Search results for: moral decision

Authors: Andrés I. Ávila, Patricia Aros, César San Martín, Elizabeth Kehr, Yovana Leal

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Planning models for fresh products is a very useful tool for improving the net profits. To get an efficient supply chain model, several functions should be considered to get a complete simulation of several operational units. We consider a linear programming model to help farmers to decide if it is convenient to choose what area should be planted for three kinds of export fruits considering their future investment. We consider area, investment, water, productivity minimal unit, and harvest restrictions to develop a monthly based model to compute the average income in five years. Also, conditions on the field as area, water availability, and initial investment are required. Using the Chilean costs and dollar-peso exchange rate, we can simulate several scenarios to understand the possible risks associated to this market. Also, this tool help to support decisions for government and individual farmers.

Keywords: mixed integer problem, fresh fruit production, support decision model, agricultural and biosystems engineering

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Authors: Anna Sikharulidze, Gia Sirbiladze

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For the evaluation of unreliability levels of movement on the closed routes in the vehicle routing problem, the fuzzy operators family is constructed. The interactions between routing factors in extreme conditions on the roads are considered. A multi-criteria decision-making model (MCDM) is constructed. Constructed aggregations are based on the Choquet integral and the associated probability class of a fuzzy measure. Propositions on the correctness of the extension are proved. Connections between the operators and the compositions of dual triangular norms are described. The conjugate connections between the constructed operators are shown. Operators reflect interactions among all the combinations of the factors in the fuzzy MCDM process. Several variants of constructed operators are used in the decision-making problem regarding the assessment of unreliability and possibility levels of movement on closed routes.

Keywords: vehicle routing problem, associated probabilities of a fuzzy measure, choquet integral, fuzzy aggregation operator

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Authors: Puran Prasad Adhikari

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Considering the fact that when we are able to communicate science and economics effectively to broader nonprofessional audiences, it promotes a great understanding of its wider relevance to society and encourages more informed and confident decision-making at all levels, from the government to communities to individuals. The study has been conducted. This study is aimed to examine the understanding of the general public of economics and the basic sciences functioning in our surroundings in our day-to-day life. Data was gathered through historical documents related to science communication and through interviews with the public. The statistical result shows that there is a great lack of knowledge in the general public about the basic sciences and how economics impacts their life daily. The difficulties faced by the public include the view that these things can only be understood by professionals and it is beyond their capacity to grasp these concepts, the use of technical words and jargon by the professionals, and the lack of the medium to understand even if they want to learn it. The result further indicates that the lack of this basic knowledge also leads to bad decision-making, which causes frustration and anxiety. The result shows the great correlation between the confidence level of a person and the knowledge of basic science and economics. The factor behind this was the right decision-making capacity of the individual, which boosts the happy hormones of the individual. So indirectly, we found the correlation between mental health and the understanding of science and economics. The public wants to have a basic understanding and concepts of these topics, but they complain that there is no effective medium through which they can gain the understanding; the medium which is available is full of jargon and technical terms directed to professional and highly educated which they consider is beyond their reach. So, communicating the basic concepts to the general public is of great importance in the 21st century for the overall progress of society. The professional one can make this possible by considering the level of public understanding and making the communication and the programs comprehensible to the layman. Various means can be used to make this successful and effective, e.g., cartoon guide books, Q&A with the layman, animations use, and daily life examples. This study’s implication will help educators of high-level institutions and policymakers improve general public [layman] access to comprehensible knowledge.

Keywords: layman, comprehensible, decision making, frustration, confidence

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Authors: Salima Smiti, Ines Gasmi, Makram Soui

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Credit risk is the most important issue for financial institutions. Its assessment becomes an important task used to predict defaulter customers and classify customers as good or bad payers. To this objective, numerous techniques have been applied for credit risk assessment. However, to our knowledge, several evaluation techniques are black-box models such as neural networks, SVM, etc. They generate applicants’ classes without any explanation. In this paper, we propose to assess credit risk using rules classification method. Our output is a set of rules which describe and explain the decision. To this end, we will compare seven classification algorithms (JRip, Decision Table, OneR, ZeroR, Fuzzy Rule, PART and Genetic programming (GP)) where the goal is to find the best rules satisfying many criteria: accuracy, sensitivity, and specificity. The obtained results confirm the efficiency of the GP algorithm for German and Australian datasets compared to other rule-based techniques to predict the credit risk.

Keywords: credit risk assessment, classification algorithms, data mining, rule extraction

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Authors: Abhigyan Hedau, Priya Shelke, Riddhi Mirajkar, Shreyash Chaple, Mrunali Gadekar, Himanshu Akula

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The heart is the coordinating centre of the major endocrine glandular structure of the body, which produces hormones that profoundly affect the operations of the body, and diagnosing cardiovascular disease is a difficult but critical task. By extracting knowledge and information about the disease from patient data, data mining is a more practical technique to help doctors detect disorders. We use a variety of machine learning methods here, including logistic regression and support vector classifiers (SVC), K-nearest neighbours Classifiers (KNN), Decision Tree Classifiers, Random Forest classifiers and Gradient Boosting classifiers. These algorithms are applied to patient data containing 13 different factors to build a system that predicts heart disease in less time with more accuracy.

