• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.1
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• pp.71-76
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• 2022

Since brightness is proportional to the operating current, a method of connecting several LEDs in series and driving with a constant current source is widely used for driving circuits of LED lights. Because several LEDs are connected in series, if some LEDs open due to a fault, the current path is broken and all other LEDs connected in series are turned off. In this paper, we designed a circuit to solve this problem by connecting a Zener diode having a breakdown voltage of about 0.4V higher than the LED operating voltage in parallel with each LED to create a current bypass in case of LED failure. Through simulations and experiments, it was confirmed that the current of the Zener diode hardly flows when the LED is operating normally, and that the Zener diode stably operates as a current bypass when the LED fails.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.436-442
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• 2022

In this paper, the performance of the selective combining according to the channel selection decision method of frequency diversity is evaluated in the underwater frequency selective channel. The underwater acoustic channel in the shallow sea has a complex multipath characteristic by combining various environmental factors such as boundary surface reflection and sound wave refraction according to the water temperature layer. In particular, frequency selectivity due to multipath causes energy fluctuation in a communication channel, which reduces SNR (Signal to Noise Ratio) and deteriorates communication performance. In this paper, we applied the frequency diversity technique using multiple channels to secure the communication performance according to the frequency selectivity by multipath. For each channel, 4-FSK (Frequency Shift Keying) and selective combining were applied, the performance was evaluated by applying the maximum value, average value, and majority decision of the signal in order to decide the demodulation channel selection of the selective combining.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.55-65
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• 2022

As Internet and mobile technology is developing, the educational environment is changing from the traditional passive way into an active one driven by learners. It is important to construct the proper learner's profile for personalized education where learners are able to study according to their learning levels. The existing studies on ICT-based personalized education have mostly focused on vocabulary and learning contents. In this paper, learning profile is constructed with not only vocabulary but grammar to define a learner's learning status in more detailed way. A proficiency metric is defined which shows how a learner is accustomed to the learning contents. The simulational results present the suggested approach is effective to the evaluation essay data with each learner's proficiency that is determined after pre-learning process. Additionally, the proposed analysis technique enables to provide statistics or graphs of the learner's status and necessary data for the learner's learning contents.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1904-1913
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• 2021

With the proliferation of smart phones and the development of IoT technology, it has become possible to collect personal data for public purposes. However, users are afraid of voluntarily providing their private data due to privacy issues. To remedy this problem, mainly three techniques have been studied: data disturbance, traditional encryption, and homomorphic encryption. In this work, we perform simulations to compare them in terms of accuracy, message length, and computation delay. Experiment results show that the data disturbance method is fast and inaccurate while the traditional encryption method is accurate and slow. Similar to traditional encryption algorithms, the homomorphic encryption algorithm is relatively effective in privacy preserving because it allows computing encrypted data without decryption, but it requires high computation costs as well. However, its main cost, arithmetic operations, can be processed in parallel. Also, data analysis using the homomorphic encryption needs to do decryption only once at any number of data.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.12
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• pp.971-980
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• 2021

Recently popularized drone technologies have revealed that low-cost small unmanned aerial vehicles(UAVs) can be a significant threat to prevailing power by operating in group or in swarms. Researchers in many countries have tried to utilize integrated swarm unmanned aerial system(SUAS) in the battlefield. Agency for Defense Development also identified four core technologies in developing SUAS: swarm control, swarm network, swarm information, and swarm collaboration, and the authors started researches on swarm control and network technologies in order to be able to operate vehicle platforms as the first stage. This paper introduces design and integration of SUAS consisting of small fixed-wing UAVs, swarm control and network algorithms, a ground control system, and a launcher, with which swarm control and network technologies have been verified by flight tests. 19 fixed-wing UAVs succeeded in swarm flight in the final flight test for the first time as a domestic research.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.89-97
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• 2023

In this paper, we propose factors that make log analysis difficult and design technique for detecting various objects embedded in the logs which helps in the subsequent analysis. In today's IT systems, logs have become a critical source data for many advanced AI analysis techniques. Although logs contain wealth of useful information, it is difficult to directly apply techniques since logs are semi-structured by nature. The factors that interfere with log analysis are various objects such as file path, identifiers, JSON documents, etc. We have designed a BERT-based object pattern recognition algorithm for these objects and performed object identification. Object pattern recognition algorithms are based on object definition, GROK pattern, and regular expression. We find that simple pattern matchings based on known patterns and regular expressions are ineffective. The results show significantly better accuracy than using only the patterns and regular expressions. In addition, in the case of the BERT model, the accuracy of classifying objects reached as high as 99%.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.42 no.2
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• pp.202-213
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• 1997

