• 전기학회논문지
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• 제65권4호
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• pp.555-560
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• 2016

Recently, many countries have placed great attention on energy security and climate changes. Governments are promoting the construction of renewable energy projects with regulatory support in Korea. Despite an increasing penetration of renewable resources, however, the photovoltaic and wind power are underutilized due to the endemic problems such as difficulties of output control and intermittent output. The Energy Storage System (ESS) is proposed as a good solution for solving the problems and has been studied in both the private business and the government. However, because of inefficient aspects, the research has been carried out for improving high costs and a small capacity. In addition, the ESS is currently installed for using only one purpose which is frequency regulation or transmission congestion relief such that has an economic limitation. Therefore, methods which are becoming economically justifiable to increase the penetration of the ESS is required. Thus, this paper presents in terms of operation efficiency to improve economic feasibility of the ESS currently used. mainly, there are two aspects for the operation efficiency. Firstly, it is intended to improve the utilization rate through a process that can utilize the ESS for various purposes. It is necessary to be able to use for other purposes by classifying and clustering for increasing the efficiency of availability. The clustering method is proposed to conduct the grouping the ESS. Especially, it is proposed to utilize ESS for frequency regulation service which is the one of ancillary services in the power system. Through case studies, it is confirmed to secure the necessary resources by clustering small size ESS.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권7호
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• pp.1986-2009
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• 2024

The integration of blockchain technology with the rapid growth of Internet of Things (IoT) devices has enabled secure and decentralised data exchange. However, security vulnerabilities and performance limitations remain significant challenges in IoT blockchain networks. This work proposes a novel approach that combines transaction representation and machine learning techniques to address these challenges. Various clustering techniques, including k-means, DBSCAN, Gaussian Mixture Models (GMM), and Hierarchical clustering, were employed to effectively group unlabelled transaction data based on their intrinsic characteristics. Anomaly transaction prediction models based on classifiers were then developed using the labelled data. Performance metrics such as accuracy, precision, recall, and F1-measure were used to identify the minority class representing specious transactions or security threats. The classifiers were also evaluated on their performance using balanced and unbalanced data. Compared to unbalanced data, balanced data resulted in an overall average improvement of approximately 15.85% in accuracy, 88.76% in precision, 60% in recall, and 74.36% in F1-score. This demonstrates the effectiveness of each classifier as a robust classifier with consistently better predictive performance across various evaluation metrics. Moreover, the k-means and GMM clustering techniques outperformed other techniques in identifying security threats, underscoring the importance of appropriate feature selection and clustering methods. The findings have practical implications for reinforcing security and efficiency in real-world IoT blockchain networks, paving the way for future investigations and advancements.

• 한국정보통신설비학회:학술대회논문집
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• 한국정보통신설비학회 2008년도 정보통신설비 학술대회
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• pp.141-145
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• 2008

Wireless sensor network (WSN) is expected to be used in many applications. However, sensor nodes still have some secure problems to use them in the real applications. They are typically deployed on open, wide, and unattended environments. An adversary using these features can easily compromise the deployed sensor nodes and use compromised sensor nodes to inject fabricated data to the sensor network (false data injection attack). The injected fabricated data drains much energy of them and causes a false alarm. To detect and drop the injected fabricated data, a filtering-based security method and adaptive methods are proposed. The number of different partitions is important to make event report since they can make a correctness event report if the representative node does not receive message authentication codes made by the different partition keys. The proposed methods cannot guarantee the detection power since they do not consider the filtering scheme. We proposed clustering method for filtering-based secure methods. Our proposed method uses fuzzy system to enhance the detection power of a cluster.

