Search results for: soft decision fusion

Authors: Alan Bhekisisa Buthelezi

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The aim of this paper is to explore African management and leadership philosophies at secondary schools in post-apartheid South Africa. The research was conducted in the King Cetshwayo district of KwaZulu-Natal province in South Africa. Apart from the literature on participative management, the paper reports on research in which an empirical investigation based on a quantitative research paradigm was used to collect data from secondary school principals. The literature findings revealed that secondary school principals need to rethink their management and leadership philosophies in the twenty-first century. The findings of this research further reveal that ubuntu (humanness) and lekgotla (Sesotho term for ‘an African participatory approach to decision-making’) should be embedded in the art of school management and leadership in the South African context. The paper concludes with the submission that ongoing capacity-building workshops should be fast-tracked on matters pertaining to management and leadership.

Keywords: transformational leadership, distributed leadership, team leadership, decentralisation of power

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Authors: Niloufar Yadgari

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GANs are a potent form of deep learning models that have found success in various fields. They are part of the larger group of generative techniques, which aim to produce authentic data using a probabilistic model that learns distributions from actual samples. In clinical settings, GANs have demonstrated improved abilities in capturing spatially intricate, nonlinear, and possibly subtle disease impacts in contrast to conventional generative techniques. This review critically evaluates the current research on how GANs are being used in imaging studies of different neurological conditions like Alzheimer's disease, brain tumors, aging of the brain, and multiple sclerosis. We offer a clear explanation of different GAN techniques for each use case in neuroimaging and delve into the key hurdles, unanswered queries, and potential advancements in utilizing GANs in this field. Our goal is to connect advanced deep learning techniques with neurology studies, showcasing how GANs can assist in clinical decision-making and enhance our comprehension of the structural and functional aspects of brain disorders.

Keywords: GAN, pathology, generative adversarial network, neuro imaging

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Authors: Y. Rathiranee, D. M. Semasinghe

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This study attempts to identify the factors influencing on women empowerment of rural area in Sri Lanka through micro finance services. Data were collected from one hundred (100) rural women involving self employment activities through a questionnaire using direct personal interviews. Judgment and Convenience Random sampling technique was used to select the sample size from three Divisional Secretariat divisions of Kandawalai, Poonakari and Karachchi in Kilinochchi District. The factor analysis was performed on fourteen (14) variables for screening and reducing the variables to identify the influencing factors on empowerment. Multiple regression analysis was used to identify the relationship between the three empowerment factors and the impact of micro-finance on overall empowerment of rural women. The result of this study summarized the variables into three factors namely decision making, freedom to mobility and family support and which are positively associated with empowerment. In addition to this the value of adjusted R2 is 0.248 indicates that all the variables extracted can be explained 24.8% of the variation in the women empowerment through microfinance. Independent variables of these three factors have a positive correlation with women empowerment as well as significant values at 5 percent level.

Keywords: influencing factors, micro finance, rural women, women empowerment

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Authors: Daehyoung Kim, Pervez Khan, Hoon Kim

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Efficient utilization of spectrum resources is a fundamental issue of wireless communications due to its scarcity. To improve the efficiency of spectrum utilization, the spectrum sharing for unlicensed bands is being regarded as one of key technologies in the next generation wireless networks. A number of schemes such as Listen-Before-Talk(LBT) and carrier sensor adaptive transmission (CSAT) have been suggested from this aspect, but more efficient sharing schemes are required for improving spectrum utilization efficiency. This work considers an opportunistic transmission approach and a dynamic Contention Window (CW) adjustment scheme for LTE-U users sharing the unlicensed spectrum with Wi-Fi, in order to enhance the overall system throughput. The decision criteria for the dynamic adjustment of CW are based on the collision evaluation, derived from the collision probability of the system. The overall performance can be improved due to the adaptive adjustment of the CW. Simulation results show that our proposed scheme outperforms the Distributed Coordination Function (DCF) mechanism of IEEE 802.11 MAC.

Keywords: spectrum sharing, adaptive opportunistic transmission, unlicensed bands, heterogeneous networks

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Authors: Iyad Ismail, Fathilatul Abdul Hamid

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This research was mainly investigated to recognize the extent of big data analysis by external auditors. This paper adopts grounded theory as a framework for conducting a series of semi-structured interviews with eighteen external auditors. The research findings comprised the availability extent of big data and big data analysis usage by the external auditors in Palestine, Gaza Strip. Considering the study's outcomes leads to a series of auditing procedures in order to improve the external auditing techniques, which leads to high-quality audit process. Also, this research is crucial for auditing firms by giving an insight into the mechanisms of auditing firms to identify the most important strategies that help in achieving competitive audit quality. These results are aims to instruct the auditing academic and professional institutions in developing techniques for external auditors in order to the big data analysis. This paper provides appropriate information for the decision-making process and a source of future information which affects technological auditing.

