• Journal of the Korean Society for Precision Engineering
• /
• v.5 no.1
• /
• pp.84-93
• /
• 1988

The on-line detection of the chip flow is one of the most important technologies in com- pletly automatic operation of machine tool, such as FMS and Unmanned Factories. This problem has been studied by many researchers, however, it is not solved as yet. For the recognition of chip flow in this study, the dynamic cutting force components due to the chip breaking were measured by dynamometer of piezo-electric type, and the frequency components of cutting force were also analyzed. From the measured results, the effect of cutting conditions and tool geometry on the dynamic cutting force component and chip formation were investigated in addition to the relationships between frequency of chip breaking (fB) and side serrated crack (fC) of chip. As a result, the following conclusions were obtaianed. 1) The chip formations have a large effect on the dynamic cutting force components. When chip breaking takes place, the dynamic cutting force component greatly increases, and the peridoic components appear, which correspond to maximum peak- frequency. 2) The crater wear of tool has a good effect on the chip control causing the chiup to be formed as upward-curl shape. In this case, the dymamic cutting force component greatly increases also 3) fB and fC of chip are closely corelated, and fC of chips has a large effect on the change of the situation of chip flow and dynamic cutting force component. 4) Under wide cutting conditions, the limit value (1.0 kgf) of dynamic cutting force component exists between the broken and continuous chips. Accordingly, this value is suitable for recognition of chip flow in on-line control of the cutting process.

• Journal of Animal Environmental Science
• /
• v.9 no.1
• /
• pp.45-56
• /
• 2003

$TAO^{TM}$ System is an auto-heated thermophilic aerated digestion process using a proprietary microbe called as a Phototropic Bacteria (PTB). High metabolic activity results in heat generation, which enables to produce a pathogen-free and digested liquid fertilizer at short retention times. TAO$^{TM}$ system has been developed to reduce a manure volume and convert into the liquid fertilizer using swine manure since 1992. About 100 units have been installed and operated in Korean swine farms so far. TAO$^{TM}$ system consists of a reactor vessel and ejector-type aeration pumps and foam removers. The swine slurry manure enters into vessel with PTB and is mixed and aerated. The process is operated at detention times from 2 to 4 days and temperature of 55 to $65^{\circ}C$. Foams are occurred and broken down by foam removers to evaporate water contents. Generally, at least 30% of water content is evaporated, 99% of volatile fatty acids caused an odor are removed and pathogen destruction is excellent with fecal coliform, rotavirus and salmonella below detection limits. The effluent from TAO$^{TM}$ system, called as the "TAO EFFLUX", is screened and has superb properties as a fertilizer. Normally N-P-K contents of screened TAO Efflux are 4.7 g/L, 0.375 g/L and 2.8 g/L respectively. The fertilizer effect of TAO EFFLUX compared to chemical fertilizer has been demonstrated and studied with various crops such as rice, potato, cabbage, pumpkin, green pepper, parsley, cucumber and apple. Generally it has better fertilizer effects and excellent soil fertility improvement effects. Moreover, the TAO EFFLUX is concentrated through membrane technology without fouling problems for a cost saving of long distance transportation and a commercialization (crop nutrient commodity) to a gardening market, for example.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.18 no.2
• /
• pp.104-113
• /
• 2019

The road management institute needs lots of cost to repair road surface damage. These damages are inevitable due to natural factors and aging, but maintenance technologies for efficient repair of the broken road are needed. Various technologies have been developed and applied to cope with such a demand. Recently, maintenance technology for road surface damage repair is being developed using image information collected in the form of a black box installed in a vehicle. There are various methods to extract the damaged region, however, we will discuss the image recognition technology of the deep neural network structure that is actively studied recently. In this paper, we introduce a new neural network which can estimate the road damage and its location in the image by region-based convolution neural network algorithm. In order to develop the algorithm, about 600 images were collected through actual driving. Then, learning was carried out and compared with the existing model, we developed a neural network with 10.67% accuracy.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.48 no.2
• /
• pp.40-46
• /
• 2011

This paper proposes a real-time face detection and tracking system that uses neural oscillators which can be applied to access regulation system or control systems of user authentication as well as a new algorithm. We study a way to track faces using the neural oscillatory network which imitates the artificial neural net of information handing ability of human and animals, and biological movement characteristic of a singular neuron. The system that is suggested in this paper can broadly be broken into two stages of process. The first stage is the process of face extraction, which involves the acquisition of real-time RGB24bit color video delivering with the use of a cheap webcam. LEGION(Locally Excitatory Globally Inhibitory)algorithm is suggested as the face extraction method to be preceded for face tracking. The second stage is a method for face tracking by discovering the leader neuron that has the greatest connection strength amongst neighbor neuron of extracted face area. Along with the suggested method, the necessary element of face track such as stability as well as scale problem can be resolved.

