• Journal of the Korean Society of Manufacturing Process Engineers
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• v.9 no.6
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• pp.7-15
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• 2010

Recently, with the high performance and efficiency of machine, there have been required the multi-functions in various machine parts, such as the heat resistance, the abrasion resistance and the stress resistance as well as the strength. Fatigue crack growth tests were carried out to investigate the fatigue characteristics of high carbon steel (SM53C) experienced by high-frequency induction treatment. The Cam nose part of the Automobile's Cam shaft is strongly bumped with rocker arm or valve-lift. Therefore abnormal wear such as unfair wear and early wear occur in the surface. This abnormal wear causes a defect that bad timing open and close actions of the engine valve happen in the combustion chamber so the fuel gas will be combustion imperfect. Therefore, the cam shaft demands high hardness and wear resistance. In this study, high frequency heat treatment has been accomplished while wear test for material SM53C.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.947-951
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• 1997

Recently, the necessity of the detection of abnormal machining process is being emphasized in order to improve the machining accuracy and reduce the cost in unmanned operating system. The vibration by chatter generated in cutting processes within machine tools is a relative motion between tools and workpieces. So, if the chatter occurs, the surface roughness and accuracy of workpieces will be deteriorate and it leads to the rapid wear of tools. The author intended to use the I /sab/RMS (current of root mean square) of current sigals and the movimg C.V. (coefficient of variation) of each phase for the detection method of chatter.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.11
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• pp.47-54
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• 2009

Spin coaters are the essential instruments in micro-fabrication processes, which apply uniform thin films to flat substrates. In this research, a spin coater diagnosis system is developed to detect the abnormal operation of TFT-LCD process in real time. To facilitate the real-time data acquisition and analysis, the circular-buffered continuous data transfer and the short-time Fourier transform are applied to the fault diagnosis system. To determine whether the system condition is normal or not, a steady-state detection algorithm and a frequency spectrum comparison algorithm using confidence interval are newly devised. Since abnormal condition of a spin coater is rarely encountered, algorithm is tested on a CD-ROM drive and the developed program is verified by a function generator. Actual threshold values for the fault detection are tuned in a spin coater in process.

• Journal of Korean Society for Quality Management
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• v.29 no.4
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• pp.38-53
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• 2001

In resolving industrial quality control problems, a vector of multiple quality characteristic variables is involved rather than a single variable. However, it is not guaranteed that a multivariate control chart based on statistical methods can monitor abnormal signal in case that small changes of relationship between each variables causes abnormal production process. Hence a quality control system for real-time monitoring of the multi-dimensional quality characteristic vector under a multivariate normal process is needed to enhance tile production system quality performance. A pattern analysis approach based on self-organizing map (SOM), an unsupervised learning technique of neural network, is applied to the design of such a quality control system. In this study we present a new material quality control system based on pattern analysis approach and illustrate the effectiveness of proposed system using actual electronic company material data.

• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.1286-1288
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• 2000

Commutation failure can be considered as the severest abnormal operation of thyristor HVDC converter. During the failure, power conversion from DC to AC is stopped until the AC voltage get recovered. The process of thyristor converter is subscribed at normal and abnormal state, respectively. The detection and the protection for Cheju HVDC are explained by computer simulation results.

• Journal of Information Processing Systems
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• v.16 no.3
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• pp.612-628
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• 2020

This paper presents a new approach for detecting abnormal behaviors in complex surveillance scenes where anomalies are subtle and difficult to distinguish due to the intricate correlations among multiple objects' behaviors. Specifically, a cascaded probabilistic topic model was put forward for learning the spatial context of local behavior and the temporal context of global behavior in two different stages. In the first stage of topic modeling, unlike the existing approaches using either optical flows or complete trajectories, spatio-temporal correlations between the trajectory fragments in video clips were modeled by the latent Dirichlet allocation (LDA) topic model based on Markov random fields to obtain the spatial context of local behavior in each video clip. The local behavior topic categories were then obtained by exploiting the spectral clustering algorithm. Based on the construction of a dictionary through the process of local behavior topic clustering, the second phase of the LDA topic model learns the correlations of global behaviors and temporal context. In particular, an abnormal behavior recognition method was developed based on the learned spatio-temporal context of behaviors. The specific identification method adopts a top-down strategy and consists of two stages: anomaly recognition of video clip and anomalous behavior recognition within each video clip. Evaluation was performed using the validity of spatio-temporal context learning for local behavior topics and abnormal behavior recognition. Furthermore, the performance of the proposed approach in abnormal behavior recognition improved effectively and significantly in complex surveillance scenes.