Keywords: big data analysis, external auditors, audit reliance, internal audit function

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Authors: Dimitra Alexiou

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During the last 10 years, in spite of the economic crisis, the number of tourists arriving in Greece has increased, particularly during the tourist season from April to October. In this paper, the number of annual tourist arrivals is studied to explore their preferences with regard to the month of travel, the selected destinations, as well the amount of money spent. The collected data are processed with statistical methods, yielding numerical and graphical results. From the computation of statistical parameters and the forecasting with exponential smoothing, useful conclusions are arrived at that can be used by the Greek tourism authorities, as well as by tourist organizations, for planning purposes for the coming years. The results of this paper and the computed forecast can also be used for decision making by private tourist enterprises that are investing in Greece. With regard to the statistical methods, the method of Simple Exponential Smoothing of time series of data is employed. The search for a best forecast for 2017 and 2018 provides the value of the smoothing coefficient. For all statistical computations and graphics Microsoft Excel is used.

Keywords: tourism, statistical methods, exponential smoothing, land spatial planning, economy

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Authors: Joko Nurkamto

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A lesson plan is a part of the planning phase in a learning and teaching system framing the scenario of pedagogical activities in the classroom. It informs a decision on what to teach and how to landscape classroom interaction. Regardless of these benefits, the writer has witnessed the fact that lesson plans are viewed merely as a teaching document. Therefore, this paper will explore teachers’ beliefs and practices in designing lesson plans. It focuses primarily on how both teachers and students negotiate lesson plans in which the students are deemed to be the agents of instructional innovations. Additionally, the paper will talk about how such lesson plans are enacted. To investigate these issues, document analysis, in-depth interviews, participant classroom observation, and focus group discussion will be deployed as data collection methods in this explorative case study. The benefits of the paper are to show different roles of lesson plans and to discover different ways to design and enact such plans from a socio-interactional perspective.

Keywords: instructional innovation, learning and teaching system, lesson plan, pedagogical activities, teachers' beliefs and practices

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Authors: Ghada Mohammed, Mohamed Abdel Salam, Passent Tantawi

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The study aimed to investigate the impact of motives and barriers for Egyptian users to use Airbnb as a platform of peer-to-peer accommodation instead of hotels on overall attitude towards Airbnb. A sequential mixed-methods approach was adopted to this study and it proposed a comprehensive research model adapted from both literature and results of qualitative phase and then tested via an online questionnaire. The findings revealed that, motives, price, home benefits, privacy, and online reviews significantly explained overall attitude towards Airbnb, while the main barriers were respectively: perceived risk and distrust in which they can predict the overall attitude. While from the subjective norms, only social influence can predict behavioral intention to use Airbnb. The study may serve as a practical reference for practitioners as well as researchers when developing programs and strategies to manage Airbnb consumers' needs and decision process. Some of the main conclusions drawn from this study are that variety was one of the major things that users like about Airbnb and the most important motives are the functional ones like price rather than the experiential ones like authenticity.

Keywords: airbnb, barriers, disruptive innovation, motives, sharing economy

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Authors: Corneliu-Ioan Dimitriu, Gheorghe Frățilă

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Romania and Bulgaria have high rates of road deaths per million inhabitants. Directive (EU) 2019/1936, known as the RISM Directive, has been transposed into national law by each Member State. The research focuses on the amendments made to Romanian legislation through Government Ordinance no. 3/2022, which aims to improve road safety management on infrastructure. The aim of the research is two-fold: to sensitize the Romanian Government and decision-making entities to develop an integrated and competitive management system and to establish a safe and proactive mobility system that ensures efficient and safe roads. The research includes a critical analysis of European and Romanian legislation, as well as subsequent normative acts related to road infrastructure safety management. Public data from European Union and national authorities, as well as data from the Romanian Road Authority-ARR and Traffic Police database, are utilized. The research methodology involves comparative analysis, criterion analysis, SWOT analysis, and the use of GANTT and WBS diagrams. The Excel tool is employed to process the road accident databases of Romania and Bulgaria. Collaboration with Bulgarian specialists is established to identify common road infrastructure safety issues. The research concludes that the legislative changes have resulted in a relaxation of road safety management in Romania, leading to decreased control over certain management procedures. The amendments to primary and secondary legislation do not meet the current safety requirements for road infrastructure. The research highlights the need for legislative changes and strengthened administrative capacity to enhance road safety. Regional cooperation and the exchange of best practices are emphasized for effective road infrastructure safety management. The research contributes to the theoretical understanding of road infrastructure safety management by analyzing legislative changes and their impact on safety measures. It highlights the importance of an integrated and proactive approach in reducing road accidents and achieving the "zero deaths" objective set by the European Union. Data collection involves accessing public data from relevant authorities and using information from the Romanian Road Authority-ARR and Traffic Police database. Analysis procedures include critical analysis of legislation, comparative analysis of transpositions, criterion analysis, and the use of various diagrams and tools such as SWOT, GANTT, WBS, and Excel. The research addresses the effectiveness of legislative changes in road infrastructure safety management in Romania and the impact on control over management procedures. It also explores the need for strengthened administrative capacity and regional cooperation in addressing road safety issues. The research concludes that the legislative changes made in Romania have not strengthened road safety management and emphasize the need for immediate action, legislative amendments, and enhanced administrative capacity. Collaboration with Bulgarian specialists and the exchange of best practices are recommended for effective road infrastructure safety management. The research contributes to the theoretical understanding of road safety management and provides valuable insights for policymakers and decision-makers in Romania.

