Search results for: soft decision fusion

Authors: Peiran Ma

Abstract:

This study explored the role of political polarization in an individual's decision of receiving the COVID-19 vaccine. A total of 15 participants participated in individual interviews and focus group discussions about the relationships among domestic political polarization, vaccine hesitancy, and behavioral responses to the COVID-19 pandemic. Political affiliation affected an individual’s decision on the COVID-19 vaccination, such that people who identified as Liberals and Democrats were more accepting of the vaccine. On the other hand, the level of influence declined over time (2020-2022) when the general conception of COVID-19 immunization shifted from political to personal. Results provided qualitative support to the previously identified positive relationship between divided political opinions and COVID-19 vaccine hesitancy and highlighted the decreasing trend in the power of political polarization in vaccination and the existence of other factors.

Keywords: COVID-19, vaccine hesitancy, political polarization, partisanship, ideology

Procedia PDF Downloads 76

Authors: S. Dhib, S. A. Addouche, T. Loukil, A. Elmhamedi

Abstract:

In this paper, a reverse supply chain network is investigated for a decision making. This decision is surrounded by complex flows of returned products, due to the increasing quantity, the type of returned products and the variety of recovery option products (reuse, recycling, and refurbishment). The most important problem in the reverse logistic network (RLN) is to orient returned products to the suitable type of recovery option. However, returned products orientations from collect sources to the recovery disposition have not well considered in performance model. In this study, we propose a performance model for designing a network configuration on reverse logistics. Conceptual and analytical models are developed with taking into account operational, economic and environmental factors on designing network.

Keywords: reverse logistics, network design, performance model, open loop configuration

Procedia PDF Downloads 433

Authors: Irina Khutsishvili

Abstract:

In the present research, a decision support methodology for the multi-attribute group decision-making (MAGDM) problem is developed, namely for the selection of investment projects. The objective of the investment project selection problem is to choose the best project among the set of projects, seeking investment, or to rank all projects in descending order. The project selection is made considering a set of weighted attributes. To evaluate the attributes in our approach, expert assessments are used. In the proposed methodology, lingual expressions (linguistic terms) given by all experts are used as initial attribute evaluations, since they are the most natural and convenient representation of experts' evaluations. Then lingual evaluations are converted into trapezoidal fuzzy numbers, and the aggregate trapezoidal hesitant fuzzy decision matrix will be built. The case is considered when information on the attribute weights is completely unknown. The attribute weights are identified based on the De Luca and Termini information entropy concept, determined in the context of hesitant fuzzy sets. The decisions are made using the extended Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) method under a hesitant fuzzy environment. Hence, a methodology is based on a trapezoidal valued hesitant fuzzy TOPSIS decision-making model with entropy weights. The ranking of alternatives is performed by the proximity of their distances to both the fuzzy positive-ideal solution (FPIS) and the fuzzy negative-ideal solution (FNIS). For this purpose, the weighted hesitant Hamming distance is used. An example of investment decision-making is shown that clearly explains the procedure of the proposed methodology.

Keywords: In the present research, a decision support methodology for the multi-attribute group decision-making (MAGDM) problem is developed, namely for the selection of investment projects. The objective of the investment project selection problem is to choose the best project among the set of projects, seeking investment, or to rank all projects in descending order. The project selection is made considering a set of weighted attributes. To evaluate the attributes in our approach, expert assessments are used. In the proposed methodology, lingual expressions (linguistic terms) given by all experts are used as initial attribute evaluations since they are the most natural and convenient representation of experts' evaluations. Then lingual evaluations are converted into trapezoidal fuzzy numbers, and the aggregate trapezoidal hesitant fuzzy decision matrix will be built. The case is considered when information on the attribute weights is completely unknown. The attribute weights are identified based on the De Luca and Termini information entropy concept, determined in the context of hesitant fuzzy sets. The decisions are made using the extended Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) method under a hesitant fuzzy environment. Hence, a methodology is based on a trapezoidal valued hesitant fuzzy TOPSIS decision-making model with entropy weights. The ranking of alternatives is performed by the proximity of their distances to both the fuzzy positive-ideal solution (FPIS) and the fuzzy negative-ideal solution (FNIS). For this purpose, the weighted hesitant Hamming distance is used. An example of investment decision-making is shown that clearly explains the procedure of the proposed methodology.

Procedia PDF Downloads 115

Authors: Encarnacion Alvarez, Noemı Hidalgo-Rebollo, Juan F. Munoz, Francisco J. Blanco-Encomienda

Abstract:

Many companies use the technique named as acceptance sampling which consists on the inspection and decision making regarding products. According to the results derived from this method, the company takes the decision of acceptance or rejection of a product. The acceptance sampling can be applied to the technology management, since the acceptance sampling can be seen as a tool to improve the design planning, operation and control of technological products. The theoretical operating characteristic (OC) curves are widely used when dealing with acceptance sampling. In this paper, we carry out Monte Carlo simulation studies to compare numerically the empirical OC curves derived from the empirical results to the customary theoretical OC curves. We analyze various possible scenarios in such a way that the differences between the empirical and theoretical curves can be observed under different situations.