• Nuclear Medicine and Molecular Imaging
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• v.42 no.1
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• pp.79-80
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• 2008

Including malignancy, various disease can show abnormal uptake in bone marrow. We report a case of non-specific inflammatory FDG uptake in bone marrow mimicking malignancy. A 35-year old woman with fever of unknown origin (FUO) underwent $^{18}F$-FDG PET/CT to find out fever $^{18}F$-FDG and unknown malignancy. $^{18}F$-FDG was injected and imaged 1hr after injection with Discovery ST (GE, USA), $^{18}F$-FDG PET/CT whole body image showed abnormal uptake in lower extremities (Fig. 1). MRI and biopsy was also done in the sites of abnormal uptake. PET and MRI suspect malignancy (Fig. 2, 3), but biopsy result was non-specific inflammatory process (Fig. 4). The patient was improved her clinical condition after antibiotics therapy.

• Biomedical Science Letters
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• v.24 no.2
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• pp.64-75
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• 2018

CCN3 (also known as NOV, Nephroblastoma overexpressed) proteins are involved in various pathologies during different developmental stages. We have previously shown that intracellular levels and normal extracellular secretion of CCN3 are important for neuronal differentiation. Furthermore, we demonstrated that a single amino acid in the CCN3 TSP-1 domain is important for extracellular secretion and that palmitoylation of CCN3 is required in this process. However, the effect of abnormal CCN3 accumulation on cells remains to be studied. Here, we found mutations in the TSP-1 domain of CCN3 that led to intracellular accumulation and abnormal aggregation of CCN3. It was observed that this mutation resulted in a phenomenon similar to neurodegeneration when overexpressed in the developing mouse cortex. This mutation also confirmed the activation of apoptotic gene expression in Neuro2a cells. In addition, we confirmed the in vivo transcriptional changes induced by this mutation using microarray analysis. We observed a significant increase in the expression of Anp32a, an apoptosis-related gene. Collectively, these results indicate that a single mutation in CCN3 can lead to abnormal cell death if it shows intracellular accumulation and abnormal aggregation.

• Proceedings of the KOSOMBE Conference
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• v.1990 no.11
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• pp.105-109
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• 1990

Nowadays, the amounts of cells and tissues in the field of pathology is being increased rapidly due to the increasing number of peoples and growing medical well fares. But, unfortunately the number of professional pathologist is not enough to deal with the great inspection amounts and there are several difficult problems in processing the inspections with naked eyes. To process a lot of inspections rapidly and solve difficults in inspections, the need of the inspection automation come appears. With this study the primarily cells and tissues can be sorted using image processing technics. As a result, the normal cells are separated from the abnormal cells and the abnormal cells can be distinguished through screening of abnormal cell's image with reference data to judge abnormal cells. Owing to this study the number of inspections which the pathologists should examine will be decreased and the time for inspection will be shortened.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.5
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• pp.25-30
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• 2011

This paper present a method for abnormal traffic behavior, or trajectory, detection in static traffic surveillance camera with user-defined trajectories. The method computes the abnormality of moving object with a trajectory of the object and user-defined trajectories. Because of using user-define based information, the presented method have more accurate and faster performance than models need a learning about normal behaviors. The method also have adaptation process of assigned rule, so it can handle scene variation for more robust performance. The experimental results show that our method can detect abnormal traffic behaviors in various situation.