• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.633-635
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• 2003

Electricity industries throughout the world are undergoing unprecedented changes. As a result, these changes lead to the separation of traditional integrated utilities and the introduction of competition in order that increase efficiency in electricity industry. Direct load control (DLC) system in competitive electricity market has a hierarchical interactive operation system, therefore, its control logic is also applied by bilateral interactive method that interchanges information related to interruptible load between operation hierarchies. Consequently, load curtailment allocation algorithm appropriate for new DLC system is required, and based on interchanged information, this algorithm should be implemented by most efficient way for each operation hierarchy. In this paper, we develop the load curtailment allocation algorithm in an emergency for new DLC system. Especially, the optimal algorithm for load aggregator (LA) that participates in competitive electricity market as a main operator for load management is developed.

• Annual Conference of KIPS
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• 2022.05a
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• pp.264-267
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• 2022

Recently, federated learning (FL) has increased prominence as a viable approach for enhancing user privacy and data security by allowing collaborative multi-party model learning without exchanging sensitive data. Despite this, most present FL systems still depend on a centralized aggregator to generate a global model by gathering all submitted models from users, which could expose user privacy and the risk of various threats from malicious users. To solve these issues, we suggested a safe FL framework that employs differential privacy to counter membership inference attacks during the collaborative FL model training process and empowers blockchain to replace the centralized aggregator server.

• Journal of Korean Library and Information Science Society
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• v.40 no.2
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• pp.223-242
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• 2009

This is an exploratory study targeting initial users to evaluate the usability of an aggregator-supplied full-text database and to analyze the differences in task performance and perceptions based on participant characteristics. The differences in completion time and perceptions on ease of use, terminology, subject categories and satisfaction were analyzed based on the participant characteristics such as Kolb learning style, gender and participation in user instruction on full-text databases. The results indicated that there was a statistically significant difference in completion time based on the Kolb learning style. Also a statistically significant difference was found in perceptions on ease of use and terminology based on gender. However no statistically significant difference was found in perceptions on the usability of the database based on the participation in user instruction.

• Journal of the Korea Society of Computer and Information
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• v.17 no.2
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• pp.119-126
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• 2012

Local monitoring is an effective technique in securing data of wireless sensor networks. Existing solutions require high communication cost for detecting false data and this results in a network lifetime being shortened. This paper proposes novel techniques of monitoring based secure data aggregation and filtering false data in wireless sensor networks. The aim is to reduce energy consumption in securing data aggregation. An aggregator and its monitoring node perform data aggregation in a 60o sextant cluster. By checking Message Authentication Codes (MAC), aggregation data will be dropped by a forward aggregator if data aggregated by the aggregator and data monitored by the monitoring node are inconsistent. The simulation shows that the proposed protocol can reduce the amount of average energy consumption about 64% when comparing with the Data Aggregation and Authentication protocol (DAA)[1]. Additionally, the network lifetime of the proposed protocol is 283% longer than that of DAA without any decline in data integrity.

• The KIPS Transactions:PartC
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• v.18C no.5
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• pp.303-316
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• 2011

Data aggregation is important in wireless sensor networks. However, it also introduces many security problems, one of which is that a compromised node may inject false data or drop a message during data aggregation. Most existing solutions rely on encryption, which however requires high computation and communication cost. But they can only detect the occurrence of an attack without finding the attacking node. This makes sensor nodes waste their energy in sending false data if attacks occur repeatedly. Even an existing work can identify the location of a false data injection attack but it has a limitation that at most 50% of total sensor nodes can participate in data transmission. Therefore, a novel approach is required such that it can identify an attacker and also increase the number of nodes which participate in data transmission. In this paper, we propose a monitoring-based secure data aggregation protocol to prevent against a compromised aggregator which injects false data or drops a message. The proposed protocol consists of aggregation tree construction and secure data aggregation. In secure data aggregation, we use integration of abnormal data detection with monitoring and a minimal cryptographic technique. The simulation results show the proposed protocol increases the number of participating nodes in data transmission to 95% of the total nodes. The proposed protocol also can identify the location of a compromised node which injects false data or drops a message. A communication overhead for tracing back a location of a compromised node is O(n) where n is the total number of nodes and the cost is the same or better than other existing solutions.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2220-2226
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• 2018

