Search results for: charging decision

Authors: Wondmnew Derebe

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Increased adoption of modern beehives improves the livelihood of smallholder farmers whose income largely depends on mixed crop-livestock farming. Improved beehives have been disseminated to farmers in many parts of Ethiopia. However, its impact on income is less investigated. Thus, this study estimates how adopting improved beehives impacts rural households' income. Survey data were collected from 350 randomly selected households' and analyzed using an endogenous switching regression model. The result revealed that the adoption of improved beehives is associated with a higher annual income. On average, improved beehive adopters earned about 6,077 (ETB) more money than their counterparts. However, the impact of adoption would have been larger for actual non-adopters, as reflected in the negative transitional heterogeneity effect of 1792 (ETB). The result also indicated that the decision to adopt or not to adopt improved beehives was subjected to individual self-selection. Improved beehive adoption can increase farmers' income and can be used as an alternative poverty reduction strategy.

Keywords: impact, adoption, endogenous switching regression, income, improved

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Authors: Vasudev Das

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In a global survey of more than 5,000 participants in 99 territories, PwC found a loss of $42 billion through fraud in the last 24 months. The specific problem is that private and public organizational leaders often do not understand the importance of sonic therapeutic intervention in preventing financial fraud. The study aimed to explore sonic therapeutic intervention practitioners' lived experiences regarding the value of sonic therapeutic intervention in preventing financial fraud. The data collection methods were semi-structured interviews of purposeful samples and documentary reviews, which were analyzed thematically. Four themes emerged from the analysis of interview transcription data: Sonic therapeutic intervention enabled self-control, pro-spiritual values, consequentiality mindset, and post-conventional consciousness. The itemized four themes helped non-engagement in financial fraud. Implications for positive social change include enhanced financial fraud management, more significant financial leadership, and result-oriented decision-taking in the financial market. Also, the study results can improve the increased de-escalation of anxiety/stress associated with defrauding.

Keywords: consciousness, consequentiality, rehabilitation, reintegration

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Authors: Estela Díaz

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This article aims to make three contributions. First, build on the literature on ethical decision-making literature by exploring factors that influence the intention of adopting veganism. Second, study the superiority of extended models of the Theory of Planned Behavior (TPB) for understanding the process involved in forming the intention of adopting veganism. Third, analyze the moderating effect of gender on TPB given that attitudes and behavior towards animals are gender-sensitive. No study, to our knowledge, has examined these questions. Veganism is not a diet but a political and moral stand that exclude, for moral reasons, the use of animals. Although there is a growing interest in studying veganism, it continues being overlooked in empirical research, especially within the domain of social psychology. TPB has been widely used to study a broad range of human behaviors, including moral issues. Nonetheless, TPB has rarely been applied to examine ethical decisions about animals and, even less, to veganism. Hence, the validity of TPB in predicting the intention of adopting veganism remains unanswered. A total of 476 non-vegan Spanish university students (55.6% female; the mean age was 23.26 years, SD= 6.1) responded to online and pencil-and-paper self-reported questionnaire based on previous studies. TPB extended models incorporated two background factors: ‘general attitudes towards humanlike-attributes ascribed to animals’ (AHA) (capacity for reason/emotions/suffer, moral consideration, and affect-towards-animals); and ‘general attitudes towards 11 uses of animals’ (AUA). SPSS 22 and SmartPLS 3.0 were used for statistical analyses. This study constructed a second-order reflective-formative model and took the multi-group analysis (MGA) approach to study gender effects. Six models of TPB (the standard and five competing) were tested. No a priori hypotheses were formulated. The results gave partial support to TPB. Attitudes (ATTV) (β = .207, p < .001), subjective norms (SNV) (β = .323, p < .001), and perceived control behavior (PCB) (β = .149, p < .001) had a significant direct effect on intentions (INTV). This model accounted for 27,9% of the variance in intention (R2Adj = .275) and had a small predictive relevance (Q2 = .261). However, findings from this study reveal that contrary to what TPB generally proposes, the effect of the background factors on intentions was not fully mediated by the proximal constructs of intentions. For instance, in the final model (Model#6), both factors had significant multiple indirect effect on INTV (β = .074, 95% C = .030, .126 [AHA:INTV]; β = .101, 95% C = .055, .155 [AUA:INTV]) and significant direct effect on INTV (β = .175, p < .001 [AHA:INTV]; β = .100, p = .003 [AUA:INTV]). Furthermore, the addition of direct paths from background factors to intentions improved the explained variance in intention (R2 = .324; R2Adj = .317) and the predictive relevance (Q2 = .300) over the base-model. This supports existing literature on the superiority of enhanced TPB models to predict ethical issues; which suggests that moral behavior may add additional complexity to decision-making. Regarding gender effect, MGA showed that gender only moderated the influence of AHA on ATTV (e.g., βWomen−βMen = .296, p < .001 [Model #6]). However, other observed gender differences (e.g. the explained variance of the model for intentions were always higher for men that for women, for instance, R2Women = .298; R2Men = .394 [Model #6]) deserve further considerations, especially for developing more effective communication strategies.

