Search results for: military decision making process (MDMP)

Authors: Çiğdem Bakır, Mecit Yüzkat

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With the increasing emphasis on water quality worldwide, the search for and expanding the market for new and intelligent monitoring systems has increased. The current method is the laboratory process, where samples are taken from bodies of water, and tests are carried out in laboratories. This method is time-consuming, a waste of manpower, and uneconomical. To solve this problem, we used machine learning methods to detect water pollution in our study. We created decision trees with the Orange3 software we used in our study and tried to determine all the factors that cause water pollution. An automatic prediction model based on water quality was developed by taking many model inputs such as water temperature, pH, transparency, conductivity, dissolved oxygen, and ammonia nitrogen with machine learning methods. The proposed approach consists of three stages: preprocessing of the data used, feature detection, and classification. We tried to determine the success of our study with different accuracy metrics and the results. We presented it comparatively. In addition, we achieved approximately 98% success with the decision tree.

Keywords: decision tree, water quality, water pollution, machine learning

Procedia PDF Downloads 83

Authors: Michel Patiño-Sáenz, Martín Haissiner, Jorge Martínez-Cotrina, Daniel Pastor, Hernando Santamaría-García, Maria-Alejandra Tangarife, Agustin Ibáñez, Sandra Baez

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It has been shown that gruesome descriptions of harm can increase the punishment given to a transgressor. This biasing effect is mediated by negative emotions, which are elicited upon the presentation of gruesome descriptions. However, there is a lack of studies inquiring the influence of such descriptions on moral decision-making in people involved in the criminal justice system. Such populations are of special interest since they have experience dealing with gruesome evidence, but also formal education on how to assess evidence and gauge the appropriate punishment according to the law. Likewise, they are expected to be objective and rational when performing their duty, because their decisions can impact profoundly people`s lives. Considering these antecedents, the objective of this study was to explore the influence gruesome written descriptions on moral decision-making in this group of people. To that end, we recruited attorneys, judges and public prosecutors (Criminal justice group, CJ, n=30) whose field of specialty is criminal law. In addition, we included a control group of people who did not have a formal education in law (n=30), but who were paired in age and years of education with the CJ group. All participants completed an online, Spanish-adapted version of a moral decision-making task, which was previously reported in the literature and also standardized and validated in the Latin-American context. A series of text-based stories describing two characters, one inflicting harm on the other, were presented to participants. Transgressor's intentionality (accidental vs. intentional harm) and language (gruesome vs. plain) used to describe harm were manipulated employing a within-subjects and a between-subjects design, respectively. After reading each story, participants were asked to rate (a) the harmful action's moral adequacy, (b) the amount of punishment deserving the transgressor and (c) how damaging was his behavior. Results showed main effects of group, intentionality and type of language on all dependent measures. In both groups, intentional harmful actions were rated as significantly less morally adequate, were punished more severely and were deemed as more damaging. Moreover, control subjects deemed more damaging and punished more severely any type of action than the CJ group. In addition, there was an interaction between intentionality and group. People in the control group rated harmful actions as less morally adequate than the CJ group, but only when the action was accidental. Also, there was an interaction between intentionality and language on punishment ratings. Controls punished more when harm was described using gruesome language. However, that was not the case of people in the CJ group, who assigned the same amount of punishment in both conditions. In conclusion, participants with job experience in the criminal justice system or criminal law differ in the way they make moral decisions. Particularly, it seems that they are less sensitive to the biasing effect of gruesome evidence, which is probably explained by their formal education or their experience in dealing with such evidence. Nonetheless, more studies are needed to determine the impact this phenomenon has on the fulfillment of their duty.

Keywords: criminal justice system, emotions, gruesome descriptions, intentionality, moral decision-making

Procedia PDF Downloads 190

Authors: Azrul Azlan Iskandar Mirza

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The purpose of Funds Transfer Pricing (FTP) for Islamic Bank is to promote prudent liquidity risk-taking behavior of business units. The acquirer of stable deposits will be rewarded whilst a business unit that generates long-term assets will be charged for added liquidity funding risks. In the end, it promotes risk-adjusted pricing by incorporating profit rate risk and liquidity risk component in the product pricing. However, in the event of Shariah non-compliant (SNCE), FTP components will be examined in the rectification plan especially when Islamic banks need to purify the non-compliance income. The finding shows that the determination between actual and provision cost will defer the decision among Shariah committee in Islamic banks. This paper will review each of FTP components to ensure the classification of actual and provision costs reflect the decision on rectification process on SNCE. This will benefit future decision and its consistency of Islamic banks.

