Search results for: data acquisition

Authors: Phusit Phukamchanoad, Thananya Santithammakul, Suwaree Yordchim, Pennapa Palapin

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This research gathered local wisdom towards career building of people in Kamchanoad Community, Baan Muang sub-district, Baan Dung district, Udon Thani province. Data was collected through in-depth interviews with village headmen, community board, teachers, monks, Kamchanoad forest managers and revered elderly aged over 60 years old. All of these 30 interviewees have resided in Kamchanoad Community for more than 40. Descriptive data analysis result revealed that the most prominent local wisdom of Kamchanoad community is their beliefs and religion. Most people in the community have strongly maintained local tradition, the festival of appeasing Chao Pu Sri Suttho on the middle of the 6th month of Thai lunar calendar which falls on the same day with Vesak Day. 100 percent of the people in this community are Buddhist. They believe that Naga, an entity or being, taking the form of a serpent, named “Sri Suttho” lives in Kamchanoad forest. The local people worship the serpent and ask for blessings. Another local wisdom of this community is Sinh fabric weaving.

Keywords: local wisdoms, careers, Kamchanoad Community, career building

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Authors: Azene Zenebe

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Deep learning is a subset of machine learning which incorporates techniques for the construction of artificial neural networks and found to be useful for modeling complex problems with large dataset. Deep learning requires a very high power computational and longer time for training. By aggregating computing power, high performance computer (HPC) has emerged as an approach to resolving advanced problems and performing data-driven research activities. Cyber threat intelligence (CIT) is actionable information or insight an organization or individual uses to understand the threats that have, will, or are currently targeting the organization. Results of review of literature will be presented along with results of experimental study that compares the performance of tree-based and function-base machine learning including deep learning algorithms using secondary dataset collected from darknet.

Keywords: deep-learning, cyber security, cyber threat modeling, tree-based machine learning, function-based machine learning, data science

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Authors: Prathik Ranka, Sridhar K, Vasanth Daniel, Mithun Shankar

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With growing global food needs and climate uncertainties, informed crop choices are critical for increasing agricultural productivity. Here we propose a machine learning-based crop recommendation system to help farmers in choosing the most proper crops according to their geographical regions and soil properties. We can deploy algorithms like Decision Trees, Random Forests and Support Vector Machines on a broad dataset that consists of climatic factors, soil characteristics and historical crop yields to predict the best choice of crops. The approach includes first preprocessing the data after assessing them for missing values, unlike in previous jobs where we used all the available information and then transformed because there was no way such a model could have worked with missing data, and normalizing as throughput that will be done over a network to get best results out of our machine learning division. The model effectiveness is measured through performance metrics like accuracy, precision and recall. The resultant app provides a farmer-friendly dashboard through which farmers can enter their local conditions and receive individualized crop suggestions.

Keywords: crop recommendation, precision agriculture, crop, machine learning

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Authors: Siwapong Dheera-Aumpon

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Resource misallocation is known to be prevalent in many countries. Such misallocation in the manufacturing sector is large and has a considerable negative effect on aggregate productivity. Thailand is one of the countries having large resource misallocation in the manufacturing sector. Resource misallocation is also known to be widespread in the agricultural sector. It is, therefore, likely that resource misallocation exists in the agricultural sector of Thailand as well. This study aims to evaluate the extent of resource misallocation in Thai rice farming. Using household-level data from 2013 Thai Agricultural Census, this study calculates farm total factor productivity (TFP) controlling for land quality and rain. Similar to the case of Malawi, marginal products of land and capital are found to be related to farm TFP implying large resource misallocation. The output gain from a reallocation of resources to their best use is 67 percent. The gain from reallocation is highest for farms in the southern region and followed by the northeastern region.

Keywords: agriculture, misallocation, productivity, rice

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Authors: Opara Monica, Suriani Ismail, Ahmad Iqmer Nashriq Mohd Nazan

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The true magnitude of the mortality and morbidity attributable to malaria worldwide is, at best, a scientific guess, although it is not disputable that the greatest burden is in sub-Saharan Africa. Those at highest risk are children younger than 5 years and pregnant women, particularly primigravidae. Nationally, malaria remains the third leading cause of death and is still considered a major public health problem. Therefore, this study is aimed to assess the effectiveness of health education intervention on insecticide-treated net use and its practices among pregnant women attending antenatal clinics. Materials and Methods: This study will be an intervention study with two arms double parallel randomized controlled trial (blinded) to be conducted in 3 stages. The first stage will develop health belief model (HBM) program, while in the second stage, pregnant women will be recruited, assessed (baseline data), randomized into two arms of the study, and follow-up for six months. The third stage will evaluate the impact of the intervention on HBM and disseminate the findings. Data will be collected with the use of a structured questionnaire which will contain validated tools. The main outcome measurement will be the treatment effect using HBM, while data will be analysed using SPSS, version 22. Discussion: The study will contribute to the existing knowledge on hospital-based care programs for pregnant women in developing countries where the literature is scanty. It will generally give insight into the importance of HBM measurement in interventional studies on malaria and other related infectious diseases in this setting.