Keywords: veganism, Theory of Planned Behavior, background factors, gender moderation

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Authors: Bronwen Wade

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Over the last half-century, child welfare systems have increasingly relied on quantitative risk assessment tools, such as actuarial or predictive risk tools. These tools are developed by performing statistical analysis of how attributes captured in administrative data are related to future child maltreatment. Some scholars argue that attributes in administrative data can serve as proxies for race and that quantitative risk assessment tools reify racial bias in decision-making. Others argue that these tools provide more “objective” and “scientific” guides for decision-making instead of subjective social worker judgment. This study performs a systematic review of the literature on the impact of quantitative risk assessment tools on racial disproportionality; it examines methodological biases in work on this topic, summarizes key findings, and provides suggestions for further work. A search of CINAHL, PsychInfo, Proquest Social Science Premium Collection, and the ProQuest Dissertations and Theses Collection was performed. Academic and grey literature were included. The review includes studies that use quasi-experimental methods and development, validation, or re-validation studies of quantitative risk assessment tools. PROBAST (Prediction model Risk of Bias Assessment Tool) and CHARMS (CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies) were used to assess the risk of bias and guide data extraction for risk development, validation, or re-validation studies. ROBINS-I (Risk of Bias in Non-Randomized Studies of Interventions) was used to assess for bias and guide data extraction for the quasi-experimental studies identified. Due to heterogeneity among papers, a meta-analysis was not feasible, and a narrative synthesis was conducted. 11 papers met the eligibility criteria, and each has an overall high risk of bias based on the PROBAST and ROBINS-I assessments. This is deeply concerning, as major policy decisions have been made based on a limited number of studies with a high risk of bias. The findings on racial disproportionality have been mixed and depend on the tool and approach used. Authors use various definitions for racial equity, fairness, or disproportionality. These concepts of statistical fairness are connected to theories about the reason for racial disproportionality in child welfare or social definitions of fairness that are usually not stated explicitly. Most findings from these studies are unreliable, given the high degree of bias. However, some of the less biased measures within studies suggest that quantitative risk assessment tools may worsen racial disproportionality, depending on how disproportionality is mathematically defined. Authors vary widely in their approach to defining and addressing racial disproportionality within studies, making it difficult to generalize findings or approaches across studies. This review demonstrates the power of authors to shape policy or discourse around racial justice based on their choice of statistical methods; it also demonstrates the need for improved rigor and transparency in studies of quantitative risk assessment tools. Finally, this review raises concerns about the impact that these tools have on child welfare systems and racial disproportionality.

Keywords: actuarial risk, child welfare, predictive risk, racial disproportionality

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Authors: Tomer Einat, Sharon Rabinovitz, Inbal Harel-Aviram

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This study explores men’s motivation and justification to remain married to their criminal, imprisoned wives. Using semi-structured interviews and content-analysis, data were collected and analyzed from eight men who maintain stable marriage relationships with their incarcerated wives. Participants are normative men who describe incarceration as a challenge that enhances mutual responsibility and commitment. They exaggerate the extent to which their partners resemble archetypal romantic ideals. They use motivational accounts to explain the woman’s criminal conduct, which is perceived as non-relevant to her real identity. Physical separation and lack of physical intimacy are perceived as the major difficulties in maintaining their marriage relations. Length of imprisonment and marriage was found to be related to the decision whether to continue or terminate the relationships. Women-inmates’ partners experience difficulties and use coping strategies very similar to those cited by other normative spouses facing lengthy separation.

