• Journal of Auto-vehicle Safety Association
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• v.15 no.4
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• pp.88-94
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• 2023

The seating postures of passengers in the automated driving vehicle are possible in atypical forms such as rear-facing and lying down. It is necessary to improve devices such as airbags and seat belts to protect occupants from injury in accidents of the automated driving vehicle, and collision safety evaluation tests must be newly developed. The purpose of this study is to define representative types of head-on collision accidents to develop collision standards for autonomous vehicles that take into account changes in driving behavior and occupants' postures. 150 frontal collision cases remained by filtering (accident videos, images, AIS 2+, passenger car, etc…) and random sampling from approximately 320,000 accidents claimed by a major insurance company over the past 5 years. The most frequent accident type is a head-on collision between a vehicle going straight and a vehicle turning left from the opposite side, accounting for 54.7% of all accidents, and most of these accidents occur in permissive left turns. The next most common frontal collision is the center-lane violation by drowsy driving and careless driving, accounting for 21.3% of the total. For the two types above, data such as vehicle speed, contact point/area, and PDOF at the moment of impact are obtained through accident reconstruction using PC-Crash. As a result, two types of autonomous vehicle crash safety test scenarios are proposed: (1) a frontal oblique collision test based on the accident types between a straight vehicle and a left-turning vehicle, and (2) a small overlap collision test based on the head-on accidents of center-lane violation.

• Research in Mathematical Education
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• v.5 no.2
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• pp.87-98
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• 2001

The Center for Science Gifted Education (CSGE) of Chongju National University of Education was established in 1998 with the financial support of the Korea. Science & Engineering Foundation (KOSEF). In fact, we had prepared mathematics and science gifted education program beginning in 1997. It was possible due to the commitment of faculty members with an interest in gifted education. Now we have 5 classes in Mathematics, two of which are fundamental, one of which is a strengthened second-grade class gifted elementary school students, and one a fundamental class, and one a strengthened class for gifted middle school students in Chungbuk province. Each class consists of 16 students selected by a rigorous examination and filtering process. Also we have a mentoring system for particularly gifted students in mathematics. We have a number of programs for Super-Saturday, Summer School, Winter School, and Mathematics and Science Gifted Camp. Each program is suitable for 90 or 180 minutes of class time. The types of tasks developed can be divided into experimental, group discussion, open-ended problem solving, and exposition and problem solving tasks. Levels of the tasks developed for talented elementary students in mathematics can be further divided into grade 5 and under, grade 6, and grade 7 and over. Types of the tasks developed can be divided into experimental, group discussion, open-ended problem solving, and exposition and problem solving task. Also levels of the tasks developed for talented elementary students in mathematics can be divided into the level of lower than grade 5, level of grade 6, and level of more than grade 7. Three tasks developed and practiced are reported in this article.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1797-1798
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• 2007

In field of voice pathology, diverse statistics extracted form pitch estimation were commonly used to assess voice quality. In this study, we proposed robust pitch detection algorithm which can estimate pitch of pathological voices in benign vocal fold lesions. we also compared our proposed algorithm with three established pitch detection algorithms; autocorrelation, simplified inverse filtering technique, and nonlinear state-space embedding methods. In the database of total pathological voices of 99 and normal voices of 30, an analysis of errors related with pitch detection was evaluated between pathological and normal voices, or among the types of pathological voices. According to the results of pitch errors, gross pitch error showed some increases in cases of pathological voices; especially excessive increase in PDA based on nonlinear time-series. In an analysis of types of pathological voices classified by aperiodicity and the degree of chaos, the more voice has aperiodic and chaotic, the more growth of pitch errors increased. Consequently, it is required to survey the severity of tested voice in order to obtain accurate pitch estimates.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.6 no.2
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• pp.222-248
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• 1996

This study was designed to survey misused expression in 37 KS (Korean Industrial standards) related to personal protective equipment. The results were as follows: 1. One hundred and twenty five misused expressions were found - 44 expressions were used illogically (35.2 %). 80 expressions were wrongly described (64.0 %) The types of illogically misused are: 10 illogical cases, 4 cases of a wrongly designated provision when cited, 12 cases of the lack of provisons for KS, 7 cases of a inappropriate uses of units, 8 cases of an overlapped sizes between standards. - The types of expressions wrongly described are: 30 cases of confusion in using an terms, 4 case of making an error when proofreading, and 29 cases of choosing words not appropriate to describe technical standard, 18 cases of unclear provisons due to missing phrases and terms, and 11 cases of provisons described differently from original intended purposes. 2. There is one case, where the same standard is categorized as two different names. There are three major causes of the misused expressions as seen from the following summary: - Imitated the developed countries' standards without filtering them by considering domestic law and ocher KS standards. - Tended to create each definition for each standard instead use of the basic standard. - Insufficiency of synthetic examination to the correlation between standards.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.139-161
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• 2019

