• Journal of Distribution Science
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• v.18 no.11
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• pp.15-22
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• 2020

Purpose: A marketing strategy for private institutions requires marketers to leverage consumer behaviors and educational psychologies when advertising and promoting product portfolios. Indeed, understanding consumers can make marketers more effective, and the purpose of this research is to tackle private institutions' education marketing by combining marketing theories and learning theories. Research design, data and methodology: The content analysis used in this study will be suitable because there exists numerous prior studies regarding marketing strategy and educational theories. Therefore, the current author could obtain and collect adequate textual facts from much of the literature review. Results: Marketing strategies that are mixed with educational theories increase consumer enrolment due to perceived usefulness, and this implies that an adequate marketing model could help improve sustainability and income as a result of enrollment in private educational institutions. The research also identified that marketing is connected to psychology and that marketers can exploit educational and psychological theories to increase successful enrolment in private educational institutions. Conclusions: Most importantly, the target market for private educational institutions is diverse, and institutions can use direct marketing to appeal to specific audiences. Also, the research implies that diversification strategies can increase enrolment if marketers exploit behavioral learning theories in the marketing process.

• Advances in Energy Research
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• v.6 no.2
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• pp.103-129
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• 2019

While global demand for energy increases annually, at the same time the demand for carbon-free, sulphur-free and NO_x-free energy sources grows considerably. This state poses a challenge in the research for newer sources like biomass and shale gas as well as renewable energy resources such as solar, wind, geothermal and hydraulic energy. Although wave energy also is a form of renewable energy it has not fully been exploited technically and economically so far. This study tries to explain those reasons in which it is beyond doubt that the demand for wave energy will soon increase as fossil energy resources are depleted and environmental concerns gain more importance. The electrical energy supplied to the grid shall be produced from wave energy whose conversion devices can basically work according to three different systems. i. Systems that exploit the motions or shape deformations of their mechanisms involved, being driven by the energy of passing waves. ii. Systems that exploit the weight of the seawater stored in a reservoir or the changes of water pressure by the oscillations of wave height, iii. Systems that convert the wave motions into air flow. One of the aims of this study is to present the classification deficits of the wave energy converters (WECs) of the "wave developers" prepared by the European Marine Energy Center, which were to be reclassified. Furthermore, a new classification of all WECs listed by the European Marine Energy Center was arranged independently. The other aim of the study is to assess the technological state of the art of these WECs designed and/or produced, to obtain an overview on them.

• Journal of IKEEE
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• v.20 no.1
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• pp.111-114
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• 2016

In HEVC, motion estimation is performed independently for each variable block size. So it requires several times of search window data, and also it is difficult to exploit early termination. In this paper, a new method is proposed to exploit search window data and early termination in variable block size. When applied to TZS algorithm, it reduces pixel comparison and search window data accesses to 1/3.7 ~ 1/2.9 with negligible image quality degradation.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.1
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• pp.93-103
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• 2019

Recently, malicious code distribution of ransomware through a web site based on a drive-by-download attack has resulted in service disruptions to the web site and damage to PC files for end users. Therefore, analyzing the characteristics of the target web site industry, distribution time, application type, and type of malicious code that is being exploited can predict and respond to the attacker's attack activities by analyzing the status and trend of malicious code sites. In this paper, we will examine the distribution of malicious codes to 3.43 million websites in Korea to draw out the characteristics of each detected landing site, exploit site, and distribution site, and discuss countermeasures.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.4105-4121
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• 2021

Recently, malware classification based on Deep Neural Networks (DNN) has gained significant attention due to the rise in popularity of artificial intelligence (AI). DNN-based malware classifiers are a novel solution to combat never-before-seen malware families because this approach is able to classify malwares based on structural characteristics rather than requiring particular signatures like traditional malware classifiers. However, these DNN-based classifiers have been found to lack robustness against malwares that are carefully crafted to evade detection. These specially crafted pieces of malware are referred to as adversarial examples. We consider a clever adversary who has a thorough knowledge of DNN-based malware classifiers and will exploit it to generate a crafty malware to fool DNN-based classifiers. In this paper, we propose a DNN-based malware classifier that becomes resilient to these kinds of attacks by exploiting Generative Adversarial Network (GAN) based data augmentation. The experimental results show that the proposed scheme classifies malware, including AEs, with a false positive rate (FPR) of 3.0% and a balanced accuracy of 70.16%. These are respective 26.1% and 18.5% enhancements when compared to a traditional DNN-based classifier that does not exploit GAN.

