Search results for: decision problems
9386 A Goal-Oriented Approach for Supporting Input/Output Factor Determination in the Regulation of Brazilian Electricity Transmission
Authors: Bruno de Almeida Vilela, Heinz Ahn, Ana Lúcia Miranda Lopes, Marcelo Azevedo Costa
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Benchmarking public utilities such as transmission system operators (TSOs) is one of the main strategies employed by regulators in order to fix monopolistic companies’ revenues. Since 2007 the Brazilian regulator has been utilizing Data Envelopment Analysis (DEA) to benchmark TSOs. Despite the application of DEA to improve the transmission sector’s efficiency, some problems can be pointed out, such as the high price of electricity in Brazil; the limitation of the benchmarking only to operational expenses (OPEX); the absence of variables that represent the outcomes of the transmission service; and the presence of extremely low and high efficiencies. As an alternative to the current concept of benchmarking the Brazilian regulator uses, we propose a goal-oriented approach. Our proposal supports input/output selection by taking traditional organizational goals and measures as a basis for the selection of factors for benchmarking purposes. As the main advantage, it resolves the classical DEA problems of input/output selection, undesirable and dual-role factors. We also provide a demonstration of our goal-oriented concept regarding service quality. As a result, most TSOs’ efficiencies in Brazil might improve when considering quality as important in their efficiency estimation.Keywords: decision making, goal-oriented benchmarking, input/output factor determination, TSO regulation
Procedia PDF Downloads 1979385 Fine-Grained Sentiment Analysis: Recent Progress
Authors: Jie Liu, Xudong Luo, Pingping Lin, Yifan Fan
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Facebook, Twitter, Weibo, and other social media and significant e-commerce sites generate a massive amount of online texts, which can be used to analyse people’s opinions or sentiments for better decision-making. So, sentiment analysis, especially fine-grained sentiment analysis, is a very active research topic. In this paper, we survey various methods for fine-grained sentiment analysis, including traditional sentiment lexicon-based methods, machine learning-based methods, and deep learning-based methods in aspect/target/attribute-based sentiment analysis tasks. Besides, we discuss their advantages and problems worthy of careful studies in the future.Keywords: sentiment analysis, fine-grained, machine learning, deep learning
Procedia PDF Downloads 2629384 Developing a Multiagent-Based Decision Support System for Realtime Multi-Risk Disaster Management
Authors: D. Moser, D. Pinto, A. Cipriano
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A Disaster Management System (DMS) for countries with different disasters is very important. In the world different disasters like earthquakes, tsunamis, volcanic eruption, fire or other natural or man-made disasters occurs and have an effect on the population. It is also possible that two or more disasters arisen at the same time, this means to handle multi-risk situations. To handle such a situation a Decision Support System (DSS) based on multiagents is a suitable architecture. The most known DMSs deal with one (in the case of an earthquake-tsunami combination with two) disaster and often with one particular disaster. Nevertheless, a DSS helps for a better realtime response. Analyze the existing systems in the literature and expand them for multi-risk disasters to construct a well-organized system is the proposal of our work. The here shown work is an approach of a multi-risk system, which needs an architecture, and well-defined aims. In this moment our study is a kind of case study to analyze the way we have to follow to create our proposed system in the future.Keywords: decision support system, disaster management system, multi-risk, multiagent system
Procedia PDF Downloads 4319383 Risk Tolerance in Youth With Emerging Mood Disorders
Authors: Ange Weinrabe, James Tran, Ian B. Hickie
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Risk-taking behaviour is common during youth. In the time between adolescence and early adulthood, young people (aged 15-25 years) are more vulnerable to mood disorders, such as anxiety and depression. What impact does an emerging mood disorder have on decision-making in youth at critical decision points in their lives? In this article, we explore the impact of risk and ambiguity on youth decision-making in a clinical setting using a well-known economic experiment. At two time points, separated by six to eight weeks, we measured risky and ambiguous choices concurrently with findings from three psychological questionnaires, the 10-item Kessler Psychological Distress Scale (K10), the 17-item Quick Inventory of Depressive Symptomatology Adolescent Version (QIDS-A17), and the 12-item Somatic and Psychological Health Report (SPHERE-12), for young help seekers aged 16-25 (n=30, mean age 19.22 years, 19 males). When first arriving for care, we found that 50% (n=15) of participants experienced severe anxiety (K10 ≥ 30) and were severely depressed (QIDS-A17 ≥ 16). In Session 2, taking attrition rates into account (n=5), we found that 44% (n=11) remained severe across the full battery of questionnaires. When applying multiple regression analyses of the pooled sample of observations (N=55), across both sessions, we found that participants who rated severely anxious avoided making risky decisions. We suggest there is some statistically significant (although weak) (p=0.09) relation between risk and severe anxiety scores as measured by K10. Our findings may support working with novel tools with which to evaluate youth experiencing an emerging mood disorder and their cognitive capacities influencing decision-making.Keywords: anxiety, decision-making, risk, adolescence
Procedia PDF Downloads 1169382 Artificial Law: Legal AI Systems and the Need to Satisfy Principles of Justice, Equality and the Protection of Human Rights
Authors: Begum Koru, Isik Aybay, Demet Celik Ulusoy
