Search results for: model for making decisions in emergencies

Authors: Yaojun Wang, Yaoqing Wang

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Stock selection is an important decision-making problem. Many machine learning and data mining technologies are employed to build automatic stock-selection system. A profitable stock-selection system should consider the stock’s investment value and the market timing. In this paper, we present a hybrid system including both engage for stock selection. This system uses a case-based reasoning (CBR) model to execute the stock classification, uses a decision-tree model to help with market timing and stock selection. The experiments show that the performance of this hybrid system is better than that of other techniques regarding to the classification accuracy, the average return and the Sharpe ratio.

Keywords: case-based reasoning, decision tree, stock selection, machine learning

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Authors: Teklay Tesfay, Gebreyesus Brhane Tesfahunegn, Abadi Berhane, Selemawit Girmay

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Adjusting the proper sowing date of a crop at a particular location with a changing climate is an essential management option to maximize crop yield. However, determining the optimum sowing date for rainfed maize production through field experimentation requires repeated trials for many years in different weather conditions and crop management. To avoid such long-term experimentation to determine the optimum sowing date, crop models such as AquaCrop are useful. Therefore, the overall objective of this study was to evaluate the performance of AquaCrop model in simulating maize productivity under varying sowing dates. A field experiment was conducted for two consecutive cropping seasons by deploying four maize seed sowing dates in a randomized complete block design with three replications. Input data required to run this model are stored as climate, crop, soil, and management files in the AquaCrop database and adjusted through the user interface. Observed data from separate field experiments was used to calibrate and validate the model. AquaCrop model was validated for its performance in simulating the green canopy and aboveground biomass of maize for the varying sowing dates based on the calibrated parameters. Results of the present study showed that there was a good agreement (an overall R2 =, Ef= d= RMSE =) between measured and simulated values of the canopy cover and biomass yields. Considering the overall values of the statistical test indicators, the performance of the model to predict maize growth and biomass yield was successful, and so this is a valuable tool help for decision-making. Hence, this calibrated and validated model is suggested to use for determining optimum maize crop sowing date for similar climate and soil conditions to the study area, instead of conducting long-term experimentation.

Keywords: AquaCrop model, calibration, validation, simulation

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Authors: Tofigh Hamidavi, Sepehr Abrishami, Pasquale Ponterosso, David Begg

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Structural design and analysis is an important and time-consuming process, particularly at the conceptual design stage. Decisions made at this stage can have an enormous effect on the entire project, as it becomes ever costlier and more difficult to alter the choices made early on in the construction process. Hence, optimisation of the early stages of structural design can provide important efficiencies in terms of cost and time. This paper suggests a structural design optimisation (SDO) framework in which Genetic Algorithms (GAs) may be used to semi-automate the production and optimisation of early structural design alternatives. This framework has the potential to leverage conceptual structural design innovation in Architecture, Engineering and Construction (AEC) projects. Moreover, this framework improves the collaboration between the architectural stage and the structural stage. It will be shown that this SDO framework can make this achievable by generating the structural model based on the extracted data from the architectural model. At the moment, the proposed SDO framework is in the process of validation, involving the distribution of an online questionnaire among structural engineers in the UK.

Keywords: building information, modelling, BIM, genetic algorithm, GA, architecture-engineering-construction, AEC, optimisation, structure, design, population, generation, selection, mutation, crossover, offspring

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Authors: F. Jiménez, R. Jódar, M. Martín, G. Sánchez, G. Sciavicco

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Abstract—Attribute or feature selection is one of the basic strategies to improve the performances of data classification tasks, and, at the same time, to reduce the complexity of classifiers, and it is a particularly fundamental one when the number of attributes is relatively high. Its application to unsupervised classification is restricted to a limited number of experiments in the literature. Evolutionary computation has already proven itself to be a very effective choice to consistently reduce the number of attributes towards a better classification rate and a simpler semantic interpretation of the inferred classifiers. We present a feature selection wrapper model composed by a multi-objective evolutionary algorithm, the clustering method Expectation-Maximization (EM), and the classifier C4.5 for the unsupervised classification of data extracted from a psychological test named BASC-II (Behavior Assessment System for Children - II ed.) with two objectives: Maximizing the likelihood of the clustering model and maximizing the accuracy of the obtained classifier. We present a methodology to integrate feature selection for unsupervised classification, model evaluation, decision making (to choose the most satisfactory model according to a a posteriori process in a multi-objective context), and testing. We compare the performance of the classifier obtained by the multi-objective evolutionary algorithms ENORA and NSGA-II, and the best solution is then validated by the psychologists that collected the data.

