Search results for: exploratory data analysis

Authors: Tambe Daniel Atem

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Background: Clinical Research is an organized research on human beings intended to provide adequate information on the drug use as a therapeutic agent on its safety and efficacy. The significance of the study is to educate the global health and life science graduates in Clinical Research in depth to perform better as it involves testing drugs on human beings. Objectives: to provide an overall understanding of the scientific approach to the evaluation of new and existing medical interventions and to apply ethical and regulatory principles appropriate to any individual research. Methodology: It is based on – Primary data analysis and Secondary data analysis. Primary data analysis: means the collection of data from journals, the internet, and other online sources. Secondary data analysis: a survey was conducted with a questionnaire to interview the Clinical Research Professionals to understand the need of training to perform clinical trials globally. The questionnaire consisted details of the professionals working with the expertise. It also included the areas of clinical research which needed intense training before entering into hardcore clinical research domain. Results: The Clinical Trials market worldwide worth over USD 26 billion and the industry has employed an estimated 2,10,000 people in the US and over 70,000 in the U.K, and they form one-third of the total research and development staff. There are more than 2,50,000 vacant positions globally with salary variations in the regions for a Clinical Research Coordinator. R&D cost on new drug development is estimated at US$ 70-85 billion. The cost of doing clinical trials for a new drug is US$ 200-250 million. Due to an increase trained Clinical Research Professionals India has emerged as a global hub for clinical research. The Global Clinical Trial outsourcing opportunity in India in the pharmaceutical industry increased to more than $2 billion in 2014 due to increased outsourcing from U.S and Europe to India. Conclusion: Assessment of training need is recommended for newer Clinical Research Professionals and trial sites, especially prior the conduct of larger confirmatory clinical trials.

Keywords: clinical research, clinical trials, clinical research professionals

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Authors: Alexandra Aslanidou

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The General Data Protection Regulation (GDPR), concerning the protection of natural persons within the European Union with regard to the processing of personal data and on the free movement of such data, became applicable in the European Union (EU) on 25 May 2018 and transformed the way personal data were being treated under the Data Protection Directive (DPD) regime, generating sweeping organizational changes to both public sector and business. A social practice that is considerably influenced in the way of its day-to-day operations is Human Resource (HR) management, for which the importance of GDPR cannot be underestimated. That is because HR processes personal data coming in all shapes and sizes from many different systems and sources. The significance of the proper functioning of an HR department, specifically in human-centered, service-oriented environments such as the education field, is decisive due to the fact that HR operations in schools, conducted effectively, determine the quality of the provided services and consequently have a considerable impact on the success of the educational system. The purpose of this paper is to analyze the decisive role that GDPR plays in HR departments that operate in schools and in order to practically evaluate the aftermath of the Regulation during the first months of its applicability; a comparative use cases analysis in five highly dynamic schools, across three EU Member States, was attempted.

Keywords: general data protection regulation, human resource management, educational system

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Authors: Olga S. Volodko, Lidiya A. Kompaniets, Ludmila V. Gavrilova

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The method of empirical orthogonal functions is the method of data analysis with a complex spatial-temporal structure. This method allows us to decompose the data into a finite number of modes determined by empirically finding the eigenfunctions of data correlation matrix. The modes have different scales and can be associated with various physical processes. The empirical orthogonal function method has been widely used for the analysis of hydrophysical characteristics, for example, the analysis of sea surface temperatures in the Western North Atlantic, ocean surface currents in the North Carolina, the study of tropical wave disturbances etc. The method used in this study has been applied to the analysis of temperature and velocity measurements in saline Lake Shira (Southern Siberia, Russia). Shira is a shallow lake with the maximum depth of 25 m. The lake Shira can be considered as a closed water site because of it has one small river providing inflow and but it has no outflows. The main factor that causes the motion of fluid is variable wind flows. In summer the lake is strongly stratified by temperature and saline. Long-term measurements of the temperatures and currents were conducted at several points during summer 2014-2015. The temperature has been measured with an accuracy of 0.1 ºC. The data were analyzed using the empirical orthogonal function method in the real version. The first empirical eigenmode accounts for 70-80 % of the energy and can be interpreted as temperature distribution with a thermocline. A thermocline is a thermal layer where the temperature decreases rapidly from the mixed upper layer of the lake to much colder deep water. The higher order modes can be interpreted as oscillations induced by internal waves. The currents measurements were recorded using Acoustic Doppler Current Profilers 600 kHz and 1200 kHz. The data were analyzed using the empirical orthogonal function method in the complex version. The first empirical eigenmode accounts for about 40 % of the energy and corresponds to the Ekman spiral occurring in the case of a stationary homogeneous fluid. Other modes describe the effects associated with the stratification of fluids. The second and next empirical eigenmodes were associated with dynamical modes. These modes were obtained for a simplified model of inhomogeneous three-level fluid at a water site with a flat bottom.