Keywords: logistic regression, support vector classifier, k-nearest neighbour, decision tree, random forest and gradient boosting

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Authors: Roberta Martino, Viviana Ventre

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From a theoretical point of view, the relationship between the risk associated with an investment and the expected value are directly proportional, in the sense that the market allows a greater result to those who are willing to take a greater risk. However, empirical evidence proves that this relationship is distorted in the minds of investors and is perceived exactly the opposite. To deepen and understand the discrepancy between the actual actions of the investor and the theoretical predictions, this paper analyzes the essential parameters used for the valuation of financial assets with greater attention to two elements: probability and the passage of time. Although these may seem at first glance to be two distinct elements, they are closely related. In particular, the error in the theoretical description of the relationship between risk and return lies in the failure to consider the impatience that is generated in the decision-maker when events that have not yet happened occur in the decision-making context. In this context, probability loses its objective meaning and in relation to the psychological aspects of the investor, it can only be understood as the degree of confidence that the investor has in the occurrence or non-occurrence of an event. Moreover, the concept of objective probability does not consider the inter-temporality that characterizes financial activities and does not consider the condition of limited cognitive capacity of the decision maker. Cognitive psychology has made it possible to understand that the mind acts with a compromise between quality and effort when faced with very complex choices. To evaluate an event that has not yet happened, it is necessary to imagine that it happens in your head. This projection into the future requires a cognitive effort and is what differentiates choices under conditions of risk and choices under conditions of uncertainty. In fact, since the receipt of the outcome in choices under risk conditions is imminent, the mechanism of self-projection into the future is not necessary to imagine the consequence of the choice and the decision makers dwell on the objective analysis of possibilities. Financial activities, on the other hand, develop over time and the objective probability is too static to consider the anticipatory emotions that the self-projection mechanism generates in the investor. Assuming that uncertainty is inherent in valuations of events that have not yet occurred, the focus must shift from risk management to uncertainty management. Only in this way the intertemporal dimension of the decision-making environment and the haste generated by the financial market can be cautioned and considered. The work considers an extension of the prospectus theory with the temporal component with the aim of providing a description of the attitude towards risk with respect to the passage of time.

Keywords: impatience, risk aversion, subjective probability, uncertainty

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Authors: S. Vaibhav Kant Sahu, Surabhi Bipin Seth

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Human well-being has multiple constituents including the basic material for a good life, freedom and choice, health, good social relations, and security. Poverty is also multidimensional and has been defined as the pronounced deprivation of well-being. Dhurwa tribe of Bastar (India) have symbiotic relation with nature, it provisions ecosystem service such as food, fuel and fiber; regulating services such as climate regulation and non-material benefits such as spiritual or aesthetic benefits and they are managing their forest from ages. The demand for ecosystem services is now so great that trade-off among services become rule. Aim of study to explore evidences for linkages between ecosystem services and well-being of indigenous community, how much it helps them in poverty reduction and interaction between them. Objective of study was to find drivers of change and evidence concerning link between ecosystem, human development and sustainability, evidence in decision making does it opt for multi sectoral objectives. Which means human well-being as the central focus for assessment, while recognizing that biodiversity and ecosystems also have intrinsic value. Ecosystem changes that may have little impact on human well-being over days or weeks may have pronounced impacts over years or decades; so assessments needed to be conducted at spatial and temporal scales under social, political, economic scales to have high-resolution data. Researcher used framework developed by Millennium ecosystem assessment; since human action now directly or unknowingly virtually alter ecosystem. Researcher used ethnography study to get primary qualitative data, secondary data collected from panchayat office. The responses were transcribed and translated into English, as interview held in Hindi and local indigenous language. Focus group discussion were held with group of 10 women at Tiriya village. Researcher concluded with well-being is not just gap between ecosystem service supply but also increases vulnerability. Decision can have consequences external to the decision framework these consequences are called externalities because they are not part of the decision-making calculus.

Keywords: Bastar, Dhurwa tribe, ecosystem services, millennium ecosystem assessment, sustainability

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Authors: Monica Lia

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This article presents a customer data analysis model using business intelligence tools for data modelling, transforming, data visualization and dynamic reports building. Economic organizational customer’s analysis is made based on the information from the transactional systems of the organization. The paper presents how to develop the data model starting for the data that companies have inside their own operational systems. The owned data can be transformed into useful information about customers using business intelligence tool. For a mature market, knowing the information inside the data and making forecast for strategic decision become more important. Business Intelligence tools are used in business organization as support for decision-making.

Keywords: customer analysis, business intelligence, data warehouse, data mining, decisions, self-service reports, interactive visual analysis, and dynamic dashboards, use cases diagram, process modelling, logical data model, data mart, ETL, star schema, OLAP, data universes

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Authors: Hamideh Rahmani

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The subject matter of ethics is being changed in modern life, which had been an issue for a long time and aimed to define its moral boundaries in human's intellectual and everyday life. This has led to the introduction of notions based on the separation of religion from ethics in recent decades. It is in conflict with the traditional view, which introduces ethics as raised from religion and religion as the most crucial credit for ethics. The purpose of this study is to investigate the elements of secular ethics from the perspective of Mostafa Malekian, seeking to achieve his notions. After examining the strengths of secular ethics parameters from the viewpoint of Malekian, this research found his ethics in his interpretation of the ideal life which he treats as ethics, got a very strong link with his secularist project known as rationality and spirituality. We will analyze, review, and critique his ethics in the following.

