• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.10
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• pp.6276-6281
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• 2014

Genetic Algorithms (GAs) are efficient methods for search and optimization problems. On the other hand, there are some problems associated with the premature convergence to local optima of the multimodal function, which has multi peaks. The problem is related to the lack of genetic diversity of the population to cover the search spaces sufficiently. A sharing and crowding method were introduced. This paper proposed strategies to improve the convergence speed and the convergence to the global optimum for solving the multimodal optimization function. These strategies included the random generated sub-population that were well-distributed and spread widely through search spaces. The results of the simulation verified the effects of the proposed method.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.1
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• pp.38-43
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• 2011

Cluster-based routing is high energy consumption of cluster head nodes. A recent approach to resolving the problem is the dynamic cluster technique that periodically re-selects cluster head nodes to distribute energy consumption of the sensor nodes. However, the dynamic clustering technique has a problem that repetitive construction of clustering consumes the more energies. This paper proposes a solution to the problems described above from the energy efficiency perspective. The round-robin cluster header(RRCH) technique, which fixes the initially structured cluster and sequentially selects cluster head nodes, is suggested for solving the energy consumption problem regarding repetitive cluster construction. A simulation result were compared with the performances of two of the most widely used conventional techniques, the LEACH(Low Energy Adaptive Clustering Hierarchy) and HEED(Hybrid, Energy Efficient, Distributed Clustering) algorithms, based on energy consumption, remaining energy for each node and uniform distribution. The evaluation confirmed that in terms of energy consumption, the technique proposed in this paper was 26.5% and 20% more efficient than LEACH and HEED, respectively.

• Journal of KIISE:Databases
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• v.33 no.2
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• pp.163-174
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• 2006

In distributed wireless sensor network, it is difficult to transmit and analyze the entire stream data depending on limited networks, power and processor. Therefore it is suitable to use alternative stream data processing after classifying the continuous stream data. We propose a classification framework for continuous multivariate stream data. The proposed approach works in two steps. In the preprocessing step, it takes input as a sliding window of multivariate stream data and discretizes the data in the window into a string of symbols that characterize the signal changes. In the classification step, it uses a standard text classification algorithm to classify the discretized data in the window. We evaluated both supervised and unsupervised classification algorithms. For supervised, we tested Bayesian classifier and SVM, and for unsupervised, we tested Jaccard, TFIDF Jaro and Jaro Winkler. In our experiments, SVM and TFIDF outperformed other classification methods. In particular, we observed that classification accuracy is improved when the correlation of attributes is also considered along with the n-gram tokens of symbols.

• The KIPS Transactions:PartD
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• v.16D no.2
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• pp.191-200
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• 2009

Location based services (LBSs) have drawn huge attention as the growing number mobile devices and wireless technology demand more pervasive information access. In LBSs, Constraint nearest neighbor queries are one of the important queries of human to fulfill his desired quickly through wireless technology. We propose new query processing of constrained nearest neighbor query on the air to support mobile clients which demand optimal uses of wireless broadcast channel and using minimum battery power of client. First we proposed NN query processing with constrained region and then explain the novel NN query processing with various types of constraints. We have proposed novel algorithms to support Constrained Nearest Neighbor queries on the air based on Distributed Spatial Index and Bitmap-based Spatial Index.

• Journal of Advanced Navigation Technology
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• v.17 no.3
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• pp.298-305
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• 2013

In this paper, we propose simple combining schemes for sensing ATSC digital television signals with spectral correlation density (SCD). The detection algorithms exploiting the cyclostationarity exhibited by the pilot of ATSC digital television signals usually use the SCD value at a given particular frequency. However, we found that non-zero SCDs are found to be distributed over a certain range of frequencies in multipath fading environment. To utilize a set of non-zero SCD values computed in the vicinity of the pilot location, we formulate a class of combining methods in analogy with the maximal ratio combining, the square law combining and the equal gain combining. We show that the proposed simple combining schemes improve the detection performance by 0.5~1.0dB under multipath fading environments.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.160-160
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• 2019

