• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.169-189
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• 2015

Detection of anomalous events from video streams is a challenging problem in many video surveillance applications. One such application that has received significant attention from the computer vision community is traffic video surveillance. In this paper, a Lossy Count based Sequential Temporal Pattern mining approach (LC-STP) is proposed for detecting spatio-temporal abnormal events (such as a traffic violation at junction) from sequences of video streams. The proposed approach relies mainly on spatial abstractions of each object, mining frequent temporal patterns in a sequence of video frames to form a regular temporal pattern. In order to detect each object in every frame, the input video is first pre-processed by applying Gaussian Mixture Models. After the detection of foreground objects, the tracking is carried out using block motion estimation by the three-step search method. The primitive events of the object are represented by assigning spatial and temporal symbols corresponding to their location and time information. These primitive events are analyzed to form a temporal pattern in a sequence of video frames, representing temporal relation between various object's primitive events. This is repeated for each window of sequences, and the support for temporal sequence is obtained based on LC-STP to discover regular patterns of normal events. Events deviating from these patterns are identified as anomalies. Unlike the traditional frequent item set mining methods, the proposed method generates maximal frequent patterns without candidate generation. Furthermore, experimental results show that the proposed method performs well and can detect video anomalies in real traffic video data.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.11
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• pp.130-137
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• 1992

This paper presents the word recognition method using a neural-fuzzy pattern matching, in order to make a proper speech pattern for a spectrum sequence and to improve a recognition rate. In this method, a frequency variation is reduced by generating binary spectrum patterns through associative memory using a neural network, and a time variation is decreased by measuring the simillarity using a fuzzy pattern matching. For this method using binary spectrum patterns and logic algebraic operations to measure the simillarity, memory capacity and computation requirements are far less than those of DTW using a conventional distortion measure. To show the validity of the recognition performance for this method, word recognition experiments are carried out using 28 DDD city names and compared with DTW and a fuzzy pattern matching. The results show that our presented method is more excellent in the recognition performance than the other methods.

• International Journal of Industrial Entomology and Biomaterials
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• v.23 no.1
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• pp.155-166
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• 2011

The leaf beetle, $Chrysolina$ $aurichalcea$ (Coleoptera: Chysomelidae), is a pest damaging plants of Compositae. In order to understand the genetic diversity and geographic variation we sequenced a portion of mitochondrial COI gene (658 bp) and complete nuclear internal transcribed spacer 2 (ITS2) of the species collected from seven Korean localities. A total of 17 haplotypes (CACOI01~CACOI17), with the maximum sequence divergence of 3.04% (20 bp) were obtained from COI gene sequence, whereas 16 sequence types (ITS2CA01~ITS2CA16), with the maximum sequence divergence of 2.013% (9 bp) were obtained from ITS2, indicating substantially larger sequence divergence in COI gene sequence. Phylogenetically, the COI gene provided two haplotype groups with a high nodal support (${\geq}87%$), whereas ITS2 provided only one sequence type group with a high nodal support (${\geq}92%$). The result of COI gene sequence may suggest the presence of historical biogeographic barriers that bolstered genetic subdivision in the species. Different grouping pattern between COI gene and ITS2 sequences were interpreted in terms of recent dispersal, reflected in the ITS2 sequence. Finding of unique haplotypes and sequence types only from Beakryeng-Islet population was interpreted as an intact remnant of ancient polymorphism. As more samples are analyzed using further hyper-variable marker, further fruitful inference on the geographic contour of the species might be available.

• Journal of Korean Medical classics
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• v.26 no.2
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• pp.47-59
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• 2013

Objective : Syndrome differentiation(辨證) has clinical importance in East Asian Traditional Medicine. There are several ways for Syndrome differentiation. However, Eight Principle Pattern Identification(八綱辨證) is the base of other Syndrome differentiations. Of the physicians focused on Eight Principle Patterns(八綱), I have researched for Eight Principle Pattern Identification concerning with Zhang Jie-Bin(張介賓), Cheng Guo-Peng(程國彭), and Jiang Han-Tun(江涵暾) in Ming(明) and Qing(淸.) Method : Applying to Eight Principle Pattern Identification, I have researched comparatively for 3 kinds for. First, Zhang Jie-Bin's Jingyuequanshu(景岳全書) that involves Yinyangpian(陰陽篇), Liubianbian(六變辨), Biaozhengpian(表證篇), Lizhengpian(裏證篇), Xushipian(虛實篇), and Hanrepian(寒熱篇), secondly, Cheng Guo-Peng's Yixuexinwu(醫學心悟) Hanrexushibiaoliyinyangbian(寒熱虛實表裏陰陽辨), at lastly Jiang Han-Tun's Bihuayijing(筆花醫鏡) Biaolixushihanreyinyangbian(表裏虛實寒熱辨). Results : All of sick cases can be explained totally by Eight Principle Patterns. Of Eight Principle Patterns, Yin(陰) and Yang(陽) include last Six Principle Patterns(六綱 : 表裏, 寒熱, 虛實). Six Principle Patterns can be divided normally by 6 pulses(六脈 : 浮沈 遲數 虛實). In all of pain cases, feeling comfortable(可按) or discomfortable(拒按) to palpation can be important foundation for distinguishing Xu(虛) from Shi(實). Physical constitution(體質) for Hanre Xushi(寒熱 虛實) and tongue-diagnosis(舌診) for Biaoli Hanre(表裏 寒熱) are used effectively. Related with tongue-diagnosis, tongue-coating(舌苔) for Biaoli and tongue status(舌質) for Hanre are used effectively. Symptoms should be divided following this sequence, Biaoli ${\rightarrow}$ Hanre ${\rightarrow}$ Xushi and lastly should be summarized of Yinyang. Conclusion : Diagnosing with Eight Principle Patterns, digestive function, urine, and feces should be checked at first. In addition, the pulse, tongue, physical constitution, and good or bad from palpation(觸診), these should be checked and give a result. And then the result can be an important evidence of syndrome differentiation. As a result, it would be the best to diagnosis that discriminating the sequence as Biaoli Hanre Xushi and summarizing with Yinyang.