• Human Ecology Research
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• 제62권1호
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• pp.69-80
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• 2024

This study explored the relationship between maternal early parental attachment (EPA) and social interest. The participants were 311 mothers with elementary schoolchildren who lived in the Daegu-Gyeongbuk area. Data were collected through an online questionnaire provided on the portal site and analyzed using k-means clustering, t-test, One-Way ANOVA, and Pearson's correlation using IBM SPSS Statistics 21 for Windows and, RMSEA, TLI, NFI and CFI using IBM SPSS AMOS 18 for Windows. The principal results were as follows. Firstly, mothers' EPA anxiety and avoidance had a negative influence on social interest. Secondly, social interest was found to be significantly higher among mothers with a secure attachment style than among mothers with an insecure attachment style. Thirdly, significant differences were observed in levels of social interest among mothers with secure, preoccupied, dismissive, and disorientated attachment styles. A Scheffé post-hoc test revealed that social interest was significantly higher among mothers with a secure attachment style than among mothers with a disorientated attachment style. The experience of relationships with caregivers early in life is therefore important in the development of social interest.

• 한국컴퓨터정보학회논문지
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• 제14권11호
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• pp.105-111
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• 2009

본 논문에서는 차량 간 안전통신을 위하여 다중홉 클러스터링 방식의 문제점을 개선하여, 거리를 계산한 지능형 클러스터링(Intelligence Cluster) 기법을 제안하고자 한다. 고속 이동시 연계성이 없는 차량간에 거리를 계산하여 클러스터링을 하게 되면 설정된 거리 값으로 각 노드들의 연계성이 형성되게 된다. 동일 구성원이 된 노드들 사이에서 거리 값으로 헤더를 선출하게 되고 헤더는 멤버가 된 노드들에게 그룹 내 정보를 전달하게 된다. 헤더 선출 후, 이동성으로 인해 헤더가 이탈되면 긴급상황이 발생될 수 있다. 이때 정보전달은 패킷에 포함된 프로그램의 실행으로 노드에서 제공하는 지능형 클러스터를 이용하여 새로운 클러스터 헤더를 선출하여 전송할 수 있도록 하였다. 본 논문에서는 기존의 Store-and-Forward 라우팅 방식에 컴퓨팅 능력을 추가한 Store-Compute-Forward 방식으로 클러스터를 선출하는 이동 Ad-hoc 통신을 위한 지능형 거리추정 클러스터방식을 제안한다. 논문에서 제안한 이동 Ad-hoc 통신을 위한 지능형 거리추정 클러스터방식은 능동적이고 지능적인 멀티 홉 클러스터 라우팅 프로토콜로서 안정된 통신이 이루어 질 수 있도록 한다.

• 한국멀티미디어학회논문지
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• 제10권2호
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• pp.236-245
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• 2007

무선 센서 네트워크는 그 크기가 작고 제한적인 계산 능력과 저장 공간을 가지고 있으며 저용량의 배터리로 이루어진 많은 수의 노드들로 이루어진다. 이러한 조건에 따라 센서 네트워크 환경에서 센서 노드의 에너지 소모를 줄이는 것은 중요한 문제이다. 따라서 센서 노드의 에너지 소모를 줄이기 위해 노드가 전송하는 메시지의 발생 빈도를 줄이는 것이 고려되어야 한다. 또 다른 과제인 네트워크의 보안은 네트워크의 다양한 응용을 고려할 때 중요한 부분을 차지한다. 이에 본 논문에 서는 동적 클러스터 모델에서의 키 분배 방법을 제안한다. 이 방법에서 사용한 동적 클러스터 모델은 무선 센서 네트워크의 수명을 연장시키는데 매우 효과적인 방법이며 또한 제안한 방법은 클러스터를 구성하는 노드들에게 그리드 기반 키 분배방법을 적용하여 기존의 키 분배 방법에 비해 향상된 보안을 제공한다. 또한 기존에 제안된 그리드 기반, 위치 기반 키 분배 방법 및 클러스터 기반 키 분배 방법들과 비교하여 제안 방법의 우수함을 보였다.