• Journal of Preventive Medicine and Public Health
• /
• v.26 no.4 s.44
• /
• pp.628-649
• /
• 1993

This study was conducted to investigate the factors related to the poor school performance of the elementary school children. Two schools in Taegu, one in the affluent area and the other in the poor area, were selected and a total of 175 children whose school performance was within low 10 percentile (poor performers) and 97 children whose school performance were within high 5 percentile (good performers) in each class of 2nd, 4th and 6th grades were tested for the physical health, behavioral problem and family background. Each child had gone through a battery of tests including visual and hearing acuity, anthropometry (body weight, height, head circumference), intelligence (Kodae Stanford-Binet test), test anxiety (TAI-K), neurologic examination by a developmental pediatrician and heavy metal content (Pb, Cd, Zn) in hair by atomic absorption spectrophotometry. A questionnaire was administered to the mothers for prenatal and prenatal courses of the child, family environment, child's developmental history, and child's behavioral and learning problems. Another questionnaire was administered to the teachers of the children for the child's family background, arithmatic & language abilities and behavioral problem. The poor school performance had a significant correlation with male gender, high birth order, broken home, low educational and occupational levels of parents, visual problem, high test anxiety score, attention deficit hyperactivity disorder (ADHD), poor physical growth (weight, height, head circumference) and low I.Q. score. The factors that had a significant correlation with the poor school performance in multiple logistic regression analysis were child's birth order (odds ratio=2.06), male gender(odds ratio=5.91), broken home(odds ratio=9.29), test anxiety score(odds ratio=1.07), ADHD (odds ratio=9.67), I.Q. score (odds ratio=0.85) and height less than Korean standard mean-1S.D.(odds ratio=11.12). The heavy metal contents in hair did not show any significant correlation with poor school performance. However the lead and cadmium contents were high in males than in females. The lead content was negatively correlated with child's grade(P<0.05) and zinc was positively correlated with grade (P<0.05). among the factors that showed a significant correlation with the poor school performance, high birth order, short stature and ADHD may be modified by a good family planning, good feeding practice for infant and child, and early detection and treatment of ADHD. Also, teacher and parents should restrain themselves from inducing excessive test anxiety by forcing the child to study and over-expecting beyond the child's intellectual capability.

• Journal of the korean academy of Pediatric Dentistry
• /
• v.31 no.2
• /
• pp.153-158
• /
• 2004

Preformed stainless steel crown is an useful restorative material for the treatment of badly broken down primary teeth. However iatrogenic damage to adjacent teeth might occur during the process of tooth reduction. Such damages might lead to plaque accumulation and increase the risks of caries initiation. Especially the damage can make a problem in the first permanent molar. Purpose of this study was to investigate an iatrogenic damage to the first permanent molar during preparation of second primary molar for preformed stainless steel crown. Twelve children restored with preformed stainless steel crown to second primary molar were selected. Contact areas were separated with separation elastics, and tooth surfaces were cleaned. After taking negative impression using vinylpolysiloxane impression material, the specimens were examined by scanning electron microscope for the detection of iatrogenic damage. The prevalence of iatrogenic damage was 66.7% and variable appearances and So we can suggest that when preparing teeth for preformed stainless steel crown, we should be careful about adjacent teeth not to make an iatrogenic damage.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.18 no.6
• /
• pp.455-463
• /
• 1998

RCCA(rod cluster control assembly) End-Tip suffers from neutron irradiation and constant vibration due to high-speed internal flow of primary coolant during plant operation. Such operating conditions cause the RCCA end-tip crackings around tile circumferential weldment of the end-tip, and in some cases, the defective end-tips were completly broken loose. However, no reliable inspection techniques for end-tip crackings were developed in the past, although some techniques exist for inspecting RCCA control rod wears. Therefore, NDE group at KEPRI has developed an ECT technique for the detection and the sizing of the end-tip crackings. The technique uses a specially designed surface-riding probe that can detect size of circumferential crackings with an accuracy of ${\pm}5.31%$ RMS error. This paper describes the ECT instrumentation including the ECT probes, calibration bars, as well as technical approaches.

• Korean Journal of Environment and Ecology
• /
• v.36 no.5
• /
• pp.535-549
• /
• 2022

Damage to forests, such as broken or falling trees, has increased due to the increased intensity and frequency of abnormal climate events, such as strong winds and heavy rains. However, it is difficult to respond to them in advance based on prediction since structural defects such as cavities and bumps inside trees are difficult to identify with a visual inspection. Non-invasive sonic tomography (SoT) is a method of estimating internal defects while minimizing physical damage to trees. Although SoT is effective in diagnosing internal defects, its accuracy varies depending on the species. Therefore, it is necessary to analyze the reliability of its measurement results before applying it in the field. In this study, we measured internal defects in wood by cross-applying destructive resistance micro drilling on old Pinus densifloraSiebold & Zucc. and Ginkgo bilobaL., which are representative tree species in Korea, to verify the reliability of SoT and compared the evaluation results. The t-test for the mean values of the defect measurement between the two groups showed no statistically significant difference in pine trees and some difference in ginkgo trees. Linear regression analysis results showed a positive correlation with an increase in defects in SoT images when the defects in the drill resistance graph increased in both species.