Keywords: malaria, health education, insecticide-treated nets, sub-Saharan Africa

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Authors: Lunliang Zhong, Bin Duan

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The undergraduate graduation project is a vital part of the higher education curriculum, crucial for engineering accreditation. Current evaluations often summarize data without identifying underlying issues. This study applies the Peter-Clark algorithm to analyze causal relationships within the graduation project data of an Electronics and Information Engineering program, creating a causal model. Structural equation modeling confirmed the model's validity. The analysis reveals key teaching stages affecting project success, uncovering problems in the process. Introducing causal discovery and inference into project evaluation helps identify issues and propose targeted improvement measures. The effectiveness of these measures is validated by comparing the learning outcomes of two student cohorts, stratified by confounding factors, leading to improved teaching quality.

Keywords: causal discovery, causal inference, continuous improvement, Peter-Clark algorithm, structural equation modeling

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Authors: Mohammad Reza Boroumand Devlagh, Seyed Mohammad Hosein Razavi, Fatemeh Ahmadi, Azam Fazli Darzi

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The issue of female presence in Iran stadiums has long been considered and debated by governmental experts and authorities, however, no conclusion is yielded yet. Thus, the present study has been done with the aim of investigating the approach of male and female spectators about the presence of female spectators in Iranian stadiums. The statistical population of the study includes all male and female spectators who have not experienced the live watching of male championship matches in stadiums. 224 subjects from the statistical population have selected through stratified random sampling as the sample of the study. For data collection, researcher-made questionnaire has been used whose validity has been confirmed by the university professors and its reliability has been studied and confirmed through an preliminary study. (r= 0.81). Data analysis has been done using descriptive and referential statistics in P< 0.05. The results of the study showed that male and female were meaningfully agreed with the female presence in stadiums and there is no meaningful difference between male and female approaches concerning the female spectators’ presence in sport stadiums of Iran (sig= 0.867).

Keywords: male, female spectators, Iran, sport stadiums, population

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Authors: Ernest Nweke, Enkhtuya Bavuudorj

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The harsh realities of the scandalous failure of several notable corporations in the past two decades have inextricably resulted in a surge in corporate governance studies. Nevertheless, little or no attention has been paid to corporate governance studies in Mongolian firms and much less to the comprehension of the correlation among ownership structure, corporate governance mechanisms and trend of innovative activities. Innovation is the bed rock of enterprise success. However, the funding and support for innovative activities in many firms are to a great extent determined by the incentives provided by the firm’s internal and external governance mechanisms. Mongolia is an East Asian country currently undergoing a fast-paced transition from socialist to democratic system and it is a widely held view that private ownership as against public ownership fosters innovation. Hence, following the privatization policy of Mongolian Government which has led to the transfer of the ownership of hitherto state controlled and state directed firms to private individuals and organizations, expectations are high that sufficient motivation would be provided for firm managers to engage in innovative activities. This research focuses on the relationship between ownership structure, corporate governance on one hand and the level of innovation on the hand. The paper is empirical in nature and derives data from both reliable secondary and primary sources. Secondary data for the study was in respect of ownership structure of Mongolian listed firms and innovation trend in Mongolia generally. These were analyzed using tables, charts, bars and percentages. Personal interviews and surveys were held to collect primary data. Primary data was in respect of corporate governance practices in Mongolian firms and were collected using structured questionnaire. Out of a population of three hundred and twenty (320) companies listed on the Mongolian Stock Exchange (MSE), a sample size of thirty (30) randomly selected companies was utilized for the study. Five (5) management level employees were surveyed in each selected firm giving a total of one hundred and fifty (150) respondents. Data collected were analyzed and research hypotheses tested using Chi-Square test statistic. Research results showed that corporate governance mechanisms were better and have significantly improved overtime in privately held as opposed to publicly owned firms. Consequently, the levels of innovation in privately held firms were considerably higher. It was concluded that a significant and positive relationship exists between private ownership and good corporate governance on one hand and the level of funding provided for innovative activities in Mongolian firms on the other hand.

Keywords: corporate governance, innovation, ownership structure, stock exchange

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Authors: Lucie Cote, Isabelle Rodier

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The main objective of the research was to identify demonstrated mechanisms promoting psychological well-being and psychological health in the workplace, and to take a critical look at the 'National Standard of Canada for Psychological Health and Safety in the Workplace - Prevention, Promotion and Guidance to Staged Implementation (Standard)' as a mechanism to promote the psychological well-being and psychological health in the workplace. A review of the scientific literature was conducted, and a case study was done using data from a Canadian federal department. The following six mechanisms with an efficiency supported by most of the studies reviewed were identified: improving psychological well-being in the workplace literacy; strengthening the resilience of employees; creating an environmentally friendly and healthy workplace; promoting a healthy lifestyle; taking into account psychological characteristics in the drafting of job descriptions and tasks during the hiring process; and offering psychological self-care tools. The Standard offers several mechanisms beyond those previously identified and their implementation can be demanding. Research based on objective data and addressing the magnitude of the effect would be required.

