• KIPS Transactions on Software and Data Engineering
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• v.6 no.12
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• pp.549-564
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• 2017

Not only services that are provided by a single system have been various with the development of the Internet of Things and autonomous software but also new services that are not possible before are provided through collaboration between systems. The collaboration between autonomous systems is similar to the ecosystem configuration in terms of biological viewpoints. Thus, it is called the IT Ecosystem, and this concept has arisen newly in recent years. The IT Ecosystem refers to a concept that achieves a mission of each of a number of heterogeneous systems rather than a single system utilizing their own autonomy as well as achieving the objectives of the overall system simultaneously in order to meet a single common goal. In our previous study, we proposed architecture of elementary level and as well as basic several meta-models to implement the IT Ecosystem. This paper proposes comprehensive reference architecture framework to implement the IT Ecosystem by cleansing the previous study. Among them, a utility function based on cost-benefit model is proposed to solve the dynamic re-configuration problem of system components. Furthermore, a measure of using genetic algorithm is proposed as a solution to reduce the dynamic re-configuration overhead that is increased exponentially according to the expansion of the number of entities of components in the IT Ecosystem. Finally, the utilization of the proposed orchestration framework is verified quantitatively through probable case studies on IT Ecosystem for unmanned forestry management.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.5
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• pp.213-222
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• 2019

Determining the meaning of a keyword in a speech dialogue system is an important technology for the future implementation of an intelligent speech dialogue interface. After extracting keywords to grasp intention from user's utterance, the intention of utterance is determined by using the semantic mark of keyword. One keyword can have several semantic marks, and we regard the task of attaching the correct semantic mark to the user's intentions on these keyword as a problem of word sense disambiguation. In this study, about 23% of all keywords in the corpus is manually tagged to build a semantic mark dictionary, a synonym dictionary, and a context vector dictionary, and then the remaining 77% of all keywords is automatically tagged. The semantic mark of a keyword is determined by calculating the context vector similarity from the context vector dictionary. For an unregistered keyword, the semantic mark of the most similar keyword is attached using a synonym dictionary. We compare the performance of the system with manually constructed training set and semi-automatically expanded training set by selecting 3 high-frequency keywords and 3 low-frequency keywords in the corpus. In experiments, we obtained accuracy of 54.4% with manually constructed training set and 50.0% with semi-automatically expanded training set.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.3
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• pp.179-186
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• 2013

PACS is a medical system for digital medical images, and PACS expand to web-based service using public network, DICOM files should be protected from the man-in-the-middle attack because they have personal medical record. To solve the problem, we designed flexible secure transmission system using IPSec and adopted to a web-based three-dimensional medical image system. And next, we performed the performance evaluation changing integrity and encryption algorithm using DICOM volume dataset. At that time, combinations of the algorithm was 'DES-MD5', 'DES-SHA1', '3DES-MD5', and '3DES-SHA1, and the experiment was performed on our test-bed. In experimental result, the overall performance was affected by encryption algorithms than integrity algorithms, DES was approximately 50% of throughput degradation and 3DES was about to 65% of throughput degradation. Also when DICOM volume dataset was transmitted using secure transmission system, the network performance degradation had shown because of increased packet overhead. As a result, server and network performance degradation occurs for secure transmission system by ensuring the secure exchange of messages. Thus, if the secure transmission system adopted to the medical images that should be protected, it could solve server performance gradation and compose secure web PACS.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.4
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• pp.84-91
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• 2011

Recently, WBAN(Wireless Body Area Network) which has progressed standardization based on IEEE 802.15.6 standardization is a network for the purpose of the short-range wireless communications within around 3 meters from the inner or outer human body. Effective QoS control technique and data efficient management in limited bandwidth such as audio and video are important elements in terms of users and loads in short-range wireless networks. In this paper, for high-speed WBAN IEEE 802.15.6 standard, the dynamic allocation to give an efficient bandwidth management and weighted fair queueing algorithm have been proposed through the adjustment of the super-frame about limited data and Quality of Service (QoS) based on the queuing algorithm. Weighted Fair Queueing(WFQ) Algorithm represents the robust performance about elements to qualitative aspects as well as maintaining fairness and maximization of system performance. The performance results show that the dynamic allocation expanded transmission bandwidth five times and the weighted fair queueing increased maximum 24.3 % throughput and also resolved delay bound problem.

