Search results for: shared-decision making

Authors: S. Chandrakaran, G. Govind

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Stone columns are effectively used to improve bearing strength of soils and also for many geotechnical applications. In soft soils when stone columns are loaded they undergo large settlements due to insufficient lateral confinement. Use of geosynthetics encasement has proved to be a solution for this problem. In this paper, results of a laboratory experimental study carried out with model stone columns with and without encasement. Sand was used for making test beds, and grain size of soil varies from 0.075mm to 4.75mm. Woven geotextiles produced by Gareware ropes India with mass per unit area of 240gm/M2 and having tensile strength of 52KN/m is used for the present investigation. Tests were performed with large scale direct shear box and also using scaled laboratory plate load tests. Stone column of 50mm and 75mm is used for the present investigation. Diameter of stone column, size of stones used for making stone columns is varied in making stone column in the present study. Two types of stone were used namely small and bigger in size. Results indicate that there is an increase in angle of internal friction and also an increase in the shear strength of soil when stone columns are encased. With stone columns with 50mm dia, an average increase of 7% in shear strength and 4.6 % in angle of internal friction was achieved. When large stones were used increase in the shear strength was 12.2%, and angle of internal friction was increased to 5.4%. When the stone column diameter has increased to 75mm increase in shear strength and angle of internal friction was increased with smaller size of stones to 7.9 and 7.5%, and with large size stones, it was 7.7 and 5.48% respectively. Similar results are obtained in plate load tests, also.

Keywords: stone columns, encasement, shear strength, plate load test

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Authors: Oualid Walid Ben Ali

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Big Data has become one of the buzzwords today. The recent explosion of digital data has led the organization, either private or public, to a new era towards a more efficient decision making. At some point, business decided to use that concept in order to learn what make their clients tick with phrases like ‘sales funnel’ analysis, ‘actionable insights’, and ‘positive business impact’. So, it stands to reason that Big Data was viewed through green (read: money) colored lenses. Somewhere along the line, however someone realized that collecting and processing data doesn’t have to be for business purpose only, but also could be used for other purposes to assist law enforcement or to improve policing or in road safety. This paper presents briefly, how Big Data have been used in the fields of policing order to improve the decision making process in the daily operation of the police. As example, we present a big-data driven system which is sued to accurately dispatch the patrol cars in a geographic environment. The system is also used to allocate, in real-time, the nearest patrol car to the location of an incident. This system has been implemented and applied in the Emirate of Abu Dhabi in the UAE.

Keywords: big data, big data analytics, patrol car allocation, dispatching, GIS, intelligent, Abu Dhabi, police, UAE

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Authors: Blessing Olamide Taiwo, Andrew Palangio, Chirag Savaliya, Jenil Patel

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Oversized material resulting from blasting presents a notable drawback in the transportation of run-off-mine material due to increased expenses associated with handling, decreased efficiency in loading, and greater wear on digging equipment. Its irregular size and weight demand additional resources and time for secondary breakage, impacting overall productivity and profitability. This paper addresses the limitations of interpreting image analysis software results and applying them to the assessment of blast-generated oversized materials. This comprehensive guide utilizes both ortho mosaic and digital photos to provide critical approaches for optimizing fragmentation analysis and improving decision-making in mining operations. It briefly covers post-blast assessment, blast block heat map interpretation, and material loading decision-making recommendations.

Keywords: blast result assessment, WipFrag, oversize identification, orthomosaic images, production optimization

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Authors: Anna Guitart Atienza, Ana Fernández del Río, Madhav Nekkar, Jelena Ljubicic, África Periáñez, Eura Shin, Lauren Bellhouse

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The use of digital devices in healthcare or mobile health (mHealth) has increased in recent years due to the advances in digital technology, making it possible to nudge healthy behaviors through individual interventions. In addition, mHealth is becoming essential in poor-resource settings due to the widespread use of smartphones in areas where access to professional healthcare is limited. In this work, we evaluate mHealth interventions in low-income countries with a focus on causal inference. Counterfactuals estimation and other causal computations are key to determining intervention success and assisting in empirical decision-making. Our main purpose is to personalize treatment recommendations and triage patients at the individual level in order to maximize the entire intervention's impact on the desired outcome. For this study, collected data includes mHealth individual logs from front-line healthcare workers, electronic health records (EHR), and external variables data such as environmental, demographic, and geolocation information.

