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

• Journal of KIISE:Computing Practices and Letters
• /
• v.12 no.2
• /
• pp.129-140
• /
• 2006

The existing CBD development methods deal with the analysis phase in a superficial manner. Applying such a superficial analysis to business applications with a number of subsystems makes analysis models be inconsistent with levels and styles, only depending on experiences of the analysts. This inconsistent analysis might cause more serious problems during the subsequent development phases, resulting in the failure of the projects. In this paper, we propose a rule-based analysis pattern that provides an analysis template for business applications. This pattern analyzes the concepts of business applications by using external events and internal rules that process the events. Employing this pattern, a huge business application can be developed by a couple of co-analysts who work together in a consistent and systematic manner. This paper also describes an efficient way to develop business components with the suggested analysis pattern using banking deposit case study through UML Components development process.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.115-115
• /
• 2000

A gait pattern classification method using electromyography(EMG) signal is presented. The gait pattern with four stages such as stance, heel-off, swing and heel-strike is analyzed and classified using feature parameters such as zero-crossing, integral absolute value and variance of the EMG signal. The EMG signal from Tibialis Anterior and Gastrocnemius muscles was obtained using the surface electrodes, and low-pass filtered at 10kHz. The filtered analog signal was sampled at every 0.5msec and converted to digital signal with 12-bit resolution. The obtained data is analyzed and classified in terms of feature parameters. Analysis results are given to show that the gait patterns classified by the proposed method are feasible.

• Korean Management Science Review
• /
• v.30 no.1
• /
• pp.43-58
• /
• 2013

Although analysis of charts, which used in stock trading by distinguishing standardized patterns in the movements of stock prices, is simple and easy to use, there can be problems stemming from specific patterns being distinguished as a result of the subjective perspectives of analysts. In accordance with such problems, through the method of template pattern matching, 4 trend reversal patterns were designed and the fitness of the patterns were quantitatively measured. In cases when a stock is purchased when the template pattern fitness value is within a certain range and held for at least 20-days, the average return ratio was analyzed to be higher-with the difference being statistically significant-than the average return ratio attained from trading a stock according to the same method per the Efficient Market Hypothesis. From the results of stock trades of 2 domestic corporations to which the values of the 4 patterns had been applied based on the 4 strategies, it was possible to ascertain differences in the strategy- and pattern-dependent return ratios. Through this study, along with presenting the exceptions for the Efficient Market Hypothesis in stock trading, the fitness level of quantitative chart patterns was measured and the theoretical basis for application of such fitness level was proposed.

• The Korean Journal of Applied Statistics
• /
• v.26 no.6
• /
• pp.933-942
• /
• 2013

Common factor analysis and principal component analysis represent two technically distinctive approaches to exploratory factor analysis. Much of the psychometric literature recommends the use of common factor analysis instead of principal component analysis. Nonetheless, factor analysts use principal component analysis more frequently because they believe that principal component analysis could yield (relatively) less accurate estimates of factor loadings compared to common factor analysis but most often produce similar pattern of factor loadings, leading to essentially the same factor interpretations. A simulation study is conducted to evaluate the relative performance of these two approaches in terms of factor pattern recovery under different experimental conditions of sample size, overdetermination, and communality.The results show that principal component analysis performs better in factor recovery with small sample sizes (below 200). It was further shown that this tendency is more prominent when there are a small number of variables per factor. The present results are of practical use for factor analysts in the field of marketing and the social sciences.

• The KIPS Transactions:PartD
• /
• v.13D no.7 s.110
• /
• pp.947-958
• /
• 2006

In order to increase extensibility and reusability of business components, the variable things need to be analyzed from the analysis phase and identified as components. In this paper, we propose a rule-based analysis pattern, which can effectively extract object-based main concepts from a variable business process in the analysis phase and identify a variable business component by applying the pattern to the UML Components development process. It can make analysis artifacts consistent and readable for analysts with different level of knowledge and experience to apply the pattern to analysis of rule-based variable business processes. And also, variable business components can be easily identified by applying the pattern to the UML Components development process. In order to prove the feasibility of the pattern, we have applied the pattern the deposit and import/export subsystem of the banking domain. According to our experience, we can make the same business conceptual models between the deposit and import/export subsystem due to the main concepts suggested by the pattern and effectively identify a variable business components in the UML Components development process.

• Journal of KIISE:Databases
• /
• v.27 no.2
• /
• pp.165-174
• /
• 2000

Recent researches about range queries in OLAP are only concerned with applying an aggregation operator over a certain region. However, data analysts in real world need not only the simple range query pattern but also an extended range query pattern that finds ranges which satisfy a special condition specified by using several aggregation operators. In this work, we define the general form of the extended range query and propose an efficient processing method for the 'MAX -of-SUM' query, which is the representative form of the extended range query pattern. The MAX-of-SUM query finds the range which has the maximum range sum value in data cube where the size of the range is given. The proposed query processing method is based on the prediction of the scope of the range sum values. That is, the search space on the query processing can be reduced by using the result of the prediction, and hence, the query response time is also reduced.

• Journal of the Korean Institute of Educational Facilities
• /
• v.21 no.1
• /
• pp.3-11
• /
• 2014

The policies is always changes according to the changing times, and changes take place in educational facilities welfare policy. Early childhood facilities, is no exception. Recent, increase in the number of kindergarten and kindergarten children according to policy changes of government's active welfare. This change in pattern, policy changes and increased support to know the impact on the community, and this is not just a simply agenda that they need to be recognized social change. In addition, it can be seen changes in relevant laws and educational process according to childhood policy change flow and depending on social change. In this study, comparative study infants and installation of the facility based on criteria, ensuring standards of early childhood facility site, facilities of evolution of infants care act, act infants, infants of activities safety management. And Standards and facilities that are required to change the direction of the revision is for the purpose of research through changes in kindergarten curriculum to respond the policies flow. Research methods are literature on the various laws and research analysts, leading comparison of different child care and child care policy changes in laws and regulations to review materials are analyzed.

• Journal of Internet of Things and Convergence
• /
• v.9 no.1
• /
• pp.77-87
• /
• 2023

Applying various association rule mining algorithms to the network intrusion detection task involves two critical issues: too large size of generated rule set which is hard to be utilized for IoT systems and hardness of control of false negative/positive rates. In this research, we propose an association rule mining algorithm based on the newly defined measures called coverage and exclusion. Coverage shows how frequently a pattern is discovered among the transactions of a class and exclusion does how frequently a pattern is not discovered in the transactions of the other classes. We compare our algorithm experimentally with the Apriori algorithm which is the most famous algorithm using the public dataset called KDDcup99. Compared to Apriori, the proposed algorithm reduces the resulting rule set size by up to 93.2 percent while keeping accuracy completely. The proposed algorithm also controls perfectly the false negative/positive rates of the generated rules by parameters. Therefore, network analysts can effectively apply the proposed association rule mining to the network intrusion detection task by solving two issues.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.4
• /
• pp.709-719
• /
• 2015

This paper introduces a proper renaming service using variable action and security services against the analysis techniques in Java code. The renaming service that is introduced is separated into API pattern and loop condition. We present our scheme algorithm with known Java obfuscation techniques and tools in order to help readers understanding, and implement prototype to prove practicality in this paper. Test result using prototype shows 73% successful variable renaming rate. Using our scheme, cooperators can intuitionally understand all of code. Also, It helps malware analysts to predict malware action by variable name. But application source code that is developed by Java is exposed to hackers easily using our scheme. So we introduce Java application code protection methods, too.