Keywords: female inmates, marriage, normative spouses, romantic accounts

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Authors: B. Sudhakara Reddy

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This study provides a snapshot of the sustainability of selected Indian cities by employing 70 indicators in four dimensions to develop an overall city sustainability index. In recent years, the concept of ‘urban sustainability’ has become prominent due to its complexity. Urban areas propel growth and at the same time poses a lot of ecological, social and infrastructural problems and risks. In case of developing countries, the high population density of and the continuous in-migration run the highest risk in natural and man-made disasters. These issues combined with the inability of policy makers in providing basic services makes the cities unsustainable. To assess whether any given policy is moving towards or against urban sustainability it is necessary to consider the relationships among its various dimensions. Hence, in recent years, while preparing the sustainability index, an integral approach involving indicators of different dimensions such as ‘economic’, ‘environmental’ and 'social' is being used. It is also important for urban planners, social analysts and other related institutions to identify and understand the relationships in this complex system. The objective of the paper is to develop a city performance index (CPI) to measure and evaluate the urban regions in terms of sustainable performances. The objectives include: i) Objective assessment of a city’s performance, ii) setting achievable goals iii) prioritise relevant indicators for improvement, iv) learning from leaders, iv) assessment of the effectiveness of programmes that results in achieving high indicator values, v) Strengthening of stakeholder participation. Using the benchmark approach, a conceptual framework is developed for evaluating 25 Indian cities. We develop City Sustainability index (CSI) in order to rank cities according to their level of sustainability. The CSI is composed of four dimensions: Economic, Environment, Social, and Institutional. Each dimension is further composed of multiple indicators: (1) Economic that considers growth, access to electricity, and telephone availability; (2) environmental that includes waste water treatment, carbon emissions, (3) social that includes, equity, infant mortality, and 4) institutional that includes, voting share of population, urban regeneration policies. The CSI, consisting of four dimensions disaggregate into 12 categories and ultimately into 70 indicators. The data are obtained from public and non-governmental organizations, and also from city officials and experts. By ranking a sample of diverse cities on a set of specific dimensions the study can serve as a baseline of current conditions and a marker for referencing future results. The benchmarks and indices presented in the study provide a unique resource for the government and the city authorities to learn about the positive and negative attributes of a city and prepare plans for a sustainable urban development. As a result of our conceptual framework, the set of criteria we suggest is somewhat different to any already in the literature. The scope of our analysis is intended to be broad. Although illustrated with specific examples, it should be apparent that the principles identified are relevant to any monitoring that is used to inform decisions involving decision variables. These indicators are policy-relevant and, hence they are useful tool for decision-makers and researchers.

Keywords: benchmark, city, indicator, performance, sustainability

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Authors: Chiara Mansanta, Daniela Sani

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The present paper presents the further development of the application of a standard methodology to boost innovation inside real case studies of manufacturing companies. The proposed methodology provides a viable solution for manufacturing companies that have to evaluate new business ideas. The study underlined the concept of entrepreneurship and how a manager can use it to promote innovation inside their companies. Starting from a literature study on entrepreneurship, this paper examines the role of the manager in supporting a company’s development. The empirical part of the study is based on two manufacturing companies that used the proposed methodology to favour entrepreneurship through an alternative approach. The research demonstrated the need for companies to have a structured and well-defined methodology to achieve their goals. The purpose of this article is to understand the significance of business models inside companies and explore how they affect business strategy and innovation management. The idea is to use business models to support entrepreneurs in their decision-making processes, reducing risks and avoiding errors.

Keywords: entrepreneurship, manufacturing companies, solution validation, strategic management

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Authors: Mouataz Zreika, Maria Estela Varua

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Stock investment decisions are often made based on current events of the global economy and the analysis of historical data. Conversely, visual representation could assist investors’ gain deeper understanding and better insight on stock market trends more efficiently. The trend analysis is based on long-term data collection. The study adopts a hybrid method that combines the Clustering algorithm and Force-directed algorithm to overcome the scalability problem when visualizing large data. This method exemplifies the potential relationships between each stock, as well as determining the degree of strength and connectivity, which will provide investors another understanding of the stock relationship for reference. Information derived from visualization will also help them make an informed decision. The results of the experiments show that the proposed method is able to produced visualized data aesthetically by providing clearer views for connectivity and edge weights.

Keywords: clustering, force-directed, graph drawing, stock investment analysis

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Authors: Aquil Ahmed, Srikant Gupta, Irfan Ali

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In this paper, we study a multi-objective capacitated transportation problem (MOCTP) with mixed constraints. This paper is comprised of the modelling and optimisation of an MOCTP in a fuzzy environment in which some goals are fractional and some are linear. In real life application of the fuzzy goal programming (FGP) problem with multiple objectives, it is difficult for the decision maker(s) to determine the goal value of each objective precisely as the goal values are imprecise or uncertain. Also, we developed the concept of linearization of fractional goal for solving the MOCTP. In this paper, imprecision of the parameter is handled by the concept of fuzzy set theory by considering these parameters as a trapezoidal fuzzy number. α-cut approach is used to get the crisp value of the parameters. Numerical examples are used to illustrate the method for solving MOCTP.

Keywords: capacitated transportation problem, multi objective linear programming, multi-objective fractional programming, fuzzy goal programming, fuzzy sets, trapezoidal fuzzy number

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Authors: Emilia Segun-Ajao

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The strategy of relocation aimed at strengthening supply chain resilience in the United States is examined, taking into account recent global disturbances and vulnerabilities in offshore manufacturing. It explains the procurement challenges faced by enterprises and offers solutions to mitigate risks and improve resilience. Through the analysis of innovative approaches, including technological advances, policy considerations, and strategic frameworks, this study provides insights to decision-makers about the complexity of supply chain management. Reshoring has gained attention as a strategy to improve supply chain resilience in the face of global disruptions. This analysis focuses on the importance of relocating as a multifaceted approach to strengthening supply chains, advocating economic benefits, technological advances, and policy frameworks to create a more robust supply landscape in the United States.