Keywords: critical review, national standard of Canada, psychological health, workplace

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Authors: Yue Huang, Hongcheng Gan

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The new urbanization pattern has led to a rapid growth in demand for short-distance intercity travel, and the emergence of new travel modes has also increased the variety of intercity travel options. In previous studies on intercity travel mode choice behavior, the impact of functional amenities of travel mode and travelers’ long-term personality characteristics has rarely been considered, and empirical results have typically been calibrated using revealed preference (RP) or stated preference (SP) data. This study designed a questionnaire that combines the RP and SP experiment from the perspective of a trip chain combining inner-city and intercity mobility, with consideration for the actual condition of the Huainan-Hefei traffic corridor. On the basis of RP/SP fusion data, a hybrid choice model considering both random taste heterogeneity and psychological characteristics was established to investigate travelers’ mode choice behavior for traditional train, high-speed rail, intercity bus, private car, and intercity online car-hailing. The findings show that intercity time and cost exert the greatest influence on mode choice, with significant heterogeneity across the population. Although inner-city cost does not demonstrate a significant influence, inner-city time plays an important role. Service attributes of travel mode, such as catering and hygiene services, as well as free wireless network supply, only play a minor role in mode selection. Finally, our study demonstrates that safety-seeking tendency, hedonism, and introversion all have differential and significant effects on intercity travel mode choice.

Keywords: intercity travel mode choice, stated preference survey, hybrid choice model, RP/SP fusion data, psychological latent variable, heterogeneity

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Authors: Xiaohan Bookman, Xiaoyan Zhu

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Margin-Based Principle has been proposed for a long time, it has been proved that this principle could reduce the structural risk and improve the performance in both theoretical and practical aspects. Meanwhile, feed-forward neural network is a traditional classifier, which is very hot at present with a deeper architecture. However, the training algorithm of feed-forward neural network is developed and generated from Widrow-Hoff Principle that means to minimize the squared error. In this paper, we propose a new training algorithm for feed-forward neural networks based on Margin-Based Principle, which could effectively promote the accuracy and generalization ability of neural network classifiers with less labeled samples and flexible network. We have conducted experiments on four UCI open data sets and achieved good results as expected. In conclusion, our model could handle more sparse labeled and more high-dimension data set in a high accuracy while modification from old ANN method to our method is easy and almost free of work.

Keywords: Max-Margin Principle, Feed-Forward Neural Network, classifier, structural risk

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Authors: Ibrahim Masud, Yusheng Kong, Adam Diyawu Rahman

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Mobile payment variously referred to as mobile money, mobile money transfer, and mobile wallet refers to payment services operated under financial regulation and performed from or via a mobile device. Mobile payment systems have come to augment and to some extent try to replace the conventional payment methods like cash, cheque, or credit cards. This study examines mobile payment adoption factors among retailers in Ghana. A conceptual framework was adopted from the extant literature using the Technology Acceptance Model and the Theory of Reasoned action as the theoretical bases. Data for the study was obtained from a sample of 240 respondents through a structured questionnaire. The PLS-SEM was used to analyze the data through SPSS v.22 and SmartPLS v.3. The findings indicate that factors such as perceived usefulness, perceived ease of use, perceived security, competitive pressure and facilitating conditions are the main determinants of mobile payment adoption among retailers in Ghana. The study contributes to the literature on mobile payment adoption from developing country context.

Keywords: mobile payment, retailers, structural equation modeling, technology acceptance model

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Authors: Hossein Havaeji, Tony Wong, Thien-My Dao