Keywords: causal inference, mHealth, intervention, personalization

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Authors: Emad Mohammed Sani

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Women encounter exclusion and discrimination in varying degrees, particularly those who marry as minors. The detrimental custom of getting married young is still prevalent worldwide and affects millions of people. It has been less common over time, although it is still widespread in underdeveloped nations. Oromia Regional State is the region in Ethiopia with the highest proportion of child brides. This study aimed at evaluating the effects of early marriage on its survivors’ life conditions – specifically, empowerment and household decision-making – in Eastern Hararghe Zone of Oromia Region. This study employed community-based cross-sectional study design. It adopted mixed method approach – survey, in-depth interview and focus group discussion (FGD) – to collect, analyses and interpret data on early marriage and its effects on household decision-making processes. Narratives and analytical descriptions were integrated to substantiate and/or explain observed quantitative results, or generate contextual themes. According to this study, married women who were married at or after the age of eighteen participated more in household decision-making than child brides. Child brides were more likely to be victims of violence and other types of spousal abuse in their marriages. These changes are mostly caused by an individual's age at first marriage. Delaying marriage had a large positive impact on women's empowerment at the household level, and age at first marriage had a considerable negative impact. In order to advance women's welfare and emancipation, we advise more research to concentrate on the relationship between the home and the social-structural forms that appear at the individual and communal levels.

Keywords: child-bride, early marriage, women, ethiopia

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Authors: Anat Keller

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Given that macro-prudential supervision is a relatively new policy area and its empirical and analytical research are still in their infancy, its theoretical foundations are also lagging behind. This paper contributes to the developing discussion on effective legal and institutional macroprudential supervision frameworks. In the first part of the paper, it is argued that effectiveness as a key benchmark poses some challenges in the context of macroprudential supervision such as the difficulty in proving causality between supervisory actions and the achievement of the supervisor’s mission. The paper suggests that effectiveness in the macroprudential context should, therefore, be assessed at the supervisory decision-making process (to be differentiated from the supervisory outcomes). The second part of the essay examines whether insights from behavioural economics can point to biases in the macroprudential decision-making process. These biases include, inter alia, preference bias, groupthink bias and inaction bias. It is argued that these biases are exacerbated in the multilateral setting of the macroprudential supervision framework in the EU. The paper then examines how legal and institutional frameworks should be designed to acknowledge and perhaps contain these identified biases. The paper suggests that the effectiveness of macroprudential policy will largely depend on the existence of clear and robust transparency and accountability arrangements. Accountability arrangements can be used as a vehicle for identifying and addressing potential biases in the macro-prudential framework, in particular, inaction bias. Inclusiveness of the public in the supervisory process in the form of transparency and awareness of the logic behind policy decisions may assist in minimising their potential unpopularity thus promoting their effectiveness. Furthermore, a governance structure which facilitates coordination of the macroprudential supervisor with other policymakers and incorporates outside perspectives and opinions could ‘break-down’ groupthink bias as well as inaction bias.

Keywords: behavioural economics and biases, effectiveness of macroprudential supervision, legal and institutional macroprudential frameworks, macroprudential decision-making process

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Authors: Siphiwe P. Mandina, Tinashe Shamuyashe

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Tourism has become a topical issue amongst academics and practitioners due to its potential to contribute significantly towards an economy’s GDP. The problem underpinning this research is the fact that the major attraction, Victoria Falls, is being marketed in neighboring countries like South Africa, Botswana and Zambia with tour operators providing just day trips to the Victoria Falls. This has deprived Zimbabwe of income from tourism with tourists making day trips and actually not spending nights in Zimbabwe. This therefore calls for cutting edge marketing strategies that are superior to or inimitable by competing nations such as South Africa and Zambia. This study proposes a shift towards an experience management paradigm in the tourism sector. A qualitative research was adopted for this study, and findings of this study were generalized across different tourism contexts, therefore making the survey based research design more appropriate. The target population for this study is tourists visiting Zimbabwe over the period 2016 and ZTA visitor database acquired from the Department of Immigration will form the sampling frame for the purposes of this study.

Keywords: tourist experiences, Zimbabwe, tourist arrivals, competitiveness

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Authors: Elaheh Talebi, Fariba Yavari, Lucy Philip, Lesley Town

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The mining industry generates vast amounts of data, necessitating robust data management systems and advanced analytics tools to achieve better decision-making processes in the development of mining production and maintaining safety. This paper highlights the advantages of Power BI, a powerful intelligence tool, over traditional Excel-based approaches for effectively managing and harnessing mining data. Power BI enables professionals to connect and integrate multiple data sources, ensuring real-time access to up-to-date information. Its interactive visualizations and dashboards offer an intuitive interface for exploring and analyzing geotechnical data. Advanced analytics is a collection of data analysis techniques to improve decision-making. Leveraging some of the most complex techniques in data science, advanced analytics is used to do everything from detecting data errors and ensuring data accuracy to directing the development of future project phases. However, while Power BI is a robust tool, specific visualizations required by geotechnical engineers may have limitations. This paper studies the capability to use Python or R programming within the Power BI dashboard to enable advanced analytics, additional functionalities, and customized visualizations. This dashboard provides comprehensive tools for analyzing and visualizing key geotechnical data metrics, including spatial representation on maps, field and lab test results, and subsurface rock and soil characteristics. Advanced visualizations like borehole logs and Stereonet were implemented using Python programming within the Power BI dashboard, enhancing the understanding and communication of geotechnical information. Moreover, the dashboard's flexibility allows for the incorporation of additional data and visualizations based on the project scope and available data, such as pit design, rock fall analyses, rock mass characterization, and drone data. This further enhances the dashboard's usefulness in future projects, including operation, development, closure, and rehabilitation phases. Additionally, this helps in minimizing the necessity of utilizing multiple software programs in projects. This geotechnical dashboard in Power BI serves as a user-friendly solution for analyzing, visualizing, and communicating both new and historical geotechnical data, aiding in informed decision-making and efficient project management throughout various project stages. Its ability to generate dynamic reports and share them with clients in a collaborative manner further enhances decision-making processes and facilitates effective communication within geotechnical projects in the mining industry.

