• ETRI Journal
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• v.43 no.4
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• pp.630-639
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• 2021

Autonomous driving requires a computerized perception of the environment for safety and machine-learning evaluation. Recognizing semantic information is difficult, as the objective is to instantly recognize and distinguish items in the environment. Training a model with real-time semantic capability and high reliability requires extensive and specialized datasets. However, generalized datasets are unavailable and are typically difficult to construct for specific tasks. Hence, a light detection and ranging semantic dataset suitable for semantic simultaneous localization and mapping and specialized for autonomous driving is proposed. This dataset is provided in a form that can be easily used by users familiar with existing two-dimensional image datasets, and it contains various weather and light conditions collected from a complex and diverse practical setting. An incremental and suggestive annotation routine is proposed to improve annotation efficiency. A model is trained to simultaneously predict segmentation labels and suggest class-representative frames. Experimental results demonstrate that the proposed algorithm yields a more efficient dataset than uniformly sampled datasets.

• Journal of the Semiconductor & Display Technology
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• v.22 no.1
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• pp.94-98
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• 2023

In the case of high-speed data transmission on high multilayer boards, signal coherence is a problem, especially due to the via hole, and a solution to improve return loss or insertion loss by applying a back drill to the via hole is being proposed. In this paper, Near-Field Electromagnetic measurements were made on a high multilayer board to determine how the presence or absence of back drill affects signal consistency. For this purpose, we used a signal generator, spectrum analyzer, and EMC scanner on a test board to determine if it is possible to distinguish between areas with and without back drill in the via holes of the stubs on the board. Also, we analyzed the measured value of S11, S21 and EMC etc. for how much it improves the signal attenuation of the stub with back drill. Through this, we knew that less electromagnetic waves are generated the stub via with back drill. At future research, we will analyze how much it improves the signal loss and electromagnetic waves due to the depth of back drill.

• Journal of Information Technology Application
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• v.2 no.1
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• pp.25-53
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• 2000

As Information Technology has developed, The structure of information system used in organizations is changing from centralized computing structure to distributed computing structure. The roles of information department have expanded, which is not only develope and maintain system but also provide usage-support service to end-user. If organization support end-user properly, they get many benefits. if they don't do it properly, they waste many resource. Therefore, the purpose of this study is the search for quality determinant factors and type of information that provide user effective service under web-based information system. The result of this study is as follow First, when SERVQUAL is used, the quality determinant factors of usage-support service are categorized three, which is responsibility and assurance, empathy and tangable, and reliability. When SERVPERF is used, the determinant factors consist of five, but the use of assurance as a factor is cautious. Second, reliability and tangability among determinant factors affect general service quality, and tangibility is most important factors. third, When the locations of user are distributed the degree of general service quality is not different whether formal or informal information center provide usage-support service. This study may suggest practical implication as follows; First, as user are good at to use information system the degree of importance for tangibility are decreased. when user are individualized and improve their ability to use information system, empathy will not be important factors any more, therfore it assume that reliability will be most important factors. Second, if organizations promote not only formal informaton center but also informal inforamtion center they may support end-user more effectively. However, this study has the following limitations: First, it is difficult to generalize the result of this study Second, service quality determinant factors used in this study don't explain the influence to general service quality fully. Third, this study analyze a simple relation between service quality determinant factor and general service quality. Finally, this study don't distinguish between information system service and information support service.

• The KIPS Transactions:PartB
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• v.13B no.7 s.110
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• pp.679-688
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• 2006

Protein-protein interaction data obtained from high-throughput experiments includes high false positives. In this paper, we introduce a new protein-protein interaction reliability verification system. The proposed system integrates various biological features related with protein-protein interactions, and then selects the most relevant and informative features among them using a feature selection method. To assess the reliability of each protein-protein interaction data, the system construct a classifier that can distinguish true interacting protein pairs from noisy protein-protein interaction data based on the selected biological evidences using a classification technique. Since the performance of feature selection methods and classification techniques depends heavily upon characteristics of data, we performed rigorous comparative analysis of various feature selection methods and classification techniques to obtain optimal performance of our system. Experimental results show that the combination of feature selection method and classification algorithms provide very powerful tools in distinguishing true interacting protein pairs from noisy protein-protein interaction dataset. Also, we investigated the effects on performances of feature selection methods and classification techniques in the proposed protein interaction verification system.

• Journal of Biomedical Engineering Research
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• v.18 no.4
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• pp.429-438
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• 1997

Mechanical valve is one of the most widely used implantable artificial organs of which the reliability is so important that its failure means the death of patient. Therefore early noninvasive detection is essentially required, though mechanical valve failure with thrombosis is the most common. The objective of this paper is to detect the thrombosis formation by spectral analysis and neural network. Using microphone and amplifier, we measured the sound from the mechanical valve which is attached to the pneumatic ventricular assist device. The sound was sampled by A/D converter(DaqBook 100) and the periodogram is the main algorithm for obtaining spectrum. We made the thrombosis models using pellethane and silicon and they are thrombosis model on the valvular disk, around the sewing ring and fibrous tissue growth across the orifice of valve. The performance of the measurment system was tested firstly using 1 KHz sinusoidal wave. The measurement system detected well 1KHz spectrum as expected. The spectrum of normal and 5 kinds of thrombotic valve were obtained and primary and secondary peak appeared in each spectrum waveform. We find that the secondary peak changes according to the thrombosis model. So to distinguish the secondary peak of normal and thrombotic valve quantatively, 3 layer back propagation neural network, which contains 7, 000 input node, 20 hidden layer and 1 output was employed The trained neural network can distinguish normal and valve with more than 90% probability. As a conclusion, the noninvasive monitoring of implanted mechanical valve is possible by analysing the acoustical spectrum using neural network algorithm and this method will be applied to the performance evaluation of other implantable artificial organs.