Keywords: secular ethics, Mostafa Malakian, global ethics, rationality, spirituality

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Authors: Preeti Nakhat

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Background: Values are essential part of one's life. They are inculcated since the early years of life and shape the personality of the individual. They play a tremendous role in decision making. Teenagers are seen perplexed about the values of their life. The challenge faced by majority of the teenage population in choosing between a positive and negative value is high. The values they adopt remain throughout their life and in every decision, hence it is a crucial topic of research. Research Methodology: This research aimed at finding out the value conflict of teenagers in relations. Hypothesis of the study are: H₀- There is no significant association between the life values and value conflict of higher secondary students; H₁– There is a significant association between the life values and value conflict of higher secondary students. For the same, the standardized tool, value conflict scale by R. L. Bhardwaj has been used. The tool consists 24 questions of different life situations with multiple choice options. Findings: There is 96% variation in value conflict due to evasion vs. fortitude, dependence vs. self-reliance, selfishness vs. probity, hate vs. love, fear vs. assertion and pragmatism vs. idealism life values. There is a positive association between all the life values and value conflict of higher secondary school students. Percentages of association are: 0.17% between value conflict and evasion vs. fortitude value, 0.16% between value conflict and dependence vs. self-reliance value, 0.17% between value conflict and selfishness vs. probity value, 0.16% between value conflict and hate vs. love value, 0.17% between value conflict and fear vs. assertion, 0.17% between value conflict and pragmatism vs. idealism value. Discussions: The dilemma faced by the students regarding value conflict is high. Bewilderment of being honest or lying, of loving or hating family and friends, being pragmatic or idealistic in life decision, being selfish or selfless is seen among the students. It is the challenge for the future. Teaching of values with a practical aspect should be added in the school curriculum.

Keywords: dilemma, conflict, school, values

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Authors: Müjde Erol Genevois, Hatice Kocaman

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Growing concerns about the increasing consumption of fossil energy and the improved recognition of environmental protection require sustainable road transportation technology. Electric vehicles (EVs) can contribute to improve environmental sustainability and to solve the energy problem with the right infrastructure. The problem of where to locate electric vehicle charging station can be grouped as decision-making problems because of including many criteria and alternatives that have to be considered simultaneously. The purpose of this paper is to present an integrated AHP and TOPSIS model to rank the optimal sites of EVs charging station in Istanbul, Turkey. Ten different candidate points and three decision criteria are identified. The performances of each candidate points with respect to criteria are obtained according to AHP calculations. These performances are used as an input for TOPSIS method to rank the candidate points. It is obtained accurate and robust results by integrating AHP and TOPSIS methods.

Keywords: electric vehicle charging station (EVCS), AHP, TOPSIS, location selection

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Authors: J. K. Alhassan, S. A. Lawal

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This work is on decision tree-based classification for the disbursement of scholarship. Tree-based data mining classification technique is used in other to determine the generic rule to be used to disburse the scholarship. The system based on the defined rules from the tree is able to determine the class (status) to which an applicant shall belong whether Granted or Not Granted. The applicants that fall to the class of granted denote a successful acquirement of scholarship while those in not granted class are unsuccessful in the scheme. An algorithm that can be used to classify the applicants based on the rules from tree-based classification was also developed. The tree-based classification is adopted because of its efficiency, effectiveness, and easy to comprehend features. The system was tested with the data of National Information Technology Development Agency (NITDA) Abuja, a Parastatal of Federal Ministry of Communication Technology that is mandated to develop and regulate information technology in Nigeria. The system was found working according to the specification. It is therefore recommended for all scholarship disbursement organizations.

Keywords: classification, data mining, decision tree, scholarship

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Authors: Muhammad Asim, Mehvish Amjad

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Background: Less than half of women in South Asia (SA) use any modern contraceptive method which leads to a huge burden of unintended pregnancies, unsafe abortions, maternal deaths, and socioeconomic loss. Women empowerment plays a pivotal role in improving various health seeking behaviours, including contraceptive use. The objective of this study to explore the association between women's empowerment and modern contraceptive, among rich and poor segment of population in SA. Methods: We used the most recent, large-scale, demographic health survey data of five South Asian countries, namely Afghanistan, Pakistan, Bangladesh, India, and Nepal. The outcome variable was the current use of modern contraceptive methods. The main exposure variable was a combination (interaction) of socio-economic status (SES) and women’s level of empowerment (low, medium, and high), where SES was bifurcated into poor and rich; and women empowerment was divided into three categories: decision making, attitude to violence and social independence. Moreover, overall women empowerment indicator was also created by using three dimensions of women empowerment. We applied both descriptive statistics and multivariable logistic regression techniques for data analyses. Results: Most of the women possessed ‘medium’ level of empowerment across South Asian Countries. The lowest attitude to violence empowerment was found in Afghanistan, and the lowest social independence empowerment was observed in Bangladesh across SA. However, Pakistani women have the lowest decision-making empowerment in the region. The lowest modern contraceptive use (22.1%) was found in Afghanistan and the highest (53.2%) in Bangladesh. The multivariate results depict that the overall measure of women empowerment does not affect modern contraceptive use among poor and rich women in most of South Asian countries. However, the decision-making empowerment plays a significant role among both poor and rich women to use modern contraceptive methods across South Asian countries. Conclusions: The effect of women’s empowerment on modern contraceptive use is not consistent across countries, and among poor and rich segment of population. Of the three dimensions of women’s empowerment, the autonomy of decision making in household affairs emerged as a stronger determinant of mCPR as compared with social independence and attitude towards violence against women.

