scholarly journals TASC-MADM: Task Assignment in Spatial Crowdsourcing Based on Multiattribute Decision-Making

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Yunhui Li ◽  
Liang Chang ◽  
Long Li ◽  
Xuguang Bao ◽  
Tianlong Gu
Keyword(s):  
Decision Making ◽  
Real World ◽  
Task Assignment ◽  
The Other ◽  
Synthetic Dataset ◽  
Spatial Crowdsourcing ◽  
Fundamental Challenge ◽  
Dual Objectives ◽  
Assignment Approach

The methodology, formulating a reasonable task assignment to find the most suitable workers for a task and achieving the desired objectives, is the most fundamental challenge in spatial crowdsourcing. Many task assignment approaches have been proposed to improve the quality of crowdsourcing results and the number of task assignment and to limit the budget and the travel cost. However, these approaches have two shortcomings: (1) these approaches are commonly based on the attributes influencing the result of task assignment. However, different tasks may have different preferences for individual attributes; (2) the performance and efficiency of these approaches are expected to be improved further. To address the above issues, we proposed a task assignment approach in spatial crowdsourcing based on multiattribute decision-making (TASC-MADM), with the dual objectives of improving the performance as well as the efficiency. Specifically, the proposed approach jointly considers the attributes on the quality of the worker and the distance between the worker and the task, as well as the influence differences caused by the task’s attribute preference. Furthermore, it can be extended flexibly to scenarios with more attributes. We tested the proposed approach in a real-world dataset and a synthetic dataset. The proposed TASC-MADM approach was compared with the RB-TPSC and the Budget-TASC algorithm using the real dataset and the synthetic dataset; the TASC-MADM approach yields better performance than the other two algorithms in the task assignment rate and the CPU cost.

scholarly journals Evaluation of quality assurance instruments in higher education institutions: A case of Oman

2021 ◽  
Vol 35 (3) ◽  
Author(s):  
A. S. Al-Amri ◽  
Y. Z. Zubairi ◽  
R. Jani ◽  
S. Naqvi
Keyword(s):  
Higher Education ◽  
Decision Making ◽  
Quality Assurance ◽  
Higher Education Institutions ◽  
The Other ◽  
Summary Statistics ◽  
Staff Members ◽  
Other Hand ◽  
Analyse Data

The use of a variety of instruments for quality assurance, management, and enhancement in higher education is well recognized. This article investigated the instruClose Panelments used by Higher Education Institutions (HEIs) in Oman to measure, control, and manage the quality of their services in alignment with the standards set by Oman Academic Accreditation Authority (OAAA). Quality Assurance Managers (QAMs) from five HEIs were interviewed to identify the instruments used by them to fulfil the requirements of each standard and the way they make use of the data gathered by using these instruments. Findings from the study reveal that questionnaires and meetings are the most common instruments used by these institutions to measure, control and assure the efficacy of their current quality activities. In addition, HEIs use summary statistics to analyse data and then present them in meetings or through reports. On the other hand, it was found that substantial efforts are made to collect data but the efficient usage of data is missing. The QAMs reported a lack of awareness among the staff on the importance of collecting data since the staff members believe that these data are collected for documentation purposes only. This study emphasizes the importance of using the data gathered from different instruments in decision making and enhancing the quality of HEIs.

Voter Information Processing and Political Decision Making

2019 ◽  
Author(s):  
Alessandro Nai
Keyword(s):  
Decision Making ◽  
Information Processing ◽  
Individual Differences ◽  
Selective Exposure ◽  
Political Information ◽  
The Other ◽  
Electoral Campaigns ◽  
Political Choices ◽  
The One

Contemporary political information processing and the subsequent decision-making mechanisms are suboptimal. Average voters usually have but vague notions of politics and cannot be said to be motivated to invest considerable amount of times to make up their minds about political affairs; furthermore, political information is not only complex and virtually infinite but also often explicitly designed to deceive and persuade by triggering unconscious mechanisms in those exposed to it. In this context, how can voters sample, process, and transform the political information they receive into reliable political choices? Two broad set of dynamics are at play. On the one hand, individual differences determine how information is accessed and processed: different personality traits set incentives (and hurdles) for information processing, the availability of information heuristics and the motivation to treat complex information determine the preference between easy and good decisions, and partisan preferences establish boundaries for information processing and selective exposure. On the other hand, and beyond these individual differences, the content of political information available to citizens drives decision-making: the alleged “declining quality” of news information poses threats for comprehensive and systematic reasoning; excessive negativity in electoral campaigns drives cynicism (but also attention); and the use of emotional appeals increases information processing (anxiety), decreases interest and attention (rage), and strengthens the reliance on individual predispositions (enthusiasm). At the other end of the decisional process, the quality of the choices made (Was the decision supported by “ambivalent” opinions? And to what extent was the decision “correct”?) is equally hard to assess, and fundamental normative questions come into play.

