Search results for: judicial decision making

Authors: Andrey V. Timofeev, Dmitry V. Egorov

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This paper introduces an original method of parametric optimization of the structure for multimodal decision-level fusion scheme which combines the results of the partial solution of the classification task obtained from assembly of the mono-modal classifiers. As a result, a multimodal fusion classifier which has the minimum value of the total error rate has been obtained.

Keywords: classification accuracy, fusion solution, total error rate, multimodal fusion classifier

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Authors: Tamir Michal

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The subject of Bedouin dispersion has accompanied the State of Israel from the day of its establishment. From a legal point of view, this subject has offered a launchpad for creative judicial decisions. Thus, for example, the first court decision in Israel to recognize affirmative action (Avitan), dealt with a petition submitted by a Jew appealing the refusal of the State to recognize the Petitioner’s entitlement to the long-term lease of a plot designated for Bedouins. The Supreme Court dismissed the petition, holding that there existed a public interest in assisting Bedouin to establish permanent urban settlements, an interest which justifies giving them preference by selling them plots at subsidized prices. In another case (The Forum for Coexistence in the Negev) the Supreme Court extended equitable relief for the purpose of constructing a bridge, even though the construction infringed the Law, in order to allow the children of dispersed Bedouin to reach school. Against this background, the recent verdict, delivered during the Protective Edge military campaign, which dismissed a petition aimed at forcing the State to spread out Protective Structures in Bedouin villages in the Negev against the risk of being hit from missiles launched from Gaza (Abu Afash) is disappointing. Even if, in arguendo, no selective discrimination was involved in the State’s decision not to provide such protection, the decision, and its affirmation by the Court, is problematic when examined through the prism of the Theory of Recognition. The article analyses the issue by tools of theory of Recognition, according to which people develop their identities through mutual relations of recognition in different fields. In the social context, the path to recognition is cognitive respect, which is provided by means of legal rights. By seeing other participants in Society as bearers of rights and obligations, the individual develops an understanding of his legal condition as reflected in the attitude to others. Consequently, even if the Court’s decision may be justified on strict legal grounds, the fact that Jewish settlements were protected during the military operation, whereas Bedouin villages were not, is a setback in the struggle to make the Bedouin citizens with equal rights in Israeli society. As the Court held, ‘Beyond their protective function, the Migunit [Protective Structures] may make a moral and psychological contribution that should not be undervalued’. This contribution is one that the Bedouin did not receive in the Abu Afash verdict. The basic thesis is that the Court’s verdict analyzed above clearly demonstrates that the reliance on classical liberal instruments (e.g., equality) cannot secure full appreciation of all aspects of Bedouin life, and hence it can in fact prejudice them. Therefore, elements of the recognition theory should be added, in order to find the channel for cognitive dignity, thereby advancing the Bedouins’ ability to perceive themselves as equal human beings in the Israeli society.

Keywords: bedouin dispersion, cognitive respect, recognition theory, sustainable development

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Authors: Som Pal Baliyan

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The purpose of this quantitative study was to analyze farm management skills in broiler poultryproducers in Botswana. The study adopted a descriptive and correlation research design. The population of the study was the poultry farm operators who had been in broiler poultry farming at least for two years. Based on the information from literature, a questionnaire was constructed for data collection on seven areas of farm management skills namely; planning skills, accounting and financial management skills, production management skills, product procurement and marketing skills, decision making skills, risk management skills, and specific technical skills. The validity and reliability of the questionnaire were accomplished by a panel of experts and by calculating the Cronbach’s alpha coefficient, respectively. Data were collected through a survey of 60 randomly sampled poultry farm operators in Botswana. Data were analyzed through descriptive statistical tools whereby the level of farm management skills were determined by calculating means and standard deviations of the management skills among the broiler producers. The level of farm management skills in broilers producers was discussed. All the seven farm management skills were ranked based on their calculated means. The specific technical skills and risk management skills were the highest and the lowest ranked farm management skills, respectively.Findings revealed that the broiler producers had skills above the average level only in specific technical skills whereas the skill levels in the remaining six farm management skills under study were found below the average level. This prevailing low level of farm management skills can be justified asthe cause of failure or poor performance of the broiler poultry farms in Botswana. Therefore, in order to improve the efficiency and productivityin broiler production in the country, it was recommended that the broiler poultry producers should be adequately trained in areas of planning skills, financial management skills, production management skills, product procurement and marketing skills, decision making skills and risk management skills.

Keywords: poultry production, broiler production, management skills, levels of skills

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Authors: Hind Bouami

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Handling life-critical systems complexity requires to be equipped with appropriate technology and the right human agents’ functions such as knowledge, experience, and competence in problem’s prevention and solving. Human agents are involved in the management and control of human-machine system’s performance. Documenting human agent’s situation awareness is crucial to support human-machine designers’ decision-making. Knowledge about risks, critical parameters and factors that can impact and threaten automation system’s performance should be collected using preventive and retrospective approaches. This paper aims to document operators’ situation awareness through the analysis of automated organizations’ feedback. The analysis of automated hospital pharmacies feedbacks helps to identify and control critical parameters influencing human machine interaction in order to enhance system’s performance and security. Our human machine system evaluation approach has been deployed in Macon hospital center’s pharmacy which is equipped with automated drug dispensing systems since 2015. Automation’s specifications are related to technical aspects, human-machine interaction, and human aspects. The evaluation of drug delivery automation performance in Macon hospital center has shown that the performance of the automated activity depends on the performance of the automated solution chosen, and also on the control of systemic factors. In fact, 80.95% of automation specification related to the chosen Sinteco’s automated solution is met. The performance of the chosen automated solution is involved in 28.38% of automation specifications performance in Macon hospital center. The remaining systemic parameters involved in automation specifications performance need to be controlled.