Keywords: geotechnical data analysis, power BI, visualization, decision-making, mining industry

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Authors: Haodong Huang, Zida Zhao, Shilong Sun, Chiyao Li, Wenfu Xu

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The control methods for legged robots based on deep reinforcement learning have seen widespread application; however, the inherent black-box nature of neural networks presents challenges in understanding the decision-making motives of the robots. To address this issue, we propose a fully interpretable deep reinforcement learning training method to elucidate the underlying principles of legged robot motion. We incorporate the dynamics of legged robots into the policy, where observations serve as inputs and actions as outputs of the dynamics model. By embedding the dynamics equations within the multi-layer perceptron (MLP) computation process and making the parameters trainable, we enhance interpretability. Additionally, Bayesian optimization is introduced to train these parameters. We validate the proposed fully interpretable motion control algorithm on a legged robot, opening new research avenues for motion control and learning algorithms for legged robots within the deep learning framework.

Keywords: deep reinforcement learning, interpretation, motion control, legged robots

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Authors: Yidnekachew Daget, Hong Zhang

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The decision-making process in order to select the suitable housing system for application in housing construction has been a challenge for many developing countries. This study evaluates the decision process to identify the suitable housing systems for adoption in Addis Ababa. Ten industrialized housing systems were considered as alternatives for comparison. These systems have been used in a housing development in different parts of the world. A relevant literature review and contextual analysis were conducted. An analytical hierarchy process and an Expert Choice Comparion platform were employed as a research technique and tool to evaluate the professionals’ level of preferences with regard to the housing systems. The findings revealed the priority rank and characteristics of the suitable housing systems to be adapted for application in housing development. The decision criteria and the analytical process used in this study can help the decision-makers and the housing developers in developing countries make effective evaluations and decisions.

Keywords: analytical hierarchy process, decision-making, expert choice comparion, industrialized housing systems

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Authors: Olumide Yusuf Jimoh

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Reading comprehension is an interactive and purposeful process of getting meaning from and bringing meaning to a text. Over the years, teachers of the English Language (in Nigeria) have been glued to the monotonous method of making students read comprehension passages silently and then answer the questions that follow such passages without making the reading session interactive. Hence, students often find such exercises monotonous and boring. Consequently, students'’ interest in language learning continues to dwindle, and this often affects their overall academic performance. Relying on Communicative Accommodation Theory therefore, the study employed the qualitative research design method to x-ray Communicative Language Teaching Approach (CLTA) in reading comprehension. Moreover, techniques such as the Genuinely Collaborative Reading Approach (GCRA), Jigsaw reading, Pre-reading, and Post-reading tasks were examined. The researcher submitted that effective reading comprehension could not be done passively. Students must respond to what they read; they must interact not only with the materials being read but also with one another and with the teacher; this can be achieved by developing communicative and interactive reading programs.

Keywords: collaborative reading approach, communicative teaching, interactive reading program, pre-reading task, reading comprehension

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Authors: Jacquelyn Burkell, Jane Bailey

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Artificial intelligence (AI) solutions deployed within the justice system face the critical task of providing acceptable explanations for decisions or actions. These explanations must satisfy the joint criteria of public and professional accountability, taking into account the perspectives and requirements of multiple stakeholders, including judges, lawyers, parties, witnesses, and the general public. This research project analyzes and integrates two existing literature on explanations in order to propose guidelines for explainable AI in the justice system. Specifically, we review three bodies of literature: (i) explanations of the purpose and function of 'explainable AI'; (ii) the relevant case law, judicial commentary and legal literature focused on the form and function of reasons for judicial decisions; and (iii) the literature focused on the psychological and sociological functions of these reasons for judicial decisions from the perspective of the public. Our research suggests that while judicial ‘reasons’ (arguably accurate descriptions of the decision-making process and factors) do serve similar explanatory functions as those identified in the literature on 'explainable AI', they also serve an important ‘justification’ function (post hoc constructions that justify the decision that was reached). Further, members of the public are also looking for both justification and explanation in reasons for judicial decisions, and that the absence of either feature is likely to contribute to diminished public confidence in the legal system. Therefore, artificially automated judicial decision-making systems that simply attempt to document the process of decision-making are unlikely in many cases to be useful to and accepted within the justice system. Instead, these systems should focus on the post-hoc articulation of principles and precedents that support the decision or action, especially in cases where legal subjects’ fundamental rights and liberties are at stake.