• The Korean Journal of Applied Statistics
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• v.32 no.1
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• pp.29-40
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• 2019

Categorical data with non-responses are frequently observed in election poll surveys, and can be represented by incomplete contingency tables. To estimate supporting rates of candidates, the identification of the missing mechanism should be pre-determined because the estimates of non-responses can be changed depending on the assumed missing mechanism. However, it has been shown that it is not possible to identify the missing mechanism when using observed data. To overcome this problem, sensitivity analysis has been suggested. The previously proposed sensitivity analysis can be applicable only to two-way incomplete contingency tables with binary variables. The previous sensitivity analysis is inappropriate to use since more than two of the factors such as region, gender, and age are usually considered in election poll surveys. In this paper, sensitivity analysis suitable to an multi-dimensional incomplete contingency table is devised, and also applied to the 19th Korean presidential election poll survey data. As a result, the intervals of estimates from the sensitivity analysis include actual results as well as estimates from various missing mechanisms. In addition, the properties of the missing mechanism that produce estimates nearest to actual election results are investigated.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.10A
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• pp.1131-1138
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• 2004

In Hierarchical Mobile Ipv6 (HMIPv6) networks, the mobility anchor point (MAP) handles binding update (BU) procedures locally to reduce signaling overhead for mobility. However, as the number of mobile nodes (MNs) handled by the MAP increases, the MAP suffers from the overhead not only to handle signaling traffic but also to Process data tunneling traffic. Therefore, it is important to control the number of MNs serviced by the MAP, in order to mitigate the burden of the MAP. We propose an adaptive load control scheme, which consists of two sub-algorithms: threshold-based admission control algorithm and session-to-mobility ratio (SMR) based replacement algorithm. When the number of MNs at a MAP reaches to the full capacity, the MAP replaces an existing MN at the MAP, whose SMR is high, with an MN that just requests binding update. The replaced MN is redirected to its home agent. We analyze the proposed load control scheme using the .Markov chain model in terms of the new MN and the ongoing MN blocking probabilities. Numerical results indicate that the above probabilities are lowered significantly compared to the threshold-based admission control alone.

• Communications of Mathematical Education
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• v.37 no.1
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• pp.65-84
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• 2023

The method of Lagrange multipliers, one of the most fundamental algorithms for solving equality constrained optimization problems, has been widely used in basic mathematics for artificial intelligence (AI), linear algebra, optimization theory, and control theory. This method is an important tool that connects calculus and linear algebra. It is actively used in artificial intelligence algorithms including principal component analysis (PCA). Therefore, it is desired that instructors motivate students who first encounter this method in college calculus. In this paper, we provide an integrated perspective for instructors to teach the method of Lagrange multipliers effectively. First, we provide visualization materials and Python-based code, helping to understand the principle of this method. Second, we give a full explanation on the relation between Lagrange multiplier and eigenvalues of a matrix. Third, we give the proof of the first-order optimality condition, which is a fundamental of the method of Lagrange multipliers, and briefly introduce the generalized version of it in optimization. Finally, we give an example of PCA analysis on a real data. These materials can be utilized in class for teaching of the method of Lagrange multipliers.

• Information Systems Review
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• v.19 no.2
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• pp.71-94
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• 2017

Recommender systems reduce information overload and enhance choice quality. This technology is used in many services and industry. Previous studies did not consider recommendation quantity and the repetitive recommendations of an item. This study is the first to examine recommender systems by considering recommendation quantity and repetitive recommendations. Only a limited number of items are displayed in offline stores because of their physical limitations. Determining the type and number of items that will be displayed is an important consideration. In this study, I suggest the use of a user-based recommender system that can recommend the most appropriate items for each store. This model is evaluated by MAE, Precision, Recall, and F1 measure, and shows higher performance than the baseline model. I also suggest a new performance evaluation measure that includes Quantity Precision, Quantity Recall, and Quantity F1 measure. This measure considers the penalty for short or excess recommendation quantity. Novelty is defined as the proportion of items in a recommendation list that consumers may not experience. I evaluate the new revenue creation effect of the suggested model using this novelty measure. Previous research focused on recommendations for customer online, but I expand the recommender system to cover stores offline.