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1. Research Problems and Research Objectives: Blockchain Technology-enabled Supply Chain System (BT-enabled SCS) is the system using BT to drive SCS transparency, security, durability, and process integrity as SCS data is not always visible, available, or trusted. The costs of operating BT in the SCS are a common problem in several organizations. The costs must be estimated as they can impact existing cost control strategies. To account for system and deployment costs, it is necessary to overcome the following hurdle. The problem is that the costs of developing and running a BT in SCS are not yet clear in most cases. Many industries aiming to use BT have special attention to the importance of BT installation cost which has a direct impact on the total costs of SCS. Predicting BT installation cost in SCS may help managers decide whether BT is to be an economic advantage. The purpose of the research is to identify some main BT installation cost components in SCS needed for deeper cost analysis. We then identify and categorize the main groups of cost components in more detail to utilize them in the prediction process. The second objective is to determine the suitable Supervised Learning technique in order to predict the costs of developing and running BT in SCS in a particular case study. The last aim is to investigate how the running BT cost can be involved in the total cost of SCS. 2. Work Performed: Applied successfully in various fields, Supervised Learning is a method to set the data frame, treat the data, and train/practice the method sort. It is a learning model directed to make predictions of an outcome measurement based on a set of unforeseen input data. The following steps must be conducted to search for the objectives of our subject. The first step is to make a literature review to identify the different cost components of BT installation in SCS. Based on the literature review, we should choose some Supervised Learning methods which are suitable for BT installation cost prediction in SCS. According to the literature review, some Supervised Learning algorithms which provide us with a powerful tool to classify BT installation components and predict BT installation cost are the Support Vector Regression (SVR) algorithm, Back Propagation (BP) neural network, and Artificial Neural Network (ANN). Choosing a case study to feed data into the models comes into the third step. Finally, we will propose the best predictive performance to find the minimum BT installation costs in SCS. 3. Expected Results and Conclusion: This study tends to propose a cost prediction of BT installation in SCS with the help of Supervised Learning algorithms. At first attempt, we will select a case study in the field of BT-enabled SCS, and then use some Supervised Learning algorithms to predict BT installation cost in SCS. We continue to find the best predictive performance for developing and running BT in SCS. Finally, the paper will be presented at the conference.

Keywords: blockchain technology, blockchain technology-enabled supply chain system, installation cost, supervised learning

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Authors: Denvi Giovanita, Wustari L. H. Mangundjaya

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The pace of globalization and technological development make changes inevitable to organizations. However, organizational change is not easy to implement and is prone to failure. One of the reasons of change failure is due to lack of employees’ commitment to change. There are many variables that can influence employees’ commitment to change. The influencing factors can be sourced from the organization or individuals themselves. This study focuses on the affective form of commitment to change. The objective of this study is to identify the effect of transformational leadership (organizational factor) and employees’ change self-efficacy (individual factor) on affective commitment to change. The respondents of this study were employees who work in organizations that are or have faced organizational change. The data were collected using Affective Commitment to Change, Change Self-Efficacy, and Transformational Leadership Inventory. The data were analyzed using regression. The result showed that both transformational leadership and change self-efficacy have a positive and significant impact on affective commitment to change. The implication of the study can be used for practitioners to enhance the success of organizational change, by developing transformational leadership on the leaders and change self-efficacy on the employees in order to create a high affective commitment to change.

Keywords: affective commitment to change, change self-efficacy, organizational change, transformational leadership

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Authors: Wahid Ahmad Dar, Irshad Ahmad Najar

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The influence of social media is percolating to every corner of our social life. It is also changing the social sphere of the classroom in particular and education in general. This paper tries to explore the ways in which social media is influencing student-teacher relationship. Differences have been found in student’s ability to draw benefits from using ICT. Besides digital divides in access and usage, there are attitudinal differences among students towards ICT aligned with traditional forms of social differences. The paper particularly focusses on how students from diverse backgrounds are using social media to interact with their teachers and how such interactions differ on the basis of social class, gender and residential background of students. A qualitative research methodology has been used for answering these questions. Open-ended questionnaire has been designed and administered to a sample of postgraduate students from University of Kashmir drawn purposively ensuring optimum number of subjects from all backgrounds. The data were analyzed by content analysis, deciphering general patterns in the data.

Keywords: social media, student-teacher relationship, social class, gender

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Authors: Rym Ghariani, Younes Boujelbene

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In contemporary times, global technological advancements, particularly those in the realm of digital technology, have emerged as pivotal instruments for enterprises in fostering viable partnerships and forging meaningful alliances with other firms. The advent of these digital innovations is poised to revolutionize nearly every facet and operation within corporate entities. The primary objective of this study is to explore the correlation between digitization, integration of supply chains, and the financial efficacy of the agro-industrial sector in Tunisia. To accomplish this, data collection employed a questionnaire as the primary research instrument. Subsequently, the research queries were addressed, and hypotheses were examined by subjecting the gathered data to principal component analysis and linear regression modeling, facilitated by the utilization of SPSS26 software. The findings revealed that digitalization within the supply chain, along with external supply chain integration, exerted discernible impacts on the financial performance of the organization.

Keywords: digitalization, supply chain integration, financial performance, Tunisian agro-industrial sector

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Authors: Domenico Chizzoniti, Monica Moscatelli, Letizia Cattani, Piero Favino, Luca Preis

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A settlement strategy is to anticipate and respond the needs of existing and future communities through the provision of primary health care facilities in marginalized areas. Access to a health care network is important to improving healthcare coverage, often lacking, in developing countries. The study explores that a good sanitary system strategy of rural contexts brings advantages to an existing settlement: improving transport, communication, water and social facilities. The objective of this paper is to define a possible methodology to implement primary health care facilities in disadvantaged areas of emerging countries. In this research, we analyze the case study of Lauro de Freitas, a municipality in the Brazilian state of Bahia, part of the Metropolitan Region of Salvador, with an area of 57,662 km² and 194.641 inhabitants. The health localization system in Lauro de Freitas is an integrated process that involves not only geographical aspects, but also a set of factors: population density, epidemiological data, allocation of services, road networks, and more. Data were collected also using semi-structured interviews and questionnaires to the local population. Synthesized data suggest that moving away from the coast where there is the greatest concentration of population and services, a network of primary health care facilities is able to improve the living conditions of small-dispersed communities. Based on the health service needs of populations, we have developed a methodological approach that is particularly useful in rural and remote contexts in emerging countries.

