• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.331-339
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• 2016

This paper developed a home wellness robot platform to perform the roles in basic health care and life care in an aging society. A robotic platform and a sensory platform were implemented for an indoor wellness service. In the robotic platform, the precise mobility and the dexterous manipulation are not only developed in a symbiotic service-robot, but they also ensure the robot architecture of human friendliness. The mobile robot was made in the agile system, which consists of Omni-wheels. The manipulator was made in the anthropomorphic system to carry out dexterous handwork. In the sensing platform, RF tags and stereo camera were used for self and target localization. They were processed independently and cooperatively for accurate position and posture. The wellness robot platform was integrated in a real-time system. Finally, its good performance was confirmed through live indoor tests for health and life care.

• The Korean Journal of Applied Statistics
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• v.28 no.1
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• pp.83-92
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• 2015

Concerning the national health, it is important to develop an accurate prediction method of atmospheric particulate matter (PM) because being exposed to such fine dust can trigger not only respiratory diseases as well as dermatoses, ophthalmopathies and cardiovascular diseases. The National Institute of Environmental Research (NIER) employs a decision tree to predict bad weather days with a high PM concentration. However, the decision tree method (even with the inherent unstableness) cannot be a suitable model to predict bad weather days which represent only 4% of the entire data. In this paper, while presenting the inaccuracy and inappropriateness of the method used by the NIER, we present the utility of a new prediction model which adopts boosting with quantile loss functions. We evaluate the performance of the new method over various ${\tau}$-value's and justify the proposed method through comparison.

• The KIPS Transactions:PartB
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• v.17B no.3
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• pp.239-248
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• 2010

Leukocyte in blood smear image provides significant information to doctors for diagnosis of patient health status. Therefore, it is necessary step to separate leukocyte from blood smear image among various blood cells for early disease prediction. In this paper, we present a saliency map and stepwise region merging based leukocyte segmentation method. Since leukocyte region has salient color and texture, we create a saliency map using these feature map. Saliency map is used for sub-image separation. Then, clustering is performed on each sub-image using mean-shift. After mean-shift is applied, stepwise region-merging is applied to particle clusters to obtain final leukocyte nucleus. The experimental results show that our system can indeed improve segmentation performance compared to previous researches with average accuracy rate of 71%.

• The Journal of the Convergence on Culture Technology
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• v.5 no.4
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• pp.467-472
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• 2019

Seaweeds are rich in in minerals, vitamins, proteins, and fiber, and are classified as green algae, and they are distributed on the coasts of Korea, East Asia, Oceania, etc. and are used as a health function material as well as food ingredients in our countries and countries. In this study, Codium fragile was extracted from ethanol and concentrated to confirm DPPH radical scavenging activity, SOD activity, FRAP and ABTS cation radical scavenging ability. As a result, DPPH scavenging activity was 0.83, 22.83, 38.27, 40.93, 45.60% at 6.25, 12.50, 25, 50 and $100{\mu}g/mL$, SOD-like activity were 23.13, 33.63, 33.93, 44.07 and 59.07%. FRAP and ABTS showed antioxidant activity in a concentration-dependent manner, as in the previous experiment. Therefore, this study confirmed that it can be used as a cosmetic material using Codium fragile, a natural material.

• Journal of the Korean Institute of Gas
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• v.22 no.6
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• pp.1-7
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• 2018

Currently chemical plant risk have been issued by occurring frequent accidents. Accidents can be generally composed of fire, explosion, release in chemical plant. In case of fire and explosion, accident victims are occurred immediately after accident but release accident, late emergency response cause damage to worker. Especially, there are many victims by late emergency response against chemical exposure to skin. In case of chemical exposure to skin, irreversible damage like death, blindness, burn can be prevented by washing immediately. Safety shower can provide the cleaning for chemical exposure to eye, skin. Most of chemical plants are built in 1980s so equipment become superannuated. In this reason, safety shower also cannot operate normally in emergency situation. Therefor safety shower should be managed by installation and management guideline. This study perform the establishment guideline for safety shower installation and inspection to increase the reliability.

