• East Asian Journal of Business Economics (EAJBE)
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• v.4 no.4
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• pp.8-20
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• 2016

Banks are the engines that drive the operations in financial sector, money markets and growth of economy. With growing banking industry in India, frauds in Banks are increasing and fraudsters are becoming more sophisticated and ingenious. Shockingly, banking industry in India dubs rising fraud as "an inevitable cost of doing business." As part of study, a questionnaire-based survey was conducted in 2012-13 among 345 Bank employees "to know their perception towards bank frauds and evaluate factors that influence the degree of their compliance level." The study reveals, "there are poor employment practices and lack of effective employee training; usually over-burdened staff, weak internal control systems, and low compliance levels on the part of Bank Managers, Offices and Clerks. Although banks cannot be 100% secure against unknown threats, a certain level of preparedness can go a long way in countering fraud risk. Internal audit professionals should play an integral role in organization's fraud-fighting efforts. Some other promising steps are: educate customers about fraud prevention, make application of laws more stringent, leverage the power of data analysis technologies, follow fraud mitigation best practices, and employ multipoint scrutiny.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10c
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• pp.4-6
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• 2002

네트워크의 광역화와 새로운 공격 유형의 발생으로 침입 탐지 시스템에서 새로운 시퀀스의 추가나 침입탐지 모델 구축의 수동적인 접근부분이 문제가 되고 있다. 특히 기존의 침입탐지 시스템들은 대량의 네트워크 하부구조를 가진 네트워크 정보를 수집 및 분석하는데 있어 각각 전담 시스템들이 담당하고 있다. 따라서 침입탐지 시스템에서 증가하는 많은 양의 감사데이터를 분석하여 다양한 공격 유형들에 대해서 능동적으로 대처할 수 있도록 하는 것이 필요하다. 최근, 침입 탐지 시스템에 데이터 마이닝 기법을 적용하여 능동적인 침입탐지시스템을 구축하고자 하는 연구들이 활발히 이루어지고 있다. 이 논문에서는 대량의 감사 데이터를 정확하고 효율적으로 분석하기 위한 마이닝 시스템을 설계하고 구현한다. 감사데이터는 트랜잭션데이터베이스와는 다른 특성을 가지는 데이터이므로 이를 고려한 마이닝 시스템을 설계하였다. 구현된 마이닝 시스템은 연관규칙 기법을 이용하여 감사데이터 속성간의 연관성을 탐사하고, 빈발 에피소드 기법을 적용하여 주어진 시간 내에서 상호 연관성 있게 발생한 이벤트들을 모음으로써 연속적인 시간간격 내에서 빈번하게 발생하는 사건들의 발견과 알려진 사건에서 시퀀스의 행동을 예측하거나 기술할 수 있는 규칙을 생성한 수 있다. 감사데이터의 마이닝 결과 생성된 규칙들은 능동적인 보안정책을 구축하는데 활용필 수 있다. 또한 데이터양의 감소로 침입 탐지시간을 최소화하는데도 기여한 것이다.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.2
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• pp.45-54
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• 2019

This study examines whether auditors restrain the analysts' opportunistic behavior as reviewing the companies' interim reports. Analysts' forecasts show a walkdown pattern in which their optimism has decreased as the earnings announcement date has approached. At the beginning of the year, there is a lack of high-quality benchmark information that enables information users to judge the accuracy of analyst's earnings forecasts. Thus, early in the year, analysts are highly inspired to disseminate optimistic forecasts in order to gain manager's favor. In this study, we examine adequate benchmarks prevent analysts from disclosing optimistically biased forecasts. We conjecture that auditors' efforts might mitigate analysts' walkdown pattern. To test this hypothesis, we use data from Korea, where it is mandatory to disclose auditor's review hours. We find that the analyst forecast's walkdown decreases with the ratio as well as the number of audit hours. It implies that an auditor's effort in reviewing interim financial information has a monitoring function that reduces analysts' opportunistic optimism at the beginning of the year. We conjecture that the tendency will be more pronounced when BIG4 auditors review the interim reports. Consistent with the prediction, BIG4 auditors' interim review effort is more effective in suppressing the analysts' walkdown.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.271-272
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• 2014

As E-discovery in criminal investigation is increasing, the importance of Forensic Tools which can legally extract data with high effectiveness is getting higher. Digital products are growing fast. Therefore, Forensic Tools should be implemented readily to suit users and events well. Although forensic industry and governments use expensive forensic tools, some have suggested limitations to its use, such as memory limitations and the limits of post-audit. We need to develop open source forensic tools that can implement a variety of forensic tool fast. This research studies digital forensics technical skills which are commercialized currently and suggests applicable strategies of the open digital forensics to help overcome these limitations.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.833-849
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• 2021

Cloud accounting represents a new area of accounting information systems. Past research has often focused on accounting information systems and its antecedents, rather than factors that adopt cloud accounting system. The purpose of this paper is to explain the factors that influence the adoption of cloud accounting in the financial sectors. This paper applied the technology acceptance model (TAM), technology-organization-environment, and the De Lone and Mc Lean model, coupled with proposed factors relevant to cloud accounting. The proposed model was empirically evaluated using survey data from 187 managers (financial managers, IT department managers, audit managers, heads of accounting departments, and head of internal control departments) in Jordanian bank branches. Based on the SEM results, top management support, organizational competency, service quality, system quality, perceived usefulness, and perceived ease of use had a positive relationship with the intention of using cloud accounting. Cloud accounting adoption positively affected cloud accounting usage. This paper contributes to a theoretical understanding of factors that activate the adoption of cloud accounting. For financial firms in general the results enable them to better develop cloud accounting framework. The paper verifies the factors that affect the adoption of cloud accounting and the proposed cloud accounting model.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.517-527
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• 2021