Keywords: single-sampling plan, lot, Monte Carlo simulation, quality control

Procedia PDF Downloads 459

Authors: Danica Maljkovic, Igor Balen, Bojana Dalbelo Basic

Abstract:

Following the regulation of EU Directive on Energy Efficiency, specifically Article 9, individual metering in district heating systems has to be introduced by the end of 2016. These directions have been implemented in member state’s legal framework, Croatia is one of these states. The directive allows installation of both heat metering devices and heat cost allocators. Mainly due to bad communication and PR, the general public false image was created that the heat cost allocators are devices that save energy. Although this notion is wrong, the aim of this work is to develop a model that would precisely express the influence of installation heat cost allocators on potential energy savings in each unit within multifamily buildings. At the same time, in recent years, a science of machine learning has gain larger application in various fields, as it is proven to give good results in cases where large amounts of data are to be processed with an aim to recognize a pattern and correlation of each of the relevant parameter as well as in the cases where the problem is too complex for a human intelligence to solve. A special method of machine learning, decision tree method, has proven an accuracy of over 92% in prediction general building consumption. In this paper, a machine learning algorithms will be used to isolate the sole impact of installation of heat cost allocators on a single building in multifamily houses connected to district heating systems. Special emphasises will be given regression analysis, logistic regression, support vector machines, decision trees and random forest method.

Keywords: district heating, heat cost allocator, energy efficiency, machine learning, decision tree model, regression analysis, logistic regression, support vector machines, decision trees and random forest method

Procedia PDF Downloads 244

Authors: Muhammad Shafiq, Huynh Trung Luong

Abstract:

In this paper, we proposed a commitment based revenue sharing contract for a supply chain comprising one manufacturer and one retailer facing highly uncertain demand of a short life span fashionable product. In our model, the retailer reserves a commitment level with the manufacturer prior to the selling season. In response, the manufacturer allocates and produces a specific quantity which is the maximum available quantity for the retailer. The retailer is motivated to commit more by offering higher revenue sharing percentage for reserved capacity than non-reserved capacity. Due to asymmetric information, it is found that the manufacturer can optimize quantity allocation decision while the commitment level decision of the retailer may not be optimal.

Keywords: supply chain coordination, revenue sharing contract, commitment based revenue sharing, quantity allocation

Procedia PDF Downloads 480

Authors: Shajida M., Sakthiyadharshini N. P., Kamalesh S., Aswitha B.

Abstract:

Natural Language Processing (NLP) continues to play a strategic part in complaint discovery and medicine discovery during the current epidemic. This abstract provides an overview of performance analysis with a combination of visualization and classification techniques of NLP for a medical chatbot. Sentiment analysis is an important aspect of NLP that is used to determine the emotional tone behind a piece of text. This technique has been applied to various domains, including medical chatbots. In this, we have compared the combination of the decision tree with heatmap and Naïve Bayes with Word Cloud. The performance of the chatbot was evaluated using accuracy, and the results indicate that the combination of visualization and classification techniques significantly improves the chatbot's performance.

Keywords: sentimental analysis, NLP, medical chatbot, decision tree, heatmap, naïve bayes, word cloud

Procedia PDF Downloads 68

Authors: Assem El-Ansary

Abstract:

This paper illustrates the event-oriented Behavioral Pattern Analysis (BPA) modeling approach in developing an Multi-Agent TeleRobotic Security Control System (MTSCS). The event defined in BPA is a real-life conceptual entity that is unrelated to any implementation. The major contributions of this research are the Behavioral Pattern Analysis (BPA) modeling methodology, and the development of an interactive software tool (DECISION), which is based on a combination of the Analytic Hierarchy Process (AHP) and the ELECTRE Multi-Criteria Decision Making (MCDM) methods.

Keywords: analysis, multi-agent, TeleRobotics control, security, modeling methodology, software modeling, event-oriented, behavioral pattern, use cases

Procedia PDF Downloads 428

Authors: Somnath Bhattacharya, Kamal Sharma, Vaibhav Sonkar

Abstract:

Composite materials emerged in the middle of the 20th century as a promising class of engineering materials providing new prospects for modern technology. Recently, a new class of composite materials known as functionally graded materials (FGMs) has drawn considerable attention of the scientific community. In general, FGMs are defined as composite materials in which the composition or microstructure or both are locally varied so that a certain variation of the local material properties is achieved. This gradual change in composition and microstructure of material is suitable to get gradient of properties and performances. FGMs are synthesized in such a way that they possess continuous spatial variations in volume fractions of their constituents to yield a predetermined composition. These variations lead to the formation of a non-homogeneous macrostructure with continuously varying mechanical and / or thermal properties in one or more than one direction. Lightweight functionally graded composites with high strength to weight and stiffness to weight ratios have been used successfully in aircraft industry and other engineering applications like in electronics industry and in thermal barrier coatings. In the present work, elastic-plastic crack growth problems (using Ramberg-Osgood Model) in an FGM plate under cyclic load has been explored by extended finite element method. Both edge and centre crack problems have been solved by taking additionally holes, inclusions and minor cracks under plane stress conditions. Both soft and hard inclusions have been implemented in the problems. The validity of linear elastic fracture mechanics theory is limited to the brittle materials. A rectangular plate of functionally graded material of length 100 mm and height 200 mm with 100% copper-nickel alloy on left side and 100% ceramic (alumina) on right side is considered in the problem. Exponential gradation in property is imparted in x-direction. A uniform traction of 100 MPa is applied to the top edge of the rectangular domain along y direction. In some problems, domain contains major crack along with minor cracks or / and holes or / and inclusions. Major crack is located the centre of the left edge or the centre of the domain. The discontinuities, such as minor cracks, holes, and inclusions are added either singly or in combination with each other. On the basis of this study, it is found that effect of minor crack in the domain’s failure crack length is minimum whereas soft inclusions have moderate effect and the effect of holes have maximum effect. It is observed that the crack growth is more before the failure in each case when hard inclusions are present in place of soft inclusions.