Keywords: Ekman spiral, empirical orthogonal functions, data analysis, stratified fluid, thermocline

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Authors: Zhidong Zhang, Zhi-Chao Zhang

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This study examines adolescent psychological and behavioral problems. The Achenbach systems of empirically based assessment (ASEBA) were used as the instrument. The problem framework consists of internal, external and social behavioral problems which are theoretically developed based on about 113 items plus relevant background variables. In this study, the sample consist of 1,975 sixth and seventh grade students in Northeast China. Stratified random sampling method was used to collect the data, meaning that samples were from different school districts, schools, and classes. The researchers looked at both macro and micro effect. Therefore, multilevel analysis techniques were used in the data analysis. The parts of the research results indicated that the background variables such as extracurricular activities were directly related to students’ internal problems.

Keywords: behavioral problems, anxious/depressed problems, internalizing problems, mental health, under-represented groups, empirically-based assessment, hierarchical modeling, ASEBA, multilevel analysis

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Authors: Piotr J. Balwierz, Mikhail Pachkov, Phil Arnold, Andreas J. Gruber, Mihaela Zavolan, Erik van Nimwegen

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Understanding the key players and interactions in the regulatory networks that control gene expression and chromatin state across different cell types and tissues in metazoans remains one of the central challenges in systems biology. Our laboratory has pioneered a number of methods for automatically inferring core gene regulatory networks directly from high-throughput data by modeling gene expression (RNA-seq) and chromatin state (ChIP-seq) measurements in terms of genome-wide computational predictions of regulatory sites for hundreds of transcription factors and micro-RNAs. These methods have now been completely automated in an integrated webserver called ISMARA that allows researchers to analyze their own data by simply uploading RNA-seq or ChIP-seq data sets and provides results in an integrated web interface as well as in downloadable flat form. For any data set, ISMARA infers the key regulators in the system, their activities across the input samples, the genes and pathways they target, and the core interactions between the regulators. We believe that by empowering experimental researchers to apply cutting-edge computational systems biology tools to their data in a completely automated manner, ISMARA can play an important role in developing our understanding of regulatory networks across metazoans.

Keywords: gene expression analysis, high-throughput sequencing analysis, transcription factor activity, transcription regulation

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Authors: Yosra Ben Salah, Wang Li Jun, Salem Bellil

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The village Hammem Zriba is a lost little paradise in the middle of a beautiful landscape that captures the eyes of every visitor. The village alone is a rich expression of different elements such as urban, architecture, technical and vernacular elements, as well as sociological, spiritual and religious behaviors. This heritage is in degrading conditions and is threatened by disappearing soon; thus, actions have to be taken as soon as possible to preserve this heritage, record, analyze and learn from its traditional ways of construction. The strategy of this study is to examine the architecture within the Berber society over a period of time and influenced by a certain location and its relationship to the social and cultural aspects; this research will focus on historical, environmental, social and cultural aspects influencing architecture. The contents of this paper should mainly be constructed by three successive layouts of historical view, a cultural view and an architectural view that will include the urban and domestic scale. This research relies on the integration of both theoretical and empirical investigations. On the theoretical level: A documentary analysis of secondary data is used. Documentary analysis means content analysis of the relevant documents that include books, journals, magazines, archival data, and field survey and observations. On the empirical level: analysis of these traditional ways of planning and house building will be carried out. Through the Analysis, three techniques will be employed to collect primary data. These techniques are; systematic analysis of the architectural drawings, quantitative analysis to the houses statistics, and a direct observation. Through this research, the technical, architectural and urban achievements of the Berber people who represent a part of the general history and architectural history will be emphasized. And on a second point the potential for the sustainability present in this traditional urban planning and housing to be used to formulate guidelines for modern urban and housing development.

Keywords: culture, history, traditional architecture, values

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Authors: A. Brunel, A. Kernevez, F. Leclere, J. Trenteseaux

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Today, wine quality is only evaluated by wine experts with their own different personal tastes, even if they may agree on some common features. So producers do not have any unbiased way to independently assess the quality of their products. A tool is here proposed to evaluate wine quality by an objective ranking based upon the variables entering wine elaboration, and analysed through principal component analysis (PCA) method. Actual climatic data are compared by measuring the relative distance between each considered wine, out of which the general ranking is performed.

Keywords: wine, grape, weather conditions, rating, climate, principal component analysis, metric analysis

