• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.8B
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• pp.1028-1037
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• 2011

Recently, Selim et al proposed public key cryptography based privacy preserving multi-context RFID authentication protocol. However Selim et al's proposed protocol not only doesn't fit into passive tag based RFID system because it uses public key based encryption algorithm to perform authentication between reader and tag, but also is insecure to an impersonation attack because it doesn't provide mutual authentication. In order to eliminate the above described efficiency problem and security vulnerabilities, this paper proposes a new multi-context RFID mutual authentication protocol that can prevent privacy invasion and tag impersonation attack through providing mutual authentication between single passive tag which is located different application space and readers which provide multi-context purposes and can secure against relay attack and denial-of-service attack. As a result, the proposed protocol performs secure mutual authentication based on the collected space and time information from the RFID reader and provides strong security and high computation efficiency because if performs secure one-way hash function and symmetric encryption operations suitable to the environments of passive RFID tags.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.9
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• pp.650-657
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• 2006

The music is a part of our daily life in these days. And when the people listen to the music, they are affected by the context. However, previous researches on the music recommendation system have the problem that they didn't consider the proper contextual information efficiently. They only used the content-based filtering or the method to use musical metadata (genre, artist, etc.). Recently, there are some researches about the music recommendation system which applies the status(temperature, humidity, etc.) of environments. But, it is difficult to be accepted by the contextual information. Therefore, we propose the music recommendation system that is dynamically applied by the contextual information as well as the metadata in the previous researches. And the system can provide users with the music that they want to listen to, and then the users can be more satisfied. Also, the services can be improved by the feedback of the users. In order to solve this problem, the context-information for selecting a music list is defined and the music recommendation system is designed by using the content-based filtering method. The system is suitable for the user's taste and the context. The music recommendation system we are proposing uses an OSGi framework in the home network. As a result, the satisfaction of users and the quality of services will be improved more efficiently by supporting the mobility of services as well as the distributed processing.

• Journal of KIISE:Software and Applications
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• v.33 no.11
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• pp.986-998
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• 2006

There has been an increasing necessity of Semantic Web-based metadata that helps computers efficiently understand and manage an information increased with the growth of Internet. However, it seems inevitable to face some semantically ambiguous information when metadata is generated. Therefore, we need a solution to this problem. This paper proposes a new method for automated metadata generation with the help of a concept of class, in which some ambiguous words imbedded in information such as documents are semantically more related to others, by using probability model of consequent words. We considers ambiguities among defined concepts in ontology and uses the Hidden Markov Model to be aware of part of a named entity. First of all, we constrict a Markov Models a better understanding of the named entity of each class defined in ontology. Next, we generate the appropriate context from a text to understand the meaning of a semantically ambiguous word and solve the problem of ambiguities during generating metadata by searching the optimized the Markov Model corresponding to the sequence of words included in the context. We experiment with seven semantically ambiguous words that are extracted from computer science thesis. The experimental result demonstrates successful performance, the accuracy improved by about 18%, compared with SemTag, which has been known as an effective application for assigning a specific meaning to an ambiguous word based on its context.

• Education of Primary School Mathematics
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• v.10 no.2
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• pp.141-149
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• 2007

It is undeniably important to bring up a solution capability of arithmetic word problems in the elementary mathematical education. The goal of this study is to acquire the implication for remedial instruction on arithmetic word problems solving through surveying elementary school students' difficulties in the solving of arithmetic word problems. In order to do it, this study was intended to analyze the following two aspects. First, it was analyzed that they generally felt more difficulties in which field among addition, subtraction, multiplication and division word problems. Second, with the result of the first analysis, it was examined that they solved it by imagining as which sphere of the other word problems. Also, the cause of their error on the word problem solving was analyzed by the interview. From the foregoing analyses, the following implications for remedial instruction on arithmetic word problems solving are acquired. First, the accumulation of learning deficiency must be diminished through the remedial instruction. Second, it must help students to understand the given problem and to make of what the goal of problem is. Third, it must help students to form a good habit for reading the problem and to understand the context of problem. forth, the teacher must help students to review and reflect their problem-solving processes.