Electric vehicles (EVs) are significant resources for demand response (DR). Thus, it is essential for EV aggregators to quantitatively evaluate their capability for DR. In this paper, a concept of dynamic equivalent battery (DEB) is proposed as a metric for evaluating the DR performance using EVs. The DEB is the available virtual battery for DR. The capacity of DEB is determined from stochastic calculation while satisfying the charging requirements of each EV, and it varies also with time. Further, a new indicator based on the DEB and time-varying electricity prices, named as value of DEB (VoDEB), is introduced to quantify the value of DEB coupled with the electricity prices. The effectiveness of the DEB and the VoDEB as metrics for the DR performance of EVs is verified with the simulations, where the difference of charging cost reduction between direct charging and optimized bidding methods is used to express the DR performance. The simulation results show that the proposed metrics accord well with the DR performance of an EV fleet. Thus, an EV aggregator may utilize the proposed concepts of DEB and VoDEB for designing an incentive scheme to EV users, who participate in a DR program.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.405-409
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• 2007

The RSS which is a kind of syndication technology enables a part or the whole of the content which it provides from web site to be able to be used in different service. It is protocol to summarize and share various contents on web site. This Paper propose the ways to implement system to aggregate RSS feed and archive it and the services using it. Also, the users register the channel RSS to the RSS aggregator system and recommend it. It can drive to share of knowledge between researchers.

• IEMEK Journal of Embedded Systems and Applications
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• v.4 no.3
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• pp.139-147
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• 2009

This paper proposed the context awareness reasoning system to provide the personalized services dynamically in a ubiquitous mobile environments. The proposed system is designed to provide the personalized services to mobile users and consists of the context aggregator and the knowledge manager. The context aggregator can collect information from networks through Open API Gateway as well as sensors in a various ubiquitous environment. And it can also extract the place types through the geocoding and the social address domain ontology. The knowledge manager is the core component to provide the personalized services, and consists of activity reasoner, user pattern learner and service recommender to provide the services predict by extracting the optimized service from user situations. Activity reasoner uses the ontology reasoning and user pattern learner learns with previous service usage history and contexts. And to design service recommender easy to flexibly apply in dynamic environments, service recommender recommends service in the only use of current accessible contexts. Finally, we evaluate the learner and recommender of proposed system by simulation.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.421-425
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• 2007

The exponential increase of digital contents brought about the e-Challenge crisis to the librarians. How can all the e-resources be managed effectively? How can we detect all the broken links? How can we assist the users to the right resources? This paper concentrates on building CLICK(Cooperative Link Center in KOREA) as a knowledge compass by collecting diverse science & technology information and creating tight coupled links between information resources for reference linking and providing users with the optimal route for the resource per user. If the publishers, Abstract & Index DB, Searching Portal, Electronic Libraries, Full-text DB and Aggregator can be linked by using a standardized way through a CLICK, the service channels can be diversified. Users can select the channels without rein under according to a use purpose and conditions.

• The Journal of Society for e-Business Studies
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• v.14 no.2
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• pp.41-56
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• 2009

The purpose of this paper is to present a statistical model that can predict the rapid shift of users' attention by analyzing the lifecycle patterns of news in a social news aggregation service. Internet news service sites have a distinct characteristic in a sense that users' attention change very quickly in a short period of time. In this research, we propose a regression model for each news category which can model the decay pattern of users' attention and the content promotion policy of a social news aggregator is proven to be a major source of the rapid growth in the popularity of news. The proposed model is expected to be useful for evaluation of the social news aggregation service provider's content promotion policy that attempts to maximize users' attention as well as the diversity of news contents.