Keywords: elastic-plastic, fatigue crack, functionally graded materials, extended finite element method (XFEM)

Procedia PDF Downloads 384

Authors: Muhammad Naveed

Abstract:

In this paper, flood issues in Gujranwala and Rawalpindi divisions are discussed as a primary importance as these zones are affected continuously from flooding in recent years, provincial variability of the issue, introduce status of the continuous administration measures, their adequacy and future needs in flood administration are secured. Flood issues in these zones are exhibited by Chenab River Basin, Jhelum Rivers Basin. Some unique problems, related to floods in these divisions is lack of major dams on Chenab and Jhelum rivers and also mismanagement of rivers and canal water like dam break stream, and water signing in Tal zones, are additionally mentioned. There are major Nalaas in these regions like Nalaa Lai of Rawalpindi and Nalaa Daik, Nalaa Palkhu, Nalaa Aik of Gujranwala are major cause of floods in these regions other than rivers. Proper management of these Nalaas and moving of nearby population well in time could reduce impacts from flood in these regions. Progress of different flood administration measures, both auxiliary and non-basic, are discussed. Likewise, future needs to accomplish proficient and fruitful flood management measures in Pakistan are additionally brought up. In this paper, we describe different hard and soft engineering techniques to overcome flood situations in these zones as these zones are more vulnerable due to lack of management in canal and river water. Effective management and use of hard and soft techniques are need of time in coming future for controlling greater flooding in flood risk zones to overcome or minimize people’s death as well as agricultural and financial resources as flood and other natural disasters are a major drawback in the economic prosperity of the country.

Keywords: flood management, rivers, major dams, agricultural and financial loss, future management and control

Procedia PDF Downloads 190

Authors: Mahmoudi Marwa, Bahim Nadhem, Aydi Abdelwaheb, Issaoui Wissal, S. Najet

Abstract:

This work represents a coupling between the geographic information system (GIS) and the multicriteria analysis aiming at the selection of an artificial recharge site by the treated wastewater for the Ariana governorate. On regional characteristics, bibliography and available data on artificial recharge, 13 constraints and 5 factors were hierarchically structured for the adequacy of an artificial recharge. The factors are subdivided into two main groups: environmental factors and economic factors. The adopted methodology allows a preliminary assessment of a recharge site, the weighted linear combination (WLC) and the analytical hierarchy process (AHP) in a GIS. The standardization of the criteria is carried out by the application of the different membership functions. The form and control points of the latter are defined by the consultation of the experts. The weighting of the selected criteria is allocated according to relative importance using the AHP methodology. The weighted linear combination (WLC) integrates the different criteria and factors to delineate the most suitable areas for artificial recharge site selection by treated wastewater. The results of this study showed three potential candidate sites that appear when environmental factors are more important than economic factors. These sites are ranked in descending order using the ELECTRE III method. Nevertheless, decision making for the selection of an artificial recharge site will depend on the decision makers in force.

Keywords: artificial recharge site, treated wastewater, analytical hierarchy process, ELECTRE III

Procedia PDF Downloads 161

Authors: E. Koyuncu

Abstract:

The problem of Order Acceptance and Scheduling (OAS) is defined as a joint decision of which orders to accept for processing and how to schedule them. Any linear programming model representing real-world situation involves the parameters defined by the decision maker in an uncertain way or by means of language statement. Fuzzy data can be used to incorporate vagueness in the real-life situation. In this study, a fuzzy mathematical model is proposed for a single machine OAS problem, where the orders are defined by their fuzzy due dates, fuzzy processing times, and fuzzy sequence dependent setup times. The signed distance method, one of the fuzzy ranking methods, is used to handle the fuzzy constraints in the model.

Keywords: fuzzy mathematical programming, fuzzy ranking, order acceptance, single machine scheduling

Procedia PDF Downloads 332

Authors: Luis Javier Serrano Tamayo

Abstract:

This research on technology makes a first approach to the selection of an amphibious landing ship with strategic capabilities, through the implementation of a multi-criteria model using Analytical Hierarchical Process (AHP), in which a significant group of alternatives of latest technology has been considered. The variables were grouped at different levels to match design and performance characteristics, which affect the lifecycle as well as the acquisition, maintenance and operational costs. The model yielded an overall measure of effectiveness and an overall measure of cost of each kind of ship that was compared each other inside the model and showed in a Pareto chart. The modeling was developed using the Expert Choice software, based on AHP method.

Keywords: analytic hierarchy process, multi-criteria decision-making, Pareto analysis, Colombian Marine Corps, projection operations, expert choice, amphibious landing ship

Procedia PDF Downloads 542

Authors: Fuqiang Wang, Jun Liu, Liyan Cai

Abstract:

This paper investigates the coordination of the conflicting two-stage low carbon supply chain consisting of upstream and downstream manufacturers. The conflict means that the upstream manufacturer takes action for carbon emissions reduction under carbon trading mechanism while the downstream manufacturer’s production cost rises. It assumes for the Stackelberg game that the upstream manufacturer plays as a leader and the downstream manufacturer does as a follower. Four kinds of the situation of decentralized decision making, centralized decision-making, the production cost sharing contract and the carbon emissions reduction revenue sharing contract under decentralized decision making are considered. The backward induction approach is adopted to solve the game. The results show that the more intense the conflict is, the lower the efficiency of carbon emissions reduction and the higher the retail price is. The optimal investment of the decentralized supply chain under the two contracts is unchanged and still lower than that of the centralized supply chain. Both the production cost sharing contract and the carbon emissions reduction revenue sharing contract cannot coordinate the supply chain, because that the sharing cost or carbon emissions reduction sharing revenue will transfer through the wholesale price mechanism. As a result, it requires more complicated contract forms to coordinate such a supply chain.