Contributions of Real-World Evidence and Real-World Data to Decision-Making in the Management of Soft Tissue Sarcomas

Oncology ◽  
2021 ◽  
Vol 99 (Suppl. 1) ◽  
pp. 3-7
Author(s):  
George D. Demetri ◽  
Silvia Stacchiotti
Keyword(s):  
Decision Making ◽  
Soft Tissue ◽  
Real World ◽  
Soft Tissue Sarcomas ◽  
Clinical Settings ◽  
Disease Entity ◽  
Real World Data ◽  
World Data ◽  
Real World Evidence

Real-world data are defined as data relating to any aspect of a patient’s health status collected in the context of routine health surveillance and medical care delivery. Sources range from insurance billing claims through to electronic surveillance data (e.g., activity trackers). Real-world data derive from large populations in diverse clinical settings and thus can be extrapolated more readily than clinical trial data to patients in different clinical settings or with a variety of comorbidities. Real-world data are used to generate real-world evidence, which might be regarded as a “meta-analysis” of accumulated real-world data. Increasingly, regulatory authorities are recognizing the value of real-world data and real-world evidence, especially for rare diseases where it may be practically unfeasible to conduct randomized controlled trials. However, the quality of real-world evidence depends on the quality of the data collected which, in turn, depends on a correct pathological diagnosis and the homogeneous behaviour of a reliably defined and consistent disease entity. As each of the more than 80 varieties of soft tissue sarcoma (STS) types represents a distinct disease entity, the situation is exceedingly complicated. Discordant diagnoses, which affect data quality, present a major challenge for use of real-world data. As real-world data are difficult to collect, collaboration across sarcoma reference institutions and sophisticated information technology solutions are required before the potential of real-world evidence to inform decision-making in the management of STS can be fully exploited.

Task Planning Considering Location Familiarity in Spatial Crowdsourcing

2021 ◽  
Vol 17 (2) ◽  
pp. 1-24
Author(s):  
Chaoqun Peng ◽  
Xinglin Zhang ◽  
Zhaojing Ou ◽  
Junna Zhang
Keyword(s):  
Simulated Annealing Algorithm ◽  
Target Location ◽  
Task Assignment ◽  
Product Placement ◽  
Divide And Conquer ◽  
Task Planning ◽  
Spatial Crowdsourcing ◽  
Divide And Conquer Algorithm ◽  
Distributed Problem Solving

Spatial crowdsourcing (SC) is a popular distributed problem-solving paradigm that harnesses the power of mobile workers (e.g., smartphone users) to perform location-based tasks (e.g., checking product placement or taking landmark photos). Typically, a worker needs to travel physically to the target location to finish the assigned task. Hence, the worker’s familiarity level on the target location directly influences the completion quality of the task. In addition, from the perspective of the SC server, it is desirable to finish all tasks with a low recruitment cost. Combining these issues, we propose a Bi-Objective Task Planning (BOTP) problem in SC, where the server makes a task assignment and schedule for the workers to jointly optimize the workers’ familiarity levels on the locations of assigned tasks and the total cost of worker recruitment. The BOTP problem is proved to be NP-hard and thus intractable. To solve this challenging problem, we propose two algorithms: a divide-and-conquer algorithm based on the constraint method and a heuristic algorithm based on the multi-objective simulated annealing algorithm. The extensive evaluations on a real-world dataset demonstrate the effectiveness of the proposed algorithms.

scholarly journals Decision Making with Dynamic Uncertain Events

2015 ◽  
Vol 54 ◽  
pp. 233-275 ◽  
Author(s):  
Meir Kalech ◽  
Shulamit Reches
Keyword(s):  
Decision Making ◽  
Approximation Algorithms ◽  
Optimal Algorithm ◽  
The Other ◽  
Uncertain Information ◽  
Effective Algorithm ◽  
Key Factor ◽  
The One ◽  
The Cost

When to make a decision is a key question in decision making problems characterized by uncertainty. In this paper we deal with decision making in environments where information arrives dynamically. We address the tradeoff between waiting and stopping strategies. On the one hand, waiting to obtain more information reduces uncertainty, but it comes with a cost. Stopping and making a decision based on an expected utility reduces the cost of waiting, but the decision is based on uncertain information. We propose an optimal algorithm and two approximation algorithms. We prove that one approximation is optimistic - waits at least as long as the optimal algorithm, while the other is pessimistic - stops not later than the optimal algorithm. We evaluate our algorithms theoretically and empirically and show that the quality of the decision in both approximations is near-optimal and much faster than the optimal algorithm. Also, we can conclude from the experiments that the cost function is a key factor to chose the most effective algorithm.

scholarly journals Real-world decision making in the upstream oil and gas industry—prescriptions for improvement

2008 ◽  
Vol 48 (1) ◽  
pp. 329
Author(s):  
Steve I Mackie ◽  
Steve H Begg ◽  
Chris Smith ◽  
Matthew Welsh
Keyword(s):  
Decision Making ◽  
Real World ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Gas Industry ◽  
The Real ◽  
Decision Outcomes ◽  
Decision Making Processes ◽  
Decision Making Model

