Search results for: administrative decisions

Authors: Elaine Wong Yee-Sing, Liaw Wee Tong

Abstract:

Rapid transformations in demographic and socioeconomic shifts are leading to a growing global demand for health and beauty products and services that demands holistic concepts of well-being. In addition, technological breakthroughs such as internet of things make it convenient and offer innovative solutions for well-being and engage consumers to track their own health conditions and fitness goals. This 'new health economy' encompasses three key concepts: well-being, well-conditioned and well-shaped; which are shaped by wellness segments and goals that influence purchasing decisions of consumers. The research protocol aims to examine the feasibility, challenges, and capabilities in provision for each customer with an ecosystem, or platform, that organizes data and insights to create an individual health and fitness, nutrition, and beauty profile. Convenience sampling of 100 consumers residing in private housing within five major districts in Singapore will be selected to participate in the study. Statistical Package for Social Science 25 will be used to conduct descriptive statistics for quantitative data while qualitative data results using focus interviews, will be translated and transcribed to identify improvements in provision of these services. Rising income in emerging global markets is fuelling the demand for these general wellbeing products and services. Combined with technological advances, it is imperative to understand how these highly personalized services with integrated technology can be designed better to support consumer preferences; provide greater flexibility and high-quality service, and generate better health awareness among consumers.

Keywords: beauty, consumers, health, technology, wellness

Procedia PDF Downloads 129

Authors: Meriem Bahij, Ahmed Nafidi, Boujemâa Achchab, Sílvio M. A. Gama, José A. O. Matos

Abstract:

Stochastic modeling concerns the use of probability to model real-world situations in which uncertainty is present. Therefore, the purpose of stochastic modeling is to estimate the probability of outcomes within a forecast, i.e. to be able to predict what conditions or decisions might happen under different situations. In the present study, we present a model of a stochastic diffusion process based on the bi-Weibull distribution function (its trend is proportional to the bi-Weibull probability density function). In general, the Weibull distribution has the ability to assume the characteristics of many different types of distributions. This has made it very popular among engineers and quality practitioners, who have considered it the most commonly used distribution for studying problems such as modeling reliability data, accelerated life testing, and maintainability modeling and analysis. In this work, we start by obtaining the probabilistic characteristics of this model, as the explicit expression of the process, its trends, and its distribution by transforming the diffusion process in a Wiener process as shown in the Ricciaardi theorem. Then, we develop the statistical inference of this model using the maximum likelihood methodology. Finally, we analyse with simulated data the computational problems associated with the parameters, an issue of great importance in its application to real data with the use of the convergence analysis methods. Overall, the use of a stochastic model reflects only a pragmatic decision on the part of the modeler. According to the data that is available and the universe of models known to the modeler, this model represents the best currently available description of the phenomenon under consideration.

Keywords: diffusion process, discrete sampling, likelihood estimation method, simulation, stochastic diffusion process, trends functions, bi-parameters weibull density function

Procedia PDF Downloads 308

Authors: Elham Taghizadeh, Mostafa Abedzadeh, Mostafa Setak

Abstract:

Logistics network is expected that opened facilities work continuously for a long time horizon without any failure; but in real world problems, facilities may face disruptions. This paper studies a reliable joint inventory location problem to optimize cost of facility locations, customers’ assignment, and inventory management decisions when facilities face failure risks and doesn’t work. In our model we assume when a facility is out of work, its customers may be reassigned to other operational facilities otherwise they must endure high penalty costs associated with losing service. For defining the model closer to real world problems, the model is proposed based on p-median problem and the facilities are considered to have limited capacities. We define a new binary variable (Z_is) for showing that customers are not assigned to any facilities. Our problem involve a bi-objective model; the first one minimizes the sum of facility construction costs and expected inventory holding costs, the second one function that mention for the first one is minimizes maximum expected customer costs under normal and failure scenarios. For solving this model we use NSGAII and MOSS algorithms have been applied to find the pareto- archive solution. Also Response Surface Methodology (RSM) is applied for optimizing the NSGAII Algorithm Parameters. We compare performance of two algorithms with three metrics and the results show NSGAII is more suitable for our model.

Keywords: joint inventory-location problem, facility location, NSGAII, MOSS

Procedia PDF Downloads 525

Authors: Eda Orhun

Abstract:

Purpose: This paper analyzes a target firm’s decision to voluntarily disclose information during a takeover event and the effect of such disclosures on the outcome of the takeover. Such voluntary disclosures especially in the form of earnings forecasts made around takeover events may affect shareholders’ decisions about the target firm’s value and in return takeover result. This study aims to shed light on this question. Design/methodology/approach: The paper tries to understand the role of voluntary disclosures by target firms during a takeover event in the likelihood of takeover success both theoretically and empirically. A game-theoretical model is set up to analyze the voluntary disclosure decision of a target firm to inform the shareholders about its real worth. The empirical implication of model is tested by employing binary outcome models where the disclosure variable is obtained by identifying the target firms in the sample that provide positive news by issuing increasing management earnings forecasts. Findings: The model predicts that a voluntary disclosure of positive information by the target decreases the likelihood that the takeover succeeds. The empirical analysis confirms this prediction by showing that positive earnings forecasts by target firms during takeover events increase the probability of takeover failure. Overall, it is shown that information dissemination through voluntary disclosures by target firms is an important factor affecting takeover outcomes. Originality/Value: This study is the first to the author's knowledge that studies the impact of voluntary disclosures by the target firm during a takeover event on the likelihood of takeover success. The results contribute to information economics, corporate finance and M&As literatures.