Keywords: fund transfer pricing, Islamic banking, Islamic finance, shariah non-compliant event

Procedia PDF Downloads 195

Authors: Dona Primasari

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This study examines the antecedent variables of Government Financial Acccounting System (SAKD) implementation and its consequence. The antecedent variables are: decentralization of decision making, adaptation, and the manager support. The consequences are satisfaction and performance officer. This research represents the empirical test which used convenience sampling technics in data collection. The data were collected from 167 officers of local government in the Regional Coordinating Agency for Development of Cross County/City Region III Central Java Province. Data analysis used Structural Equation Model (SEM) with the AMOS 18.0 program. The result of hypothesis examination indicates that six raised hypothesis are accepted and two hypothesis are rejected.

Keywords: decentralization of decision making, adaptation officer, manager support, implementation of Government Accounting Financial System (SAKD), satisfaction and performance officer

Procedia PDF Downloads 389

Authors: Samia Dahmani

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The research investigated the process and outcomes of an ongoing project “Den Grønne Rute”: a network of recreational rooms to be implemented throughout a former vulnerable neighborhood: Trekanten in the city of Holstebro in Denmark. The aim of the project is to better integrate Trekanten in the city and which initiated reflections upon the (dis)connection and the integration in relation to urban planning and city management, as well as the extent to which the project considers diversity since Holstebro is a growing multicultural city. With this research, it was first verified if Trekanten is splintered from Holstebro city, and secondly if planning for diversity, by engaging people in the process via place-making approaches, can help redress the disconnection between the neighborhood and the rest of the city. More specifically, the paper aims at exploring the role of place-making “Den Grønne Rute” in Trekanten in promoting planning for diversity and reassembling the splintering in the city. The theoretical and conceptual framework served to analyze the relationship between the splintering urbanism concept and the community involvement’s role in an inclusive process. The field study examines the detachment between Trekanten and Holstebro and the extent to which the project can overcome the disconnection. Methodologically a mix-methods approach was adopted where two semi-structured interviews, a focus group, and an online survey were conducted. Contrary to prior assumptions, the results showed that not only is Trekanten splintered from the city, but also the city is greatly disconnected from Trekanten, and hence Holstebro is a splintered city. The surprise was that Trekanten is moreover inner-splintered. The splintering urbanism accordingly has different dimensions. Even though the project’s design seemed to incorporate diverse ages and groups of people, its process lacks an understanding of the diversity’s relevance in promoting inclusiveness. In fact, the analysis revealed socio-cultural and psychological splintering. Since place-making, as a collaborative approach in planning, is itself an expression of diversity (since it brings differences into play), reconsidering diversity within the process by engaging people at the early stages of planning was recommended. Another suggestion was not to limit the project to a destination but more as an experience to remember and a story to tell. Only by bringing people together in re-imagining the place can Trekanten reassemble with Holstebro and vice versa. The aim of the research was to add a new perspective to the splintering urbanism and planning for diversity so to advance place-making as an approach in promoting the latter and redressing the former.

Keywords: the splintering urbanism, place-making, planning for diversity, Den Grønne Rute, Trekanten, Holstebro

Procedia PDF Downloads 127

Authors: Bernard Igoche Igoche, Olumuyiwa Matthew, Peter Bednar, Alexander Gegov

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This study presents an ontology-driven approach for knowledge discovery and validation from admission databases in Nigerian polytechnic institutions. The research aims to address the challenges of extracting meaningful insights from vast amounts of admission data and utilizing them for decision-making and process improvement. The proposed methodology combines the knowledge discovery in databases (KDD) process with a structural causal model (SCM) ontological framework. The admission database of Benue State Polytechnic Ugbokolo (Benpoly) is used as a case study. The KDD process is employed to mine and distill knowledge from the database, while the SCM ontology is designed to identify and validate the important features of the admission process. The SCM validation is performed using the conditional independence test (CIT) criteria, and an algorithm is developed to implement the validation process. The identified features are then used for machine learning (ML) modeling and prediction of admission status. The results demonstrate the adequacy of the SCM ontological framework in representing the admission process and the high predictive accuracies achieved by the ML models, with k-nearest neighbors (KNN) and support vector machine (SVM) achieving 92% accuracy. The study concludes that the proposed ontology-driven approach contributes to the advancement of educational data mining and provides a foundation for future research in this domain.

