• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5555-5567
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• 2018

State-of-art instance segmentation networks are successful at generating 2D segmentation mask for region proposals with highest classification score, yet 3D object segmentation task is limited to geocentric embedding or detector of Sliding Shapes. To this end, we propose an amodal 3D instance segmentation network called A3IS-CNN, which extends the detector of Deep Sliding Shapes to amodal 3D instance segmentation by adding a new branch of 3D ConvNet called A3IS-branch. The A3IS-branch which takes 3D amodal ROI as input and 3D semantic instances as output is a fully convolution network(FCN) sharing convolutional layers with existing 3d RPN which takes 3D scene as input and 3D amodal proposals as output. For two branches share computation with each other, our 3D instance segmentation network adds only a small overhead of 0.25 fps to Deep Sliding Shapes, trading off accurate detection and point-to-point segmentation of instances. Experiments show that our 3D instance segmentation network achieves at least 10% to 50% improvement over the state-of-art network in running time, and outperforms the state-of-art 3D detectors by at least 16.1 AP.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1481-1501
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• 2019

In opportunistic network, the behavior of a node is autonomous and has social attributes such as selfishness.If a node wants to forward information to another node, it is bound to be limited by the node's own resources such as cache, power, and energy.Therefore, in the process of communication, some nodes do not help to forward information of other nodes because of their selfish behavior. This will lead to the inability to complete cooperation, greatly reduce the success rate of message transmission, increase network delay, and affect the overall network performance. This article proposes a hybrid incentive mechanism (Mim) based on the Reputation mechanism and the Credit mechanism.The selfishness model, energy model (The energy in the article exists in the form of electricity) and transaction model constitute our Mim mechanism. The Mim classifies the selfishness of nodes and constantly pay attention to changes in node energy, and manage the wealth of both sides of the node by introducing the Central Money Management Center. By calculating the selfishness of the node, the currency trading model is used to differentiate pricing of the node's services. Simulation results show that by using the Mim, the information delivery rate in the network and the fairness of node transactions are improved. At the same time, it also greatly increases the average life of the network.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.280-282
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• 2019

Windows 환경에서 상용 저지연 NIC를 이용하여 컴퓨터 네트워크 통신 지연을 감소시킬 수 있다. 일반적으로 시스템의 커널에서 네트워크 처리를 담당하지만 본 논문은 커널을 우회하여 NIC에서 처리하여 운영체제에서 발생하는 지연을 최소화한다. 상용 NIC과 광섬유 케이블을 사용하여 네트워크 지연에 대한 비교결과를 보이며 네트워크 저지연 시스템의 구성을 제시한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.443-446
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• 2010

본 연구의 목적은 GPS 수신기를 내장한 스마트폰 사용자를 대상으로 위치 기반 서비스와 모바일 소셜 네트워크 서비스를 이용한 중고물품 거래 시스템을 개발하는 것이다. 이 시스템은 GPS를 이용하여 사용자의 현재 위치를 파악하고 해당 위치를 중심으로 주변의 가까운 장소에 등록되어있는 판매물품을 쉽게 찾을 수 있도록 한다. 또한 소셜 네트워크 서비스(Twitter)와 연동하여 물품 거래 사용자간의 물품에 대한 의견, 신뢰도 확인, 적정 가격 설정, 관심 물품에 대한 빠른 소식을 공유할 수 있는 특징을 가진다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.123-130
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• 2021

With the recent developments in computer technology, there has been an increasing interest in the field of machine learning. This also has led to a significant increase in real business cases of machine learning theory in various sectors. In finance, it has been a major challenge to predict the future value of financial products. Since the 1980s, the finance industry has relied on technical and fundamental analysis for this prediction. For future value prediction models using machine learning, model design is of paramount importance to respond to market variables. Therefore, this paper quantitatively predicts the stock price movements of individual stocks listed on the KOSPI market using machine learning techniques; specifically, the reinforcement learning model. The DQN and A2C algorithms proposed by Google Deep Mind in 2013 are used for the reinforcement learning and they are applied to the stock trading strategies. In addition, through experiments, an input value to increase the cumulative profit is selected and its superiority is verified by comparison with comparative algorithms.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.17-22
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• 2024

This paper introduces the implementation of a secondhand clothing trading system equipped with virtual fitting functionality based on deep learning. The proposed system provides users with the ability to visually try on secondhand clothing items online and assess their fit. To achieve this, it utilizes the Convolutional Neural Network (CNN) algorithm to create virtual representations of users considering their body shape and the design of the clothing. This enables buyers to pre-assess the fit of clothing items online before actually wearing them, thereby aiding in their purchase decisions. Additionally, sellers can present accurate clothing sizes and fits through the system, enhancing customer satisfaction. This paper delves into the CNN model's training process, system implementation, user feedback, and validates the effectiveness of the proposed system through experimental results.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.4
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• pp.213-224
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• 1998