Keywords: evolutionary computation, feature selection, classification, clustering

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Authors: Le Kang

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According to the nature of the university, as a free and responsible academic community, USR is based on a different foundation —academic responsibility, so the Pyramid and the IC Model of CSR could not fully explain the most distinguished feature of USR. This paper sought to put forward a new model— Ferris Wheel Model, to illustrate the nature of USR and the process of achievement. The Ferris Wheel Model of USR shows the university creates a balanced, fairness and neutrality systemic structure to afford social responsibilities; that makes the organization could obtain a synergistic effect to achieve more extensive interests of stakeholders and wider social responsibilities.

Keywords: USR, achievement model, ferris wheel model, social responsibilities

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Authors: Anastasia Rita Widiarti, Agus Harjoko, Marsono, Sri Hartati

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This paper presents the results of a study to test whether the Javanese character manuscript image preprocessing model that have been more widely applied, can also be applied to segment of the Batak characters manuscripts. The treatment process begins by converting the input image into a binary image. After the binary image is cleaned of noise, then the segmentation lines using projection profile is conducted. If unclear histogram projection is found, then the smoothing process before production indexes line segments is conducted. For each line image which has been produced, then the segmentation scripts in the line is applied, with regard of the connectivity between pixels which making up the letters that there is no characters are truncated. From the results of manuscript preprocessing system prototype testing, it is obtained the information about the system truth percentage value on pieces of Pustaka Batak Podani Ma AjiMamisinon manuscript ranged from 65% to 87.68% with a confidence level of 95%. The value indicates the truth percentage shown the initial processing model in Javanese characters manuscript image can be applied also to the image of the Batak characters manuscript.

Keywords: connected component, preprocessing, manuscript image, projection profiles

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Authors: Alireza Shahraki, Kaveh Keshmiry Zadeh

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Total quality management in libraries is of particular importance because high-quality libraries can facilitate the sustained development process in countries. This study has been conducted to examine the feasibility of implementation of total quality management in libraries of Sistan and Baluchestan and to provide an appropriate model for this concern. All of the officials and employees of Sistan and Baluchestan libraries (23 individuals) constitute the population of the study. Data gathering tool is a questionnaire that is designated based on ISO9000. The data extracted from questionnaires were analyzed using SPSS software. Results indicate that the highest degree of conformance to the 8 principles of ISO9000 is attributed to the principle of 'users' (69.9%) and the lowest degree is associated with 'decision making based on facts' (39.1%). Moreover, a significant relationship was observed among the items (1 and 3), (2 and 5), (2 and 7), (3 and 5), (4 and 5), (4 and 7), (4 and 8), (5 and 7), and (7 and 8). According to the research findings, it can generally be said that it is not eligible now to utilize TQM in libraries of Sistan and Baluchestan.

Keywords: quality management, total quality, university libraries, libraries management

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Authors: Christina Zourna, Ioanna Papavassiliou-Alexiou

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The purpose of this multi-phased action research PhD study in Greece was to investigate if and how Drama in Education (DiE) – used as an innovative group counselling method – may have positive effects on secondary education students’career self-efficacy and career decision-making skills development. Using both quantitative and qualitative research tools, high quality data were gathered at various stages of the research and were analysed through multivariate methods and open-source computer aided data analysis software such as R Studio, QualCoder, and SPSS packages. After a five-month-long educational intervention based on DiE method, it was found that 9th, 10th, and 11th gradersameliorated their self-efficacy and learned the process of making an informed career decision – through targeted information gathering about themselves and possible study paths – thus, developing career problem-solving and career management skills. Gender differences were non statistically important, while differences in grades showed a minor influence on some of the measured factorssuch as general career indecisiveness and self-evaluation. Students in the 11th grade scored significantly higher than younger students in the career self-efficacy scale and have stronger faith in their abilities e.g., choosing general over vocational school and major study orientation. The study has shown that DiE can be effective in group career guidance, especially concerning the pillars of self-awareness, self-efficacy, and career decision-making processes.