Keywords: admission databases, educational data mining, machine learning, ontology-driven knowledge discovery, polytechnic education, structural causal model

Procedia PDF Downloads 66

Authors: Ahmad Alqatan

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Purpose: The purpose of this study is to analyze how the adoption of cloud accounting systems influences the governance practices and performance of boards of directors in MENA countries. The research aims to identify the benefits and challenges associated with cloud accounting and its role in improving board efficiency and oversight. Methodology: This research employs a mixed-method approach, combining quantitative surveys and qualitative interviews with board members and financial officers from a diverse range of companies in the MENA region. The quantitative data is analyzed to determine patterns and correlations, while qualitative insights provide a deeper understanding of the contextual factors influencing cloud accounting adoption and its impacts. Findings: The findings indicate that cloud accounting significantly enhances the decision-making capabilities of boards by providing real-time financial information and facilitating better communication among board members. Companies using cloud accounting reports improved financial oversight and more timely and accurate financial reporting. However, the research also identifies challenges such as cybersecurity concerns, resistance to change, and the need for ongoing training and support. Practical Implications: The study suggests that MENA companies can benefit from investing in cloud accounting technologies to improve board governance and strategic decision-making. It highlights the importance of addressing cybersecurity issues and providing adequate training for board members to maximize the advantages of cloud accounting. Originality: This research contributes to the limited literature on cloud accounting in the MENA region, offering valuable insights for policymakers, business leaders, and academics. It underscores the transformative potential of cloud accounting for enhancing board performance and corporate governance in emerging markets.

Keywords: cloud accounting, board of directors, MENA region, corporate governance, financial transparency, real-time data, decision-making, cybersecurity, technology adoption

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Authors: Yingxiao Ye, Christopher Doehring, Angelos Georghiou, Hugh Robinson, Phebe Vayanos

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Human development is a threat to biodiversity, and conservation organizations (COs) are purchasing land to protect areas for biodiversity preservation. However, COs have limited budgets and thus face hard prioritization decisions that are confounded by uncertainty in future human land use. This research proposes a data-driven sequential planning model to help COs choose land parcels that minimize the uncertain human impact on biodiversity. The proposed model is robust to uncertain development, and the sequential decision-making process is adaptive, allowing land purchase decisions to adapt to human land use as it unfolds. The cellular automata model is leveraged to simulate land use development based on climate data, land characteristics, and development threat index from NASA Socioeconomic Data and Applications Center. This simulation is used to model uncertainty in the problem. This research leverages state-of-the-art techniques in the robust optimization literature to propose a computationally tractable reformulation of the model, which can be solved routinely by off-the-shelf solvers like Gurobi or CPLEX. Numerical results based on real data from the Jaguar in Central and South America show that the proposed method reduces conservation loss by 19.46% on average compared to standard approaches such as MARXAN used in practice for biodiversity conservation. Our method may better help guide the decision process in land acquisition and thereby allow conservation organizations to maximize the impact of limited resources.

Keywords: data-driven robust optimization, biodiversity conservation, uncertainty simulation, adaptive sequential planning

Procedia PDF Downloads 211

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

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Authors: Hyunjoo Park, Taehyun Kim, Taehyun Kim

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The government that declared 'de-nuclearization' pushes up renewable energy policies such as solar power and wind power as an alternative to nuclear power generation. However, local residents who are concerned about the development and natural disasters have been hit by opposition, and related businesses around the country are experiencing difficulties. There is also a voice saying that installing a large wind power generator will cause landslides, low frequencies and noise, which will have a bad influence. Renewal is only a harmful and disgusting facility for the residents. In this way, it is expected that extreme social conflicts will occur in the decision making process related to the locally unwanted land-use (LULU). The government's efforts to solve this problem have been steadily progressing, but the systematic methodology for bringing in active participation and opinion gathering of the residents has not yet been established except for the simple opinion poll or referendum. Therefore, it is time to identify the factors that concern the local residents about the wind power generation facilities, and to find ways to make policy decision-making possible. In this study, we analyze the perception of people about offshore and onshore wind power facilities through questionnaires or interviews, and examine quantitative and qualitative precedent studies to analyze them. In addition, the study evaluates what factors affect the local acceptance of wind power facilities. As a result of the factor analysis of the questionnaire items, factors affecting the residents' acceptance of the wind power facility were extracted from four factors such as environmental, economic, risk, social, and management factor. The study also found that the influence of the determinants of local acceptance on the regional acceptability differs according to the demographic characteristics such as gender and income level. This study will contribute to minimizing the conflict on the installation of wind power facilities through communication among the local residents.