Keywords: takeovers, target firm, voluntary disclosures, earnings forecasts, takeover success

Procedia PDF Downloads 318

Authors: Masood Karamoozian, Zhang Hong

Abstract:

The necessity and complexity of the decision-making process and the interference of the various factors to make decisions and consider all the relevant factors in a problem are very obvious nowadays. Hence, researchers show their interest in multi-criteria decision-making methods. In this research, the Analytical Hierarchy Process (AHP), Simple Additive Weighting (SAW), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods of multi-criteria decision-making have been used to solve the problem of optimal construction systems. Systems being evaluated in this problem include; Light Steel Frames (LSF), a case study of designs by Zhang Hong studio in the Southeast University of Nanjing, Insulating Concrete Form (ICF), Ordinary Construction System (OCS), and Prefabricated Concrete System (PRCS) as another case study designs in Zhang Hong studio in the Southeast University of Nanjing. Crowdsourcing was done by using a questionnaire at the sample level (200 people). Questionnaires were distributed among experts, university centers, and conferences. According to the results of the research, the use of different methods of decision-making led to relatively the same results. In this way, with the use of all three multi-criteria decision-making methods mentioned above, the Prefabricated Concrete System (PRCS) was in the first rank, and the Light Steel Frame (LSF) system ranked second. Also, the Prefabricated Concrete System (PRCS), in terms of performance standards and economics, was ranked first, and the Light Steel Frame (LSF) system was allocated the first rank in terms of environmental standards.

Keywords: multi-criteria decision making, AHP, SAW, TOPSIS

Procedia PDF Downloads 110

Authors: Mohammad Mehdi Mohebi, Nima Kazempour, Mohammad Naeim Kazempour

Abstract:

Strategic thinking enables managers to find out what factors are effective in achieving the desired goals and how these factors create value for the customer. Strategic thinking can be interpreted as a form of mental and inner strength in the manager, who by utilizing it, while considering the conditions of the environment and unstable global environment changes, takes decisions, and plans actions, and designs the strategy of his organization in today's changing and unsustainable business environment. Strategic thinking is very important in today’s business world, because without this thinking, the organization's efforts to achieve developed strategies will not be effective. In this study, through a detailed study of the challenges and barriers to strategic thinking that is carried out by various scholars and experts theoretically and experimentally, 7 major factors were identified. Then, based on these main factors of challenges and related elements, a tool in the form of a questionnaire was developed in order to determine their importance and priority from the perspective of strategic management experts. Using statistical tests the reliability and validity of this instrument, including its structural validity, has been examined and approved using factor analysis. These factors are weighted and prioritized using AHP techniques and the opinions of scholars and experts. Prioritization of barriers to strategic thinking include: lack of participatory management, lack of a systematic approach, difficulty in aligning the organization members, lack of incentive organizational culture, behavioural and internal barriers of managers, lack of key managers and lack of access to timely and accurate information.

Keywords: strategic thinking, challenges and barriers to strategic thinking, EN bank, AHP method

Procedia PDF Downloads 546

Authors: Mane Darbinyan, Lusine Hayrapetyan, Elen Matevosyan

Abstract:

Artificial Intelligence in Education (AIED) has been created to help students get ready for the workforce, and over the past 25 years, it has grown significantly, offering a variety of technologies to support academic, institutional, and administrative services. However, this is still challenging, especially considering the labor market's rapid change. While choosing a career, people face various obstacles because they do not take into consideration their own preferences, which might lead to many other problems like shifting jobs, work stress, occupational infirmity, reduced productivity, and manual error. Besides preferences, people should properly evaluate their technical and non-technical skills, as well as their personalities. Professional counseling has become a difficult undertaking for counselors due to the wide range of career choices brought on by changing technological trends. It is necessary to close this gap by utilizing technology that makes sophisticated predictions about a person's career goals based on their personality. Hence, there is a need to create an automated model that would help in decision-making based on user inputs. Improving career guidance can be achieved by embedding machine learning into the career consulting ecosystem. There are various systems of career guidance that work based on the same logic, such as the classification of applicants, matching applications with appropriate departments or jobs, making predictions, and providing suitable recommendations. Methodologies like KNN, Neural Networks, K-means clustering, D-Tree, and many other advanced algorithms are applied in the fields of data and compute some data, which is helpful to predict the right careers. Besides helping users with their career choice, these systems provide numerous opportunities which are very useful while making this hard decision. They help the candidate to recognize where he/she specifically lacks sufficient skills so that the candidate can improve those skills. They are also capable to offer an e-learning platform, taking into account the user's lack of knowledge. Furthermore, users can be provided with details on a particular job, such as the abilities required to excel in that industry.

Keywords: career guidance system, machine learning, career prediction, predictive decision, data mining, technical and non-technical skills

Procedia PDF Downloads 80

Authors: Aschenaki Zerihun Kea, Bernt Lindtjorn, Achamyelesh Gebretsadik, Sven Gudmund Hinderaker

Abstract:

Introduction: Maternal mortality studies conducted at the national level do not provide the information needed for planning and monitoring health programs at lower administrative levels. The aim of this study was to measure maternal mortality, identify risk factors and district-level variations in Sidama National Regional State, southern Ethiopia. Methods: A cross sectional population-based survey was carried out in households where women reported pregnancy and birth outcomes in the past five years. The study was conducted in the Sidama National Regional State, southern Ethiopia, from July 2019 to May 2020. Multi-stage cluster sampling technique was employed. The outcome variable of the study was maternal mortality. Complex sample logistic regression analysis was applied to assess variables independently associated with maternal mortality. Results: We registered 10602 live births (LB) and 48 maternal deaths, yielding an overall maternal mortality ratio (MMR) of 419; 95% CI: 260-577 per 100,000 LB. Aroresa district had the highest MMR with 1142 (95% CI: 693-1591) per 100,000 LB. Leading causes of death were haemorrhage 21 (41%) and eclampsia 10 (27%). Thirty (59%) mothers died during labour, or within 24 hours after delivery, 25 (47%) died at home and 17 (38%) at a health facility. Mothers who did not have formal education had a higher risk of maternal death (AOR: 4.4; 95% CI: 1.7 – 11.0). The risk of maternal death was higher in districts with a low midwife-to-population ratio (AOR: 2.9; 95% CI: 1.0-8.9). Conclusion: The high maternal mortality with district-level variations in Sidama Region highlights the importance of improving obstetric care and employing targeted interventions in areas with high mortality rates. Due attention should be given to improving access to female education. Additional midwives have to be trained and deployed to improve maternal health services and consequently save the lives of mothers.