Keywords: cap-and-trade mechanism, carbon emissions reduction, conflict, supply chain coordination

Procedia PDF Downloads 336

Authors: Sultan Ghaleb Aldaihani

Abstract:

- The environment in which educational leadership takes place is becoming increasingly complex due to factors like globalization and rapid technological change. - This is creating a "leadership gap" where the complexity of the environment outpaces the ability of leaders to effectively respond. - Educational leadership involves guiding teachers and the broader school system towards improved student learning and achievement. 2. Implications of Artificial Intelligence (AI) in Educational Leadership: - AI has great potential to enhance education, such as through intelligent tutoring systems and automating routine tasks to free up teachers. - AI can also have significant implications for educational leadership by providing better information and data-driven decision-making capabilities. - Computer-adaptive testing can provide detailed, individualized data on student learning that leaders can use for instructional decisions and accountability. 3. Enhancing Decision-Making Processes: - Statistical models and data mining techniques can help identify at-risk students earlier, allowing for targeted interventions. - Probability-based models can diagnose students likely to drop out, enabling proactive support. - These data-driven approaches can make resource allocation and decision-making more effective. 4. Improving Efficiency and Productivity: - AI systems can automate tasks and change processes to improve the efficiency of educational leadership and administration. - Integrating AI can free up leaders to focus more on their role's human, interactive elements.

Keywords: Education, Leadership, Technology, Artificial Intelligence

Procedia PDF Downloads 28

Authors: Ferdi Sönmez, Nihal Yorulmaz

Abstract:

Decision making on the true planning of the public transportation systems to serve potential users is a must for metropolitan areas. To take attraction of travelers to projected modes of transport, adequately fair overall travel times should be provided. In this fashion, other benefits such as lower traffic congestion, road safety and lower noise and atmospheric pollution may be earned. The congestion which comes with increasing demand of public transportation is becoming a part of our lives and making residents’ life difficult. Hence, regulations should be done to reduce this congestion. To provide a constructive and balanced regulation in public transportation systems, right stations should be located in right places. In this study, it is aimed to design and implement a Decision Support System (DSS) Application to determine the optimal bus stop places for public transport in Istanbul which is one of the biggest and oldest cities in the world. Required information is gathered from IETT (Istanbul Electricity, Tram and Tunnel) Enterprises which manages all public transportation services in Istanbul Metropolitan Area. By using the most real-like values, cost assignments are made. The cost is calculated with the help of equations produced by bi-level optimization model. For this study, 300 buses, 300 drivers, 10 lines and 110 stops are used. The user cost of each station and the operator cost taken place in lines are calculated. Some components like cost, security and noise pollution are considered as significant factors affecting the solution of set covering problem which is mentioned for identifying and locating the minimum number of possible bus stops. Preliminary research and model development for this study refers to previously published article of the corresponding author. Model results are represented with the intent of decision support to the specialists on locating stops effectively.

Keywords: operator cost, bi-level optimization model, user cost, urban transportation

Procedia PDF Downloads 240

Authors: Mahesh Vishwakarma, Sadhana Vishwakarma

Abstract:

Vocational education includes all kind of education which can help students to acquire skills related to a certain profession, art, or activity so that they are able to exercise that profession, art or activity after acquiring such qualification. However, in this global economy of the modern world, job seekers are expected to have certain soft skills over and above the technical knowledge and skills acquired in their areas of expertise. These soft skills include but not limited to interpersonal communication, understanding, personal attributes, problem-solving, working in team, quick adaptability to the workplace environment, and other. Not only the hands-on, job-related skills, and competencies are now being sought by the employers, but also a complex of attitudinal dispositions and affective traits are being looked by them in their prospective employees. This study was performed to identify the employability skills of technical students from an Industrial Training Centre (ITC) in central India. It also aimed to convey a message to the students currently on the role, that for them to remain relevant in the job market, they would need to constantly adapt to changes and evolving requirements in the work environment, including the use of updated technologies. Five hypotheses were formulated and tested on the employability skills of students as a function of gender, trade, work experience, personal attributes, and IT skills. Data were gathered with the help of center’s training officers who approached 200 recently graduated students from the center and administered the instrument to students. All 200 respondents returned the completed instrument. The instrument used for the study consisted of 2 sections; demographic details and employability skills. To measure the employability skills of the trainees, the instrument was developed by referring to the several instruments developed by the past researchers for similar studies. The 1st section of the instrument of demographic details recorded age, gender, trade, year of passing, interviews faced, and employment status of the respondents. The 2nd section of the instrument on employability skills was categorized into seven specific skills: basic vocational skills; personal attributes; imagination skills; optimal management of resources; information-technology skills; interpersonal skills; adapting to new technologies. The reliability and validity of the instrument were checked. The findings revealed valuable information on the relationship and interdependence of vocational education and employability skills of students in the central Indian scenario. The findings revealed a valuable information on supplementing the existing vocational education programs with few soft skills and competencies so as to develop a superior workforce much better equipped to face the job market. The findings of the study can be used as an example by the management of government and private industrial training centers operating in the other parts of the Asian region. Future research can be undertaken on a greater population base from different geographical regions and backgrounds for an enhanced outcome.

