• Journal of the Korea Society of Computer and Information
• /
• v.20 no.1
• /
• pp.111-118
• /
• 2015

This paper deals with the routing and wavelength assignment problem (RWAP) that decides the best lightpaths for multiple packet demands for (s,t) in optical communication and assigns the minimum number of wavelengths to given lightpaths. There has been unknown of polynomial-time algorithm to obtain the optimal solution for RWAP. Hence, the RWAP is classified as NP-complete problem and one can obtain the approximate solution in polynomial-time. This paper decides the shortest main and alternate lightpath with same hop count for all (s,t) for given network in advance. When the actual demands of communication for particular multiple packet for (s,t), we decrease the maximum utilized edge into b utilized number using these dual-paths. Then, we put these (s,t) into b-wavelength bins without duplicated edge. This algorithm can be get the optimal solution within O(kn) computational complexity. For two experimental data, the proposed algorithm shows that can be obtain the known optimal solution.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.4
• /
• pp.47-53
• /
• 2020

Blockchain is a distributed shared ledger that transparently manages information through verification and agreement between nodes connected to a distributed network. Recently, cases of data management among authorized agencies based on private blockchain are increasing. In this paper, we investigated the application cases and technical processes of PBFT, the representative consensus algorithm of private blockchain, and proposed a modified PBFT algorithm that enables efficient consensus by simplifying duplicate verification and consensus processes that occur during PBFT processing. The algorithm proposed in this paper goes through the process of selecting a delegation node through an authoritative node and can increase the safety of the delegation node selection process by considering an efficient re-election algorithm for candidate nodes. By utilizing this research, it is possible to reduce the burden on the network communication cost of the consensus process and effectively process the final consensus process between nodes.

• Journal of Digital Convergence
• /
• v.19 no.12
• /
• pp.359-367
• /
• 2021

The purpose of this study is to analyze domestic patient safety culture research topics using text mining and CONCOR analysis. The research method was conducted in the stages of data collection, data preprocessing, text mining and social network analysis, and CONCOR analysis. A total of 136 articles were analyzed excluding papers that were not published. Data analysis was performed using Textom and UCINET programs. As a result of this study, TF (frequency) of patient safety culture-related studies showed that patient safety was the highest, and TF-IDF (importance in documents) was highest in nursing. As a result of the CONCOR analysis, a total of seven clusters were derived: knowledge and attitude, communication, medical service, team, work environment, structure, organization and management that constitute the patient safety culture. In the future, it is necessary to conduct research on the relationship between the establishment of a patient safety culture and patient outcomes.

• The Journal of the Korea Contents Association
• /
• v.18 no.12
• /
• pp.35-45
• /
• 2018

Motion Estimation(ME) has been developed to reduce the redundant data in digital video signal. ME is an important part of video encoding system, However, it requires huge computational complexity of the encoder part, and fast motion search methods have been proposed to reduce huge complexity. Multi- view video is obtained by capturing on a three-dimensional scene with many cameras at different positions and its complexity increases in proportion to the number of cameras. In this paper, we proposed an efficient motion method which chooses a search pattern adaptively by using the temporal-spatial correlation of the block and the characteristics of the block. Experiment results show that the computational complexity reduction of the proposed method over TZ search method and FS method can be up to 70~75% and 99% respectively while keeping similar image quality and bit rates.

• KIPS Transactions on Software and Data Engineering
• /
• v.8 no.1
• /
• pp.27-36
• /
• 2019

In this paper, we propose a method to find the most similar answer to the user's response from the question-answer database in order to avoid generating a redundant question in retrieval-based automatic question generation system. As a question of the most similar answer to user's response may already be known to the user, the question should be removed from a set of question candidates. A similarity detector calculates a similarity between two answers by utilizing the same words, paraphrases, and sentential meanings. Paraphrases can be acquired by building a phrase table used in a statistical machine translation. A sentential meaning's similarity of two answers is calculated by an attention-based convolutional neural network. We evaluate the accuracy of the similarity detector on an evaluation set with 100 answers, and can get the 71% Mean Reciprocal Rank (MRR) score.