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The discipline of law is quite complex and has its own terminology. Apart from written legal rules, there is also living law, which refers to legal practice. Basic legal rules aim at the happiness of individuals in social life and have different characteristics in different branches such as public or private law. On the other hand, law is a national phenomenon. The law of one nation and the legal system applied on the territory of another nation may be completely different. People who are experts in a particular field of law in one country may have insufficient expertise in the law of another country. Today, in addition to the local nature of law, international and even supranational law rules are applied in order to protect basic human values and ensure the protection of human rights around the world. Systems that offer algorithmic solutions to legal problems using artificial intelligence (AI) tools will perhaps serve to produce very meaningful results in terms of human rights. However, algorithms to be used should not be developed by only computer experts, but also need the contribution of people who are familiar with law, values, judicial decisions, and even the social and political culture of the society to which it will provide solutions. Otherwise, even if the algorithm works perfectly, it may not be compatible with the values of the society in which it is applied. The latest developments involving the use of AI techniques in legal systems indicate that artificial law will emerge as a new field in the discipline of law. More AI systems are already being applied in the field of law, with examples such as predicting judicial decisions, text summarization, decision support systems, and classification of documents. Algorithms for legal systems employing AI tools, especially in the field of prediction of judicial decisions and decision support systems, have the capacity to create automatic decisions instead of judges. When the judge is removed from this equation, artificial intelligence-made law created by an intelligent algorithm on its own emerges, whether the domain is national or international law. In this work, the aim is to make a general analysis of this new topic. Such an analysis needs both a literature survey and a perspective from computer experts' and lawyers' point of view. In some societies, the use of prediction or decision support systems may be useful to integrate international human rights safeguards. In this case, artificial law can serve to produce more comprehensive and human rights-protective results than written or living law. In non-democratic countries, it may even be thought that direct decisions and artificial intelligence-made law would be more protective instead of a decision "support" system. Since the values of law are directed towards "human happiness or well-being", it requires that the AI algorithms should always be capable of serving this purpose and based on the rule of law, the principle of justice and equality, and the protection of human rights.Keywords: AI and law, artificial law, protection of human rights, AI tools for legal systems
Procedia PDF Downloads 769381 Competence-Based Human Resources Selection and Training: Making Decisions
Authors: O. Starineca, I. Voronchuk
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Human Resources (HR) selection and training have various implementation possibilities depending on an organization’s abilities and peculiarities. We propose to base HR selection and training decisions about on a competence-based approach. HR selection and training of employees are topical as there is room for improvement in this field; therefore, the aim of the research is to propose rational decision-making approaches for an organization HR selection and training choice. Our proposals are based on the training development and competence-based selection approaches created within previous researches i.e. Analytic-Hierarchy Process (AHP) and Linear Programming. Literature review on non-formal education, competence-based selection, AHP form our theoretical background. Some educational service providers in Latvia offer employees training, e.g. motivation, computer skills, accounting, law, ethics, stress management, etc. that are topical for Public Administration. Competence-based approach is a rational base for rational decision-making in both HR selection and considering HR training.Keywords: competence-based selection, human resource, training, decision-making
Procedia PDF Downloads 3389380 Probing Environmental Sustainability via Brownfield Remediation: A Framework to Manage Brownfields in Ethiopia Lesson to Africa
Authors: Mikiale Gebreslase Gebremariam, Chai Huaqi, Tesfay Gebretsdkan Gebremichael, Dawit Nega Bekele
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In recent years, brownfield redevelopment projects (BRPs) have contributed to the overarching paradigm of the United Nations 2030 agendas. In the present circumstance, most developed nations adopted BRPs, an efficacious urban policy tool. However, in developing and some advanced countries, BRPs are lacking due to limitations of awareness, policy tools, and financial capability for cleaning up brownfield sites. For example, the growth and development of Ethiopian cities were achieved at the cost of poor urban planning, including no community consultations and excessive urbanization for future growth. The demand for land resources is more and more urgent as the result of an intermigration to major cities and towns for socio-economic reasons and population growth. In the past, the development mode of spreading major cities has made horizontal urbanizations stretching outwards. Expansion in search of more land resources, while the outer cities are growing, the inner cities are polluted by environmental pollution. It is noteworthy that the rapid development of cities has not brought about an increase in people's happiness index. Thus, the proposed management framework for managing brownfields in Ethiopia as a lesson to the developing nation facing similar challenges and growth will add immense value in solving the problems and give insights into brownfield land utilization. Under the umbrella of the grey incidence decision-making model and with the consideration of multiple stakeholders and tight environmental and economic constraints, the proposed management framework integrates different criteria from economic, social, environmental, technical, and risk aspects into the grey incidence decision-making model and gives useful guidance to manage brownfields in Ethiopia. Furthermore, it will contribute to the future development of the social economy and the missions of the 2030 UN sustainable development goals.Keywords: Brownfields, environmental sustainability, Ethiopia, grey-incidence decision-making, sustainable urban development
Procedia PDF Downloads 929379 Knowledge Management in the Interactive Portal for Decision Makers on InKOM Example
Authors: K. Marciniak, M. Owoc
