• Journal of Drive and Control
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• v.13 no.2
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• pp.19-25
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• 2016

Recently, drivers have begun to regard comfort in the cabin as one of the most important factors in construction equipment like forklifts. Accordingly, it has become more important to design a forklift cabin with a better sound quality as well as lower sound level, which can make a driver more comfortable. In this paper, the correlation between subjective evaluation and Zwicker's sound quality index was analyzed through a blind test by a few workers in forklifts and other construction equipment in several countries. Correlation analysis showed that Loudness and Sharpness were ranked in sequence, and tendencies were different from country to country. Also, contribution analysis for Loudness and Sharpness using operational transfer path analysis (OTPA), which is widely used in the field of noise, vibration, and harshness (NVH), was performed. However, Loudness and Sharpness cannot be used with OTPA directly because there are no linear relationships between the sources and receivers. In this paper, both are calculated by applying the DIN 45631 method with a contribution rate (%) of 1/3 Octave Sound Pressure Level by OTPA method in addition to considering spectral masking.

• Journal of IKEEE
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• v.25 no.3
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• pp.430-436
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• 2021

The non-contact body temperature measurement system is one of the key factors, which is manage febrile diseases in mass facilities using optical and thermal imaging cameras. Conventional systems can only be used for simple body temperature measurement in the face area, because it is used only a deep learning-based face detection algorithm. So, there is a limit to detecting abnormal symptoms of the infants and young children, who have difficulty expressing their opinions. This paper proposes an improved facial expression recognition algorithm for detecting abnormal symptoms in infants and young children. The proposed method uses an object detection model to detect infants and young children in an image, then It acquires the coordinates of the eyes, nose, and mouth, which are key elements of facial expression recognition. Finally, facial expression recognition is performed by applying a selective sharpening filter based on the obtained coordinates. According to the experimental results, the proposed algorithm improved by 2.52%, 1.12%, and 2.29%, respectively, for the three expressions of neutral, happy, and sad in the UTK dataset.

• Journal of Digital Convergence
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• v.17 no.6
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• pp.185-192
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• 2019

The purpose of this study examines the effects of corporate CSR on corporate image, customer satisfaction, and customer citizenship behavior in order to provide implications for CSR. To verify hypotheses, we conducted a questionnaire survey on university students using Apple, Sony, Sharp, and Kyocera mobile phones, and used structural equation model analysis for 294 units. As a result, four factors, economic responsibility, legal responsibility, ethical responsibility and philanthropic responsibility were derived from corporate social responsibility, and all three factors except for ethical responsibility factors were proved to have a positive effect on corporate image. In addition, corporate image has a positive effect on customer satisfaction and customer civic behavior. As an implication, Japanese companies will need to take a systematic approach to CSR to help them understand their CSR and improve the level of CSR they can sympathize with.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.10
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• pp.1234-1239
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• 2019

This paper proposes a method for measuring fine dust concentration through digital processing of images captured by only existing CCTVs without additional equipment. This image processing algorithm consists of noise reduction, edge sharpening, ROI setting, edge strength calculation, and correction through HSV conversion. This algorithm is implemented using the C ++ OpenCV library. The algorithm was applied to CCTV images captured over a month. The edge strength values calculated for the ROI region are found to be closely related to the fine dust concentration data. To infer the correlation between the two types fo data, a trend line in the form of a power equation is established using MATLAB. The number of data points deviating from the trend line accounts for around 12.5%. Therefore, the overall accuracy is about 87.5%.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.65-82
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• 2021

Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.

• Journal of The Korean Society of Inherited Metabolic disease
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• v.17 no.2
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• pp.55-62
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• 2017

Gaucher disease (GD) is an autosomal recessive lysosomal storage disorder caused by beta-glucosidase deficiency. An 18 month-old male with hepatosplenomegaly, anemia, thrombocytopenia, and growth retardation referred to our hospital. The patient showed neurological symptoms, such as supranuclear gaze palsy and developmental delay. Bone marrow biopsy performed to rule out malignancy and the results revealed no malignant cell; however, abnormal histiocytes suggesting storage disease was noted. Based on hepatosplenomegaly, bicytopenia and unexplained neurologic manifestations, enzyme activity and genetic analysis were conducted emergently with a strong suspicion of GD. Beta-glucosidase activity in leukocyte was decreased. GBA sequencing to confirm the diagnosis revealed compound heterozygous pathogenic variants (i.e., c.754T>A, c.887G>A), both previously reported as the cause of neuronopathic GD. Under the diagnosis of type 3 GD, the patient immediately received enzyme replacement therapy (ERT). After 17 months of ERT, the size of spleen decreased, and hemoglobin and platelet count returned to normal. In addition, the activity of chitotriosidase and angiotensin converting enzyme decreased. However, myoclonic movement and generalized seizure occurred at the age of 19 months and antiepileptic drug was started. Other neurological deterioration including supranuclear gaze palsy and developmental delay also persisted. A new therapy to overcome neurologic problems should be developed for patients with type 3 GD.