Keywords: maternal mortality variation, maternal death, Sidama, Ethiopia

Procedia PDF Downloads 72

Authors: Chuks Odiegwu-Enwerem

Abstract:

The classical notion of opinion leadership presupposes that the media is at the center of an effective and successful opinion leadership. Under this idea, an opinion leader is an active media user who consumes, understands, digests and interprets the messages for the understanding and acceptance/adoption by lower-end media users – whose access and understanding of media content are supposedly low. Because of their unique access to and presumed understanding of media functions and their content, opinion leaders are typically esteemed by those who look forward to and accept their opinions. Lazarsfeld and Katz’s two-step flow of communication theory is the basis of opinion leadership – propelled by limited access to the media. With the emergence and spread of social media and its unlimited access by all and sundry, however, the study interrogates the relevance and application of opinion leaders and, by implication, the two-step flow communication theory in Nigeria’s Northcentral region. It seeks to determine whether opinion leaders still exist in the picture and if they still exert considerable influence, especially in matters of political conversations and decision-making among the citizens of this area. It further explores whether the diffusion of social media is a reality and how the ‘low-end’ media users react to the new-found freedom of access to media, and how they are using it to inform their decisions on important matters as well as examines if they are still glued to their opinion leaders. This study explores the empirical dimensions of the two-step flow hypothesis in relation to the activities of social media to determine if a change has occurred and in what direction, using mixed methos of Survey and in-depth interviews. Our understanding and belief in some theoretical assumptions may be enhanced or challenged by the study outcome.

Keywords: Opinion Leadership, Active Media User, Two-Step-Flow, Social media, Northcentral Nigeria

Procedia PDF Downloads 70

Authors: Mane Darbinyan, Lusine Hayrapetyan, Elen Matevosyan

Abstract:

Artificial Intelligence in Education (AIED) has been created to help students get ready for the workforce, and over the past 25 years, it has grown significantly, offering a variety of technologies to support academic, institutional, and administrative services. However, this is still challenging, especially considering the labor market's rapid change. While choosing a career, people face various obstacles because they do not take into consideration their own preferences, which might lead to many other problems like shifting jobs, work stress, occupational infirmity, reduced productivity, and manual error. Besides preferences, people should evaluate properly their technical and non-technical skills, as well as their personalities. Professional counseling has become a difficult undertaking for counselors due to the wide range of career choices brought on by changing technological trends. It is necessary to close this gap by utilizing technology that makes sophisticated predictions about a person's career goals based on their personality. Hence, there is a need to create an automated model that would help in decision-making based on user inputs. Improving career guidance can be achieved by embedding machine learning into the career consulting ecosystem. There are various systems of career guidance that work based on the same logic, such as the classification of applicants, matching applications with appropriate departments or jobs, making predictions, and providing suitable recommendations. Methodologies like KNN, neural networks, K-means clustering, D-Tree, and many other advanced algorithms are applied in the fields of data and compute some data, which is helpful to predict the right careers. Besides helping users with their career choice, these systems provide numerous opportunities which are very useful while making this hard decision. They help the candidate to recognize where he/she specifically lacks sufficient skills so that the candidate can improve those skills. They are also capable of offering an e-learning platform, taking into account the user's lack of knowledge. Furthermore, users can be provided with details on a particular job, such as the abilities required to excel in that industry.

Keywords: career guidance system, machine learning, career prediction, predictive decision, data mining, technical and non-technical skills

Procedia PDF Downloads 70

Authors: Lisa M. Coleman

Abstract:

The focus on disability, LGBTQ+, and internationalization has certainly been the subject of much research and programmatic across higher education. Many universities have entered into global partnerships with varying success and challenges across the various areas, including laws and policies. Attentiveness to the specific nuances of global inclusion, diversity, equity, belonging, and access (GIDBEA) and the leadership to support these efforts is crucial to the development of longstanding success across the programs. There have been a number of shifts related to diversification across student and alumni bodies. These shifts include but are not limited to how people identify gender, race, and sexuality (and the intersections across such identities), as well as trends across emerging and diverse disability communities. NYU is the most international campus in the United States, with the most campuses and sites outside of its county of origin and the most international students and exchange programs than any other university. As a result, the ongoing work related to GIDEBA is at the center of much of the leadership, administrative, and research efforts. Climate assessment work across NYU’s diverse global campus landscape will serve as the foundation to exemplify best practices related to data collection and dissemination, community and stakeholder engagement, and effective implementation of innovative strategies to close gap areas as identified. The data (quantitative and qualitative) and related research findings represent data collected from close to 22,000 stakeholders across the NYU campuses. The case study centers on specific methodological considerations, data integrity, stakeholder engagement from across student-faculty, staff, and alumni constituencies, and tactics to advance specific GIDBEA initiatives related to navigating shifting landscapes. Design thinking, incubation, and co-creation strategies have been employed to expand, leverage, actualize, and implement GIDBEA strategies that are – concrete, measurable, differentiated, and specific to global sites and regions and emerging trends.