Keywords: life-critical systems, situation awareness, human-machine interaction, decision-making

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Authors: Luay Jum'a

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Many challenges are facing third-party logistics (3PL) providers in the domestic and global markets which create a volatile decision making environment. All these challenges such as managing changes in consumer behaviour, demanding expectations from customers and time compressions have turned into complex problems for 3PL providers. Since the movement towards increased outsourcing outpaces movement towards insourcing, the need to achieve a competitive advantage over competitors in 3PL market increases. This trend continues to grow over the years and as a result, areas of strengths and improvements are highlighted through the analysis of the LSQ factors that lead to B2B customers’ satisfaction which become a priority for 3PL companies. Consequently, 3PL companies are increasingly focusing on the most important issues from the perspective of their customers and relying more on this value of information in making their managerial decisions. Therefore, this study is concerned with providing guidance for improving logistics service quality (LSQ) levels in the context of 3PL industry in Jordan. The study focused on the most important factors in LSQ and used a managerial tool that guides 3PL companies in making LSQ improvements based on a quadrant analysis of two main dimensions: LSQ declared importance and LSQ inferred importance. Although, a considerable amount of research has been conducted to investigate the relationship between logistics service quality (LSQ) and customer satisfaction, there remains a lack of developing managerial tools to aid in the process of LSQ improvement decision-making. Moreover, the main advantage for the companies to use 3PL service providers as a trend is due to the realised percentage of cost reduction on the total cost of logistics operations and the incremental improvement in customer service. In this regard, having a managerial tool that help 3PL service providers in managing the LSQ factors portfolio effectively and efficiently would be a great investment for service providers. One way of suggesting LSQ improvement actions for 3PL service providers is via the adoption of analysis tools that perform attribute categorisation such as Importance–Performance matrix. In mind of the above, it can be stated that the use of quadrant analysis will provide a valuable opportunity for 3PL service providers to identify improvement opportunities as customer service attributes or factors importance are identified in two different techniques that complete each other. Moreover, the data were collected through conducting a survey and 293 questionnaires were returned from business-to-business (B2B) customers of 3PL companies in Jordan. The results showed that the LSQ factors vary in their importance and 3PL companies should focus on some LSQ factors more than other factors. Moreover, ordering procedures, timeliness/responsiveness LSQ factors considered being crucial in 3PL businesses and therefore they need to have more focus and development by 3PL service providers in the Jordanian market.

Keywords: logistics service quality, managerial decisions, quadrant analysis, third party logistics service provider

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Authors: Pilly Joseph Kagosi

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The study aims at assessing challenges observed during the implementation of participatory irrigation management (PIM) approach for food security in semi-arid areas of Tanzania. Data were collected through questionnaire, PRA tools, key informants discussion, Focus Group Discussion (FGD), participant observation, and literature review. Data collected from the questionnaire was analysed using SPSS while PRA data was analysed with the help of local communities during PRA exercise. Data from other methods were analysed using content analysis. The study revealed that PIM approach has a contribution in improved food security at household level due to the involvement of communities in water management activities and decision making which enhanced the availability of water for irrigation and increased crop production. However, there were challenges observed during the implementation of the approach including; minimum participation of beneficiaries in decision-making during planning and designing stages, meaning inadequate devolution of power among scheme owners. Inadequate and lack of transparency on income expenditure in Water Utilization Associations’ (WUAs), water conflict among WUAs members, conflict between farmers and livestock keepers and conflict between WUAs leaders and village government regarding training opportunities and status; WUAs rules and regulation are not legally recognized by the National court and few farmers involved in planting trees around water sources. However, it was realized that some of the mentioned challenges were rectified by farmers themselves facilitated by government officials. The study recommends that the identified challenges need to be rectified for farmers to realize impotence of PIM approach as it was realized by other Asian countries.

Keywords: challenges, participatory approach, irrigation management, food security, semi arid areas

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Authors: Satish Kumar, Nisha Goyal