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Authors: Avi Shrivastava

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In 2021, two heart-wrenching scenes, shown live on television screens across countries, painted a grim picture of refugees. One of them was of people clinging onto an airplane's wings in their desperate attempt to flee war-torn Afghanistan. They ultimately fell to their death. The other scene was the U.S. government authorities separating children from their parents or guardians to deter migrants/refugees from coming to the U.S. These events show the desperation refugees feel when they are trying to leave their homes in disaster zones. However, data paints a grave picture of the current refugee situation. It also indicates that a bleak future lies ahead for the refugees across the globe. Data and information are the two threads that intertwine to weave the shimmery fabric of modern society. Data and information are often used interchangeably, but they differ considerably. For example, information analysis reveals rationale, and logic, while data analysis, on the other hand, reveals a pattern. Moreover, patterns revealed by data can enable us to create the necessary tools to combat huge problems on our hands. Data analysis paints a clear picture so that the decision-making process becomes simple. Geopolitical and economic data can be used to predict future refugee hotspots. Accurately predicting the next refugee hotspots will allow governments and relief agencies to prepare better for future refugee crises. The refugee crisis does not have binary answers. Given the emotionally wrenching nature of the ground realities, experts often shy away from realistically stating things as they are. This hesitancy can cost lives. When decisions are based solely on data, emotions can be removed from the decision-making process. Data also presents irrefutable evidence and tells whether there is a solution or not. Moreover, it also responds to a nonbinary crisis with a binary answer. Because of all that, it becomes easier to tackle a problem. Data science and A.I. can predict future refugee crises. With the recent explosion of data due to the rise of social media platforms, data and insight into data has solved many social and political problems. Data science can also help solve many issues refugees face while staying in refugee camps or adopted countries. This paper looks into various ways data science can help solve refugee problems. A.I.-based chatbots can help refugees seek legal help to find asylum in the country they want to settle in. These chatbots can help them find a marketplace where they can find help from the people willing to help. Data science and technology can also help solve refugees' many problems, including food, shelter, employment, security, and assimilation. The refugee problem seems to be one of the most challenging for social and political reasons. Data science and machine learning can help prevent the refugee crisis and solve or alleviate some of the problems that refugees face in their journey to a better life. With the explosion of data in the last decade, data science has made it possible to solve many geopolitical and social issues.

Keywords: refugee crisis, artificial intelligence, data science, refugee camps, Afghanistan, Ukraine

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Authors: Mulligan T., Barker-Collo S., Gobson K., Jones K.

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There is a relatively scarce body of literature regarding adolescent experiences of traumatic brain injury (TBI). This qualitative study explored how sustaining a TBI at this unique stage of development might impact a young person as they navigate the challenges of adolescence and transition to adulthood, and what might support recovery. Thirteen young adults who sustained a mild-moderate TBI as an adolescent (aged 13 – 17 years), approximately 7.7 years (range = 6.7 – 8.0 years) prior, participated in the research. Semi-structured individual interviews were conducted to explore participants’ experiences surrounding and following their TBIs. Thematic analysis of interview data produced five key categories of findings: (1) Following their TBIs, many participants experienced problems with cognitive (e.g., forgetfulness, concentration difficulties), physical (e.g., migraines, fatigue) and emotional (e.g., depression, anxiety) functioning, which were often endured into adulthood. (2) TBI-related problems often adversely affected important areas of life for the participant, including school, work and friendships. (3) Changes following TBI commonly impacted identity formation. (4) Recovery processes evolved over time as the participants coped initially by just ‘getting on with it’, before learning to accept new limitations and, ultimately, growing from their TBI experiences. (5) While the presence of friends and family assisted recovery, struggles were often exacerbated by a lack of emotional support from others, in addition to the absence of any assistance or information-provision from professionals regarding what to expect following TBI. The findings suggest that even mild TBI sustained during adolescence can have consequences for an individual’s functioning, engagement in life and identity development, whilst also giving rise to post-traumatic growth. Recovery following adolescent TBI might be maximised by facilitating greater understanding of the injury and acknowledging its impacts on important areas of life, as well as the provision of emotional support and facilitating self-reflection and meaning-making.

Keywords: adolescent, brain Injury, qualitative, post-traumatic growth

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Authors: M. G. R. S. Perera, B. S. Weerakoon, L. P. G. Sherminie, M. L. Jayatilake, R. D. Jayasinghe, W. Huang

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The aim of this study was to measure and evaluate the Longitudinal Relaxation Times (T1) in bone marrow of an Acute Myeloid Leukaemia (AML) patient in order to explore the potential for a prognostic biomarker using Magnetic Resonance Imaging (MRI) which will be a non-invasive prognostic approach to AML. MR image data were collected in the DICOM format and MATLAB Simulink software was used in the image processing and data analysis. For quantitative MRI data analysis, Region of Interests (ROI) on multiple image slices were drawn encompassing vertebral bodies of L3, L4, and L5. T1 was evaluated using the T1 maps obtained. The estimated bone marrow mean value of T1 was 790.1 (ms) at 3T. However, the reported T1 value of healthy subjects is significantly (946.0 ms) higher than the present finding. This suggests that the T1 for bone marrow can be considered as a potential prognostic biomarker for AML patients.

Keywords: acute myeloid leukaemia, longitudinal relaxation time, magnetic resonance imaging, prognostic biomarker.

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Authors: Mashood C., Abdul Vahid K., Ashique C. K.

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The technology is growing beyond human expectation. Internet is one of very sophisticated product of the information technology. It has various advantages like connecting the world, simplifying the difficult tasks done in past etc. Simultaneously it has demerits also; that is lack of authenticity and internet addiction. To find out the problems of internet addiction, a study conducted among the Postgraduate students of Pondicherry University and collected 454 samples. The study strictly focused to identify the internet addiction among students, influence and interdependence of personality on internet addiction among first years and second years. To evaluate this, we used two major analysis, these are Confirmatory Factor Analysis (CFA) to predict the internet addiction with the observed data and Logistic Regression to identify the difference between first years and second years in the case of internet addiction. Before applying to the core analysis, the data applied to some preliminary tests to check the model fit. The empirical findings shows that , the students of Pondicherry University are very much addicted to the internet, But there is no such huge difference between first years and second years in case of internet addiction.

