• Food Science and Preservation
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• v.18 no.1
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• pp.103-110
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• 2011

We investigated consumer perceptions of and purchase intentions for health foods. Data were collected from 454 adults over the age of 20 years living in Seoul and Gyeonggi province, from May 10 to June 5, 2010. Those that "hardly ever drink" (41.4%) were most prevalent in terms of drinking activity, whereas 80.8% of respondents did not smoke. Also, those who responded "hardly ever exercise" ranked highest; although 43.8% in fact exercised frequently. Of all respondents, 44.5% admitted to suffering slightly from stress. A total of 59.5% of respondents opined "I am healthy but I do worry about health", and "exercise" topped the list of approved (37.2% of respondents) health care methods. We also found that 83.5% of respondents claimed to have tried health foods, whereas in the case of having no taking experience, 60% had not purchased such foods because, in their view, this was unnecessary. The extent of concerns about health foods scored 3.09, and the level of purchase intentions for health food was high, with a score of 3.40. Therefore, all of government, producers, distributors, and academic researchers must provide consumers with accurate and complete information, and need to collaborate in the development of consumer education programs on health foods. This will enhance consumer interest in such foods, and empower logical choices.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.558-564
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• 2013

Wireless sensor networks (WSNs) contain limited energy resources and are left in open environments. Since these sensor nodes are self-operated, attacks such as sinkhole attacks are possible as they can be compromised by an adversary. The sinkhole attack may cause to change initially constructed routing paths, and capture of significant information at the compromised node. A localized encryption and authentication protocol (LEAP) has been proposed to authenticate packets and node states by using four types of keys against the sinkhole attack. Even though this novel approach can securely transmits the packets to a base station, the packets are forwarded along the constructed paths without checking the next hop node states. In this paper, we propose the next hop node selection method to cater this problem. Our proposed method evaluates the next hop node considering three factors (i.e., remaining energy level, number of shared keys, and number of filtered false packets). When the suitability criterion for next hop node selection is satisfied against a fix threshold value, the packet is forwarded to the next hop node. We aim to enhance energy efficiency and a detour of attacked areas to be effectively selected Experimental results demonstrate validity of the proposed method with up to 6% energy saving against the sinkhole attack as compared to the LEAP.

• Journal of Korea Port Economic Association
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• v.27 no.2
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• pp.261-273
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• 2011

Mega-corporations are emerging as a result of M&As (mergers and acquisitions) in the logistics industry. The global logistics market has progressed in a continuously competitive manner. Global logistics corporations provide integrated set of services, from production to disposal in order to manage the process efficiently throughout the diverse regions of the world. To advance into an total integrated logistics provider, the corporation must have professional knowledge in logistics and information technology which are necessary to deliver effective integrated logistics solutions. The government has integrated the logistics corporations both horizontally and vertically with the aim to foster logistics corporations possessing global competitiveness. Six years have passed since the implementation of the comprehensive (total) logistics industry certification system in pursuit of making Korea the hub for the Northeast Asian logistics market. This study compares and analyzes the efficiency of nine mega integrated logistics providers by applying the CCR model and BCC model. Each of the nine corporations is subject to certification as integrated logistics corporations. In Korea, nine corporations are certified individually as integrated logistics corporations out of the 31 logistics providers. The analysis showed that the Glovis was the most efficient integrated logistics provider reaching 100% in efficiency and displayed the highest efficiency for six consecutive years from 2005 to 2010. The study also found that the Glovis will be able to maintain 100% in efficiency rate, even though the input are increased over six times as many as those of 2010.

• Journal of the Korea Society for Simulation
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• v.19 no.2
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• pp.73-80
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• 2010

A wireless sensor network which is deployed in hostile environment can be easily compromised by attackers. The selective forwarding attack can jam the packet or drop a sensitive packet such as the movement of the enemy on data flow path through the compromised node. Xiao, Yu and Gao proposed the checkpoint-based multi-hop acknowledgement scheme(CHEMAS). In CHEMAS, each path node enable to be the checkpoint node according to the pre-defined probability and then can detect the area where the selective forwarding attacks is generated through the checkpoint nodes. In this scheme, the number of hops is very important because this parameter may trade off between energy conservation and detection capacity. In this paper, we used the fuzzy rule system to determine adaptive threshold value which is the number of hops for the ACK packets. In every period, the base station determines threshold value while using fuzzy logic. The energy level, the number of compromised node, and the distance to each node from base station are used to determine threshold value in fuzzy logic.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.456-462
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• 2011

