• Journal of Information Technology Services
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• v.14 no.1
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• pp.53-68
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• 2015

This article aims to identify the quality factors of public data which have increased as a public issue; analyze the impact of users satisfaction in the perspective of Technology Acceptance Model (TAM), and investigate the effect of service satisfaction on the government's open policy of public data. This study is consistent with Total Data Quality Management (TDQM) of MIT, it focuses on three main qualities except Contextual Data Quality (CDQ) and includes seven independent variables : accuracy, reliability, fairness for Intrinsic Data Quality (IDQ), accessibility, security for Accessibility Data Quality (ADQ), Consistent representation and understandability for Representational Data Quality (RDQ). Basing on TAM, the research model was conducted to examine which factors affect to perceived usefulness, perceived ease of use, service satisfaction and how service satisfaction affects to the government's open policy of public data. The results showed that accuracy, fairness, understandability affect both perceived ease of use and perceived usefulness; while reliability, consistent representation, security, and accessibility affect only perceived ease of use. This article found that the influence of perceived ease of use on perceived usefulness and the influence of these two causes on service satisfaction in the perspective of TAM were significant and it was consistent with prior studies. The service satisfaction when using public data leads to the reliability of public data open policy. As an initial study on unstructured public data open policy, this article offered quality factors that pubic data providers should consider and also present the operation plan of public data open policy in the future.

• Convergence Security Journal
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• v.23 no.1
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• pp.27-33
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• 2023

Digitalization due to COVID-19 has rapidly developed artificial intelligence-based voice recognition technology. However, this technology causes unfair social problems, such as race and gender discrimination if datasets are biased against some groups, and degrades the reliability and security of artificial intelligence services. In this work, we compare and analyze accuracy-based unfairness in biased data environments using VGGNet (Visual Geometry Group Network), ResNet (Residual Neural Network), and MobileNet, which are representative CNN (Convolutional Neural Network) models of artificial intelligence. Experimental results show that ResNet34 showed the highest accuracy for women and men at 91% and 89.9%in Top1-accuracy, while ResNet18 showed the slightest accuracy difference between genders at 1.8%. The difference in accuracy between genders by model causes differences in service quality and unfair results between men and women when using the service.

• Development and Reproduction
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• v.15 no.1
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• pp.71-76
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• 2011

Due to its role in maintaining the health of scientific societies, research ethics (or integrity) is notably receiving attention by academia, governments and even individuals who are not engaged in scientific researches. In this paper, I will introduce some valuable papers dealt with plagiarism as a representative research misconduct. In general, researcher's results that will soon be published must meet the crucial scientific criteria: originality, accuracy, reproducibility, precision and research ethics. The definition of plagiarism is "appropriation of another person's ideas, processes, results, or words without giving appropriate credit." Compared to fabrication and falcification, plagiarism is often considered as a minor misconduct. With intentionality, however, plagiarism can be corresponding to 'theft of intellectual product'. The context of plagiarism is not restricted to the stage of publication. It can be extended to prior stages of proposing (i.e. preparing the research proposal) and performing (executing the research), and reviewing (writing the review papers). Duplicate publication is regarded as a self-plagiarism in broad interpretation of plagiarism. To avoid dangers of plagiarism, earnest efforts from all members of scientific community are needed. First of all, researchers should keep 'transparency' and 'integrity' in their scientific works. Editorial board members and reviewers should keep fairness and well-deserved qualification. Government and research foundations must be willing to provide sufficient financial and policy support to the scientific societies; Up-graded editorial services, making good use of plagiarism detection tools, and thorough instruction on how to write a honest scientific paper will contribute to building up a healthy basis for scientific communities.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.259-278
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• 2022