Keywords: internet addiction, students, Pondicherry University, empirical study

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Authors: M. Osipova

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Thanks to informational technologies development every sphere of economics is becoming more and more data-centralized as people are generating huge datasets containing information on any aspect of their life. Applying research of such data to human resources management allows getting scarce statistics on labor market state including salary expectations and potential employees’ typical career behavior, and this information can become a reliable basis for management decisions. The following article presents results of career behavior research based on freely accessible resume data. Information used for study is much wider than one usually uses in human resources surveys. That is why there is enough data for statistically significant results even for subgroups analysis.

Keywords: human resources management, salary expectations, statistics, turnover

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Authors: Oyedele Ogundana, Amon Simba, Kostas Galanakis, Lynn Oxborrow

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The debate about factors influencing the business growth of women-owned businesses has been a topical issue in business management. Currently, scholars have identified the issues of access to money, market, and management as canvasing factors influencing the business growth of women-owned businesses. However, the influence of motherhood (household/family context) on business growth is inconclusive in the literature; despite that women are more family-oriented than their male counterparts. Therefore, this research study considers the influence of motherhood factor (household/family context) on the business growth of women-owned sewing businesses (WOSBs) in Lagos, Nigeria. The sewing business sector is chosen as the fashion industry (which includes sewing businesses) currently accounts for the second largest number of jobs in Sub-Saharan Africa, following agriculture. Thus, sewing businesses provide a rich ground for contributing to existing scholarly work. Research questions; (1) In what way does the motherhood factor influence the business growth of WOSBs in Lagos? (2) To what extent does the motherhood factor influence the business growth of WOSBs in Lagos? For the method design, a pragmatic approach, a mixed-methods technique and an abductive form of reasoning are adopted. The method design is chosen because it fits, better than other research perspectives, with the research questions posed in this study. For instance, using a positivist approach will not sufficiently answer research question 1, neither will an interpretive approach sufficiently answer research question 2. Therefore, the research method design is divided into 2 phases, and the results from one phase are used to inform the development of the subsequent phases (only phase 1 has been completed at the moment). The first phase uses qualitative data and analytical method to answer research question 1. While the second phase of the research uses quantitative data and analytical method to answer research question 2. For the qualitative phase, 5 WOSBs were purposefully selected and interviewed. The sampling technique is selected as it was not the intention of the researcher to make any statistical inferences, at this phase, rather the purpose was just exploratory. Therefore, the 5 sampled women comprised of 2 unmarried women, 1 married woman with no child, and 2 married women with children. A 40-60 minutes interview was conducted per participants. The interviews were audio-recorded and transcribed. Thereafter, the data were analysed using thematic analysis in order to unearth patterns and relationships. Findings for the first phase of this research reveals that motherhood (household/family context) directly influences (positively/negatively) the performance of WOSBs in Lagos. Apart from a direct influence on WOSBs, motherhood also moderates (positively/negatively) other factors–e.g., access to money, management/human resources and market/opportunities– influencing WOSBs in Lagos. To further strengthen this conclusion, a word frequency query result shows that ‘family,’ ‘husband’ and ‘children’ are among the 10 words used frequently in all the interview transcripts. This first phase contributes to existing studies by showing the various forms by which motherhood influences WOSBs. The second phase (which data are yet to be collected) would reveal the extent to which motherhood influence the business growth of WOSBs in Lagos.

Keywords: women-owned sewing businesses, business growth, motherhood, Lagos

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Authors: Ulas Vural, M. Ergun Okay, E. Mesut Yildiz

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Telecommunication service providers demand accurate and precise prediction of customer churn probabilities to increase the effectiveness of their customer relation services. The large amount of customer data owned by the service providers is suitable for analysis by machine learning methods. In this study, expenditure data of customers are analyzed by using an artificial neural network (ANN). The ANN model is applied to the data of customers with different billing duration. The proposed model successfully predicts the churn probabilities at 83% accuracy for only three months expenditure data and the prediction accuracy increases up to 89% when the nine month data is used. The experiments also show that the accuracy of ANN model increases on an extended feature set with information of the changes on the bill amounts.