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In the stock market, individual investors exhibit different kinds of behaviour. Traditional finance is built on the notion of 'homo economics', which states that humans always make perfectly rational choices to maximize their wealth and minimize risk. That is, traditional finance has concern for how investors should behave rather than how actual investors are behaving. Behavioural finance provides the explanation for this phenomenon. Although finance has been studied for thousands of years, behavioural finance is an emerging field that combines the behavioural or psychological aspects with conventional economic and financial theories to provide explanations on how emotions and cognitive factors influence investors’ behaviours. These emotions and cognitive factors are known as behavioural biases. Because of these biases, investors make irrational investment decisions. Besides, the emotional and cognitive factors, the social influence of media as well as friends, relatives and colleagues also affect investment decisions. Psychological factors influence individual investors’ investment decision making, but few studies have used qualitative methods to understand these factors. The aim of this study is to explore the behavioural factors or biases that affect individuals’ investment decision making. For the purpose of this exploratory study, an in-depth interview method was used because it provides much more exhaustive information and a relaxed atmosphere in which people feel more comfortable to provide information. Twenty investment advisors having a minimum 5 years’ experience in securities firms were interviewed. In this study, thematic content analysis was used to analyse interview transcripts. Thematic content analysis process involves analysis of transcripts, coding and identification of themes from data. Based on the analysis we categorized the statements of advisors into various themes. Past market returns and volatility; preference for safe returns; tendency to believe they are better than others; tendency to divide their money into different accounts/assets; tendency to hold on to loss-making assets; preference to invest in familiar securities; tendency to believe that past events were predictable; tendency to rely on the reference point; tendency to rely on other sources of information; tendency to have regret for making past decisions; tendency to have more sensitivity towards losses than gains; tendency to rely on own skills; tendency to buy rising stocks with the expectation that this rise will continue etc. are some of the major concerns showed by experts about investors. The findings of the study revealed 13 biases such as overconfidence bias, disposition effect, familiarity bias, framing effect, anchoring bias, availability bias, self-attribution bias, representativeness, mental accounting, hindsight bias, regret aversion, loss aversion and herding bias/media biases present in Indian investors. These biases have a negative connotation because they produce a distortion in the calculation of an outcome. These biases are classified under three categories such as cognitive errors, emotional biases and social interaction. The findings of this study may assist both financial service providers and researchers to understand the various psychological biases of individual investors in investment decision making. Additionally, individual investors will also be aware of the behavioural biases that will aid them to make sensible and efficient investment decisions.

Keywords: financial advisors, individual investors, investment decisions, psychological biases, qualitative thematic content analysis

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Authors: Rana Tajammal Rashid

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Federalism is a political system in which government power and responsibility are divided between a federal legislature and units of the state or provincial legislatures. This system provides the structure for the states having large territory and through that can manage the state affairs and administration easily. Many of the largest countries in the world are federations, like; The United States, Canada, India, Pakistan South Africa, Argentina, and Australia. Every large democratic nation has a federal system of government. This study will explore the feature and good governance of two developed countries Canada and Australia. This study will be helpful to the developing countries like Pakistan, India which have a federal form of structure to run the affairs of the state. In the federal system of Pakistan there are lot of issues and conflicts with the provinces with a comparative study of these two developed countries, i.e., Australia and Canada, our policy and decision maker political actors will understand in which way a state will successfully manage the issues related to federalism. This study will also provide the help to the students of comparative politics that how to analysis the different political system of the developed countries of the world.

Keywords: federalism, features of federalism, types of federalism, history of federalism, Australian federalism, Canadian federalism, federalism developments, executives, federal and provincial autonomy legislative, judicial

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Authors: Henrique Rangel, Alexandre Fadel, Igor De Lazari, Bianca Neri, Carlos Bolonha

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This paper promotes a comparative analysis of American and Brazilian models of federalism assuming their levels of political centralization as main criterion. The central problem faced herein is the Brazilian approach of Unitarian regime. Although the hegemony of federative form after 1989, Brazil had a historical frame of political centralization that remains under the 1988 constitutional regime. Meanwhile, United States framed a federalism in which States absorb significant authorities. The hypothesis holds that the amount of alternative criteria of federalization – which can generate political centralization –, and the way they are upheld on judicial review, are crucial to understand the levels of political centralization achieved in each model. To test this hypothesis, the research is conducted by a methodology temporally delimited to 1994-2014 period. Three paradigmatic precedents of U.S. Supreme Court were selected: United States vs. Morrison (2000), on gender-motivated violence, Gonzales vs. Raich (2005), on medical use of marijuana, and United States vs. Lopez (1995), on firearm possession on scholar zones. These most relevant cases over federalism in the recent activity of Supreme Court indicates a determinant parameter of deliberation: the commerce clause. After observe the criterion used to permit or prohibit the political centralization in America, the Brazilian normative context is presented. In this sense, it is possible to identify the eventual legal treatment these controversies could receive in this Country. The decision-making reveals some deliberative parameters, which characterizes each federative model. At the end of research, the precedents of Rehnquist Court promote a broad revival of federalism debate, establishing the commerce clause as a secure criterion to uphold or not the necessity of centralization – even with decisions considered conservative. Otherwise, the Brazilian federalism solves them controversies upon in a formalist fashion, within numerous and comprehensive – sometimes casuistic too – normative devices, oriented to make an intense centralization. The aim of this work is indicate how jurisdictional federalism found in United States can preserve a consistent model with States robustly autonomous, while Brazil gives preference to normative mechanisms designed to starts from centralization.

Keywords: constitutional design, federalism, U.S. Supreme Court, legislative authority

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Authors: Asma Ben Yaghlane, Mohamed Naceur Azaiez

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In this paper, we briefly introduce the concept of Poisson attacks in the case of defense/attack strategies where attacks are assumed to be continuous. We suggest a game model in which the attacker will combine both criteria of a sufficient confidence level of a successful attack and a reasonably small size of the estimation error in order to launch an attack. Here, estimation error arises from assessing the system failure upon attack using aggregate data at the system level. The corresponding error is referred to as aggregation error. On the other hand, the defender will attempt to deter attack by making one or both criteria inapplicable. The defender will build his/her strategy by both strengthening the targeted system and increasing the size of error. We will formulate the defender problem based on appropriate optimization models. The attacker will opt for a Bayesian updating in assessing the impact on the improvement made by the defender. Then, the attacker will evaluate the feasibility of the attack before making the decision of whether or not to launch it. We will provide illustrations to better explain the process.