Keywords: collaborative partnerships, supply chain resilience, procurement challenges, technology adoption

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Authors: Javier Sanchez Vidal, Ciarán Mac An Bhaird, Brian Lucey

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This study examines the decision by firm owners not to apply for intermediated debt due to a perception that their application will be rejected. Based on a sample of SMEs in 9 European countries over the period 2009-2011, we examine potential explanatory factors for borrower discouragement, including firm, macroeconomic, regulatory and banking industry variables. Compared with firms that applied for bank loans, discouraged borrowers are smaller, younger, have declining turnover and an increasing debt/assets ratio. Perceived willingness of banks to lend rather than the company’s own credit history is more important to encourage applications. Perceptions of refusal are procyclical and may be self-perpetuating. Increased concentration in the banking sector reduces discouragement, indicating the importance of relationship banking. Transmission of macro effects through the banking system and economic environment may also lead to higher levels of discouragement. A good regulatory scheme is also advisable, either for the lenders or the borrowers (overall the good ones).

Keywords: entrepreneurial finance, discouraged borrowers, banking, financial crisis, eurozone

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Authors: Mina Fawzy Ishak Gad Elsaid

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There is a strong link between technology and development. Architecture as a profession is a call to service and society. Maybe next to soldiers, engineers and patriots. However, unlike soldiers, they always remain employees of society under all circumstances. Despite the construction profession's role in society, there appears to be a lack of respect as some projects fail. This paper focuses on the need to improve development engineering performance in developing countries, using engineering education in Nigerian universities as a tool for discussion. A purposeful survey, interviews and focus group discussions were conducted on one hundred and twenty (120) prominent companies in Nigeria. The subject is approached through a large number of projects that companies have been involved in from the planning stage, some of which have been completed and even reached the maintenance and monitoring stage. It has been found that certain factors beyond the control of engineers are hindering the full development and success of the construction sector in developing countries. The main culprit is corruption and its eradication will put the country on a stable path to develop construction and combat poverty.

Keywords: decision analysis, industrial engineering, direct vs. indirect values, engineering management

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Authors: Haneen Joseph Habib Yeldoka

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There is a strong link between technology and development. Architecture as a profession is a call to service and society. Maybe next to soldiers, engineers and patriots. However, unlike soldiers, they always remain employees of society under all circumstances. Despite the construction profession's role in society, there appears to be a lack of respect as some projects fail. This paper focuses on the need to improve development engineering performance in developing countries, using engineering education in Nigerian universities as a tool for discussion. A purposeful survey, interviews and focus group discussions were conducted on one hundred and twenty (120) prominent companies in Nigeria. The subject is approached through a large number of projects that companies have been involved in from the planning stage, some of which have been completed and even reached the maintenance and monitoring stage. It has been found that certain factors beyond the control of engineers are hindering the full development and success of the construction sector in developing countries. The main culprit is corruption and its eradication will put the country on a stable path to develop construction and combat poverty.

Keywords: decision analysis, industrial engineering, direct vs. indirect values, engineering management

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Authors: Khachen Kongpakwattana, Nathorn Chaiyakunapruk

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Background: Decision-analytic models for Alzheimer’s disease (AD) have been advanced to discrete-event simulation (DES), in which individual-level modelling of disease progression across continuous severity spectra and incorporation of key parameters such as treatment persistence into the model become feasible. This study aimed to apply the DES to perform a cost-effectiveness analysis of treatment for AD in Thailand. Methods: A dataset of Thai patients with AD, representing unique demographic and clinical characteristics, was bootstrapped to generate a baseline cohort of patients. Each patient was cloned and assigned to donepezil, galantamine, rivastigmine, memantine or no treatment. Throughout the simulation period, the model randomly assigned each patient to discrete events including hospital visits, treatment discontinuation and death. Correlated changes in cognitive and behavioral status over time were developed using patient-level data. Treatment effects were obtained from the most recent network meta-analysis. Treatment persistence, mortality and predictive equations for functional status, costs (Thai baht (THB) in 2017) and quality-adjusted life year (QALY) were derived from country-specific real-world data. The time horizon was 10 years, with a discount rate of 3% per annum. Cost-effectiveness was evaluated based on the willingness-to-pay (WTP) threshold of 160,000 THB/QALY gained (4,994 US$/QALY gained) in Thailand. Results: Under a societal perspective, only was the prescription of donepezil to AD patients with all disease-severity levels found to be cost-effective. Compared to untreated patients, although the patients receiving donepezil incurred a discounted additional costs of 2,161 THB, they experienced a discounted gain in QALY of 0.021, resulting in an incremental cost-effectiveness ratio (ICER) of 138,524 THB/QALY (4,062 US$/QALY). Besides, providing early treatment with donepezil to mild AD patients further reduced the ICER to 61,652 THB/QALY (1,808 US$/QALY). However, the dominance of donepezil appeared to wane when delayed treatment was given to a subgroup of moderate and severe AD patients [ICER: 284,388 THB/QALY (8,340 US$/QALY)]. Introduction of a treatment stopping rule when the Mini-Mental State Exam (MMSE) score goes below 10 to a mild AD cohort did not deteriorate the cost-effectiveness of donepezil at the current treatment persistence level. On the other hand, none of the AD medications was cost-effective when being considered under a healthcare perspective. Conclusions: The DES greatly enhances real-world representativeness of decision-analytic models for AD. Under a societal perspective, treatment with donepezil improves patient’s quality of life and is considered cost-effective when used to treat AD patients with all disease-severity levels in Thailand. The optimal treatment benefits are observed when donepezil is prescribed since the early course of AD. With healthcare budget constraints in Thailand, the implementation of donepezil coverage may be most likely possible when being considered starting with mild AD patients, along with the stopping rule introduced.