Keywords: customer relationship management, churn prediction, telecom industry, deep learning, artificial neural networks

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Authors: Fatemeh Havas Beigi

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The purpose of this study is to identify the objectives of a multicultural curriculum for the primary education period from the perspective of ethnic teachers and education experts and cultural professionals. The research paradigm is interpretive, the research approach is qualitative, the research strategy is content analysis, the sampling method is purposeful and it is a snowball, and the sample of informants in the research for Iranian ethnic teachers and experts until the theoretical saturation was estimated to be 67 people. The data collection tools used were based on semi-structured interviews and individual interviews and focal interviews were used to collect information. The data format was also in audio format and the first period coding and the second coding were used to analyze the data. Based on data analysis 11 Objective: Paying attention to ethnic equality, expanding educational opportunities and justice, peaceful coexistence, anti-ethnic and racial discrimination education, paying attention to human value and dignity, accepting religious diversity, getting to know ethnicities and cultures, promoting teaching-learning, fostering self-confidence, building national unity, and developing cultural commonalities for a multicultural curriculum were identified.

Keywords: objective, multicultural curriculum, connect, elementary education period

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Authors: Muhammad Naveed Babur, Maria Liaqat

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Background & Objective: People with disabilities especially neurological disabilities have many unmet health and rehabilitation needs, face barriers in accessing mainstream health-care services, and consequently have poor health. There are not sufficient epidemiological studies from Pakistan which assess barriers to neurorehabilitation and ways to counter it. Objectives: The objective of the study was to determine the challenges and to evaluate the barriers for neuro-rehabilitation services in developing countries. Methods: This is Exploratory sequential qualitative study based on the Panel discussion forum in International rehabilitation sciences congress and national rehabilitation conference 2017. Panel group discussion has been conducted in February 2017 with a sample size of eight professionals including Rehabilitation medicine Physician, Physical Therapist, Speech Language therapist, Occupational Therapist, Clinical Psychologist and rehabilitation nurse working in multidisciplinary/Interdisciplinary team. A comprehensive audio-videography have been developed, recorded, transcripted and documented. Data was transcribed and thematic analysis along with characteristics was drawn manually. Data verification was done with the help of two separate coders. Results: After extraction of two separate coders following results are emerged. General category themes are disease profile, demographic profile, training and education, research, barriers, governance, global funding, informal care, resources and cultural beliefs and public awareness. Barriers identified at the level are high cost, stigma, lengthy course of recovery. Hospital related barriers are lack of social support and individually tailored goal setting processes. Organizational barriers identified are lack of basic diagnostic facilities, lack of funding and human resources. Recommendations given by panelists were investment in education, capacity building, infrastructure, governance support, strategies to promote communication and realistic goals. Conclusion: It is concluded that neurorehabilitation in developing countries need attention in following categories i.e. disease profile, demographic profile, training and education, research, barriers, governance, global funding, informal care, resources and cultural beliefs and public awareness. This study also revealed barriers at the level of patient, hospital, organization. Recommendations were also given by panelists.

Keywords: disability, neurorehabilitation, telerehabilitation, disability

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Authors: Bernardo Cedano, Ahmed H. Eltom, Bob Hay, Jim Glass, Raga Ahmed

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The deployment of smart grid devices such as smart meters and smart switches (SS) supported by a reliable and fast communications system makes automated distribution possible, and thus, provides great benefits to electric power consumers and providers alike. However, more research is needed before the full utility of smart switch data is realized. This paper presents new automated switching techniques using SS within the electric power grid. A concise background of the SS is provided, and operational examples are shown. Organization and presentation of data obtained from SS are shown in the context of the future goal of total automation of the distribution network. The description of application techniques, the examples of success with SS, and the vision outlined in this paper serve to motivate future research pertinent to disturbance analysis automation.

Keywords: disturbance automation, electric power grid, smart grid, smart switches

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Authors: My Linh Hoang, Van Dung Hoang

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Environmental, Social, and Governance (ESG) factors have become a focus for companies globally, as businesses are now focusing on long-term sustainable goals rather than only operating for the goals of profit maximization. According to recent research, in several countries, companies have shown positive results in their financial performance by improving their ESG performance. The construction industry is one of the most crucial components of social and economic development; as a result, considerations for ESG factors are becoming more and more essential for companies in this sector. In Vietnam, the construction industry has been growing rapidly in recent years; however, it has yet to be discussed and studied extensively in Vietnam how ESG factors create impacts on corporate financial performance in general and construction corporations’ financial performance in particular. This research aims to examine the relationship between ESG factors and financial indicators in construction companies from 2011 to 2021 through panel data analysis of 75 listed construction companies in Vietnam and to provide insights into how these companies can better integrate ESG considerations into their operations to enhance their financial performance. The data was analyzed through 3 main methods: descriptive statistics, correlation coefficient analysis applied to all dependent, explanatory and control variables, and panel data analysis method. In panel data analysis, the study uses the fixed effects model (FEM) and random effects model (REM). The Hausman test will be used to select which model is suitable to be used. The findings indicate that maintaining a strong commitment to ESG principles can have a positive impact on financial performance. Finally, FGLS estimation will be performed when the problem of autocorrelation and variable variance appears in the model. This is significant for all parties involved, including investors, company managers, decision-makers, and industry regulators.