Keywords: attacker, defender, game theory, information

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Authors: Mohamed Bualhamam

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Due to the complex nature of tourism resources of the Northern part of the United Arab Emirates (UAE), the potential of Geographical Information Systems (GIS) and Remote Sensing (RS) in resolving these issues was used. The study was an attempt to use existing GIS data layers to identify sensitive natural environment and archaeological heritage resources that may be threatened by increased urban growth and give some specific recommendations to protect the area. By identifying sensitive natural environment and archaeological heritage resources, public agencies and citizens are in a better position to successfully protect important natural lands and direct growth away from environmentally sensitive areas. The paper concludes that applications of GIS and RS in study of urban growth impact in tourism resources are a strong and effective tool that can aid in tourism planning and decision-making. The study area is one of the fastest growing regions in the country. The increase in population along the region, as well as rapid growth of towns, has increased the threat to natural resources and archeological sites. Satellite remote sensing data have been proven useful in assessing the natural resources and in monitoring the changes. The study used GIS and RS to identify sensitive natural environment and archaeological heritage resources that may be threatened by increased urban growth. The result of GIS analyses shows that the Northern part of the UAE has variety for tourism resources, which can use for future tourism development. Rapid urban development in the form of small towns and different economic activities are showing in different places in the study area. The urban development extended out of old towns and have negative affected of sensitive tourism resources in some areas. Tourism resources for the Northern part of the UAE is a highly complex resources, and thus requires tools that aid in effective decision making to come to terms with the competing economic, social, and environmental demands of sustainable development. The UAE government should prepare a tourism databases and a GIS system, so that planners can be accessed for archaeological heritage information as part of development planning processes. Applications of GIS in urban planning, tourism and recreation planning illustrate that GIS is a strong and effective tool that can aid in tourism planning and decision- making. The power of GIS lies not only in the ability to visualize spatial relationships, but also beyond the space to a holistic view of the world with its many interconnected components and complex relationships. The worst of the damage could have been avoided by recognizing suitable limits and adhering to some simple environmental guidelines and standards will successfully develop tourism in sustainable manner. By identifying sensitive natural environment and archaeological heritage resources of the Northern part of the UAE, public agencies and private citizens are in a better position to successfully protect important natural lands and direct growth away from environmentally sensitive areas.

Keywords: GIS, natural environment, UAE, urban growth

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Authors: Ana Neves, John Leander, Ignacio Gonzalez, Raid Karoumi

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Systematic monitoring and inspection are needed to assess the present state of a structure and predict its future condition. If an irregularity is noticed, repair actions may take place and the adequate intervention will most probably reduce the future costs with maintenance, minimize downtime and increase safety by avoiding the failure of the structure as a whole or of one of its structural parts. For this to be possible decisions must be made at the right time, which implies using systems that can detect abnormalities in their early stage. In this sense, Structural Health Monitoring (SHM) is seen as an effective tool for improving the safety and reliability of infrastructures. This paper explores the decision-making problem in SHM regarding the maintenance of civil engineering structures. The aim is to assess the present condition of a bridge based exclusively on measurements using the suggested method in this paper, such that action is taken coherently with the information made available by the monitoring system. Artificial Neural Networks are trained and their ability to predict structural behavior is evaluated in the light of a case study where acceleration measurements are acquired from a bridge located in Stockholm, Sweden. This relatively old bridge is presently still in operation despite experiencing obvious problems already reported in previous inspections. The prediction errors provide a measure of the accuracy of the algorithm and are subjected to further investigation, which comprises concepts like clustering analysis and statistical hypothesis testing. These enable to interpret the obtained prediction errors, draw conclusions about the state of the structure and thus support decision making regarding its maintenance.

Keywords: artificial neural networks, clustering analysis, model-free damage detection, statistical hypothesis testing, structural health monitoring

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Authors: Ling-Lang Huang

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Background: The holistic health care should ideally cover physical, mental, spiritual, and social aspects of a patient. With very constrained time in current clinical practice system, medical decisions often tip the balance in favor of evidence-based medicine (EBM) in comparison to patient's personal values. Even in the era of competence-based medical education (CBME), when scrutinizing the items of entrustable professional activities (EPAs), we found that EPAs of establishing doctor-patient relationship remained incomplete or even missing. This phenomenon prompted us to raise this project aiming at advocating value-based medicine (VBM), which emphasizes the importance of patient’s values in medical decisions. A true and effective doctor-patient communication and relationship should be a well-balanced harmony of EBM and VBM. By constructing VBM into current EPAs, we can further promote genuine shared decision making (SDM) and fix the missing link in holistic health care. Methods: In this project, we are going to find out EPA elements crucial for establishing an ideal doctor-patient relationship through three distinct pairs of doctor-patient relationships: patients with pulmonary arterial hypertension (relatively young but with grave disease), patients undergoing surgery (facing critical medical decisions), and patients with terminal diseases (facing forthcoming death). We’ll search for important EPA elements through the following steps: 1. Narrative approach to delineate patients’ values among 2. distinct groups. 3.Hermeneutics-based interview: semi-structured interview will be conducted for both patients and physicians, followed by qualitative analysis of collected information by compiling, disassembling, reassembling, interpreting, and concluding. 4. Preliminarily construct those VBM elements into EPAs for doctor-patient relationships in 3 groups. Expected Outcomes: The results of this project are going to give us invaluable information regarding the impact of patients’ values, while facing different medical situations, on the final medical decision. The competence of well-blending and -balanced both values from patients and evidence from clinical sciences is the missing link in holistic health care and should be established in future EPAs to enhance an effective SDM.

