• ETRI Journal
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• v.33 no.5
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• pp.791-801
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• 2011

Security in wireless sensor networks (WSNs) is an upcoming research field which is quite different from traditional network security mechanisms. Many applications are dependent on the secure operation of a WSN, and have serious effects if the network is disrupted. Therefore, it is necessary to protect communication between sensor nodes. Key management plays an essential role in achieving security in WSNs. To achieve security, various key predistribution schemes have been proposed in the literature. A secure key management technique in WSN is a real challenging task. In this paper, a novel approach to the above problem by making use of elliptic curve cryptography (ECC) is presented. In the proposed scheme, a seed key, which is a distinct point in an elliptic curve, is assigned to each sensor node prior to its deployment. The private key ring for each sensor node is generated using the point doubling mathematical operation over the seed key. When two nodes share a common private key, then a link is established between these two nodes. By suitably choosing the value of the prime field and key ring size, the probability of two nodes sharing the same private key could be increased. The performance is evaluated in terms of connectivity and resilience against node capture. The results show that the performance is better for the proposed scheme with ECC compared to the other basic schemes.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.11 no.6
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• pp.799-807
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• 1999

Exergy analysis is widely used in energy system analysis for more efficient energy use. Pinch technology has focused on chemical plants, such as pure heat exchanger networks. In this study, the objective is to seek more effective means with integrating above two methods. In order to demonstrate effective result and to prove possibility for pinch analysis, the steam turbine is adopted to make heat recovery in the heat exchanger network. Three cases are introduced using the integration of exergy and pinch analysis. The standard steam turbine utility is the base case, and adding the heat pump to this system is the second case. The third case is the system with the heat pump and minimum utilities. The results show that the output power of steam turbine in the case(2) and case(3) are increased up to 42% and 46%, respectively, compared with that of base case.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.17 no.3
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• pp.81-90
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• 2007

In the UMTS (Universal Mobile Telecommunication System), which is one of 3G mobile communication standards, the protocol called UMTS AKA (Authentication and Key Agreement) is used to authenticate mobile stations. However, the UMTS AKA protocol has some weakness, including network bandwidth consumption between a SN (Serving Network) and a HN (Home Network) and SQN (SeQuence Number) synchronization. In this paper, we propose a new improved protocol for UMTS that overcomes UMTS AKA weakness. Our protocol solves the privacy problem caused by IMSI (International Mobile Subscriber Identity)'s disclosure and provides perfect forward secrecy using ECDH (Elliptic Curve Diffie Hellman).

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.1 no.1
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• pp.67-74
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• 2008

As wireless network market is increasing rapidly, the biggest issue is to transfer safe data and to authenticate users. This paper proposes ECbA(Elliptic Curve based Authentication) which consists of the mutual authentication mechanism that users can ascertain the identity of an authentication server and the user authentication mechanism that an authentication server can make sure users' identity, by using Elliptic Curve algorithms. The proposed ECbA system diminishes the message quantity and the execution time by using the small elliptic curve algorithm with the small key length in authentication. In addition, as this paper reduces the authentication steps of existing EAP_TLS into 6 authentication steps, the communication cost and mutual authentication time can be saved. As this paper distributes new keys, whenever authenticating users by using key exchange mechanism, it provides safe encryption communication and prevents DoS attack by controlling the users authentication request by authentication server.

• Journal of the Korean Geotechnical Society
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• v.32 no.11
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• pp.31-42
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• 2016

Usually the seismic stability analysis of slope uses the pseudostatic analysis considering the inertial force by the earthquake as a static load. Geostructures such as slope include the uncertainty of soil properties. Therefore, it is necessary to consider probabilistic method for stability analysis. In this study, the probabilistic stability analysis of slope considering the uncertainty of soil properties has been performed. The fragility curve that represents the probability of exceeding limit state of slope as a function of the ground motion has been established. The Monte Carlo Simulation (MCS) has been implemented to perform the probabilistic stability analysis of slope with pseudostatic analysis. A procedure to develop the fragility curve by the pseudostatic horizontal acceleration has been presented by calculating the probability of failure based on the Artificial Neural Network (ANN) based response surface technique that reduces the required time of MCS. The results showed that the proposed method can get the fragility curve that is similar to the direct MCS-based fragility curve, and can be efficiently used to reduce the analysis time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.8
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• pp.518-527
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• 2014

This study is to estimate the learning curve based on the consequences of reduced voice of customer from each telecommunication service products. We used Exponential Decay Model, which is the most popular among the learning curve models. We attempted to add how VOC changes in accordance with seasonal factors, human resource input, application of software, and the investment. The results of the empirical analysis of each service product as follows: First, as learning curve, customer complaints decreased. Second, human resource input, Network fault make increase or decrease customer complaints(VOC). Third, even though increasing the customer's quality of experience, VOC would not decrease due to service paradox.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.11a
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• pp.873-876
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• 2005

