• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.204-212
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• 2023

Diabetes is a condition that can be brought on by a variety of different factors, some of which include, but are not limited to, the following: age, a lack of physical activity, a sedentary lifestyle, a family history of diabetes, high blood pressure, depression and stress, inappropriate eating habits, and so on. Diabetes is a disorder that can be brought on by a number of different factors. A chronic disorder that may lead to a wide range of complications. Diabetes mellitus is synonymous with diabetes. There is a correlation between diabetes and an increased chance of having a variety of various ailments, some of which include, but are not limited to, cardiovascular disease, nerve damage, and eye difficulties. There are a number of illnesses that are connected to kidney dysfunction, including stroke. According to the figures provided by the International Diabetes Federation, there are more than 382 million people all over the world who are afflicted with diabetes. This number will have risen during the years in order to reach 592 million by the year 2035. There are a substantial number of people who become victims on a regular basis, and a significant percentage of those people are uninformed of whether or not they have it. The individuals who are most adversely impacted by it are those who are between the ages of 25 and 74 years old. This paper reviews about various machine learning techniques used to detect diabetes mellitus.

• Journal of Advanced Marine Engineering and Technology
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• v.8 no.1
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• pp.17-36
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• 1984

Since 1973, the competition on the development of fuel saving type internal combustion engines has become severe by the two times oil shock, and new type engines are reported every several months. Whenever these new type engines are developed, new designs are required and they will be offered in the market after performing the endurance test for a long time. But the engine market is faced with a heavy burden of finance, as the developing of a new engine requires tremendous expenses. For this reason, the computer simulation method has been lately developed to cope with it. The computer simulation method can be available to perform the reasonable research works by the theoretical analysis before carrying out practical experiments. With these processes, the developing expenses are cut down and the period of development is curtailed. The object of this study is the development of simulation computer program for the small naturally aspirated four-stroke diesel engine which is intended to product by the original design of our country. The process of simulation is firstly investigated for the ideal engine cycle, and secondly for the real engine cycle. In the ideal engine cycle, each step of the cycle is simulated by the energy balance according to the first law of thermodynamics, and then the engine performance is calculated. In the real cycle imulation program, the injection rate, the preparation rate and the combustion rate of fuel and the heat transfer through the wall of combustion chamber are considered. In this case, the injection rate is supposed as constant through the crank angle interval of injection and the combustion rate is calculated by the Whitehouse-Way equation and the heat transfer is calculated by the Annand's equation. The simulated values are compared with measured values of the YANMAR NS90(C) engine and Mitsubishi 4D30 engine, and the following conclusions are drawn. 1. The heat loss by the exhaust gas is well agree with each other in the lower load, but the measured value is greater than the calculated value in the higher load. The maximum error rate is about 15% in the full load. 2. The calculated quantity of heat transfer to the cooling water is greater than the measured value. The maximum error rate is about 11.8%. 3. The mean effective pressure, the fuel consumption, the power and the torque are well agree with each other. The maximum error is occurred in the fuel consumption, and its error rate is about 7%. From the above remarks, it may be concluded that the prediction of the engine performance is possibly by using the developed program, although the program needs to reform by adding the simulation of intake and exhaust process and assumping more reliable mechanical efficiency, volumetric efficiency, preparation rate and combustion rate.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.1
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• pp.47-52
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• 2013

The higher energy efficiency for ship and the lower pollution for global environment are required strictly. However the performance of marine diesel engine is gradually deteriorated with time. And also the operation condition is varied with sea conditions. Hence the optimization for operating condition of marine engines is needed for energy saving and environment kindly. In this paper, it was attempted to investigate the influence of aging for marine diesel engine. The deterioration of engine performance is assessed by the calculation results of the simulation program for two-stroke marine diesel engine developed by author which was reported before. And three parameters for deterioration of engine performance were considered such as lower efficiency of turbocharger by fouling, increase of blow-by gas due to wear of cylinder liner and getting worse of combustion by poor injection. By the results, it was shown that the influence of engine performance by aging was relatively not so small - 10.4 bar low in Pmax and 3.2% decrease in Pmi.

• Journal of the Korean Society of Propulsion Engineers
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• v.19 no.1
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• pp.68-75
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• 2015

In this paper, unsteady characteristics of pressure in solid rocket motor were analyzed by using response of pintle actuation, pressure and thrust data from ground test. Pressure and thrust in solid rocket motor can be controlled in real time by varying nozzle throat area with pintle, installed in the valve. Unsteady characteristics of pressure can be observed in this system occurred by various reasons. Two critical reasons, error of pintle actuation and ablation of center tube, are found and effects of each reason can be analyzed individually by re-prediction of pressure with response of pintle actuation and analyzing thrust to pressure ratio.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.6
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• pp.219-225
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• 2019

There is a problem with the existing method of selecting the difficulty levels of Hanja characters. Some Hanja characters selected by the existing methods are different from Sino-Korean words used in real life and it is impossible to know how many times the Hanja characters are used. To solve this problem, we measure the difficulty of Hanja characters using the multiple regression analysis with the frequency as the features. Based on the elementary textbooks, FWS and FHU are counted. A questionnaire is written using the two frequencies and stroke together to answer the appropriate timing of learning the Hanja characters and use them as target variables for regression. Use stepwise regression to select the appropriate features and perform multiple linear regression. The R² score of the model was 0.1105 and the RMSE was 0.1105.