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Managers as decision-makers present in different sectors should be supported in efficient and more and more sophisticated way. There are huge number of software tools developed for such users starting from simple registering data from business area – typical for operational level of management – up to intelligent techniques with delivering knowledge - for tactical and strategic levels of management. There is a big challenge for software developers to create intelligent management dashboards allowing to support different decisions. In more advanced solutions there is even an option for selection of intelligent techniques useful for managers in particular decision-making phase in order to deliver valid knowledge-base. Such a tool (called Intelligent Dashboard for SME Managers–InKOM) is prepared in the Business Intelligent framework of Teta products. The aim of the paper is to present solutions assumed for InKOM concerning on management of stored knowledge bases offering for business managers. The paper is managed as follows. After short introduction concerning research context the discussed supporting managers via information systems the InKOM platform is presented. In the crucial part of paper a process of knowledge transformation and validation is demonstrated. We will focus on potential and real ways of knowledge-bases acquiring, storing and validation. It allows for formulation conclusions interesting from knowledge engineering point of view.Keywords: business intelligence, decision support systems, knowledge management, knowledge transformation, knowledge validation, managerial systems
Procedia PDF Downloads 5139378 Modeling the Acquisition of Expertise in a Sequential Decision-Making Task
Authors: Cristóbal Moënne-Loccoz, Rodrigo C. Vergara, Vladimir López, Domingo Mery, Diego Cosmelli
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Our daily interaction with computational interfaces is plagued of situations in which we go from inexperienced users to experts through self-motivated exploration of the same task. In many of these interactions, we must learn to find our way through a sequence of decisions and actions before obtaining the desired result. For instance, when drawing cash from an ATM machine, choices are presented in a step-by-step fashion so that a specific sequence of actions must be performed in order to produce the expected outcome. But, as they become experts in the use of such interfaces, do users adopt specific search and learning strategies? Moreover, if so, can we use this information to follow the process of expertise development and, eventually, predict future actions? This would be a critical step towards building truly adaptive interfaces that can facilitate interaction at different moments of the learning curve. Furthermore, it could provide a window into potential mechanisms underlying decision-making behavior in real world scenarios. Here we tackle this question using a simple game interface that instantiates a 4-level binary decision tree (BDT) sequential decision-making task. Participants have to explore the interface and discover an underlying concept-icon mapping in order to complete the game. We develop a Hidden Markov Model (HMM)-based approach whereby a set of stereotyped, hierarchically related search behaviors act as hidden states. Using this model, we are able to track the decision-making process as participants explore, learn and develop expertise in the use of the interface. Our results show that partitioning the problem space into such stereotyped strategies is sufficient to capture a host of exploratory and learning behaviors. Moreover, using the modular architecture of stereotyped strategies as a Mixture of Experts, we are able to simultaneously ask the experts about the user's most probable future actions. We show that for those participants that learn the task, it becomes possible to predict their next decision, above chance, approximately halfway through the game. Our long-term goal is, on the basis of a better understanding of real-world decision-making processes, to inform the construction of interfaces that can establish dynamic conversations with their users in order to facilitate the development of expertise.Keywords: behavioral modeling, expertise acquisition, hidden markov models, sequential decision-making
Procedia PDF Downloads 2529377 Risk Analysis in Road Transport of Dangerous Goods Using Complex Multi-Criteria Analysis Method
Authors: Zoran Masoničić, Siniša Dragutinović, Ivan Lazović
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In the management and organization of the road transport of dangerous goods, in addition to the existing influential criteria and restrictions that apply to the road transport in general, it is necessary to include an additional criteria related to the safety of people and the environment, considering the danger that comes from the substances being transported. In that manner, the decision making process becomes very complex and rather challenging task that is inherent to the application of complex numerical multi-criteria analysis methods. In this paper some initial results of application of complex analysis method in decision making process are presented. Additionally, the method for minimization or even complete elimination of subjective element in the decision making process is provided. The results obtained can be used in order to point the direction towards some measures have to be applied in order to minimize or completely annihilate the influence of the risk source identified.Keywords: road transport, dangerous goods, risk analysis, risk evaluation
Procedia PDF Downloads 189376 Use of Information Technology in the Government of a State
Authors: Pavel E. Golosov, Vladimir I. Gorelov, Oksana L. Karelova
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There are visible changes in the world organization, environment and health of national conscience that create a background for discussion on possible redefinition of global, state and regional management goals. Authors apply the sustainable development criteria to a hierarchical management scheme that is to lead the world community to non-contradictory growth. Concrete definitions are discussed in respect of decision-making process representing the state mostly. With the help of system analysis it is highlighted how to understand who would carry the distinctive sign of world leadership in the nearest future.Keywords: decision-making, information technology, public administration
Procedia PDF Downloads 5169375 A Study of Permission-Based Malware Detection Using Machine Learning
Authors: Ratun Rahman, Rafid Islam, Akin Ahmed, Kamrul Hasan, Hasan Mahmud