Keywords: healthcare, settlement strategy, urban health, rural

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Authors: Nuno Biga

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The integration of serious games with gamification in management education and training has gained significant importance in recent years as innovative strategies are sought to improve target audience engagement and learning outcomes. This research builds on the author's previous work in this field and presents a case study that evaluates the ex-post impact of a sample of applications of the BIGAMES management simulator in the training of top managers from various hospital institutions. The methodology includes evaluating the reaction of participants after each edition of BIGAMES Accident & Emergency (A&E) carried out over the last 3 years, as well as monitoring the career path of a significant sample of participants and their feedback more than a year after their experience with this simulator. Control groups will be set up, according to the type of role their members held when they took part in the BIGAMES A&E simulator: Administrators, Clinical Directors and Nursing Directors. Former participants are invited to answer a questionnaire structured for this purpose, where they are asked, among other questions, about the importance and impact that the BIGAMES A&E simulator has had on their professional activity. The research methodology also includes an exhaustive literature review, focusing on empirical studies in the field of education and training in management and business that investigate the effectiveness of gamification and serious games in improving learning, team collaboration, critical thinking, problem-solving skills and overall performance, with a focus on training contexts in the health sector. The results of the research carried out show that gamification and serious games that simulate real scenarios, such as Business Interactive Games - BIGAMES©, can significantly increase the motivation and commitment of participants, stimulating the development of transversal skills, the mobilization of group synergies and the acquisition and retention of knowledge through interactive user-centred scenarios. Individuals who participate in game-based learning series show a higher level of commitment to learning because they find these teaching methods more enjoyable and interactive. This research study aims to demonstrate that, as executive education and training programs develop to meet the current needs of managers, gamification and serious games stand out as effective means of bridging the gap between traditional teaching methods and modern educational and training requirements. To this end, this research evaluates the medium/long-term effects of gamified learning on the professional performance of participants in the BIGAMES simulator applied to healthcare. Based on the conclusions of the evaluation of the effectiveness of training using gamification and taking into account the results of the opinion poll of former A&E participants, this research study proposes an integrated approach for the transversal application of the A&E Serious Game in various educational contexts, covering top management (traditionally the target audience of BIGAMES A&E), middle and operational management in healthcare institutions (functional area heads and professionals with career development potential), as well as higher education in medicine and nursing courses. The integrated solution called “BIGAMES A&E plus”, developed as part of this research, includes the digitalization of key processes and the incorporation of AI.

Keywords: artificial intelligence (AI), executive training, gamification, higher education, management simulators, serious games (SG), training effectiveness

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Authors: Mohamed El Hattab

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The Supercritical carbon dioxide (SFE) and the focused microwave-assisted hydrodistillation (FMAHD) were employed to isolate the volatile fraction of the brown alga Dictyopteris membranacea from the crude extract. The volatiles fractions obtained were analyzed by GC/MS. The major compounds in this case: dictyopterene A, 6-butylcyclohepta-1,4-diene, Undec-1-en-3-one, Undeca-1,4-dien-3-one, (3-oxoundec-4-enyl) sulphur, tetradecanoic acid, hexadecanoic acid, 3-hexyl-4,5-dithia-cycloheptanone and albicanol (this later is present only in the FMAHD oil) are identified by comparing their mass spectra with those reported on the commercial MS data base and also on our previously work. A kinetic study realized on both extraction processes and followed by an external standard quantification has allowed the study of the mass percent evolution of the major compounds in the two oils, an empirical mathematical modelling was used to describe their kinetic extraction.

Keywords: dictyopteris membranacea, extraction techniques, mathematical modeling, volatile oils

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Authors: Tahereh Yavari, Sara Norozi Far

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The aim of this study was to compare psychological well-being, hope, and health concerns in leukemia patients before and after receiving stem cells. The statistical population of the present study was made up of leukemia patients in Tehran, and the research sample was among the patients referred to the Bone Marrow Transplant Center of Shariati Hospital in Tehran, and they were placed in two experimental and control groups (15 people in each group), which were selected by purposive sampling method. In order to collect the data for the research, three psychological well-being questionnaires were used by Riff (2002), Schneider's Hope Scale (SHS), and Schneider's Health Concern Questionnaire (HCQ). In order to analyze the data in this research, according to the "pre-test-post-test design with a control group," covariance analysis was used. Based on the research findings, it was concluded that receiving stem cells increases hope and psychological well-being in leukemia patients and significantly reduces health concerns.