Keywords: disability, LGBTQ+, DEI, research, case studies

Procedia PDF Downloads 105

Authors: E. Asadollahi-Yazdi, J. Gardan, P. Lafon

Abstract:

Nowadays, manufactures are encountered with production of different version of products due to quality, cost and time constraints. On the other hand, Additive Manufacturing (AM) as a production method based on CAD model disrupts the design and manufacturing cycle with new parameters. To consider these issues, the researchers utilized Design For Manufacturing (DFM) approach for AM but until now there is no integrated approach for design and manufacturing of product through the AM. So, this paper aims to provide a general methodology for managing the different production issues, as well as, support the interoperability with AM process and different Product Life Cycle Management tools. The problem is that the models of System Engineering which is used for managing complex systems cannot support the product evolution and its impact on the product life cycle. Therefore, it seems necessary to provide a general methodology for managing the product’s diversities which is created by using AM. This methodology must consider manufacture and assembly during product design as early as possible in the design stage. The latest approach of DFM, as a methodology to analyze the system comprehensively, integrates manufacturing constraints in the numerical model in upstream. So, DFM for AM is used to import the characteristics of AM into the design and manufacturing process of a hybrid product to manage the criteria coming from AM. Also, the research presents an integrated design method in order to take into account the knowledge of layers manufacturing technologies. For this purpose, the interface model based on the skin and skeleton concepts is provided, the usage and manufacturing skins are used to show the functional surface of the product. Also, the material flow and link between the skins are demonstrated by usage and manufacturing skeletons. Therefore, this integrated approach is a helpful methodology for designer and manufacturer in different decisions like material and process selection as well as, evaluation of product manufacturability.

Keywords: additive manufacturing, 3D printing, design for manufacturing, integrated design, interoperability

Procedia PDF Downloads 316

Authors: Latifa Alenezi, Liz Croot, Janet Harris

Abstract:

Chronic Low Back Pain (CLBP) is one of the most common and recurrent musculoskeletal problems that causes patients to access health care services frequently. The Bio-psychosocial Model emphasises that psychological, behavioural and social factors contribute to the development and persistence of CLBP. Cognitive behavioural therapy (CBT) is a psychological pain management strategy that can be used by physiotherapists treating chronic low back pain. However, evidence of the effectiveness of CBT for CLBP varies between different studies. The proposed study was preceded by a mixed methods systematic review that found that CBT has a beneficial effect for CLBP patients when compared to waiting list or other treatments; however, there is variation in effectiveness across different settings. Little is known about how CBT is applied by physiotherapists in physiotherapy settings. The interest of this study is directed towards generating an explanation and understanding of why, when, and how some physiotherapists make decisions and choose to apply CBT for CLBP patients, whereas others do not. Also, how and for what type of CLBP patients does CBT work, and for whom might CBT not work? Therefore, the study will take a qualitative approach to explore CLBP patients’, physiotherapists’ and managers’ perceptions of CBT and how it is used in physiotherapy to enable a deeper understanding and richer explanation of CBT effectiveness and help to inform research and practice. The study will use grounded theory approach to generate an explanatory theory of the clinical application of CBT for CLBP in physiotherapy settings. Physiotherapists, patients and managers of physiotherapy services will be interviewed. Grounded theory techniques will be used to analyse the data. The presentation will describe findings from the interviews and the emerging theory. This research will help to further inform RCTs about the effectiveness of CBT for CLBP in physiotherapy.

Keywords: CBT, CLBP, perception, physiotherapy, theory

Procedia PDF Downloads 233

Authors: Tajinder Pal Singh

Abstract:

Teaching of mathematics to engineering students is an open ended problem in education. The main goal of mathematics learning for engineering students is the ability of applying a wide range of mathematical techniques and skills in their engineering classes and later in their professional work. Most of the undergraduate engineering students and faculties feels that no efforts and attempts are made to demonstrate the applicability of various topics of mathematics that are taught thus making mathematics unavoidable for some engineering faculty and their students. The lack of understanding of concepts in engineering mathematics may hinder the understanding of other concepts or even subjects. However, for most undergraduate engineering students, mathematics is one of the most difficult courses in their field of study. Most of the engineering students never understood mathematics or they never liked it because it was too abstract for them and they could never relate to it. A right balance of application and concept based teaching can only fulfill the objectives of teaching mathematics to engineering students. It will surely improve and enhance their problem solving and creative thinking skills. In this paper, some practical (informal) ways of making mathematics-teaching application based for the engineering students is discussed. An attempt is made to understand the present state of teaching mathematics in engineering colleges. The weaknesses and strengths of the current teaching approach are elaborated. Some of the causes of unpopularity of mathematics subject are analyzed and a few pragmatic suggestions have been made. Faculty in mathematics courses should spend more time discussing the applications as well as the conceptual underpinnings rather than focus solely on strategies and techniques to solve problems. They should also introduce more ‘word’ problems as these problems are commonly encountered in engineering courses. Overspecialization in engineering education should not occur at the expense of (or by diluting) mathematics and basic sciences. The role of engineering education is to provide the fundamental (basic) knowledge and to teach the students simple methodology of self-learning and self-development. All these issues would be better addressed if mathematics and engineering faculty join hands together to plan and design the learning experiences for the students who take their classes. When faculties stop competing against each other and start competing against the situation, they will perform better. Without creating any administrative hassles these suggestions can be used by any young inexperienced faculty of mathematics to inspire engineering students to learn engineering mathematics effectively.

