• KIPS Transactions on Computer and Communication Systems
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• v.9 no.9
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• pp.207-212
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• 2020

The amount of data has increased significantly due to advances in technology, and various big data processing platforms are emerging, to handle it. Among them, the most widely used platform is Hadoop developed by the Apache Software Foundation, and Hadoop is also used in the IoT field. However, the existing Hadoop-based IoT sensor data collection and analysis environment has a problem of overloading the name node due to HDFS' Small File, which is Hadoop's core project, and it is impossible to update or delete the imported data. This paper uses Apache Kudu and Impala to design Lambda Architecture. The proposed Architecture classifies IoT sensor data into Cold-Data and Hot-Data, stores it in storage according to each personality, and uses Batch-View created through Batch and Real-time View generated through Apache Kudu and Impala to solve problems in the existing Hadoop-based IoT sensor data collection analysis environment and shorten the time users access to the analyzed data.

• Archives of design research
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• v.17 no.3
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• pp.363-372
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• 2004

Lannon(1994) asserted, 'Today consumer market has reached its maturity, and products gets more and more similar. So brands should be distinguished from competitors by emotional values.' Parody ads, one of advertisements appealing to emotion, would distort some original work well known to the public with its blemish or seriousness on target by imitating or exaggerating it regardless of expression styles, and announce the results to criticize the work itself or social situations or excite laughter. Such parody ads are stimulating consumers' emotion in particular and diverse methods. But This study on parody and especially parody in advertising, deals with the basic concepts of parody in advertising, as well as copyright infringement issues highlighting the different legal interpretations in American and Korean law when dealing with indiscreet cases of parody in advertising. some suggestions are made on desirable and forword-looking solutions. Different to the acceptance of parody in the American culture, Korean law was limiting in allowing parody to be used and applied.

• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.81-88
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• 2021

Convertible bonds are financial products that contain the nature of both bonds and shares, which are generally issued by companies with lower credit ratings to increase liquidity. Conversion bonds rely on qualitative judgment in the past, although decision-making on whether and when to exercise the right to convert is the most important issue. Therefore, this paper proposes to apply artificial neural network techniques to scientifically determine the exercise of conversion rights. We distinguish between a total of 1,800 learning data published in the past and 200 predictive experimental data and build an artificial neural network learning model. As a result, the parity performance in most groups was excellent, achieving an average excess of about 10% or more. In particular, groups 3-6 recorded an average excess of about 20% and group 6 recorded an average excess of about 37%. This paper is meaningful in that it focused on solving decision problems by converging and applying machine learning techniques, a representative technology of the fourth industry, to the financial sector.

• The Transactions of the Korea Information Processing Society
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• v.1 no.2
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• pp.225-236
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• 1994

Many research result conducted by neural network researchers claimed that the degree of generalization of the neural network system is higher or at least equal to that of statistical methods. However, those successful results could be brought only if the neural network was trained by appropriately sound data, having a little of noisy data and being large enough to control noisy data. Real data used in a lot of fields, especially business fields, were not so sound that the network have frequently failed to obtain satisfactory prediction accuracy, the degree of generalization. Enhancing the degree of generalization with noisy data is discussed in this study. The suggestion, which was obtained through a series of experiments, to enhance the degree of generalization is to remove inconsistent data by checking overlapping and inconsistencies. Furthermore, the previous conclusion by other reports is also confirmed that the learning mechanism of neural network takes average value of two inconsistent data included in training set［2］. The interim results of on-going research project are reported in this paper These are ann architecture of the neural network adopted in this project and the whole idea of developing on-line credit evaluation system,being intergration of the expert(resoning)system and the neural network(learning system.Another definite result is corroborated through this study that quickprop,being agopted as a learing algorithm, also has more speedy learning process than does back propagation even in very noisy environment.