Keywords: ESG, financial performance, construction company, Vietnam

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Authors: Y. K. Park, B. K. Kim, J. W. Lee, S. J. Lee

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To assess the risk of the underground structures and surrounding ground, we collect basic data by the engineering method of measurement, exploration and surveys and, derive the risk through proper analysis and each assessment for urban railroad underground structures and surrounding ground including station inflow. Basic data are obtained by the fiber-optic sensors, MEMS sensors, water quantity/quality sensors, tunnel scanner, ground penetrating radar, light weight deflectometer, and are evaluated if they are more than the proper value or not. Based on these data, we analyze the risk level of urban railroad underground structures and surrounding ground. And we develop the risk management system to manage efficiently these data and to support a convenient interface environment at input/output of data.

Keywords: urban railroad, underground structures, ground subsidence, station inflow, risk

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Authors: Lassi Lehto, Jaakko Kahkonen, Juha Oksanen, Tapani Sarjakoski

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The use of raster-formatted data sets in geospatial analysis is increasing rapidly. At the same time, geographic data are being introduced into disciplines outside the traditional domain of geoinformatics, like climate change, intelligent transport, and immigration studies. These developments call for better methods to deliver raster geodata in an efficient and easy-to-use manner. Data cube technologies have traditionally been used in the geospatial domain for managing Earth Observation data sets that have strict requirements for effective handling of time series. The same approach and methodologies can also be applied in managing other types of geospatial data sets. A cloud service-based geodata cube, called GeoCubes Finland, has been developed to support online delivery and analysis of most important geospatial data sets with national coverage. The main target group of the service is the academic research institutes in the country. The most significant aspects of the GeoCubes data repository include the use of multiple resolution levels, cloud-optimized file structure, and a customized, flexible content access API. Input data sets are pre-processed while being ingested into the repository to bring them into a harmonized form in aspects like georeferencing, sampling resolutions, spatial subdivision, and value encoding. All the resolution levels are created using an appropriate generalization method, selected depending on the nature of the source data set. Multiple pre-processed resolutions enable new kinds of online analysis approaches to be introduced. Analysis processes based on interactive visual exploration can be effectively carried out, as the level of resolution most close to the visual scale can always be used. In the same way, statistical analysis can be carried out on resolution levels that best reflect the scale of the phenomenon being studied. Access times remain close to constant, independent of the scale applied in the application. The cloud service-based approach, applied in the GeoCubes Finland repository, enables analysis operations to be performed on the server platform, thus making high-performance computing facilities easily accessible. The developed GeoCubes API supports this kind of approach for online analysis. The use of cloud-optimized file structures in data storage enables the fast extraction of subareas. The access API allows for the use of vector-formatted administrative areas and user-defined polygons as definitions of subareas for data retrieval. Administrative areas of the country in four levels are available readily from the GeoCubes platform. In addition to direct delivery of raster data, the service also supports the so-called virtual file format, in which only a small text file is first downloaded. The text file contains links to the raster content on the service platform. The actual raster data is downloaded on demand, from the spatial area and resolution level required in each stage of the application. By the geodata cube approach, pre-harmonized geospatial data sets are made accessible to new categories of inexperienced users in an easy-to-use manner. At the same time, the multiresolution nature of the GeoCubes repository facilitates expert users to introduce new kinds of interactive online analysis operations.

Keywords: cloud service, geodata cube, multiresolution, raster geodata

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Authors: Marcos Bosques-Perez, Walter Izquierdo, Harold Martin, Liangdon Deng, Josue Rodriguez, Thony Yan, Mercedes Cabrerizo, Armando Barreto, Naphtali Rishe, Malek Adjouadi

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Aerial imagery is a powerful tool when it comes to analyzing temporal changes in ecosystems and extracting valuable information from the observed scene. It allows us to identify and assess various elements such as objects, structures, textures, waterways, and shadows. To extract meaningful information, multispectral cameras capture data across different wavelength bands of the electromagnetic spectrum. In this study, the collected multispectral aerial images were subjected to principal component analysis (PCA) to identify independent and uncorrelated components or features that extend beyond the visible spectrum captured in standard RGB images. The results demonstrate that these principal components contain unique characteristics specific to certain wavebands, enabling effective object identification and image segmentation.

Keywords: big data, image processing, multispectral, principal component analysis

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Authors: M. Naidoo

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Artificial intelligence often requires large amounts of good quality data. Within important fields, such as healthcare, the training of AI systems predominately relies on health and personal data; however, the usage of this data is complicated by various layers of law and ethics that seek to protect individuals’ privacy rights. This research seeks to establish the challenges AI and data sciences pose to (i) informational rights, (ii) privacy rights, and (iii) data protection. To solve some of the issues presented, various methods are suggested, such as embedding values in technological development, proper balancing of rights and interests, and others.