Keywords: management, road infrastructure safety, legislation, amendments, collaboration

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Authors: Irina Canco, Amela Malaj

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It is evident that there exists a relationship between supply chain management and business performance. Surveys have showed that in many cases the manager's beliefs and expectations on supply chain management do not match the reality of the business. In this context, the study of supply chain issues is of particular importance and interest considering specifically the current period. The economic problems of this period, are present in Albania as well. The complexity of the supply chain focuses on order fulfilment. Therefore, in this paper, attention will be paid to the impact of supply chain management on business performance. The objective of the paper is to find a relationship between the good supply chain management and business performance. This research is based on the results of surveys referring to the experience of successful businesses on issues related to sustainable supply chain management and its synchronization with the provision of products and services required by the final customers. This study clearly evidenced the impact of the speed of meeting customer requirements on AMAZONA performance. This was also confirmed mathematically through one of the decision criteria in conditions of uncertainty—Laplace criterion.

Keywords: supply chain management, AMAZONA, business performance, Laplace criteria

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Authors: Amal Abdou, Yasser ElSayed, Nora Selim

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Public urban spaces are an essential component in any urban settlement. They are quite important in enhancing the quality of urban life while offering social, health, environmental and economic benefits to a city and its residents. Place-making assessment of public urban spaces has been one of the major guiding principles for urban planning and policymaking, of which the definition and evaluation have become the crucial research topic. It is increasingly being essential to mitigate the undesirable impacts of urbanization in cities while improving public urban space’s resilience to environmental, social, and economic changes. Globally, several place-making assessment tools (PATs) have been developed to make such informed decision-making. They act as a catalyst to increase market demand for sustainable products and services by providing a mechanism for recognizing excellence. Assessing how placemaking can positively contribute to urban environments is critical to inform both the continued development of the place and the way placemaking is done as a practice. Therefore, this study aims to review different themes for assessing urban placemaking in public urban spaces.

Keywords: urban placemaking, public urban spaces, placemaking assessment, literature review

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Authors: Meera Rajeev Kumar

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An overall social, emotional, and cultural development in a child is what a parent expects. There is no point in comparing the generations of 70’s or 80’s with that of the children of today as the trends are changing drastically. Technology has enabled them to become smart as well as over smart in one way or the other. Children today are quite ignorant of today’s values or ethics and are imbibing different cultures around them and ultimately confused on what to follow. The researcher has gained experience in transmitting or imparting the traditional culture through performing arts. It is understood that the children undergo a transformation from what they knew to what the truth is, through learning and experience. Through performing arts, the child develops an emotional, quick learning, abundant creativity, and ultimately self-realisation on what is right and wrong. The child also gains good organising skills, good decision making skills, therefore summing up to a holistic development. The sample study is 50, and a random sampling technique is adopted to differentiate between a normal child and a child learning an art. The study is conducted in Tamil Nadu, in India.

Keywords: creativity, cultural, emotional, empower

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Authors: Simona Grasso, Gabrielle Smith, Sophie Bowers, Oluseyi Moses Ajayi, Mark Swainson

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Hybrid meat analogues are meat products whereby a proportion of meat has been partially replaced by more sustainable protein sources. These products could bridge the gap between meat and meat-free products, providing convenience, and allowing consumers to continue using meat products as they conventionally would, while lowering their overall meat intake. The study aimed to investigate the effect of introducing texturized soy protein (TSP) at different levels (15% and 30%) with and without nutritional yeast as flavour enhancer on the sensory and instrumental quality of beef meatballs, compared to a soy and yeast-free control. Proximate analysis, yield, colour, instrumental texture, and sensory quality were investigated. The addition of soy and yeast did not have significant effects on the overall protein content, but the total fat and moisture content went down with increasing soy substitution. Samples with 30% TSP had significantly higher yield than the other recipes. In terms of colour, a* redness values tended to go down and b* yellowness values tended to go up with increasing soy addition. The addition of increasing levels of soy and yeast modified the structure of meatballs resulting in a progressive decrease in hardness and chewiness compared to control. Sixty participants assessed the samples using Check-all-that-apply (CATA) questions and hedonic scales. The texture of all TSP-containing samples received significantly higher acceptability scores than control, while 15% TSP with yeast received significantly higher flavour and overall acceptability scores than control. Control samples were significantly more often associated than the other recipes to the term 'hard' and the least associated to 'soft' and 'crumbly and easy to cut'. All recipes were similarly associated to the terms 'weak meaty', 'strong meaty', 'characteristic' and 'unusual'. Correspondence analysis separated the meatballs in three distinct groups: 1) control; 2) 30%TSP with yeast; and 3) 15%TSP, 15%TSP with yeast and 30%TSP located together on the sensory map, showing similarity. Adding 15-30% TSP with or without yeast inclusion could be beneficial for the development of future meat hybrids with acceptable sensory quality. These results can provide encouragement for the use of the hybrid concept by the meat industry to promote the partial substitution of meat in flexitarians’ diets.