Keywords: psychological well-being, hope, health concerns, blood cancer, stem cells

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Authors: Oti Ibiam, Alexanda O. Kalu

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Human Resource Accounting is the process of identifying and measuring data about human resources and communicating this information to interested parties in order to meaningful investment decisions. In recent time, firms focus has shifted to human resource accounting so as to ensure efficiency and effectiveness in their operations. This study focused on the effect of human resource accounting on the financial performance of Banks in Nigerian. The problem that led to the study revolves around the current trend whereby Nigeria banks do not efficiently account for the input of human resource in their annual statement, thereby instead of capitalizing human resources in their statement of financial position; they expend it in their income statement thereby reducing their profit after tax. The broad objective of this study is to determine the extent to which human resource accounting affects the financial performance and value of Nigerian Banks. This study is therefore considered significant because, there are still universally, grey areas to be sorted out on the subject matter of human resources accounting. In the bid to achieve the study objectives, the researcher gathered data from sixteen commercial banks. Data were collected from both primary and secondary sources using an ex-post facto research design. The data collected were then tabulated and analyzed using the multiple regression analysis. The result of hypothesis one revealed that there is a significant relationship between Capitalized Human Resource Cost and post capitalization Profit before tax of banks in Nigeria. The finding of hypothesis two revealed that the association between Capitalized Human Resource Cost and post capitalization Net worth of banks in Nigeria is significant. The finding in Hypothesis three reveals that there is a significant difference between pre and post capitalization profit before tax of banks in Nigeria. The study concludes that human resources accounting positively influenced financial performance of banks in Nigeria within the period under study. It is recommended that standards should be set for human resources identification and measurement in the banking sector and also the management of commercial banks in Nigeria should have a proper appreciation of human resource accounting. This will enable managers to take right decision regarding investment in human resource. Also, the study recommends that policies on enhancing the post capitalization profit before tax of banks in Nigeria should pay great attention to capitalized human resources cost, net worth and total asset as the variables significantly influenced post capitalization profit before tax of the studied banks in Nigeria. The limitation of the study centers on the limited number of years and companies that was adopted for the study.

Keywords: capitalization, human resources cost, profit before tax, net worth

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Authors: Murat Iskender Aktaş, Sadi Ergin, Rasime Acar Aktaş

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In the light of fast-paced changes and developments in the health sector, the Ministry of Health started a new structuring with decree law numbered 663 within the scope of the Project of Transformation in Health. Accordingly, hospitals should ensure patient satisfaction through more efficient, more effective use of resources and sustainable finance by placing patients in the centre and should operate to increase efficiency to its maximum level while doing these. Within this study, in order to find out how efficient the hospitals were in terms of medical waste management between the years 2011-2014, the data from six hospitals of Amasya Public Hospitals Union were evaluated separately through Data Envelopment Analysis (DEA) method. First of all, input variables were determined. Input variables were the number of patients admitted to polyclinics, the number of inpatients in clinics, the number of patients who were operated and the number of patients who applied to the laboratory. Output variable was the cost of medical wastes in Turkish liras. Each hospital’s total medical waste level before and after public hospitals union; the amounts of average medical waste per patient admitted to polyclinics, per inpatient in clinics, per patient admitted to laboratory and per operated patient were compared within each group. In addition, average medical waste levels and costs were compared for Turkey in general and Europe in general. Paired samples t-test was used to find out whether the changes (increase-decrease) after public hospitals union were statistically significant. The health facilities that were unsuccessful in terms of medical waste management before and after public hospital union and the factors that caused this failure were determined. Based on the results, for each health facility that was ineffective in terms of medical waste management, the level of improvement required for each input was determined. The results of the study showed that there was an improvement in medical waste management applications after the health facilities became a member of public hospitals union; their medical waste levels were lower than the average of Turkey and Europe while the averages of cost of disposal were the highest.

Keywords: medical waste management, cost of medical waste, public hospitals, data envelopment analysis

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Authors: Pius Marthin, Nihal Ata Tutkun

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Survival analysis has become one of the paramount procedures in the modeling of time-to-event data. When we encounter complex survival problems, the traditional approach remains limited in accounting for the complex correlational structure between the covariates and the outcome due to the strong assumptions that limit the inference and prediction ability of the resulting models. Several studies exist on the deep learning approach to survival modeling; moreover, the application for the case of complex survival problems still needs to be improved. In addition, the existing models need to address the data structure's complexity fully and are subject to noise and redundant information. In this study, we design a deep learning technique (CmpXRnnSurv_AE) that obliterates the limitations imposed by traditional approaches and addresses the above issues to jointly predict the risk-specific probabilities and survival function for recurrent events with competing risks. We introduce the component termed Risks Information Weights (RIW) as an attention mechanism to compute the weighted cumulative incidence function (WCIF) and an external auto-encoder (ExternalAE) as a feature selector to extract complex characteristics among the set of covariates responsible for the cause-specific events. We train our model using synthetic and real data sets and employ the appropriate metrics for complex survival models for evaluation. As benchmarks, we selected both traditional and machine learning models and our model demonstrates better performance across all datasets.