• Journal of the Korea Convergence Society
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• v.10 no.9
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• pp.11-16
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• 2019

People are subject to time sanctions in a busy modern society. Therefore, people find it difficult to eat simple junk food and even exercise, which is bad for their health. As a result, the incidence of chronic diseases is increasing. Also, the importance of making accurate and appropriate inferences to individual characteristics is growing due to unnecessary information overload phenomenon. In this paper, we propose a knowledge reasoning model using association rules and cluster analysis of multi-contexts. The proposed method provides a personalized healthcare to users by generating association rules based on the clusters based on multi-context information. This can reduce the incidence of each disease by inferring the risk for each disease. In addition, the model proposed by the performance assessment shows that the F-measure value is 0.027 higher than the comparison model, and is highly regarded than the comparison model.

• Journal of the Korea Society of Computer and Information
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• v.26 no.6
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• pp.19-28
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• 2021

Nowadays, interest in health care is increasing due to Coronavirus (COVID-19), and a lot of people are doing home training as there are more difficulties in using fitness centers and public facilities that are used together. In this paper, we propose a personalized exercise recommendation algorithm using personalized propensity information to provide more accurate and meaningful exercise recommendation to home training users. Thus, we classify the data according to the criteria for obesity with a k-nearest neighbor algorithm using personal information that can represent individuals, such as eating habits information and physical conditions. Furthermore, we differentiate the exercise dataset by the level of exercise activities. Based on the neighborhood information of each dataset, we provide personalized exercise recommendations to users through a dimensionality reduction algorithm (SVD) among model-based collaborative filtering methods. Therefore, we can solve the problem of data sparsity and scalability of memory-based collaborative filtering recommendation techniques and we verify the accuracy and performance of the proposed algorithms.

• Convergence Security Journal
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• v.18 no.5_1
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• pp.19-24
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• 2018

For a long time now, general-purpose processors have provided dedicated hardware / software tracing modules to provide developers with tools to fix bugs. A hardware tracer generates its enormous data into a log that is used for both performance analysis and debugging. Processor Trace (PT) is a new hardware-based tracing feature for Intel CPUs that traces branches executing on the CPU, which allows the reconstruction of the control flow of all executed code with minimal labor. Hardware tracer has been integrated into the operating system, which allows tight integration with its profiling and debugging mechanisms. However, in the Windows environment, existing studies related to PT focused on decoding only one flow in sequence. In this paper, we propose an extended PT decoder structure that provides basic data for real-time trace and malicious code detection using the functions provided by PT in Windows environment.

• Journal of the Korea Society of Computer and Information
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• v.26 no.2
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• pp.183-191
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• 2021

This study examined physiological activity of aronia chung with or without aspartame. High sugar content of food is recognized to induce chronic disease including diabetes and obesity. Sugar was replaced with aspartame to develop low-sugar aronia chung containing 0%, 25%, 50% and 75% aspartame based on sugar content of control in the study. Sweetness was the similar in the chungs with 0%, 25% and 50% aspartame but it was lower in the chung with 75% aspartame. pH was the highest in aronia chung with 75% aspartame as 2.95. Total phenolic content was the highest in aronia chung with 50% aspartame but it was not significantly different with 75% one. Flavonoid content increased with addition of aspartame and it was the highest in the chung with 75% aspartame as 206.60 ㎍ QEAC/mL. Reducing power also showed the same aspect with flavonoid content. However DPPH radical scavenging ability was the highest in aronia chung without aspartame and lowest in the chung with 75% aspartame. This result implies that the addition of aspartame could sustain the sweetness and improve the physiological activity of food at the same time although there is some limitation.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.5
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• pp.73-82
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• 2022

Chronic diseases such as hypertension require a differentiated approach according to age and life cycle. Chronic diseases such as hypertension require differentiated management according to the life cycle. It is also known that the cause of hypertension is a combination of various factors. This study uses machine learning prediction techniques to analyze various factors affecting hypertension by life cycle. To this end, a total of 35 variables were used through preprocessing and variable selection processes for the National Health and Nutrition Survey data of the Korea Centers for Disease Control and Prevention. As a result of the study, among the tree-based machine learning models, XGBoost was found to have high predictive performance in both middle and old age. Looking at the risk factors for hypertension by life cycle, individual characteristic factors, genetic factors, and nutritional intake factors were found to be risk factors for hypertension in the middle age, and nutritional intake factors, dietary factors, and lifestyle factors were derived as risk factors for hypertension. The results of this study are expected to be used as basic data useful for hypertension management by life cycle.