• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.451-453
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• 2007

This paper describes the design of an asynchronous implementation of a sensor network processor. The main purpose of this work is the reduction of power consumption in sensor network node processors and the research presented here tries to explore the suitability of asynchronous circuits for this purpose. The Handshake Solutions toolkit is used to implement an asynchronous version of a sensor processor. The design is made compact, trading area and leakage power savings with dynamic power costs, targeting the typical sparse operating characteristics of sensor node processors. It is then compared with a synchronous version of the same processor. Both versions are then compared with existing commercial processors in terms of power consumption.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.65-74
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• 2021

The rapid change in gold price is an issue of concern in the global economy and financial markets. Gold has been used as a means for trading and transaction around the world for long period of time and it plays an integral role in monetary, business, commercial and financial activities. More importantly, it is used as economic measure for the global economy and will continue to play an important economic vital role - both locally and globally. There has been an explosive growth in demand for efficient and effective scheme to predict gold price due its volatility and fluctuation. Hence, there is need for the development of gold price prediction scheme to assist and support investors, marketers, and financial institutions in making effective economic and monetary decisions. This paper primarily proposed an intelligent based system for predicting and characterizing the gold market trend. The simulation result shows that the proposed intelligent gold price scheme has been able to predict the gold price with high accuracy and precision, and ultimately it has significantly reduced the prediction error when compared to baseline neural network (NN).

• Proceedings of the KIEE Conference
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• summer
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• pp.698-700
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• 2004

Electric power restructuring offers a major change to the vertically integrated utility monopoly. Deregulation has had a great impact on the electric power industry in various countries. Bidding competition is one of the main transaction approaches after deregulation. The energy trading levels between market participants is largely dependent on the short-term price forecasts. This paper presents the short-term System Marginal Price (SMP) forecasting implementation using backpropagation Neural Network in competitive electricity market. Demand and SMP that supplied from Korea Power Exchange (KPX) are used by a input data and then predict SMP. It needs to analysis the input data for accurate prediction.

• Management Science and Financial Engineering
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• v.11 no.3
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• pp.1-17
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• 2005

Agent technology has been widely applied in today's electronic business, such as mobile agents, multi-agent information systems, etc. In particular, multi-agent systems have been applied as powerful simulation tools to study complex business networks composed of various self-interested trading firms and/or human beings. In this paper, we build an integrated model that consists of a multi-agent B2C market model and a B2B trade network model, and incorporate more reality than much of prior work. Then with this model, we carry out experimental studies on two different strategies that are common in electronic business - 'loyal' strategy (retailers try to build stable cooperation with suppiers to ensure material supply) and 'cost-saving' strategy (retailers try to reduce cost by choosing suppliers with lower wholesale price).

• IE interfaces
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• v.24 no.2
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• pp.139-150
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• 2011

The EPCglobal Network is a computer network used to share product data among trading partners. It provides the supply chain with improved visibility and traceability by using Electronic Product Code (EPC), which is stored on an RFID tag. Although this network model is widely accepted as a global standard and the growth of EPCglobal-subscriber base is considerable, the EPC technology adoption process is still in its infancy. This is because some of the critical issues on this model still remain to be verified such as scalability, data management, security, privacy and the economic value of data sharing. In this paper, we focus on scalability issue among the challenges to overcome and we regard performance of the EPCglobal Network only as a track and trace query-processing cost in the network. We developed performance models consisting of three elements of the EPCglobal Network : Discovery Services (DS), EPC Information Services (EPCIS), Object Naming Services (ONS). Then we abstracted out the track and trace query execution model to evaluate performance of the overall EPCglobal Network. Finally using the proposed models, we carried out simulation analysis based on an RFID-based inbound logistics process of automobile parts. This work is an important step towards the EPC technology diffusion and provides guidelines for businesses looking to buy or build the EPCglobal Network-based systems.

• Journal of KIISE:Information Networking
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• v.30 no.3
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• pp.293-306
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• 2003

In recent years, distributed computing environments have been radically changing to a structure of global, heterogeneous, federative and wide-area systems. This structure's environments consist of a let of objects which are implemented on telecommunication network to provide a wide range of services. Furthermore, all of objects existing on the earth have the duplicated characteristics according to how to categorize their own names or properties. But, the existing naming or trading mechanism has not supported the binding services of duplicated objects, because of deficiency of independent location service. Also, if the duplicated objects which is existing on different nodes provide the same service, it is possible to distribute the client requests considering each system's load. For this reason, we designed and implemented a new model that can not only support the location management of replication objects, but also provide the dynamic binding service of objects located in a system with minimum overload for maintaining load balancing among nodes in wide-area object computing environments. Our model is functionally divided into two parts; one part is to obtain an unique object handle of replicated objects with same property as a naming and trading service, and the other is to search one or more contact addresses by a location service using a given object handle. From a given model mentioned above, we present the procedures for the integrated binding mechanism in design phase, that is, Naming/Trading Service and Location Service. And then, we described in details the architecture of components for Integrated Binding Service implemented. Finally, we showed our implement environment and executing result of our model.