• ETRI Journal
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• v.44 no.1
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• pp.10-23
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• 2022

Despite the significant progress in camera pose estimation and structure-from-motion reconstruction from unstructured images, methods that exploit a priori information on camera arrangements have been overlooked. Conventional state-of-the-art methods do not exploit the geometric structure to recover accurate camera poses from a set of patch images in an array for mosaic-based imaging that creates a wide field-of-view image by sewing together a collection of regular images. We propose a camera pose estimation framework that exploits the array-structured image settings in each incremental reconstruction step. It consists of the two-way registration, the 3D point outlier elimination and the bundle adjustment with a constraint term for consistent rotation vectors to reduce reprojection errors during optimization. We demonstrate that by using individual images' connected structures at different camera pose estimation steps, we can estimate camera poses more accurately from all structured mosaic-based image sets, including omnidirectional scenes.

• Korean small business review
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• v.39 no.2
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• pp.19-35
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• 2017

It is very important for entrepreneurial firms to acquire and exploit the resources necessary for growth. This study examines how venture capital financing affect these entrepreneurial firms' ability to acquire and exploit the resources. Particularly, based on the resource based view, the authors explain the relationship between venture capital financing and entrepreneurial firm's market performance. Empirical results illustrate that venture capital financing positively and significantly affects the market performance of entrepreneurial firms. It is concluded that entrepreneurial firms need to increase the number of alliances with venture capital, which supports various activities after the investment to achieve growth with resource limitation.

• Journal of Information Science Theory and Practice
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• v.12 no.1
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• pp.39-59
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• 2024

An online social network is a platform that is continuously expanding, which enables groups of people to share their views and communicate with one another using the Internet. The social relations among members of the public are significantly improved because of this gesture. Despite these advantages and opportunities, criminals are continuing to broaden their attempts to exploit people by making use of techniques and approaches designed to undermine and exploit their victims for criminal activities. The field of digital forensics, on the other hand, has made significant progress in reducing the impact of this risk. Even though most of these digital forensic investigation techniques are carried out manually, most of these methods are not usually appropriate for use with online social networks due to their complexity, growth in data volumes, and technical issues that are present in these environments. In both civil and criminal cases, including sexual harassment, intellectual property theft, cyberstalking, online terrorism, and cyberbullying, forensic investigations on social media platforms have become more crucial. This study explores the use of machine learning techniques for addressing criminal incidents on social media platforms, particularly during forensic investigations. In addition, it outlines some of the difficulties encountered by forensic investigators while investigating crimes on social networking sites.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.117-121
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• 2024

기존의 외장 하드디스크는 보안 기능의 부재로 인하여, 비인가자로부터 디스크가 탈취되는 경우에는 저장된 데이터가 유출되거나 훼손되는 문제점이 존재한다. 이러한 문제점을 보완하기 위하여, 보안 기능을 제공하는 보안 외장 하드디스크가 등장하였지만, 보안 기능 중 패스워드나 지문 인증과 같은 사용자 인증을 우회하는 취약점이 지속적으로 발견됨으로써, 비인가자가 장치 내부에 안전하게 저장된 데이터에 접근하는 보안위협이 발생하였다. 이러한 보안위협은 국가사이버안보센터에서 공개한 보안 요구사항을 만족하지 못하거나, 만족하더라도 설계나 구현 과정에서 내포된 취약점으로 인하여 발생한다. 본 논문은 이와 같이 보안 외장 하드디스크에서 발생하는 취약점을 점검하기 위한 목적으로 보안 외장 하드디스크 익스플로잇 프레임워크를 설계하였다. 취약점을 점검하기 위한 전체 프레임워크를 설계하였고, 프레임워크에서 제공하는 각 기능 및 유즈케이스 다이어그램을 설계하였으며, 설계된 프레임워크를 활용한다면, 현재 상용화되었거나 추후 개발될 보안 외장 하드디스크를 대상으로 안전성을 평가할 것으로 판단된다. 그뿐만 아니라, 안전성 평가 결과를 기반으로, 보안 외장 하드디스크에 내재된 취약점을 보완함으로써 안전성을 더욱 향상시키고, 수동으로 분석하여야만 하는 보안 외장 하드디스크의 취약점 점검을 자동화함으로써, 안전성을 평가하는 시간과 비용 또한 절감할 것으로 사료된다.

• Biotechnology and Bioprocess Engineering:BBE
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• v.4 no.1
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• pp.78-81
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• 1999

Light penetration depth in high-density Chlorella cultures can be successfully estimated by Beer-Lambert's law. The efficiency of light energy absorption algal cultures was so high that algal cells near the illuminating surface shade the cells deep in the culture. To exploit the potential of high-density algal cultures, this mutual shading should be eliminated or minimized. However, providing more light energy will not ease the situation and it will simply drop the overall light utilization efficiency.