• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.5
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• pp.911-918
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• 2014

Over the past few years, security breaches have been consistently reported around the world. Especially, people's personal information are at risk of being breached as the firms gather and utilize the information for their marketing purposes. As an effort to revamp their data infrastructures, companies have rebuilt their system that almost every data, including the personal information, are stored within the digital database. However, this migration provides easier access to the database but it has also increased the system vulnerability. As the data can be easily exposed to the unauthorized personnel both intentionally and unintentionally, it is necessary for companies to establish a set of security protocol and operate the personal information protection system. There are two major certified security system in South Korea; PIMS from KISA and PIPL from NIA. This paper analyzes the preferences of SMEs and small business using conjoint attributes of PIMS and PIPL. The study shows that the business owners take post certification rewards as the most important factor. It also shows that the attributes that have the highest utility rates are the following; 1) KISA certification, 2) 79 points of protection counter measurements, 3) 28 items of life cycle, 3) 50 percent discount on certification fee, and 4) Reduced amount of fine for personal information leakage incident.

• The Journal of Society for e-Business Studies
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• v.24 no.2
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• pp.199-216
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• 2019

The public SW market is 3 trillion won, which is less than 10% of the total SW market. However, due to the nature of the domestic market, it is an important market with a relatively large impact on small and medium-sized software companies. In this market, government is operating the Public SW Project Demand Forecasting System in order to support the marketing activities of small and medium sized SW companies and establish a fair market order. The current system has limitations such as lack of user convenience, insufficient analysis capability and less business connection. This study was conducted to identify the problems of these systems and to propose a new system for improving the convenience of users and expanding the information utilization of SMEs. To this end, we analyzed the requirements of each stakeholder. We proposed the 2-phased forecasting cycle, the management cycle, and the system life cycle of public SW projects and created a unified identifier (UID) so that the information of those projects can be identified and linked among them. As a result, an integrated reference model of project information management based on system life cycle was developed, which can explain the demand forecasting and project information, and the improved processes was also designed to implement them. Through the result of this study, it is expected that integrated management of public SW projects will be possible.

• The Journal of Society for e-Business Studies
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• v.27 no.1
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• pp.15-28
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• 2022

Due to recent expansion of online market such as clothing, utilizing customer review has become a major marketing measure. User review has been used as a tool of analyzing sentiment of customers. Sentiment analysis can be largely classified with machine learning-based and lexicon-based method. Machine learning-based method is a learning classification model referring review and labels. As research of sentiment analysis has been developed, multi-modal models learned by images and video data in reviews has been studied. Characteristics of words in reviews are differentiated depending on products' and customers' categories. In this paper, sentiment is analyzed via considering review data and metadata of products and users. Gated Recurrent Unit (GRU), Long Short-Term Memory (LSTM), Self Attention-based Multi-head Attention models and Bidirectional Encoder Representation from Transformer (BERT) are used in this study. Same Multi-Layer Perceptron (MLP) model is used upon every products information. This paper suggests a multi-modal sentiment analysis model that simultaneously considers user reviews and product meta-information.

• The Journal of Society for e-Business Studies
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• v.27 no.1
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• pp.43-62
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• 2022

This paper is a study to analyze when ISV(independent software company) has more active participation in the platform ecosystem. According to previous studies, companies are active in technological innovation when they can appropriate the outcome of innovation and when they have complementary assets (marketing, manufacturing capabilities, etc.) that can convert the innovation into value. The effect of these two conditions to join platform ecosystem is investigated. The duplication between the ISV's product portfolio and platform service is also included as an independent variable. The two sample groups are composed of independent SW companies that signed a partner agreement with platform companies and non-participating companies in the platform. As a result of empirical study, it is found that the patent rights do not affect participation in the platform. The ISVs might have believed that the benefits from cooperation with platform companies are greater than the risks of exposure to innovative technologies and unique Biz models. On the other hand, downstream's capability and the duplication of product portfolio affect participation in the platform. If ISVs have the downstream capability to transform cooperation into value creation, ISVs are actively participating in the platform. In addition, cooperation is active when the product portfolio is complementary to platform service rather than competition. This study is the empirical study of open innovation between Korean independent software companies and digital platform companies. There are similar prior studies abroad, but there are no similar studies in Korea. It is meaningful in that the determinants of platform ecosystem participation were investigated through empirical analysis by composing a sample group of companies participating in the platform ecosystem and companies not participating in the platform ecosystem.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.71-79
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• 2024

ChatGPT, an interactive artificial intelligence (AI) chatbot developed by Open AI in the U.S., gaining popularity with great repercussions around the world. Some academia are concerned that ChatGPT can be used by students for plagiarism, but ChatGPT is also widely used in a positive direction, such as being used to write marketing phrases or website phrases. There is also an opinion that ChatGPT could be a new future for "search," and some analysts say that the focus should be on fostering rather than excessive regulation. This study analyzed consciousness about ChatGPT for college students through a survey of their perception of ChatGPT. And, plagiarism inspection systems were prepared to establish an education support model using ChatGPT and ChatGPT. Based on this, a university education support model using ChatGPT was constructed. The education model using ChatGPT established an education model based on text, digital, and art, and then composed of detailed strategies necessary for the era of the 4th industrial revolution below it. In addition, it was configured to guide students to use ChatGPT within the permitted range by using the ChatGPT detection function provided by the plagiarism inspection system, after the instructor of the class determined the allowable range of content generated by ChatGPT according to the learning goal. By linking and utilizing ChatGPT and the plagiarism inspection system in this way, it is expected to prevent situations in which ChatGPT's excellent ability is abused in education.