Keywords: application based learning, conceptual learning, engineering mathematics, word problem

Procedia PDF Downloads 232

Authors: Kwok W. Mui, Ling T. Wong, Chi T. Cheung

Abstract:

Cooling energy consumption in the residential sector, different from shopping mall, office or commercial buildings, is significantly subject to occupant decisions where in-depth investigations are found limited. It shows that energy consumptions could be associated with housing types. Surveys have been conducted in existing Hong Kong public housings to understand the housing characteristics, apartment electricity demands, occupant’s thermal expectations, and air–conditioning usage patterns for further cooling energy-saving assessments. The aim of this study is to develop a hybrid cooling energy prediction model, which integrated by EnergyPlus (EP) and artificial neural network (ANN) to estimate cooling energy consumption in public residential sector. Sensitivity tests are conducted to find out the energy impacts with changing building parameters regarding to external wall and window material selection, window size reduction, shading extension, building orientation and apartment size control respectively. Assessments are performed to investigate the relationships between cooling demands and occupant behavior on thermal environment criteria and air-conditioning operation patterns. The results are summarized into a cooling energy calculator for layman use to enhance the cooling energy saving awareness in their own living environment. The findings can be used as a directory framework for future cooling energy evaluation in residential buildings, especially focus on the occupant behavioral air–conditioning operation and criteria of energy-saving incentives.

Keywords: artificial neural network, cooling energy, occupant behavior, residential buildings, thermal environment

Procedia PDF Downloads 168

Authors: Farhad Eizakshiri

Abstract:

The potential for groupthink to explain the issues contributing to deterioration of decision-making ability within the unitary team and so to cause poor outcomes attracted a great deal of attention from a variety of disciplines, including psychology, social and organizational studies, political science, and others. Yet what remains unclear is how and why the team members’ strivings for unanimity and cohesion override their motivation to realistically appraise alternative courses of action. In this paper, the findings of a sequential explanatory mixed-methods research containing an experiment with thirty groups of three persons each and interviews with all experimental groups to investigate this issue is reported. The experiment sought to examine how individuals aggregate their views in order to reach a consensual group decision concerning the completion time of a task. The results indicated that groups made better estimates when they had no interaction between members in comparison with the situation that groups collectively agreed on time estimates. To understand the reasons, the qualitative data and informal observations collected during the task were analyzed through conversation analysis, thus leading to four reasons that caused teams to neglect divergent viewpoints and reduce the number of ideas being considered. Reasons found were the concurrence-seeking tendency, pressure on dissenters, self-censorship, and the illusion of invulnerability. It is suggested that understanding the dynamics behind the aforementioned reasons of groupthink will help project teams to avoid making premature group decisions by enhancing careful evaluation of available information and analysis of available decision alternatives and choices.

Keywords: groupthink, group decision, cohesiveness, project teams, mixed-methods research

Procedia PDF Downloads 396

Authors: Mehrnoosh Abouzari, Shahrokh Shahraei

Abstract:

With the development of artificial intelligence in the present age, intelligent machines and systems have proven their actual and potential capabilities and are mindful of increasing their presence in various fields of human life in the fields of industry, financial transactions, marketing, manufacturing, service affairs, politics, economics and various branches of the humanities .Therefore, despite the conservatism and prudence of law enforcement, the traces of artificial intelligence can be seen in various areas of law. Including judicial robotics capability estimation, intelligent judicial decision making system, intelligent defender and attorney strategy adjustment, dissemination and regulation of different and scattered laws in each case to achieve judicial coherence and reduce opinion, reduce prolonged hearing and discontent compared to the current legal system with designing rule-based systems, case-based, knowledge-based systems, etc. are efforts to apply AI in law. In this article, we will identify the ways in which AI is applied in its laws and regulations, identify the dominant concerns in this area and outline the relationship between these two areas in order to answer the question of how artificial intelligence can be used in different areas of law and what the implications of this application will be. The authors believe that the use of artificial intelligence in the three areas of legislative, judiciary and executive power can be very effective in governments' decisions and smart governance, and helping to reach smart communities across human and geographical boundaries that humanity's long-held dream of achieving is a global village free of violence and personalization and human error. Therefore, in this article, we are going to analyze the dimensions of how to use artificial intelligence in the three legislative, judicial and executive branches of government in order to realize its application.

Keywords: artificial intelligence, law, intelligent system, judge

Procedia PDF Downloads 119

Authors: Damanhur Munardi, Muhammad Hafiz, Dina Nurmalita Sari, Syarifah Ridani Alifa

Abstract:

Purpose: This research aims to analyze the Benefits, Opportunity, Cost, and Risk aspects of applying the Green Finance concept and to obtain the right Green Finance financing strategy to be implemented within a long-term and short-term strategic framework.Methodology: This research method uses a qualitative-descriptive analysis approach. The analysis technique uses Analytical Network Process (ANP) with a BOCR network structure approach.Findings: The research results show that the most priority long-term strategic alternative based on the long-term BOCR analysis is increasing awareness among the public and industry by 52% and the importance of coordination between related institutions by 50%. Meanwhile, the most priority short-term strategic alternatives are the importance of coordination between related institutions 29%, increasing awareness among the public and industry 28%, the banking industry proactively funding environmentally friendly companies and technology 23%, the existence of Green Finance POS (Standard Operating Procedures) 20%.Implications: This research can be used as a reference for regulators and policymakers in making strategic decisions that can increase green finance financing. The novelty of this research is identifying problems that occur in green finance financing in Aceh province by analyzing opinions from experts in related fields and financial regulators in Aceh to create a strategy that can be implemented to increase green finance financing in Aceh province through BPD in Aceh, namely Bank Aceh.