Keywords: employability skills, vocational education, industrial training centers, students

Procedia PDF Downloads 129

Authors: Mai Kaneda, Sarah Feeney

Abstract:

This study examined the association between adult attachment security and career decision-making self-efficacy (CDMSE) among college students in the United States. Previous studies show that attachment security is associated with levels of CDMSE among college students. Given that a majority of studies examining career development variables have used parental attachment measures, this study adds to understanding of this phenomenon by utilizing a broader measure of attachment. The participants included 269 college students (76% female) between the ages of 19-29. An anonymous survey was distributed online via social media as well as in hard copy format in classrooms. Multiple regression analyses were conducted to determine the relationship between anxious and avoidant attachment and CDMSE. Results revealed anxious attachment was a significant predictor of CDMSE (B = -.13, p = .01), such that greater anxiety in attachment was associated with lower levels of CDMSE. When accounting for anxious attachment, avoidant attachment was no longer significant as a predictor of CDMSE (B = -.12, p = .10). The variance in college CDMSE explained by the model was 7%, F(2,267) = 9.51, p < .001. Results for anxious attachment are consistent with existing literature that finds insecure attachment to be related to lower levels of CDMSE, however the non-significant results for avoidant attachment as a predictor of CDMSE suggest not all types of attachment insecurity are equally related to CDMSE. Future research is needed to explore the nature of the relationship between different dimensions of attachment insecurity and CDMSE.

Keywords: attachment, career decision-making, college students, self-efficacy

Procedia PDF Downloads 215

Authors: Vânia Costa, Nuno De Sá Teixeira, Ana C. Santos, Eduardo Santos

Abstract:

Financial literacy and numeracy have been regarded as paramount for rational household decision making in the increasing complexity of financial markets. However, financial decisions are often made under sub-optimal circumstances, including cognitive overload. The present study aims to clarify how financial literacy and numeracy, taken as relevant expert knowledge for financial decision-making, modulate possible effects of cognitive load. Participants were required to perform a choice between a sure loss or a gambling pertaining a financial investment, either with or without a competing memory task. Two experiments were conducted varying only the content of the competing task. In the first, the financial choice task was made while maintaining on working memory a list of five random letters. In the second, cognitive load was based upon the retention of six random digits. In both experiments, one of the items in the list had to be recalled given its serial position. Outcomes of the first experiment revealed no significant main effect or interactions involving cognitive load manipulation and numeracy and financial literacy skills, strongly suggesting that retaining a list of random letters did not interfere with the cognitive abilities required for financial decision making. Conversely, and in the second experiment, a significant interaction between the competing mnesic task and level of financial literacy (but not numeracy) was found for the frequency of choice of a gambling option. Overall, and in the control condition, both participants with high financial literacy and high numeracy were more prone to choose the gambling option. However, and when under cognitive load, participants with high financial literacy were as likely as their illiterate counterparts to choose the gambling option. This outcome is interpreted as evidence that financial literacy prevents intuitive risk-aversion reasoning only under highly favourable conditions, as is the case when no other task is competing for cognitive resources. In contrast, participants with higher levels of numeracy were consistently more prone to choose the gambling option in both experimental conditions. These results are discussed in the light of the opposition between classical dual-process theories and fuzzy-trace theories for intuitive decision making, suggesting that while some instances of expertise (as numeracy) are prone to support easily accessible gist representations, other expert skills (as financial literacy) depend upon deliberative processes. It is furthermore suggested that this dissociation between types of expert knowledge might depend on the degree to which they are generalizable across disparate settings. Finally, applied implications of the present study are discussed with a focus on how it informs financial regulators and the importance and limits of promoting financial literacy and general numeracy.

Keywords: decision making, cognitive load, financial literacy, numeracy

Procedia PDF Downloads 175

Authors: Tamas Jancso, Andrea Podor, Eva Nagyne Hajnal, Peter Udvardy, Gabor Nagy, Attila Varga, Meng Qingyan

Abstract:

The paper deals with the conditions and circumstances of integration of remotely sensed data for rural environmental monitoring purposes. The main task is to make decisions during the integration process when we have data sources with different resolution, location, spectral channels, and dimension. In order to have exact knowledge about the integration and data fusion possibilities, it is necessary to know the properties (metadata) that characterize the data. The paper explains the joining of these data sources using their attribute data through a sample project. The resulted product will be used for rural environmental analysis.

Keywords: remote sensing, GIS, metadata, integration, environmental analysis

Procedia PDF Downloads 113

Authors: S. Niamkaeo, O. Robert, O. Chaowalit

Abstract:

In this investigation, we focus on discovering spatial relationship of drug smuggling along the northern border of Thailand. Thailand is no longer a drug production site, but Thailand is still one of the major drug trafficking hubs due to its topographic characteristics facilitating drug smuggling from neighboring countries. Our study areas cover three districts (Mae-jan, Mae-fahluang, and Mae-sai) in Chiangrai city and four districts (Chiangdao, Mae-eye, Chaiprakarn, and Wienghang) in Chiangmai city where drug smuggling of methamphetamine crystal and amphetamine occurs mostly. The data on drug smuggling incidents from 2011 to 2017 was collected from several national and local published news. Geo-spatial drug smuggling database was prepared. Decision tree algorithm was applied in order to discover the spatial relationship of factors related to drug smuggling, which was converted into rules using rule-based system. The factors including land use type, smuggling route, season and distance within 500 meters from check points were found that they were related to drug smuggling in terms of rules-based relationship. It was illustrated that drug smuggling was occurred mostly in forest area in winter. Drug smuggling exhibited was discovered mainly along topographic road where check points were not reachable. This spatial relationship of drug smuggling could support the Thai Office of Narcotics Control Board in surveillance drug smuggling.