Keywords: cumulative incidence function (CIF), risk information weight (RIW), autoencoders (AE), survival analysis, recurrent events with competing risks, recurrent neural networks (RNN), long short-term memory (LSTM), self-attention, multilayers perceptrons (MLPs)

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Authors: Yu Yitian, Chen Kaizhe, Liu Jin

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'Glass ceiling' phenomenon refers to the invisible barriers that specific groups encounter in career advancement within organizations. This phenomenon is widespread all over the world and is prevalent among university faculty. However, there has been limited attention in the previous studies on Chinese university faculty. This research mainly focuses on whether the existence of 'glass ceiling' phenomenon exists among female faculty in the Chinese academic community and the characteristics among different disciplines in China. By utilizing the big data from education faculty members in 149 research-oriented universities in China, the research employs a Curriculum Vitae analysis to draw the academic career trajectories of faculty, along with potential variations across different academic disciplines within the Chinese academic landscape. This research addresses the existing gap in the scholarly investigation of gender equality in China and is helpful to promote gender equality in the academic community.

Keywords: big data, China academic community, curriculum vitae analysis, glass ceiling

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Authors: Mustafa Ekici, Sacide Güzin Mazman

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Programming is the one of ability in computer science fields which is generally perceived difficult by students and various individual differences have been implicated in that ability success. Although several factors that affect programming ability have been identified over the years, there is not still a full understanding of why some students learn to program easily and quickly while others find it complex and difficult. Programming self-efficacy and mathematic success are two of those essential individual differences which are handled as having important effect on the programming success. This study aimed to identify the relationship between programming performance, programming self efficacy and mathematics success. The study group is consisted of 96 undergraduates from Department of Econometrics of Uşak University. 38 (39,58%) of the participants are female while 58 (60,41%) of them are male. Study was conducted in the programming-I course during 2014-2015 fall term. Data collection tools are comprised of programming course final grades, programming self efficacy scale and a mathematics achievement test. Data was analyzed through correlation analysis. The result of study will be reported in the full text of the study.

Keywords: programming performance, self efficacy, mathematic success, computer science

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Authors: Jorge M. Uribe

Abstract:

We propose a methodology for setting the price of an insurance contract targeted to manage the risk associated with weather conditions that affect variable renewable energy generation. The methodology relies on conditional quantile regressions to estimate the weather risk of a solar panel. It is illustrated using real daily radiation and weather data for three cities in Spain (Valencia, Barcelona and Madrid) from February 2/2004 to January 22/2019. We also adapt the concepts of value at risk and expected short fall from finance to this context, to provide a complete panorama of what we label as weather risk. The methodology is easy to implement and can be used by insurance companies to price a contract with the aforementioned characteristics when data about similar projects and accurate cash flow projections are lacking. Our methodology assigns a higher price to an insurance product with the stated characteristics in Madrid, compared to Valencia and Barcelona. This is consistent with Madrid showing the largest interquartile range of operational deficits and it is unrelated to the average value deficit, which illustrates the importance of our proposal.

Keywords: insurance, weather, vre, risk

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Authors: Wen Luo, Phil J. Vardon, Anne-Catherine Dieudonne

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One key process that partly controls the success of geothermal projects is fluid reinjection, which benefits in dealing with waste water, maintaining reservoir pressure, and supplying heat-exchange media, etc. Thus, sustaining the injectivity is of great importance for the efficiency and sustainability of geothermal production. However, the injectivity is sensitive to the reinjection process. Field experiences have illustrated that the injectivity can be damaged or improved. In this paper, the focus is on how the injectivity is improved. Since the injection pressure is far below the formation fracture pressure, hydraulic fracturing cannot be the mechanism contributing to the increase in injectivity. Instead, thermal stimulation has been identified as the main contributor to improving the injectivity. For low-enthalpy geothermal reservoirs, which are not fracture-controlled, thermal fracturing, instead of thermal shearing, is expected to be the mechanism for increasing injectivity. In this paper, field data from the sedimentary low-enthalpy geothermal reservoirs in the Netherlands were analysed to show the occurrence of thermal fracturing due to the cooling shock during reinjection. Injection data were collected and compared to show the effects of the thermal fractures on injectivity. Then, a thermo-hydro-mechanical (THM) model for the near field formation was developed and solved by finite element method to simulate the observed thermal fractures. It was then compared with the HM model, decomposed from the THM model, to illustrate the thermal effects on thermal fracturing. Finally, the effects of operational parameters, i.e. injection temperature and pressure, on the changes in injectivity were studied on the basis of the THM model. The field data analysis and simulation results illustrate that the thermal fracturing occurred during reinjection and contributed to the increase in injectivity. The injection temperature was identified as a key parameter that contributes to thermal fracturing.