Keywords: Alzheimer's disease, cost-effectiveness analysis, discrete event simulation, health technology assessment

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Authors: Mahasa Zahirnia

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The purpose of this paper is to explore new and effective ways of optimizing satellite images using artificial intelligence, and the process of implementing reinforcement learning to enhance the quality of data captured within the image. In our implementation of Bellman's Reinforcement Learning equations, associated state diagrams, and multi-stage image processing, we were able to enhance image quality, detect and define objects. Reinforcement learning is the differentiator in the area of artificial intelligence, and Q-Learning relies on trial and error to achieve its goals. The reward system that is embedded in Q-Learning allows the agent to self-evaluate its performance and decide on the best possible course of action based on the current and future environment. Results show that within a simulated environment, built on the images that are commercially available, the rate of detection was 40-90%. Reinforcement learning through Q-Learning algorithm is not just desired but required design criteria for image optimization and enhancements. The proposed methods presented are a cost effective method of resolving uncertainty of the data because reinforcement learning finds ideal policies to manage the process using a smaller sample of images.

Keywords: Q-learning, image optimization, reinforcement learning, Markov decision process

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Authors: Fadwa Chtioui

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Vital Pulp Therapy (VPT) is nowadays challenging the deep-rooted dogma of root canal treatment, being the only therapeutic option for permanent teeth diagnosed with irreversible pulpitis or carious pulp exposure. Histologic and clinical research has shown that compromised dental pulp can be treated without the full removal or excavation of all healthy pulp, and the outcome of the partial or full pulpotomy followed by a Tricalcium-Silicate-based dressing seems to show promising results in maintaining pulp vitality and preserving affected teeth in the long term. By reviewing recent advances in the techniques of VPT and their clinical effectiveness and safety in permanent teeth with irreversible Pulpitis, this work provides a new understanding of pulp pathophysiology and defense mechanisms and will reform dental practitioners' decision-making in treating irreversible pulpits from root canal therapy to vital pulp therapy by taking advantage of the biological effects of Tricalcium Silicate materials.

Keywords: irreversible pulpitis, vital pulp therapy, pulpotomy, Tricalcium Silicate

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Authors: Bogusław Schreyer

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The paper enquires on the two methods of the wheeled robot braking torque control. Those two methods are applied when the adhesion coefficient under left side wheels is different from the adhesion coefficient under the right side wheels. In case of the select-low (SL) method the braking torque on both wheels is controlled by the signals originating from the wheels on the side of the lower adhesion. In the select-high (SH) method the torque is controlled by the signals originating from the wheels on the side of the higher adhesion. The SL method is securing stable and secure robot behaviors during the braking process. However, the efficiency of this method is relatively low. The SH method is more efficient in terms of time and braking distance but in some situations may cause wheels blocking. It is important to monitor the velocity of all wheels and then take a decision about the braking torque distribution accordingly. In case of the SH method the braking torque slope may require significant decrease in order to avoid wheel blocking.

Keywords: select-high, select-low, torque distribution, wheeled robots

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Authors: Wassim Katerji, Mercedes Farjas, Carmen Morillo

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Terrain-Based Analysis results in derived products from an input DEM and these products are needed to perform various analyses. To efficiently use these products in decision-making, their accuracies must be estimated systematically. This paper proposes a procedure to assess the accuracy of these derived products, by calculating the accuracy of the slope dataset and its significance, taking as an input the accuracy of the DEM. Based on the output of previously published research on modeling the relative accuracy of a DEM, specifically ASTER and SRTM DEMs with Lebanon coverage as the area of study, analysis have showed that ASTER has a low significance in the majority of the area where only 2% of the modeled terrain has 50% or more significance. On the other hand, SRTM showed a better significance, where 37% of the modeled terrain has 50% or more significance. Statistical analysis deduced that the accuracy of the slope dataset, calculated on a cell-by-cell basis, is highly correlated to the accuracy of the input DEM. However, this correlation becomes lower between the slope accuracy and the slope significance, whereas it becomes much higher between the modeled slope and the slope significance.