Keywords: women empowerment, modern contraceptive use, South Asia, socio economic status

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Authors: Panagiota Katsikouli, William Hamilton Byrne, Thomas Gammeltoft-Hansen, Tijs Slaats

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An individual who demonstrates a well-founded fear of persecution or faces real risk of being subjected to torture is eligible for asylum. In Danish law, the exact legal thresholds reflect those established by international conventions, notably the 1951 Refugee Convention and the 1950 European Convention for Human Rights. These international treaties, however, remain largely silent when it comes to how states should assess asylum claims. As a result, national authorities are typically left to determine an individual’s legal eligibility on a narrow basis consisting of an oral testimony, which may itself be hampered by several factors, including imprecise language interpretation, insecurity or lacking trust towards the authorities among applicants. The leaky ground, on which authorities must assess their subjective perceptions of asylum applicants' credibility, questions whether, in all cases, adjudicators make the correct decision. Moreover, the subjective element in these assessments raises questions on whether individual asylum cases could be afflicted by implicit biases or stereotyping amongst adjudicators. In fact, recent studies have uncovered significant correlations between decision outcomes and the experience and gender of the assigned judge, as well as correlations between asylum outcomes and entirely external events such as weather and political elections. In this study, we analyze a publicly available dataset containing approximately 8,000 summaries of asylum cases, initially rejected, and re-tried by the Refugee Appeals Board (RAB) in Denmark. First, we look for variations in the recognition rates, with regards to a number of applicants’ features: their country of origin/nationality, their identified gender, their identified religion, their ethnicity, whether torture was mentioned in their case and if so, whether it was supported or not, and the year the applicant entered Denmark. In order to extract those features from the text summaries, as well as the final decision of the RAB, we applied natural language processing and regular expressions, adjusting for the Danish language. We observed interesting variations in recognition rates related to the applicants’ country of origin, ethnicity, year of entry and the support or not of torture claims, whenever those were made in the case. The appearance (or not) of significant variations in the recognition rates, does not necessarily imply (or not) bias in the decision-making progress. None of the considered features, with the exception maybe of the torture claims, should be decisive factors for an asylum seeker’s fate. We therefore investigate whether the decision can be predicted on the basis of these features, and consequently, whether biases are likely to exist in the decisionmaking progress. We employed a number of machine learning classifiers, and found that when using the applicant’s country of origin, religion, ethnicity and year of entry with a random forest classifier, or a decision tree, the prediction accuracy is as high as 82% and 85% respectively. tentially predictive properties with regards to the outcome of an asylum case. Our analysis and findings call for further investigation on the predictability of the outcome, on a larger dataset of 17,000 cases, which is undergoing.

Keywords: asylum adjudications, automated decision-making, machine learning, text mining

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Authors: Siti Noor Baiti Binti Mustafa

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Energy management studies regarding energy efficiency investments in Malaysia has yet to address the lack of empirical research that examines pro- sustainability behavior of managers in the industrial sector and how it influences energy efficiency investment decision-making. This study adopts the Theory of Planned Behavior (TPB) to examine the relationship between personal attitude, subjective norms, and perceived behavioral control (PBC), the intention of energy efficiency investments, and how perceptions of Non-Energy Benefits (NEB) influence these intentions among managers in the industrial sector in Malaysia. Managers from various sub-sectors in the industrial sector were selected from a sample of companies that are participants of the Government-led program named the Energy Audit Conditional Grant (EACG) that aimed to promote energy efficiency. Data collection was conducted through an online semi-structured, open-ended questionnaire and then later interviewed. The results of this explorative sequential qualitative study showed that perceived behavioral control was a significant predictor of energy efficiency investment intentions as compared to factors such as attitude and subjective norms. The level of awareness and perceptions towards NEB further played a significant factor in influencing energy efficiency investment decision-making as well. Various measures and policy recommendations are provided together with insights on factors that influence decision-makers intention to invest in energy efficiency, whilst new knowledge on NEB perceptions will be useful to enhance the attractiveness of energy-efficient investments.

Keywords: energy efficiency investments, non-energy benefits, theory of planned behavior, personal attitude, subjective norms, perceived behavioral control, Malaysia industrial sector

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Authors: Yongsheng Guo, Xiaoxian Zhu, Mandella Osei-Assibey Bonsu

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This study explores the effects of national culture on consumer behaviour by identifying the characteristics of Chinese consumers’ decision making in Europe. It offers a better understanding of how cultural factors affect consumers’ behaviour, and how consumers make decisions in other nations with different culture. It adopted a grounded theory approach and conducted twenty-four in-depth interviews. Grounded theory models are developed to link the causal conditions, process and consequences. Results reveal that some cultural factors including conservatism, emotionality, acquaintance community, long-term orientation and principles affect Chinese consumers when making purchase decisions in Europe. Most Chinese consumers plan and prepare their expenditure and stay in Europe as cultural learners, and purchase durable products or assets as investment, and share their experiences within a community. This study identified potential problems such as political and social environment, complex procedures, and restrictions. This study found that external factors influence on internal factors and then internal characters determine consumer behaviour. This study proposes that cultural traits developed in convergence evolution through social selection and Chinese consumers persist most characters but adapt some perceptions and actions overtime in other countries. This study suggests that cultural marketing could be adopted by companies to reflect consumers’ preferences. Agencies, shops, and the authorities could take actions to reduce the complexity and restrictions.