In order to find out a high potential black soybean lines, of which demand has been increasing in Korea, twenty eight local cultivars were evaluated on agronomic characteristics and the classification of the cultivars was made by the cluster analysis. Days to maturity and days to growing of black soybeans were widely ranged from 58 to 82 days, and 117 to 148 days, respectively. Late maturing group showed over 140 maturity days, and heavy 100 seed weight. There was shown low yield potential in late maturing group, and growing days was positively correlated with flowering days, days to maturity, 100-seed weight and stem length, respectively. From the principal component analysis upper two components composed 76.5％ cumulative eigen value to total. Nine varietal groups were identified in relations to their affinity of the black soybeans. Selected black soybeans, Namhae-2 and Hamyang-l were field-tested and those characteristics of many pod, small seed and high yield were found out to be suitable for sprouting.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.2
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• pp.175-182
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• 2023

Differential cryptanalysis is one of the analysis techniques for block ciphers, and uses the property that the output difference with respect to the input difference exists with a high probability. If random data and differential data can be distinguished, data complexity for differential cryptanalysis can be reduced. For this, many studies on deep learning-based neural distinguisher have been conducted. In this paper, a deep learning-based neural distinguisher for PIPO 64/128 is proposed. As a result of experiments with various input differences, the 3-round neural distinguisher for the differential characteristics for 0, 1, 3, and 5-rounds achieved accuracies of 0.71, 0.64, 0.62, and 0.64, respectively. This work allows distinguishing attacks for up to 8 rounds when used with the classical distinguisher. Therefore, scalability was achieved by finding a distinguisher that could handle the differential of each round. To improve performance, we plan to apply various neural network structures to construct an optimal neural network, and implement a neural distinguisher that can use related key differential or process multiple input differences simultaneously.

• Journal of the Korea Institute of Building Construction
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• v.23 no.3
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• pp.241-249
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• 2023

The objective of this research was to engineer a tile module that could efficiently curtail the incidence of tile defects during the construction phase. To assess the potential diminution in defect manifestation, we executed experiments centered on surface condition, the variation in mass before and after the freeze-thaw test, and adhesive strength. Our findings demonstrated that thermal contraction and expansion induced a relatively escalated frequency of defects in the underwater setting for the aluminum mesh, while the steel mesh saw a higher defect incidence in the air environment. Additionally, it was noted that the adhesive strength exhibited a trend towards augmentation as the mesh size dwindled. Collectively, these results suggest that the employment of smaller mesh sizes can foster improved adhesive strength, consequently diminishing tile defects. Further exploration and development of the tile module, informed by these insights, can substantially enhance the efficacy of the construction process.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.463-463
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• 2021

국내에서는 물관리 기술과 물관리 여건 고도화 등의 다양한 노력을 통하여 통합물관리(IWRM: Integrated Water Resources Management)에 기틀을 만들어 왔다. 그러나 우리나라는 수량, 수질, 수재해 분야로 구분하여 다수의 부처가 물관리 업무를 수행하고 있어 물관리 사업간 연계성 부족 및 사업의 중복으로 인한 예산 낭비와 물관리 어려움이 나타나고 있다. 기후변화로 나타나는 집중호우의 발생 빈도의 증가로 도시지역과 지류하천의 홍수, 녹조의 발생으로 피해가 증가 및 하천생태계의 변화 등으로 다양한 물관리 현안이 발생하고 있는 실정이다. 인간이 살아가는데 있어 물은 없어서는 안되는 중요한 자원이다. 지역별로 도시개발과 인구의 집중, 대규모 특정작물 재배 등으로 한정된 수자원을 개발하고 이용하는데 있어 물분쟁이 지속적으로 발생하고 있어 합리적인 해결방법이 필요하다. 이에 물관리의 기본이념 및 원칙을 마련하고 국가차원의 통합적인 물관리와 유역중심의 물관리를 위한 국가·유역물관리위원회 설치, 물관리에 필요한 기본적인 사항을 규정하여 지속 가능한 물순환 체계를 확립하여 국민의 삶의 질 향상에 이바지하고자 등을 물관리기본법을 입법하였다. 물관리기본법에서는 국가차원의 물관리기본계획과 유역차원의 유역물관리종합계획을 10년마다 수립하고 5년마다 타당성을 검토하도록 명시되어 있다. 본 연구에서는 금강유역을 대상으로 수립 중에 있는 유역계획의 목표와 전략에 대하여 발표하고자 한다.