Keywords: career decision-making skills, career self-efficacy, CDDQ scale, CDMSE-SF scale, drama in education method

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Authors: Irtaza M. Syed, Kaamran Raahemifar

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This paper presents a model predictive control (MPC) of a utility interactive three phase inverter (TPI) for a photovoltaic (PV) system at commercial level. The proposed model uses phase locked loop (PLL) to synchronize TPI with the power electric grid (PEG) and performs MPC control in a dq reference frame. TPI model consists of boost converter (BC), maximum power point tracking (MPPT) control, and a three leg voltage source inverter (VSI). Operational model of VSI is used to synthesize sinusoidal current and track the reference. Model is validated using a 35.7 kW PV system in Matlab/Simulink. Implementation and results show simplicity and accuracy, as well as reliability of the model.

Keywords: model predictive control, three phase voltage source inverter, PV system, Matlab/simulink

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Authors: Mohit Kumar, Mayur Betharia

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Healthcare domain, with the emergence of Electronic Medical Record (EMR), collects a lot of data which have been attracting Data Mining expert’s interest. In the past, doctors have relied on their intuition while making critical clinical decisions. This paper presents the means to analyze the Medical workflows to get business insights out of huge dumped medical databases. Market Basket Analysis (MBA) which is a special data mining technique, has been widely used in marketing and e-commerce field to discover the association between products bought together by customers. It helps businesses in increasing their sales by analyzing the purchasing behavior of customers and pitching the right customer with the right product. This paper is an attempt to demonstrate Market Basket Analysis applications in healthcare. In particular, it discusses the Market Basket Analysis Algorithm ‘Apriori’ applications within healthcare in major areas such as analyzing the workflow of diagnostic procedures, Up-selling and Cross-selling of Healthcare Systems, designing healthcare systems more user-friendly. In the paper, we have demonstrated the MBA applications using Angiography Systems, but can be extrapolated to other modalities as well.

Keywords: data mining, market basket analysis, healthcare applications, knowledge discovery in healthcare databases, customer relationship management, healthcare systems

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Authors: Laura V. Gonzalez, Juan B. Duarte, Luis A. Palacio

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Decision making can be conditioned by factors such as the environments, circumstances, behavioral biases, emotions, beliefs and preferences of the participants. The objective of this paper is to analyze the effect ‘amount of information’ and ‘number of options’, on the behavior of competitors under a bilateral negotiation context. For the above, it has been designed an experiment as a classroom game where they negotiate goods, under the condition that none of the players knows exactly the real value of the asset. The game is designed under the concept of zero-sum (non-cooperative game) and focuses on the fact that agents must anticipate the strategies of their opponent to improve their chances of winning in the negotiation. The empirical results show that, contrary to the traditional view of expected utility theory, players prefer to obtain low profits and losses, when faced with a higher expectation of losses, using sub-optimal strategies not in accordance with game theory.

Keywords: bilateral negotiation, classroom game, decision making, game theory

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Authors: Héctor Rivera-Gómez, Eva Selene Hernández-Gress, Oscar Montaño-Arango, Jose Ramon Corona-Armenta

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This research studies the joint production, maintenance and subcontracting control policy for an unreliable deteriorating manufacturing system. Production activities are controlled by a derivation of the Hedging Point Policy, and given that the system is subject to deterioration, it reduces progressively its capacity to satisfy product demand. Multiple deterioration effects are considered, reflected mainly in the quality of the parts produced and the reliability of the machine. Subcontracting is available as support to satisfy product demand; also overhaul maintenance can be conducted to reduce the effects of deterioration. The main objective of the research is to determine simultaneously the production, maintenance and subcontracting rate which minimize the total incurred cost. A stochastic dynamic programming model is developed and solved through a simulation-based approach composed of statistical analysis and optimization with the response surface methodology. The obtained results highlight the strong interactions between production, deterioration and quality which justify the development of an integrated model. A numerical example and a sensitivity analysis are presented to validate our results.