• Journal of Ginseng Culture
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• v.2
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• pp.39-70
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• 2020

In this paper, through the mutual interpretation and verification of the ancient Korean history books with different origin that have been suspected as false documents, it proves that they could be logically real records and reveal that the substance of the legendary 'medicine for anti-aging and longevity', which also had been mentioned in Chinese old books, is Korean ginseng. Furthermore, with reference to the modern Y chromosomal map of the migratory routes of mankind corresponding to these routes recorded in 「Budoji」, the core history book, the formation of the four ethnic constitution groups (Sasang Constitution) based on the life style of each human group has been estimated. And the cause of Korean ginseng with fever problem for Southeast Asians is their pharmacogenomic constitution problem by protopanaxatriol (PPT) type ginsenosides in ginseng. It was resolved with over production of protopanaxdiol (PPD) type ginsenosides against PPT type in Korean red ginseng as historical or scientific point of view. In addition, by explaining that the processing method to Korean red ginseng could increase red ginseng acidic polysaccharides (RGAP), the RGAP, PPD type ginsenosides, and arginine which is originally abundant in Korean ginseng could increase the expression of the 'heat shock proteins' as a kind of chaperone in the body, this paper presents the theory allowing the scientific interpretation of the efficacy of Korean red ginseng as an 'adaptogen' or 'medicine for anti-aging and longevity'. Lastly, through the consideration of the growing environment of American ginseng and Korean ginseng, the differences are presented.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.1 s.307
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• pp.9-16
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• 2006

This Paper proposes an adaptive error diffusioThis paper proposes an adaptive error diffusion algorithm for text enhancement followed by an efficient text segmentation that uses the maximum gradient difference (MGD). The gradients are calculated along with scan lines, and the MGD values are filled within a local window to merge the potential text segments. Isolated segments are then eliminated in the non-text region filtering process. After the left segmentation, a conventional error diffusion method is applied to the background, while the edge enhancement error diffusion is used for the text. Since it is inevitable that visually objectionable artifacts are generated when using two different halftoning algorithms, the gradual dilation is proposed to minimize the boundary artifacts in the segmented text blocks before halftoning. Sharpening based on the gradually dilated text region (GDTR) prevents the printing of successive dots around the text region boundaries. The error diffusion algorithm with edge enhancement is extended to halftone color images to sharpen the tort regions. The proposed adaptive error diffusion algorithm involves color halftoning that controls the amount of edge enhancement using a general error filter. The multiplicative edge enhancement parameters are selected based on the amount of edge sharpening and color difference. Plus, the additional error factor is introduced to reduce the dot elimination artifact generated by the edge enhancement error diffusion. By using the proposed algorithm, the text of a scanned image is sharper than that with a conventional error diffusion without changing background.

• Applied Chemistry for Engineering
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• v.28 no.6
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• pp.632-637
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• 2017

The vehicle lubricant occupies upto 35% in a total lubricant market and engine oil occupies upto 77% in the vehicle lubricant market in Korea. A suitable quality management of the circulating engine oil is necessary for driver and engine protection. But, KS and synthetic engine oil products (involved over 30% synthetic oil) are exempt to any quality management under Petroleum and Alternative Fuel Business Act. It is also known that synthetic oils such as PAO (poly alpha olefin) have excellent properties and performance like anti-wear, varnish control and oxidation stability than those of mineral oils. For this reason, PAO has been used for an engine oil, rotary screw and reciprocating compressor in addition to heavy duty and other extreme service applications. In this study, our research group analyzed the chromatogram pattern for the mineral oil, PAO and mineral oil involved a typical ratio of PAO using SIMDIST (simulated distillation). In the SIMDIST chromatogram, the mineral oil showed a broad peak, while PAO showed a sharp typical peak. Also the oil with a large viscosity grade exhibited a long retention time due to the heavy molecular weight and high boiling point. In particular, the blended mineral oil with 20% PAO sample showed a distinctly different pattern compared to that of using the conventional mineral oil. For monitoring PAO contents in distributing engine oils, we analyzed the SIMDIST for 27 kinds of engine oils which were popularly sold in Korea. The analytic results indicate that all kinds of engine oils showed that PAO contents were below 20% in engine oil products. Moreover, the PAO titled product was found to have a small amount of PAO. Thus, we conclude that the related laws for the proper quality management of synthetic oils are needed to be established.

• Journal of The Korean Society of Inherited Metabolic disease
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• v.13 no.1
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• pp.37-42
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• 2013

Gaucher disease is a lysosomal storage disease caused by deficiency of glucocerebrosidase (GBA). This condition is characterized by accumulation of glucocerebrosidase in liver, spleen, lung, skeletal system, and central nervous system. Gaucher disease is the prototype of disease in which efficacy of enzyme replacement therapy has been established. However, because recombinant enzyme is not able to enter the central nervous system, its efficacy is limited to the non-neurological manifestations of Gaucher disease. Importantly, approximately a half of Korean patients with Gaucher disease suffer from neurological manifestations. In addition, Korean Gaucher disease patients exhibit distinct mutation spectrum from those in other populations. Common mutations in Korean patients with Gaucher disease are also associated with neurological phenotype. Therefore, therapeutic strategies tailored to Korean patients were necessary. Interestingly, a chemical chaperone, ambroxol, has been known to increase residual enzymatic activities of the select mutant GBAs encoded by mutations prevalent in Korean patients. One promising aspect of this drug is that it can cross blood-brain barrier, and enhance the enzyme activity in the brain. In vitro study suggested this chemical chaperone as one of new therapeutic agents in Gaucher disease, and a well-designed human trial is required to confirm its efficacy.