• Design & Manufacturing
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• v.16 no.4
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• pp.1-6
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• 2022

Fine blanking is a press processing technology that can process most of the product thickness into a smooth surface with a single stroke. In this fine blanking process, shear is an essential step. The punches and dies used in the shear are subjected to impacts of tens to hundreds of gravitational accelerations, depending on the type and thickness of the material. Therefore, among the components of the fine blanking mold (dies), punches and dies are the parts with the shortest lifespan. In the actual production site, various types of tool damage occur such as wear of the tool as well as sudden punch breakage. In this study, machine learning algorithms were used to predict these problems in advance. The dataset used in this paper consisted of the signal of the vibration sensor installed in the tool and the measured burr size (tool wear). Various features were extracted so that artificial intelligence can learn effectively from signals. It was trained with 5 features with excellent distinguishing performance, and the SVM algorithm performance was the best among 33 learning models. As a result of the research, the vibration signal at the time of imminent tool replacement was matched with an accuracy of more than 85%. It is expected that the results of this research will solve problems such as tool damage due to accidental punch breakage at the production site, and increase in maintenance costs due to prediction errors in punch exchange cycles due to wear.

• The Korea Journal of Herbology
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• v.38 no.6
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• pp.73-91
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• 2023

Objectives : This study used a network pharmacology approach to elucidate the efficacy and molecular mechanisms of Daehwangmokdanpitang (DHMDPT) on Psoriasis. Methods : Using OASIS databases and PubChem database, compounds of DHMDPT and their target genes were collected. The putative target genes of DHMDPT and known target genes of psoriasis were compared and found the correlation. Then, the network was constructed using Cytoscape 3.10.1. The key target genes were screened by Analyzer network and their functional enrichment analysis was conducted based on the Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathways to predict the mechanisms. Results : The result showed that total 30 compounds and 439 related genes were gathered from DHMDPT. 264 genes were interacted with psoriasis gene set, suggesting that the effects of DHMDPT are closely related to psoriasis. Based on GO enrichment analysis and KEGG pathways, 'Binding', 'Cytokine Activity', 'Receptor Ligand Activity' 'HIF-1 signaling pathway', 'IL-17 signaling pathway', 'Toll-like receptor signaling pathway', and 'TNF signaling pathway' were predicted as functional pathways of 16 key target genes of DHMDPT on psoriasis. Among the target genes, IL6, IL1B, TNF, AKT1 showed high correlation with the results of KEGG pathways. Additionally, Emodin, Acetovanillone, Gallic acid, and Ferulic acid showed a high relevance with key genes and their mechanisms. Conclusion : Through a network pharmacological method, DHMDPT was predicted to have high relevance with psoriasis. This study could be used as a basis for studying therapeutic effects of DHMDPT on psoriasis.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.7
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• pp.683-689
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• 2017

We have carried out the development for hydraulic breaker which can be operated by optimal mode with ICT convergence technology. This developed system can predict the rock properties. Moreover, this system can maximize the energy efficient with intelligent control of hydraulic system. In order to provide the optimal impact force, this system can measure the descending depth of piston with the proximity sensor and discriminate the rock properties with the measuring data and control the piston stroke using solenoid valve eventually. In addition, we have developed the controller, display module and operating device for cascade (multi-level impact) system and applied the module which can communicate each system by wireless communications. In conclusion, the control system which can control the multi-level impact in accordance with strength of rocks has been developed and approved by several field tests.

• Journal of Biomedical Engineering Research
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• v.25 no.6
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• pp.479-487
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• 2004

Biopotential signals have been used as command in systems using electrical stimulation of motor nerves to restore movement after an injury to the central nervous system (CNS). In order to use the voluntary EMG (electromyography) among the biopotentials as a control signal for the electrical stimulation of the same muscle for CNS injury patients, it is necessary to remove M-wave of having high magnitude from raw data. We designed an optimal filter for removing the M-wave and preserving the voluntary EMG and showed that the optimal filter is eigen filter. We also proved that the previous method using the prediction error filter(PEF) is a suboptimal filtering in the sense of preserving the voluntary EMG. On basis of the data obtained from a model for M-wave and voluntary EMG and from actual CNS injury patients, with false-positive rate analysis, the proposed adaptive filter showed a very promising performance in comparison with previous method.

• Sleep Medicine and Psychophysiology
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• v.24 no.1
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• pp.38-45
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• 2017

Objectives: Sleep disturbance is a very rapidly growing disease with aging. The purpose of this study was to investigate the prevalence of sleep disturbances and its predictive factors in a three-year cohort study of people aged 60 years and over in Korea. Methods: In 2012 and 2014, we obtained data from a survey of the Korean Social Life, Health, and Aging Project. We asked participants if they had been diagnosed with stroke, myocardial infarction, angina pectoris, arthritis, pulmonary tuberculosis, asthma, cataract, glaucoma, hepatitis B, urinary incontinence, prostate hypertrophy, cancer, osteoporosis, hypertension, diabetes, hyperlipidemia, or metabolic syndrome. Cognitive function was assessed using the Mini-Mental State Examination for dementia screening in 2012, and depression was assessed using the Center for Epidemiologic Studies Depression Scale in 2012 and 2014. In 2015, a structured clinical interview for Axis I psychiatric disorders was administered to 235 people, and sleep disturbance was assessed using the Pittsburgh Sleep Quality Index. The perceived stress scale and the State-trait Anger Expression Inventory were also administered. Logistic regression analysis was used to predict sleep disturbance by gender, age, education, depression score, number of coexisting diseases in 2012 and 2014, current anger score, and perceived stress score. Results: Twenty-seven percent of the participants had sleep disturbances. Logistic regression analysis showed that the number of medical diseases three years ago, the depression score one year ago, and the current perceived stress significantly predicted sleep disturbances. Conclusion: Comorbid medical disease three years previous and depressive symptoms evaluated one year previous were predictive of current sleep disturbances. Further studies are needed to determine whether treatment of medical disease and depressive symptoms can improve sleep disturbances.