• Journal of the Korean Society of Earth Science Education
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• v.9 no.3
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• pp.276-291
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• 2016

This study is to develop a valid and reliable instrument for measuring students' creative engineering problem solving propensity. The creative engineering problem solving is operationally defined in this study as a creative problem solving skill in an engineering context. To develop the instrument, first we define seven common constructs between engineering problem solving skill and creative problem solving skill through an intensive literature review; motivation, context, personal character, engineering design, engienering habits of mind, understandings of engineering and engineers, communication skill, and collaboration skill. Based on the seven constructs and the face validity test conducted by two in-service science teachers and 4 experts in science education research, 40 preliminary items were developed. Then the preliminary instrument was implemented in a science gifted highschool to measure the reliability of the instrument. From the 40 items, 34 items were selected through the initial reliability test by Cronbach's ${\alpha}$(>.75). Finally through the three times of factor analysis process, 28 items in five construct categories were selected; motivation (3 items), engineering design (6 items), engineering habits of mind (9 items), understandings of engineering and engineers (4 items), communication and collaboration skill (6 items). The factor analysis result showed that the reliability of each construct category was between .733 to .892., meaning that the instrument is reliable in terms of the higher structural validity (each item is categorized in an appropriate construct category). We expect that the creative engineering problem solving propensity instrument developed in this study can be used in various contexts for STEAM education research as a reliable and valid instrument.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.6
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• pp.215-223
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• 2010

New information technologies make it easy to access and acquire information in various ways. However, It also enable powerful and various threat to system security. The prominent database technology challenging these threats is access control. Currently, to keep pace with the new paradigms, new extended access control methods are challenged. We study access control with uncertain context. With respect to access control, it is possible that there is a discrepancy between the syntactic phrase in security policies and that in queries, called semantic gap problem. In our semantic access control, we extract semantic implications from context tree and introduce the measure factor to calculate the degree of the discrepancy, which is used to control the exceed privileges.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.538-561
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• 2020

Recommender Systems (RecSys) have a major role in e-commerce for recommending products, which they may like for every user and thus improve their business aspects. Although many types of RecSyss are there in the research field, the state of the art RecSys has focused on finding the user similarity based on sequence (e.g. purchase history, movie-watching history) analyzing and prediction techniques like Recurrent Neural Network in Deep learning. That is RecSys has considered as a sequence prediction problem. However, evaluation of similarities among the customers is challenging while considering temporal aspects, context and multi-component ratings of the item-records in the customer sequences. For addressing this issue, we are proposing a Deep Learning based model which learns customer similarity directly from the sequence to sequence similarity as well as item to item similarity by considering all features of the item, contexts, and rating components using Dynamic Temporal Warping(DTW) distance measure for dynamic temporal matching and 2D-GRU (Two Dimensional-Gated Recurrent Unit) architecture. This will overcome the limitation of non-linearity in the time dimension while measuring the similarity, and the find patterns more accurately and speedily from temporal and spatial contexts. Experiment on the real world movie data set LDOS-CoMoDa demonstrates the efficacy and promising utility of the proposed personalized RecSys architecture.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.3
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• pp.86-96
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• 2008

In ubiquitous environments, invisible devices and software are connected to one another to provide convenient services to users. In order to provide such services, we must have mobile devices that connect users and services. However, the types of available services have thus far been limited due to the limited resources of mobile devices. This paper proposes a solution to the resource limitation problem of mobile devices by presenting a context-based collaboration system that allows mobile devices to share various nearby resources. Our system has a feature to enable personalized resource sharing by dynamically re-configuring user's preference and resource information.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.4
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• pp.69-78
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• 2010

Multi-criteria ABC inventory classification is one of the most widely employed techniques for efficient inventory control, and it considers more than one criterion for categorizing inventory items into groups of different importance. Recently, Ramanathan (2006) proposed a weighted linear optimization (WLO) model for the problem of multi-criteria ABC inventory classification. The WLO model generates a set of criteria weights for each item and assigns a normalized score to each item for ABC analysis. Although the WLO model is considered to have many advantages, it has a limitation that many items can share the same optimal efficiency score. This limitation can hinder a precise classification of inventory items. To overcome this deficiency, we propose a context-dependent DEA based method for multi-criteria ABC inventory classification problems. In the proposed model, items are first stratified into several efficiency levels, and then the relative attractiveness of each item is measured with respect to less efficient ones. Based on this attractiveness measure, items can be further discriminated in terms of their importance. By a comparative study between the proposed model and the WLO model, we argue that the proposed model can provide a more reasonable and accurate classification of inventory items.

• Journal of the Korean Society for information Management
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• v.23 no.2
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• pp.147-165
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• 2006

The explosive growth of Web-based educational resources requires a new approach for accessing relevant information effectively. Social searching in the context of social navigation is one of several answers to this problem, in the domain of information retrieval. It provides users with not merely a traditional ranked list, but also with visual hints which can guide users to information provided by their colleagues. A personalized and context-dependent social searching system has been implemented on a platform called KnowledgeSea II, an open-corpus Web-based educational support system with multiple access methods. Validity tests were run on a variety of aspects and results have shown that this is an effective way to help users access relevant, essential information.