Keywords: green financing, banking, sharia, islamic

Procedia PDF Downloads 64

Authors: Md. Rifad Chowdhury

Abstract:

This research study investigates employees' conception of work motivation to perform at the municipal corporation in Bangladesh. The municipal corporation is one of the key administrative bodies of Bangladesh’s local government. Municipal corporation employees provide essential public services in the country’s semi-urban areas. Work motivation has been defined as a result of interaction between the individual and the environment. Local government studies indicate the work environment of the municipal corporation is unique because of its key colonial and political history, several reform attempts, non-western social perspectives, job functions, and traditional governance. The explorative purpose of this study is to find and analyse the conceptions of employees’ work motivation within this environment to expand a better understanding of work motivation. According to the purpose of this study, a qualitative method has been adopted, which has remained a very unpopular method among work motivational researchers in Bangladesh. Twenty-two semi-structured online interviews were conducted in this study. Phenomenographic research methodology has been adopted to describe the limited number of qualitatively different ways of experiencing work motivation. During the analysis of the semi-structured interview transcripts, the focus was on the employees' perspectives as employees experience work motivation or the second-order perspective to explore and analyse the conceptions. Based on the participants' collective experiences and dimensions of variation across the different ways of experiencing, six conceptions of employee work motivation to perform at the municipal corporation were identified in this study. The relationships between conceptions were further elaborated in terms of critical variations across the conceptions. Six dimensions of critical variations have emerged within and between the conceptions. In the outcome space, the relationships between conceptions and dimensions of critical variations are presented in a logical structure. The findings of this research study show significance to expand the understanding of work motivation and the research context of phenomenography. The findings of this research will contribute to the ongoing attention of contextual work motivational understanding from a Bangladeshi perspective and phenomenographic research conceptions in organisational behaviour studies.

Keywords: work motivation, qualitative, phenomenography, local government

Procedia PDF Downloads 92

Authors: Antonio M. Oliveira, Patricia Oliveira-Silva, Jose Matias Alves, Gary McPherson

Abstract:

The music teaching is oriented towards offering formal music training. Due to its specificities, this vocational program starts at a very young age. Although provided by the State, the offer is limited to 6 schools throughout the country, which means that the vacancies for prospective students are very limited every year. It is therefore crucial that these vacancies be taken by especially motivated children grown within households that offer the ideal setting for success. Some of the instruments used to evaluate musical performance are highly sensitive to specific previous training, what represents a severe validity problem for testing children who have had restricted opportunities for formal training. Moreover, these practices may be unfair because, for instance, they may not reflect the candidates’ music aptitudes. Based on what constitutes a prerequisite for making an excellent music student, researchers in this field have long argued that motivation, task commitment, and parents’ support are as important as ability. Thus, the aim of this study is: (1) to prepare an inventory of admission requirements in Australia, Portugal and Ireland; (2) to examine whether the candidates to music conservatories and parents’ level of motivation, assessed at three evaluation points (i.e., admission, at the end of the first year, and at the end of the second year), correlates positively with the candidates’ progress in learning a musical instrument (i.e., whether motivation at the admission may predict student musicianship); (3) an adaptation of an existing instrument to assess the motivation (i.e., to adapt the items to the music setting, focusing on the motivation for playing a musical instrument). The inclusion criteria are: only children registered in the administrative services to be evaluated for entrance to the conservatory will be accepted for this study. The expected number of participants is fifty (5-6 years old) in all the three frequency schemes: integrated, articulated and supplementary. Revisiting musical admission procedures is of particular importance and relevance to musical education because this debate may bring guidance and assistance about the needed improvement to make the process of admission fairer and more transparent.

Keywords: music learning, music admission requirements, student’s motivation, parent’s motivation

Procedia PDF Downloads 166

Authors: Chiling Chen, Chiaoying Chou, Siyang Wu

Abstract:

Taiwan locates at the west of Pacific Ocean and intersects between continental and marine climate. Typhoons frequently strike Taiwan and come with meteorological disasters, i.e., heavy flooding, landslides, loss of life and properties, etc. Global climate change brings more extremely meteorological disasters. So, develop techniques to improve disaster prevention and mitigation is needed, to improve rescue processes and rehabilitations is important as well. In this study, UAVs (Unmanned Aerial Vehicles) are applied to take instant images for improving the disaster investigation and rescue processes. Paddy rice fields in the central Taiwan are the study area. There have been attacked by heavy rain during the monsoon season in June 2016. UAV images provide the high ground resolution (3.5cm) with 3D Point Clouds to develop image discrimination techniques and digital surface model (DSM) on rice lodging. Firstly, image supervised classification with Maximum Likelihood Method (MLD) is used to delineate the area of rice lodging. Secondly, 3D point clouds generated by Pix4D Mapper are used to develop DSM for classifying the lodging levels of paddy rice. As results, discriminate accuracy of rice lodging is 85% by image supervised classification, and the classification accuracy of lodging level is 87% by DSM. Therefore, UAVs not only provide instant images of agricultural damage after the meteorological disaster, but the image discriminations on rice lodging also reach acceptable accuracy (>85%). In the future, technologies of UAVs and image discrimination will be applied to different crop fields. The results of image discrimination will be overlapped with administrative boundaries of paddy rice, to establish GIS-based assist system on agricultural damage discrimination. Therefore, the time and labor would be greatly reduced on damage detection and monitoring.

Keywords: Monsoon, supervised classification, Pix4D, 3D point clouds, discriminate accuracy

Procedia PDF Downloads 300

Authors: Ridha Abdulla Al Hammam

Abstract:

Purpose: to measure the extent of perceived structural empowerment and work commitment the intensive care unit in SMC have in their work place. Background: nurses’ access to power structures (information, recourses, opportunity, and support) directly influences their productivity, retention, and job satisfaction. Exploring nurses’ level and sources of work commitment (affective, normative, and continuance) is very essential to guide nursing leaders making decisions to improve work environment to facilitate effective nursing care. Both concepts (Structural Empowerment and Work Commitment) were never investigated in our critical care unit. Methods: a sample of 50 nurses attained from the Intensive Care Unit (Adult). Conditions for Workplace Effectiveness Questionnaire and Three-Component Model Employee Commitment Survey were used to measure the two concepts respectively. The study is quantitative, descriptive, and correlational in design. Results: the participants reported moderate structural empowerment provided by their work place (M=15 out of 20). The sample perceived high access to opportunity mainly through gaining more skills (M=4.45 out of 5) where the rest power structures were perceived with moderate accessibility. The participants’ affective commitment (M=5.6 out of 7) to work in the ICU overweighed their normative and continuance commitment (M=5.1, M=4.9 out of 7) implying a stronger emotional connection with their unit. Strong positive and significant correlations were observed between the participants’ structural empowerment scores and all work commitment sources. Conclusion: these results provided an insight on aspects of work environment that need to be fostered and improved in our intensive care unit which have a direct linkage to nurses’ work commitment and potentially to their quality of care they provide.

