• Journal of Multimedia Information System
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• v.8 no.4
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• pp.211-220
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• 2021

The process of inspecting SMDs on the PCB boards improves the product quality, performance and reduces frequent issues in this field. However, undesirable scenarios such as assembly failure and device breakdown can occur sometime during the assembly process and result in costly losses and time-consuming. The detection of these components with a model based on deep learning may be effective to reduce some errors during the inspection in the manufacturing process. In this paper, YOLO models were used due to their high speed and good accuracy in classification and target detection. A SMD detection and classification method using YOLO networks based on robust data preprocessing and augmentation techniques to deal with various types of variation such as illumination and geometric changes is proposed. For 9 different components of data provided from a PCB manufacturer company, the experiment results show that YOLOv4 is better with fast detection and classification than YOLOv3.

• Electronics and Telecommunications Trends
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• v.37 no.4
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• pp.28-35
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• 2022

To solve the challenge of waste plastics, this study investigated the related technologies and company trends along the plastic life cycle, and primarily describes ICT technologies to improve efficiency in the process of sorting and sorting waste plastics. Waste plastic discharge caused by the explosive increase in parcel traffic because of COVID-19 is also growing exponentially. Hence, waste treatment is emerging as a social challenge. Most of the domestic waste classification depends on the manual process according to the waste pollution level. The plastic material classification approach using the spectroscopy approach reveals a high error in the contaminated waste plastic classification, but if the Artificial Intelligence-based image classification technology is employed together, the classification precision can be enhanced because of the type of waste plastic product and the contaminated part can be differentiated.

• Journal of the Society of Naval Architects of Korea
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• v.46 no.1
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• pp.57-68
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• 2009

In automotive industries, reusability of product information is increasing through database construction of previous product data. The product data is stored by data quality management in product information systems. For naval ships, have the functional similarity by the ships of the same classification and class, that are built by series. Information of hull structures as well as embarked equipments are similar. So it would be effective to use database systems that are considered product information quality of previous ships in design and production processes. In this paper we discuss product information quality in database construction of naval ship product models. For this, we propose a basic concept and reference model for data quality verification. Based on this concept, A verification guideline is defined and it is applied for the case study of the digital naval ship which was built to the naval ship product model.

• Communications for Statistical Applications and Methods
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• v.26 no.1
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• pp.1-9
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• 2019

Various probabilistic methods have been proposed for using interpopulation allele frequency differences to infer the ethnic group of a DNA specimen. The selection of the statistical method is critical because the accuracy of the statistical classification results vary. For the ancestry classification, we proposed a new ancestry evaluation method that estimate the combined ethnicity index as well as compared its performance with various classical classification methods using two real data sets. We selected 13 SNPs that are useful for the inference of ethnic origin. These single nucleotide polymorphisms (SNPs) were analyzed by restriction fragment mass polymorphism assay and followed by classification among ethnic groups. We genotyped 400 individuals from four ethnic groups (100 African-American, 100 Caucasian, 100 Korean, and 100 Mexican-American) for 13 SNPs and allele frequencies that differed among the four ethnic groups. Additionally, we applied our new method to HapMap SNP genotypes for 1,011 samples from 4 populations (African, European, East Asian, and Central-South Asian). Our proposed method yielded the highest accuracy among statistical classification methods. Our ethnic group classification system based on the analysis of ancestry informative SNP markers can provide a useful statistical tool to identify ethnic groups.

• Journal of Dairy Science and Biotechnology
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• v.25 no.1
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• pp.47-54
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• 2007

The labeling for functionality of food or food components are recognized globally and are essential for the growth of dairy product industry. To expand the functional claims of dairy product especially fermented milk product, the regulations restricting the labeling of functionality should be amended as soon as possible. The labeling regulations of functionality and efficacy for processed and functional foods in related Acts and subordinated statues such as definition, scope of claims, etc. were reviewed and the problems existed in the system were identified. The definition and classification of efficacy for processed food in Food Sanitation Act were analyzed to revise the labeling regulation of dairy product. A draft of amended labeling regulation for the functionality of dairy product is proposed, which provides consumers with appropriate information of beneficial effects on health purpose for human body structure and function. In order to develop the dairy products and related industries, these contents should be considered when the annexed Table 14 in the Enforcement Rule of the Processing of Livestock Products Act is amended.