Keywords: factor analysis, local acceptance, locally unwanted land-use, LULU, wind power generation facilities

Procedia PDF Downloads 156

Authors: Lara Dutil-Fafard, Caroline Rhéaume, Patrick Archambault, Daniel Lafond, Neal W. Pollock

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Improving resources for medical autonomy of astronauts in prolonged space missions, such as a Mars mission, requires not only technology development, but also decision-making support systems. The Advanced Crew Medical System - Medical Condition Requirements study, funded by the Canadian Space Agency, aimed to create knowledge content and a scenario-based query capability to support medical autonomy of astronauts. The key objective of this study was to create a prototype tool for identifying medical infrastructure requirements in terms of medical knowledge, skills and materials. A multicriteria decision-making method was used to prioritize the highest risk medical events anticipated in a long-term space mission. Starting with those medical conditions, event sequence diagrams (ESDs) were created in the form of decision trees where the entry point is the diagnosis and the end points are the predicted outcomes (full recovery, partial recovery, or death/severe incapacitation). The ESD formalism was adapted to characterize and compare possible outcomes of medical conditions as a function of available medical knowledge, skills, and supplies in a given mission scenario. An extensive literature review was performed and summarized in a medical condition database. A PostgreSQL relational database was created to allow query-based evaluation of health outcome metrics with different medical infrastructure scenarios. Critical decision points, skill and medical supply requirements, and probable health outcomes were compared across chosen scenarios. The three medical conditions with the highest risk rank were acute coronary syndrome, sepsis, and stroke. Our efforts demonstrate the utility of this approach and provide insight into the effort required to develop appropriate content for the range of medical conditions that may arise.

Keywords: decision support system, event-sequence diagram, exploration mission, medical autonomy, scenario-based queries, space medicine

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Authors: Manpreet Singh, V. P. Agrawal, Gurmanjot Singh Bhatti

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From the last decades, there is a significant technological advancement in the field of robotics, and a number of modular self-reconfigurable robots were introduced that can help in space exploration, bucket to stuff, search, and rescue operation during earthquake, etc. As there are numbers of self-reconfigurable robots, choosing the optimum one is always a concern for robot user since there is an increase in available features, facilities, complexity, etc. The objective of this research work is to present a multiple attribute decision making based methodology for coding, evaluation, comparison ranking and selection of modular self-reconfigurable robots using a technique for order preferences by similarity to ideal solution approach. However, 86 attributes that affect the structure and performance are identified. A database for modular self-reconfigurable robot on the basis of different pertinent attribute is generated. This database is very useful for the user, for selecting a robot that suits their operational needs. Two visual methods namely linear graph and spider chart are proposed for ranking of modular self-reconfigurable robots. Using five robots (Atron, Smores, Polybot, M-Tran 3, Superbot), an example is illustrated, and raking of the robots is successfully done, which shows that Smores is the best robot for the operational need illustrated, and this methodology is found to be very effective and simple to use.

Keywords: self-reconfigurable robots, MADM, TOPSIS, morphogenesis, scalability

Procedia PDF Downloads 224

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 71

Authors: Shunsuke Saito, Kazuho Yoshimoto, Shunichi Ohmori, Sirawadee Arunyanart

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In this paper, we suggest a mechanism of assessment that rater and Ratee (or employees) to convince. There are many problems exist in the personnel assessment. In particular, we were focusing on the three. (1) Raters are not sufficiently recognized assessment point. (2) Ratee are not convinced by the mechanism of assessment. (3) Raters (or Evaluators) and ratees have empathy. We suggest 1: Setting of "understanding of the assessment points." 2: Setting of "relative assessment ability." 3: Proposal of two-way assessment mechanism to solve these problems. As a prerequisite, it is assumed that there are multiple raters. This is because has been a growing importance of multi-faceted assessment. In this model, it determines the weight of each assessment point evaluators by the degree of understanding and assessment ability of raters and ratee. We used the ANP (Analytic Network Process) is a theory that an extension of the decision-making technique AHP (Analytic Hierarchy Process). ANP can be to address the problem of forming a network and assessment of Two-Way is possible. We apply this technique personnel assessment, the weights of rater of each point can be reasonably determined. We suggest absolute assessment for Two-Way assessment by ANP. We have verified that the consent of the two approaches is higher than conventional mechanism. Also, human resources consultant we got a comment about the application of the practice.