Keywords: CATA, hybrid meat products, texturised soy protein, yeast

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Authors: Phumelele Kubheka, Pius Owolawi, Gbolahan Aiyetoro

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Twitter is one of the most popular social media platforms where users can share their opinions on different subjects. As of 2010, The Twitter platform generates more than 12 Terabytes of data daily, ~ 4.3 petabytes in a single year. For this reason, Twitter is a great source for big mining data. Many industries such as Telecommunication companies can leverage the availability of Twitter data to better understand their markets and make an appropriate business decision. This study performs topic modeling on Twitter data using Latent Dirichlet Allocation (LDA). The obtained results are benchmarked with another topic modeling technique, Latent Semantic Indexing (LSI). The study aims to retrieve topics on a Twitter dataset containing user tweets on South African Telcos. Results from this study show that LSI is much faster than LDA. However, LDA yields better results with higher topic coherence by 8% for the best-performing model represented in Table 1. A higher topic coherence score indicates better performance of the model.

Keywords: big data, latent Dirichlet allocation, latent semantic indexing, telco, topic modeling, twitter

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Authors: Anna Guitart Atienza, Ana Fernández del Río, Madhav Nekkar, Jelena Ljubicic, África Periáñez, Eura Shin, Lauren Bellhouse

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The use of digital devices in healthcare or mobile health (mHealth) has increased in recent years due to the advances in digital technology, making it possible to nudge healthy behaviors through individual interventions. In addition, mHealth is becoming essential in poor-resource settings due to the widespread use of smartphones in areas where access to professional healthcare is limited. In this work, we evaluate mHealth interventions in low-income countries with a focus on causal inference. Counterfactuals estimation and other causal computations are key to determining intervention success and assisting in empirical decision-making. Our main purpose is to personalize treatment recommendations and triage patients at the individual level in order to maximize the entire intervention's impact on the desired outcome. For this study, collected data includes mHealth individual logs from front-line healthcare workers, electronic health records (EHR), and external variables data such as environmental, demographic, and geolocation information.

Keywords: causal inference, mHealth, intervention, personalization

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Authors: Marie-Claude Roy, David Locky, Ermias Azeria, Jim Schieck

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It is estimated that up to 70% of the wetlands in the Parkland and Grassland natural regions of Alberta have been lost due to various land-use activities. These losses include ecosystem function and services they once provided. Those wetlands remaining are often embedded in a matrix of human-modified habitats and despite efforts taken to protect them the effects of land-uses on wetland condition and function remain largely unknown. We used biophysical field data and remotely-sensed human footprint data collected at 322 open-water wetlands by the Alberta Biodiversity Monitoring Institute (ABMI) to evaluate the impact of surrounding land use on the physico-chemistry characteristics and plant functional traits of wetlands. Eight physio-chemistry parameters were assessed: wetland water depth, water temperature, pH, salinity, dissolved oxygen, total phosphorus, total nitrogen, and dissolved organic carbon. Three plant functional traits were evaluated: 1) origin (native and non-native), 2) life history (annual, biennial, and perennial), and 3) habitat requirements (obligate-wetland and obligate-upland). Intensity land-use was quantified within a 250-meter buffer around each wetland. Ninety-nine percent of wetlands in the Grassland and Parkland regions of Alberta have land-use activities in their surroundings, with most being agriculture-related. Total phosphorus in wetlands increased with the cover of surrounding agriculture, while salinity, total nitrogen, and dissolved organic carbon were positively associated with the degree of soft-linear (e.g. pipelines, trails) land-uses. The abundance of non-native and annual/biennial plants increased with the amount of agriculture, while urban-industrial land-use lowered abundance of natives, perennials, and obligate wetland plants. Our study suggests that land-use types surrounding wetlands affect the physicochemical and biological conditions of wetlands. This research suggests that reducing human disturbances through reclamation of wetland buffers may enhance the condition and function of wetlands in agricultural landscapes.