Keywords: explainable AI, judicial reasons, public accountability, explanation, justification

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Authors: Shannon Hashemi, Alireza Daneshfar

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Accounting ethical awareness has been widely promoted in recent years both in academia and in practice. However, the effectiveness of ethical awareness on accountants' judgment and choice of action is still debatable. This study investigates whether Machiavellianism and gender, as significant personality factors, influence the effect of ethical awareness on accountants' decision-making. Using an experiment, the results of ANOVA tests show that although introducing ethical awareness positively influences the accountants' judgment and choice of action, such an effect is significantly moderated by the accountants' Machiavellianism score and gender. Specifically, the test results show that the effect of introducing ethical awareness was higher on males with low Machiavellian score. The results also show that when the Machiavellian scores were high, the effect of ethical awareness was lower for both males and females. Applications of the results are discussed for accounting professionals as well as accounting ethics educators and researchers.

Keywords: ethical awareness, accounting decision making, Machiavellianism, ANOVA, ethics, accounting education

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Authors: Mannan Ahmad Rasheed, Sawera Kanwal, Mansoor Ahmad Rasheed

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The Internet of Things (IoT) has revolutionized the way we collect and process information, making it possible to gather data from a wide range of connected devices and sensors. This has led to the development of IoT-based information processing and computing systems that are capable of handling large amounts of data in real time. This paper provides a comprehensive overview of the current state of IoT-based information processing and computing, as well as the key challenges and gaps that need to be addressed. This paper discusses the potential benefits of IoT-based information processing and computing, such as improved efficiency, enhanced decision-making, and cost savings. Despite the numerous benefits of IoT-based information processing and computing, several challenges need to be addressed to realize the full potential of these systems. These challenges include security and privacy concerns, interoperability issues, scalability and reliability of IoT devices, and the need for standardization and regulation of IoT technologies. Moreover, this paper identifies several gaps in the current research related to IoT-based information processing and computing. One major gap is the lack of a comprehensive framework for designing and implementing IoT-based information processing and computing systems.

Keywords: IoT, computing, information processing, Iot computing

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Authors: Grace Omowunmi Soyebi

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Data Mining is the extraction of information from a large database which helps in predicting a trend or behavior, thereby helping management make knowledge-driven decisions. One principal problem of most hospitals in rural areas is making use of the file management system for keeping records. A lot of time is wasted when a patient visits the hospital, probably in an emergency, and the nurse or attendant has to search through voluminous files before the patient's file can be retrieved; this may cause an unexpected to happen to the patient. This Data Mining application is to be designed using a Structured System Analysis and design method, which will help in a well-articulated analysis of the existing file management system, feasibility study, and proper documentation of the Design and Implementation of a Computerized medical record system. This Computerized system will replace the file management system and help to easily retrieve a patient's record with increased data security, access clinical records for decision-making, and reduce the time range at which a patient gets attended to.

Keywords: data mining, medical record system, systems programming, computing

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Authors: Pascal François Faye, Baye Mor Sall, Bineta Dembele, Jeanne Ana Awa Faye

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In agriculture, estimating crop yields is key to improving productivity and decision-making processes such as financial market forecasting and addressing food security issues. The main objective of this paper is to have tools to predict and improve the accuracy of crop yield forecasts using machine learning (ML) algorithms such as CART , KNN and SVM . We developed a mobile app and a web app that uses these algorithms for practical use by farmers. The tests show that our system (collection and deployment architecture, web application and mobile application) is operational and validates empirical knowledge on agro-climatic parameters in addition to proactive decision-making support. The experimental results obtained on the agricultural data, the performance of the ML algorithms are compared using cross-validation in order to identify the most effective ones following the agricultural data. The proposed applications demonstrate that the proposed approach is effective in predicting crop yields and provides timely and accurate responses to farmers for decision support.

Keywords: prediction, machine learning, artificial intelligence, digital agriculture

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Authors: Javad Abdi, Azam Famil Khalili

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Modeling emotions have attracted much attention in recent years, both in cognitive psychology and design of artificial systems. However, it is a negative factor in decision-making; emotions have shown to be a strong faculty for making fast satisfying decisions. In this paper, we have adapted a computational model based on the limbic system in the mammalian brain for control engineering applications. Learning in this model based on Temporal Difference (TD) Learning, we applied the proposed controller (termed BELBIC) for a simple model of a submarine. The model was supposed to reach the desired depth underwater. Our results demonstrate excellent control action, disturbance handling, and system parameter robustness for TDBELBIC. The proposal method, regarding the present conditions, the system action in the part and the controlling aims, can control the system in a way that these objectives are attained in the least amount of time and the best way.