Keywords: terrain-based analysis, slope, accuracy assessment, Digital Elevation Model (DEM)

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Authors: Andressa dos Santos Nicolau, João P. da S.C Algusto, Claudio Márcio do N. A. Pereira, Roberto Schirru

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In case of abnormal situations, the nuclear power plant (NPP) operators must follow written procedures to check the condition of the plant and to classify the type of emergency. In this paper, we proposed a Real Time Expert System in order to improve operator’s performance in case of transient or accident with reactor shutdown. The expert system’s knowledge is based on the sequence of events (SoE) of known accident and two emergency procedures of the Brazilian Pressurized Water Reactor (PWR) NPP and uses two kinds of knowledge representation: rule and logic trees. The results show that the system was able to classify the response of the automatic protection systems, as well as to evaluate the conditions of the plant, diagnosing the type of occurrence, recovery procedure to be followed, indicating the shutdown root cause, and classifying the emergency level.

Keywords: emergence procedure, expert system, operator support, PWR nuclear power plant

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Authors: Sylwia Frydrych, Jörg Prokop, Michał Buszko

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This study investigates the complex relationship between corporate ESG (Environmental, Social, Governance) performance and stock price risk within the European market context. By analyzing a dataset of 435 companies across 19 European countries, the research assesses the impact of both combined ESG performance and its individual components on various risk measures, including volatility, idiosyncratic risk, systematic risk, and downside risk. The findings reveal that while overall ESG scores do not significantly influence stock price risk, disaggregating the ESG components uncovers significant relationships. Governance practices are shown to consistently reduce market risk, positioning them as critical in risk management. However, environmental engagement tends to increase risk, particularly in times of regulatory shifts like those introduced in the EU post-2018. This research provides valuable insights for investors and corporate managers on the nuanced roles of ESG factors in financial risk, emphasizing the need for careful consideration of each ESG pillar in decision-making processes.

Keywords: ESG performance, ESG factors, ESG pillars, ESG scores

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Authors: L. S. Chathurika

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Early prediction of student performance is an important factor to be gained academic excellence. Whatever the study stream in secondary education, students lay the foundation for higher studies during the first year of their degree or diploma program in Sri Lanka. The information technology (IT) field has certain improvements in the education domain by selecting specialization areas to show the talents and skills of students. These specializations can be software engineering, network administration, database administration, multimedia design, etc. After completing the first-year, students attempt to select the best path by considering numerous factors. The purpose of this experiment is to predict the best study path using machine learning algorithms. Five classification algorithms: decision tree, support vector machine, artificial neural network, Naïve Bayes, and logistic regression are selected and tested. The support vector machine obtained the highest accuracy, 82.4%. Then affecting features are recognized to select the best study path.

Keywords: algorithm, classification, evaluation, features, testing, training

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Authors: H. Erbiyik, A. Bal, M. Sirakaya, Ö. Yesildal, E. Yolcu

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The emergence of many environmental issues began with the Industrial Revolution. The depletion of natural resources and emerging environmental challenges over time requires enterprises and managers to take into consideration environmental factors while managing business. If we take notice of these causes; the design and implementation of environmentally friendly green purchasing, production and waste management systems become very important at green logistics systems. Companies can adopt green supply chain with the awareness of these facts. The concept of green supply chain constitutes from green purchasing, green production, green logistics, waste management and reverse logistics. In this study, we wanted to identify the concept of green supply chain and why green supply chain should be applied. In the practice part of the study an analytic hierarchy process (AHP) study is conducted on an aluminum production company to evaluate suppliers.

Keywords: aluminum sector, analytic hierarchy process, decision making, green logistics