• Journal of Intelligence and Information Systems
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• v.16 no.1
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• pp.93-116
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• 2010

Ensemble approach is applied to the detection modeling of illegal cash accommodation (ICA) that is the well-known type of fraudulent usages of credit cards in far east nations and has not been addressed in the academic literatures. The performance of fraud detection model (FDM) suffers from the imbalanced data problem, which can be remedied to some extent using an ensemble of many classifiers. It is generally accepted that ensembles of classifiers produce better accuracy than a single classifier provided there is diversity in the ensemble. Furthermore, recent researches reveal that it may be better to ensemble some selected classifiers instead of all of the classifiers at hand. For the effective detection of ICA, we adopt ensemble size reduction technique that prunes the ensemble of all classifiers using accuracy and diversity measures. The diversity in ensemble manifests itself as disagreement or ambiguity among members. Data imbalance intrinsic to FDM affects our approach for ICA detection in two ways. First, we suggest the training procedure with over-sampling methods to obtain diverse training data sets. Second, we use some variants of accuracy and diversity measures that focus on fraud class. We also dynamically calculate the diversity measure-Forward Addition and Backward Elimination. In our experiments, Neural Networks, Decision Trees and Logit Regressions are the base models as the ensemble members and the performance of homogeneous ensembles are compared with that of heterogeneous ensembles. The experimental results show that the reduced size ensemble is as accurate on average over the data-sets tested as the non-pruned version, which provides benefits in terms of its application efficiency and reduced complexity of the ensemble.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.655-660
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• 2022

This paper analyzes the problem of the economic order quantity (lot size) of a retailer in a two-stage supply chain consisting of a supplier, a retailer(distributor), and a customer. In this two-stage supply chain, the supplier permits the retailer to defer payment for a certain fixed period of time for the purchase cost to be paid by the retailer as a price differentiation strategy with his competitor. In addition, in the case of customer goods such as food and grain, it is common to see that end-customer demand is generally depend on the level of inventory displayed by the retailer. From this perspective, this paper analyzes the inventory problem of retailers under the assumption that the supplier may allow a certain period to suspend payments for the purchase of goods and the end customer demand is a function of the retailer's inventory level increasing with size. In this regard, we need to analyze how much the length of the grace period for product purchase costs affect the retailer's lot-sizing policy. Therefore, we formulate the retailer's annual net profit and analyze the effect of the length of credit period on the retailer's inventory policy numerically.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.4
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• pp.167-176
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• 2024

The Personal Information Protection Commission was launched in August 2020 as an integrated control tower for personal information protection, but several problems have been pointed out in the personal information protection operation system. First, despite the fact that Korea's personal information protection system has an integrated legal system that regulates both the public and private sectors, it has been pointed out that it is difficult to carry out smooth personal information protection functions due to incomplete integration of protection functions, such as the Financial Services Commission being in charge of personal credit information protection and the Korea Communications Commission being in charge of personal location information protection. Next, despite the increasing number of public sector personal information leakage incidents, there is a lack of personnel with expertise and specialized support organizations to efficiently investigate them, and there is a concern that the lack of an efficient response system to personal information infringement by global IT companies in Korea in the era of digital commerce may weaken the protection of citizens' personal information. In order to solve these problems, I reviewed overseas cases and literature and proposed the following measures. First, it is necessary to centralize the personal information protection supervision function for credit information and location information to the Personal Information Protection Commission. Second, it is necessary to secure expertise by securing specialized personnel and establishing specialized institutions to respond to public sector personal information leakage incidents. Third, it is necessary to revitalize the domestic agency designation system and establish an international cooperation system to protect people's personal information in the digital commerce era. I believe that these measures to develop the personal information protection system will lead to more systematic personal information protection.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.113-137
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• 2021