Keywords: artificial neural networks, temporal difference, brain emotional learning based intelligent controller, heating- ventilating and air conditioning

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Authors: Saniye Çeşmecioğlu

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The importance of project sustainability and success has become increasingly significant due to the proliferation of external environmental factors that have decreased project resistance in contemporary times. The primary approach to forestall the failure of projects is to ensure their long-term viability through the strategic selection of projects as creating judicious project selection framework within the organization. Decision-makers require precise decision contexts (models) that conform to the company's business objectives and sustainability expectations during the project selection process. The establishment of a rational model for project selection enables organizations to create a distinctive and objective framework for the selection process. Additionally, for the optimal implementation of this decision-making model, it is crucial to establish a Project Management Office (PMO) team and Project Steering Committee within the organizational structure to oversee the framework. These teams enable updating project selection criteria and weights in response to changing conditions, ensuring alignment with the company's business goals, and facilitating the selection of potentially viable projects. This paper presents a multi-criteria decision model for selecting project sustainability and project success criteria that ensures timely project completion and retention. The model was developed using MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique) and was based on broadcaster companies’ expectations. The ultimate results of this study provide a model that endorses the process of selecting the appropriate project objectively by utilizing project selection and sustainability criteria along with their respective weights for organizations. Additionally, the study offers suggestions that may ascertain helpful in future endeavors.

Keywords: project portfolio management, project selection, multi-criteria decision making, project sustainability and success criteria, MACBETH

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Authors: Joohyun Park, Jin Baek

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The purpose of this study is to Analyze the role and effect arise from Diagonal Plane Control by Street Width (DPCSW) in Architecture in Seoul, and to predict the aspect of transition about the relationship among buildings and Urban morphology After the abolition. To find the tendency of building shape regulation, This study review Building Acts concerned with form making (the building to land Ratio, building designated line, wall designated line, building height limit (DPCSW) and etc.) and simulate the shape of urban blocks made by Acts in drawings. The review results show DPCSW is not only limitation about height, but also making the building setback from road and make the Road broader. And it makes the typical shape of the urban block that buildings are moving away from surrounding road After the Abolition of DPCSW; it is expected by the legislature that domestic real estate’s market would be promoted by increased total floor areas in each building. Some substitution from the legislature is announced, but it just deals with Building Maximum unit by Block unit except the regulation about arrangement in urban Figure and Ground. In conclusion, refrain from the uncontrolled development of city, It is important to make regulation about not only height factors but limitation line in land. Furthermore, through revising District Unit Plan, It is positively necessary to reset the relationship between buildings for the making the city space better.

Keywords: diagonal plane control by street width, building maximum height, district unit plan, building acts, urban block type, morphology, building shape

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Authors: Dimitrios J. Dimitriou, Maria F. Sartzetaki

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Transport infrastructures are high-cost, long-term investments that serve as vital foundations for the operation of a region or nation and are essential to a country’s or business’s economic development and prosperity, by improving well-being and generating jobs and income. The development of appropriate financing options is of key importance in the decision making process in order develop viable transport infrastructures. The development of transport infrastructure has increasingly been shifting toward alternative methods of project financing such as Public Private Partnership (PPPs) and hybrid forms. In this paper, a methodological decision-making framework based on the evaluation of the financial viability of transportation infrastructure for different financial schemes is presented. The framework leads to an assessment of the financial viability which can be achieved by performing various financing scenarios analyses. To illustrate the application of the proposed methodology, a case study of rail transport infrastructure financing scenario analysis in Greece is developed.

Keywords: rail transport infrastructure, financial viability, scenario analysis, rail project feasibility

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Authors: W. Rowan, Y. O’Connor, L. Lynch, C. Heavin

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Situation Awareness can offer the potential for conscious dynamic reflection. In an era of online health data sharing, it is becoming increasingly important that users of health social networks (HSNs) have the information necessary to make informed decisions as part of the registration process and in the provision of eConsent. This research aims to leverage an adapted Situation Awareness (SA) model to explore users’ decision making processes in the provision of eConsent. A HSN platform was used to investigate these behaviours. A mixed methods approach was taken. This involved the observation of registration behaviours followed by a questionnaire and focus group/s. Early results suggest that users are apt to automatically accept eConsent, and only later consider the long-term implications of sharing their personal health information. Further steps are required to continue developing knowledge and understanding of this important eConsent process. The next step in this research will be to develop a set of guidelines for the improved presentation of eConsent on the HSN platform.

