• Land and Housing Review
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• v.11 no.1
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• pp.103-108
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• 2020

Autonomous things system is a technology that judges and acts based on using surrounding information by itself, and it is evaluated as a future technology that can replace the current IoT technology. The current IoT technology is widely used from facility monitoring to machine control but it is shown weakness as a evaluation and prediction technique despite of smart city important technology. In this study, in order to confirm the application of the autonomous things technology, a monitoring system was installed on a real reservoir dam facility and long-term monitoring was performed that the measuring device itself judges and control as a facility monitoring technology. The autonomous things technology was confirmed during 19 months and it is possible to continuous measurement in the same way as current automated instrumentation. In addition, it was confirmed that the ICT device itself could to control autonomously measurement cycle according to the rainfall by itself.

• The Journal of Economics, Marketing and Management
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• v.8 no.1
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• pp.12-19
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• 2020

Purpose - Strategic causes for the failure include unrealistic growth, overexpansion, unfamiliar new markets, volume obsession, unrealistic promises and poor project selection. Organizational causes are insufficient capital and profits, lack of business knowledge, poor financial management, poor sales skills, inadequate marketing, poor leadership, poor leadership transfer, project losses, poor field performance and owner bankruptcy. Uncontrollable causes include industry and economic weakness and banking and surety changes. While helpful, the list provides insufficient clarity regarding the causal roots of failure. Research design, data and methodology - The research framework to organize the information involved with many of the recent and large failures in the industry. Results - This research then identified five dominant root causes - excessive egoism, poor strategic leadership, too much change, loss of discipline and inadequate capitalization. Conclusion - Finally, additional input from external forces may accelerate the firm's pace to failure. It is important on the development of diagnostic tools that are based on this model and that will provide new ways to assess a conglomerate's level of risk for incurring a financial crisis.

• Iberoamérica
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• v.13 no.1
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• pp.351-388
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• 2011

Many global business failures have been ascribed to a lack of intercultural competence, especially to a lack of an adequate conceptualization and definition of intercultural competence, focusing instead on the knowledge, skills, and attributes that appear to be its antecedents. Intercultural competence should be perceived as multifaceted important components of global management capabilities. Depending on the related concepts of intercultural competence, such as global mindset, intercultural sensitivity, and cultural intelligence, dynamic aspects of intercultural competence as learning process are suggested. Also, the domain of intercultural competence in the context of global management or business comprised three dimensions - perception management, relationship management, and self management. Each dimension is characterized by facets that further delineate aspects of intercultural competence. With respect to the domain of intercultural competence, appropriateintercultural training methods should be designed. In practice, human resource managers may benefit from gaining knowledge about which measures to use for identifying employee's weakness in intercultural competence in order to create appropriate training programs.

• Journal of the Korea Society of Computer and Information
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• v.19 no.12
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• pp.247-255
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• 2014

This study supplements the existing bus information system's weakness which is a text-based system, transmits GUI based user request contents, design and implements the bus information system using smart-phone GPS. The existing bus information system had to install the terminals on the bus and take enormous expenses on maintenance with setting up the direction board on each bus station. The proposed system provides bus route and user location using the smart-phone map screen, finds the nearest bus station, indicates the bus route on map screen, applies our algorithm which increases accuracy of the bus arriving time, and provides route construction of the inner-cycle bus. The accuracy of the estimated bus arriving time has increased to about 88.71% which is 22.71% more than the existing system whose accuracy is 67% and improved into GUI form that the existing system was on text and table UI. Consequently, the upgraded bus information system uses the smart-phone GPS to supplement the existing bus information system and satisfies different requests of users.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4662-4679
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• 2015

Currently, the leakage of internal information has emerged as one of the most significant security concerns in enterprise computing environments. Especially, damage due to internal information leakage by insiders is more serious than that by outsiders because insiders have considerable knowledge of the system's identification and password (ID&P/W), the security system, and the main location of sensitive data. Therefore, many security companies are developing internal data leakage prevention techniques such as data leakage protection (DLP), digital right management (DRM), and system access control, etc. However, these techniques cannot effectively block the leakage of internal information by insiders who have a legitimate access authorization. The security system does not easily detect cases which a legitimate insider changes, deletes, and leaks data stored on the server. Therefore, we focused on the insider as the detection target to address this security weakness. In other words, we switched the detection target from objects (internal information) to subjects (insiders). We concentrated on biometrics signals change when an insider conducts abnormal behavior. When insiders attempt to leak internal information, they appear to display abnormal emotional conditions due to tension, agitation, and anxiety, etc. These conditions can be detected by the changes of biometrics signals such as pulse, temperature, and skin conductivity, etc. We carried out experiments in two ways in order to verify the effectiveness of the emotional recognition technology based on biometrics signals. We analyzed the possibility of internal information leakage detection using an emotional recognition technology based on biometrics signals through experiments.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.6
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• pp.1449-1461
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• 2018