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Malware is becoming more prevalent, and several threat categories have risen dramatically in recent years. This paper provides a bird's-eye view of the world of malware analysis. The efficiency of five different machine learning methods (Naive Bayes, K-Nearest Neighbor, Decision Tree, Random Forest, and TensorFlow Decision Forest) combined with features picked from the retrieval of Android permissions to categorize applications as harmful or benign is investigated in this study. The test set consists of 1,168 samples (among these android applications, 602 are malware and 566 are benign applications), each consisting of 948 features (permissions). Using the permission-based dataset, the machine learning algorithms then produce accuracy rates above 80%, except the Naive Bayes Algorithm with 65% accuracy. Of the considered algorithms TensorFlow Decision Forest performed the best with an accuracy of 90%.Keywords: android malware detection, machine learning, malware, malware analysis
Procedia PDF Downloads 1709374 Strategic Thinking to Enhance Critical Transport Infrastructure and Build Resilience
Authors: Jayantha Withanaarachchi, Sujeeva Setunge, Sara Moridpour
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Gaps in strategic thinking and planning lead to critical transport infrastructure resilience. These gaps in strategic transport and land use development planning have an impact on communities and cities. Natural and man-induced disasters can be catastrophic to communities. After a disaster, many types of critical infrastructure, including transport infrastructure gets un-usable or gets damaged. This paper examines strategic thinking behind the resilience and protection of Critical Transport Infrastructure (CI) within transport networks by investigating the impact of disasters such as bushfires, hurricanes and earthquakes. A detailed analysis of three case studies have been conducted to identify the gaps in strategic transport planning and strategic decision making processes required to mitigate the impacts of disasters. Case studies will be analysed to identify existing gaps in road design, transport planning and decision making. This paper examines the effect of road designing, transport corridors and decision making during transport planning stages and how it impacts transport infrastructure as well as community resilience. A set of recommendations to overcome the shortcomings of existing strategic planning and designing process are presented. This research paper reviews transport infrastructure planning issues and presents the common approach suitable for future strategic thinking and planning which could be adopted in practices.Keywords: community resilience, decision making , infrastructure resilience, strategic transport planning, transport infrastructure
Procedia PDF Downloads 2939373 Terrorism Is a Crime under International Law
Authors: Miguel Manero De Lemos
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The ‘innovative and creative’ seminal decision of the Special Tribunal for Lebanon (STL) was not welcomed by academic opinion. The court recognized that terrorism is a crime under international law in times of peace. Scholars widely – and sometimes aggressively – criticize this conclusion. This article asserts that, while some aspects of the decision of the STL might be defective, the basic premise, that it is indeed such a crime, is sound. This article delves into the method that the court used to attain such an outcome and explains why the conclusion of the court is correct, albeit the use of a different method is to be preferred. It also argues that subsequent developments leave little room to keep arguing that there is no international crime of terrorism.Keywords: terrorism, STL, crime, international criminal law
Procedia PDF Downloads 3319372 Inverse Polynomial Numerical Scheme for the Solution of Initial Value Problems in Ordinary Differential Equations
Authors: Ogunrinde Roseline Bosede
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This paper presents the development, analysis and implementation of an inverse polynomial numerical method which is well suitable for solving initial value problems in first order ordinary differential equations with applications to sample problems. We also present some basic concepts and fundamental theories which are vital to the analysis of the scheme. We analyzed the consistency, convergence, and stability properties of the scheme. Numerical experiments were carried out and the results compared with the theoretical or exact solution and the algorithm was later coded using MATLAB programming language.Keywords: differential equations, numerical, polynomial, initial value problem, differential equation
Procedia PDF Downloads 4489371 Thai Tourists’ Satisfaction and Tourist’s Decision Making Process in Southern of Thailand
Authors: Rewadee Waiyawassana
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The objectives of the research on Thai tourists’ satisfaction of visiting Southern of Thailand are i) to study the Thai tourists’ satisfaction who select southern of Thailand as their destinations ii) to study their tourist’s decision making process in Southern of Thailand. The samples of the study are 619 Thai visitors at Southern of Thailand by accidental sampling technic and focus group interview for 12 key informant by purposive sampling. The data analysis includes Percentage, Frequency and One-way ANOVA. The findings from the research are the satisfaction of Thai visitors on southern of Thailand ranks from the resources of the destination, transportation, convenience, security, and promotion and public relations; with the high level of satisfaction on all the factors the government or responsible agencies should also modernize the marketing and public relation with increasing public relations, the potential visitors shall be updated with new information and alternative tourist destination also.Keywords: public relations, Southern of Thailand, Thai Tourists’ satisfaction, Tourist’s decision making process
Procedia PDF Downloads 3289370 Supplier Selection Using Sustainable Criteria in Sustainable Supply Chain Management
Authors: Richa Grover, Rahul Grover, V. Balaji Rao, Kavish Kejriwal