Keywords: national culture, consumer behaviour, decision making, cultural marketing

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Authors: Stephan Printz, Kristina Lahl, René Vossen, Sabina Jeschke

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Strategic investment decisions are characterized by high innovation potential and long-term effects on the competitiveness of enterprises. Due to the uncertainty and risks involved in this complex decision making process, the need arises for well-structured support activities. A method that considers cost and the long-term added value is the cost-benefit effectiveness estimation. One of those methods is the “profitability estimation focused on benefits – PEFB”-method developed at the Institute of Management Cybernetics at RWTH Aachen University. The method copes with the challenges associated with strategic investment decisions by integrating long-term non-monetary aspects whilst also mapping the chronological sequence of an investment within the organization’s target system. Thus, this method is characterized as a holistic approach for the evaluation of costs and benefits of an investment. This participation-oriented method was applied to business environments in many workshops. The results of the workshops are a library of more than 96 cost aspects, as well as 122 benefit aspects. These aspects are preprocessed and comparatively analyzed with regards to their alignment to a series of risk levels. For the first time, an accumulation and a distribution of cost and benefit aspects regarding their impact and probability of occurrence are given. The results give evidence that the PEFB-method combines precise measures of financial accounting with the incorporation of benefits. Finally, the results constitute the basics for using information technology and data science for decision support when applying within the PEFB-method.

Keywords: cost-benefit analysis, multi-criteria decision, profitability estimation focused on benefits, risk and uncertainty analysis

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Authors: Donato Vese

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According to the common interpretation, in a legal system, public powers are established by law. Exceptions are admitted in an emergency or particular relationship with public power. However, we currently agree that law allows public administration a margin of decision, even in the case of non-discretionary acts. Hence, the administrative decision not exclusively established by law becomes the rule in the ordinary state of things, non-only in state of exception. This paper aims to analyze and discuss different ideas on discretionary power on the Rule of Law and Rechtsstaat. Observing the legal literature in Europe and Nord and South America, discretionary power can be described as follow: it could be considered a margin that law accords to the executive power for political decisions or a choice between different interpretations of vague legal previsions. In essence, this explanation admits for the executive a decision not established by law or anyhow not exclusively established by law. This means that the discretionary power of public administration integrates the law. However, integrating law does not mean to decide according to the law, but it means to integrate law with a decision involving public power. Consequently, discretionary power is essentially free will. In this perspective, also the Rule of Law and the Rechtsstaat are notions explained differently. Recently, we can observe how the European notion of Rechtsstaat is founded on the formal validity of the law; therefore, for this notion, public authority’s decisions not regulated by law represent a problem. Thus, different systems of law integration have been proposed in legal literature, such as values, democracy, reasonableness, and so on. This paper aims to verify how, looking at those integration clauses from a logical viewpoint, integration based on the recourse to the legal system itself does not resolve the problem. The aforementioned integration clauses are legal rules that require hard work to explain the correct meaning of the law; in particular, they introduce dangerous criteria in favor of the political majority. A different notion of public power can be proposed. This notion includes two main features: (a) sovereignty belongs to persons and not the state, and (b) fundamental rights are not grounded but recognized by Constitutions. Hence, public power is a system based on fundamental rights. According to this approach, it can also be defined as the notion of public interest as concrete maximization of fundamental rights enjoyments. Like this, integration of the law, vague or subject to several interpretations, must be done by referring to the system of fundamental individual rights. We can think, for instance, to fundamental rights that are right in an objective view but not legal because not established by law.

Keywords: administrative discretion, free will, fundamental rights, public power, sovereignty

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Authors: Fabiola Xavier Leal, Lara Campanharo, Sueli Aparecida Rodrigues Lucas

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The phenomenon of judicialization in health policy brings with it a great deal of problematization, but in general, it means that some issues that were previously solved by traditional political bodies are being decided by the Judiciary bodies. It is, therefore, a controversial topic that has generated many reflections both in the academic and political fields, considering that not only a dispute of public funds is at stake, but also the debate on access to social rights provided for in the Brazilian Federal Constitution of 1988 and in the various public policies, such as healthcare. With regard to the phenomenon in the Mental Health Policy focusing on people who use drugs, the disputes that permeate this scenario are evident: moral, cultural, sanitary, economic, psychological aspects. There are also the individual and collective dimensions of suffering. And in this process, we all question: What is the role of the Brazilian State in this matter? In this context, another question that needs to be answered is the amount spent on this procedure in the state of Espírito Santo (ES), Brazil (in the last 04 years, around R$121,978,591.44 were paid only for compulsory hospitalization of individuals) in the field in question, which is the financing of the services of the Psychosocial Care Network (RAPS). Therefore, this article aims to problematize the phenomenon of judicialization in Mental Health Policy through the compulsory hospitalization of people who use drugs in Espírito Santo (ES). We proposed a study that sought to understand how this has been occurring and making an impact on the provision of RAPS services in the Espírito Santo scenario. Therefore, the general objective of this study is to analyze the expenses with compulsory hospitalizations for drug use carried out by the State Health Department (SESA) between 2014 and 2019, in which we will seek to identify its destination and the impact of these actions on public health policy. For the purposes of this article, we will present the preliminary data of this study, such as the amount spent by the state and the receiving institutions. For data collection, the following data sources were used: documents available publicly on the Transparency Portal (payments made per year, institutions that received, subjects hospitalized, period and the amount of the daily rates paid); as well as the processes generated by SESA through its own system - ONBASE. For qualitative analysis, content analysis was used; and for quantitative analysis, descriptive statistics was used. Thus, we seek to problematize the issue of judicialization for compulsory hospitalizations, considering the current situation in which this resource has been widely requested to legitimize the war on drugs. This scenario highlights the moral-legal discourse, pointing out strategies through the control of bodies and through faith as an alternative.