According to the clear potential of mobile banking growth, many studies related to this are being conducted, but in Korea, it is concentrated on the analysis of technical factors or consumers' intentions, behaviors, and satisfaction. In addition, even though it has a strong customer base of 20s, there are few studies that have been conducted specifically for this customer group. In order for mobile banking to take a leap forward, a strategy to secure various perspectives is needed not only through research on itself but also through research on external factors affecting mobile banking. Therefore, this study analyzes impulsiveness, credit card use, and SNS addiction among various external factors that can significantly affect mobile banking in their 20s. This study examines whether the relationship between impulsiveness and mobile banking usage depends on whether or not a credit card is used, and checks whether a customer's impulsiveness is possible by examining whether a credit card is used. Based on this, it is possible to establish new standards for classification of marketing target groups of mobile banking. After finding out the static or unsuitable relationship between whether to use a credit card and impulsiveness, we want to indirectly predict the customer's impulsiveness through whether to use a credit card or not to use a credit card. It also verifies the mediating effect of SNS addiction in the relationship between impulsiveness and mobile banking usage. For this analysis, the collected data were conducted according to research problems using the SPSS Statistics 25 program. The findings are as follows. First, positive urgency has been shown to have a significant static effect on mobile banking usage. Second, whether to use credit cards has shown moderating effects in the relationship between fraudulent urgency and mobile banking usage. Third, it has been shown that all subfactors of impulsiveness have significant static relationships with subfactors of SNS addiction. Fourth, it has been confirmed that the relationship between positive urgency, SNS addiction, and mobile banking usage has total effect and direct effect. The first result means that mobile banking usage may be high if positive urgency is measured relatively high, even if the multi-dimensional impulsiveness scale is low. The second result indicates that mobile banking usage rates were not affected by the independent variable, negative urgency, but were found to have a significant static relationship with negative urgency when using credit cards. The third result means that SNS is likely to become addictive if lack of premeditation or lack of perseverance is high because it provides instant enjoyment and satisfaction as a mobile-based service. This also means that SNS can be used as an avoidance space for those with negative urgency, and as an emotional expression space for those with high positive urgency.

• Journal of KIISE:Information Networking
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• v.35 no.4
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• pp.345-354
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• 2008

Recently, small-scale mobile network which is composed of many mobile devices in a man becomes popular. Also, Examples of large-scale mobile network can be thought access networks deployed on public transportation such as ships, trains and buses. To provide seamless mobility for mobile nodes in this mobile network, binding update messages must be exchanged frequently. However, it incurs network overhead increasingly and decreases energy efficiency of mobile router. If we try to reduce the number of the messages to cope with the problem, it may happen the security -related problems conversely Thus, mobile router needs a effective algorithm to update location information with low cost and to cover security problems. In this paper, mobility management scheme based on mobile router's mobility pattern is proposed. Whenever each mobile router leaves a visiting network, it records related information as moving log. And then it periodically computes mean resident time for all visited network, and saves them in the profile. If each mobile router moves into the visited network hereafter, the number of binding update messages can be reduced since current resident time may be expected based on the profile. At this time, of course, security problems can happen. The problems, however, are solved using key credit, which just sends some keys once. Through extensive experiments, bandwidth usages are measured to compare binding update messages in proposed scheme with that in existing scheme. From the results, we can reduce about 65% of mobility-management-related messages especially when mobile router stays more than 50 minutes in a network. Namely, the proposed scheme improves network usage and energy usage of mobile router by decreasing the number of messages and authorization procedure.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.5
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• pp.163-171
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• 2011

In e-commerce environment, security should be considered as an essential factor for success. In this paper, we analyze security requirements for e-commerce system, and it is focused on the practical usage, not theoretical contribution, in the field of e-commerce security. To identify the security requirements being specific to e-commerce environment, the researches related to e-commerce security are surveyed and a phase of Delphi method and Analytic Hierarchy Process(AHP) are used to determine the relative importance of e-commerce security factors. Since researchers and practitioners can have significantly different views because of each different work environment, we divide the professionals into two respondents' group. This survey result can be useful security guidelines in the development of e-commerce service system from the initial system development step to the completion.