Keywords: wetlands, biophysical assessment, land use, grassland and parkland natural regions

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Authors: David Obafemi Adebayo

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An occupational challenge has been identified as one of the factors that could cripple set goals and life ambitions of an Internally Displaced Person (IDP). The main thrust of this study is therefore, explore the use of life support/adjustment strategy with a view to repositioning these internally displaced persons in Nigeria in revamping their goals and achieving their life-long ambitions. The study intends to investigate whether there exist, on the basis of gender, religion, years of working experience and educational qualification any significant difference in the occupational challenges and adjustment strategies of IDPs. The study being descriptive of survey type adopted a multi-stage sampling technique to select the minimum of 400 internally displaced persons from IDP camps in Yimitu Village, Waru District in the Federal Capital Territory (FCT), Abuja. The research instrument used for the study was a researcher-designed questionnaire entitled “Questionnaire on Occupational Challenges and Adjustment Strategy of Internally Displaced Persons (QOCASIDPs)”. Eight null hypotheses were tested at 0.05 alpha levels of significance. Frequency counts and percentages, means and rank order, t-test, Analysis of Variance (ANOVA) and Duncan Multiple Range Test (DMRT) (where applicable) were employed to analyze the data. The Study determined whether occupational challenges of internally displaced persons included loss of employment, vocational discrimination, marginalization by employers of labour, isolation due to joblessness, lack of occupational freedom, which were found to be true. The results were discussed in line with the findings. The study established the place of notable adjustment strategies adopted by internally displaced person like engaging in petty trading, sourcing soft loans from NGOs, setting up small-scale businesses in groups, acquiring new skills, engaging in further education, among others. The study established that there was no significant difference in the occupational challenges of IDPs on the basis of years of working experience and highest educational qualifications, though there was significant difference on the basis of gender as well as religion. Based on the findings of the study, recommendations were made.

Keywords: internally displaced persons, occupational challenges, adjustment strategies, Abuja-Nigeria

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Authors: Nizar Souiden, Riadh Ladhari

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Like tobacco and alcohol, recreational marijuana falls under the umbrella of ‘sin’ industries’. Notwithstanding this general negative image surrounding marijuana use, some scholars argue that most of the widely believed claims made about recreational marijuana users are irrelevant and that marijuana use can even improve individuals’ decision-making. This study intends to shed light on this particular product category (i.e., marijuana) often overlooked or portrayed as taboo from a business view. More specifically, it investigates whether legalizing the consumption of recreational marijuana would be perceived as ethical and whether companies/organizations involved in the commercialization of this particular product would be held socially responsible. Based on primary data collected in Canada, this study aims to answer the following questions: 1) What moral thoughts do individuals hold with regard to the consumption of recreational marijuana? 2) How do these moral thoughts determine consumers’ attitude toward the consumption of recreational marijuana? Regardless of the legalization of recreational marijuana in some countries such as Canada, probing people’s opinions, and investigating their attitudes toward the consumption of recreational marijuana is of important interest to different stakeholders such as consumers, public organizations, private businesses, and trade associations.

Keywords: recreational marijuana, moral thoughts, ethics, attitude

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Authors: Melissa C. Monney

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Psychological testing has been of interest to researchers for many years as useful tools in assessing and diagnosing various disorders as well as to assist in understanding human behavior. However, for over 20 years now, researchers and laypersons alike have been interested in using them for other purposes, such as determining factors in employee selection, promotion, and even termination. In recent years, psychological assessments have been useful in facilitating workplace decision processing, regarding employee circulation within organizations. This literature review explores four of the most commonly used psychological tests in workplace environments, namely cognitive ability, emotional intelligence, integrity, and personality tests, as organizations have used these tests to assess different factors of human behavior as predictive measures of future employee behaviors. The findings suggest that while there is much controversy and debate regarding the validity and reliability of these tests in workplace settings as they were not originally designed for these purposes, the use of such assessments in the workplace has been useful in decreasing costs and employee turnover as well as increase job satisfaction by ensuring the right employees are selected for their roles.

Keywords: cognitive ability, personality testing, predictive validity, workplace behavior

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Authors: Hyun-Woo Cho

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Continuous monitoring of industrial plants is one of necessary tasks when it comes to ensuring high-quality final products. In terms of monitoring and diagnosis, it is quite critical and important to detect some incipient abnormal events of manufacturing processes in order to improve safety and reliability of operations involved and to reduce related losses. In this work a new multivariate statistical online diagnostic method is presented using a case study. For building some reference models an empirical discriminant model is constructed based on various past operation runs. When a fault is detected on-line, an on-line diagnostic module is initiated. Finally, the status of the current operating conditions is compared with the reference model to make a diagnostic decision. The performance of the presented framework is evaluated using a dataset from complex industrial processes. It has been shown that the proposed diagnostic method outperforms other techniques especially in terms of incipient detection of any faults occurred.