Keywords: compulsory hospitalization, drugs, judicialization, mental health

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Authors: Md. Moniruzzaman, Thirayoot Limanond

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Being the most visible indicator, the transport system of a city points out how developed the city is. Dhaka megacity holds a mixed composition of motorized and non-motorized modes of transport and the number of vehicle figure is escalating over times. And this obviously poses associated environmental costs like air pollution, noise etc. which is degrading the quality of life in the city. Eventually sustainable transport or more importantly green transport from environmental point of view has become a prime choice to the transport professionals in order to cope up the crisis. Currently the city authority is planning to execute such sustainable transport systems that could serve the pressing demand of the present and meet the future needs effectively. This study focuses on the selection and evaluation of green transportation systems among potential alternatives on a priority basis. In this paper, Fuzzy TOPSIS - a multi-criteria decision method is presented to find out the most prioritized alternative. In the first step, Twenty-one individual specific criteria for sustainability assessment are selected. In the following step, experts provide linguistic ratings to the potential alternatives with respect to the selected criteria. The approach is used to generate aggregate scores for sustainability assessment and selection of the best alternative. In the third step, a sensitivity analysis is performed to understand the influence of criteria weights on the decision making process. The key strength of fuzzy TOPSIS approach is its practical applicability having a generation of good quality solution even under uncertainty.

Keywords: green transport, multi-criteria decision approach, urban transportation system, sustainability assessment, fuzzy theory, uncertainty

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Authors: Pablo Reyes, Vanessa Riveros Fiallo, Cesar Acevedo, Camila Castellanos, Catalina Moncaleano, Maria F. Parra, Laura Colmenares

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Social emotions are physiological, cognitive and behavioral phenomenon that intervene in the mechanisms of adaptation of individuals and their context. These are mediated by interpersonal relationship and language. Such emotions are subdivided into moral and comparison. The present research emphasizes two comparative emotions: Envy and Schadenfreude. Envy arises when a person lack of quality, possessions or achievements and these are superior in someone else. The Schadenfreude (SC) expresses the pleasure that someone experienced by the misfortune of the other. The relationship between both emotions has been questioned before. Hence there are reports showing that envy increases and modulates SC response. Other documents suggest that envy causes SC response. However, the methodological approach of the topic has been made through self-reports, as well as the hypothetical scenarios. Given this problematic, the neuroscience social framework provides an alternative and demonstrates that social emotions have neurophysiological correlates that can be measured. This is relevant when studying social emotions that are reprehensible like envy or SC are. When tested, the individuals tend to report low ratings due to social desirability. In this study, it was drawn up a proposal in research's protocol and the progress on its own piloting. The aim is to evaluate the effect of feeling envy and Schadenfreude has on the decision-making process, as well as the cooperative behavior in an economic game. To such a degree, it was proposed an experimental model that will provoke to feel envious by performing games against an unknown opponent. The game consists of asking general knowledge questions. The difficulty level in questions and the strangers' facial response have been manipulated in order to generate an ecological comparison framework and be able to arise both envy and SC emotions. During the game, an electromyography registry will be made for two facial muscles that have been associated with the expressiveness of envy and SC emotions. One of the innovations of the current proposal is the measurement of the effect that emotions have on a specific behavior. To that extent, it was evaluated the effect of each condition on the dictators' economic game. The main intention is to evaluate if a social emotion can modulate actions that have been associated with social norms, in the literacy. The result of the evaluation of a pilot model (without electromyography record and self-report) have shown an association between envy and SC, in a way that as the individuals report a greater sense of envy, the greater the chance to experience SC. The results of the economic game show a slight tendency towards profit maximization decisions. It is expected that at the time of using real cash this behavior will be strengthened and also to correlate with the responses of electromyography.

Keywords: envy, schadenfreude, electromyography, economic games

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Authors: D. Garg, S. Luthra, A. Haleem

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Reverse logistics (RL) is supposed to be a systematic procedure that helps in improving the environmental hazards and maintain business sustainability for industries. Industries in Indian are now opting for adoption of RL techniques in business. But, RL practices are not popular in Indian industries because of many barriers for its successful implementation. Therefore, need arises to identify and evaluate the barriers to implement RL practices by taking an Indian industries perspective. Literature review approach and case study approach have been adapted to identify relevant barriers to implement RL practices. Further, Fuzzy Decision Making Trial and Evaluation Laboratory methodology has been brought into use for evaluating causal relationships among the barriers to implement RL practices. Seven barriers out of ten barriers have been categorized into the cause group and remaining into effect group. This research will help Indian industries to manage these barriers towards effective implementing RL practices.