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Selection of suppliers is a crucial problem in the supply chain management. On top of that, sustainable supplier selection is the biggest challenge for the organizations. Environment protection and social problems have been of concern to society in recent years, and the traditional supplier selection does not consider about this factor; therefore, this research work focuses on introducing sustainable criteria into the structure of supplier selection criteria. Sustainable Supply Chain Management (SSCM) is the management and administration of material, information, and money flows, as well as coordination among business along the supply chain. All three dimensions - economic, environmental, and social - of sustainable development needs to be taken care of. Purpose of this research is to maximize supply chain profitability, maximize social wellbeing of supply chain and minimize environmental impacts. Problem statement is selection of suppliers in a sustainable supply chain network by ranking the suppliers against sustainable criteria identified. The aim of this research is twofold: To find out what are the sustainable parameters that can be applied to the supply chain, and to determine how these parameters can effectively be used in supplier selection. Multicriteria decision making tools will be used to rank both criteria and suppliers. AHP Analysis will be used to find out ratings for the criteria identified. It is a technique used for efficient decision making. TOPSIS will be used to find out rating for suppliers and then ranking them. TOPSIS is a MCDM problem solving method which is based on the principle that the chosen option should have the maximum distance from the negative ideal solution (NIS) and the minimum distance from the ideal solution.Keywords: sustainable supply chain management, sustainable criteria, MCDM tools, AHP analysis, TOPSIS method
Procedia PDF Downloads 3259369 Differences in Patient Satisfaction Observed between Female Japanese Breast Cancer Patients Who Receive Breast-Conserving Surgery or Total Mastectomy
Authors: Keiko Yamauchi, Motoyuki Nakao, Yoko Ishihara
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The increase in the number of women with breast cancer in Japan has required hospitals to provide a higher quality of medicine so that patients are satisfied with the treatment they receive. However, patients’ satisfaction following breast cancer treatment has not been sufficiently studied. Hence, we investigated the factors influencing patient satisfaction following breast cancer treatment among Japanese women. These women underwent either breast-conserving surgery (BCS) (n = 380) or total mastectomy (TM) (n = 247). In March 2016, we conducted a cross-sectional internet survey of Japanese women with breast cancer in Japan. We assessed the following factors: socioeconomic status, cancer-related information, the role of medical decision-making, the degree of satisfaction regarding the treatments received, and the regret arising from the medical decision-making processes. We performed logistic regression analyses with the following dependent variables: extreme satisfaction with the treatments received, and regret regarding the medical decision-making process. For both types of surgery, the odds ratio (OR) of being extremely satisfied with the cancer treatment was significantly higher among patients who did not have any regrets compared to patients who had. Also, the OR tended to be higher among patients who chose to play a wanted role in the medical decision-making process, compared with patients who did not. In the BCS group, the OR of being extremely satisfied with the treatment was higher if, at diagnosis, the patient’s youngest child was older than 19 years, compared with patients with no children. The OR was also higher if patient considered the stage and characteristics of their cancer significant. The OR of being extremely satisfied with the treatments was lower among patients who were not employed on full-time basis, and among patients who considered the second medical opinions and medical expenses to be significant. These associations were not observed in the TM group. The OR of having regrets regarding the medical decision-making process was higher among patients who chose to play a role in the decision-making process as they preferred, and was also higher in patients who were employed on either a part-time or contractual basis. For both types of surgery, the OR was higher among patients who considered a second medical opinion to be significant. Regardless of surgical type, regret regarding the medical decision-making process decreases treatment satisfaction. Patients who received breast-conserving surgery were more likely to have regrets concerning the medical decision-making process if they could not play a role in the process as they preferred. In addition, factors associated with the satisfaction with treatment in BCS group but not TM group included the second medical opinion, medical expenses, employment status, and age of the youngest child at diagnosis.Keywords: medical decision making, breast-conserving surgery, total mastectomy, Japanese
Procedia PDF Downloads 1499368 A New Multi-Target, Multi-Agent Search and Rescue Path Planning Approach
Authors: Jean Berger, Nassirou Lo, Martin Noel
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Perfectly suited for natural or man-made emergency and disaster management situations such as flood, earthquakes, tornadoes, or tsunami, multi-target search path planning for a team of rescue agents is known to be computationally hard, and most techniques developed so far come short to successfully estimate optimality gap. A novel mixed-integer linear programming (MIP) formulation is proposed to optimally solve the multi-target multi-agent discrete search and rescue (SAR) path planning problem. Aimed at maximizing cumulative probability of successful target detection, it captures anticipated feedback information associated with possible observation outcomes resulting from projected path execution, while modeling agent discrete actions over all possible moving directions. Problem modeling further takes advantage of network representation to encompass decision variables, expedite compact constraint specification, and lead to substantial problem-solving speed-up. The proposed MIP approach uses CPLEX optimization machinery, efficiently computing near-optimal solutions for practical size problems, while giving a robust upper bound obtained from Lagrangean integrality constraint relaxation. Should eventually a target be positively detected during plan execution, a new problem instance would simply be reformulated from the current state, and then solved over the next decision cycle. A computational experiment shows the feasibility and the value of the proposed approach.Keywords: search path planning, search and rescue, multi-agent, mixed-integer linear programming, optimization
Procedia PDF Downloads 3729367 Discrete State Prediction Algorithm Design with Self Performance Enhancement Capacity