Keywords: subcontracting, optimal control, deterioration, simulation, production planning

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Authors: Jesugnon E. A. Kpodo, Aurlus D. Ouindeyama, Jan H. Sommer, Fifanou G. Vodouhe, Kolo Yeo

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Local communities are recognized as key actors for sustainable land use and to some extent actors driving land use land cover (LULC) change around protected areas. Understanding drivers responsible for these changes are very crucial for better policy decisions making. This study analyzed perception of 425 local people in 28 villages towards land cover change around Pendjari Biosphere Reserve using semi-structured questionnaire. 72.9% of local communities perceive land cover as degrading while 24.5% as improving and only 2.6% as stable during the five last years. Women perceived more land cover degradation than men do (84.1 vs. 67.1%). Local communities identified cultivated land expansion, logging, firewood collection, charcoal production, population growth, and poverty as the key drivers of declined LULC in the study area. Education has emerged as a significant factor influencing respondents’ perceptions of these drivers of LULC changes. Appropriate management measures and government policies should be implemented around Pendjari Biosphere Reserve to control drivers of LULC change.

Keywords: local perceptions, LULC drivers, LULC dynamics, Pendjari Biosphere Reserve, rural livelihoods, sustainable resource management

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Authors: Serhat Tuzun, Tufan Demirel

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Multi-Criteria Decision Making (MCDM) is the modelling of real-life to solve problems we encounter. It is a discipline that aids decision makers who are faced with conflicting alternatives to make an optimal decision. MCDM problems can be classified into two main categories: Multi-Attribute Decision Making (MADM) and Multi-Objective Decision Making (MODM), based on the different purposes and different data types. Although various MADM techniques were developed for the problems encountered, their methodology is limited in modelling real-life. Moreover, objective results are hard to obtain, and the findings are generally derived from subjective data. Although, new and modified techniques are developed by presenting new approaches such as fuzzy logic; comprehensive techniques, even though they are better in modelling real-life, could not find a place in real world applications for being hard to apply due to its complex structure. These constraints restrict the development of MADM. This study aims to conduct a comprehensive analysis of preference methods in MADM and propose an approach based on information. For this purpose, a detailed literature review has been conducted, current approaches with their advantages and disadvantages have been analyzed. Then, the approach has been introduced. In this approach, performance values of the criteria are calculated in two steps: first by determining the distribution of each attribute and standardizing them, then calculating the information of each attribute as informational energy.

Keywords: literature review, multi-attribute decision making, operations research, preference method, informational energy

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Authors: Amreth Chandrasehar

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Machine Learning (ML) Models are developed and run in production to solve various use cases that help organizations to be more efficient and help drive the business. But this comes at a massive development cost and lost business opportunities. According to the Gartner report, 85% of data science projects fail, and one of the factors impacting this is not paying attention to Model Observability. Model Observability helps the developers and operators to pinpoint the model performance issues data drift and help identify root cause of issues. This paper focuses on providing insights into incorporating model observability in model development and operationalizing it in production.

Keywords: model observability, monitoring, drift detection, ML observability platform

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Authors: Omar Mayyas

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Clinical decision-making (CDM) is essential to community health nursing (CHN) education. For this reason, nursing educators are responsible for developing these skills among nursing students because nursing students are exposed to highly critical conditions after graduation. However, due to limited exposure to real-world situations, many nursing students need help developing clinical decision-making skills in this area. Therefore, the impact of Virtual Simulation (VS) on community health nursing students' clinical decision-making in nursing education has to be investigated. This study aims to examine the difference in CDM ability among CHN students who received traditional education compared to those who received VS classes, to identify the factors that may influence CDM ability differences between CHN students who received a traditional education and VS classes, and to provide recommendations for educational programs that can enhance the CDM ability of CHN students and improve the quality of care provided in community settings. A mixed-method study will conduct. A randomized controlled trial will compare the CDM ability of CHN students who received 1hr traditional class with another group who received 1hr VS scenario about diabetic patient nursing care. Sixty-four students in each group will randomly select to be exposed to the intervention from undergraduate nursing students who completed the CHN course at York University. The participants will receive the same Clinical Decision Making in Nursing Scale (CDMNS) questionnaire. The study intervention will follow the Medical Research Council (MRC) approach. SPSS and content analysis will use for data analysis.