Keywords: barriers, decision making trial and evaluation laboratory (DEMATEL), fuzzy set theory, Indian industries, reverse logistics (RL)

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Authors: Deepak Singh, Rail Kuliev

Abstract:

The abstract highlights the critical importance of optimizing data integration and management strategies in the upstream oil and gas industry. With its complex and dynamic nature generating vast volumes of data, efficient data integration and management are essential for informed decision-making, cost reduction, and maximizing operational performance. Challenges such as data silos, heterogeneity, real-time data management, and data quality issues are addressed, prompting the proposal of several strategies. These strategies include implementing a centralized data repository, adopting industry-wide data standards, employing master data management (MDM), utilizing real-time data integration technologies, and ensuring data quality assurance. Training and developing the workforce, “reskilling and upskilling” the employees and establishing robust Data Management training programs play an essential role and integral part in this strategy. The article also emphasizes the significance of data governance and best practices, as well as the role of technological advancements such as big data analytics, cloud computing, Internet of Things (IoT), and artificial intelligence (AI) and machine learning (ML). To illustrate the practicality of these strategies, real-world case studies are presented, showcasing successful implementations that improve operational efficiency and decision-making. In present study, by embracing the proposed optimization strategies, leveraging technological advancements, and adhering to best practices, upstream oil and gas companies can harness the full potential of data-driven decision-making, ultimately achieving increased profitability and a competitive edge in the ever-evolving industry.

Keywords: master data management, IoT, AI&ML, cloud Computing, data optimization

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Authors: Feras Hanandeh, Majdi Shannag

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This research studies the different factors that could affect the Faculty of Information Technology in Hashemite University students’ accumulative average. The research paper verifies the student information, background, their academic records, and how this information will affect the student to get high grades. The student information used in the study is extracted from the student’s academic records. The data mining tools and techniques are used to decide which attribute(s) will affect the student’s accumulative average. The results show that the most important factor which affects the students’ accumulative average is the student Acceptance Type. And we built a decision tree model and rules to determine how the student can get high grades in their courses. The overall accuracy of the model is 44% which is accepted rate.

Keywords: data mining, classification, extracting rules, decision tree

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Authors: Farnoosh Faal

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The rapid growth of social media has brought significant changes to the field of urban e-planning. This study aims to review the existing literature on the impact of social media on urban e-planning processes. The study begins with a discussion of the evolution of social media and its role in urban e-planning. The review covers research on the use of social media for public engagement, citizen participation, stakeholder communication, decision-making, and monitoring and evaluation of urban e-planning initiatives. The findings suggest that social media has the potential to enhance public participation and improve decision-making in urban e-planning processes. Social media platforms such as Facebook, Twitter, and Instagram can provide a platform for citizens to engage with planners and policymakers, express their opinions, and provide feedback on planning proposals. Social media can also facilitate the collection and analysis of data, including real-time data, to inform urban e-planning decision-making. However, the literature also highlights some challenges associated with the use of social media in urban e-planning. These challenges include issues related to the representativeness of social media users, the quality of information obtained from social media, the potential for bias and manipulation of social media content, and the need for effective data management and analysis. The study concludes with recommendations for future research on the use of social media in urban e-planning. The recommendations include the need for further research on the impact of social media on equity and social justice in planning processes, the need for more research on effective strategies for engaging underrepresented groups, and the development of guidelines for the use of social media in urban e-planning processes. Overall, the study suggests that social media has the potential to transform urban e-planning processes but that careful consideration of the opportunities and challenges associated with its use is essential for effective and ethical planning practice.

Keywords: social media, Urban e-planning, public participation, citizen engagement

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Authors: Bello Abdullahi, Yahaya M. Ibrahim, Ahmed D. Ibrahim, Kabir Bala

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Public sector tendering has traditionally been conducted using manual paper-based processes which are known to be inefficient, less transparent and more prone to manipulations and errors. The advent of the Internet and the World Wide Web has led to the development of numerous e-Tendering systems that addressed some of the problems associated with the manual paper-based tendering system. However, most of these systems rarely support the evaluation of tenders and where they do it is mostly based on the single decision maker which is not suitable in public sector tendering, where for the sake of objectivity, transparency, and fairness, it is required that the evaluation is conducted through a tender evaluation committee. Currently, in Nigeria, the public tendering process in general and the evaluation of tenders, in particular, are largely conducted using manual paper-based processes. Automating these manual-based processes to digital-based processes can help in enhancing the proficiency of public sector tendering in Nigeria. This paper is part of a larger study to develop an electronic tendering system that supports the whole tendering lifecycle based on Nigerian procurement law. Specifically, this paper presents the design and implementation of part of the system that supports group evaluation of tenders based on a technique called fuzzy multi-attributes group decision making. The system was developed using Object-Oriented methodologies and Unified Modelling Language and hypothetically applied in the evaluation of technical and financial proposals submitted by bidders. The system was validated by professionals with extensive experiences in public sector procurement. The results of the validation showed that the system called NPS-eTender has an average rating of 74% with respect to correct and accurate modelling of the existing manual tendering domain and an average rating of 67.6% with respect to its potential to enhance the proficiency of public sector tendering in Nigeria. Thus, based on the results of the validation, the automation of the evaluation process to support tender evaluation committee is achievable and can lead to a more proficient public sector tendering system.