Keywords: decision tree, drug smuggling, Geographic Information System, GIS knowledge discovery, rule-based system

Procedia PDF Downloads 162

Authors: Aisha Adam

Abstract:

This study critically examines the transformative impact of automated decision-making (ADM) and artificial intelligence (AI) systems on South African labour law. As AI technologies increasingly infiltrate workplaces, existing liability frameworks face challenges in addressing the unique complexities presented by these innovations. This article explores the necessity of redefining liability to accommodate the nuanced landscape of ADM and AI within South African labour law. It emphasises the importance of ensuring responsible deployment and safeguarding the rights of workers amid evolving technological dynamics. This research investigates the central concern of fairness, bias, and discrimination in ADM and AI decision-making. Focusing on algorithmic bias and discriminatory outcomes, the paper advocates for the integration of mechanisms within the South African legal framework, particularly under the Promotion of Equality and Prevention of Unfair Discrimination Act (PEPUDA) and the Employment Equity Act (EEA). The study scrutinises the shifting dynamics of the employment relationship, calling for clear guidelines on the responsibilities and liabilities of employers, employees, and technology providers. Furthermore, the article analyses legal and policy responses to ADM and AI within South African labour law, exploring potential amendments to legislation, guidelines, and codes of practice. It assesses the role of regulatory bodies, specifically the Commission for Conciliation, Mediation, and Arbitration (CCMA), in overseeing and enforcing responsible practices in the workplace. Lastly, the research evaluates the impact of ADM and AI on human and social rights in the South African context. Emphasising the protection of constitutional rights, including fair labour practices, privacy, and equality, the study proposes remedies and safeguards. It advocates for a multidisciplinary approach involving legal, technological, and ethical considerations to redefine liability in South African labour law effectively. The article contends that a shift from accountability to responsibility is crucial for promoting fairness, antidiscrimination, and the protection of human and social rights in the age of automated decision-making. It calls for collaborative efforts among stakeholders to shape responsible practices and redefine liability in this evolving technological landscape.

Keywords: automated decision-making, artificial intelligence, labour law, vicarious liability

Procedia PDF Downloads 76

Authors: Neha Ahirwar

Abstract:

In the contemporary digital era, the rise of credit card fraud poses a significant threat to both financial institutions and consumers. As fraudulent activities become more sophisticated, there is an escalating demand for robust and effective fraud detection mechanisms. Advanced machine learning algorithms have become crucial tools in addressing this challenge. This paper conducts a thorough examination of the design and evaluation of a credit card fraud detection system, utilizing four prominent machine learning algorithms: random forest, logistic regression, decision tree, and XGBoost. The surge in digital transactions has opened avenues for fraudsters to exploit vulnerabilities within payment systems. Consequently, there is an urgent need for proactive and adaptable fraud detection systems. This study addresses this imperative by exploring the efficacy of machine learning algorithms in identifying fraudulent credit card transactions. The selection of random forest, logistic regression, decision tree, and XGBoost for scrutiny in this study is based on their documented effectiveness in diverse domains, particularly in credit card fraud detection. These algorithms are renowned for their capability to model intricate patterns and provide accurate predictions. Each algorithm is implemented and evaluated for its performance in a controlled environment, utilizing a diverse dataset comprising both genuine and fraudulent credit card transactions.

Keywords: efficient credit card fraud detection, random forest, logistic regression, XGBoost, decision tree

Procedia PDF Downloads 57

Authors: Ahmed Abdulghani Taha, Mohammad Abdulghani Taha

Abstract:

This study aims at being acquainted with the using the body fat percentage (%BF) with body Mass Index (BMI) as input parameters in fuzzy logic decision support system to predict properly the lifted weight for students at weightlifting class lift according to his abilities instead of traditional manner. The sample included 53 male students (age = 21.38 ± 0.71 yrs, height (Hgt) = 173.17 ± 5.28 cm, body weight (BW) = 70.34 ± 7.87.6 kg, Body mass index (BMI) 23.42 ± 2.06 kg.m-2, fat mass (FM) = 9.96 ± 3.15 kg and fat percentage (% BF) = 13.98 ± 3.51 %.) experienced the weightlifting class as a credit and has variance at BW, Hgt and BMI and FM. BMI and % BF were taken as input parameters in FUZZY logic whereas the output parameter was the lifted weight (LW). There were statistical differences between LW values before and after using fuzzy logic (Diff 3.55± 2.21, P > 0.001). The percentages of the LW categories proposed by fuzzy logic were 3.77% of students to lift 1.0 fold of their bodies; 50.94% of students to lift 0.95 fold of their bodies; 33.96% of students to lift 0.9 fold of their bodies; 3.77% of students to lift 0.85 fold of their bodies and 7.55% of students to lift 0.8 fold of their bodies. The study concluded that the characteristic changes in body composition experienced by students when undergoing weightlifting could be utilized side by side with the Fuzzy logic decision support system to determine the proper workloads consistent with the abilities of students.