Keywords: value-based medicine, shared decision making, entrustable professional activities, holistic health care

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Authors: Srinivas Vangari

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In the era of big data, ensuring the accuracy, consistency, and reliability of critical data assets is crucial for data-driven enterprises. Master Data Management (MDM) plays a crucial role in this endeavor. This paper investigates the role of Artificial Intelligence (AI) in enhancing MDM, focusing on how AI-driven solutions can automate and optimize various stages of the master data lifecycle. By integrating AI (Quantitative and Qualitative Analysis) into processes such as data creation, maintenance, enrichment, and usage, organizations can achieve significant improvements in data quality and operational efficiency. Quantitative analysis is employed to measure the impact of AI on key metrics, including data accuracy, processing speed, and error reduction. For instance, our study demonstrates an 18% improvement in data accuracy and a 75% reduction in duplicate records across multiple systems post-AI implementation. Furthermore, AI’s predictive maintenance capabilities reduced data obsolescence by 22%, as indicated by statistical analyses of data usage patterns over a 12-month period. Complementing this, a qualitative analysis delves into the specific AI-driven strategies that enhance MDM practices, such as automating data entry and validation, which resulted in a 28% decrease in manual errors. Insights from case studies highlight how AI-driven data cleansing processes reduced inconsistencies by 25% and how AI-powered enrichment strategies improved data relevance by 24%, thus boosting decision-making accuracy. The findings demonstrate that AI significantly enhances data quality and integrity, leading to improved enterprise performance through cost reduction, increased compliance, and more accurate, real-time decision-making. These insights underscore the value of AI as a critical tool in modern data management strategies, offering a competitive edge to organizations that leverage its capabilities.

Keywords: artificial intelligence, master data management, data governance, data quality

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Authors: Ewa M. Laskowska, Jorn Vatn

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Industry 4.0 focuses on digital optimization of industrial processes. The idea is to use extracted data in order to build a decision support model enabling use of those data for real time decision making. In terms of predictive maintenance, the desired decision support tool would be a model enabling prognostics of system's health based on the current condition of considered equipment. Within area of system prognostics and health management, a commonly used health indicator is Remaining Useful Lifetime (RUL) of a system. Because the RUL is a random variable, it has to be estimated based on available health indicators. Health indicators can be of different types and come from different sources. They can be process variables, equipment performance variables, data related to number of experienced failures, etc. The aim of this study is the analysis of performance variables of emergency shutdown valves (ESV) used in oil and gas industry. ESV is inspected periodically, and at each inspection torque and time of valve operation are registered. The data will be analyzed by means of machine learning or statistical analysis. The purpose is to investigate whether the available data could be used as a health indicator for a prognostic purpose. The second objective is to examine what is the most efficient way to incorporate the data into predictive model. The idea is to check whether the data can be applied in form of explanatory variables in Markov process or whether other stochastic processes would be a more convenient to build an RUL model based on the information coming from registered data.

Keywords: emergency shutdown valves, health indicator, prognostics, remaining useful lifetime, RUL

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Authors: Erdal Akyol, Mutlu Alkan

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Multi criteria decision analysis (MDCA) covers both data and experience. It is very common to solve the problems with many parameters and uncertainties. GIS supported solutions improve and speed up the decision process. Weighted grading as a MDCA method is employed for solving the geotechnical problems. In this study, geotechnical parameters namely soil type; SPT (N) blow number, shear wave velocity (Vs) and depth of underground water level (DUWL) have been engaged in MDCA and GIS. In terms of geotechnical aspects, the settlement suitability of the municipal area was analyzed by the method. MDCA results were compatible with the geotechnical observations and experience. The method can be employed in geotechnical oriented microzoning studies if the criteria are well evaluated.

Keywords: GIS, spatial analysis, multi criteria decision analysis, geotechnics

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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: Artur Krukowski, Emmanouela Vogiatzaki

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The article presents an ongoing work in research projects such as SCAN4RECO or ARCH, both funded by the European Commission under Horizon 2020 program. The former one concerns multimodal and multispectral scanning of Cultural Heritage assets for their digitization and conservation via spatiotemporal reconstruction and 3D printing, while the latter one aims to better preserve areas of cultural heritage from hazards and risks. It co-creates tools that would help pilot cities to save cultural heritage from the effects of climate change. It develops a disaster risk management framework for assessing and improving the resilience of historic areas to climate change and natural hazards. Tools and methodologies are designed for local authorities and practitioners, urban population, as well as national and international expert communities, aiding authorities in knowledge-aware decision making. In this article we focus on 3D modelling of object geometry using primarily photogrammetric methods to achieve very high model accuracy using consumer types of devices, attractive both to professions and hobbyists alike.