Authors: Smail Tigani, Mohamed Ouzzif
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This work presents a discrete quantitative state prediction algorithm with intelligent behavior making it able to self-improve some performance aspects. The specificity of this algorithm is the capacity of self-rectification of the prediction strategy before the final decision. The auto-rectification mechanism is based on two parallel mathematical models. In one hand, the algorithm predicts the next state based on event transition matrix updated after each observation. In the other hand, the algorithm extracts its residues trend with a linear regression representing historical residues data-points in order to rectify the first decision if needs. For a normal distribution, the interactivity between the two models allows the algorithm to self-optimize its performance and then make better prediction. Designed key performance indicator, computed during a Monte Carlo simulation, shows the advantages of the proposed approach compared with traditional one.Keywords: discrete state, Markov Chains, linear regression, auto-adaptive systems, decision making, Monte Carlo Simulation
Procedia PDF Downloads 4989366 Modelling Mode Choice Behaviour Using Cloud Theory
Authors: Leah Wright, Trevor Townsend
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Mode choice models are crucial instruments in the analysis of travel behaviour. These models show the relationship between an individual’s choice of transportation mode for a given O-D pair and the individual’s socioeconomic characteristics such as household size and income level, age and/or gender, and the features of the transportation system. The most popular functional forms of these models are based on Utility-Based Choice Theory, which addresses the uncertainty in the decision-making process with the use of an error term. However, with the development of artificial intelligence, many researchers have started to take a different approach to travel demand modelling. In recent times, researchers have looked at using neural networks, fuzzy logic and rough set theory to develop improved mode choice formulas. The concept of cloud theory has recently been introduced to model decision-making under uncertainty. Unlike the previously mentioned theories, cloud theory recognises a relationship between randomness and fuzziness, two of the most common types of uncertainty. This research aims to investigate the use of cloud theory in mode choice models. This paper highlights the conceptual framework of the mode choice model using cloud theory. Merging decision-making under uncertainty and mode choice models is state of the art. The cloud theory model is expected to address the issues and concerns with the nested logit and improve the design of mode choice models and their use in travel demand.Keywords: Cloud theory, decision-making, mode choice models, travel behaviour, uncertainty
Procedia PDF Downloads 3899365 Investigating Problems and Social Support for Mothers of Poor Households
Authors: Niken Hartati
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This study provides a description of the problem and sources of social support that given to 90 mothers from poor households. Data were collected using structured interviews with the three main questions: 1) what kind of problem in mothers daily life, 2) to whom mothers ask for help to overcome it and 3) the form of the assistances that provided. Furthermore, the data were analyzed using content analysis techniques were then coded and categorized. The results of the study illustrate the problems experienced by mothers of poor households in the form of: subsistence (37%), child care (27%), management of money and time (20%), housework (5%), bad place of living (5%), the main breadwinner (3%), and extra costs (3%). While the sources of social support that obtained by mothers were; neighbors (10%), extended family (8%), children (8%), husband (7%), parents (7%), and siblings (5%). Unfortunately, more mothers who admitted not getting any social support when having problems (55%). The form of social support that given to mother from poor household were: instrumental support (91%), emotional support (5%) and informational support (2%). Implications for further intervention also discussed in this study.Keywords: household problems, social support, mothers, poor households
Procedia PDF Downloads 3669364 The Role of Artificial Intelligence in Criminal Procedure
Authors: Herke Csongor
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The artificial intelligence (AI) has been used in the United States of America in the decisionmaking process of the criminal justice system for decades. In the field of law, including criminal law, AI can provide serious assistance in decision-making in many places. The paper reviews four main areas where AI still plays a role in the criminal justice system and where it is expected to play an increasingly important role. The first area is the predictive policing: a number of algorithms are used to prevent the commission of crimes (by predicting potential crime locations or perpetrators). This may include the so-called linking hot-spot analysis, crime linking and the predictive coding. The second area is the Big Data analysis: huge amounts of data sets are already opaque to human activity and therefore unprocessable. Law is one of the largest producers of digital documents (because not only decisions, but nowadays the entire document material is available digitally), and this volume can only and exclusively be handled with the help of computer programs, which the development of AI systems can have an increasing impact on. The third area is the criminal statistical data analysis. The collection of statistical data using traditional methods required enormous human resources. The AI is a huge step forward in that it can analyze the database itself, based on the requested aspects, a collection according to any aspect can be available in a few seconds, and the AI itself can analyze the database and indicate if it finds an important connection either from the point of view of crime prevention or crime detection. Finally, the use of AI during decision-making in both investigative and judicial fields is analyzed in detail. While some are skeptical about the future role of AI in decision-making, many believe that the question is not whether AI will participate in decision-making, but only when and to what extent it will transform the current decision-making system.Keywords: artificial intelligence, international criminal cooperation, planning and organizing of the investigation, risk assessment