Keywords: fuzzy logic, body mass index, body fat percentage, weightlifting

Procedia PDF Downloads 424

Authors: Nurul Azmawati Mohamed, Zarini Ismail, Shalinawati Ramli, Nurul Hayati Chamhuri, Nur Syahrina Rahim, K. Omar

Abstract:

Choosing a career is one of the most important decisions in our life. A right career leads a person to grow with that career and achieve success through the decision. Thus, career suitability assessment is important to help individuals to understand how a variety of personal attributes can impact their potential success and satisfaction with different career options and work environments. Some career needs specific personality trait that relates to attributes of job requirements and commitments. For medicine, being caring, approachable, inquisitive, able to listen and understand patients’ pain, anxiety and sorrow are important. The aim of this study was to evaluate the career suitability of pre-clinical students. This was a cross sectional study conducted among pre-clinical medical students in Universiti Sains Islam Malaysia. 'Sidek Career Interest Inventory’ was used to assess the students’ suitability for the course. This instrument had been validated locally to suit the local social and cultural context. It assessed the students’ personality trait based on Holland’s theory and their interests. For students to pursue in the medical course, two main personality trait are believed to be essential namely investigative and social trait personalities. Some of the characteristics of investigative trait are analytical, rational, intellectual and curious, while the characteristics of social trait personality include empathy, friendly, understanding and accommodating. The score for each personality trait were categorized as low (0-3.99), moderate (4-6.99) and high (7-10). A total of 81 pre-clinical medical students were included in this study. About two third (93.8%) of them were female and all of them are from 20 to 21 of age. Approximately, half of the students (47.5%) scored high and another 46.3% scored moderate for investigative trait. For social trait, only 13.8% scored high while 31.3% scored moderate. Only 12.5% (10) students had high scores for both investigative and social traits. Most of the pre-clinical medical students scored high in the investigative sections, however their social values were inadequate (low scores). For them to become good medical doctors, they should be good in both investigative and social skills to enhance their suitability for this career. Therefore, there is a need to nurture these medical students with appropriate social values and soft skills.

Keywords: career suitability, career interest, medical students, personality trait

Procedia PDF Downloads 313

Authors: Ahmad Mohsin, Syda Fatima, Falak Nawaz, Aman Ullah Khan

Abstract:

Selection of an appropriate architectural style is vital to the success of target web service under development. The nature of architecture design and selection for service-oriented computing applications is quite different as compared to traditional software. Web Services have complex and rigorous architectural styles to choose. Due to this, selection for accurate architectural style for web services development has become a more complex decision to be made by architects. Architectural style selection is a multi-criteria decision and demands lots of experience in service oriented computing. Decision support systems are good solutions to simplify the selection process of a particular architectural style. Our research suggests a new approach using DSS for selection of architectural styles while developing a web service to cater FRs and NFRs. Our proposed DSS helps architects to select right web service architectural pattern according to the domain and non-functional requirements. In this paper, a rule base DSS has been developed using CLIPS (C Language Integrated Production System) to support decisions using multi-criteria requirements. This DSS takes architectural characteristics, domain requirements and software architect preferences for NFRs as input for different architectural styles in use today in service-oriented computing. Weighted sum model has been applied to prioritize quality attributes and domain requirements. Scores are calculated using multiple criterions to choose the final architecture style.

Keywords: software architecture, web-service, rule-based, DSS, multi-criteria requirements, quality attributes

Procedia PDF Downloads 354

Authors: Layaly Ayoub, Mariana Ribeiro

Abstract:

Introduction: Breast cancer is currently considered the leading cause of cancer-related deaths among women in Brazil. Mastectomy, essential in this treatment, often necessitates subsequent breast reconstruction to restore physical appearance and aid in the emotional and psychological recovery of patients. The choice between immediate or delayed reconstruction is influenced by factors such as the type and stage of cancer, as well as the patient's overall health. The decision between autologous breast reconstruction or implant-based reconstruction requires a detailed analysis of individual conditions and needs. Objectives: This study analyzes the techniques and indications used in post-mastectomy breast reconstruction. Methodology: Literature review conducted in the PubMed and SciELO databases, focusing on articles that met the inclusion and exclusion criteria and descriptors. Results: After mastectomy, breast reconstruction is commonly performed. It is necessary to determine the type of technique to be used in each case depending on the specific characteristics of each patient. The tissue expander technique is indicated for patients with sufficient skin and tissue post-mastectomy, who do not require additional radiotherapy, and who opt for a less complex surgery with a shorter recovery time. This procedure promotes the gradual expansion of soft tissues where the definitive implant will be placed. Both temporary and permanent expanders offer flexibility, allowing for adjustment in the expander size until the desired volume is reached, enabling the skin and tissues to adapt to the breast implant area. Conversely, autologous reconstruction is indicated for patients who will undergo radiotherapy, have insufficient tissue, and prefer a more natural solution. This technique uses the transverse rectus abdominis muscle (TRAM) flap, the latissimus dorsi muscle flap, the gluteal flap, and local muscle flaps to shape a new breast, potentially combined with a breast implant. Conclusion: In this context, it is essential to conduct a thorough evaluation regarding the technique to be applied, as both have their benefits and challenges.