Keywords: 3D modelling, UAS, cultural heritage, preservation

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Authors: Angga Hidayah Ramadhan, Luciana Andrawina, M. Azani Hasibuan

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Data will be as a core of the decision if it has a good treatment or process, which is process that data into information, and information into knowledge to make a wisdom or decision. Today, many companies have not realize it include XYZ University Admission Directorate as executor of National Admission called Seleksi Masuk Bersama (SMB) that during the time, the workers only uses their feeling to make a decision. Whereas if it done, then that company can analyze the data to make a right decision to get a pin sales from student candidate or registrant that follow SMB as many as possible. Therefore, needs Knowledge Management System (KMS) with Geographic Information System (GIS) use 5C4C that can process that company data becomes more useful and can help make decisions. This information system can process data into information based on the pin sold data with 5C (Contextualized, Categorize, Calculation, Correction, Condensed) and convert information into knowledge with 4C (Comparing, Consequence, Connection, Conversation) that has been several steps until these data can be useful to make easier to take a decision or wisdom, resolve problems, communicate, and quicker to learn to the employees have not experience and also for ease of viewing/visualization based on spatial data that equipped with GIS functionality that can be used to indicate events in each province with indicator that facilitate in this system. The system also have a function to save the tacit on the system then to be proceed into explicit in expert system based on the problems that will be found from the consequences of information. With the system each team can make a decision with same ways, structured, and the important is based on the actual event/data.

Keywords: 5C4C, data, information, knowledge

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Authors: Lauren Freed

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This research proposal outlines an examination of homeschool oversight in the Massachusetts educational system amid the backdrop of ideological differences between various parties with contributing interests. This mixed methodology study will follow an interpretive policy research approach, involving the use of existing data, surveys, and focus groups. The aim is to capture distinct sets of meanings, values, feelings, and beliefs by principal stakeholders, while exploring the ways in which they/each interact with, interpret, and implement homeschool guidelines set forth by the Massachusetts Supreme Judicial Court Decision Care and Protection of Charles (1987). This analysis will identify and contextualize the attitudes, administrative choices, financial implications, and educational impacts that result from the process and practice of enacting current homeschool oversight policy in Massachusetts. The following question will guide this study: How do districts, homeschooling parents, and Massachusetts Department of Elementary and Secondary Education (DESE) regulate, fund, collect, interpret, implement and report Massachusetts homeschool oversight policy? The resulting analysis will produce a unique and original baseline snapshot of qualitative and quantifiable point-in-time data based on the registered homeschool population in the state of Massachusetts.

Keywords: alternative education, homeschooling, home education, home schooling policy

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

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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: Maria Antonieta Erna Castillo Holly

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During the last decade, data analysis, strategic decision making, and the use of artificial intelligence (AI) tools in Latin American agriculture have been a challenge. In some countries, the availability, quality, and reliability of historical data, in addition to the current data recording methodology in the field, makes it difficult to use information systems, complete data analysis, and their support for making the right strategic decisions. This is something essential in Agriculture 4.0. where the increase in the global demand for fresh agricultural products of tropical origin, during all the seasons of the year requires a change in the production model and greater agility in the responses to the consumer market demands of quality, quantity, traceability, and sustainability –that means extensive data-. Having quality information available and updated in real-time on what, how much, how, when, where, at what cost, and the compliance with production quality standards represents the greatest challenge for sustainable and profitable agriculture in the region. The objective of this work is to present a methodological proposal for the collection of georeferenced data from the protected agriculture sector, specifically in production units (UP) with tall structures (Greenhouses), initially for Venezuela, taking the state of Mérida as the geographical framework, and horticultural products as target crops. The document presents some background information and explains the methodology and tools used in the 3 phases of the work: diagnosis, data collection, and analysis. As a result, an evaluation of the process is carried out, relevant data and dashboards are displayed, and the first satellite maps integrated with layers of information in a geographic information system are presented. Finally, some improvement proposals and tentatively recommended applications are added to the process, understanding that their objective is to provide better qualified and traceable georeferenced data for subsequent analysis of the information and more agile and accurate strategic decision making. One of the main points of this study is the lack of quality data treatment in the Latin America area and especially in the Caribbean basin, being one of the most important points how to manage the lack of complete official data. The methodology has been tested with horticultural products, but it can be extended to other tropical crops.

Keywords: greenhouses, protected agriculture, data analysis, geographic information systems, Venezuela

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Authors: T. Aragaw, P. Gari

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In spite of social, political, and economic marginalization, women are still considered as the backbone of Ethiopia, one of the least developed countries in the world. The general purpose of this study was to assess factors that affect participation of women in politics, social and economic decisions at Kelem-Wollega Administrative Zone of Oromia Regional State, Ethiopia. Data used in this paper is mainly primary, and a few secondary data were incorporated. Respondents were selected using a systematic random sampling method and were placed questionnaires containing open-ended and closed-ended. Focus group discussion was also used for the study subjects in two offices. According to the information collected from the KWAZ Development and Social Service Office, a total of 18,473 tax-paying employees are present in the Zone, which is 14% of the total population of the Zone. Among the total number of employees in the Zone, 2,617 have been recruited for this study based on the criteria stated. This showed 1.8% of them were comprised of several churches and religious owned integrated development projects in the KWAZ. The 2,103 (80.34%) study participants responded personally, and they completed and returned the questionnaire to the researchers. The study revealed that in public institutions existed in KWAZ, the majority of women were having an educational status of diploma and lower, practicing lower non-decision making and leadership positions. Conclusion: Major barriers hindering women include: Socio-cultural attitudes, lack of necessary experience, education, the burden of domestic responsibilities, and lack of role models of women leaders in the Zone. Empowerment of women via social organizations, critical involvement of the government, and Affirmative action for women is critical. Further research is needed on the scope and challenges in implementing the strategies.