Since the late 1980s, an Increasing number of neural network models have been studied in the areas of financial prediction and analysis. The purpose of this study is to Investigate the possibility of building a neural network model that is able to construct a profitable trading strategy in the Korean Stock Market. This study classifies stocks into the future market winners and losers from the publicly available accounting information and builds portfolios based on this information. The performances of the winner portfolios and the loser portfolios are compared with each other and against the market index. The empirical result of this research is consistent with the traditional fundamental analysis where it is claimed that the financial statements contain firm values that may not be fully reflected In stock prices without delay. Despite the supporting empirical evidence. It is somewhat Inconclusive as to whether or not the abnormal return in excess of market return is the result of the extra knowledge obtained in the neural network models derived from the historical accounting data. This research attempts to open another avenue using neural network models for searching for evidence against market efficiency where statistics and intuition have played a major role.

• Journal of the Korea Society of Computer and Information
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• v.24 no.3
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• pp.29-39
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• 2019

In this study, we introduce a model that satisfies energy efficiency and economical efficiency by introducing and demonstrating cogeneration generators in industrial complexes using various actual data collected at the site. The proposed model is composed of three scenarios, ie, full - time operation, scenario operated according to demand, and a fusion type. In this study, the power generation profit and surplus thermal energy are measured according to the operation of the generator, and the thermal energy is traded according to the demand of the customer to calculate the profit and loss including the heat and evaluate the economic efficiency. As a result of the study, it is relatively profitable to reduce the generation of the generator under the condition that the electricity rate is low and the gas rate is high, while the basic charge is not increased. On the contrary, if the electricity rate is high and the gas rate is low, The more you start up, the more profit you can see. These results show that even a cogeneration power plant with a low economic efficiency due to a low "spark spread" has sufficient economic value if it can sell more than a certain amount of heat energy from a nearby customer and adjust the applied power through peak management.

• Journal of the Korean Institute of Navigation
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• v.18 no.3
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• pp.81-103
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• 1994

Increasing costs and competition in the global trade and transportation arena have led to a search for effient, cost-effective, particularly through the application of computer and information technologies. Most recently the introduction of Electronic Data Interchange(EDI) technologies in both trading and trade facili-tation activitiess have bagun to change the complextion of the international transport space. Korea as well as the other developing countries has become aware of the need to embrace EDI strate-gies in order to maintain a competitive market position with their more technologically advanced neighbou-ring and international trading partners. A way of EDI implementation, KMPA has invested large budgets in the research of the EDI since 1990. As the result of study in EDI of transport, KL-Net(Korea Logistics Network) was organized for the EDI business in cargo logistics. In spite of these KMPA's activities, the development plan of container logistics data interchange is not good and useful. So a new model of EDI in transportation is required by using the concepts of cargo data sharing. The purpose of this paper is to suggest a new way of container logistics data interchange model. This paper therefore analyze the information flow in the current container logistics and find the problem in the area to derive a new model. The followings are the results of this paper : (1) There are many problems and user's requirements in container logistics data interchange in Korea. (2) Many messages of UN/EDIFACT are able to be used in container logistics data interchange. (3) The container cargo data are stored in Container Logistics Network(CL-Net) database. And when necessary by requesting message transmission, the container logistics data interchange is possible. (4) Customs cargo clearance system and PORT-MIS can be linked to CL-Net. If the systems, however, are to introduce EDI in data interchange, the quality of user's software has to be assured.

• The Journal of the Convergence on Culture Technology
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• v.5 no.3
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• pp.55-60
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• 2019

It is true that Blockchain has been known as a core technology for cryptocurrency like bitcoin (BTC). It is caused by its rapid value rises. Now, one BTC is trading around 10,000 US dollars while it bought just less than one dollar at its first trading in May, 2010. Blockchain makes on-line transactions possible by the safe cryptocurrency swiftly based on P2P network and distributed public ledger while its on-line traffic is rapidly increasing. However, this technology has bigger potential in the fourth industrial revolution era and its application areas will be varied. The evolving intelligent information society needs to make new added value through utilizing, sharing and processing of useful digital information. Obstacles such as hacking and fraud often exist when transactions of digital properties, right transfers, etc. are done through digital network specialized with anonymity. It is expected that blockchain will be a definite solution in this regard. This paper addresses useful development directions and countermeasures for blokchain in the digital economy by analysis of its current status and issues.