Keywords: data mining, empirical model, on-line diagnostics, process fault, process monitoring

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Authors: Reyhaneh Saeedi, Nima Ghasemloo

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Iran is a capable zone for earthquake that follows loss of lives and financial damages. To have sheltering for earthquake victims is one of the basic requirements although it is hard to select suitable places for temporary resettling after an earthquake happens. Before these kinds of disasters happen, the best places for resettling the victims must be designated. This matter is an important issue in disaster management and planning. Geospatial Information System (GIS) has a determining role in disaster management; it can determine the best places for temporary resettling after such a disaster. In this paper the best criteria have been determined associated with their weights and buffers by use of research and questionnaire for locating the best places. In this paper, AHP method is used as decision model and to locate the best places for temporary resettling is done based on the selected criteria. Also in this research are made the buffer layers of criteria and change them to the raster layers. Later on, the raster layers are multiplied on desired weights then, the results are added together. Finally there are suitable places for resettling of victims by desired criteria by different colors with their optimum rate in QGIS software.

Keywords: disaster management, temporary resettlement, earthquake, criteria

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Authors: Y. Tahat, T. Dunne, S. Fifield, D. Power

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Information about a firm’s usage of Financial Instruments (FIs) plays a very important role in determining its financial position and performance. Yet accounting standard-setters have encountered problems when deciding on the FI-related disclosures which firms must make. The primary objective of this paper is to review the extant literature on FI disclosure. This objective is achieved by surveying the literature on: the corporate usage of FIs; the different accounting standards adopted concerning FIs; and empirical studies on FI disclosure. This review concludes that the current research on FI disclosure has generated a number of useful insights. In particular, the paper reports that: FIs are a very important risk management mechanism in ensuring that companies have the cash available to make value-enhancing investments, however, without a clear set of risk management objectives, using such instruments can be dangerous; accounting standards concerning FIs have resulted in enhanced transparency about the usage of these instruments; and FI-related information is a key input into investors’ decision-making processes. Finally, the paper provides a number of suggestions for future research in the area.

Keywords: financial instruments, financial reporting, accounting standards, value relevance, corporate disclosure

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Authors: Medjadj Tarek, Ghribi Hayet

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This study aims to develop a flood sensitivity assessment tool using machine learning (ML) techniques and geographic information system (GIS). The importance of this study is integrating the geographic information systems (GIS) and machine learning (ML) techniques for mapping flood risks, which help decision-makers to identify the most vulnerable areas and take the necessary precautions to face this type of natural disaster. To reach this goal, we will study the case of the city of M'sila, which is among the areas most vulnerable to floods. This study drew a map of flood-prone areas based on the methodology where we have made a comparison between 3 machine learning algorithms: the xGboost model, the Random Forest algorithm and the K Nearest Neighbour algorithm. Each of them gave an accuracy respectively of 97.92 - 95 - 93.75. In the process of mapping flood-prone areas, the first model was relied upon, which gave the greatest accuracy (xGboost).

Keywords: Geographic information systems (GIS), machine learning (ML), emergency mapping, flood disaster management

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Authors: Vine Petzer, Mirna Nel

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An explanatory mixed method design was used to investigate accounting classroom conditions in the Further Education and Training (FET) Phase in South Africa. A descriptive survey research study with a heterogeneous group of learners and teachers was conducted in the first phase. In the qualitative phase, semi-structured individual interviews with learners and teachers, as well as observations in the accounting classroom, were employed to gain more in depth understanding of the learning conditions in the accounting classroom. The findings of the empirical research informed the development of a model for teachers in accounting, supporting them to use more effective teaching methods and create positive learning conditions for all learners to experience successful learning. A model towards creating positive Accounting classroom conditions that support successful learning was developed and recommended for education policy and decision-makers for use as a classroom intervention capacity building tool. The model identifies and delineates classroom practices that exert significant effect on learner attainment of quality education.

Keywords: accounting classroom conditions, positive education, successful learning, teaching accounting

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Authors: Rahbel Rahman, Rogério Meireles Pinto, Margareth Santos Zanchetta