Keywords: women, affirmative action, leadership, empowerment, Ethiopia

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Authors: Mijoh A. Gbededo, Kapila Liyanage, Ilias Oraifige

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Decision making for sustainable manufacturing design and management requires critical considerations due to the complexity and partly conflicting issues of economic, social and environmental factors. Although there are tools capable of assessing the combination of one or two of the sustainability factors, the frameworks have not adequately integrated all the three factors. Case study and review of existing simulation applications also shows the approach lacks integration of the sustainability factors. In this paper we discussed the development of a simulation based framework for support of a holistic assessment of sustainable manufacturing design and management. To achieve this, a strategic approach is introduced to investigate the strengths and weaknesses of the existing decision supporting tools. Investigation reveals that Discrete Event Simulation (DES) can serve as a rock base for other Life Cycle Analysis frameworks. Simio-DES application optimizes systems for both economic and competitive advantage, Granta CES EduPack and SimaPro collate data for Material Flow Analysis and environmental Life Cycle Assessment, while social and stakeholders’ analysis is supported by Analytical Hierarchy Process, a Multi-Criteria Decision Analysis method. Such a common and integrated framework creates a platform for companies to build a computer simulation model of a real system and assess the impact of alternative solutions before implementing a chosen solution.

Keywords: discrete event simulation, life cycle sustainability analysis, manufacturing, sustainability

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Authors: Nhi Ngoc Thien

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Franchising is a popular trend in Vietnam retail industry, especially in fast food industry. Several famous foreign fast food brands such as KFC, Lotteria, Jollibee or Pizza Hut invested on this potential market since the 1990s. Following this trend, in 2011, Burger King - the second largest fast food hamburger chain all over the world - entered Vietnam with its first store located in Tan Son Nhat International Airport, with the expectation to become the leading brand in the country. However, the business performance of Burger King was not going well in the first few years making it questioned about its strategy. The given assumption was that its business performance was affected negatively by its store location selection strategy. This research aims to investigate the current performance of Burger King Vietnam in terms of the controllable variables like store location as well as to explore the key factors influencing customer decision to choose Burger King. Therefore, a case study research method was conducted to approach deeply on the opinions and evaluations of 10 Burger King’s customers, Burger King's staffs and other fast food experts on Burger King’s performance through in-depth interview, direct observation and documentary analysis. Findings show that there are 8 determinants affecting the decision-making of Burger King’s customers, which are store location, quality of food, service quality, store atmosphere, price, promotion, menu and brand reputation. Moreover, findings present that Burger King’s staffs and fast food experts also mentioned the main problems of Burger King, which are about store location and food quality. As a result, there are some recommendations for Burger King Vietnam to improve its performance in the market and attract more Vietnamese target customers by giving suitable promotional activities among its customers and being differentiated itself from other fast food brands.

Keywords: overall retail strategy, controllable variables, store location, quality of food

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Authors: Mannan Ahmad Rasheed, Sawera Kanwal, Mansoor Ahmad Rasheed

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The Internet of Things (IoT) has revolutionized the way we collect and process information, making it possible to gather data from a wide range of connected devices and sensors. This has led to the development of IoT-based information processing and computing systems that are capable of handling large amounts of data in real time. This paper provides a comprehensive overview of the current state of IoT-based information processing and computing, as well as the key challenges and gaps that need to be addressed. This paper discusses the potential benefits of IoT-based information processing and computing, such as improved efficiency, enhanced decision-making, and cost savings. Despite the numerous benefits of IoT-based information processing and computing, several challenges need to be addressed to realize the full potential of these systems. These challenges include security and privacy concerns, interoperability issues, scalability and reliability of IoT devices, and the need for standardization and regulation of IoT technologies. Moreover, this paper identifies several gaps in the current research related to IoT-based information processing and computing. One major gap is the lack of a comprehensive framework for designing and implementing IoT-based information processing and computing systems.

Keywords: IoT, computing, information processing, Iot computing

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Authors: Grace Omowunmi Soyebi

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Data Mining is the extraction of information from a large database which helps in predicting a trend or behavior, thereby helping management make knowledge-driven decisions. One principal problem of most hospitals in rural areas is making use of the file management system for keeping records. A lot of time is wasted when a patient visits the hospital, probably in an emergency, and the nurse or attendant has to search through voluminous files before the patient's file can be retrieved; this may cause an unexpected to happen to the patient. This Data Mining application is to be designed using a Structured System Analysis and design method, which will help in a well-articulated analysis of the existing file management system, feasibility study, and proper documentation of the Design and Implementation of a Computerized medical record system. This Computerized system will replace the file management system and help to easily retrieve a patient's record with increased data security, access clinical records for decision-making, and reduce the time range at which a patient gets attended to.

