• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.15 no.6
• /
• pp.8-14
• /
• 2006

The object transport system is used in many industry field such as the conveyor belt, which transports huge goods in container harbor, the magnetic levitation system, and the indexing system which transports precision components such as semiconductor and optical components. In conventional transport system, the magnetic field may damage semiconductor and the contact force may scratch on the optical lens. So ultrasonic wave transport system has been proposed to replace the previous transport system. In this paper, the good transport condition of optical lens is obtained according to the flexural beam shapes. The working frequency and transport speed are measured and the vibration characteristics of the flexural beams are investigated by Laser Scanning Vibrometer.

• Journal of Internet Computing and Services
• /
• v.3 no.2
• /
• pp.69-77
• /
• 2002

Recently, Digital video is one of the important information media delivered on the Internet and playing an increasingly important role in multimedia. This paper proposes a Video Browsing Service(VBS) that provides both the video content retrieval and the video browsing by the real-time user interface on Web, For the scene segmentation and key frame extraction of video sequence, we proposes an efficient scene change detection method that combines the RGB color histogram with the $x^2$(Chi Square) histogram. Resulting key frames are linked by both physical and logical indexing, This system involves the video editing and retrieval function of a VCR's, Three elements that are the date, the field and the subject are used for video browsing. A Video Browsing Service is implemented with MySQL, PHP and JMF under Apache Web Server.

• Journal of the Semiconductor & Display Technology
• /
• v.13 no.2
• /
• pp.45-52
• /
• 2014

This paper proposes an efficient photo retrieval system that automatically indexes for searching of relevant images, using a combination of geo-coded information, direction/location of image capture device and content-based visual features. A photo image is labeled with its GPS (Global Positioning System) coordinates and direction of the camera view at the moment of capture, and the label leads to generate a geo-spatial index with three core elements of latitude, longitude and viewing direction. Then, content-based visual features are extracted and combined with the geo-spatial information, for indexing and retrieving the photo images. For user's querying process, the proposed method adopts two steps as a progressive approach, filtering the relevant subset prior to use a content-based ranking function. To evaluate the performance of the proposed scheme, we assess the simulation performance in terms of average precision and F-score, using a natural photo collection. Comparing the proposed approach to retrieve using only visual features, an improvement of 20.8% was observed. The experimental results show that the proposed method exhibited a significant enhancement of around 7.2% in retrieval effectiveness, compared to previous work. These results reveal that a combination of context and content analysis is markedly more efficient and meaningful that using only visual feature for image search.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.13 no.10
• /
• pp.2140-2146
• /
• 2009

Since tags do not have location informations, the identifiers of tags which are symbolic data are used as the location informations. Therefore, it is difficult to define the proxmity between two trajectories of tags and inefficient to process the user queries for tags. In this paper, we define the perceptual space to model the location of a tag and propose the proximity of the perceptual spaces. The proximity of the perceptual spaces is composed of the static proximity and dynamic proximity. Using the proximity of the perceptual spaces, it is possible to measure the proximity between two trajectories of tags and build the efficient indexes for tag trajectories. We evaluated the performance of the proposed proximity function for tag trajectories on the IR-tree and the $R^*$-tree.

• Proceedings of the KAIS Fall Conference
• /
• 2003.11a
• /
• pp.178-184
• /
• 2003

Case-based reasoning (CBR) often shows significant promise for improving effectiveness of complex and unstructured decision making. Consequently, it has been applied to various problem-solving areas including manufacturing, finance and marketing. However, the design of appropriate case indexing and retrieval mechanisms to improve the performance of CBR is still challenging issue. Most of previous studies to improve the effectiveness for CBR have focused on the similarity function or optimization of case features and their weights. However, according to some of prior researches, finding the optimal k parameter for k-nearest neighbor (k-NN) is also crucial to improve the performance of CBR system. Nonetheless, there have been few attempts which have tried to optimize the number of neighbors, especially using artificial intelligence (AI) techniques. In this study, we introduce a genetic algorithm (GA) to optimize the number of neighbors to combine. This study applies the new model to the real-world case provided by an online shopping mall in Korea. Experimental results show that a GA-optimized k-NN approach outperforms other AI techniques for purchasing behavior forecasting.

• Journal of Integrative Natural Science
• /
• v.2 no.4
• /
• pp.243-251
• /
• 2009

This paper surveys some researches to accomplish on bioinformatics. These researches wish to propose a database architecture combining a general view of bioinformatics data as a graph of data objects and data relationships, with the efficiency and robustness of data management and query provided by indexing and generic programming techniques. Here, these invert the role of the index, and make it a first-class citizen in the query language. It is possible to do this in a structured way, allowing users to mention indexes explicitly without yielding to a procedural query model, by converting functional relations into explicit functions. In the limit, the database becomes a graph, in which the edges are these indexes. Function composition can be specified either explicitly or implicitly as path queries. The net effect of the inversion is to convert the database into a hyperdatabase: a database of databases, connected by indexes or functions. The inversion approach was motivated by their work in biological databases, for which hyperdatabases are a good model. The need for a good model has slowed progress in bioinformatics.

• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 2017.04a
• /
• pp.166-166
• /
• 2017

모돈의 건강 상태를 정량 지수화 하기 위한 연구를 수행 중이다. 지제이상, 섭식 불량, 수면 패턴 등의 운동 특성 분석을 위하여 복수의 초음파 센서를 이용하였다. 시계열 계측 신호를 분석하여 정량 지수화를 수행하는 과정에서 주파수 도메인 분석을 시도하였다. 이 과정에서 주파수 도메인의 분해능에 따른 편차 극복을 위한 비선형 모델링을 수행하였다. 또한 인접한 시계열 데이터 구간 간의 상관성 분석이 가능하면 대용량 데이터의 실시간 처리로 인한 지연 시간 극복 및 기대되는 예후에 대한 조기 진단이 가능할 것이다. 본 연구에서는 구글에서 제공하는 Tensorflow와 NVIDIA에서 제공하는 CUDA 엔진을 동시 적용한 심층 학습 시스템을 이용하였다. 전 처리를 위하여 주파수 분해능 (2분, 3분, 5분, 7분, 11분, 13분, 17분, 19분)에 따른 데이터 집합을 1단계로 두고, 상위 10 순위 안에 드는 파워 스펙트럼 밀도의 크기를 2단계로 하여, 총 2~10개의 입력 노드를 순차적으로 선정하였고, 동일한 방식으로 인접한 시계열의 파워 스펙터럼 밀도를 순위를 변화시켜 지정하였다. 대표적인 심층학습 모델인 Softmax regression with a multilayer convolutional network를 이용하여 Recursive feature selection 경우의 수를 $8{\times}9{\times}9$로 총 648 가지 선정하고, Epoch는 10,000회로 지정하였다. Calibration 모델링의 경우 Cost function이 10% 이하인 경우 해당 경우의 학습을 중단하였으며, 모델 간 상호 교차 검증을 수행하기 위하여 $_8C_2{\times}_8C_2{\times}_8C_2$ 경우의 수에 대한 Verification test를 수행하였다. Calibration 과정 상 모든 경우에 대하여 10% 이하의 Cost function 값을 보였으나, 검증 테스트 과정에서 모든 경우에 대하여 $r^2$ < 0.5 인 결정 계수 값이 나타났다. 단적으로 심층학습 모델의 과도한 적합(Over fitting) 방식의 한계를 보인 것이라 판단할 수 있다. 적합한 Feature selection 및 심층 학습 모델에 대한 지속적이고 추가적인 고려를 통해 과도적합을 해소함과 동시에 실효적이고 활용 가능한 Classification을 위한 입, 출력 노드 단의 전후 Indexing, Quantization에 대한 고려가 필요할 것이다. 이를 통해 모돈 생체 정보 정량화를 위한 지능형 현장 진단 기술 연구를 지속할 것이다.

• Journal of KIISE:Databases
• /
• v.33 no.3
• /
• pp.261-270
• /
• 2006

Positional data of moving objects can be regularly sampled in order to minimize the cost of data collection in LBS. Since position data which are regularly sampled cannot include the changes of position occurred between sampling periods, sampled position data differ from the data predicted by a time parameterized linear function. Uncertain position data caused by these differences make the accuracy of the range queries for present positions diminish in the TPR tree. In this paper, we propose the uncertainty region to handle the range queries for uncertain position data. The uncertainty region is defined by the position data predicted by the time parameterized linear function and the estimated uncertainty error. We also present the weighted recent uncertainty error policy and the kalman filter policy to estimate the uncertainty error. For performance test, the query processor based by the uncertainty region is implemented in the TPR tree. The experiments show that the Proposed query processing methods are more accurate than the existing method by 15%.

• The KIPS Transactions:PartD
• /
• v.13D no.3 s.106
• /
• pp.357-368
• /
• 2006

This paper discusses the way of processing time-series subsequence matching under time warping. Time warping enables finding sequences with similar patterns even when they are of different lengths. The prefix-querying method is the first index-based approach that performs time-series subsequence matching under time warping without false dismissals. This method employs the $L_{\infty}$ as a base distance function for allowing users to issue queries conveniently. In this paper, we extend the prefix-querying method for absorbing $L_1$, which is the most-widely used as a base distance function in time-series subsequence matching under time warping, instead of $L_{\infty}$. We also formally prove that the proposed method does not incur any false dismissals in the subsequence matching. To show the superiority of our method, we conduct performance evaluation via a variety of experiments. The results reveal that our method achieves significant performance improvement in orders of magnitude compared with previous methods.

• The KIPS Transactions:PartD
• /
• v.9D no.2
• /
• pp.173-184
• /
• 2002

This paper discuss an index-based subsequence matching that supports time warping in large sequence databases. Time warping enables finding sequences with similar patterns even when they are of different lengths. In earlier work, Kim et al. suggested an efficient method for whole matching under time warping. This method constructs a multidimensional index on a set of feature vectors, which are invariant to time warping, from data sequences. For filtering at feature space, it also applies a lower-bound function, which consistently underestimates the time warping distance as well as satisfies the triangular inequality. In this paper, we incorporate the prefix-querying approach based on sliding windows into the earlier approach. For indexing, we extract a feature vector from every subsequence inside a sliding window and construct a multidimensional index using a feature vector as indexing attributes. For query processing, we perform a series of index searches using the feature vectors of qualifying query prefixes. Our approach provides effective and scalable subsequence matching even with a large volume of a database. We also prove that our approach does not incur false dismissal. To verify the superiority of our approach, we perform extensive experiments. The results reveal that our approach achieves significant speedup with real-world S&P 500 stock data and with very large synthetic data.