Keywords: structural empowerment, commitment, intensive care, nurses

Procedia PDF Downloads 287

Authors: Zohreh Moghaddas, Morteza Yazdani, Farhad Hosseinzadeh

Abstract:

Nowadays, data envelopment analysis (DEA) models featuring network structures have gained widespread usage for evaluating the performance of production systems and activities (Decision-Making Units (DMUs)) across diverse fields. By examining the relationships between the internal stages of the network, these models offer valuable insights to managers and decision-makers regarding the performance of each stage and its impact on the overall network. To further empower system decision-makers, the inverse data envelopment analysis (IDEA) model has been introduced. This model allows the estimation of crucial information for estimating parameters while keeping the efficiency score unchanged or improved, enabling analysis of the sensitivity of system inputs or outputs according to managers' preferences. This empowers managers to apply their preferences and policies on resources, such as inputs and outputs, and analyze various aspects like production, resource allocation processes, and resource efficiency enhancement within the system. The results obtained can be instrumental in making informed decisions in the future. The top result of this study is an analysis of infeasibility and incorrect estimation that may arise in the theory and application of the inverse model of data envelopment analysis with network structures. By addressing these pitfalls, novel protocols are proposed to circumvent these shortcomings effectively. Subsequently, several theoretical and applied problems are examined and resolved through insightful case studies.

Keywords: inverse models of data envelopment analysis, series network, estimation of inputs and outputs, efficiency, resource allocation, sensitivity analysis, infeasibility

Procedia PDF Downloads 51

Authors: Zhongnan Ye, Xiaoyi Liu, Shu-Chien Hsu

Abstract:

Rapid urbanization has led to a significant increase in construction and demolition waste (C&D waste), underscoring the need for sustainable waste management strategies in the construction industry. Aiming to enhance the sustainability of urban construction practices, this study develops an optimization model to effectively suggest the optimal recycling and reuse strategies for C&D waste, including concrete and steel. By employing Life Cycle Assessment (LCA), the model evaluates the environmental impacts of adopted construction materials throughout their lifecycle. The model optimizes the quantity of materials to recycle or reuse, the selection of specific recycling and reuse processes, and logistics decisions related to the transportation and storage of recycled materials with the objective of minimizing the overall environmental impact, quantified in terms of carbon emissions, energy consumption, and associated costs, while adhering to a range of constraints. These constraints include capacity limitations, quality standards for recycled materials, compliance with environmental regulations, budgetary limits, and temporal considerations such as project deadlines and material availability. The strategies are expected to be both cost-effective and environmentally beneficial, promoting a circular economy within the construction sector, aligning with global sustainability goals, and providing a scalable framework for managing construction waste in densely populated urban environments. The model is helpful in reducing the carbon footprint of construction projects, conserving valuable resources, and supporting the industry’s transition towards a more sustainable future.

Keywords: circular construction, construction and demolition waste, material recycling, optimization modeling

Procedia PDF Downloads 57

Authors: Cristian Pauna

Abstract:

Trading the financial markets is a widespread activity today. A large number of investors, companies, public of private funds are buying and selling every day in order to make profit. Algorithmic trading is the prevalent method to make the trade decisions after the electronic trading release. The orders are sent almost instantly by computers using mathematical models. This paper will present a price prediction methodology based on a multi-dimensional neural network. Using the Fisher transform, the neural network will be instructed for a low-latency auto-adaptive process in order to predict the price evolution for the next period of time. The model is designed especially for algorithmic trading and uses the real-time price series. It was found that the characteristics of the Fisher function applied at the nodes scale level can generate reliable trading signals using the neural network methodology. After real time tests it was found that this method can be applied in any timeframe to trade the financial markets. The paper will also include the steps to implement the presented methodology into an automated trading system. Real trading results will be displayed and analyzed in order to qualify the model. As conclusion, the compared results will reveal that the neural network methodology applied together with the Fisher transform at the nodes level can generate a good price prediction and can build reliable trading signals for algorithmic trading.

Keywords: algorithmic trading, automated trading systems, financial markets, high-frequency trading, neural network

Procedia PDF Downloads 160

Authors: Zhongnan Ye, Xiaoyi Liu, Shu-Chien Hsu

Abstract:

Rapid urbanization has led to a significant increase in construction and demolition waste (C&D waste), underscoring the need for sustainable waste management strategies in the construction industry. Aiming to enhance the sustainability of urban construction practices, this study develops an optimization model to effectively suggest the optimal recycling and reuse strategies for C&D waste, including concrete and steel. By employing Life Cycle Assessment (LCA), the model evaluates the environmental impacts of adopted construction materials throughout their lifecycle. The model optimizes the quantity of materials to recycle or reuse, the selection of specific recycling and reuse processes, and logistics decisions related to the transportation and storage of recycled materials with the objective of minimizing the overall environmental impact, quantified in terms of carbon emissions, energy consumption, and associated costs, while adhering to a range of constraints. These constraints include capacity limitations, quality standards for recycled materials, compliance with environmental regulations, budgetary limits, and temporal considerations such as project deadlines and material availability. The strategies are expected to be both cost-effective and environmentally beneficial, promoting a circular economy within the construction sector, aligning with global sustainability goals, and providing a scalable framework for managing construction waste in densely populated urban environments. The model is helpful in reducing the carbon footprint of construction projects, conserving valuable resources, and supporting the industry’s transition towards a more sustainable future.