• Fire Science and Engineering
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• v.31 no.4
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• pp.95-102
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• 2017

The fires in the traditional markets often occur recently with the most of them expanded into great fires so that the damage is very serious. The status of traditional markets handling the distribution for ordinary people is greatly shrunk with the aggressive marketing of the local large companies and the foreign large distribution companies after the overall opening of the local distribution market. Most of the traditional markets have the history and tradition from decades to centuries and have grown steadily with the joys and sorrows of ordinary people and the development of the local economy. The fire developing to the large fire has the characteristics of the problem that the fire possibility is high since all products can be flammable due to the deterioration of facilities, the arbitrary modification of equipment, and the crowding of the goods for sale. Furthermore, most of the stores are petty with their small sizes so that the passage is narrow affecting the passage of pedestrians. Accordingly, the traditional markets are vulnerable to fire due to the initial unplanned structural problem so that the large scale fire damage occurs. The study is concerned with systematically classifying and analyzing the result by applying the TRIZ tool to the fire risk factors to extract the fundamental problem with the fire of the traditional market and make the active response. The study was done for preventing the fire on the basis of it and the expansion to the large fire in case of fire to prepare the specific measure to minimize the fire damage. On the basis of the fire expansion risk factor of the derived traditional market, the study presented the passive measures such as the improvement of the fire resisting capacity, the fire safety island, etc. and the active and institutional measures such as the obligation of the fire breaking news facilities, the application of the extra-high pressure pump system, the divided use of the electric line, etc.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.101-107
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• 2014

With the development of online service, recent forms of databases have been changed from static database structures to dynamic stream database structures. Previous data mining techniques have been used as tools of decision making such as establishment of marketing strategies and DNA analyses. However, the capability to analyze real-time data more quickly is necessary in the recent interesting areas such as sensor network, robotics, and artificial intelligence. Landmark window-based frequent pattern mining, one of the stream mining approaches, performs mining operations with respect to parts of databases or each transaction of them, instead of all the data. In this paper, we analyze and evaluate the techniques of the well-known landmark window-based frequent pattern mining algorithms, called Lossy counting and hMiner. When Lossy counting mines frequent patterns from a set of new transactions, it performs union operations between the previous and current mining results. hMiner, which is a state-of-the-art algorithm based on the landmark window model, conducts mining operations whenever a new transaction occurs. Since hMiner extracts frequent patterns as soon as a new transaction is entered, we can obtain the latest mining results reflecting real-time information. For this reason, such algorithms are also called online mining approaches. We evaluate and compare the performance of the primitive algorithm, Lossy counting and the latest one, hMiner. As the criteria of our performance analysis, we first consider algorithms' total runtime and average processing time per transaction. In addition, to compare the efficiency of storage structures between them, their maximum memory usage is also evaluated. Lastly, we show how stably the two algorithms conduct their mining works with respect to the databases that feature gradually increasing items. With respect to the evaluation results of mining time and transaction processing, hMiner has higher speed than that of Lossy counting. Since hMiner stores candidate frequent patterns in a hash method, it can directly access candidate frequent patterns. Meanwhile, Lossy counting stores them in a lattice manner; thus, it has to search for multiple nodes in order to access the candidate frequent patterns. On the other hand, hMiner shows worse performance than that of Lossy counting in terms of maximum memory usage. hMiner should have all of the information for candidate frequent patterns to store them to hash's buckets, while Lossy counting stores them, reducing their information by using the lattice method. Since the storage of Lossy counting can share items concurrently included in multiple patterns, its memory usage is more efficient than that of hMiner. However, hMiner presents better efficiency than that of Lossy counting with respect to scalability evaluation due to the following reasons. If the number of items is increased, shared items are decreased in contrast; thereby, Lossy counting's memory efficiency is weakened. Furthermore, if the number of transactions becomes higher, its pruning effect becomes worse. From the experimental results, we can determine that the landmark window-based frequent pattern mining algorithms are suitable for real-time systems although they require a significant amount of memory. Hence, we need to improve their data structures more efficiently in order to utilize them additionally in resource-constrained environments such as WSN(Wireless sensor network).