Keywords: eConsent, health social network, mixed methods, situation awareness

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Authors: Jingsi Li, Neil S. Ferguson

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Time pressure could have an influence on the productivity, quality of decision making, and the efficiency of problem-solving. This has been mostly stemmed from cognitive research or psychological literature. However, a salient scarce discussion has been held for transport adjacent fields. It is conceivable that in many activity-travel contexts, time pressure is a potentially important factor since an excessive amount of decision time may incur the risk of late arrival to the next activity. The activity-travel rescheduling behavior is commonly explained by costs and benefits of factors such as activity engagements, personal intentions, social requirements, etc. This paper hypothesizes that an additional factor of perceived time pressure could affect travelers’ rescheduling behavior, thus leading to an impact on travel demand management. Time pressure may arise from different ways and is assumed here to be essentially incurred due to travelers planning their schedules without an expectation of unforeseen elements, e.g., transport disruption. In addition to a linear-additive utility-maximization model, the less computationally compensatory heuristic models are considered as an alternative to simulate travelers’ responses. The paper will contribute to travel behavior modeling research by investigating the following questions: how to measure the time pressure properly in an activity-travel day plan context? How do travelers reschedule their plans to cope with the time pressure? How would the importance of the activity affect travelers’ rescheduling behavior? What will the behavioral model be identified to describe the process of making activity-travel rescheduling decisions? How do these identified coping strategies affect the transport network? In this paper, a Mixed Heuristic Model (MHM) is employed to identify the presence of different choice heuristics through a latent class approach. The data about travelers’ activity-travel rescheduling behavior is collected via a web-based interactive survey where a fictitious scenario is created comprising multiple uncertain events on the activity or travel. The experiments are conducted in order to gain a real picture of activity-travel reschedule, considering the factor of time pressure. The identified behavioral models are then integrated into a multi-agent transport simulation model to investigate the effect of the rescheduling strategy on the transport network. The results show that an increased proportion of travelers use simpler, non-compensatory choice strategies instead of compensatory methods to cope with time pressure. Specifically, satisfying - one of the heuristic decision-making strategies - is adopted commonly since travelers tend to abandon the less important activities and keep the important ones. Furthermore, the importance of the activity is found to increase the weight of negative information when making trip-related decisions, especially route choices. When incorporating the identified non-compensatory decision-making heuristic models into the agent-based transport model, the simulation results imply that neglecting the effect of perceived time pressure may result in an inaccurate forecast of choice probability and overestimate the affectability to the policy changes.

Keywords: activity-travel rescheduling, decision making under uncertainty, mixed heuristic model, perceived time pressure, travel demand management

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Authors: Maria M. Calheiros, Carla Silva, Eunice Magalhães

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Professionals working in child protection services (CPS) need to have common and clear criteria to identify cases of maltreatment and to differentiate levels of severity in order to determine when CPS intervention is required, its nature and urgency, and, in most countries, the service that will be in charge of the case (community or specialized CPS). Actually, decision-making process is complex in CPS, and, for that reason, such criteria are particularly important for who significantly contribute to that decision-making in child maltreatment cases. The main objective of this presentation is to describe the Maltreatment Severity Assessment Questionnaire (MSQ), specifically designed to be used by professionals in the CPS, which adopts a multidimensional approach and uses a scale of severity within subtypes. Specifically, we aim to provide evidence of validity and reliability of this tool, in order to improve the quality and validity of assessment processes and, consequently, the decision making in CPS. The total sample was composed of 1000 children and/or adolescents (51.1% boys), aged between 0 and 18 years old (M = 9.47; DP = 4.51). All the participants were referred to official institutions of the children and youth protective system. Children and adolescents maltreatment (abuse, neglect experiences and sexual abuse) were assessed with 21 items of the Maltreatment Severity Questionnaire (MSQ), by professionals of CPS. Each item (sub-type) was composed of four descriptors of increasing severity. Professionals rated the level of severity, using a 4-point scale (1= minimally severe; 2= moderately severe; 3= highly severe; 4= extremely severe). The construct validity of the Maltreatment Severity Questionnaire was assessed with a holdout method, performing an Exploratory Factor Analysis (EFA) followed by a Confirmatory Factor Analysis (CFA). The final solution comprised 18 items organized in three factors 47.3% of variance explained. ‘Physical neglect’ (eight items) was defined by parental omissions concerning the insurance and monitoring of the child’s physical well-being and health, namely in terms of clothing, hygiene, housing conditions and contextual environmental security. ‘Physical and Psychological Abuse’ (four items) described abusive physical and psychological actions, namely, coercive/punitive disciplinary methods, physically violent methods or verbal interactions that offend and denigrate the child, with the potential to disrupt psychological attributes (e.g., self-esteem). ‘Psychological neglect’ (six items) involved omissions related to children emotional development, mental health monitoring, school attendance, development needs, as well as inappropriate relationship patterns with attachment figures. Results indicated a good reliability of all the factors. The assessment of child maltreatment cases with MSQ could have a set of practical and research implications: a) It is a valid and reliable multidimensional instrument to measure child maltreatment, b) It is an instrument integrating the co-occurrence of various types of maltreatment and a within-subtypes scale of severity; c) Specifically designed for professionals, it may assist them in decision-making processes; d) More than using case file reports to evaluate maltreatment experiences, researchers could guide more appropriately their research about determinants and consequences of maltreatment.