While the two principles of lean manufacturing and time-driven activity-based costing (TDABC) have been established out of multiple incentives and do not follow the same particular targets, there is substantial commonality between them. In these conditions, the supply management of a multi-product system needs a rigorous production model to minimize costs. In this sense, this paper proposes an interactive model with the consideration of optimizing product-mix decisions using both lean development tools and TDABC. This paper proposes a qualitative approach using the case study of the Iraqi state company for battery production. The suggested model decreased manufacturing time and costs, along with some substantial reduction in idle production capacity by 26 percent in 2019, based on the findings of the case study. On the other hand, the proposed model gives two side advantages: an efficient division of costs on goods due to the use of time spent as a cost factor for products and cost savings due to the introduction of the lean manufacturing approach that reduces all additional costs and increases product-mix decisions. Furthermore, the analytical data gathered here suggests that the incorporation of lean management concepts and TDABC has a strong and important influence on product-mix decisions.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.11-19
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• 2021

The study aims to investigate the impact of seasonality in Gulf Cooperation Council (GCC) countries' share market during the month of Ramadan. It helps in finding the opportunities for stock market investors to earn abnormal (returns) gain by investing during Ramadan in GCC stock markets. This study uses stock returns data of GCC countries (Saudi Arabia, Bahrain, Qatar, Kuwait, Dubai, and UAE) from January 2004 to November 2019. Stock prices indexes of GCC stock markets have been obtained from Datastream. The ARCH-GARCH model is used to study the impact of the Ramadan month on the return and volatility of the stock market in GCC countries. The results showed that the Ramadan month has a significant impact on share market prices in Saudi Arabia and the United Arab Emirates. However, Ramadan has an insignificant impact on share market prices in Bahrain and Oman. The study found no evidence of serial correlational between residuals in Kuwait; meaning that stock return was not dependent on the prior stock returns in Kuwait, therefore, we cannot go for forecasting. The ARCH-LM test statistic for Qatar does not fulfill the requirement of a good regression model; therefore, we cannot go for forecasting or testing the hypothesis of Qatar.

• Korean Circulation Journal
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• v.53 no.9
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• pp.594-605
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• 2023

Acute myocardial infarction (AMI) is a major cause of morbidity and mortality in the Asia-Pacific region, and mortality rates differ between countries in the region. Systems of care have been shown to play a major role in determining AMI outcomes, and this review aims to highlight pre-hospital and in-hospital system deficiencies and suggest possible improvements to enhance quality of care, focusing on Korea, Japan, Singapore and Malaysia as representative countries. Time to first medical contact can be shortened by improving patient awareness of AMI symptoms and the need to activate emergency medical services (EMS), as well as by developing robust, well-coordinated and centralized EMS systems. Additionally, performing and transmitting pre-hospital electrocardiograms, algorithmically identifying patients with high risk AMI and developing hospital networks that appropriately divert such patients to percutaneous coronary intervention-capable hospitals have been shown to be beneficial. Within the hospital environment, developing and following clinical practice guidelines ensures that treatment plans can be standardised, whilst integrated care pathways can aid in coordinating care within the healthcare institution and can guide care even after discharge. Prescription of guideline directed medical therapy for secondary prevention and patient compliance to medications can be further optimised. Finally, the authors advocate for the establishment of more regional, national and international AMI registries for the formal collection of data to facilitate audit and clinical improvement.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.8
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• pp.2082-2102
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• 2024

Accurate segmentation of magnetic resonance (MR) images is crucial for providing doctors with effective quantitative information for diagnosis. However, the presence of weak boundaries, intensity inhomogeneity, and noise in the images poses challenges for segmentation models to achieve optimal results. While deep learning models can offer relatively accurate results, the scarcity of labeled medical imaging data increases the risk of overfitting. To tackle this issue, this paper proposes a novel fuzzy c-means (FCM) model that integrates a deep learning approach. To address the limited accuracy of traditional FCM models, which employ Euclidean distance as a distance measure, we introduce a measurement function based on the skewed normal distribution. This function enables us to capture more precise information about the distribution of the image. Additionally, we construct a regularization term based on the Kullback-Leibler (KL) divergence of high-confidence deep learning results. This regularization term helps enhance the final segmentation accuracy of the model. Moreover, we incorporate orthogonal basis functions to estimate the bias field and integrate it into the improved FCM method. This integration allows our method to simultaneously segment the image and estimate the bias field. The experimental results on both simulated and real brain MR images demonstrate the robustness of our method, highlighting its superiority over other advanced segmentation algorithms.

• Korean Journal of Health Education and Promotion
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• v.29 no.2
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• pp.83-91
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• 2012

Objectives: This study is to examine that drinking problems among university students were accounted for not only by student's individual characteristics but alcohol policy and environmental characteristics of the university in which students were enrolled. Method: Secondary data analysis was employed in which variables under study were derived from a raw data of a nationwide representative sample in 2009. Raw data under analysis included 3,665 students from 63 universities across Korea. Organizational and environmental characteristics of the university were collected from university administrators while individual characteristics and drinking behavior from the students in using self-administrated questionnaire. Multilevel regression analyses were employed to describe alcohol policy effects on students's drinking problems measured by AUDIT by using HLM7.0. Results: ICCs indicate that variation in drinking problem depends on alcohol policy of university. Multilevel regression models identified statistically significant factors in explaining variance of drinking problems. Group means on drinking problem are affected by indicators representing alcohol policy with level of drinking problem of student being decreased in accordance to level of availability of alcohol on campus. Conclusions: It is concluded that drinking problems among university students were associated with both individual characteristics and alcohol policy of the university they enrolled. This study supports policy belief that interventions at environmental as well as individual level are required to prevent drinking problem among university students.