• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.374-376
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• 2022

Community detection is meaningful research in social network analysis, and many existing studies use graph theory analysis methods to detect communities. This paper proposes a method to detect community by detecting maximal cliques and obtain the high influence cliques by high influence nodes, then merge the cliques with high similarity in social network.

• Journal of the Korean Data and Information Science Society
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• v.15 no.2
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• pp.477-483
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• 2004

One of the major paradigms for supervised learning in neural network community is back-propagation learning. The standard implementations of back-propagation learning are optimal under the assumptions of identical and independent Gaussian noise. In this paper, for regression function estimation, we introduce $\varepsilon-insensitive$ back-propagation learning algorithm, which corresponds to minimizing the least absolute error. We compare this algorithm with support vector machine(SVM), which is another $\varepsilon-insensitive$ supervised learning algorithm and has been very successful in pattern recognition and function estimation problems. For comparison, we consider a more realistic model would allow the noise variance itself to depend on the input variables.

• Journal of Electrical Engineering and information Science
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• v.2 no.5
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• pp.1-8
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• 1997

The main purpose of the Boolean equivalence problem is to verify that two Boolean expressions have the same functionality. Simulation has been extensively used as the standard method for the equivalence problem. Obviously, the number of tests required to perform a satisfactory coverage grows exponentially with the number of input variables. However, formal methods as opposed to simulation are getting more attention from the community. We propose a new algorithm called the Cover-Merge Algorithm based on a derivational method using the concept of cover and merge for the equivalence problem and investigate its theoretical aspects. Because of the difficulty of the problem, we emphasize simplification techniques in order to reduce the search space or problem size. Heuristics based on types of merges are developed to speed up the derivation process by allowing simplifications. In comparison with widely used technique called Binary Decision Diagram or BDD, the algorithm proposed outperforms BDD in nearly all cases of input including standard benchmark problems.

• Journal of the Korea Convergence Society
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• v.8 no.9
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• pp.319-330
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• 2017

Recently, various universities in Korea have started to work on strengthening their liberal arts and character education through the residential college (RC) system, carrying out various community programs for this purpose. However, because most programs are based on student-to-student relationships, problems can often arise within the community living environments. This paper proposes the roommate assignment algorithm in the context of a residential college, as to effectively achieve character education goals. The clustering algorithm we propose is based on the similarity hypothesis. As a result of the assignment, the degree of similarity (euclidean distance) between roommates was significantly higher than that assigned randomly. The algorithm developed in this study was applied to the data of the students living in the international campus of H University.

• Korean Journal of Agricultural Science
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• v.49 no.2
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• pp.193-202
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• 2022

The recurrent neural network (RNN) algorithm has been widely used in water-related research areas, such as water level predictions and water quality predictions, due to its excellent time series learning capabilities. However, studies on water quality predictions using RNN algorithms are limited because of the scarcity of water quality data. Therefore, most previous studies related to water quality predictions were based on monthly predictions. In this study, the quality of the water in a reservoir in Nonsan, Chungcheongnam-do Republic of Korea was predicted using the RNN-LSTM algorithm. The study was conducted after constructing data that could then be, linearly interpolated as daily data. In this study, we attempt to predict the water quality on the 7th, 15th, 30th, 45th and 60th days instead of making daily predictions of water quality factors. For daily predictions, linear interpolated daily water quality data and daily weather data (rainfall, average temperature, and average wind speed) were used. The results of predicting water quality concentrations (chemical oxygen demand [COD], dissolved oxygen [DO], suspended solid [SS], total nitrogen [T-N], total phosphorus [TP]) through the LSTM algorithm indicated that the predictive value was high on the 7th and 15th days. In the 30th day predictions, the COD and DO items showed R² that exceeded 0.6 at all points, whereas the SS, T-N, and T-P items showed differences depending on the factor being assessed. In the 45th day predictions, it was found that the accuracy of all water quality predictions except for the DO item was sharply lowered.

• Physical Therapy Korea
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• v.26 no.3
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• pp.106-114
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• 2019

Background: It is difficult to assess whether community-dwelling frail older adults may remain pre-frail status or improve into a robust state without being directly checked by health care professionals. The health information perceived by older adults is considered to be one of best sources of potential concerns in older adult population. An online measurement system combined with item response theory (IRT) and computer adaptive testing (CAT) methods is likely to become a realistic approach to remotely monitor physical activity status of frail older adults. Objects: This article suggests an approach to provide a precise and efficient means of measuring physical activity levels of community-dwelling frail older adults. Methods: Article reviews were reviewed and summarized. Results: In comparison to the classical test theory (CTT), the IRT method is empirically aimed to focus on the psychometric properties of individual test items in lieu of the test as a whole. These properties allow creating a large item pool that can capture the broad range of physical activity levels. The CAT method administers test items by an algorithm that select items matched to the physical activity levels of the older adults. Conclusion: An online measurement system combined with these two methods would allow adequate physical activity measurement that may be useful to remotely monitor the activity level of community-dwelling frail older adults.

• Nuclear Engineering and Technology
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• v.52 no.8
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• pp.1661-1668
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• 2020

A physical protection system (PPS) is used for the protection of critical facilities. This paper proposes a structure analytic hierarchy approach (SAHA) for the hierarchical evaluation of the PPS effectiveness in critical infrastructure. SAHA is based on the traditional analysis methods "estimate of adversary sequence interruption, EASI". A community algorithm is used in the building of the SAHA model. SAHA is applied to cluster the associated protection elements for the topological design of complicated PPS with graphical vertexes equivalent to protection elements.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.75-82
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• 2017

In this paper, we consider social network analysis that focuses on community detection. Social networks embed community structure characteristics, i.e., a society can be partitioned into many social groups of individuals, with dense intra-group connections and much sparser inter-group connections. Exploring the community structure allows predicting as well as understanding individual's behaviors and interactions between people. In this paper, based on the interaction information extracted from a real-life Bluetooth contacts, we aim to reveal the social groups in a society of mobile carriers. Focusing on estimating the closeness of relationships between network entities through different similarity measurement methods, we introduce the clustering scheme to determine the underlying social structure. To evaluate our community detection method, we present the evaluation mechanism based on the basic properties of friendship.

• Proceedings of the Korea Multimedia Society Conference
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• 2012.05a
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• pp.190-192
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• 2012

Vehicular Ad hoc Networks (VANETs) is the new wireless networking concept of mobile ad hoc networks in research community. Routing in vehicular is a major challenge and research area. The majority of current routing algorithms for VANETs utilize indirect metrics to select the next hop and produce optimal node path. In this paper, we propose a distance and angle based routing algorithm for VANETs, which combines a distance approach with an angle based geographical strategy for selecting the next hop, with the purpose of using direct metrics to build a optimal node route. The proposed algorithm has better performance than the previous scheme.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.176-183
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• 2013

We propose a rolled fingerprint merging algorithm that effectively merges plain fingerprints in consecutive frame units that are fed through rolling and detects more fingerprint minutiae in order to increase the fingerprint recognition rate. The proposed rolled fingerprint merging algorithm uses a adaptive projection mask; it contains a detector that separates plain fingerprints from the background and a projection mask generator that sequentially projects the detect ed images. In addition, in the merging unit, the pyramid-shaped projection method is used to detect merged rolled fingerprints from the generated variable projective mask, starting from the main images. Simulations show that the extracted minutia e are 46.79% more than those from plain fingerprints, and the proposed algorithm exhibits excellent performance by detecting 52.0% more good fingerprint minutiae that are needed for matching.