• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 하계종합학술대회 논문집(3)
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• pp.117-120
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• 2000

This study is to construct a general purpose library for a computer vision system development. The library includes many core algorithms required for computer vision systems such as image Processing algorithms, feature extracting methods, neural networks and etc. We have experimented the efficiency of the library by building a vehicle plate recognition system and the overall time and effort in development could be reduced to a certain extent.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1617-1622
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• 1991

Plane sweep is a general method in computational geometry. There are many efficient theoretical algorithms designed using plane sweep technique. However, their practical implementations are still suffering from the topological inconsistencies resulting from the numerical errors in geometric computations with finite-precision arithmetic. In this paper, we suggest new implementation techniques for the plane sweep algorithms to resolve the topological inconsistencies and construct the planar object boundaries from given input curve segments.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2011년도 제42회 하계학술대회
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• pp.1027-1028
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• 2011

In this paper, three reliability calculation algorithms: Monte Carlo Simulation (MCS), Reliability Index Approach (RIA), and Sensitivity-based Monte Carlo Simulation (SMCS) are studied. Their efficiency and accuracy are validated by analytic test functions.

• Journal of Information Processing Systems
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• 제17권2호
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• pp.213-226
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• 2021

Given that most of the link prediction algorithms for signed social networks can only complete sign prediction, a novel algorithm is proposed aiming to achieve both link prediction and sign prediction in signed networks. Based on the structural balance theory, the local link tightness and global link tightness are defined respectively by using the structural information of paths with the step size of 2 and 3 between the two nodes. Then the total similarity of the node pair can be obtained by combining them. Its absolute value measures the possibility of the two nodes to establish a link, and its sign is the sign prediction result of the predicted link. The effectiveness and correctness of the proposed algorithm are verified on six typical datasets. Comparison and analysis are also carried out with the classical prediction algorithms in signed networks such as CN-Predict, ICN-Predict, and PSNBS (prediction in signed networks based on balance and similarity) using the evaluation indexes like area under the curve (AUC), Precision, improved AUC', improved Accuracy', and so on. Results show that the proposed algorithm achieves good performance in both link prediction and sign prediction, and its accuracy is higher than other algorithms. Moreover, it can achieve a good balance between prediction accuracy and computational complexity.

• Journal of Information Processing Systems
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• 제16권5호
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• pp.1196-1213
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• 2020

There is a growing interest in the development of smart environments through predicting the behaviors of inhabitants of smart spaces in the recent past. Various smart services are deployed in modern smart cities to facilitate residents and city administration. Prediction algorithms are broadly used in the smart fields in order to well equip the smart services for the future demands. Hence, an accurate prediction technology plays a vital role in the smart services. In this paper, we take out an extensive survey of smart spaces such as smart homes, smart farms and smart cars and smart applications such as smart health and smart energy. Our extensive survey is based on more than 400 articles and the final list of research studies included in this survey consist of 134 research papers selected using Google Scholar database for period of 2008 to 2018. In this survey, we highlight the role of prediction algorithms in each sub-domain of smart Internet of Things (IoT) environments. We also discuss the main algorithms which play pivotal role in a particular IoT subfield and effectiveness of these algorithms. The conducted survey provides an efficient way to analyze and have a quick understanding of state of the art work in the targeted domain. To the best of our knowledge, this is the very first survey paper on main categories of prediction algorithms covering statistical, heuristic and hybrid approaches for smart environments.