Keywords: personnel evaluation, pairwise comparison, analytic network process (ANP), two-ways

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Authors: Ilya A. Snegirev

Abstract:

The article focuses on the comparative study of Russian military poetry of the 20th century. To make a complete description, the verse of different genres, mainly minor lyrical form, is taken. The study makes it possible to emphasize the idea that genre is not completely representative for a comprehensive research, as it is also necessary to dwell upon the strategies of war description in verse. Furthermore, the tendency of lyrical hero individualization is noted. This tendency can be traced throughout the whole second half of the 20th century – the poets of the Second World War – and further, to the whole post-war poetry. To characterize these changes, the texts by K.M. Simonov and A.A. Surkov are being analyzed as the examples of the qualitative transition to an individual hero.

Keywords: literature’s evolution, narrator, storytelling poetry, tradition

Procedia PDF Downloads 189

Authors: Pejman Hosseinioun, Hasan Shakeri, Ghasem Ghorbanirostam

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In recent years, we have seen an increasing importance of research and study on knowledge source, decision support systems, data mining and procedure of knowledge discovery in data bases and it is considered that each of these aspects affects the others. In this article, we have merged information source and knowledge source to suggest a knowledge based system within limits of management based on storing and restoring of knowledge to manage information and improve decision making and resources. In this article, we have used method of data mining and Apriori algorithm in procedure of knowledge discovery one of the problems of Apriori algorithm is that, a user should specify the minimum threshold for supporting the regularity. Imagine that a user wants to apply Apriori algorithm for a database with millions of transactions. Definitely, the user does not have necessary knowledge of all existing transactions in that database, and therefore cannot specify a suitable threshold. Our purpose in this article is to improve Apriori algorithm. To achieve our goal, we tried using fuzzy logic to put data in different clusters before applying the Apriori algorithm for existing data in the database and we also try to suggest the most suitable threshold to the user automatically.

Keywords: decision support system, data mining, knowledge discovery, data discovery, fuzzy logic

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Authors: Siti Noor Baiti Binti Mustafa

Abstract:

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

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

Procedia PDF Downloads 126

Authors: Ömer Akkaya, Muammer Zerenler

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Ethics is important for all shareholders and stakeholders that a firm has in its environment. Whether a firm behaves ethically or unethically has a significant influence on consumers’ decision making and buying process. This research tries to explain business ethics from consumers’ perspective. The survey includes several questions to explain how consumers react if they know a firm behave unethically or ethically. What are consumers’ expectations regarding the ethical behavior of firm? Do consumer reward or punish the firms considering the ethics? Does it really important for consumers firms behaving ethical?

Keywords: business ethics, consumer behavior, ethics, social responsibility

Procedia PDF Downloads 362

Authors: Tania Viju, Bimal P., Naseer M. A.

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This study aims to develop a conceptual framework for the decision support system (DSS), that helps the decision-makers to dynamically choose appropriate safety measures for each identified accident blackspot. An accident blackspot is a segment of road where the frequency of accident occurrence is disproportionately greater than other sections on roadways. According to a report by the World Bank, India accounts for the highest, that is, eleven percent of the global death in road accidents with just one percent of the world’s vehicles. Hence in 2015, the Ministry of Road Transport and Highways of India gave prime importance to the rectification of accident blackspots. To enhance road traffic safety and reduce the traffic accident rate, effectively identifying and rectifying accident blackspots is of great importance. This study helps to understand and evaluate the existing methods in accident blackspot identification and prediction that are used around the world and their application in Indian roadways. The decision support system, with the help of IoT, ICT and smart systems, acts as a management and planning tool for the government for employing efficient and cost-effective rectification strategies. In order to develop a decision criterion, several factors in terms of quantitative as well as qualitative data that influence the safety conditions of the road are analyzed. Factors include past accident severity data, occurrence time, light, weather and road conditions, visibility, driver conditions, junction type, land use, road markings and signs, road geometry, etc. The framework conceptualizes decision-making by classifying blackspot stretches based on factors like accident occurrence time, different climatic and road conditions and suggesting mitigation measures based on these identified factors. The decision support system will help the public administration dynamically manage and plan the necessary safety interventions required to enhance the safety of the road network.