• Journal of Dairy Science and Biotechnology
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• v.27 no.2
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• pp.55-62
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• 2009

Milk is called an almost complete food in terms of nutrition, especially for the younger generations because it contains a number of nutrients required for growth and development. Lactose intolerance is defined as a malabsorption of lactose in the intestine with some typical symptoms of abdominal pains and bloating, and occurred at 75% of global populations, which hampers milk consumption worldwide. Lacks of milk consumption in the underdeveloped countries frequently lead to many nutrients deficiencies, so that diseases including osteoporosis, hypertension, and colon cancer are more prevalent in the recent days. Lactose in foods needs to be hydrolyzed prior to intestinal absorption. The hydrolytic enzyme responsible for splitting lactose into its monomeric forms, glucose and galactose, is called as lactase or $\beta$-galactosidase. The former is primarily used as blood sugar and energy source and the latter used in glycolipid synthesis of brain tissues in infants. Lactose is clinically diagnosed with the breath hydrogen production test as well as intestinal biopsy. Reportedly, symptoms of lactose intolerance are widely prevalent at 25% of Europeans, 50 to 80% of Hispanics, South Indians, Africans, and Jews, almost 100% of Asians and native Americans. For the adults, phenotype of lactase persistence, which is able to hydrolyse lactose, is more common in the northern Europeans, but in the other area lactase non-persistence or adult-type hypolactasia is dominant. Genetic analysis on human lactase gene continued that lactase persistence was closely related to the err site of 1390 single nucleotide polymorphism from the 5'-end. To alleviate severity of lactose intolerance symptoms, some eating patterns including drinking milk a single cup or less, consumption along with other foods, whole milk rather than skimmed milk, and drink with live yogurt cultures, are highly recommended for the lactose maldigesters. Also, delay of gastric emptying is effective to avoid the symptoms from lactose intolerance. Frequency of lactose intolerance with conventional diagnosis is thought overestimated mainly because the subjects are exposed to too much lactose of 50 g rather than a single serving amount. Thus simple and accurate diagnostic method for lactose intolerance need to be established. It is thought that fermented milk products and low- or free lactose milks help improve currently stagnant milk consumption due to lactose intolerance which contributes to major barrier in milk marketing especially in Asian countries.

• The KIPS Transactions:PartD
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• v.12D no.3 s.99
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• pp.417-428
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• 2005

Today, IT organizations perform projects with vision related to marketing and financial profit. The objective of realizing the vision is to improve the project performing ability in terms of QCD. Organizations have made a lot of efforts to achieve this objective through process improvement. Large companies such as IBM, Ford, and GE have made over $80\%$ of success through business process re-engineering using information technology instead of business improvement effect by computers. It is important to collect, analyze and manage the data on performed projects to achieve the objective, but quantitative measurement is difficult as software is invisible and the effect and efficiency caused by process change are not visibly identified. Therefore, it is not easy to extract the strategy of improvement. This paper measures and analyzes the project performance, focusing on organizations' external effectiveness and internal efficiency (Qualify, Delivery, Cycle time, and Waste). Based on the measured project performance scores, an OT (Opportunity Tree) model was designed for optimizing the project performance. The process of design is as follows. First, meta data are derived from projects and analyzed by quantitative GQM(Goal-Question-Metric) questionnaire. Then, the project performance model is designed with the data obtained from the quantitative GQM questionnaire and organization's performance score for each area is calculated. The value is revised by integrating the measured scores by area vision weights from all stakeholders (CEO, middle-class managers, developer, investor, and custom). Through this, routes for improvement are presented and an optimized improvement method is suggested. Existing methods to improve software process have been highly effective in division of processes' but somewhat unsatisfactory in structural function to develop and systemically manage strategies by applying the processes to Projects. The proposed OT model provides a solution to this problem. The OT model is useful to provide an optimal improvement method in line with organization's goals and can reduce risks which may occur in the course of improving process if it is applied with proposed methods. In addition, satisfaction about the improvement strategy can be improved by obtaining input about vision weight from all stakeholders through the qualitative questionnaire and by reflecting it to the calculation. The OT is also useful to optimize the expansion of market and financial performance by controlling the ability of Quality, Delivery, Cycle time, and Waste.

• Journal of the Korean Geographical Society
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• v.39 no.4
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• pp.643-664
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• 2004

This study aims to review what geographers have contributed to GIS industries and national needs. To-be-geographers and geographers are expected to meet the gap between what we have teamed in school and what we have to do after graduation. The characteristics of GIS industry in the 1990 are summarized with approximate evaluation of the contribution of geographers in each stage. Author introduced the requirement for the licenses of geomatics and geospatial engineering experts and the other licenses, which are important to get a job in GIS industry from 2003 to 2004. A set of questionnaire on the user's requirements was given to GIS people in private companies and public GIS research centers and analyzed. Author found that they put an emphasis on hands-on experiences and programming skills. no advantages or geography such as capability or integration and inter-disciplinary collaboration were not appreciated. The prospects for the GIS tend to be positive but the reflectance of the prospect was not accompanied by at the same degree of preference for geography. Most government strategies for the next ten years' GIS focus on new-growth leading industries. SWOT(strength, weakness, opportunity, threat) analysis of geography for GIS industry will give some directions such as telematics, regional marketing strategies with web-based GIS technology, location based service. That means intra-disciplinary study in geography will evoke the potentiality of GIS, compared with interdisciplinary studies.