• The KIPS Transactions:PartA
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• v.8A no.4
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• pp.509-516
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• 2001

As results of many genome projects, genomic sequences of many organisms are revealed. Various methods such as global alignment, local alignment are used to analyze the sequences of the organisms, and k -mer analysis is one of the methods for analyzing the genomic sequences. The k -mer analysis explores the frequencies of all k-mers or the symmetry of them where the k -mer is the sequenced base with the length of k. However, existing on-memory algorithms are not applicable to the k -mer analysis because a whole genomic sequence is usually a large text. Therefore, efficient data structures and algorithms are needed. String B-tree is a good data structure that supports external memory and fits into pattern matching. In this paper, we improve the string B-tree in order to efficiently apply the data structure to k -mer analysis, and the results of k -mer analysis for C. elegans and other 30 genomic sequences are shown. We present a visualization system which enables users to investigate the distribution and symmetry of the frequencies of all k -mers using CGR (Chaotic Game Representation). We also describe the method to find the signature which is the part of the sequence that is similar to the whole genomic sequence.

• Journal of the Korean Ceramic Society
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• v.38 no.2
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• pp.199-206
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• 2001

납석-뮬라이트의 상변이 과정을 주로 에너지여과 투과전자현미경을 이용하여 연구하였다. 납석은 (OH)를 읽고 pyrophyllite dehydroxylate로 된 후 뮬라이트와 크리스토발라이트로 상변이한다. Pyrophyllite dehydroxylate의 장주기 질서는 105$0^{\circ}C$에서도 유지된다. 생성 초기단계에서 뮬라이트는 pyrophyllite dehydroxylate에 대해 topotaxy를 보이며, elongation direction이 c*인 침상 결정으로 자라기 때문에 textured ED pattern을 나타낸다. Pyrophyllite dehydroxylate는 120$0^{\circ}C$에서 완전히 분해되어 뮬라이트의 결정 성장과 비정질 실리카로부터 크리스토발라이트의 생성이 이루어진다.

• Proceedings of the IEEK Conference
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• 2003.11b
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• pp.87-90
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• 2003

본 논문에서는 정현파를 이용한 spread-spectrum watermarking 에서 비가청성을 높이기 위한 방법과 효율적인 threshold 설정 방법을 제안한다. 제안하는 방법에서는 spread-spectrum 기법을 사용할 때 계산량이 많이 요구되는 심리음향모델 계산을 피하면서도 가청잡음을 줄이기 위한 방법을 제시한다. 또한 outlier 를 이용하여 워터마크 검출에서 적절한 threshold 설정방법을 제안한다.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.376-379
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• 2001

In this paper, I design the control chip that controls inner test sequence of Logic Tester to test chip. Logic tester has the thirteen inner instructions to control test sequence in test. And these instructions are saved in memory with test pattern data. Control chip generates address and control signal such as read, write signal of memory. Before testing, necessary data such as start address, end address, etc. are written to inner register of control chip. When test started, control chip receives the instruction in start address and executes, and generates address and control signals to access tester' inner memory. So whole test sequence is controlled by making the address and control signal in tester's inner memory. Control chip designs instruction's execution blocks, respectively. So if inner instruction is added from now on, a revision is easy. The control chip will be made using FPGA of Xilinx Co. in future.

• The Journal of the Korea Contents Association
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• v.8 no.5
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• pp.44-51
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• 2008

Pattern matching and pattern searching in time series data have been active issues in a number of disciplines. This paper suggests a novel pattern matching technology which can be used in the field of stock market analysis as well as in forecasting stock market trend. First, we define conceptual patterns, and extract data forming each pattern from given time series, and then generate learning model using Hidden Markov Model. The results show that the context-based pattern matching makes the matching more accountable and the method would be effectively used in real world applications. This is because the pattern for new data sequence carries not only the matching itself but also a given context in which the data implies.

• ETRI Journal
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• v.43 no.3
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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.