Keywords: artificial intelligence, data science, law, policy

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Authors: Panwasn Mahalawalert

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The purposes of this research were analyzed differential item functioning and differential test functioning of SWUSAT aptitude test classification by sex variable. The data used in this research is the secondary data from Srinakharinwirot University Scholastic Aptitude Test 2013 (SWUSAT). SWUSAT test consists of four subjects. There are verbal ability test, number ability test, reasoning ability test and spatial ability test. The data analysis was analyzed in 2 steps. The first step was analyzing descriptive statistics. In the second step were analyzed differential item functioning (DIF) and differential test functioning (DTF) by using the DIFAS program. The research results were as follows: The results of DIF and DTF analysis for all 10 tests in year 2013. Gender was the characteristic that found DIF all 10 tests. The percentage of item number that found DIF is between 6.67% - 60%. There are 5 tests that most of items favors female group and 2 tests that most of items favors male group. There are 3 tests that the number of items favors female group equal favors male group. For Differential test functioning (DTF), there are 8 tests that have small level.

Keywords: aptitude test, differential item functioning, differential test functioning, educational measurement

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Authors: Khurram Shahzad, Muhammad Usman

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The main aim of this study is to examine the direct and interactive effects of job insecurity and Islamic work ethics on employee’s attitude towards change and organizational citizenship behavior. Design/methodology/approach: The data was collected from 171 male and female university teachers of Pakistan. Self administered, close ended questionnaires were used to collect the data. Data was analyzed through correlation and regression analysis. Findings: Through the analysis of data, it was found that job insecurity has a strong negative effect on the attitude towards change of university teachers. On the contrary, job insecurity has no significant effect on organizational citizenship behavior of university teachers. Our results also show that Islamic work ethics does not moderate the relationship of job insecurity and attitude towards change, while a strong moderation effect of Islamic wok ethics is found on the relationship of job insecurity and organizational citizenship behavior. Originality/value: This study for the first time examines the relationship of job insecurity with employee’s attitude towards change and organizational citizenship behavior with the moderating effect of Islamic work ethics.

Keywords: job security, islamic work ethics, attitude towards change, organizational citizenship behavior

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Authors: Karolína Vozková, Matěj Kuc

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This paper analyzes recent trends in cost efficiency of European cooperative banks using efficient frontier analysis. Our methodology is based on stochastic frontier analysis which is run on a set of 649 European cooperative banks using data between 2006 and 2015. Our results show that average inefficiency of European cooperative banks is increasing since 2008, smaller cooperative banks are significantly more efficient than the bigger ones over the whole time period and that share of net fee and commission income to total income surprisingly seems to have no impact on bank cost efficiency.

Keywords: cooperative banks, cost efficiency, efficient frontier analysis, stochastic frontier analysis, net fee and commission income

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Authors: Rossella Arcucci, Luisa D'Amore, Simone Celestino, Giuseppe Scotti, Giuliano Laccetti

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This work is the first dowel in a rather wide research activity in collaboration with Euro Mediterranean Center for Climate Changes, aimed at introducing scalable approaches in Ocean Circulation Models. We discuss designing and implementation of a parallel algorithm for solving the Variational Data Assimilation (DA) problem on Graphics Processing Units (GPUs). The algorithm is based on the fully scalable 3DVar DA model, previously proposed by the authors, which uses a Domain Decomposition approach (we refer to this model as the DD-DA model). We proceed with an incremental porting process consisting of 3 distinct stages: requirements and source code analysis, incremental development of CUDA kernels, testing and optimization. Experiments confirm the theoretic performance analysis based on the so-called scale up factor demonstrating that the DD-DA model can be suitably mapped on GPU architectures.

Keywords: data assimilation, GPU architectures, ocean models, parallel algorithm

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Authors: Katarzyna Niewiadomska

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Many technology startups fail to achieve a worthwhile return on investment for their funders, founders, and employees. Failures in product development, to-market strategy, sales, and delivery are commonly recognized. Founder failures are not as obvious and harder to identify. This paper explores six critical failure points that entrepreneurs and innovators are susceptible to and aims to link their emotional intelligence and behavioral profile to the points at which they experienced self-perceived failure. A model of six failure points from the perspective of the technology entrepreneur ranging from pre-startup to maturity is provided. By analyzing emotional and behavioral profile data from entrepreneurs and recording in-person accounts, certain key emotional and behavioral clusters contributing to each failure point are determined, and several underlying factors are defined and discussed. Recommendations that support entrepreneurs and innovators stalling at each failure point are given. This work can enable stakeholders to evaluate founder emotional and behavioral profiles and to take risk-mitigating action, either through coaching or through more robust team creation, to avoid founder-related company failure. The paper will be of interest to investors funding startups, executives leading them and mentors supporting them.

Keywords: behavior, emotional intelligence, entrepreneur, failure

Procedia PDF Downloads 232

Authors: Amanda T. Badaró, Douglas F. Barbin, Sofia T. Garcia, Maria Teresa P. S. Clerici, Amanda R. Ferreira