As the number of software vulnerabilities grows year by year, attacks on software are also taking place a lot. As a result, the security administrator must identify and patch vulnerabilities in the software. However, it is important to prioritize the patches because patches for all vulnerabilities are realistically hard. In this paper, we propose a scoring system that expands the scale of risk assessment metric by taking into consideration attack patterns or weaknesses cause vulnerabilities with the vulnerability information provided by the NIST(National Institute of Standards and Technology). The proposed scoring system is expanded based on the CWSS and uses only public vulnerability information to utilize easily for any company. In this paper, we applied the automated scoring system to software vulnerabilities, and showed the expanded metrics with consideration for influence of attack pattern and weakness are meaningful.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.204-211
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• 2020

In this paper, we propose an optimal deep learning network architecture for main object location detection through weak supervised learning. The proposed network adds convolution blocks for improving the localization accuracy of the main object through weakly-supervised learning. The additional deep learning network consists of five additional blocks that add a composite product layer based on VGG-16. And the proposed network was trained by the method of weakly-supervised learning that does not require real location information for objects. In addition, Grad-CAM to compensate for the weakness of GAP in CAM, which is one of weak supervised learning methods, was used. The proposed network was tested through the CUB-200-2011 data set, we could obtain 50.13% in top-1 localization error. Also, the proposed network shows higher accuracy in detecting the main object than the existing method.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.17 no.6
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• pp.65-76
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• 2007

The P2P file sharing system sends the results to users by searching the files in the shared folders. In the process of it, the problem is that the transferred information includes the pathname and file information and it can be revealed who searches which files. In related to this problem, anonymous file sharing P2P protocol has been an active research area where a number of works have been produced. However, the previous studies still have a few of weakness. Therefore, We propose two anonymous P2P file sharing protocols based on the decentralized and unstructured Random Walk. The first scheme uses the dynamic onion routing where the requester can receive the wanted file without knowing other peers' IDs. The second scheme uses the IP multicast method which lowers the computational overhead. Both of them are more suited for the dynamic P2P system.

• Korean Journal of Cognitive Science
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• v.35 no.1
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• pp.49-95
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• 2024

Polygraph examination, statement validity analysis and P300-based concealed information test are major three examination tools, which are use to determine a person's truthfulness and credibility in criminal procedure. Although polygraph examination is most common in criminal procedure, but it has little admissibility of evidence due to the weakness of scientific basis. In 1990s to support the weakness of scientific basis about polygraph, Farwell and Donchin proposed the P300-based concealed information test technique. The P300-based concealed information test has two strong points. First, the P300-based concealed information test is easy to conduct with polygraph. Second, the P300-based concealed information test has plentiful scientific basis. Nevertheless, the utilization of P300-based concealed information test is infrequent, because of the quantity of probe stimulus. The probe stimulus contains closed information that is relevant to the crime or other investigated situation. In tradition P300-based concealed information test protocol, three or more probe stimuli are necessarily needed. But it is hard to acquire three or more probe stimuli, because most of the crime relevant information is opened in investigative situation. In addition, P300-based concealed information test uses oddball paradigm, and oddball paradigm makes imbalance between the number of probe and irrelevant stimulus. Thus, there is a possibility that the unbalanced number of probe and irrelevant stimulus caused systematic underestimation of P300 amplitude of irrelevant stimuli. To overcome the these two limitation of P300-based concealed information test, one-probe P300-based concealed information test protocol is explored with various machine learning algorithms. According to this study, parameters of the modified one-probe protocol are as follows. In the condition of female and male face stimuli, the duration of stimuli are encouraged 400ms, the repetition of stimuli are encouraged 60 times, the analysis method of P300 amplitude is encouraged peak to peak method, the cut-off of guilty condition is encouraged 90% and the cut-off of innocent condition is encouraged 30%. In the condition of two-syllable word stimulus, the duration of stimulus is encouraged 300ms, the repetition of stimulus is encouraged 60 times, the analysis method of P300 amplitude is encouraged peak to peak method, the cut-off of guilty condition is encouraged 90% and the cut-off of innocent condition is encouraged 30%. It was also conformed that the logistic regression (LR), linear discriminant analysis (LDA), K Neighbors (KNN) algorithms were probable methods for analysis of P300 amplitude. The one-probe P300-based concealed information test with machine learning protocol is helpful to increase utilization of P300-based concealed information test, and supports to determine a person's truthfulness and credibility with the polygraph examination in criminal procedure.

• Journal of Korean Library and Information Science Society
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• v.40 no.2
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• pp.287-310
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• 2009

This paper strives to shed a new light on current academic resource sharing initiatives of both Korea Research Foundation(KRF) and Korea Science and Engineering Foundation(KOSEF), and seeks the measure to administer information resource effectively for a unified organization, which will launch soon, through the comparison and scrutiny, and analyses of strength and weakness on current projects. It first of all attempts to draw outcomes and suggestions on the basis of issues and implications identified through the exhaustive as-is analyses in the aspects of management, service, and infrastructure of academic resource sharing initiatives carried out by each foundations. The unification of projects and information systems are discussed in two aspects, as viewed each significant measures, that is, 1) an organizational aspect in terms to develop a new academic and research information service through the unification of operation systems related to information service project of each foundation; 2) An Initiative toward the integrated service via the unification of scattered individual unit systems in each foundation.