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Background: Existing shortcomings of current health-service delivery include poor teamwork, competencies that do not address consumer needs, and episodic rather than continuous care. Brazil’s Sistema Único de Saúde (Unified Health System, UHS) is acknowledged worldwide as a model for delivering community-based care through Estratégia Saúde da Família (FHS; Family Health Strategy) interdisciplinary teams, comprised of Community Health Agents (in Portuguese, Agentes Comunitário de Saude, ACS), nurses, and physicians. FHS teams are mandated to collectively offer clinical care, disease prevention services, vector control, health surveillance and social services. Our study compares medical providers (nurses and physicians) and community-based providers (ACS) on their perceptions of work environment, professional skills, cognitive capacities and job context. Global health administrators and policy makers can leverage on similarities and differences across care providers to develop interprofessional training for community-based primary care. Methods: Cross-sectional data were collected from 168 ACS, 62 nurses and 32 physicians in Brazil. We compared providers’ demographic characteristics (age, race, and gender) and job context variables (caseload, work experience, work proximity to community, the length of commute, and familiarity with the community). Providers perceptions were compared to their work environment (work conditions and work resources), professional skills (consumer-input, interdisciplinary collaboration, efficacy of FHS teams, work-methods and decision-making autonomy), and cognitive capacities (knowledge and skills, skill variety, confidence and perseverance). Descriptive and bi-variate analysis, such as Pearson Chi-square and Analysis of Variance (ANOVA) F-tests, were performed to draw comparisons across providers. Results: Majority of participants were ACS (64%); 24% nurses; and 12% physicians. Majority of nurses and ACS identified as mixed races (ACS, n=85; nurses, n=27); most physicians identified as males (n=16; 52%), and white (n=18; 58%). Physicians were less likely to incorporate consumer-input and demonstrated greater decision-making autonomy than nurses and ACS. ACS reported the highest levels of knowledge and skills but the least confidence compared to nurses and physicians. ACS, nurses, and physicians were efficacious that FHS teams improved the quality of health in their catchment areas, though nurses tend to disagree that interdisciplinary collaboration facilitated their work. Conclusion: To our knowledge, there has been no study comparing key demographic and cognitive variables across ACS, nurses and physicians in the context of their work environment and professional training. We suggest that global health systems can leverage upon the diverse perspectives of providers to implement a community-based primary care model grounded in interprofessional training. Our study underscores the need for in-service trainings to instill reflective skills of providers, improve communication skills of medical providers and curative skills of ACS. Greater autonomy needs to be extended to community based providers to offer care integral to addressing consumer and community needs.

Keywords: global health systems, interdisciplinary health teams, community health agents, community-based care

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Authors: Carlos M. Parra, Matthew Sutherland, Ranjita Poudel

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Reduced mental-bandwidth related to low socioeconomic status (low-SES) might lead to impulsivity and risk-taking behavior, which poses as a major hurdle towards asset building (savings) behavior. Understanding the relationship between risk-related personality metrics as well as laboratory risk behavior and real-life savings behavior can help facilitate the development of effective asset building programs, which are vital for mitigating financial vulnerability and income inequality. As such, this study explored the relationship between personality metrics, laboratory behavior in a risky decision-making task and real-life asset building (savings) behaviors among individuals with low-SES from Miami, Florida (FL). Study participants (12 male, 15 female) included racially and ethnically diverse adults (mean age 41.22 ± 12.65 years), with incomplete higher education (18% had High School Diploma, 30% Associates, and 52% Some College), and low annual income (mean $13,872 ± $8020.43). Participants completed eight self-report surveys and played a widely used risky decision-making paradigm called the Balloon Analogue Risk Task (BART). Specifically, participants played three runs of BART (20 trials in each run; total 60 trials). In addition, asset building behavior data was collected for 24 participants who opened and used savings accounts and completed a 6-month savings program that involved monthly matches, and a final reward for completing the savings program without any interim withdrawals. Each participant’s total savings at the end of this program was the main asset building indicator considered. In addition, a new effective use of average pump bet (EUAPB) indicator was developed to characterize each participant’s ability to place winning bets. This indicator takes the ratio of each participant’s total BART earnings to average pump bet (APB) in all 60 trials. Our findings indicated that EUAPB explained more than a third of the variation in total savings among participants. Moreover, participants who managed to obtain BART earnings of at least 30 cents out of their APB, also tended to exhibit better asset building (savings) behavior. In particular, using this criterion to separate participants into high and low EUAPB groups, the nine participants with high EUAPB (mean BART earnings of 35.64 cents per APB) ended up with higher mean total savings ($255.11), while the 15 participants with low EUAPB (mean BART earnings of 22.50 cents per APB) obtained lower mean total savings ($40.01). All mean differences are statistically significant (2-tailed p  .0001) indicating that the relation between higher EUAPB and higher total savings is robust. Overall, these findings can help refine asset building interventions implemented by policy makers and practitioners interested in reducing financial vulnerability among low-SES population. Specifically, by helping identify individuals who are likely to readily take advantage of savings opportunities (such as matched savings programs) and avoiding the stipulation of unnecessary and expensive financial coaching programs to these individuals. This study was funded by J.P. Morgan Chase (JPMC) and carried out by scientists from Florida International University (FIU) in partnership with Catalyst Miami.

Keywords: balloon analogue risk task (BART), matched savings programs, asset building capability, low-SES participants

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Authors: Snezhana G. Gocheva-Ilieva, Maya P. Stoimenova

Abstract:

Ambient air pollution with fine particulate matter (PM10) is a systematic permanent problem in many countries around the world. The accumulation of a large number of measurements of both the PM10 concentrations and the accompanying atmospheric factors allow for their statistical modeling to detect dependencies and forecast future pollution. This study applies the classification and regression trees (CART) method for building and analyzing PM10 models. In the empirical study, average daily air data for the city of Pleven, Bulgaria for a period of 5 years are used. Predictors in the models are seven meteorological variables, time variables, as well as lagged PM10 variables and some lagged meteorological variables, delayed by 1 or 2 days with respect to the initial time series, respectively. The degree of influence of the predictors in the models is determined. The selected best CART models are used to forecast future PM10 concentrations for two days ahead after the last date in the modeling procedure and show very accurate results.