Keywords: assessment, maltreatment, children and youth, decision-making

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Authors: Kamran Yazdanbakhsh, Somayeh Mahmoudi

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Three reasons make good use of the decision theory in medicine: 1. Increased medical knowledge and their complexity makes it difficult treatment information effectively without resorting to sophisticated analytical methods, especially when it comes to detecting errors and identify opportunities for treatment from databases of large size. 2. There is a wide geographic variability of medical practice. In a context where medical costs are, at least in part, by the patient, these changes raise doubts about the relevance of the choices made by physicians. These differences are generally attributed to differences in estimates of probabilities of success of treatment involved, and differing assessments of the results on success or failure. Without explicit criteria for decision, it is difficult to identify precisely the sources of these variations in treatment. 3. Beyond the principle of informed consent, patients need to be involved in decision-making. For this, the decision process should be explained and broken down. A decision problem is to select the best option among a set of choices. The problem is what is meant by "best option ", or know what criteria guide the choice. The purpose of decision theory is to answer this question. The systematic use of decision models allows us to better understand the differences in medical practices, and facilitates the search for consensus. About this, there are three types of situations: situations certain, risky situations, and uncertain situations: 1. In certain situations, the consequence of each decision are certain. 2. In risky situations, every decision can have several consequences, the probability of each of these consequences is known. 3. In uncertain situations, each decision can have several consequences, the probability is not known. Our aim in this article is to show how decision theory can usefully be mobilized to meet the needs of physicians. The decision theory can make decisions more transparent: first, by clarifying the data systematically considered the problem and secondly by asking a few basic principles should guide the choice. Once the problem and clarified the decision theory provides operational tools to represent the available information and determine patient preferences, and thus assist the patient and doctor in their choices.

Keywords: decision making, medicine, treatment strategies, patient

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Authors: Ali Zaimi

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Citizen participation in local government is an opportunity given to citizens and government to increase communication between them, create public support for local government plans and most important grow public trust in government. Also, the citizens’ involvement in the political process is an important part of democracy. This study aims to define the strategies for increasing citizen participation in local governance and concentrated in two important mechanisms such as participatory budget and public policy councils. Three strategies that promote more effective citizen involvement in local governance are understanding and using formal institutions of power, collaboration of citizens’ groups and governments officials to jointly formulate programs plans, electing and appointing local officials. A unique aspect of citizen participation to operate effectively is the transparency of government and the inclusion of actors into decision-making. The citizen engagement in local governance enhances accountability and problem solving, promote more inclusive and cohesive communities and enlarge the quality and quantity of initiatives made by communities.

Keywords: accountability, citizen participation, democracy, government

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Authors: Suzanne Overstreet-Juenke

Abstract:

Disproportionate minority contact (DMC) is a salient issue that has been found at every stage of the decision-making process in the juvenile justice system. Existing research indicates that DMC influences adjudication for drug, property, and personal crimes. Because intimate partner violence (IPV) is a major public health problem and global concern, the current study examines DMC at adjudication among youth charged for crimes of interpersonal violence. This research uses administrative, Court Designated Worker (CDW) data collected from 2014 to 2016. The results are contextualized using Steffensmeier’s version of focal concerns theory of judicial decision-making. This study assesses race and two seriousness of offense measures to establish whether a link exists between race and adjudication. The results of the study is similar to prior research on the topic. These results are discussed in terms of policy implications, limitations, and future research.

Keywords: race, disproportionate minority contact, focal concerns theory, juvenile

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Authors: Luc Beal

Abstract:

Introduction. Among the stakeholders involved in the tourist decision-making process, the accommodation provider has the potential to play a crucial role in raising awareness, disseminating information, and thus influencing the tourists’ choice of transportation. Since the early days of tourism, the accommodation provider has consistently served as the primary point of contact with the destination, and consequently, as the primary source of information for visitors. By offering accommodation and hospitality, the accommodation provider has evolved into a trusted third party, functioning as an 'ambassador' capable of recommending the finest attractions and activities available at the destination. In contemporary times, when tourists plan their trips, they make a series of consecutive decisions, with the most important decision being to lock-in the accommodation reservation for the earliest days, so as to secure a safe arrival. Consequently, tourists place their trust in the accommodation provider not only for lodging but also for recommendations regarding restaurants, activities, and more. Thus, the latter has the opportunity to inform and influence tourists well in advance of their arrival, particularly during the booking phase, namely when it comes to selecting their mode of transportation. The pressing need to reduce greenhouse gas emissions within the tourism sector presents an opportunity to underscore the influence that accommodation providers have historically exerted on tourist decision-making . Methodology A participatory research, currently ongoing in south-western France, in collaboration with a nationwide hotel group and several destination management organizations, aims at examining the factors that determine the ability of accommodation providers to influence tourist transportation choices. Additionally, the research seeks to identify the conditions that motivate accommodation providers to assume a proactive role, such as fostering customer loyalty, reduced distribution costs, and financial compensation mechanisms. A panel of hotels participated in a series of focus group sessions with tourists, with the objective of modeling the decision-making process of tourists regarding their choice of transportation mode and to identify and quantify the types and levels of incentives liable to encourage environmentally responsible choices. Individual interviews were also conducted with hotel staff, including receptionists and guest relations officers, to develop a framework for interactions with tourists during crucial decision-making moments related to transportation choices. The primary finding of this research indicates that financial incentives significantly outweigh symbolic incentives in motivating tourists to opt for eco-friendly modes of transportation. Another noteworthy result underscores the crucial impact of organizational conditions governing interactions with tourists both before and during their stay. These conditions greatly influence the ability to raise awareness at key decision-making moments and the possibility of gathering data about the chosen transportation mode during the stay. In conclusion, this research has led to the formulation of practical recommendations for accommodation providers and Destination Marketing Organizations (DMOs). These recommendations pertain to communication protocols with tourists, the collection of evidences confirming chosen transportation modes, and the implementation of necessary incentives. Through these measures, accommodation provider can assume a central role in guiding tourists towards making responsible choices in terms of transportation.

Keywords: accommodation provider, trusted third party, environmentally-friendly transportation, green house gas, tourist decision-making process

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Authors: Ubaid Ur Rahman, Waqar Younas, Sooraj Kumar Chhabira

Abstract:

Environmentally sustainable building construction has experienced significant growth during the past 10 years at international level. This paper shows that the conceptual framework adopts sustainability techniques in construction to develop environment friendly building called green building. Waste occurs during the different construction phases which causes the environmental problems like, deposition of waste on ground surface creates major problems such as bad smell. It also gives birth to different health diseases and produces toxic waste agent which is specifically responsible for making soil infertile. Old recycled building material is used in the construction of new building. Sustainable construction is economical and saves energy sources. Sustainable construction is the major responsibility of designer and project manager. The designer has to fulfil the client demands while keeping the design environment friendly. Project manager has to deliver and execute sustainable construction according to sustainable design. Steel is the most appropriate sustainable construction material. It is more durable and easily recyclable. Steel occupies less area and has more tensile and compressive strength than concrete, making it a better option for sustainable construction as compared to other building materials. New technology like green roof has made the environment pleasant, and has reduced the construction cost. It minimizes economic, social and environmental issues. This paper presents an overview of research related to the material use of green building and by using this research recommendation are made which can be followed in the construction industry. In this paper, we go through detailed analysis on construction material. By making suitable adjustments to project management practices it is shown that a green building improves the cost efficiency of the project, makes it environmental friendly and also meets future generation demands.

Keywords: sustainable construction, green building, recycled waste material, environment

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Authors: Wuttigrai Ngamsirijit

Abstract:

Talent management in today’s modern organizations has become data-driven due to a demand for objective human resource decision making and development of analytics technologies. HR managers have been faced with some obstacles in exploiting data and information to obtain their effective talent management decisions. These include process-based data and records; insufficient human capital-related measures and metrics; lack of capabilities in data modeling in strategic manners; and, time consuming to add up numbers and make decisions. This paper proposes a framework of talent management through integration of talent value chain and human capital analytics approaches. It encompasses key data, measures, and metrics regarding strategic talent management decisions along the organizational and talent value chain. Moreover, specific predictive and prescriptive models incorporating these data and information are recommended to help managers in understanding the state of talent, gaps in managing talent and the organization, and the ways to develop optimized talent strategies.    

Keywords: decision making, human capital analytics, talent management, talent value chain

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Authors: Muhammad Sulman, Tabinda Khurshid, Afsheen Masood

Abstract:

The current research focused on determining the factors that determine the brand loyalty in consumers. It was hypothesized that there are certain demographical features that lead the consumers to adhere more towards certain brands. Cross-sectional research design was used. The sample for the current research comprised of participants (N=500) from age group 16 to 55 years. The data was collected through self-constructed demographic questionnaire as well as from a self-constructed Brand Loyalty Questionnaire. Brand Loyalty Questionnaire was adapted after taking permission from researchers. A pilot study was conducted to chalk out all the ambiguities of the questionnaire. The final version was administered on 250 participants. The descriptive and inferential analyses were carried on through SPSS version 24.00 to explore the factors that determine Brand Loyalty. The findings revealed that there is a relationship between brand loyalty and brand loyalty demographics and certain factors emerged as significant predictors of brand loyalty in young and middle aged consumers. The research findings carry strong implications for organizational and consumer psychologists in particular and for professionals in marketing and policy making in general.

Keywords: consumers, consumer psychologists, marketing, organizational, policy making

Procedia PDF Downloads 271