• Proceedings of the Korea Database Society Conference
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• 2008.05a
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• pp.413-419
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• 2008

Product information system contains information concerning products such as classification, attributes and UOM. Product information system stores their product information to a Relational Database. However, they do not support interoperability between product systems since their database is designed and optimized for their services. We suggest a standard product model and the scenarios of web services based on our model.

• Journal of the Korea Safety Management & Science
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• v.2 no.3
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• pp.151-169
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• 2000

Product Liability(P.L) is designed for system which charge with a compensation for demages that has nothing to do with whether manufacturer make a mistake or not in that case suffer heavy losses anyone of body or property by defect of product. Now and then, most people interest of safety of product and main countries already carry out Product Liability. This paper analyzes newly studied cases by defects, products, countries in Korea and some developed countries (USA and Japan mainly) in order to prepare for Product Liability, which will be enforced on July 1, 2002 in Korea. Before P.L. began to enforce, many cases have happened and resulted in sues. Therfore, each country have revised the current P.L. after many trials and errors. From this respect, the cases of other countries and Korea will be compared and analyzed.

• Journal of the Korea Safety Management & Science
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• v.2 no.2
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• pp.57-69
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• 2000

Beginning from July. 2000, the product liability of Korea is designed for reduction of customer loss by defective products. Therefore, most of company are supposed to be ready for taking care of safety and quality of products. ISO9001：2000 quality management system reform to emphasize continual improvement of the process with customer satisfaction. First of all, this paper start with introduction motive of the product liability and examine distinctive mark of the ISO9001：2000 quality management system. We consider the correlation between ISO9001：2000 quality management system and product liability and would like to propose product liability prevention by ISO9001：2000 quality management system with classification a defect style of product, the management guide and the law case.

• The Journal of Society for e-Business Studies
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• v.14 no.4
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• pp.19-33
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• 2009

With the continuously increasing volume of e-commerce transactions, it is now popular to buy some products and to evaluate them on the World Wide Web. The product reviews are very useful to customers because they can make better decisions based on the indirect experiences obtainable through the reviews. Product Reviews are results expressing customer's sentiments and thus are divided into positive reviews and negative ones. However, as the number of reviews in on-line shopping increases, it is inefficient or sometimes impossible for users to read all the relevant review documents. In this paper, we present a sentiment analysis algorithm for automatically classifying subjective opinions of customer's reviews using opinion mining technology. The proposed algorithm is to focus on product reviews of on-line shopping, and provides summarized results from large product review data by determining whether they are positive or negative. Additionally, this paper introduces an automatic review analysis system implemented based on the proposed algorithm, and also present the experiment results for verifying the efficiency of the algorithm.

• Science of Emotion and Sensibility
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• v.23 no.2
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• pp.75-88
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• 2020

Given the development of information technology, various methods for efficient information delivery have been constructed as the method of delivering product information moves from offline and 2D to online and 3D. These attempts not only are about delivering product information in an online space where no real product exists but also play a crucial role in diversifying and revitalizing online shopping by providing virtual experiences to consumers. 360 product image is a photorealistic VR that allows a subject to be rotated and photographed to view objects in three dimensions. 360 product image has also attracted considerable attention considering that it can deliver richer information about an object compared with the existing still image photography. 360 product image is influenced by divergent production factors, and accordingly, a difference emerges in the responses of users. However, as the history of technology is short, related research is also insufficient. Therefore, this study aimed to grasp the responses of users, which vary depending on the type of products and the number of source images in the 360 product image process. To this end, a representative product among the product groups that can be frequently found in online shopping malls was selected to produce a 360 product image and experiment with 75 users. The emotional responses to the 360 product image were analyzed through an experimental questionnaire to which the semantic classification method was applied. The results of this study could be used as basic data to understand and grasp the sensitivity of consumers to 360 product image.