With the spread of Artificial Intelligence (AI), various AI-based services are expanding in the financial sector such as service recommendation, automated customer response, fraud detection system(FDS), credit scoring services, etc. At the same time, problems related to reliability and unexpected social controversy are also occurring due to the nature of data-based machine learning. The need Based on this background, this study aimed to contribute to improving trust in AI-based financial services by proposing a checklist to secure fairness in AI-based credit scoring services which directly affects consumers' financial life. Among the key elements of trustworthy AI like transparency, safety, accountability, and fairness, fairness was selected as the subject of the study so that everyone could enjoy the benefits of automated algorithms from the perspective of inclusive finance without social discrimination. We divided the entire fairness related operation process into three areas like data, algorithms, and user areas through literature research. For each area, we constructed four detailed considerations for evaluation resulting in 12 checklists. The relative importance and priority of the categories were evaluated through the analytic hierarchy process (AHP). We use three different groups: financial field workers, artificial intelligence field workers, and general users which represent entire financial stakeholders. According to the importance of each stakeholder, three groups were classified and analyzed, and from a practical perspective, specific checks such as feasibility verification for using learning data and non-financial information and monitoring new inflow data were identified. Moreover, financial consumers in general were found to be highly considerate of the accuracy of result analysis and bias checks. We expect this result could contribute to the design and operation of fair AI-based financial services.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.8
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• pp.543-553
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• 2020

The purpose of this study is to investigate factors affecting the leadership capacity of middle managers and then evaluate the corresponding effect on the performance of subordinates in Vietnamese economic and defense enterprises. Data for the study was collected from questionnaire survey of 15 economic and defense enterprises, preceded by in-depth interviews with respondents who are subordinates of the departments/divisions of these enterprises. The research used logistic regression estimator to address econometric issues and to improve the accuracy of the regression coefficients. Our results show that the determinants of the leadership capacity of mid-level managers in defense and economic enterprises include: (i) personal qualities and qualities of managerial officials (understanding, courage), fairness, assertiveness and compliance), and leadership behaviors of two leadership styles - (ii) a transforming leadership style (influenced by ideals, inspirations, concerns) subordinates, stimulating intellect) and (iii) transactional leadership style (rewarding, detecting and handling problems for subordinates). Based on these results, our study suggests that middle managers should possess superior knowledge, care more about subordinates, understand the strengths and weaknesses of each subordinate, always be creative, assertive and courageous people as well as have high standards of competency and morality in order to become outstanding leaders in Vietnamese economic and defense enterprises.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.191-202
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• 2023

This study aims to propose a framework for evaluating the impact of artificial intelligence (AI) services, based on the concept of AI service impact. It also suggests a model for evaluating this impact and identifies relevant factors and measurement approaches for each item of the model. The study classifies the impact of AI services into five categories: ethics, safety and reliability, compliance, user rights, and environmental friendliness. It discusses these five categories from a broad perspective and provides 21 detailed factors for evaluating each category. In terms of ethics, the study introduces three additional factors-accessibility, openness, and fairness-to the ten items initially developed by KISDI. In the safety and reliability category, the study excludes factors such as dependability, policy, compliance, and awareness improvement as they can be better addressed from a technical perspective. The compliance category includes factors such as human rights protection, privacy protection, non-infringement, publicness, accountability, safety, transparency, policy compliance, and explainability.For the user rights category, the study excludes factors such as publicness, data management, policy compliance, awareness improvement, recoverability, openness, and accuracy. The environmental friendliness category encompasses diversity, publicness, dependability, transparency, awareness improvement, recoverability, and openness.This study lays the foundation for further related research and contributes to the establishment of relevant policies by establishing a model for evaluating the impact of AI services. Future research is required to assess the validity of the developed indicators and provide specific evaluation items for practical use, based on expert evaluations.

