• International Journal of Automotive Technology
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• v.7 no.2
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• pp.195-199
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• 2006

According to the United States FMVSS 208, every passenger car on the market after September of 2006 must install a safety system, which can deploy the airbag with different intensity or suppression based on the passenger type, to reduce infant and child injuries from airbag deployments. The Weight Classification System, which has been developed by Hyundai Autonet, is a system that classifies the person occupying the passenger seat. To overcome sensing problems due to the weight sensors small voltage, the Distributed Systems Interface is adopted.

• The KIPS Transactions:PartB
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• v.19B no.4
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• pp.237-242
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• 2012

Web information service needs a document classification system for efficient management and conveniently searches. Existing document classification systems have a problem of low accuracy in classification, if a few number of feature words is selected in documents or if the number of documents that belong to a specific category is excessively large. To solve this problem, we propose a document classification system using 'Modified ECCD' feature selection method and 'Category Weight for each Document'. Experimental results show that the 'Modified ECCD' feature selection method has higher accuracy in classification than ${\chi}^2$ and the ECCD method. Moreover, combining the 'Category Weight for each Document' feature value and 'Modified ECCD' feature selection method results better accuracy in classification.

• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.4
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• pp.487-494
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• 2016

In order to comply with the Federal Motor Vehicle Safety Standard(FMVSS) No. 208 that has been in force since September 2003, an automatic airbag suppression system has become an essential option for detecting and protecting infants and children seated in the front passenger seat of vehicles in the U.S. market. MOBIS has developed the world's first weight-based OCS under the name NWCS. NWCS is composed of two sensors and ECU. It is sub-packaged in order to minimize the seat structure deviation. In this paper, technical features, robustness and performance of NWCS are summarized and discussed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.229-232
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• 2022

Recently, production of offshore fisheries in Korea has been decreasing. Since production of offshore fisheries in 2016 fell below 1 million tons for the first time in 44 years, it has not recovered and has been decreasing. In order to cope with such a decrease in fishery resources, the TAC (total allowable catch) system is implemented internationally for fisheries resource management. Since 1999, South Korea has introduced the TAC system to perform resource management. In this paper, we propose an artificial intelligence-based fish classification and weight estimation system that can be used to investigate fishery resources of land observers essential for the implementation of the TAC system. The system consists of an app and a cloud server that automatically measures the body size and height of fish and takes photos using a terminal equipped with a lidar sensor. In the cloud server, fish classification is performed using a CNN-based efficientnet model and the weight of fish is predicted using automatically measured body length and body height information. Using this system, it is possible to improve the existing method in which the land observer manually writes after measuring the tape measure and weight in the stomach market.

• Journal of Integrative Natural Science
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• v.4 no.1
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• pp.31-37
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• 2011

Various algorithms and system development are being required to support the advanced decision making of navigation information support system because of a serious loss of lives and property accidents by officer's error like as carelessness and decision faults. Much of researchers have introduced the techniques about the systems, but they hardly consider environmental factors. In this paper, We collect the context information in order to assess the risk, which is considered the various factor of the sailing ship, then extract the features of knowledge context, which is to apply the weight of correlation coefficients among data in context information. We decide the risk after the extract features through the classification and prediction of context information, and compare the value accuracy of proposed method in order to compare efficiency of the weighted value with the non-weighted value. As a result of experience, we know that the method of weight properties effectively reflect the marine environment because the weight accurate better than the non-weighted.

• Journal of Korea Multimedia Society
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• v.25 no.1
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• pp.39-51
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• 2022

Image-based gender classification and age estimation of human are classic problems in computer vision. Most of researches in this field focus just only one task of either gender classification or age estimation and most of the reported methods for each task focus on accuracy performance and are not computationally light. Thus, running both tasks together simultaneously on low cost mobile or embedded systems with limited cpu processing speed and memory capacity are practically prohibited. In this paper, we propose a novel light-weight gender classification and age estimation method based on ensemble multitasking deep learning with light-weight processing neural network architecture, which processes both gender classification and age estimation simultaneously and in real-time even for embedded systems. Through experiments over various well-known datasets, it is shown that the proposed method performs comparably to the state-of-the-art gender classification and/or age estimation methods with respect to accuracy and runs fast enough (average 14fps) on a Jestson Nano embedded board.

• Journal of Sensor Science and Technology
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• v.18 no.5
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• pp.385-392
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• 2009

This paper describes the algorithm development of a new body pressure detection sensor for occupant classification system. U.S. Government has required that advanced airbag system should be installed to every automobiles after 2006 according to FMVSS 208 regulation. Therefore, Occupant Classification System should be provided the passenger with safety in order to protect the infants or children that sit in the front passenger seat. When an occupant sits on the chair of the vehicle, deployment of the airbag depends on passenger's weigh distribution and postures. Authors have been developed a new pattern recognition of passenger and weight distribution at the same time by Force Sensing Resistor for the safety.

• 한국디지털정책학회:학술대회논문집
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• 2007.06a
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• pp.79-87
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• 2007

This paper aims to offer a solution based on semantic document classification to improve e-Government utilization and efficiency for people using their own information retrieval system and linguistic expression Generally, semantic document classification method is an approach that classifies documents based on the diverse relationships between keywords in a document without fully describing hierarchial concepts between keywords. Our approach considers the deep meanings within the context of the document and radically enhances the information retrieval performance. Concept Weight Document Classification(CoWDC) method, which goes beyond using exist ing keyword and simple thesaurus/ontology methods by fully considering the concept hierarchy of various concepts is proposed, experimented, and evaluated. With the recognition that in order to verify the superiority of the semantic retrieval technology through test results of the CoWDC and efficiently integrate it into the e-Government, creation of a thesaurus, management of the operating system, expansion of the knowledge base and improvements in search service and accuracy at the national level were needed.

• Convergence Security Journal
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• v.18 no.4
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• pp.19-25
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• 2018

In this paper, we propose an user-centered integrated lost-goods management system through a ranking system based on weight and a hierarchical image classification system based on Deep Learning. The proposed system consists of a hierarchical image classification system that automatically classifies images through deep learning, and a ranking system modules that listing the registered lost property information on the system in order of weight for the convenience of the query process.In the process of registration, various information such as category classification, brand, and related tags are automatically recognized by only one photograph, thereby minimizing the hassle of users in the registration process. And through the ranking systems, it has increased the efficiency of searching for lost items by exposing users frequently visited lost items on top. As a result of the experiment, the proposed system allows users to use the system easily and conveniently.

• The Research Journal of the Costume Culture
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• v.13 no.2 s.55
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• pp.200-208
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• 2005

This study was aimed to provide the measurement data and shape classification of the head of the Korean female children for the headwear sizing systems. Four hundred nineteen female children, aged nine to twelve years, participated for this study. The 19 regions on the head and height, weight of the subjects were directly measured by the expert experimenters. Factor analysis, cluster analysis, GLM analysis and Tukey HSD test were performed using these data. Through factor analysis, five factors were extracted upon factor scores and those factors comprised $71.318\%$ for the total variances. Three clusters as their head shape were categorized using fiver factor scores by cluster analysis. Type 1 was characterized by the widest head width, Bitragion arc, and shortest head length, and medium height and weight. Type 2 had the longest head length and the widest side head width and the highest head circumference, and highest height and largest weight. Type 3 was characterized by the medium head length, smallest head circumstance, narrowest head width and side head width, and smallest height and weight.