• Journal of Institute of Control, Robotics and Systems
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• v.11 no.8
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• pp.709-716
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• 2005

As a way to build more efficient and intelligent container cranes for todays hub ports, communication networks are used to interconnect numerous sensors, actuators, controllers, and operator switches and consoles that are spatially distributed over a crane. Various signals such as sensor values and operator's commands are digitized and broadcast on the network instead of using separate wiring cables. This not only makes the design and manufacturing of a crane more efficient, but also easier implementation of intelligent control algorithms. This paper presents the performance evaluation of CAN(Controller Area Network), TTP(Time Triggered Protocol) and Byteflight that can be used for cranes. Through discrete event simulation, several important quantitative performance factors such as the probability of a transmission failure, average system delay (data latency) and maximum system delay have been evaluated.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.8
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• pp.794-799
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• 2012

The international standard, ISO-11783, was designed for the communication within an agriculture machinery. Even if it is based on the CAN (Control Area Network) protocol, its extended features which include point-to-point communication and large data transmission support show different network performance from the standard CAN. This paper proposes a dynamic priority allocation method to improve the real-time performance of ISO-11783. Computer simulation shows reduction of the deadline-missed cases and community latency via proposed algorithm.

• Journal of Information Technology Applications and Management
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• v.25 no.2
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• pp.73-90
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• 2018

Despite of increasing studies for product recommendation, the recommendation of product repurchase timing has not yet been studied actively. This study aims to propose deep neural network models usingsimple purchase history data to predict the repurchase timing of each customer and compare performances of the models from the perspective of prediction quality, including expected ROI of promotion, variability of precision and recall, and diversity of target selection for promotion. As an experiment result, a recurrent neural network (RNN) model showed higher promotion ROI and the smaller variability compared to MLP and other models. The proposed model can be used to develop a CRM system that can offer SMS or app-based promotionsto the customer at the right time. This model can also be used to increase sales for product repurchase businesses by balancing the level of ordersas well as inducing repurchases by customers.

• The Transactions of the Korea Information Processing Society
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• v.6 no.3
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• pp.571-579
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• 1999

A Macro-Star graph which has a star graph as a basic module has node symmetry, maximum fault tolerance, and hierarchical decomposition property. And, it is an interconnection network which improves a network cost against a star graph. A matrix star graph also has such good properties of a Macro-Star graph and is an interconnection network which has a lower network cost than a Maco-Star graph. In this paper, we propose a method to embed between a Macro-Star graph and a matrix star graph. We show that a Macro-Star graph MS(k, n) can be embedded into a matrix star graph MS\ulcorner with dilation 2. In addition, we show that a matrix star graph MS\ulcorner can be embedded into a Macro-Star graph MS(k,n+1) with dilation 4 and average dilation 3 or less as well. This result means that several algorithms developed in a star graph can be simulated in a matrix star graph with constant cost.

• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.177-180
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• 2008

There are many application areas of sensor networks, such as surveillance, hospital monitoring, and home network. These are dependent on the secure operation of networks, and will have serious outcome if the networks is injured. An adversary can inject false data into the network through the compromising node. Ye et al. proposed a statistical en-route filtering scheme (SEF) to detect such false data during forwarding process. In this scheme, it is important that the choice of the threshold value since it trades off security and overhead. This paper presents an adaptive threshold value determining method in the SEF using fuzzy logic. The fuzzy logic determines a security distance value by considering the situation of the network. The Sensor network is divided into several areas by the security distance value, it can each area to uses the different threshold value. The fuzzy based threshold value can reduce the energy consumption in transmitting.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.75-77
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• 1994

This paper presents a method of obtaining transmission network equivalents from the network's driving-point admittance characteristic. Proposed method is based on modal decomposition representation for the large-scale interconnected system. As a result, Norton-type of discrete-time filter model can be generated. It can reproduce the driving-point admittance characteristic of the network. Furthermore proposed model can be implemented into the EMTP in a direct manner. The simulation results with the full system representation and the developed equivalent system showed a good agreement.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.86-88
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• 2004

Personal Robot System in developing, have a module architecture, each module are connected through variety network system like ethernet, WLAN (802.11), IEEE 1394 (firewire), bluetooth, CAN, or RS-232C. In developing personal robot system. We think that the key of robot performance is interoperablity among modules. Each network protocol are well connected in the view of network system for the interoperability. So we make a bridging architecture that can routing converting, and transporting packets with matching each network's properties. Furthermore, we suggest a advanced design scheme for realtime / non-realtime and control signal (short, requiring hard-realtime) / multimedia data (large, requiring soft-realtime).

• Proceedings of the Korea Information Processing Society Conference
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• 2004.05a
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• pp.1589-1592
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• 2004

현재 무선 인터넷 환경은 이동 단말에 컨텐츠 서비스를 제공할 경우, 서비스 사용자가 소유한 단말 환경의 다양성을 고려한 컨텐츠 최적화 작업을 필요로 한다. 기존 환경에서는 이런 기능을 위한 서버를 따로 설치하여 관리함으로 사용자가 늘어나게 되면 서버에 부하가 집중되어 제공되는 서비스의 질이 저하되는 문제가 발생한다. 본 논문에서는 이런 컨텐츠 최적화 기능을 망에서 제공하여 서버의 부하 집중 문제를 해결하는 이동 컨텐츠 적응형 네트워크(Mobile Contents Adaptation: MobiCAN)를 제안한다. MobiCAN 시스템은 ABone(Active Network Backbone) 데몬과 ANTS(Active Network Transfer System) 실행환경, 컨텐츠 최적화를 위한 액티브 응용으로 구성된다. 본 연구에서는 위와 같이 구성된 MobiCAN 시스템을 실제 무선 인터넷 망과 연동시킴으로 해서 액티브 네트워크의 무선 인터넷 적용 가능성을 확인하였다.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.23-30
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• 2021

Sentiment Analysis has become very important field of research because posting of reviews is becoming a trend. Supervised, unsupervised and semi supervised machine learning methods done lot of work to mine this data. Feature engineering is complex and technical part of machine learning. Deep learning is a new trend, where this laborious work can be done automatically. Many researchers have done many works on Deep learning Convolutional Neural Network (CNN) and Long Shor Term Memory (LSTM) Neural Network. These requires high processing speed and memory. Here author suggested two models simple & bidirectional deep leaning, which can work on text data with normal processing speed. At end both models are compared and found bidirectional model is best, because simple model achieve 50% accuracy and bidirectional deep learning model achieve 99% accuracy on trained data while 78% accuracy on test data. But this is based on 10-epochs and 40-batch size. This accuracy can also be increased by making different attempts on epochs and batch size.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.3
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• pp.214-227
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• 2022

The successful implementation of green supply chain management(GSCM) practices requires a level of cooperation that can be difficult to conduct. Despite this challenge, limited scholarly attention has been paid to exploring how the implementation of GSCM practices can be effectively facilitated and enhanced through accumulated social capital with suppliers. Based on social capital theory, this study postulates that supplier network characteristics derived from social capital with key suppliers can be critical antecedents of GSCM, which in turn enhances the firm's environmental performance. To test hypotheses, data were collected from 330 firms in 15 countries, and structural equation modeling was employed. Results show that GSCM improves environmental performance, and structural and cognitive social capitals of the supplier network act as antecedents and lead to GSCM implementation.