• Journal of Information Technology Services
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• v.3 no.1
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• pp.21-41
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• 2004

The technical proposal suggested and published by MIC(Ministry of Information and Communication, henceforth MIC) contains too general assessment elements, which causes qualitative and subjective assessment of technical proposals. Thus, in terms of the technical proposal assessment. It lacks In fairness, validity and accuracy. Furthermore, it has a great deal of difficulty in assessment caused by the inconsistency between proposal planning and assessment methods. Also, each company has different writing format, so it is impossible to make use of its maneuvering data for the assessment. To overcome these weaknesses, our research focused on a quantitative evaluation on development organization, which is a part of organizational and administrative part of the technical proposal suggested and published by MIC. In this research, we divided development organization for the technical proposal into organization, teams, and team members, and then studied addition, deletion and merging for the assessment criteria. For the related study, we chose especially CMM(Capability Maturity Model) from a lot of international and national references, which is a model measuring the maturity of organization, and then we focused on Small-CMM which is available in the small-sized organization. We also suggested input form, description method, assessment elements for the quantitative assessment in the chosen developmental organization, and finally we proposed standard referencing criteria for the assessment. Our study concludes that our assessment method are valid and available in comparison with the previous Delphi method through a validity evaluation test.

• Journal of Fisheries and Marine Sciences Education
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• v.24 no.2
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• pp.234-245
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• 2012

This study aims to analyze the factors of the extra-curricula area in personal school performance record and propose the practical strategies for entrance examination affairs on this area. To address this goal, we have applied a SWOT analysis with related documents and research results. We found out five strengths: (S1) Link the students' experience to right people for the university, (S2) Quantitative Indicators, (S3) Qualitative Indicators, (S4) Link to other evaluation factors, and (S5) Analysis of Human Resource. The weakness included: (W1) Fairness, (W2) Reliability, (W3) Difficulties to set standards, (W4) Difficulties to set environments, and (W5) Lack of systemic experience of an evaluation. We also discovered five opportunities (O1) Recognition of public education, (O2) The need of national support, (O3) The importance of autonomy, (O4) Specialization, and (O5) Networks. Finally, threat factors consisted of: (T1) Frequent change of educational policy, (T2) Increasing of private education, (T3) Lack of information and preparation time, and (T4) The accuracy and reliability of personal school records. Based on these results, we suggested practical strategies with these four dimensions: S-O, W-O, S-T, and W-T.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.6 no.2
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• pp.1-10
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• 2003

The purpose of this study was to survey the status of the operation of site-based environmental education(EE) programs. This study surveyed 165 schools and organizations that operated site-based EE program in 2000 using a mail questionnaire and interviews. The response rate was 43%. The result indicated that awareness, participation, and attitude were considerably addressed, while knowledge and skills were addressed to a lesser degree. There were some difficulties in motivating students and in considering the developmental stage of participants. For programing the site-based EE, financial support and expert knowledge of EE were needed most of all. Learning materials for various and hand-on activities were also needed. The affective domain, such as awareness and attitude, showed marked improvement in the outcomes of the programs. Direct experience and sensitivity, connection with school education, regional characteristics were sufficiently addressed in the programs, while cultural aspects, fairness, originality, and accuracy were not. Flexibility in performing the programs and less rigidity of report on operations were needed. Through the discussion of the results, some improvements for the operation of site-based EE program were suggested.

• The Korean Society of Law and Medicine
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• v.13 no.2
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• pp.115-139
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• 2012

Civil proceedings, surveyed results and medical expenses that are evidenced by expert witness are just one of the methods of proof. Since a judge makes decision by synthesizing all evidences on a concerned case, thus the judgement would be different from that of expert witness. It is not rational for medical institutions, of which priorities are medical treatment, to give priority to disability decision. However, despite of its importance, medical institutions less recognize about the necessity of procedural stability and predictability in expert valuation. It is necessary to identify actual problems and investigate rational alternatives to acquire fairness in valuation procedures and accuracy in calculating future medical expenses. Therefore, this research explores the problems and realities of evaluation process in medical treatments, and then discuss the alternatives of written expert opinion and estimation of future medical expenses.