• Journal of Intelligence and Information Systems
• /
• v.26 no.2
• /
• pp.57-78
• /
• 2020

With the development of the Internet, consumers have had an opportunity to check product information easily through E-Commerce. Product reviews used in the process of purchasing goods are based on user experience, allowing consumers to engage as producers of information as well as refer to information. This can be a way to increase the efficiency of purchasing decisions from the perspective of consumers, and from the seller's point of view, it can help develop products and strengthen their competitiveness. However, it takes a lot of time and effort to understand the overall assessment and assessment dimensions of the products that I think are important in reading the vast amount of product reviews offered by E-Commerce for the products consumers want to compare. This is because product reviews are unstructured information and it is difficult to read sentiment of reviews and assessment dimension immediately. For example, consumers who want to purchase a laptop would like to check the assessment of comparative products at each dimension, such as performance, weight, delivery, speed, and design. Therefore, in this paper, we would like to propose a method to automatically generate multi-dimensional product assessment scores in product reviews that we would like to compare. The methods presented in this study consist largely of two phases. One is the pre-preparation phase and the second is the individual product scoring phase. In the pre-preparation phase, a dimensioned classification model and a sentiment analysis model are created based on a review of the large category product group review. By combining word embedding and association analysis, the dimensioned classification model complements the limitation that word embedding methods for finding relevance between dimensions and words in existing studies see only the distance of words in sentences. Sentiment analysis models generate CNN models by organizing learning data tagged with positives and negatives on a phrase unit for accurate polarity detection. Through this, the individual product scoring phase applies the models pre-prepared for the phrase unit review. Multi-dimensional assessment scores can be obtained by aggregating them by assessment dimension according to the proportion of reviews organized like this, which are grouped among those that are judged to describe a specific dimension for each phrase. In the experiment of this paper, approximately 260,000 reviews of the large category product group are collected to form a dimensioned classification model and a sentiment analysis model. In addition, reviews of the laptops of S and L companies selling at E-Commerce are collected and used as experimental data, respectively. The dimensioned classification model classified individual product reviews broken down into phrases into six assessment dimensions and combined the existing word embedding method with an association analysis indicating frequency between words and dimensions. As a result of combining word embedding and association analysis, the accuracy of the model increased by 13.7%. The sentiment analysis models could be seen to closely analyze the assessment when they were taught in a phrase unit rather than in sentences. As a result, it was confirmed that the accuracy was 29.4% higher than the sentence-based model. Through this study, both sellers and consumers can expect efficient decision making in purchasing and product development, given that they can make multi-dimensional comparisons of products. In addition, text reviews, which are unstructured data, were transformed into objective values such as frequency and morpheme, and they were analysed together using word embedding and association analysis to improve the objectivity aspects of more precise multi-dimensional analysis and research. This will be an attractive analysis model in terms of not only enabling more effective service deployment during the evolving E-Commerce market and fierce competition, but also satisfying both customers.

• Journal of the Society of Cosmetic Scientists of Korea
• /
• v.33 no.4
• /
• pp.263-267
• /
• 2007

Parabens are used in nearly all types of cosmetics and toiletries because they are formulated well and have broad spectrum of activity, interness, low costs and excellent chemical stability in relation to pH. 2-phenoxyethanol and chlorphenesin are common preservatives which are usually used in combination with parabens in cosmetics. Toxicity of parabens is generally low but application of parabens to damaged or broken skin has resulted in sensitization. Moreover, the possibility of their estrogenic potential, anesthetic effects and reproductive toxicity has been reported. Consequently there are some regulations in use of parabens. And the maximum permitted concentrations of chlorphenesin and 2-phenoxyethanol in cosmetic products are authorized by the same reasons. So it is important to control and estimate the amount of parabens in products. In this article, we proposed a valid method for the simultaneous determination of 8 preservatives including parabens in a short time using ultra performance liquid $chromatography^{TM}\;(UPLC^{TM})$. Separation of eight components was achieved in less than 10 min and resolutions were reasonable (USP resolution ${\geqq}\;2$). And limit of detection and quantification were evaluated. The method was suitably validated for specificity, linearity, precision (repeatability, intermediate precision) and accuracy for assay (recovery) based on International conference on harmonisation (ICH) guideline. The method was applicable to analysis of preservatives in cosmetic products.