Water is a limited source that needs to be properly managed and distributed to the ever-growing population of the world. Rapid urbanization and development have increased the overall water demand of the world drastically. However, there is loss of billions of liters of water every year due to leakages in water distribution systems. Such water loss means significant financial loss for the utilities as well. World bank estimates a loss of $14 billion annually from wasted water. To address these issues and for the development of efficient and reliable leakage management techniques, high efforts have been made by the researchers and engineers. Over the past decade, various techniques and technologies have been developed for leakage management and leak detection. These include ideas such as pressure management in water distribution networks, use of Advanced Metering Infrastructure, use of machine learning algorithms, etc. For leakage detection, techniques such as acoustic technique, and in recent yeats transient test-based techniques have become popular. Smart Water Grid uses two-way real time network monitoring by utilizing sensors and devices in the water distribution system. Hence, valuable real time data of the water distribution network can be collected. Best results and outcomes may be produced by proper utilization of the collected data in unison with advanced detection and management techniques. Long term reduction in Non Revenue Water can be achieved by detecting, localizing and repairing leakages as quickly and as efficiently as possible. However, there are still numerous challenges to be met and future research works to be conducted in this field.

• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.66-74
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• 2021

With the development of the Internet, user authentication technology that proves me online is improving. Existing ID methods pose a threat of personal information leakage if the service provider manages personal information and security is weak, and the information subject is to the service provider. In this study, as online identification technology develops, we propose a DID-based self-authentication model to prevent the threat of leakage of personal information from a centralized format and strengthen sovereignty. The proposed model allows users to directly manage personal information and strengthen their sovereignty over information topics through VC issued by the issuing agency. As a research method, a self-authentication model that guarantees security and integrity is presented using a decentralized identifier method based on distributed ledger technology, and the security of the attack method is analyzed. Because it authenticates through DID Auth using public key encryption algorithms, it is safe from sniffing, man in the middle attack, and the proposed model can replace real identity card.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.25-32
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• 2019

The core of the block chain technology is solving the problem of agreement on double payment, and the PoW, PoS and DPoS algorithms used for this have been studied. PoW in-process proofs are consensus systems that require feasible efforts to prevent minor or malicious use of computing capabilities, such as sending spam e-mail or initiating denial of service (DoS) attacks. The proof of the PoS is made to solve the Nothing at stake problem as well as the energy waste of the proof of work (PoW) algorithm, and the decision of the sum of each node is decided according to the amount of money, not the calculation ability. DPoS is that a small number of authorized users maintain a trade consensus through a distributed network, whereas DPS provides consent authority to a small number of representatives, whereas PoS has consent authority to all users. If PoS is direct democracy, DPoS is indirect democracy. This study aims to contribute to the continuous development of the related field through the study of the algorithm of the block chain agreement.

• Convergence Security Journal
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• v.19 no.2
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• pp.11-19
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• 2019

The blockchain is a technique for managing transaction data in distributed computing manner without the involvement of central trust authority. The blockchain has been used in various area such as manufacturing, culture, and public as well as finance because of its advantage of the security, efficiency and applicability. In the blockchain, it was considered safe against 51% attack because the adversary could not have more than 50% hash power. However, there have been cases caused by large-scale computing attacks such as 51% and selfish mining attack, and the frequency of these attacks is increasing. In addition, since the development of quantum computers can hold exponentially more information than their classical computer, it faces a new type of threat using quantum algorithms. In this paper, we perform the security analysis of blockchain attacks composing the large computing capabilities including quantum computing attacks. Finally, we suggest the technologies and future direction of the blockchain development in order to be safe against large-scale computing attacks.

• The Journal of the Acoustical Society of Korea
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• v.40 no.2
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• pp.169-175
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• 2021

Recently, an ultrasound hologram and its applications have gained attention in the ultrasound research field. However, the determination technique of transmit signal phases, which generate a hologram, has not been significantly advanced from the previous algorithms which are time-consuming iterative methods. Thus, we applied the deep learning technique, which has been previously adopted to generate an optical hologram, to generate an ultrasound hologram. We further examined the Deep learning-based Holographic Ultrasound Generation algorithm (Deep-HUG). We implement the U-Net-based algorithm and examine its generalizability by training on a dataset, which consists of randomly distributed disks, and testing on the alphabets (A-Z). Furthermore, we compare the Deep-HUG with the previous algorithm in terms of computation time, accuracy, and uniformity. It was found that the accuracy and uniformity of the Deep-HUG are somewhat lower than those of the previous algorithm whereas the computation time is 190 times faster than that of the previous algorithm, demonstrating that Deep-HUG has potential as a useful technique to rapidly generate an ultrasound hologram for various applications.