무선 센서 네트워크 (Wireless Sensor Network)에서 기존에 존재하는 대부분의 보안 프로토콜들은 대칭적인 공유키(symmetric pairwise key) 설정에 기반하고 있다. 그러나 이러한 프로토콜들은 노드 전복 (node compromising), 그리고 과중한 트래픽의 문제점을 안고 있다. 더욱이, 대칭키 방법을 이용한 브로드캐스트 메시지 인증은 자원이 제약된 센서네트워크에서 적용하기에는 너무 복잡하다. 본 논문은 공개키를 이용한 공유키(Pairwise Key) 설정에 기반한 보안 프로토콜들을 제안한다. 특히 경량성을 위하여 타원 곡선 암호 (Ellptic Curve Cryptography)를 채택하였다. 제안 프로토콜은 공유키 설정과 브로드캐스트 메시지 인증을 위하여 각각 Elliptic Curve Diffie-Hellman (ECDH)과 Elliptic Curve Digital Signature Algorithm (ECDSA)를 이용한다. 더욱이, 분산된 rekeying 메커니즘 (decentralized rekeying mechanism)을 도입함으로써 TinySec 의 성능을 향상시킨다.

• Journal of Animal Science and Technology
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• v.59 no.2
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• pp.3.1-3.7
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• 2017

Background: The modelling of lactation curve provides guidelines in formulating farm managerial practices in dairy cows. The aim of the present study was to determine the suitable non-linear model which most accurately fitted to lactation curves of five lactations in 134 Gir crossbred cows reared in Research-CumDevelopment Project (RCDP) on Cattle farm, MPKV (Maharashtra). Four models viz. gamma-type function, quadratic model, mixed log function and Wilmink model were fitted to each lactation separately and then compared on the basis of goodness of fit measures viz. adjusted $R^2$, root mean square error (RMSE), Akaike's Informaion Criteria (AIC) and Bayesian Information Criteria (BIC). Results: In general, highest milk yield was observed in fourth lactation whereas it was lowest in first lactation. Among the models investigated, mixed log function and gamma-type function provided best fit of the lactation curve of first and remaining lactations, respectively. Quadratic model gave least fit to lactation curve in almost all lactations. Peak yield was observed as highest and lowest in fourth and first lactation, respectively. Further, first lactation showed highest persistency but relatively higher time to achieve peak yield than other lactations. Conclusion: Lactation curve modelling using gamma-type function may be helpful to setting the management strategies at farm level, however, modelling must be optimized regularly before implementing them to enhance productivity in Gir crossbred cows.

• Steel and Composite Structures
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• v.36 no.5
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• pp.493-506
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• 2020

The load-slip relationship of the shear connection is an important parameter in design and analysis of composite structures. In this paper, a load-slip curve prediction method of the shear connection based on the artificial neural networks (ANNs) is proposed. The factors which are significantly related to the structural and deformation performance of the connection are selected, and the shear stiffness of shear connections and the transverse coordinate slip value of the load-slip curve are taken as the input parameters of the network. Load values corresponding to the slip values are used as the output parameter. A twolayer hidden layer network with 15 nodes and 10 nodes is designed. The test data of two different forms of shear connections, the stud shear connection and the perforated shear connection with flange heads, are collected from the previous literatures, and the data of six specimens are selected as the two prediction data sets, while the data of other specimens are used to train the neural networks. Two trained networks are used to predict the load-slip curves of their corresponding prediction data sets, and the ratio method is used to study the proximity between the prediction loads and the test loads. Results show that the load-slip curves predicted by the networks agree well with the test curves.

• Journal of the Korea Society of Computer and Information
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• v.21 no.1
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• pp.115-123
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• 2016

In this study, we collect various side effect pairs which are appeared frequently at many drugs, and select side effect pairs that have higher severity. For every selected side effect pair, we extract common genetic networks which are shared by side effects' genes and drugs' target genes based on PPI(Protein-Protein Interaction) network. For this work, firstly, we gather drug related data, side effect data and PPI data. Secondly, for extracting common genetic network, we find shortest paths between drug target genes and side effect genes based on PPI network, and integrate these shortest paths. Thirdly, we develop a classification model which uses this common genetic network as a classifier. We calculate similarity score between the common genetic network and genetic network of a drug for classifying the drug. Lastly, we validate our classification model by means of AUC(Area Under the Curve) value.