Keywords: injectivity, reinjection, thermal fracturing, thermo-hydro-mechanical model

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Authors: Syed Asif Ali Naqvi, Muhammad Azeem Tufail

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Inadequate sanitation causes direct costs of treating illnesses and loss of income through reduced productivity. This study estimated the economic cost of health (ECH) due to poor sanitation and factors determining the lack of access to latrine for the rural, backward hamlets and slums of district Faisalabad, Pakistan. Cross sectional data were collected and analyzed for the study. As the population under study was homogenous in nature, it is why a simple random sampling technique was used for the collection of data. Data of 440 households from 4 tehsils were gathered. The ordinary least square (OLS) model was used for health cost analysis, and the Probit regression model was employed for determining the factors responsible for inaccess to toilets. The results of the study showed that condition of toilets, situation of sewerage system, access to adequate sanitation, Cholera, diarrhea and dysentery, Water and Sanitation Agency (WASA) maintenance, source of medical treatment can plausibly have a significant connection with the dependent variable. Outcomes of the second model showed that the variables of education, family system, age, and type of dwelling have positive and significant sway with the dependent variable. Variable of age depicted an insignificant association with access to toilets. Variable of monetary expenses would negatively influence the dependent variable. Findings revealed the fact, health risks are often exacerbated by inadequate sanitation, and ultimately, the cost on health also surges. Public and community toilets for youths and social campaigning are suggested for public policy.

Keywords: sanitation, toilet, economic cost of health, water, Punjab

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Authors: Libor Zachoval, Daire O Broin, Oisin Cawley

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E-learning platforms, such as Blackboard have two major shortcomings: limited data capture as a result of the limitations of SCORM (Shareable Content Object Reference Model), and lack of incorporation of Artificial Intelligence (AI) and machine learning algorithms which could lead to better course adaptations. With the recent development of Experience Application Programming Interface (xAPI), a large amount of additional types of data can be captured and that opens a window of possibilities from which online education can benefit. In a corporate setting, where companies invest billions on the learning and development of their employees, some learner behaviours can be troublesome for they can hinder the knowledge development of a learner. Behaviours that hinder the knowledge development also raise ambiguity about learner’s knowledge mastery, specifically those related to gaming the system. Furthermore, a company receives little benefit from their investment if employees are passing courses without possessing the required knowledge and potential compliance risks may arise. Using xAPI and rules derived from a state-of-the-art review, we identified three learner behaviours, primarily related to guessing, in a corporate compliance course. The identified behaviours are: trying each option for a question, specifically for multiple-choice questions; selecting a single option for all the questions on the test; and continuously repeating tests upon failing as opposed to going over the learning material. These behaviours were detected on learners who repeated the test at least 4 times before passing the course. These findings suggest that gauging the mastery of a learner from multiple-choice questions test scores alone is a naive approach. Thus, next steps will consider the incorporation of additional data points, knowledge estimation models to model knowledge mastery of a learner more accurately, and analysis of the data for correlations between knowledge development and identified learner behaviours. Additional work could explore how learner behaviours could be utilised to make changes to a course. For example, course content may require modifications (certain sections of learning material may be shown to not be helpful to many learners to master the learning outcomes aimed at) or course design (such as the type and duration of feedback).

Keywords: artificial intelligence, corporate e-learning environment, knowledge maintenance, xAPI

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Authors: Amir Abbas Fatemi, Zahra Tabrizian, Kabir Sadeghi

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To find the location and severity of damage that occurs in a structure, characteristics changes in dynamic and static can be used. The non-destructive techniques are more common, economic, and reliable to detect the global or local damages in structures. This paper presents a non-destructive method in structural damage detection and assessment using GA and static data. Thus, a set of static forces is applied to some of degrees of freedom and the static responses (displacements) are measured at another set of DOFs. An analytical model of the truss structure is developed based on the available specification and the properties derived from static data. The damages in structure produce changes to its stiffness so this method used to determine damage based on change in the structural stiffness parameter. Changes in the static response which structural damage caused choose to produce some simultaneous equations. Genetic Algorithms are powerful tools for solving large optimization problems. Optimization is considered to minimize objective function involve difference between the static load vector of damaged and healthy structure. Several scenarios defined for damage detection (single scenario and multiple scenarios). The static damage identification methods have many advantages, but some difficulties still exist. So it is important to achieve the best damage identification and if the best result is obtained it means that the method is Reliable. This strategy is applied to a plane truss. This method is used for a plane truss. Numerical results demonstrate the ability of this method in detecting damage in given structures. Also figures show damage detections in multiple damage scenarios have really efficient answer. Even existence of noise in the measurements doesn’t reduce the accuracy of damage detections method in these structures.

Keywords: damage detection, finite element method, static data, non-destructive, genetic algorithm

Procedia PDF Downloads 237