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Food fortification is the intentional addition of a nutrient in a food matrix and has been widely used to overcome the lack of nutrients in the diet or increasing the nutritional value of food. Fortified food must meet the demand of the population, taking into account their habits and risks that these foods may cause. Wheat and its by-products, such as semolina, has been strongly indicated to be used as a food vehicle since it is widely consumed and used in the production of other foods. These products have been strategically used to add some nutrients, such as fibers. Methods of analysis and quantification of these kinds of components are destructive and require lengthy sample preparation and analysis. Therefore, the industry has searched for faster and less invasive methods, such as Near-Infrared Spectroscopy (NIR). NIR is a rapid and cost-effective method, however, it is based on indirect measurements, yielding high amount of data. Therefore, NIR spectroscopy requires calibration with mathematical and statistical tools (Chemometrics) to extract analytical information from the corresponding spectra, as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). PCA is well suited for NIR, once it can handle many spectra at a time and be used for non-supervised classification. Advantages of the PCA, which is also a data reduction technique, is that it reduces the data spectra to a smaller number of latent variables for further interpretation. On the other hand, LDA is a supervised method that searches the Canonical Variables (CV) with the maximum separation among different categories. In LDA, the first CV is the direction of maximum ratio between inter and intra-class variances. The present work used a portable infrared spectrometer (NIR) for identification and classification of pure and fiber-fortified semolina samples. The fiber was added to semolina in two different concentrations, and after the spectra acquisition, the data was used for PCA and LDA to identify and discriminate the samples. The results showed that NIR spectroscopy associate to PCA was very effective in identifying pure and fiber-fortified semolina. Additionally, the classification range of the samples using LDA was between 78.3% and 95% for calibration and 75% and 95% for cross-validation. Thus, after the multivariate analysis such as PCA and LDA, it was possible to verify that NIR associated to chemometric methods is able to identify and classify the different samples in a fast and non-destructive way.

Keywords: Chemometrics, fiber, linear discriminant analysis, near-infrared spectroscopy, principal component analysis, semolina

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Authors: M. Mert, M. T. Ozkan

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Pile load tests should be applied to check the bearing capacity calculations and to determine the settlement of the pile corresponding to test load. Strain gauges can be installed into pile in order to determine the shaft resistance of the piles for every soil layer respectively. Detailed results can be obtained by means of strain gauges placed at certain levels into test piles. In the scope of this study, pile load test data obtained from two different projects are examined.  Instrumented static pile load tests were applied on totally 7 test bored piles of different diameters (80 cm, 150 cm, and 200 cm) and different lengths (between 30-76 m) in two different project site. Settlement analysis of test piles is done by using some of load transfer methods and finite element method. Plaxis 3D which is a three-dimensional finite element program is also used for settlement analysis of the test piles. In this study, firstly bearing capacity of test piles are determined and compared with strain gauge data which is required for settlement analysis. Then, settlement values of the test piles are estimated by using load transfer methods developed in recent years and finite element method. The aim of this study is to show similarities and differences between the results obtained from settlement analysis methods and instrumented pile load tests.

Keywords: failure, finite element method, monitoring and instrumentation, pile, settlement

Procedia PDF Downloads 176

Authors: Prajakta Khare

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There is a huge number of social enterprises operating in India, across all enterprise sizes and forms addressing diverse social issues. Some cases such as such as Aravind eye care, Narayana Hridalaya, SEWA have been studied extensively in management literature and are known cases in social entrepreneurship. But there are several smaller social enterprises in India that are not called so per se due to the lack of understanding of the concept. There is a lack of academic research on social entrepreneurship in India and the term ‘social entrepreneurship’ is not yet widely known in the country, even by people working in this field as was found by this study. The present study aims to identify the most prominent form of social enterprises in India, the profile of the entrepreneurs, challenges faced, the lessons (theory and practices) emerging from their functioning and finally the factors contributing to the enterprises’ success. This is a preliminary exploratory study using primary data from 30 social enterprises in India. The study used snow ball sampling and a qualitative analysis. Data was collected from founders of social enterprises through written structured questionnaires, open-ended interviews and field visits to enterprises. The sample covered enterprises across sectors such as environment, affordable education, children’s rights, rain water harvesting, women empowerment etc. The interview questions focused on founder’s background and motivation, qualifications, funding, challenges, founder’s understanding and perspectives on social entrepreneurship, government support, linkages with other organizations etc. apart from several others. The interviews were conducted across 3 languages - Hindi, Marathi, English and were then translated and transcribed. 50% of founders were women and 65% of the total founders were highly qualified with a MBA, PhD or MBBS. The most important challenge faced by these entrepreneurs is recruiting skilled people. When asked about their understanding of the term, founders had diverse perspectives. Also, their understandings about the term social enterprise and social entrepreneur were extremely varied. Some founders identified the terms with doing something good for the society, some thought that every business can be called a social enterprise. 35% of the founders were not aware of the term social entrepreneur/ social entrepreneurship. They said that they could identify themselves as social entrepreneurs after discussions with the researcher. The general perception in India is that ‘NGOs are corrupt’- fighting against this perception to secure funds is also another problem as pointed out by some founders. There are unique challenges that social entrepreneurs in India face, as the political, social, economic environment around them is rapidly changing; and getting adequate support from the government is a problem. The research in its subsequent stages aims to clarify existing, missing and new definitions of the term to provide deeper insights in the terminology and issues relating to Social Entrepreneurship in India.

Keywords: challenges, India, social entrepreneurship, social entrepreneurs

Procedia PDF Downloads 471