Procedia PDF Downloads 429363 Hybrid Weighted Multiple Attribute Decision Making Handover Method for Heterogeneous Networks
Authors: Mohanad Alhabo, Li Zhang, Naveed Nawaz
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Small cell deployment in 5G networks is a promising technology to enhance capacity and coverage. However, unplanned deployment may cause high interference levels and high number of unnecessary handovers, which in turn will result in an increase in the signalling overhead. To guarantee service continuity, minimize unnecessary handovers, and reduce signalling overhead in heterogeneous networks, it is essential to properly model the handover decision problem. In this paper, we model the handover decision according to Multiple Attribute Decision Making (MADM) method, specifically Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). In this paper, we propose a hybrid TOPSIS method to control the handover in heterogeneous network. The proposed method adopts a hybrid weighting, which is a combination of entropy and standard deviation. A hybrid weighting control parameter is introduced to balance the impact of the standard deviation and entropy weighting on the network selection process and the overall performance. Our proposed method shows better performance, in terms of the number of frequent handovers and the mean user throughput, compared to the existing methods.Keywords: handover, HetNets, interference, MADM, small cells, TOPSIS, weight
Procedia PDF Downloads 1509362 Good Practices for Model Structure Development and Managing Structural Uncertainty in Decision Making
Authors: Hossein Afzali
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Increasingly, decision analytic models are used to inform decisions about whether or not to publicly fund new health technologies. It is well noted that the accuracy of model predictions is strongly influenced by the appropriateness of model structuring. However, there is relatively inadequate methodological guidance surrounding this issue in guidelines developed by national funding bodies such as the Australian Pharmaceutical Benefits Advisory Committee (PBAC) and The National Institute for Health and Care Excellence (NICE) in the UK. This presentation aims to discuss issues around model structuring within decision making with a focus on (1) the need for a transparent and evidence-based model structuring process to inform the most appropriate set of structural aspects as the base case analysis; (2) the need to characterise structural uncertainty (If there exist alternative plausible structural assumptions (or judgements), there is a need to appropriately characterise the related structural uncertainty). The presentation will provide an opportunity to share ideas and experiences on how the guidelines developed by national funding bodies address the above issues and identify areas for further improvements. First, a review and analysis of the literature and guidelines developed by PBAC and NICE will be provided. Then, it will be discussed how the issues around model structuring (including structural uncertainty) are not handled and justified in a systematic way within the decision-making process, its potential impact on the quality of public funding decisions, and how it should be presented in submissions to national funding bodies. This presentation represents a contribution to the good modelling practice within the decision-making process. Although the presentation focuses on the PBAC and NICE guidelines, the discussion can be applied more widely to many other national funding bodies that use economic evaluation to inform funding decisions but do not transparently address model structuring issues e.g. the Medical Services Advisory Committee (MSAC) in Australia or the Canadian Agency for Drugs and Technologies in Health.Keywords: decision-making process, economic evaluation, good modelling practice, structural uncertainty
Procedia PDF Downloads 1879361 Understanding Cruise Passengers’ On-board Experience throughout the Customer Decision Journey
Authors: Sabina Akter, Osiris Valdez Banda, Pentti Kujala, Jani Romanoff
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This paper examines the relationship between on-board environmental factors and customer overall satisfaction in the context of the cruise on-board experience. The on-board environmental factors considered are ambient, layout/design, social, product/service and on-board enjoyment factors. The study presents a data-driven framework and model for the on-board cruise experience. The data are collected from 893 respondents in an application of a self-administered online questionnaire of their cruise experience. This study reveals the cruise passengers’ on-board experience through the customer decision journey based on the publicly available data. Pearson correlation and regression analysis have been applied, and the results show a positive and a significant relationship between the environmental factors and on-board experience. These data help understand the cruise passengers’ on-board experience, which will be used for the ultimate decision-making process in cruise ship design.Keywords: cruise behavior, customer activities, on-board environmental factors, on-board experience, user or customer satisfaction
Procedia PDF Downloads 1699360 Disclosure Experience of Working People Living with HIV/AIDS in Nigeria: A Qualitative Research
Authors: Dorcas I. Adeoye
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Disclosure experience of people living with HIV/AIDS has been a public health concern, it has also been attributed to effective way of limiting the spread of the disease. However, among working people living with HIV, it is a great issue that attracts several consequences, it is also a way of managing HIV and balancing their emotional, physical and social aspect of life. The economic, social and political aspect has been affected since the emergent of HIV. It is also not a medical problem that only needs a medical approach; it is a psychological problem that needs not to be ignored. Work attitude model and consequential theory were used to understanding the experience of disclosure or non-disclosure in the workplace. Work attitude model explains the job satisfaction and the organisational commitment of an employee that have effect on the decision and well-being in the workplace; it can also influence a decision to disclosure one’s health condition, however, consequential theory comes to play when a decision is being made, either to disclose or not, and that will attract consequences (either negative or positive) in which ever decision made. A phenomenological study was conducted