigating individual deaths, the lack of information also detrimentally affects being able to define and evaluate the ARD cohort generally. More comprehensive, better information leads to better interpretation in individual cases and also to better research. The purpose of this presentation is to provide MEs with a comprehensive evidence-based checklist to assist in the assessment of CEW-ARD cases. Methods: PUBMED and Sociology/Criminology data bases were queried to find all medical, scientific, electrical, modeling, engineering, and sociology/criminology peer-reviewed literature for mentions of CEW or synonymous terms. Each paper was then individually reviewed to identify those that discussed possible bioelectrical mechanisms relating CEW to ARD. A Naranjo-type pharmacovigilance algorithm was also employed, when relevant, to identify and quantify possible direct CEW electrical myocardial stimulation. Additionally, CEW operational manuals and training materials were reviewed to allow incorporation of CEW-specific technical parameters. Results: Total relevant PUBMED citations of CEWs were less than 250, and reports of death extremely rare. Much relevant information was available from Sociology/Criminology data bases. Once the relevant published papers were identified, and reviewed, we compiled an annotated checklist of data that we consider critical to a thorough CEW-involved ARD investigation. Conclusion: We have developed an evidenced-based checklist that can be used by MEs and their staffs to assist them in identifying, collecting, documenting, maintaining, and objectively analyzing the role, if any, played by a CEW in any specific case of sudden death temporally associated with the use of a CEW. Even in cases where the collected information is deemed by the ME as insufficient for formulating an opinion or diagnosis to a reasonable degree of medical certainty, information collected as per the checklist will often be adequate for other stakeholders to use as a basis for informed decisions. Having reviewed the appropriate materials in a significant number of cases careful examination of the heart and brain is likely adequate. Channelopathy testing should be considered in some cases, however it may be considered cost prohibitive (aprox $3000). Law enforcement agencies may want to consider establishing a reserve fund to help manage such rare cases. The expense may stay the enormous costs associated with incident-precipitated litigation.

Keywords: ARD, CEW, police, TASER

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Authors: Sarah Werner, Michael J. Pritchard

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From pilots to engineers, the skills development within the aerospace industry is exceptionally broad. Employers often struggle with finding the right mixture of qualified skills to fill their organizational demands. This effort to find qualified talent is further complicated by the industrial delineation between two key areas: aviation and aerospace. In a broad sense, the aerospace industry overlaps with the aviation industry. In turn, the aviation industry is a smaller sector segment within the context of the broader definition of the aerospace industry. Furthermore, it could be conceptually argued that -in practice- there is little distinction between these two sectors (i.e., aviation and aerospace). However, through our unstructured text analysis of over 6,000 job listings captured, our team found a clear delineation between aviation-related jobs and aerospace-related jobs. Using techniques in natural language processing, our research identifies an integrated workforce skill pattern that clearly breaks between these two sectors. While the aviation sector has largely maintained its need for pilots, mechanics, and associated support personnel, the staffing needs of the aerospace industry are being progressively driven by integrative engineering needs. Increasingly, this is leading many aerospace-based organizations towards the acquisition of 'system level' staffing requirements. This research helps to better align higher educational institutions with the current industrial staffing complexities within the broader aerospace sector.

Keywords: aerospace industry, job demand, text mining, workforce development

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Authors: Elen Gasparyan, Naira Hakobyan

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One of the leading factors determining the effectiveness of work in a modern organization is the motivation of its employees. In the scientific psychological literature, this phenomenon is understood mainly as constructive forms of motivation and the search for ways to increase it. At the same time, the motivation of employees can sometimes lead to a decrease in the productivity of the organization, i.e., destructive motivation is usually not considered from the point of view of various motivational theories. This article provides an analysis of various forms of destructive motivation of employees. These forms include formalism in labor behavior, inadequate assessment of the work done, and an imbalance of personal and organizational interests. The destructive motivation of personnel has certain negative consequences both for the employees themselves and for the entire organization - it leads to a decrease in the rate of production and the quality of products or services, increased conflict in the behavior of employees, etc. Currently, there is an increase in scientific interest in the study of destructive motivation. The subject of psychological research is not only modern socio-psychological processes but also the achievements of scientific thought in the field of theories of motivation and management. This article examines the theoretical approaches of J. S. Adams and Porter-Lawler, provides an analysis of theoretical concepts, and emphasizes the main characteristics of the destructiveness of motivation. Destructive work motivation is presented at the macro, meso, and micro levels. These levels express various directions of development of motivation stimuli, such as social, organizational, and personal ones. At the macro level, the most important characteristics of destructive motivation are the high-income gap between employers and employees, а high degree of unemployment, weak social protection of workers, non-compliance by employers with labor legislation, and emergencies. At the organizational level, the main characteristics are decreasing the diversity of work and insufficient work conditions. At the personal level, the main characteristic of destructive motivation is a discrepancy between personal and organizational interests. A comparative analysis of the theoretical and methodological foundations of the study of motivation makes it possible to identify not only the main characteristics of destructive motivation but also to determine the contours of psychological counseling to reduce destructiveness in the behavior of employees.

Keywords: destructive, motivation, organization, behavior

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Authors: Chao-Ton Su, Li-Fei Chen

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The parameter design is crucial to improving the uniformity of a product or process. In the product design stage, parameter design aims to determine the optimal settings for the parameters of each element in the system, thereby minimizing the functional deviations of the product. In the process design stage, parameter design aims to determine the operating settings of the manufacturing processes so that non-uniformity in manufacturing processes can be minimized. The parameter design, trying to minimize the influence of noise on the manufacturing system, plays an important role in the high-tech companies. Taiwan has many well-known high-tech companies, which show key roles in the global economy. Quality remains the most important factor that enables these companies to sustain their competitive advantage. In Taiwan however, many high-tech companies face various quality problems. A common challenge is related to root causes and defect patterns. In the R&D stage, root causes are often unknown, and defect patterns are difficult to classify. Additionally, data collection is not easy. Even when high-volume data can be collected, data interpretation is difficult. To overcome these challenges, high-tech companies in Taiwan use more advanced quality improvement tools. In addition to traditional statistical methods and quality tools, the new trend is the application of powerful tools, such as neural network, fuzzy theory, data mining, industrial engineering, operations research, and innovation skills. In this study, several examples of optimizing the parameter settings for the manufacturing process in Taiwan’s tech companies will be presented to illustrate proposed approach’s effectiveness. Finally, a discussion of using traditional experimental design versus the proposed approach for process optimization will be made.

Keywords: quality engineering, parameter design, neural network, genetic algorithm, experimental design

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