The utilization of the e-commerce market has become a common life style in today. It has become important part to know where and how to make reasonable purchases of good quality products for customers. This change in purchase psychology tends to make it difficult for customers to make purchasing decisions in vast amounts of information. In this case, the recommendation system has the effect of reducing the cost of information retrieval and improving the satisfaction by analyzing the purchasing behavior of the customer. Amazon and Netflix are considered to be the well-known examples of sales marketing using the recommendation system. In the case of Amazon, 60% of the recommendation is made by purchasing goods, and 35% of the sales increase was achieved. Netflix, on the other hand, found that 75% of movie recommendations were made using services. This personalization technique is considered to be one of the key strategies for one-to-one marketing that can be useful in online markets where salespeople do not exist. Recommendation techniques that are mainly used in recommendation systems today include collaborative filtering and content-based filtering. Furthermore, hybrid techniques and association rules that use these techniques in combination are also being used in various fields. Of these, collaborative filtering recommendation techniques are the most popular today. Collaborative filtering is a method of recommending products preferred by neighbors who have similar preferences or purchasing behavior, based on the assumption that users who have exhibited similar tendencies in purchasing or evaluating products in the past will have a similar tendency to other products. However, most of the existed systems are recommended only within the same category of products such as books and movies. This is because the recommendation system estimates the purchase satisfaction about new item which have never been bought yet using customer's purchase rating points of a similar commodity based on the transaction data. In addition, there is a problem about the reliability of purchase ratings used in the recommendation system. Reliability of customer purchase ratings is causing serious problems. In particular, 'Compensatory Review' refers to the intentional manipulation of a customer purchase rating by a company intervention. In fact, Amazon has been hard-pressed for these "compassionate reviews" since 2016 and has worked hard to reduce false information and increase credibility. The survey showed that the average rating for products with 'Compensated Review' was higher than those without 'Compensation Review'. And it turns out that 'Compensatory Review' is about 12 times less likely to give the lowest rating, and about 4 times less likely to leave a critical opinion. As such, customer purchase ratings are full of various noises. This problem is directly related to the performance of recommendation systems aimed at maximizing profits by attracting highly satisfied customers in most e-commerce transactions. In this study, we propose the possibility of using new indicators that can objectively substitute existing customer 's purchase ratings by using RFM multi-dimensional analysis technique to solve a series of problems. RFM multi-dimensional analysis technique is the most widely used analytical method in customer relationship management marketing(CRM), and is a data analysis method for selecting customers who are likely to purchase goods. As a result of verifying the actual purchase history data using the relevant index, the accuracy was as high as about 55%. This is a result of recommending a total of 4,386 different types of products that have never been bought before, thus the verification result means relatively high accuracy and utilization value. And this study suggests the possibility of general recommendation system that can be applied to various offline product data. If additional data is acquired in the future, the accuracy of the proposed recommendation system can be improved.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2000.04a
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• pp.36-43
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• 2000

Many formats are used for recording and processing in the research of earthquake seismology and earthquake engineering. It is very difficult to program the Reading and writing algorithm for data processing because fill formats are very different from each other. It is suggested new file format of Korea Standard earthquake data (KSED) two types of ASCII and binary that are read and written easily. The Program package of basic data processing (Analyst) which has function of basic filtering spectrum analysis event gathering phase picking and location is developed In addition this program supports file transformation from another format(Mini SEED OMD K2) to KSED format.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.478-481
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• 2002

In this paper, the zerotrees of DWT is proposed to be used in a speech based digital watermarking for digital images. Since in this research work the raw speech and its content are used as a watermark signal, in the watermarking scheme, the PCM coded speech signal is embedded into a sequence of images. The performance of the scheme is evaluated by the PSNR obtained from the watermarked images and the strength of attacks the embedded speech signal can survive. Moreover, since in this research work the contents contained in the speech is used to identify the specific information hidden in the embedded signal. The speech signal after being extracted from the watermarked images is played back to the listeners to determine whether its content is intelligible or not. The experimental results show impressive performance of the scheme implementing our proposed technique, judged by the higher robustness obtained form the embedded signal against various types of attack, including brightness/contrast enhancement, Twirling, highpass filtering and JPEG compression standard.

• Journal of Advanced Marine Engineering and Technology
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• v.32 no.8
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• pp.1309-1314
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• 2008

Seismic data is often contaminated with high-energy, spatially aliased noise, which has proven impractical to attenuate using Fourier techniques. Wavelet filtering, however, has proven capable of attacking several types of localized noise simultaneously regardless of their frequencies. In this study a 2-D stationary wavelet transform is used to decompose seismic data into its wavelet components. A threshold is applied to these coefficients to attenuate high amplitude noise, followed by an inverse transform to reconstruct the seismic trace. The stationary wavelet transform minimizes the phase-shift errors induced by thresholding that occur when the conventional discrete wavelet transform is used.

• Journal of information and communication convergence engineering
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• v.9 no.3
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• pp.336-340
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• 2011

Many approaches to image restoration are aimed at removing either gauss or impulse noise. This is because both types of degradation processes are distinct in nature, and hence they are easier to manage when considered separately. Nevertheless, it is possible to find them operating on the same image, which produces a hard damage. This happens when an image, already contaminated by Gaussian noise in the image acquisition procedure, undergoes impulsive corruption during its digital transmission. Here we proposed an algorithm first judge the type of the noise according to the difference values of pixel's neighborhood region and impulse noise's characteristic. Then removes the gauss noise by modified weighted mean filter and removes the impulse noise by modified nonlinear filter. The result of computer simulation on test images indicates that the proposed method is superior to traditional filtering algorithms. The proposed method can not only remove mixed noise effectively, but also preserve image details.

• Annals of Clinical Neurophysiology
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• v.19 no.2
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• pp.113-117
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• 2017

The performance of electroencephalogram (EEG) recordings is affected by electrode type, electronic parameters such as filtering, amplification, signal conversion, data storage; and environmental conditions. However, no single method has been identified for optimal EEG recording quality in all situations. Therefore, we aimed to provide general principles for EEG electrode selection as well as electronic noise reduction, and to present comprehensive information regarding the acquisition of satisfactory EEG signals. The standards provided in this document may be regarded as Korean guidelines for the clinical recording of EEG data. The equipment, types and nomenclature of electrodes, and the details for EEG recording are discussed.