Business under-performance in the upstream oil and gas industry, and the failure of many decisions to return anticipated results, has led to a growing interest in the past few years in understanding the impacts of decision-making processes and their relationship with decision outcomes. Improving oil and gas decision making is, thus, increasingly seen as reliant on an understanding of the processes of decision making in the real world. There has been significant work carried out within the discipline of cognitive psychology, observing how people actually make decisions; however, little is known as to whether these general observations apply to decision making in the upstream oil and gas industry. This paper is a step towards filling this gap by developing the theme of decision-making process. It documents a theoretical decision-making model and a real-world decision-making model that has been distilled from interviews with many Australian upstream oil and gas professionals. The context of discussion is to review the theoretical model (how people should make decisions) and the real-world model (how people do make decisions). By comparing and contrasting the two models we develop a prescriptive list of how to improve the quality of decisions in practice, specifically as it applies in the upstream oil and gas industry.

scholarly journals Aspects Of Multicriterial Mathematical Modeling And Of The Fuzzy Formalism For The Hierarchization Of Study Programs Based On Several Quality Characteristics

2015 ◽  
Vol 67 (1) ◽  
pp. 1-6
Author(s):  
Amelia Bucur
Keyword(s):  
Mathematical Modeling ◽  
Decision Making ◽  
Utility Theory ◽  
Quality Characteristics ◽  
The Other ◽  
Weighting Method ◽  
Multicriterial Optimization ◽  
Study Programs ◽  
Simple Additive Weighting

Abstract The aim of this paper is to present aspects of mathematical modeling for the hierarchization of study programs from universities, based on several quality characteristics. The tools used pertain to multicriterial optimization, to the different methods of assessing importance coefficients, to the utility theory, the fuzzy formalism, and to the fuzzy simple additive weighting method. The conclusion is that multicriterial decision-making methods can be efficiently used in assessing the quality of study programs, noting that, just like other methods from the decision theory, the multicriterial decision-making methods highlight aspects of problems differently, therefore, there can be no comparison or competitiveness between them, and choosing one over the other is up to the decision-maker.

scholarly journals AN OBJECTIVE MULTI-CRITERIA APPROACH TO OPTIMIZATION USING MOORA METHOD AND INTERVAL GREY NUMBERS

2012 ◽  
Vol 18 (2) ◽  
pp. 331-363 ◽  
Author(s):  
Dragisa Stanujkic ◽  
Nedeljko Magdalinovic ◽  
Rodoljub Jovanovic ◽  
Sanja Stojanovic
Keyword(s):  
Decision Making ◽  
Real World ◽  
Operational Research ◽  
The Other ◽  
Previous Period ◽  
Moora Method ◽  
Real World Problems

Many real-world problems are complex and/or related to the manifestation of some form of uncertainty and/or prediction. Therefore the use of extended MCDM methods is more appropriate than the use of the other classic decision making methods. These methods are improved by the use of a form of fuzzy or interval grey numbers. In the field of operational research, during the previous period, numerous MCDM methods were formed, but one newly proposed, the MOORA method, is very specific and yet has no extension. Therefore, in this paper we combine concept of interval grey numbers and MOORA method in order to propose extended MOORA method which will be more appropriate to solve many complex real-world problems.

scholarly journals Socio-Psychological Factors of a Personal Decision on Labor Migration

2020 ◽  
Keyword(s):  
Decision Making ◽  
Work Experience ◽  
Labor Migration ◽  
Psychological Factors ◽  
Necessary Conditions ◽  
Social Indicators ◽  
The Other ◽  
The One ◽  
Personal Decision

The article deals with the problem of decision-making by an individual on labor migration. There was studied directly the phenomenon of labor migration, its features in the global and Ukrainian scale. The modality of influence on the development of the economy and public life of Ukraine is considered. There were outlined social and psychological factors influencing decision making. Among the factors, the crisis life situations of a person are highlighted, namely, an age crisis, a spiritual crisis, a biographical crisis. We also describe the life strategies by which a person is guided in his life. Such an important factor as the nervousness of the situation in which a person is found is considered. The levels of his stress resistance. The phenomenon of "decision" and the necessary conditions for its adoption are analyzed. There was theoretically substantiated the study of the effectiveness dependence in the decision-making process on social indicators and psychological criteria of the personality. The sample in the study consisted of 44 women who are citizens of Ukraine, 22 women of whom have work experience abroad, and the other half is considering this option and is in the process of forming and making an appropriate decision. As a result of empirical research, certain parameters of dependence were found by socio-psychological factors in decision-making. Considering the psychological aspect, there was found a relationship between the prevailing coping strategy that a person chooses to act in stressful situations and the general indicator of resilience - on the one hand, and the ability to make decisions - on the other. The result of our research is a developed program that helps women in overcoming internal obstacles on the way to improving the quality of their own life, because the ability to make decisions indicates the awareness of oneself as a subject of their own life about sufficient resilience.

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