• International Commerce and Information Review
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• v.14 no.4
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• pp.563-582
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• 2012

In this paper, UPnP Network SaaS model has been studied. Currently, this model of UPnP Network and the trade mission is being used by outsourcing. From now on, the introduction of new trading systems and existing systems and the commercialization of this model as a UPnP network service connection should work. The future of UPnP network SaaS model will become commercially available software, commercial software can be accessed remotely via the Internet should be. Customer site activities must be managed from a central location. Application software architecture, pricing, partnerships, management should not include the character models. N should be the model. When used in small and medium enterprises have a very high value.

• Journal of Science and Technology Studies
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• v.19 no.2
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• pp.1-40
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• 2019

Built upon ethnographic method such as participant observation and in-depth interview, this study analyzes the material culture of electronic flower auctions at Yangjae Flower Market. From the viewpoint of Actor-Network Theory(ANT), this research examines how human actors like dealers and auctioneers interact with nonhuman actors such as market devices and these interactions form networks called "agencement." This research is focused on three main objectives: first, to study how the performance of auctions - i.e. the interactions between auctioneers and dealers - change in the wake of new market devices in the auctions; secondly, to look into what changes artifacts bring to the social relationships between auctioneers and dealers; lastly, to analyze the influence of new market devices on auction price in the market. The results of this research are as follows. First, the appearance of new market devices generates changes in the performance of auctions, which means the change of 'agencement' of flower auctions. Direct interactions between auctioneers and dealers turned into indirect interactions through new market devices. Moreover, the changes in the agencement brought changes to the identity of auctioneers and dealers. Secondly, the new agencement caused by the inflow of new market devices formed the trust between the devices and human actors, which gave rise to the trust in electronic auction and in counterpart actors as well. In addition, new market devices lowered direct interactions between auctioneers and dealers and thus made more equal relationships between the two than before. Lastly, market devices like trading screen reduced the leverage of auctioneers by providing dealers with bidding information previously possessed by auctioneers much openly and dealers were able to decide auction prices in more reasonable and dispassionate manner. Economic agency, power, trust, price, and information in the market is material and sensory.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.1872-1885
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• 2011

In recent years, due to the economic growth of the Northeast Asia, the trading relationship among the Asian countries becomes more active, and the mutual level of dependence is increasing. As the general market, the Northeast Asia pursue a function of market and economic activities among the Northeast Asia become more active consistently. It is important that Korea strengthened logistics network connection systems with China and Japan are improving the logistics facilities and expanding the transport network steadily. In order for Korea to improve as a logistics position, Korea needs to build various and efficient multimodal transport system and sets up a position as a major efficient logistics network center. Therefore, this paper intended to analyze transport cost and time of Korea-China-Japan logistics network and suggest a competitive multimodal transport with the maritime transport and new multimodal transport systems by comparing scenarios.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1997.10a
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• pp.105-108
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• 1997

Previous studies in stock market predictions using artificial intelligence techniques such as artificial neural networks and case-based reasoning, have focused mainly on spot market prediction. Korea launched trading in index futures market (KOSPI 200) on May 3, 1996, then more people became attracted to this market. Thus, this research intends to predict the daily up/down fluctuant direction of the price for KOSPI 200 index futures to meet this recent surge of interest. The forecasting methodologies employed in this research are the integration of genetic algorithm and artificial neural network (GAANN) and the integration of genetic algorithm and case-based reasoning (GACBR). Genetic algorithm was mainly used to select relevant input variables. This study adopts the categorical data preprocessing based on expert's knowledge as well as traditional data preprocessing. The experimental results of each forecasting method with each data preprocessing method are compared and statistically tested. Artificial neural network and case-based reasoning methods with best performance are integrated. Out-of-the Model Integration and In-Model Integration are presented as the integration methodology. The research outcomes are as follows; First, genetic algorithms are useful and effective method to select input variables for Al techniques. Second, the results of the experiment with categorical data preprocessing significantly outperform that with traditional data preprocessing in forecasting up/down fluctuant direction of index futures price. Third, the integration of genetic algorithm and case-based reasoning (GACBR) outperforms the integration of genetic algorithm and artificial neural network (GAANN). Forth, the integration of genetic algorithm, case-based reasoning and artificial neural network (GAANN-GACBR, GACBRNN and GANNCBR) provide worse results than GACBR.