Keywords: indications, post-mastectomy, breast reconstruction, techniques

Procedia PDF Downloads 25

Authors: Konstantinos Tolidis

Abstract:

The mountains are amongst the most fragile environments in the world. The world’s mountain areas cover 24% of the Earth’s land surface and are home to 12% of the global population. A further 14% of the global population is estimated to live in the vicinity of their surrounding areas. As urbanization continues to increase in the world, the mountains are also key centers for recreation and tourism; their attraction is often heightened by their remarkably high levels of biodiversity. Due to the fact that the features in mountain areas vary spatially (development degree, human geography, socio-economic reality, relations of dependency and interaction with other areas-regions), the spatial planning on these areas consists of a crucial process for preserving the natural, cultural and human environment and consists of one of the major processes of an integrated spatial policy. This research has been focused on the spatial decision problem of land use allocation optimization which is an ordinary planning problem on the mountain areas. It is a matter of fact that such decisions must be made not only on what to do, how much to do, but also on where to do, adding a whole extra class of decision variables to the problem when combined with the consideration of spatial optimization. The utility of optimization as a normative tool for spatial problem is widely recognized. However, it is very difficult for planners to quantify the weights of the objectives especially when these are related to mountain areas. Furthermore, the land use allocation optimization problems at mountain areas must be addressed not only by taking into account the general development objectives but also the spatial objectives (e.g. compactness, compatibility and accessibility, etc). Therefore, the main research’s objective was to approach the land use allocation problem by utilizing a hybrid meta-heuristic optimization technique tailored to the mountain areas’ spatial characteristics. The results indicates that the proposed methodological approach is very promising and useful for both generating land use alternatives for further consideration in land use allocation decision-making and supporting spatial management plans at mountain areas.

Keywords: multiobjective land use allocation, mountain areas, spatial planning, spatial decision making, meta-heuristic methods

Procedia PDF Downloads 336

Authors: Athina Puype, Lorenzo Malerba, Nico De Wispelaere, Roumen Petrov, Jilt Sietsma

Abstract:

Reduced Activation Ferritic/Martensitic (FM) steels like EUROFER are of interest for first wall application in the future demonstration (DEMO) fusion reactor. Depending on the final design codes for the DEMO reactor, the first wall material will have to function in low-temperature mode or high-temperature mode, i.e. around 250-300°C of above 550°C respectively. However, the use of RAFM steels is limited up to a temperature of about 550°C. For the low-temperature application, the material suffers from irradiation embrittlement, due to a shift of ductile-to-brittle transition temperature (DBTT) towards higher temperatures upon irradiation. The high-temperature response of the material is equally insufficient for long-term use in fusion reactors, due to the instability of the matrix phase and coarsening of the precipitates at prolonged high-temperature exposure. The objective of this study is to investigate the influence of thermal ageing for 1000 hrs and 4000 hrs on microstructural features and mechanical properties of lab-cast EUROFER. Additionally, the ageing behavior of the lab-cast EUROFER is compared with the ageing behavior of standard EUROFER97-2 and T91. The microstructural features were investigated with light optical microscopy (LOM), electron back-scattered diffraction (EBSD) and transmission electron microscopy (TEM). Additionally, hardness measurements, tensile tests at elevated temperatures and Charpy V-notch impact testing of KLST-type MCVN specimens were performed to study the microstructural features and mechanical properties of four different F/M grades, i.e. T91, EUROFER97-2 and two lab-casted EUROFER grades. After ageing for 1000 hrs, the microstructures exhibit similar martensitic block sizes independent on the grain size before ageing. With respect to the initial coarser microstructures, the aged microstructures displayed a dislocation structure which is partially fragmented by polygonization. On the other hand, the initial finer microstructures tend to be more stable up to 1000hrs resulting in similar grain sizes for the four different steels. Increasing the ageing time to 4000 hrs, resulted in an increase of lath thickness and coarsening of M23C6 precipitates leading to a deterioration of tensile properties.

Keywords: ageing experiments, EUROFER, ferritic/martensitic steels, mechanical properties, microstructure, T91

Procedia PDF Downloads 257

Authors: Ravi Patel, Krishna K. Krishnan

Abstract:

In global supply chains, appropriate and sustainable suppliers play a vital role in supply chain development and feasibility. In a larger organization with huge number of suppliers, it is necessary to divide suppliers based on their past history of quality and delivery of each product category. Since performance of any organization widely depends on their suppliers, well evaluated selection criteria and decision-making models lead to improved supplier assessment and development. In this paper, SCOR® performance evaluation approach and ISO standards are used to determine selection criteria for better utilization of supplier assessment by using hybrid model of Analytic Hierchchy Problem (AHP) and Fuzzy Techniques for Order Preference by Similarity to Ideal Solution (FTOPSIS). AHP is used to determine the global weightage of criteria which helps TOPSIS to get supplier score by using triangular fuzzy set theory. Both qualitative and quantitative criteria are taken into consideration for the proposed model. In addition, a multi-product and multi-time period model is selected for order allocation. The optimization model integrates multi-objective integer linear programming (MOILP) for order allocation and a hybrid approach for supplier selection. The proposed MOILP model optimizes order allocation based on manufacturing process and product tolerances as per manufacturer’s requirement for quality product. The integrated model and solution approach are tested to find optimized solutions for different scenario. The detailed analysis shows the superiority of proposed model over other solutions which considered individual decision making models.

Keywords: AHP, fuzzy set theory, multi-criteria decision making, multi-objective integer linear programming, TOPSIS

Procedia PDF Downloads 166