Keywords: decision support system, dynamic management, road accident blackspots, road safety

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Authors: Yu-Ching Cheng, Yi-Kai Juan, Daniel Castro

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Energy consumption of buildings has been an increasing concern for researchers and practitioners in the last decade. Sustainable building renovation can reduce energy consumption and carbon dioxide emissions; meanwhile, it also can extend existing buildings useful life and facilitate environmental sustainability while providing social and economic benefits to the society. School buildings are different from other designed spaces as they are more crowded and host the largest portion of daily activities and occupants. Strategies that focus on reducing energy use but also improve the students’ learning environment becomes a significant subject in sustainable school buildings development. A decision model is developed in this study to solve complicated and large-scale combinational, discrete and determinate problems such as school renovation projects. The task of this model is to automatically search for the most cost-effective (lower cost and higher quality) renovation strategies. In this study, the search process of optimal school building renovation solutions is by nature a large-scale zero-one programming determinate problem. A* is suitable for solving deterministic problems due to its stable and effective search process, and genetic algorithms (GA) provides opportunities to acquire global optimal solutions in a short time via its indeterminate search process based on probability. These two algorithms are combined in this study to consider trade-offs between renovation cost and improved quality, this decision model is able to evaluate current school environmental conditions and suggest an optimal scheme of sustainable school buildings renovation strategies. Through adoption of this decision model, school managers can overcome existing limitations and transform school buildings into spaces more beneficial to students and friendly to the environment.

Keywords: decision model, school buildings, sustainable renovation, genetic algorithm, A* search algorithm

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Authors: Ryan Vincent Teodoro, Adrian Paul Virador, Jan Christopher Cardenas

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In the field of construction, managerial positions are completely dominated by males. The researchers conducted this study to see if there is a significant difference between the competencies of male and female project managers in the construction field. To see if there is a significant difference, they subdivided the competency of project managers into three components; decision making, organizing skills, and resiliency. The researchers conducted a five-point Likert scale survey of 28 project managers in the construction field, 18 of them are males and 10 are females. The researchers used Cronbach’s alpha to translate the raw scores of the respondents into competency scores. Then, the competency scores are analyzed using the Mann-Whitney U Test to see if there is a significant difference between the male’s and female’s competency scores. A p-value of 0.808 was calculated, which is greater than 0.05, which means that the null hypothesis is accepted. Therefore, the researchers concluded that there is no significant difference between the competencies of male and female project managers in terms of decision making, organizing skills, and resiliency in the construction field in the National Capital Region, Philippines.

Keywords: competency, resiliency, project managers, Mann-Whitney U test

Procedia PDF Downloads 134

Authors: Hosein Hamisheh Bahar, Mohammad Hossein Fazel Zarandi, Akbar Esfahanipour

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In this paper, a hybrid expert system is developed by using fuzzy genetic network programming with reinforcement learning (GNP-RL). In this system, the frame-based structure of the system uses the trading rules extracted by GNP. These rules are extracted by using technical indices of the stock prices in the training time period. For developing this system, we applied fuzzy node transition and decision making in both processing and judgment nodes of GNP-RL. Consequently, using these method not only did increase the accuracy of node transition and decision making in GNP's nodes, but also extended the GNP's binary signals to ternary trading signals. In the other words, in our proposed Fuzzy GNP-RL model, a No Trade signal is added to conventional Buy or Sell signals. Finally, the obtained rules are used in a frame-based system implemented in Kappa-PC software. This developed trading system has been used to generate trading signals for ten companies listed in Tehran Stock Exchange (TSE). The simulation results in the testing time period shows that the developed system has more favorable performance in comparison with the Buy and Hold strategy.