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Authors: Zofia Wlodarczyk

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I study the experiences of domestic violence survivors who flee their countries of origin in times of political conflict using insight and evidence from forty-five biographical interviews with female Chechen refugees and twelve refugee resettlement professionals in Poland. Both refugees and women are often described as having less agency—that is, they lack the power to decide to migrate – refugees less than economic migrants and women less than men. In this paper, I focus on how female refugees who have been victims of domestic violence make decisions about leaving their countries of origin during times of political conflict. I use several existing migration theories to trace how the migration experience of these women is shaped by dynamics at different levels of society: the macro level, the meso level and the micro level. At the macro level of analysis, I find that political conflict can be both a source of and an escape from domestic violence. Ongoing conflict can strengthen the patriarchal cultural norms, increase violence and constrain women’s choices when it comes to marriage. However, political conflict can also destabilize families and make pathways for women to escape. At the meso level I demonstrate that other political migrants and institutions that emerge due to politically triggered migration can guide those fleeing domestic violence. Finally, at the micro level, I show that family dynamics often force domestic abuse survivors to make their decision to escape alone or with the support of only the most trusted female relatives. Taken together, my analyses show that we cannot look solely at one level of society when describing decision-making processes of women fleeing domestic violence. Conflict-related micro, meso and macro forces interact with and influence each other: on the one hand, strengthening an abusive trap, and on the other hand, opening a door to escape. This study builds upon several theoretical and empirical debates. First, it expands theories of migration by incorporating both refugee and gender perspectives. Few social scientists have used the migration theory framework to discuss the unique circumstances of refugee flows. Those who have mainly focus on “political” migrants, a designation that frequently fails to account for gender, does not incorporate individuals fleeing gender-based violence, including domestic-violence victims. The study also enriches migration scholarship, typically focused on the US and Western-European context, with research from Eastern Europe and Caucasus. Moreover, it contributes to the literature on the changing roles of gender in the context of migration. I argue that understanding how gender roles and hierarchies influence the pre-migration stage of female refugees is crucial, as it may have implications for policy-making efforts in host countries that recognize the asylum claims of those fleeing domestic violence. This study also engages in debates about asylum and refugee law. Domestic violence is normatively and often legally considered an individual-level problem whereas political persecution is recognized as a structural or societal level issue. My study challenges these notions by showing how the migration triggered by domestic violence is closely intertwined with politically motivated refuge.

Keywords: AGENCY, DOMESTIC VIOLENCE, FEMALE REFUGEES, POLITICAL REFUGE, SOCIAL NETWORKS

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Authors: Hilya Mudrika Arini, Nur Aini Masruroh, Budi Hartono

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There are more than 20 terrorist threats from 2002 to 2012 in Indonesia. Despite of this fact, preventive solution through studies in the field of national security in Indonesia has not been conducted comprehensively. This study aims to provide a preventive solution by developing prediction model of the terrorist threat in Indonesia by using Bayesian network. There are eight stages to build the model, started from literature review, build and verify Bayesian belief network to what-if scenario. In order to build the model, four experts from different perspectives are utilized. This study finds several significant findings. First, news and the readiness of terrorist group are the most influent factor. Second, according to several scenarios of the news portion, it can be concluded that the higher positive news proportion, the higher probability of terrorist threat will occur. Therefore, the preventive solution to reduce the terrorist threat in Indonesia based on the model is by keeping the positive news portion to a maximum of 38%.

Keywords: Bayesian network, decision analysis, national security system, text mining

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Authors: Moustafa Osman

Abstract:

The paper describes and analyses different good practice examples of protective levels, and initiatives actions (“framework conditions”) and encourages the uptake of environmental management systems (EMSs) to small and medium-sized enterprises (SMEs). Most of industries tend to take EMS as tools leading towards sustainability planning. The application of these tools has numerous environmental obligations that neither suggests decision nor recommends what a company should achieve ultimately. These set up clearly defined criteria to evaluate environmental protective action (EEPA) into sustainability indicators. The physical integration will evaluate how to incorporate traditional knowledge into baseline information, preparing impact prediction, and planning mitigation measures in monitoring conditions. Thereby efforts between the government, industry and community led protective action to concern with present needs for future generations, meeting the goal of sustainable development. The paper discusses how to set out distinct aspects of sustainable indicators and reflects inputs, outputs, and modes of impact on the environment.

Keywords: environmental management, sustainability, indicators, protective action

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Authors: Mahsa Pishdar

Abstract:

Food traceability through the supply chain is facing increased demand. IoT and blockchain are among the tools under consideration in the Industry 4.0 era that could be integrated to help implementation of the Circular Economy (CE) principles while enhancing food traceability solutions. However, such tools need intellectual system, and infrastructureto be settled as guidance through the way, helping overcoming obstacles. That is why the critical success factors for implementing Industry 4.0 and circular economy principles in food traceability concept are analyzed in this paper by combination of interval type 2 fuzzy Worst Best Method and Measurement Alternatives and Ranking according to Compromise Solution (Interval Type 2 fuzzy WBM-MARCOS). Results indicate that “Knowledge of Industry 4.0 obligations and CE principle” is the most important factor that is the basis of success following by “Management commitment and support”. This will assist decision makers to seize success in gaining a competitive advantage while reducing costs through the supply chain.