• Fire Science and Engineering
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• v.33 no.6
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• pp.190-203
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• 2019

Since the amendment of the Accidental Fire Liability Act in 2009, interested parties in accidental fire liability contracts have settled issues associated with the estimation of each other's liability amounts through lawsuits. As fire accidents are complex in nature, it is difficult to distinguish between direct and additional damages caused by extended combustion while calculating liability amounts for accidental fires. Additionally, there is an increasing need for establishing and using a framework that includes validity and reliability. To establish such a framework for estimating the liability amounts in case of an accidental fire, this study suggests a novel categorization of fires to be applied to the framework. This will be organized by the subjects of the liability of accidental fires, and quantified and probabilistic processed qualitative items through the methods applied to quantification (AMEA/FTA) based on the fire statistics data published by the government and the previous researchers' research application data and results.

• Journal of Microbiology and Biotechnology
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• v.13 no.1
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• pp.119-124
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• 2003

This study was conducted to evaluate the practical usefulness of the sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PACE) fingerprinting of whole cell proteins far the identification of lactic acid bacteria in Kimchi. SDS- PACE of whole cell proteins of the reference strains and lactic acid bacteria isolated from Kimchi yielded differential banding patterns that were highly specific fingerprints, thus making it possible to identify. Identification of the isolates from Kimchi was achieved by comparing the SDS-PAGE fingerprints of isolates to those of reference strains. In addition, the reliability of SDS-PAGE was examined by comparing the results with those of the APL 50 CHL system assay and 16S rRNA gene sequence. SDS-PACE assay showed a different identity to reference strains, while the APL 50 CHL system and 16S rRNA gene sequence could not distinguish a few strains. Therefore, SDS-PAGE of the whole cell proteins is a specific and a reliable method that will be useful for the identification of lactic acid bacteria in Kimchi to the species level, and can be used as an alternative or complementary identification method.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.5
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• pp.168-176
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• 2014

Detecting moving objects from a video sequence is a fundamental and critical task in video surveillance, traffic monitoring and analysis, and human detection and tracking. It is very difficult to detect moving objects in a video sequence degraded by the environmental factor such as fog. In particular, the color of an object become similar to the neighbor and it reduces the saturation, thus making it very difficult to distinguish the object from the background. For such a reason, it is shown that the performance and reliability of object detection and tracking are poor in the foggy weather. In this paper, we propose a novel method to improve the performance of object detection, combining a haze removal algorithm and a local histogram-based object tracking method. For the quantitative evaluation of the proposed system, information retrieval measurements, recall and precision, are used to quantify how well the performance is improved before and after the haze removal. As a result, the visibility of the image is enhanced and the performance of objects detection is improved.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.28 no.4
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• pp.197-212
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• 2017

Objectives: This study aims to supplement the limitations of the preliminary study and expand the use of the Child-Adolescent Functional Assessment Scale by providing standardized T-scores for measuring function in different areas, as well as guidelines for their interpretation. Methods: The Child-Adolescent Functional Assessment Scale and Korean-Child Behavior Checklist were administered to a total of 623 individuals, including 467 parents of emotionally and behaviorally disturbed elementary school students, 45 parents of emotionally and behaviorally disturbed middle school adolescents and 111 parents of elementary school students with developmental disorders, as well as to a control group consisting of 186 parents of mainstream elementary school children in the Seoul metropolitan area. Results: In contrast to the preliminary study, the emotional domain was disassociated into two factors, negative affect and emotion regulation, and the coefficient of determination for misconduct was increased significantly. Also, the overall reliability and validity of the Child-Adolescent Functional Assessment Scale were similar to those in the preliminary study, and the item structure was consistent. This study provides standardized T-scores of function in different areas based on the revised scale, and provides guidelines for their interpretation. Conclusion: The Child-Adolescent Functional Assessment Scale can assist the Child Global Assessment in Functioning in providing the information necessary for case management and treatment planning by comparing the impairment severity in each area of functioning, and also determining changes in behavior and function after treatment interventions. On the other hand, this scale has yet to clearly distinguish between rebellious behavior and misconduct. Further research is necessary to provide standards for more diverse age groups and for its utilization.

• Smart Media Journal
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• v.5 no.4
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• pp.26-40
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• 2016

Recent researches have been conducted for a user of the position acquisition and analysis since the mobile devices was developed. Trajectory data mining of location analysis method for a user is used to extract the meaningful information based on the user's trajectory. It should be preceded by a process of extracting Stay Point. In order to carry out trajectory data mining by analyzing the user of the GPS Trajectory. The conventional Stay Point extraction algorithm is low confidence because the user to arbitrarily set the threshold values. It does not distinguish between staying indoors and outdoors. Thus, the ambiguity of the position is increased. In this paper we proposed extraction method of Stay Point using a statistical analysis. We proposed algorithm improves position accuracy by extracting the points that are staying indoors and outdoors using Gaussian distribution. And we also improve reliability of the algorithm since that does not use arbitrarily set threshold.