Keywords: cross-validation, decision tree, lagged variables, short-term forecasting

Procedia PDF Downloads 194

Authors: Kuan-Chou Chen

Abstract:

This paper will demonstrate a simulation model of an information security system by using the systems dynamic approach. The relationships in the system model are designed to be simple and functional and do not necessarily represent any particular information security environments. The purpose of the paper aims to develop a generic system dynamic information security system model with implications on information security research. The interrelated and interdependent relationships of five primary sectors in the system dynamic model will be presented in this paper. The integrated information security systems model will include (1) information security characteristics, (2) users, (3) technology, (4) business functions, and (5) policy and management. Environments, attacks, government and social culture will be defined as the external sector. The interactions within each of these sectors will be depicted by system loop map as well. The proposed system dynamic model will not only provide a conceptual framework for information security analysts and designers but also allow information security managers to remove the incongruity between the management of risk incidents and the management of knowledge and further support information security managers and decision makers the foundation for managerial actions and policy decisions.

Keywords: system thinking, information security systems, security management, simulation

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Authors: Haodong Huang, Zida Zhao, Shilong Sun, Chiyao Li, Wenfu Xu

Abstract:

The control methods for legged robots based on deep reinforcement learning have seen widespread application; however, the inherent black-box nature of neural networks presents challenges in understanding the decision-making motives of the robots. To address this issue, we propose a fully interpretable deep reinforcement learning training method to elucidate the underlying principles of legged robot motion. We incorporate the dynamics of legged robots into the policy, where observations serve as inputs and actions as outputs of the dynamics model. By embedding the dynamics equations within the multi-layer perceptron (MLP) computation process and making the parameters trainable, we enhance interpretability. Additionally, Bayesian optimization is introduced to train these parameters. We validate the proposed fully interpretable motion control algorithm on a legged robot, opening new research avenues for motion control and learning algorithms for legged robots within the deep learning framework.

Keywords: deep reinforcement learning, interpretation, motion control, legged robots

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Authors: J. S. M. Yang, G. E. T. Chua

Abstract:

Diploma in Optometry (OPT) course is a three-year program offered by Ngee Ann Polytechnic (NP) to train students to provide primary eye care. Students are equipped with foundational conceptual knowledge and practical skills in the first three semesters before clinical modules in fourth to six semesters. In the clinical modules, students typically have difficulties in integrating the acquired knowledge and skills from the past semesters to perform general eye examinations on public patients at NP Optometry Centre (NPOC). To help the students overcome the challenge, a web-based game Virtual Optometrist (VO) was developed to help students apply their skills and knowledge through scenario-based learning. It consisted of two interfaces, Optical Practice Counter (OPC) and Optometric Consultation Room (OCR), to provide two simulated settings for authentic learning experiences. In OPC, students would recommend and provide appropriate frame and lens selection based on virtual patient’s case history. In OCR, students would diagnose and manage virtual patients with common ocular conditions. Simulated scenarios provided real-world clinical situations that required contextual application of integrated knowledge from relevant modules. The stages in OPC and OCR are of increasing complexity to align to expected students’ clinical competency as they progress to more senior semesters. This prevented gameplay fatigue as VO was used over the semesters to achieve different learning outcomes. Numerous feedback opportunities were provided to students based on their decisions to allow individualized learning to take place. The game-based learning element in VO was achieved through the scoreboard and leader board to enhance students' motivation to perform. Scores were based on the speed and accuracy of students’ responses to the questions posed in the simulated scenarios, preparing the students to perform accurately and effectively under time pressure in a realistic optometric environment. Learning analytics was generated in VO’s backend office based on students’ responses, offering real-time data on distinctive and observable learners’ behavior to monitor students’ engagement and learning progress. The backend office allowed versatility to add, edit, and delete scenarios for different intended learning outcomes. Likert Scale was used to measure students’ learning experience with VO for OPT Year 2 and 3 students. The survey results highlighted the learning benefits of implementing VO in the different modules, such as enhancing recall and reinforcement of clinical knowledge for contextual application to develop higher-order thinking skills, increasing efficiency in clinical decision-making, facilitating learning through immediate feedback and second attempts, providing exposure to common and significant ocular conditions, and training effective communication skills. The results showed that VO has been useful in reinforcing optometry students’ learning and supporting the development of higher-order thinking, increasing efficiency in clinical decision-making, and allowing students to learn from their mistakes with immediate feedback and second attempts. VO also exposed the students to diverse ocular conditions through simulated real-world clinical scenarios, which may otherwise not be encountered in NPOC, and promoted effective communication skills.

Keywords: authentic learning, game-based learning, scenario-based learning, simulated clinical scenarios

Procedia PDF Downloads 117