among employed people that are infected with HIV/AIDS in a south-eastern region of Nigeria where unemployment rate is high. A one-to-one semi-structured interview was used to gather in-depth information about the experience of 20 working people living with HIV. Participants were recruited in a hospital and for some, hospital serves as their workplace. The outcome of the research shows that participants’ experiences vary. One thing that stood out and was found similar among all participants including participants that have disclosed, planning to disclose, or never intended to disclose, is that workplace is a place not to be trusted despite the positive outcomes disclosure could give in the workplace, and disclosure decision needs to be carefully taken. The study was concluded with recommendations that cover various aspects; however, clearer policies should be followed by all organisations to protect people living with HIV in the workplace.Keywords: disclosure, employment, HIV/AIDS, Nigeria, workplace
Procedia PDF Downloads 3059359 Child Protection Decision Making in England and Finland: A Comparative Analysis
Authors: Rachel Falconer
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Background: The United Nations Convention on the Rights of the Child sets out the duties placed on signatory nations to take measures to protect children from all forms of violence, abuse, neglect and maltreatment. The systems for ensuring this protection vary globally, shaped by national welfare policies. In England and Finland, past research has highlighted differences in how child protection issues are framed and how state agencies respond. However, less is known about how such differences impact processes of social work judgment and decision making in practice. Method: Data was collected as part of a wider PhD project in three stages. First, social workers in sites across England and Finland were asked to complete a short questionnaire. Participants were then asked to comment on two constructed case vignettes, and were interviewed about their experiences of child protection decision making at the point of referral. Interviews were analyzed using NVivo to draw out key themes. Findings: There were similarities in how the English and Finnish social workers responded to the case vignettes; for example, participants in both countries expressed concerns about similar risk factors and all felt further assessment was needed. Differences were observed, in particular, in regard to the sources of support and guidance participants referred to, with the English social workers appearing to rely more upon managerial input for their decisions than the Finnish social workers. These findings suggest evidence for two distinct decision making approaches: ‘supervised’ and ‘supported’ judgement. Implications for practice: The findings have relevance to the conference theme of research and evaluation of social work practice, and support the findings of previous studies that have emphasized the significance of organizational factors in child protection decision making. The comparative methodology has also helped to demonstrate how organizational factors can influence practice in different child protection system ‘orientations’. The presentation will discuss the potential practice implications of ‘supervised’, manager-led approaches to decision making as contrasted with ‘supported’, team-led approaches, inviting discussion about the relevance of these findings for social work in other countries.Keywords: child protection, comparative research, decision making, social work, vignettes
Procedia PDF Downloads 2539358 Analytic Hierarchy Process for the Container Terminal Choice from Multiple Terminals within the Port of Colombo
Authors: G. M. B. P. Abeysekara, W. A. D. C. Wijerathna
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Terminal choice from the multiple terminals region is not a simple decision and it is very complex, because shipping lines should consider on influential factors for the terminal choice at once according to their requirement. Therefore, terminal choice is a multiple criterion decision making (MCDM) situation under a specially designed decision hierarchy. Identification of perspective of shipping lines regarding terminal choice is vital important for the decision makers regarding container terminals. Thus this study is evaluated perception on main and feeder shipping lines’ regarding port of Colombo container terminals, and ranked terminals according to shipping lines preference. Analytic Hierarchy Process (AHP) model is adapted to this study, since it has features similar to the MCDM, it is weighted every influential factor by using pair wise comparisons, and consistency of the decision makers’ judgments are checked to evaluate trustworthiness of gathered data. And rating method is used to rank the terminals within Port of Colombo by assigning particular preference values with respect to the criteria and sub criteria. According to the findings of this study, main lines’ mainly concern on water depth of approach channel, depth of berth, handling charges and handling equipment facilities. And feeder lines’ main concerns were handling equipment facilities, loading and discharging efficiency, depth of berth and handling charges. Findings of the study suggested concentrating regarding the emphasized areas in order to enhance the competitiveness of terminals, and to increase number of vessel callings at the Port of Colombo. Application of above finding of the terminals within Port of Colombo lead to a far better competition among terminals and would uplift the overall level of services.Keywords: AHP, Main and feeder shipping lines, criteria, sub criteria
Procedia PDF Downloads 4219357 Problems Encountered in Teaching English as a Second Language in Asia
Authors: Geraldine Agbor Ojong
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This paper conveys some of the problems teachers of ESL face in classroom settings in Thailand. The results of this paper is achieved through close and open ended questionaires administered to a group of English language teachers of three prominent schools in Kaengkhoi, saraburi Province, Thailand.(Saengvithaya school, kaengkhoi school and Pytoon withaya school). Face to face interview of some foreign teachers and students selected randomly And general observation. The data was analysed by frequency distribution and percentage: The result of the study may be generalized so that the conference committee can suggest possible solutions or give contributing ideas on how to handle some of these problems.Keywords: Asian, colonize, ESL, foreign country
Procedia PDF Downloads 443