• KIPS Transactions on Software and Data Engineering
• /
• v.7 no.11
• /
• pp.443-450
• /
• 2018

Crohn's disease, which is recently increasing in Korea, may be seen throughout the gastrointestinal tract and cause various symptoms. In particular, Crohn's disease is especially difficult to diagnose with several symptoms similar to other ulcerative colonic diseases. Thus, some studies are underway to distinguish two or more similar diseases. However, the previous studies have not described the procedural diagnosis process of it, which may lead to over-examination in the process. Therefore, we propose a diagnosis process of Crohn's disease based on the analysis of redundancy, sequential linkage and decision point in the diagnosis of Crohn's disease, so that it enables to identify ulcerative colonic diseases with symptoms similar to Crohn's disease. Finally, we can distinguish the colon diseases that have symptoms similar to Crohn's disease and help diagnose Crohn's disease effectively by defining the proposed process-oriented association as an ontology. Applying the proposed ontology to 5 cases showed that more accurate diagnosis was possible and in one case it could be diagnosed even with fewer tests.

• Journal of Korean Library and Information Science Society
• /
• v.49 no.4
• /
• pp.265-294
• /
• 2018

Nowadays, due to an explosive increase in information, information filtering is very important to provide proper information for users. Users hardly obtain scholarly information from a huge amount of information in NDSL of KISTI, except for simple search. In this paper, we propose the service, PIN to solve this problem. Pin provides the word cloud including analyzed users' and others' interesting, co-occurence, and searched keywords, rather than the existing word cloud simply consisting of all keywords and so offers user-customized papers, reports, patents, and trends. In addition, PIN gives the paper classification in NDSL according to keyword matching based classification with the overlapping classification enabled-academic classification system for better search and access to solve this problem. In this paper, Keywords are extracted according to the classification from papers published in Korean journals in 2016 to design classification model and we verify this model.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.23 no.8
• /
• pp.1011-1017
• /
• 2019

This paper proposes reinforcement learning to solve the node-disjoint path problem which establishes multipath for reliable data transmission in wireless ad-hoc networks. The node-disjoint path problem is a problem of determining a plurality of paths so that the intermediate nodes do not overlap between the source and the destination. In this paper, we propose an optimization method considering transmission distance in a large-scale wireless ad-hoc network using Q-learning in reinforcement learning, one of machine learning. Especially, in order to solve the node-disjoint path problem in a large-scale wireless ad-hoc network, a large amount of computation is required, but the proposed reinforcement learning efficiently obtains appropriate results by learning the path. The performance of the proposed reinforcement learning is evaluated from the viewpoint of transmission distance to establish two node-disjoint paths. From the evaluation results, it showed better performance in the transmission distance compared with the conventional simulated annealing.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.21 no.2
• /
• pp.111-116
• /
• 2021

This study is a study on improving the pedestrian Care system, which delivers jaywalking events in real time to the autonomous driving control center and Autonomous driving vehicles in operation and issues warnings and announcements to pedestrians based on pedestrian signals. In order to secure reliability of object detection method of pedestrian Care system, the inspection method combined with camera sensor with Lidar sensor and the improved system algorithm were presented. In addition, for the occurrence events of Lidar sensors and intelligent CCTV received during the operation of autonomous driving vehicles, the system algorithm for the elimination of overlapping events and the improvement of accuracy of the same time, place, and object was presented.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.4
• /
• pp.63-74
• /
• 2021

Location-based services (LBSs) are expected to process a large number of spatial queries, such as shortest path and k-nearest neighbor queries that arrive simultaneously at peak periods. Deploying more LBS servers to process these simultaneous spatial queries is a potential solution. However, this significantly increases service operating costs. Recently, batch processing solutions have been proposed to process a set of queries using shareable computation. In this study, we investigate the problem of batch processing moving k-nearest neighbor (MkNN) queries in dynamic spatial networks, where the travel time of each road segment changes frequently based on the traffic conditions. LBS servers based on one-query-at-a-time processing often fail to process simultaneous MkNN queries because of the significant number of redundant computations. We aim to improve the efficiency algorithmically by processing MkNN queries in batches and reusing sharable computations. Extensive evaluation using real-world roadmaps shows the superiority of our solution compared with state-of-the-art methods.