Keywords: fuzzy genetic network programming, hybrid expert system, technical trading signal, Tehran stock exchange

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Authors: Xiaohua Zou, Yongxin Su

Abstract:

The reasonable operation of heating, ventilation, and air conditioning (HVAC) is of great significance in improving the security, stability, and economy of power system operation. However, the uncertainty of the operating environment, thermal comfort varies by users and rapid decision-making pose challenges for HVAC demand response optimization. In this regard, this paper proposes a reinforcement learning-based method for HVAC demand response optimization considering few-shot personalized thermal comfort (PTC). First, an HVAC DR optimization framework based on few-shot PTC model and DRL is designed, in which the output of few-shot PTC model is regarded as the input of DRL. Then, a few-shot PTC model that distinguishes between awake and asleep states is established, which has excellent engineering usability. Next, based on soft actor criticism, an HVAC DR optimization algorithm considering the user’s PTC is designed to deal with uncertainty and make decisions rapidly. Experiment results show that the proposed method can efficiently obtain use’s PTC temperature, reduce energy cost while ensuring user’s PTC, and achieve rapid decision-making under uncertainty.

Keywords: HVAC, few-shot personalized thermal comfort, deep reinforcement learning, demand response

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Authors: Renjith George, Preethy Mary Donald

Abstract:

Use of internet sources to retrieve health care related information among health care professionals has increased tremendously as the accessibility to internet is made easier through smart phones and tablets. Though there are huge data available at a finger touch, it is doubtful whether all the sources providing health care information adhere to evidence based practice. The objective of this survey was to study the prevalence of use of internet sources to get health care information, to assess the mind-set towards the authenticity of health care information available via internet sources and to study the awareness about evidence based practice in health care among medical and dental students in Melaka-Manipal Medical College. The survey was proposed as there is limited number of studies reported in the literature and this is the first of its kind in Malaysia. A cross sectional survey was conducted among the medical and dental students of Melaka-Manipal Medical College. A total of 521 students including medical and dental students in their clinical years of undergraduate study participated in the survey. A questionnaire consisting of 14 questions were constructed based on data available from the published literature and focused group discussion and was pre-tested for validation. Data analysis was done using SPSS. The statistical analysis of the results of the survey proved that the use of internet resources for health care information are equally preferred over the conventional resources among health care students. Though majority of the participants verify the authenticity of information from internet sources, there was considerable percentage of candidates who feels that all the information from the internet can be utilised for clinical decision making or were not aware about the need of verification of authenticity of such information. 63.7 % of the participants rely on evidence based practice in health care for clinical decision making while 34.2 % were not aware about it. A minority of 2.1% did not agree with the concept of evidence based practice. The observations of the survey reveals the increasing use of internet resources for health care information among health care students. The results warrants the need to move towards evidence based practice in health care as all health care information available online may not be reliable. The health care person should be judicious while utilising the information from such resources for clinical decision making.

Keywords: authenticity, evidence based practice, health care information, internet

Procedia PDF Downloads 447

Authors: Kesya Terinda Natalie, Marcellina Natasha, Rosinta Ria Panggabean

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Purpose: Over the last few years, the company has been implementing sustainability practices to ensure business continuity. However, there are pros and cons regarding the impact of financial reports if companies provide non-financial reports. So this paper aims to prove what the effect of Sustainability Reporting (SR) has on company profitability, as well as things that can be considered as the decision-making of SR disclosure. Methodology: This paper uses the literature review method to describe the results of published articles concerning Sustainability Reporting and Profitability. This study links and analyzes the essence of 50 previous studies related to SR on company profitability, most of which were conducted in Asia. Therefore this research is limited to only 23 studies in Asia. Findings: Sustainability Reporting does not have a significant impact on company profitability because the SR quality of each company varies based on Agency & Legitimacy Theory considerations. Stakeholders are required to focus not only on profitability but also on the long-term of the company. Thus, it is found that SR is used by companies as a sustainable investment, which can improve overall company performance by reducing capital costs and generating positive company value in increasing reputation capital. Value: This paper focuses on how sustainability reporting affects company profitability, as well as things that can be considered as the decision-making of SR disclosure.

