• Journal of the Korea Society of Computer and Information
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• v.16 no.1
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• pp.31-38
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• 2011

A RAM-based Neural Net is a weightless neural network based on binary neural network. 3-D neural network using this paper is binary neural network with multiful information bits and store counts of training. Recognition method by MRD technique is based on the supervised learning. Therefore neural network by itself can not distinguish between the categories and well-separated categories of training data can achieve only through the performance. In this paper, unsupervised learning algorithm is proposed which is trained existing 3-D neural network without distinction of data, to distinguish between categories depending on the only input training patterns. The training data for proposed unsupervised learning provided by the NIST handwritten digits of MNIST which is consist of 0 to 9 multi-pattern, a randomly materials are used as training patterns. Through experiments, neural network is to determine the number of discriminator which each have an idea of the handwritten digits that can be interpreted.

• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.127-136
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• 2009

This paper proposes an on-line mining algorithm of moving trajectory patterns in RFID data streams considering changing characteristics over time and constraints of single-pass data scan. Since RFID, sensor, and mobile network technology have been rapidly developed, many researchers have been recently focused on the study of real-time data gathering from real-world and mining the useful patterns from them. Previous researches for sequential patterns or moving trajectory patterns based on stream data have an extremely time-consum ing problem because of multi-pass database scan and tree traversal, and they also did not consider the time-changing characteristics of stream data. The proposed method preserves the sequential strength of 2-lengths frequent patterns in binary relationship table using the time-evolving graph to exactly reflect changes of RFID data stream from time to time. In addition, in order to solve the problem of the repetitive data scans, the proposed algorithm infers candidate k-lengths moving trajectory patterns beforehand at a time point t, and then extracts the patterns after screening the candidate patterns by only one-pass at a time point t+1. Through the experiment, the proposed method shows the superior performance in respect of time and space complexity than the Apriori-like method according as the reduction ratio of candidate sets is about 7 percent.

• The Journal of Korean Medicine
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• v.25 no.4
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• pp.180-187
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• 2004

Objective : This study was undertaken for discovering the characteristics of sleep in ordinary symptoms based on the Sasang Constitution. The result of this study could be helpful to understand and to identify patients such as Taeumin, Soyangin Soeumin or Taeyangin. Methods : There were 1,229 patients (529 men), who answered the questionnaire about their ordinary sleeping patterns. They were diagnosed, including their clinical Sasang Constitution, by the Sasang Constitution specialist at Bundang Oriental Hospital of Dongguk University. By applying the multinomial and binary logistic regression analysis to those collected materials, we can measure the characteristics and the influence of ordinary sleeping patterns to the dependent variable (Sasang Constitution). Results : In order of the item's influence that had decided one's constitution, between Taeumin and Soeumin, Taeumin snored frequently or well more than Soeumin, Soeumin had more dreams and more sleeping times than Taeumin, and Taeumin struggled frequently or well more than Soeumin. Between Soyangin and Soeumin, Soeumin dreams more frequently than Soyangin, Soyangin snored frequently or well more than Soeumin, and Soeumin has more sleeping times than Taeumin. Between Taeumin and Soyangin, Taeumin snored frequently or well more than Soyangin. Between Taeyangin and a group of the other constitutions, Taeyangin felt unwell after sleeping more than the other constitutions, the other constitutions awaked frequently more than Taeyangin during sleeping. Conclusion : This study will be used for identifying patients as Taeumin, Soyangin, Soeumin or Taeyangin by contrast with each other.

• Journal of Advanced Navigation Technology
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• v.11 no.1
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• pp.59-63
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• 2007

In this paper, an image segmentation algorithm is described to extract both the contour line and the inner grid patterns of body in case of ambiguous environment. The binary method using a threshold is used to extract image boundary. To reduce image noise, the $3{\times}3$ hybrid high pass filter adjusted for applying 3D information extraction of complicated shape object is proposed. This hybrid high pass filter algorithm can be applied to extract complicated shape object such as 3D body shape, CAD system, and factory automation since the processing time for image denoising is shorter than the conventional methods.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.2
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• pp.168-177
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• 1996

In this paper, we propose an on-line recognition system of chinese characters using an adaptive resonance theory-1(ART-1) neural network. Strokes, primitive components of chinese characters are usually warped into a cursive form and classifying them is very difficult. To deal with such cursive strokes, we use an ART-1 neural network that has the following advantages: (1) it automatically assembles similar patterns together to form classes in a self-organized manner: (2) it directly accesses the recognition codes corresponding to binary input patterns after self-stabilizing; (3) it doesn't tends to get trapped in local minima, or globally incorrect solutions. A database for character recognition also dynamically constructed with generalized character lists, and a new character can be included simply by adding a new sequence to the list. Character recognition is achieved by traversing the chinese datbase with a sequence of recognized strokes and positional relations between the strokes. To verify the performance of the system. We tested it for 1800 daily-used basic chinese second per character. This results suggest that the proposed system is pertinent to be put into practical use.