Keywords: data mining, medical record system, systems programming, computing

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Authors: Bahadir Aydin

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It is difficult to access accurate knowledge because of mass data. This huge data make environment more and more caotic. Data are main piller of intelligence. The affiliation between intelligence and knowledge is quite significant to understand underlying truths. The data gathered from different sources can be modified, interpreted and classified by using intelligence cycle process. This process is applied in order to progress to wisdom as well as intelligence. Within this process the effect of tacit knowledge is crucial. Knowledge which is classified as explicit and tacit knowledge is the key element for any purpose. Tacit knowledge can be seen as "the tip of the iceberg”. This tacit knowledge accounts for much more than we guess in all intelligence cycle. If the concept of intelligence cycle is scrutinized, it can be seen that it contains risks, threats as well as success. The main purpose of all organizations is to be successful by eliminating risks and threats. Therefore, there is a need to connect or fuse existing information and the processes which can be used to develop it. Thanks to this process the decision-makers can be presented with a clear holistic understanding, as early as possible in the decision making process. Altering from the current traditional reactive approach to a proactive intelligence cycle approach would reduce extensive duplication of work in the organization. Applying new result-oriented cycle and tacit knowledge intelligence can be procured and utilized more effectively and timely.

Keywords: information, intelligence cycle, knowledge, tacit Knowledge

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Authors: Philip A. Szlosek, M. Susan Guyer, Mary G. Barnum, Elizabeth M. Mullin

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In the United States, athletic training is a healthcare profession that encompasses the prevention, examination, diagnosis, treatment, and rehabilitation of injuries and medical conditions. Athletic trainers work under the direction of or in collaboration with a physician and are recognized by the American Medical Association as allied healthcare professionals. Internationally, this profession is often known as athletic therapy. As healthcare professionals, athletic trainers must be prepared for autonomous practice immediately after graduation. However, new athletic trainers have been shown to have clinical areas of strength and weakness.To better assess professional readiness and improve the preparedness of new athletic trainers, the factors of athletic training professional readiness must be defined. Limited research exists defining the holistic aspects of professional readiness needed for athletic trainers. Confirming the factors of professional readiness in athletic training could enhance the professional preparation of athletic trainers and result in more highly prepared new professionals. The objective of this study was to further explore and confirm the factors of professional readiness in athletic training. Authors useda qualitative design based in grounded theory. Participants included athletic trainers with greater than 24 months of experience from a variety of work settings from each district of the National Athletic Trainer’s Association. Participants took the demographic questionnaire electronically using Qualtrics Survey Software (Provo UT). After completing the demographic questionnaire, 20 participants were selected to complete one-on-one interviews using GoToMeeting audiovisual web conferencing software. IBM Statistical Package for the Social Sciences (SPSS, v. 21.0) was used to calculate descriptive statistics for participant demographics. The first author transcribed all interviews verbatim and utilized a grounded theory approach during qualitative data analysis. Data were analyzed using a constant comparative analysis and open and axial coding. Trustworthiness was established using reflexivity, member checks, and peer reviews. Analysis revealed four overarching themes, including management, interpersonal relations, clinical decision-making, and confidence. Management was categorized as athletic training services not involving direct patient care and was divided into three subthemes, including administration skills, advocacy, and time management. Interpersonal Relations was categorized as the need and ability of the athletic trainer to properly interact with others. Interpersonal relations was divided into three subthemes, including personality traits, communication, and collaborative practice. Clinical decision-making was categorized as the skills and attributes required by the athletic trainer whenmaking clinical decisions related to patient care. Clinical decision-making was divided into three subthemes including clinical skills, continuing education, and reflective practice. The final theme was confidence. Participants discussed the importance of confidence regarding relationships building, clinical and administrative duties, and clinical decision-making. Overall, participants explained the value of a well-rounded athletic trainer and emphasized that athletic trainers need communication and organizational skills, the ability to collaborate, and must value self-reflection and continuing education in addition to having clinical expertise. Future research should finalize a comprehensive model of professional readiness for athletic training, develop a holistic assessment instrument for athletic training professional readiness, and explore the preparedness of new athletic trainers.

Keywords: autonomous practice, newly certified athletic trainer, preparedness for professional practice, transition to practice skills

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Authors: Javad Abdi, Azam Famil Khalili

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Modeling emotions have attracted much attention in recent years, both in cognitive psychology and design of artificial systems. However, it is a negative factor in decision-making; emotions have shown to be a strong faculty for making fast satisfying decisions. In this paper, we have adapted a computational model based on the limbic system in the mammalian brain for control engineering applications. Learning in this model based on Temporal Difference (TD) Learning, we applied the proposed controller (termed BELBIC) for a simple model of a submarine. The model was supposed to reach the desired depth underwater. Our results demonstrate excellent control action, disturbance handling, and system parameter robustness for TDBELBIC. The proposal method, regarding the present conditions, the system action in the part and the controlling aims, can control the system in a way that these objectives are attained in the least amount of time and the best way.

Keywords: artificial neural networks, temporal difference, brain emotional learning based intelligent controller, heating- ventilating and air conditioning

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