Keywords: circular construction, construction and demolition waste, life cycle assessment, material recycling

Procedia PDF Downloads 81

Authors: Onur Kaya, Halit Bayer

Abstract:

Global grocery and supermarket sales are among the largest markets in the world and perishable products such as fresh produce, dairy and meat constitute the biggest section of these markets. Due to their deterioration over time, the demand for these products depends highly on their freshness. They become totally obsolete after a certain amount of time causing a high amount of wastage and decreases in grocery profits. In addition, customers are asking for higher product variety in perishable product categories, leading to less predictable demand per product and to more out-dating. Effective management of these perishable products is an important issue since it is observed that billions of dollars’ worth of food is expired and wasted every month. We consider coordinated inventory and pricing decisions for perishable products with a time and price dependent random demand function. We use stochastic dynamic programming to model this system for both periodically-reviewed and continuously-reviewed inventory systems and prove certain structural characteristics of the optimal solution. We prove that the optimal ordering decision scenario has a monotone structure and the optimal price value decreases by time. However, the optimal price changes in a non-monotonic structure with respect to inventory size. We also analyze the effect of 1 different parameters on the optimal solution through numerical experiments. In addition, we analyze simple-to-implement heuristics, investigate their effectiveness and extract managerial insights. This study gives valuable insights about the management of perishable products in order to decrease wastage and increase profits.

Keywords: age-dependent demand, dynamic programming, perishable inventory, pricing

Procedia PDF Downloads 247

Authors: Edward Y. W. Chu

Abstract:

This paper exemplifies how the political and educational considerations have shaped the heavy-handed MOI policy in Hong Kong after its handover to China in 1997. Its result, a significant degeneration of English standard among the non-elite students, will be reported based on a detailed analysis of the public exam statistics available and other empirical studies. The remedial action taken by the Education Bureau out of the economic and educational considerations will be reported with reference to the official documents. The political, economic and educational considerations exemplified in different stages of Mother-tongue MOI policy in Hong Kong are found to be influential in the MOI policy in other Asian countries as well. For example, out of rapid internationalization and marketization, there has been increasing adoption of English as the MOI in post-secondary institutions in China, Japan & South Korea. On the other hand, while colonial languages were firmly made as the MOI in former colonies such as Vietnam and India, they were greatly retrieved upon independence for political and educational reasons. Malaysia also followed the same pattern upon independence but re-introduced partial English MOI policy in late 90s hoping to capitalize favourable globalization benefits. The short-lived policy was abandoned in 2009 because of the perceived political threat of national identity as well as the lack of educational effectiveness. Based on the great majority of Asian countries studied, this paper argues that MOI policy in Asia is much more than an educational issue, and that there is a clear pattern of how decisions of MOI matters are made. Studying the history and development of MOI in Hong Kong and other Asian countries provides a unique angle to view of how Asian countries prepare for the political, economic and educational challenges nowadays.

Keywords: economics, Hong Kong, medium of instruction, politics

Procedia PDF Downloads 498

Authors: Kenan Morani, Esra Kaya Ayana

Abstract:

This study aimed to develop a novel pipeline for COVID-19 detection using a large and rigorously annotated database of computed tomography (CT) images. The pipeline consists of UNet-based segmentation, lung extraction, and a classification part, with the addition of optional slice removal techniques following the segmentation part. In this work, a batch normalization was added to the original UNet model to produce lighter and better localization, which is then utilized to build a full pipeline for COVID-19 diagnosis. To evaluate the effectiveness of the proposed pipeline, various segmentation methods were compared in terms of their performance and complexity. The proposed segmentation method with batch normalization outperformed traditional methods and other alternatives, resulting in a higher dice score on a publicly available dataset. Moreover, at the slice level, the proposed pipeline demonstrated high validation accuracy, indicating the efficiency of predicting 2D slices. At the patient level, the full approach exhibited higher validation accuracy and macro F1 score compared to other alternatives, surpassing the baseline. The classification component of the proposed pipeline utilizes a convolutional neural network (CNN) to make final diagnosis decisions. The COV19-CT-DB dataset, which contains a large number of CT scans with various types of slices and rigorously annotated for COVID-19 detection, was utilized for classification. The proposed pipeline outperformed many other alternatives on the dataset.

Keywords: classification, computed tomography, lung extraction, macro F1 score, UNet segmentation

Procedia PDF Downloads 131

Authors: Alae El Fahsi

Abstract:

This study explores the ‘Tajawob’ app's role in urban development, demonstrating how mobile applications can empower citizens and facilitate urban planning. Tajawob serves as a digital platform for community feedback, engagement, and participatory governance, addressing urban challenges through innovative tech solutions. This research synthesizes data from a variety of sources, including user feedback, engagement metrics, and interviews with city officials, to assess the app’s impact on citizen participation in urban development in Morocco. By integrating advanced data analytics and user experience design, Tajawob has bridged the communication gap between citizens and government officials, fostering a more collaborative and transparent urban planning process. The findings reveal a significant increase in civic engagement, with users actively contributing to urban management decisions, thereby enhancing the responsiveness and inclusivity of urban governance. Challenges such as digital literacy, infrastructure limitations, and privacy concerns are also discussed, providing a comprehensive overview of the obstacles and opportunities presented by mobile app-based citizen engagement platforms. The study concludes with strategic recommendations for scaling the Tajawob model to other contexts, emphasizing the importance of adaptive technology solutions in meeting the evolving needs of urban populations. This research contributes to the burgeoning field of smart city innovations, offering key insights into the role of digital tools in facilitating more democratic and participatory urban environments.

Keywords: smart cities, digital governance, urban planning, strategic design

Procedia PDF Downloads 58