Keywords: sustainability reporting, profitability, agency theory, legitimacy theory

Procedia PDF Downloads 90

Authors: Luay Jum'a

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

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

Procedia PDF Downloads 127

Authors: Qin Xvelian

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organic renewal" based on the development of existing resources in high-density urban areas has become the mainstream of urban development in the new era. As an important stock resource of public space in high-density urban areas, promoting its value remodeling is an effective way to alleviate the shortage of public space resources. However, due to the lack of evaluation links in the process of underpass space renewal, a large number of underpass space resources have been left idle, facing the problems of low space conversion efficiency, lack of accuracy in development decision-making, and low adaptability of functional positioning to citizens' needs. Therefore, it is of great practical significance to construct the evaluation system of under-bridge space renewal potential and explore the renewal mode. In this paper, some of the under-bridge spaces in the main urban area of Chongqing are selected as the research object. Through the questionnaire interviews with the users of the built excellent space under the bridge, three types of six levels and twenty-two potential evaluation indexes of "objective demand factor, construction feasibility factor and construction suitability factor" are selected, including six levels of land resources, infrastructure, accessibility, safety, space quality and ecological environment. The analytical hierarchy process and expert scoring method are used to determine the index weight, construct the potential evaluation system of the space under the bridge in high-density urban areas of Chongqing, and explore the direction of renewal and utilization of its suitability. To provide feasible theoretical basis and scientific decision support for the use of under bridge space in the future.

Keywords: high density urban area, potential evaluation, space under bridge, updated using

Procedia PDF Downloads 68

Authors: Boukelkoul Lahcen

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The cumulative costs for O&M may represent as much as 65%-90% of the turbine's investment cost. Nowadays the cost effectiveness concept becomes a decision-making and technology evaluation metric. The cost of energy metric accounts for the effect replacement cost and unscheduled maintenance cost parameters. One key of the proposed approach is the idea of maintaining the WTs which can be captured via use of a finite state Markov chain. Such a model can be embedded within a probabilistic operation and maintenance simulation reflecting the action to be done. In this paper, an approach of estimating the cost of O&M is presented. The finite state Markov model is used for decision problems with number of determined periods (life cycle) to predict the cost according to various options of maintenance.

Keywords: cost, finite state, Markov model, operation and maintenance

Procedia PDF Downloads 533

Authors: Otto Kakhidze, Hoda Alkhzaimi, Adam Ramey, Nasir Memon

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This paper provides an alternative, cyber security based a conceptual framework for the ethics of automated warfare. The large body of work produced on fully or partially autonomous warfare systems tends to overlook malicious security factors as in the possibility of technical attacks on these systems when it comes to the moral and legal decision-making. The argument provides a risk-oriented justification to why technical malicious risks cannot be dismissed in legal, ethical and policy considerations when warfare models are being implemented and deployed. The assumptions of the paper are supported by providing a broader model that contains the perspective of technological vulnerabilities through the lenses of the Game Theory, Just War Theory as well as standard and non-standard defense ethics. The paper argues that a conventional risk-benefit analysis without considering ethical factors is insufficient for making legal and policy decisions on automated warfare. This approach will provide the substructure for security and defense experts as well as legal scholars, ethicists and decision theorists to work towards common justificatory grounds that will accommodate the technical security concerns that have been overlooked in the current legal and policy models.

Keywords: automated warfare, ethics of automation, inherent hijacking, security vulnerabilities, risk, uncertainty

Procedia PDF Downloads 357

Authors: Diana López-Soto, Soumaya Yacout, Francisco Ángel-Bello

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Although inventories are considered as stocks of money sitting on shelve, they are needed in order to secure a constant and continuous production. Therefore, companies need to have control over the amount of inventory in order to find the balance between excessive and shortage of inventory. The classification of items according to certain criteria such as the price, the usage rate and the lead time before arrival allows any company to concentrate its investment in inventory according to certain ranking or priority of items. This makes the decision making process for inventory management easier and more justifiable. The purpose of this paper is to present a new approach for the classification of new items based on the already existing criteria. This approach is called the Logical Analysis of Data (LAD). It is used in this paper to assist the process of ABC items classification based on multiple criteria. LAD is a data mining technique based on Boolean theory that is used for pattern recognition. This technique has been tested in medicine, industry, credit risk analysis, and engineering with remarkable results. An application on ABC inventory classification is presented for the first time, and the results are compared with those obtained when using the well-known AHP technique and the ANN technique. The results show that LAD presented very good classification accuracy.

Keywords: ABC multi-criteria inventory classification, inventory management, multi-class LAD model, multi-criteria classification

Procedia PDF Downloads 884