• The Mathematical Education
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• v.63 no.2
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• pp.255-272
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• 2024

This study aims to design mathematics-integrated classes that cultivate artificial intelligence (AI) thinking and to analyze students' AI thinking within these classes. To do this, four classes were designed through the integration of the AI4K12 Initiative's AI Big Ideas with the 2015 revised elementary mathematics curriculum. Implementation of three classes took place with 5th and 6th grade elementary school students. Leveraging the computational thinking taxonomy and the AI thinking components, a comprehensive framework for analyzing of AI thinking was established. Using this framework, analysis of students' AI thinking during these classes was conducted based on classroom discourse and supplementary worksheets. The results of the analysis were peer-reviewed by two researchers. The research findings affirm the potential of mathematics-integrated classes in nurturing students' AI thinking and underscore the viability of AI education for elementary school students. The classes, based on AI Big Ideas, facilitated elementary students' understanding of AI concepts and principles, enhanced their grasp of mathematical content elements, and reinforced mathematical process aspects. Furthermore, through activities that maintain structural consistency with previous problem-solving methods while applying them to new problems, the potential for the transfer of AI thinking was evidenced.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.129-143
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• 2012

Recently, the rapid progress of a number of standardized web technologies and the proliferation of web users in the world bring an explosive increase of producing and consuming information documents on the web. In addition, most companies have produced, shared, and managed a huge number of information documents that are needed to perform their businesses. They also have discretionally raked, stored and managed a number of web documents published on the web for their business. Along with this increase of information documents that should be managed in the companies, the need of a solution to locate information documents more accurately among a huge number of information sources have increased. In order to satisfy the need of accurate search, the market size of search engine solution market is becoming increasingly expended. The most important functionality among much functionality provided by search engine is to locate accurate information documents from a huge information sources. The major metric to evaluate the accuracy of search engine is relevance that consists of two measures, precision and recall. Precision is thought of as a measure of exactness, that is, what percentage of information considered as true answer are actually such, whereas recall is a measure of completeness, that is, what percentage of true answer are retrieved as such. These two measures can be used differently according to the applied domain. If we need to exhaustively search information such as patent documents and research papers, it is better to increase the recall. On the other hand, when the amount of information is small scale, it is better to increase precision. Most of existing web search engines typically uses a keyword search method that returns web documents including keywords which correspond to search words entered by a user. This method has a virtue of locating all web documents quickly, even though many search words are inputted. However, this method has a fundamental imitation of not considering search intention of a user, thereby retrieving irrelevant results as well as relevant ones. Thus, it takes additional time and effort to set relevant ones out from all results returned by a search engine. That is, keyword search method can increase recall, while it is difficult to locate web documents which a user actually want to find because it does not provide a means of understanding the intention of a user and reflecting it to a progress of searching information. Thus, this research suggests a new method of combining ontology-based search solution with core search functionalities provided by existing search engine solutions. The method enables a search engine to provide optimal search results by inferenceing the search intention of a user. To that end, we build an ontology which contains concepts and relationships among them in a specific domain. The ontology is used to inference synonyms of a set of search keywords inputted by a user, thereby making the search intention of the user reflected into the progress of searching information more actively compared to existing search engines. Based on the proposed method we implement a prototype search system and test the system in the patent domain where we experiment on searching relevant documents associated with a patent. The experiment shows that our system increases the both recall and precision in accuracy and augments the search productivity by using improved user interface that enables a user to interact with our search system effectively. In the future research, we will study a means of validating the better performance of our prototype system by comparing other search engine solution and will extend the applied domain into other domains for searching information such as portal.