Keywords: clinical decision-making, virtual simulation, community health nursing students, community health nursing education

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Authors: Parisa Bagheri Tookanlou

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In this paper, we analyze a product line design problem faced by a manufacturing firm where the product line consists of a customized product in addition to a standard product and is offered in a market in which customers are heterogeneous on aesthetic attributes of the product. The customization level of a product is defined by the fraction of aesthetic attributes of the product that the manufacturer chooses to customize. In contrast to the existing literature on product line design that predominantly assumes deterministic demand, we consider the presence of demand uncertainty and frame the product line design problem in a single period (news vendor) setting. We examine the effect of demand uncertainty on product line decisions. Furthermore, we also examine how product line decisions are influenced by channel structure. While we use the centralized channel as a benchmark, we consider the decentralized dual channel where the customized product is sold through an online channel owned by the manufacturer and the standard product is sold through a retailer. We introduce a supply contract between the manufacturer and the retailer for improving channel efficiency and coordinate the distribution channel.

Keywords: product line design, demand uncertainty, customization level, distribution channel

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Authors: S. A. Sadegh Zadeh, C. Kambhampati

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Mathematical and computational modellings are the necessary tools for reviewing, analysing, and predicting processes and events in the wide spectrum range of scientific fields. Therefore, in a field as rapidly developing as neuroscience, the combination of these two modellings can have a significant role in helping to guide the direction the field takes. The paper combined mathematical and computational modelling to prove a weakness in a very precious model in neuroscience. This paper is intended to analyse all-or-none principle in Hodgkin-Huxley mathematical model. By implementation the computational model of Hodgkin-Huxley model and applying the concept of all-or-none principle, an investigation on this mathematical model has been performed. The results clearly showed that the mathematical model of Hodgkin-Huxley does not observe this fundamental law in neurophysiology to generating action potentials. This study shows that further mathematical studies on the Hodgkin-Huxley model are needed in order to create a model without this weakness.

Keywords: all-or-none, computational modelling, mathematical model, transmembrane voltage, action potential

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Authors: Yi Yu, Vu Xuan Nguyen, Gaoxi Xiao

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Opinion formation in complex social networks may exhibit complex system dynamics even when based on some simplest system evolution models. An interesting and important issue is the effects of the initial state on the final steady-state opinion distribution. By carrying out extensive simulations and providing necessary discussions, we show that, while different initial opinion distributions certainly make differences to opinion evolution in social systems without noises, in systems with noises, given enough time, different initial states basically do not contribute to making any significant differences in the final steady state. Instead, it is the basal distribution of the preferred opinions that contributes to deciding the final state of the systems. We briefly explain the reasons leading to the observed conclusions. Such an observation contradicts with a long-term belief on the roles of system initial state in opinion formation, demonstrating the dominating role that opinion mutation can play in opinion formation given enough time. The observation may help to better understand certain observations of opinion evolution dynamics in real-life social networks.

Keywords: opinion formation, Deffuant model, opinion mutation, consensus making

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Authors: Jules Selles

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The Atlantic and Mediterranean bluefin tuna fishery have been considered as the archetype of an overfished and mismanaged fishery. This crisis has demonstrated the role of public awareness and the importance of the interactions between science and management about scientific uncertainties. This work aims at investigating the policy making process associated with a regional fisheries management organization. We propose a contextualized computer-based experimental approach, in order to explore the effects of key factors on the cooperation process in a complex straddling stock management setting. Namely, we analyze the effects of the introduction of a socio-economic tipping point and the uncertainty surrounding the estimation of the resource level. Our approach is based on a Gordon-Schaefer bio-economic model which explicitly represents the decision making process. Each participant plays the role of a stakeholder of ICCAT and represents a coalition of fishing nations involved in the fishery and decide unilaterally a harvest policy for the coming year. The context of the experiment induces the incentives for exploitation and collaboration to achieve common sustainable harvest plans at the Atlantic bluefin tuna stock scale. Our rigorous framework allows testing how stakeholders who plan the exploitation of a fish stock (a common pool resource) respond to two kinds of effects: i) the inclusion of a drastic shift in the management constraints (beyond a socio-economic tipping point) and ii) an increasing uncertainty in the scientific estimation of the resource level.