Keywords: food traceability, industry 4.0, internet of things, block chain, best worst method, marcos

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Authors: Javad Jozaei, Rob G. Bell, Paula Blackett, Scott A. Stephens

Abstract:

In the last few decades, Social Vulnerability Assessment (SVA) has been a favoured means in evaluating the susceptibility of social systems to drivers of change, including climate change and natural disasters. However, the application of SVA to inform responsive and practical strategies to deal with uncertain climate change impacts has always been challenging, and typically agencies resort back to conventional risk/vulnerability assessment. These challenges include complex nature of social vulnerability concepts which influence its applicability, complications in identifying and measuring social vulnerability determinants, the transitory social dynamics in a changing environment, and unpredictability of the scenarios of change that impacts the regime of vulnerability (including contention of when these impacts might emerge). Research suggests that the conventional quantitative approaches in SVA could not appropriately address these problems; hence, the outcomes could potentially be misleading and not fit for addressing the ongoing uncertain rise in risk. The second phase of New Zealand’s Resilience to Nature’s Challenges (RNC2) is developing a forward-looking vulnerability assessment framework and methodology that informs the decision-making and policy development in dealing with the changing coastal systems and accounts for complex dynamics of New Zealand’s coastal systems (including socio-economic, environmental and cultural). Also, RNC2 requires the new methodology to consider plausible drivers of incremental and unknowable changes, create mechanisms to enhance social and community resilience; and fits the New Zealand’s multi-layer governance system. This paper aims to analyse the conventional approaches and methodologies in SVA and offer recommendations for more responsive approaches that inform adaptive decision-making and policy development in practice. The research adopts a qualitative research design to examine different aspects of the conventional SVA processes, and the methods to achieve the research objectives include a systematic review of the literature and case study methods. We found that the conventional quantitative, reductionist and deterministic mindset in the SVA processes -with a focus the impacts of rapid stressors (i.e. tsunamis, floods)- show some deficiencies to account for complex dynamics of social-ecological systems (SES), and the uncertain, long-term impacts of incremental drivers. The paper will focus on addressing the links between resilience and vulnerability; and suggests how resilience theory and its underpinning notions such as the adaptive cycle, panarchy, and system transformability could address these issues, therefore, influence the perception of vulnerability regime and its assessment processes. In this regard, it will be argued that how a shift of paradigm from ‘specific resilience’, which focuses on adaptive capacity associated with the notion of ‘bouncing back’, to ‘general resilience’, which accounts for system transformability, regime shift, ‘bouncing forward’, can deliver more effective strategies in an era characterised by ongoing change and deep uncertainty.

Keywords: complexity, social vulnerability, resilience, transformation, uncertain risks

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Authors: Arati Siddharth Petkar, Joel E. M. Macwan

Abstract:

Preferences for residential location are of a diverse nature. Primarily they are based on the socio-economic, socio-cultural, socio-demographic characteristics of the household. It also depends on character, and the growth potential of different areas in a city. In the present study, various criteria affecting residential location preferences from the Urban Dwellers’ perspective have been analyzed. The household survey has been conducted in two parts: Existing Buyers’ survey and Future Buyers’ survey. The analysis reveals that workplace location is the most governing criterion in deciding residential location from the majority of the urban dwellers perspective. For analyzing the importance of varied criteria, Analytical Hierarchy Process approach has been explored. The suggested approach will be helpful for urban planners, decision makers and developers, while designating a new residential area or redeveloping an existing one.

Keywords: analytical hierarchy process (AHP), household, preferences, residential location preferences, residential land use, urban dwellers

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Authors: Mais Khader, Xingjie Wei

Abstract:

This research sheds light on female entrepreneurs by providing new insights on the survival predictions of companies led by females in the UK. This study aims to build a predictive machine learning model of the survival of female-led & co-led small & medium enterprises (SMEs) in the UK over the period 2000-2020. The predictive model built utilised a combination of financial and non-financial features related to both companies and their directors to predict SMEs' survival. These features were studied in terms of their contribution to the resultant predictive model. Five machine learning models are used in the modelling: Decision tree, AdaBoost, Naïve Bayes, Logistic regression and SVM. The AdaBoost model had the highest performance of the five models, with an accuracy of 73% and an AUC of 80%. The results show high feature importance in predicting companies' survival for company size, management experience, financial performance, industry, region, and females' percentage in management.

Keywords: company survival, entrepreneurship, females, machine learning, SMEs

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Authors: Yang Zhang, Jian He

Abstract:

Heart disease is one of the leading causes of death in the world, and coronary heart disease (CHD) is one of the major heart diseases. Electrocardiogram (ECG) is widely used in the detection of heart diseases, but the traditional manual method for CHD prediction by analyzing ECG requires lots of professional knowledge for doctors. This paper introduces sliding window and continuous wavelet transform (CWT) to transform ECG signals into images, and then ResNet and Bi-LSTM are introduced to build the ECG feature extraction network (namely ECGNet). At last, an auxiliary system for coronary heart disease prediction was developed based on modified ResNet18 and Bi-LSTM, and the public ECG dataset of CHD from MIMIC-3 was used to train and test the system. The experimental results show that the accuracy of the method is 83%, and the F1-score is 83%. Compared with the available methods for CHD prediction based on ECG, such as kNN, decision tree, VGGNet, etc., this method not only improves the prediction accuracy but also could avoid the degradation phenomenon of the deep learning network.

Keywords: Bi-LSTM, CHD, ECG, ResNet, sliding window

Procedia PDF Downloads 89