As the ARRA enacted recently in the United States, the interest in EHR systems have been increased in the field of medical industry. The passage of the ARRA presents a program that provides incentives to office-based physicians and hospitals adapting the EHR systems to guarantee interoperability with various medical standards. Thanks to the incentive program, a great number of EHR systems have been developed and lots of office-based physicians and hospitals have adapted the EHR systems certified by CCHIT. Keeping pace with the rapid changes in the market of healthcare, some enterprises try to push in to the United States healthcare market based on the experience acquired by developing EHR systems for hospitals in Korea. However, the developed system must be customized because of the different medical environment between Korea and the United States. In this paper, therefore, we design and develop an integrated EHR platform to guarantee the interoperability between different medical information systems based on medical standard technologies. In the developed platform, an integrated system has been composed by integrating various basic techniques such as data transmission standards and its methods, medical standard terminologies and its usage, and knowledge management for medical decision-making support. Moreover, medical data can be processed electronically by adapting an HL7 interface engine and the terminologies for exchanging medical information and the standardization of medical information. We develop SeniCare, an EHR system for supporting ambulatory care of the office-based physicians, based on the platform, and we verify the usability of the platform by confirming whether SeniCare satisfies the criteria of "meaningful use" issued by CMS or not.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.295-302
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• 2013

Many reported methods assume that the people in an image or an image sequence have been identified and localization. People detection is one of very important variable to affect for the system's performance as the basis technology about the detection of other objects and interacting with people and computers, motion recognition. In this paper, we present an efficient linear discriminant for multi-view people detection. Our approaches are based on linear discriminant. We define training data with fisher Linear discriminant to efficient learning method. People detection is considerably difficult because it will be influenced by poses of people and changes in illumination. This idea can solve the multi-view scale and people detection problem quickly and efficiently, which fits for detecting people automatically. In this paper, we extract people using fisher linear discriminant that is hierarchical models invariant pose and background. We estimation the pose in detected people. The purpose of this paper is to classify people and non-people using fisher linear discriminant.

• Journal of The Korean Association of Information Education
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• v.7 no.1
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• pp.37-47
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• 2003

A grading system of practical word processor skills is designed and implemented by using HWPML(Hangul Word Processor Markup Language) which is a product of Hangul and Computer Co Ltd. By using HWPML, which is a markup tag structure of Hangul file, Hangul files can be edited in other application programs. Authorized users can make questions. However, only the manager is allowed to register answers to the questions in order to maintain the correctness of grading. The result of test is stored in the database and the statistics on pass or failure can be shown interactively. The number of taking test and scores for each user are stored in the database and they can be accessed to whenever the user wants them. Comments on the test results are provided by the manager so that learners can intensity their weak points.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.4
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• pp.903-910
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• 2016

As smart mobile devices having touchscreens are growingly deployed, a pattern lock system, which is one of the graphical password systems, has become a major authentication mechanism. However, a user's unlocking behaviour leaves smudges on a touchscreen and they are vulnerable to the so-called smudge attacks. Smudges can help an adversary guess a secret pattern correctly. Several advanced pattern lock systems, such as TinyLock, have been developed to resist the smudge attacks. In this paper, we study an automated smudge attack that employs machine learning techniques and its effectiveness in comparison to the human-only smudge attacks. We also compare Android pattern lock and TinyLock schemes in terms of security. Our study shows that the automated smudge attacks are significantly advanced to the human-only attacks with regard to a success ratio, and though the TinyLock system is more secure than the Android pattern lock system.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.4
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• pp.961-972
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• 2016

For securing password-based authentication, a user must select and manage a strong password that has sufficient length and randomness. Unfortunately, however, it is known that many users are likely to choose easy-to-remember weak passwords and very poorly manage them. In this paper, we study a domestic user case of password selection and management. We conducted a survey on 327 domestic users and analyzed their tendency on password creation and update strategies, and also on the password structure and account management. We then analyzed an effect of a server's password creation rule on a structure of a user-chosen password. Our findings include that there are password structures and special characters that users significantly prefer while the effect of server's password creation rule is insignificant.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.1
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• pp.39-47
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• 2017

Nowadays, there have been an increasing number of illegal use cases where people try to fabricate the working hours by using fake fingerprints. So, the fingerprint liveness detection techniques have been actively studied and widely demanded in various applications. This paper proposes a new method to detect fake fingerprints using CNN (Convolutional Neural Ntworks) based on the patches of fingerprint images. Fingerprint image is divided into small square sized patches and each patch is classified as live, fake, or background by the CNN. Finally, the fingerprint image is classified into either live or fake based on the voting result between the numbers of fake and live patches. The proposed method does not need preprocessing steps such as segmentation because it includes the background class in the patch classification. This method shows promising results of 3.06% average classification errors on LivDet2011, LivDet2013 and LivDet2015 dataset.