Keywords: economic experiment, fisheries management, game theory, policy making, Atlantic Bluefin tuna

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Authors: Divyansh Goel, Varun Jain

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Classical economics works on the principle that people are rational and analytical in their decision making and their choices fall in line with the most suitable option according to the dominant strategy in a standard game theory model. This model has failed at many occasions in estimating the behavior and dealings of rational people, giving proof of some other underlying heuristics and cognitive biases at work. This paper probes into the study of these factors, which fall under the umbrella of behavioral economics and through their medium explore the solution to a problem which a lot of nations presently face. There has long been a wide disparity in the number of people holding favorable views on organ donation and the actual number of people signing up for the same. This paper, in its entirety, is an attempt to shape the public policy which leads to an increase the number of organ donations that take place and close the gap in the statistics of the people who believe in signing up for organ donation and the ones who actually do. The key assumption here is that in cases of cognitive dissonance, where people have an inconsistency due to conflicting views, people have a tendency to go with the default choice. This tendency is a well-documented cognitive bias known as the status quo bias. The research in this project involves an assay of mandated choice models of organ donation with two case studies. The first of an opt-in system of Germany (where people have to explicitly sign up for organ donation) and the second of an opt-out system of Austria (every citizen at the time of their birth is an organ donor and has to explicitly sign up for refusal). Additionally, there has also been presented a detailed analysis of the experiment performed by Eric J. Johnson and Daniel G. Goldstein. Their research as well as many other independent experiments such as that by Tsvetelina Yordanova of the University of Sofia, both of which yield similar results. The conclusion being that the general population has by and large no rigid stand on organ donation and are gullible to status quo bias, which in turn can determine whether a large majority of people will consent to organ donation or not. Thus, in our paper, we throw light on how governments can use status quo bias to drive positive social change by making policies in which everyone by default is marked an organ donor, which will, in turn, save the lives of people who succumb on organ transplantation waitlists and save the economy countless hours of economic productivity.

Keywords: behavioral economics, game theory, organ donation, status quo bias

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Authors: Jeremy Dixon

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Safeguarding adults forms a core part of social work practice. The Government in England and Wales has made efforts to standardise practices through The Care Act 2014. The Act states that local authorities have duties to make inquiries in cases where an adult with care or support needs is experiencing or at risk of abuse and is unable to protect themselves from abuse or neglect. Despite the importance given to safeguarding adults within law there remains little research about how social workers conduct such decisions on the ground. This presentation reports on findings from a pilot research study conducted within two social work teams in a Local Authority in England. The objective of the project was to find out how social workers interpreted safeguarding duties as laid out by The Care Act 2014 with a particular focus on how workers assessed and managed risk. Ethnographic research methods were used throughout the project. This paper focusses specifically on decisions made by workers in the assessment team. The paper reports on qualitative observation and interviews with five workers within this team. Drawing on governmentality theory, this paper analyses the techniques used by workers to manage risk from a distance. A high proportion of safeguarding referrals came from care workers or managers in residential care homes. Social workers conducting safeguarding assessments were aware that they had a duty to work in partnership with these agencies. However, their duty to safeguard adults also meant that they needed to view them as potential abusers. In making judgments about when it was proportionate to refer for a safeguarding assessment workers drew on a number of common beliefs about residential care workers which were then tested in conversations with them. Social workers held the belief that residential homes acted defensively, leading them to report any accident or danger. Social workers therefore encouraged residential workers to consider whether statutory criteria had been met and to use their own procedures to manage risk. In addition social workers carried out an assessment of the workers’ motives; specifically whether they were using safeguarding procedures as a shortcut for avoiding other assessments or as a means of accessing extra resources. Where potential abuse was identified social workers encouraged residential homes to use disciplinary policies as a means of isolating and managing risk. The study has implications for understanding risk within social work practice. It shows that whilst social workers use law to govern individuals, these laws are interpreted against cultural values. Additionally they also draw on assumptions about the culture of others.

Keywords: adult safeguarding, governmentality, risk, risk assessment

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Authors: Chen Xi, Lao Xuerui, Li Junjie, Jiang Yike, Wang Hanwei, Zeng Zihao

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To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behaviour recognition models, to provide empirical data such as 'pedestrian flow data and human behavioural characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.