• Asian-Australasian Journal of Animal Sciences
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• v.18 no.8
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• pp.1194-1198
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• 2005

A computer vision system was designed and validated to recognize an individual Holstein cattle by processing images of their body patterns. This system involves image capture, image pre-processing, algorithm processing, and an artificial neural network recognition algorithm. Optimum management of individuals is one of the most important factors in keeping cattle healthy and productive. In this study, an image-processing system was used to recognize individual Holstein cattle by identifying the body-pattern images captured by a charge-coupled device (CCD). A recognition system was developed and applied to acquire images of 49 cattles. The pixel values of the body images were transformed into input data comprising binary signals for the neural network. Images of the 49 cattle were analyzed to learn input layer elements, and ten cattles were used to verify the output layer elements in the neural network by using an individual recognition program. The system proved to be reliable for the individual recognition of cattles in natural light.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.5
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• pp.871-876
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• 2006

In this thesis, to accurately measure 3D face information using the spatial encoding patterns, the new algorithm to segment the pattern images from initial face pattern image is proposed. If the obtained images is non-homogeneous texture and ambiguous boundary pattern, the pattern segmentation is very difficult. Furthermore. the non-encoded areas by accumulated error are occurred. In this thesis, the FCM(fuzzy c-means) clustering method is proposed to enhance the robust encoding and segmentation rate under non-homogeneous texture and ambiguous boundary pattern. The initial parameters for experiment such as clustering class number, maximum repetition number, and error tolerance are set with 2, 100, 0.0001 respectively. The proposed pattern segmentation method increased 8-20% segmentation rate with conventional binary segmentation methods.

• Journal of Bio-Environment Control
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• v.1 no.1
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• pp.37-51
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• 1992

Quantizing and extracting visual features of mushroom(Lentinus edodes L.) are crucial to the sorting and grading automation, the growth state measurement, and the dried performance indexing. A computer image processing system was utilized for the extraction and measurement of visual features of front and back sides of the mushroom. The image processing system is composed of the IBM PC compatible 386DK, ITEX PCVISION Plus frame grabber, B/W CCD camera, VGA color graphic monitor, and image output RGB monitor. In this paper, an automatic thresholding algorithm was developed to yield the segmented binary image representing skin states of the front and back sides. An eight directional Freeman's chain coding was modified to solve the edge disconnectivity by gradually expanding the mask size of 3$\times$3 to 9$\times$9. A real scaled geometric quantity of the object was directly extracted from the 8-directional chain element. The external shape of the mushroom was analyzed and converted to the quantitative feature patterns. Efficient algorithms for the extraction of the selected feature patterns and the recognition of the front and back side were developed. The developed algorithms were coded in a menu driven way using MS_C language Ver.6.0, PC VISION PLUS library fuctions, and VGA graphic functions.

• The KIPS Transactions:PartB
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• v.19B no.2
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• pp.135-148
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• 2012

This paper proposes a model for recognizing sentential paraphrases through Predicate-Argument Tuple (PAT)-based approximate alignment between two texts. We cast the paraphrase recognition problem as a binary classification by defining and applying various alignment features which could effectively express the semantic relatedness between two sentences. Experiment confirmed the potential of our approach and error analysis revealed various paraphrase patterns not being solved by our system, which can help us devise methods for further performance improvement.

• International Journal of Aeronautical and Space Sciences
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• v.7 no.1
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• pp.106-117
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• 2006

The active vibration control of composite shell structure has been performed with the optimized sensor/actuator system. For the design of sensor/actuator system, a method based on finite element technique is developed. The nine-node Mindlin shell element has been used for modeling the integrated system of laminated composite shell with PVDF sensor/actuator. The distributed selective modal sensor/actuator system is established to prevent the effect of spillover. Electrode patterns and lamination angles of sensor/actuator are optimized using genetic algorithm. Continuous electrode patterns are discretized according to finite element mesh, and orientation angle is encoded into discrete values using binary string. Sensor is designed to minimize the observation spillover, and actuator is designed to minimize the system energy of the control modes under a given initial condition. Modal sensor/actuator for the first and the second mode vibration control of singly curved cantilevered composite shell structure are designed with the method developed on the finite element method and optimization. For verification, the experimental test of the active vibration control is performed for the composite shell structure. Discrete LQG method is used as a control law.