Keywords: e-Tendering, e-Procurement, group decision making, tender evaluation, tender evaluation committee, UML, object-oriented methodologies, system development

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Authors: Thewodros K. Geberemariam

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The rapid physical expansion of urbanization coupled with aging infrastructure presents a unique decision and management challenges for many big city municipalities. Cities must therefore upgrade and maintain the existing aging urban drainage infrastructure systems to keep up with the demands. Given the overall contribution of assets to municipal revenue and the importance of infrastructure to the success of a livable city, many municipalities are currently looking for a robust and smart urban drainage infrastructure asset management solution that combines management, financial, engineering and technical practices. This robust decision-making shall rely on sound, complete, current and relevant data that enables asset valuation, impairment testing, lifecycle modeling, and forecasting across the multiple asset portfolios. On this paper, predictive computational intelligence (CI) and multi-class machine learning (ML) coupled with online, offline, and historical record data that are collected from an array of multi-parameter sensors are used for the extraction of different operational and non-conforming patterns hidden in structured and unstructured data to determine and produce actionable insight on the current and future states of the network. This paper aims to improve the strategic decision-making process by identifying all possible alternatives; evaluate the risk of each alternative, and choose the alternative most likely to attain the required goal in a cost-effective manner using historical and near real-time urban drainage infrastructure data for urban drainage infrastructures assets that have previously not benefited from computational intelligence and machine learning advancements.

Keywords: computational intelligence, machine learning, urban drainage infrastructure, machine learning, classification, prediction, asset management space

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Authors: Thanh Nguyen, Andrei Doncescu, Pierre Siegel

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Classification is an important data mining technique and could be used as data filtering in artificial intelligence. The broad application of classification for all kind of data leads to be used in nearly every field of our modern life. Classification helps us to put together different items according to the feature items decided as interesting and useful. In this paper, we compare two classification methods Naïve Bayes and ADTree use to detect spam e-mail. This choice is motivated by the fact that Naive Bayes algorithm is based on probability calculus while ADTree algorithm is based on decision tree. The parameter settings of the above classifiers use the maximization of true positive rate and minimization of false positive rate. The experiment results present classification accuracy and cost analysis in view of optimal classifier choice for Spam Detection. It is point out the number of attributes to obtain a tradeoff between number of them and the classification accuracy.

Keywords: classification, data mining, spam filtering, naive bayes, decision tree

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Authors: Ritsuko Kawasaki (Aiba), Takeshi Hiromatsu

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Management is required to understand all information security risks within an organization, and to make decisions on which information security risks should be treated in what level by allocating how much amount of cost. However, such decision-making is not usually easy, because various measures for risk treatment must be selected with the suitable application levels. In addition, some measures may have objectives conflicting with each other. It also makes the selection difficult. Moreover, risks generally have trends and it also should be considered in risk treatment. Therefore, this paper provides the extension of the model proposed in the previous study. The original model supports the selection of measures by applying a combination of weighted average method and goal programming method for multi-objective analysis to find an optimal solution. The extended model includes the notion of weights to the risks, and the larger weight means the priority of the risk.

Keywords: information security risk treatment, selection of risk measures, risk acceptance, multi-objective optimization

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Authors: Pei-Ru Yang, Yu-Chen Lin, Jia-Min Wu

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Background: A 58-year-old man with a history of osteoporosis and diabetes presented with chronic pain in his left knee due to severe knee joint degeneration. The knee replacement surgery was recommended by the doctor. But the patient suffered from low pain tolerance and wondered if virtual reality could relieve acute postoperative wound pain. Methods: We used the PICO (patient, intervention, comparison, and outcome) approach to generate indexed keywords and searched systematic review articles from 2017 to 2021 on the Cochran Library, PubMed, and Clinical Key databases. Results: The initial literature results included 38 articles, including 12 Cochrane library articles and 26 PubMed articles. One article was selected for further analysis after removing duplicates and off-topic articles. The eight trials included in this article were published between 2013 and 2019 and recruited a total of 723 participants. The studies, conducted in India, Lebanon, Iran, South Korea, Spain, and China, included adults who underwent hemorrhoidectomy, dental surgery, craniotomy or spine surgery, episiotomy repair, and knee surgery, with a mean age (24.1 ± 4.1 to 73.3 ± 6.5). Virtual reality is an emerging non-drug postoperative analgesia method. The findings showed that pain control was reduced by a mean of 1.48 points (95% CI: -2.02 to -0.95, p-value < 0.0001) in minor surgery and 0.32 points in major surgery (95% CI: -0.53 to -0.11, p-value < 0.03), and the overall postoperative satisfaction has improved. Discussion: Postoperative pain is a common clinical problem in surgical patients. Research has confirmed that virtual reality can create an immersive interactive environment, communicate with patients, and effectively relieve postoperative pain. However, virtual reality requires the purchase of hardware and software and other related computer equipment, and its high cost is a disadvantage. We selected the best literature based on clinical questions to answer the patient's question and used share decision making (SDM) to help the patient make decisions based on the clinical situation after knee replacement surgery to improve the quality of patient-centered care.

Keywords: knee replacement surgery, postoperative pain, share decision making, virtual reality

Procedia PDF Downloads 56