Keywords: urban planning, urban governance, CIM, artificial intelligence, convolutional neural network

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Authors: Eda Orhun

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

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

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Authors: Münevver Başman, Ezel Tavşancıl

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Making the right decisions about students depends on teachers’ use of the assessment and evaluation techniques effectively. In order to do that, teachers should have positive attitudes and adequate self-efficacy perception towards assessment and evaluation. The purpose of this study is to investigate relationship between self-efficacy perception and the attitudes of prospective teachers towards assessment and evaluation and what kind of differences these issues have in terms of a variety of demographic variables. The study group consisted of 277 prospective teachers who have been studying in different departments of Marmara University, Faculty of Education. In this study, ‘Personal Information Form’, ‘A Perceptual Scale for Measurement and Evaluation of Prospective Teachers Self-Efficacy in Education’ and ‘Attitudes toward Educational Measurement Inventory’ are applied. As a result, positive correlation was found between self-efficacy perceptions and the attitudes of prospective teachers towards assessment and evaluation. Considering different departments, there is a significant difference between the mean score of attitudes of prospective teachers and between the mean score of self-efficacy perceptions of them. However, considering variables of attending statistics class and the class types at the graduated high school, there is no significant difference between the mean score of attitudes of prospective teachers and between the mean score of self-efficacy perceptions of them.

Keywords: attitude, perception, prospective teacher, self-efficacy

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Authors: Navneet Sharma, Himanshu Ojha, Dharam Pal Pathak, Rakesh Kumar Sharma

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Radio-nuclides decontamination is an important task because any extra second of deposition leads to deleterious health effects. We had developed and characterise nanoemulsion of p-tertbutylcalix[4]arens using phase inversion temperature (PIT) method and evaluate its decontamination efficacy (DE). The solubility of the drug was determined in various oils and surfactants. Nanoemulsion developed with an HLB value of 11 and different ratios of the surfactants 10% (7:3, w/w), oil (20%, w/w), and double distilled water (70%) were selected. Formulation was characterised by multi-photon spectroscopy and parameters like viscosity, droplet size distribution, zeta potential and stability were optimised. In vitro and Ex vivo decontamination efficacy (DE) was evaluated against Technetium-99m, Iodine-131, and Thallium-201 as radio-contaminants applied over skin of Sprague-Dawley rat and human tissue equivalent model. Contaminants were removed using formulation soaked in cotton swabs at different time intervals and whole body imaging and static counts were recorded using SPECT gamma camera before and after decontamination attempt. Data were analysed using one-way analysis of variance (ANOVA) and was found to be significant (p <0.05). DE of the nanoemulsion loaded with p-tertbutylcalix[4]arens was compared with placebo and recorded to be 88±5%, 90±3% and 89±3% for 99mTc, 131I and 201Tl respectively. Ex-vivo complexation study of p-tertbutylcalix[4]arene nanoemulsion with surrogate nuclides of radioactive thallium and Iodine, were performed on rat skin mounted on Franz diffusion cell using high-resolution sector field inductively coupled plasma mass spectroscopy (HR-SF-ICPMS). More than 90% complexation of the formulation with these nuclides was observed. Results demonstrate that the prepared nanoemulsion formulation was found efficacious for the decontamination of radionuclides from a large contaminated population.

Keywords: p-tertbutylcalix[4]arens, skin decontamination, radiological emergencies, nanoemulsion, iodine-131, thallium-201

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Authors: Wen Liu, Errol Haarhoff, Lee Beattie

Abstract:

In 2010, New Zealand’s central government re-organise the local governments arrangements in Auckland, New Zealand by amalgamating its previous regional council and seven supporting local government units into a single unitary council, the Auckland Council. The Auckland Council is charged with providing local government services to approximately 1.5 million people (a third of New Zealand’s total population). This includes addressing Auckland’s strategic urban growth management and setting its urban planning policy directions for the next 40 years. This is expressed in the first ever spatial plan in the region – the Auckland Plan (2012). The Auckland plan supports implementing a compact city model by concentrating the larger part of future urban growth and development in, and around, existing and proposed transit centres, with the intention of Auckland to become globally competitive city and achieving ‘the most liveable city in the world’. Turning that vision into reality is operatized through the statutory land use plan, the Auckland Unitary Plan. The Unitary plan replaced the previous regional and local statutory plans when it became operative in 2016, becoming the ‘rule book’ on how to manage and develop the natural and built environment, using land use zones and zone standards. Common to the broad range of literature on urban growth management, one significant issue stands out about intensification. The ‘gap’ between strategic planning and what has been achieved is evident in the argument for the ‘compact’ urban form. Although the compact city model may have a wide range of merits, the extent to which these are actualized largely rely on how intensification actually is delivered. The transformation of the rhetoric of the residential intensification model into reality is of profound influence, yet has enjoyed limited empirical analysis. In Auckland, the establishment of the Auckland Plan set up the strategies to deliver intensification into diversified arenas. Nonetheless, planning policy itself does not necessarily achieve the envisaged objectives, delivering the planning system and high capacity to enhance and sustain plan implementation is another demanding agenda. Though the Auckland Plan provides a wide ranging strategic context, its actual delivery is beholden on the Unitary Plan. However, questions have been asked if the Unitary Plan has the necessary statutory tools to deliver the Auckland Plan’s policy outcomes. In Auckland, there is likely to be continuing tension between the strategies for intensification and their envisaged objectives, and made it doubtful whether the main principles of the intensification strategies could be realized. This raises questions over whether the Auckland Plan’s policy goals can be achieved in practice, including delivering ‘quality compact city’ and residential intensification. Taking Auckland as an example of traditionally sprawl cities, this article intends to investigate the efficacy plan making and implementation directed towards higher density development. This article explores the process of plan development, plan making and implementation frameworks of the first ever spatial plan in Auckland, so as to explicate the objectives and processes involved, and consider whether this will facilitate decision making processes to realize the anticipated intensive urban development.

Keywords: urban intensification, sustainable development, plan making, governance and implementation

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Authors: Harun Aydilek, Asiye Aydilek, Ali Allahverdi

Abstract:

Our objective is to minimize the total tardiness in an m-machine two-stage assembly flowshop scheduling problem. The objective is an important performance measure because of the fact that the fulfillment of due dates of customers has to be taken into account while making scheduling decisions. In the literature, the problem is considered with zero setup times which may not be realistic and appropriate for some scheduling environments. Considering separate setup times from processing times increases machine utilization by decreasing the idle time and reduces total tardiness. We propose two new algorithms and adapt four existing algorithms in the literature which are different versions of simulated annealing and genetic algorithms. Moreover, a dominance relation is developed based on the mathematical formulation of the problem. The developed dominance relation is incorporated in our proposed algorithms. Computational experiments are conducted to investigate the performance of the newly proposed algorithms. We find that one of the proposed algorithms performs significantly better than the others, i.e., the error of the best algorithm is less than those of the other algorithms by minimum 50%. The newly proposed algorithm is also efficient for the case of zero setup times and performs better than the best existing algorithm in the literature.

Keywords: algorithm, assembly flowshop, scheduling, simulation, total tardiness

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

Abstract:

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

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

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Authors: Liang-Hsuan Chen, Sheng-Shing Nien

Abstract:

This study aims to develop approaches to formulate intuitionistic fuzzy regression (IFR) models for many decision-making applications in the fuzzy environments using intuitionistic fuzzy observations. Intuitionistic fuzzy numbers (IFNs) are used to characterize the fuzzy input and output variables in the IFR formulation processes. A mathematical programming problem (MPP) is built up to optimally determine the IFR parameters. Each parameter in the MPP is defined as a couple of alternative numerical variables with opposite signs, and an intuitionistic fuzzy error term is added to the MPP to characterize the uncertainty of the model. The IFR model is formulated based on the distance measure to minimize the total distance errors between estimated and observed intuitionistic fuzzy responses in the MPP resolution processes. The proposed approaches are simple/efficient in the formulation/resolution processes, in which the sign of parameters can be determined so that the problem to predetermine the sign of parameters is avoided. Furthermore, the proposed approach has the advantage that the spread of the predicted IFN response will not be over-increased, since the parameters in the established IFR model are crisp. The performance of the obtained models is evaluated and compared with the existing approaches.

Keywords: fuzzy sets, intuitionistic fuzzy number, intuitionistic fuzzy regression, mathematical programming method

Procedia PDF Downloads 138