• ETRI Journal
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• 제43권3호
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• pp.483-510
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• 2021

In computational biology, desired patterns are searched in large text databases, and an exact match is preferable. Classical benchmark algorithms obtain competent solutions for pattern matching in O (N) time, whereas quantum algorithm design is based on Grover's method, which completes the search in $O(\sqrt{N})$ time. This paper briefly explains existing quantum algorithms and defines their processing limitations. Our initial work overcomes existing algorithmic constraints by proposing the quantum-based combined exact (QBCE) algorithm for the pattern-matching problem to process exact patterns. Next, quantum random access memory (QRAM) processing is discussed, and based on it, we propose the QRAM processing-based exact (QPBE) pattern-matching algorithm. We show that to find all t occurrences of a pattern, the best case time complexities of the QBCE and QPBE algorithms are $O(\sqrt{t})$ and $O(\sqrt{N})$, and the exceptional worst case is bounded by O (t) and O (N). Thus, the proposed quantum algorithms achieve computational speedup. Our work is proved mathematically and validated with simulation, and complexity analysis demonstrates that our quantum algorithms are better than existing pattern-matching methods.

• 산업경영시스템학회지
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• 제47권1호
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• pp.9-19
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• 2024

Deep learning-based computer vision anomaly detection algorithms are widely utilized in various fields. Especially in the manufacturing industry, the difficulty in collecting abnormal data compared to normal data, and the challenge of defining all potential abnormalities in advance, have led to an increasing demand for unsupervised learning methods that rely on normal data. In this study, we conducted a comparative analysis of deep learning-based unsupervised learning algorithms that define and detect abnormalities that can occur when transparent contact lenses are immersed in liquid solution. We validated and applied the unsupervised learning algorithms used in this study to the existing anomaly detection benchmark dataset, MvTecAD. The existing anomaly detection benchmark dataset primarily consists of solid objects, whereas in our study, we compared unsupervised learning-based algorithms in experiments judging the shape and presence of lenses submerged in liquid. Among the algorithms analyzed, EfficientAD showed an AUROC and F1-score of 0.97 in image-level tests. However, the F1-score decreased to 0.18 in pixel-level tests, making it challenging to determine the locations where abnormalities occurred. Despite this, EfficientAD demonstrated excellent performance in image-level tests classifying normal and abnormal instances, suggesting that with the collection and training of large-scale data in real industrial settings, it is expected to exhibit even better performance.

• ETRI Journal
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• 제37권1호
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• pp.43-53
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• 2015

In this paper, a selective coefficient updating (SCU) approach at each branch of the per-tone equalization (PTEQ) structure has been applied for insufficient cyclic prefix (CP) length. Because of the high number of adaptive filters and their complex adaption process in the PTEQ structure, SCU has been proposed. Using this method leads to a reduction in the computational complexity, while the performance remains almost unchanged. Moreover, the use of set-membership filtering with variable step size is proposed for a sufficient CP case to increase convergence speed and decrease the average number of calculations. Simulation results show that despite the aforementioned algorithms having similar performance in comparison with conventional algorithms, they are able to reduce the number of calculations necessary. In addition, compensation of both the channel effect and the transmitter/receiver in-phase/quadrature-phase imbalances are achievable by these algorithms.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1987년도 전기.전자공학 학술대회 논문집(II)
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• pp.1195-1198
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• 1987

This paper develops algorithms of element generation, addition, multiplication and inversion based on GF($2^m$). Since these algorithms are implemented by general purpose computer, these are more efficient than the conventional algorithms(Table Lookup, Euclid's Algorithm) in each operation. It is also implied that they can be applied to not only the normally defined elements but the arbitrarily defined ones for constructing multi-valued logic function.

• ETRI Journal
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• 제27권2호
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• pp.195-205
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• 2005

In this paper, an error-free Butcher algorithm is introduced to study the singular system of a linear electrical circuit for time invariant and time varying cases. The discrete solutions obtained using Runge-Kutta (RK)-Butcher algorithms are compared with the exact solutions of the electrical circuit problem and are found to be very accurate. Stability regions for the single term Walsh series (STWS) method and the RK-Butcher algorithm are presented. Error graphs for inductor currents and capacitor voltages are presented in a graphical form to show the efficiency of the RK-Butcher algorithm. This RK-Butcher algorithm can be easily implemented in a digital computer for any singular system of electrical circuits.