• 인터넷정보학회논문지
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• 제9권6호
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• pp.15-25
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• 2008

이동 에드 혹 네트워크와 센서 네트워크의 차이 때문에 이동 에드 혹 네트워크를 위한 pre-existing autoconfiguration를 센서 네트워크에 간단히 적용할 수 없다. 그러나, 아직 지역적으로 효과적인 유일한 주소 할당이 필요한 메커니즘이 있다. 본 논문은 지역적인 센서 네트워크의 하이브리드 방식의 아이디 할당 계획안을 제안한다. 이러한 하이브리드 방식은 proactive IDs assignment와 reactive IDs assignment를 결합한 방식이다. 제안된 계획안은 reactive IDs assignment을 사용하여 효율적인 통신을 고려하고, zone-based self-organized clustering with Byzantine Agreement를 사용하여 공격에 대한 안전을 고려한다. 따라서 본 논문은 네트워크 트래픽을 최소화하고 센서 네트워크의 이탈한 노드로부터 네트워크를 회복하는 문제를 해결한다.

• International Journal of Computer Science & Network Security
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• 제23권8호
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• pp.121-136
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• 2023

Wireless Sensor Networks (WSNs) have many potential applications and unique challenges. Some problems of WSNs are: severe resources' constraints, low reliability and fault tolerant, low throughput, low scalability, low Quality of Service (QoS) and insecure operational environments. One significant solution against mentioned problems is hierarchical and clustering-based multipath routing. But, existent algorithms have many weaknesses such as: high overhead, security vulnerabilities, address-centric, low-scalability, permanent usage of optimal paths and severe resources' consumption. As a result, this paper is proposed an energy-aware, congestion-aware, location-based, data-centric, scalable, hierarchical and clustering-based multipath routing algorithm based on Numerical Taxonomy technique for homogenous WSNs. Finally, performance of the proposed algorithm has been compared with performance of LEACH routing algorithm; results of simulations and statistical-mathematical analysis are showing the proposed algorithm has been improved in terms of parameters like balanced resources' consumption such as energy and bandwidth, throughput, reliability and fault tolerant, accuracy, QoS such as average rate of packet delivery and WSNs' lifetime.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2020년도 봄 학술논문 발표대회
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• pp.206-207
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• 2020

Accurate estimation of concrete strength development at early ages is a critical factor to secure structural stability as well as to speed up the construction process. The temperature generated from the heat of hydration is considered as a key parameter in predicting the early age strength. Conventionally, concrete temperature has been measured by temperature sensors installed inside concrete. However, considering the measurement on building structures with multiple floors, this method requires reinstallation and repositioning of hardware such as sensors, data loggers and routers for data transfer. This makes the temperature monitoring work cumbersome and inefficient. Concrete temperature monitoring by using thermal remote sensing can be an effective alternative to supplement those shortcomings. In this study, image processing was carried out through K-means clustering technique, which is a unsupervised learning method, and the classification results were analyzed accordingly. In the future, research will be conducted on how to automatically recognize concrete among various objects by using deep learning techniques.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권10호
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• pp.3834-3857
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• 2021

The design of cluster-based routing protocols is necessary for Wireless Sensor Networks (WSN). But, due to the lack of features, the traditional methods face issues, especially on unbalanced energy consumption of routing protocol. This work focuses on enhancing the security and energy efficiency of the system by proposing Energy Efficient Based Secure Routing Protocol (EESRP) which integrates trust management, optimization algorithm and key management. Initially, the locations of the deployed nodes are calculated along with their trust values. Here, packet transfer is maintained securely by compiling a Digital Signature Algorithm (DSA) and Elliptic Curve Cryptography (ECC) approach. Finally, trust, key, location and energy parameters are incorporated in Particle Swarm Optimization (PSO) and meta-heuristic based Harmony Search (HS) method to find the secure shortest path. Our results show that the energy consumption of the proposed approach is 1.06mJ during the transmission mode, and 8.69 mJ during the receive mode which is lower than the existing approaches. The average throughput and the average PDR for the attacks are also high with 72 and 62.5 respectively. The significance of the research is its ability to improve the performance metrics of existing work by combining the advantages of different approaches. After simulating the model, the results have been validated with conventional methods with respect to the number of live nodes, energy efficiency, network lifetime, packet loss rate, scalability, and energy consumption of routing protocol.