• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.2-5
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• 2022

Human organs in the body have a complex structure, and in particular, the small intestine is about 7m long, so endoscopy is not easy and the risk of endoscopy is high. Currently, the test is performed with a capsule endoscope, and the test time is very long. The doctor connects the removed storage device to the computer to store the patient's capsule endoscope image and reads it using a program, but the capsule endoscope test results in a long image length, which takes a lot of time to read. In addition, in the case of the small intestine, there are many curves due to villi, so the occlusion area or light and shade of the image are clearly visible during the examination, and there may be cases where lesions and abnormal signs are missed during the examination. In this paper, we provide a method of assisting small intestine capsule endoscopic lesion examination using artificial neural networks to shorten the doctor's image reading time and improve diagnostic reliability.

• Journal of Environmental Health Sciences
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• v.49 no.2
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• pp.108-117
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• 2023

Background: When particles are absorbed into the human body, they penetrate deep into the lungs and interact with the tissues of the body. Heavy metals in PM_2.5 can cause various diseases. The main source of PM_2.5 emissions in South Korea's atmosphere has been surveyed to be places of business. Objectives: The concentration of heavy metals in PM_2.5 near the Ulsan Industrial Complex was measured and a health risk assessment was performed for residents near the industrial complex for exposure to heavy metals in PM_2.5. Methods: Concentrations of heavy metals in PM_2.5 were measured at four measurement sites (Ulsan, Mipo, Onsan, Maegok) near the industrial complexes. Heavy metals were analyzed according to the Air Pollution Monitoring Network Installation and Operation Guidelines presented by the National Institute of Environmental Research. Among them, only five substances (Mn, Ni, As, Cd, Cr⁶⁺) were targeted. The risk assessment was conducted on inhalation exposure for five age groups, and the excess cancer risk and hazard quotient were calculated. Results: In the risk assessment of exposure to heavy metals in PM_2.5, As, Cd, and Cr⁶⁺ exceeded the risk tolerance standard of 10^-6 for carcinogenic hazards. The highest hazard levels were observed in Onsan and Mipo industrial complexes. In the case of non-carcinogenic hazards, Mn was identified as exceeding the hazard tolerance of 1, and it showed the highest hazard in the Ulsan Industrial Complex. Conclusions: This study presented a detailed health risk from exposure to heavy metals in PM_2.5 by industrial complexes located in Ulsan among five age groups. It is expected to be utilized as the basis for preparing damage control and industrial emission reduction measures against PM_2.5 exposure at the Ulsan Industrial Complex.

• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.459-462
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• 2021

The article examines the main problems of land market formation in Ukraine. The article is devoted to the study of problems and prospects of land market introduction after the abolition of the ban on alienation. The advantages and disadvantages of lifting the moratorium on the purchase and sale of agricultural land are highlighted. The experience of such European countries as France, Germany, Latvia, Romania and Poland in regulating the market of agricultural lands is analyzed. The historical stages of market formation, features of state policy in this area are considered. The authors found that in these countries the market for agricultural land is well developed and works effectively, which has positive consequences for the economy of these countries. After analyzing the experience, we identified common elements of an effective mechanism for regulating the land market in European countries, which can be implemented in Ukraine. It is emphasized that after the opening of the land market it is necessary to prevent the concentration of a large number of agricultural lands in the hands of one person or close persons and it is necessary to create an effective supervisory body, whose main functions will be supervising sales prevention of speculation in the land market. Emphasis is placed on the need to improve legislation in the field of land, organizational and informational conditions for land reform. The Law of Ukraine "On Amendments to Certain Legislative Acts of Ukraine Concerning the Circulation of Agricultural Land" was analyzed, the adoption of which put an end to the systematic extension of the moratorium on the sale of agricultural land. The positive aspects of such reservations are noted, such as the gradual introduction of the land market, quantitative restrictions, the lower limit of the value equivalent, which can not be less than the normative monetary value. At the same time, the problem is that the lack of an imperative norm on termination of the lease agreement in case of refusal of the lessee to purchase such land at a price not lower than expert assessment, will negatively affect its price formation and actually make the landlord hostage.

• Journal of the Korean earth science society
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• v.34 no.3
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• pp.235-248
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• 2013

The purpose of this study is to investigate a feasibility of a small mountain as a field work site on geological features in Earth sciences classes at all levels. Mt. Geumdang with the height of 305 meters from the sea level is located in the metropolitan city of Gwangju, southern part of Korea. The study reviews the human and natural geography, geological features, geomorphic resources, landscapes, and conveniences of the mountain for a possibility of meaningful field work. The population within the distance of 5 km from the mountain stands at about 620,000 and 170,000 of them are students and teachers. Mt. Geumdang has a warm temperature climate with low rainfall throughout the year, so it seems suitable for a field survey. Road network and public transportation system around the area are well-developed and easily accessible. Mt. Geumdang shows various rock type and geological structures. The basement rock is Gwangju granite, which is plutonic body of the Jurassic period. Also, granophyre (micrographic granite) and various volcanic rocks distributed as bedded tuff, lapilli tuff, and rhyolite of the Cretaceous period. Many andesitic and felsic dykes were intruded into the rock by joint system. In Mt. Geumdang, many geomorphic resources are found such as U shaped mountain, joint, fault, lamination, gnamma, tor, cliff, groove, block stream and block field, regolith, and saprolite. It has a beautiful mountain scenery including the view of whole shape of Mt. Mudeung, panoramic view of the town, Pungam lake, World Cup stadium and sunrise and sunset. Furthermore, the area has ecologic study facilities related to geology, emergency medical and convenience facilities for field works. In conclusion, Mt. Geumdang is highly feasible for geological field studies at all levels.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.4
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• pp.1318-1324
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• 2010

Recently, U-Healthcare is receiving attentions as a research for reducing the manpower, time in treatment, and etc. Although fundamental technologies, such as sensing, measuring, and etc. are sufficiently investigated. However, Technologies of IT/Medical convergence, which graft IT technologies to medical area, are still in germ. For this, we present a novel healthcare system, which can be applied to the middle sized medical environment, such as private hospital, home, or etc., by means of pre-verified technologies and the expert system. There exist IT element technologies are sufficiently developed in the fields, such as network, database or etc. due to the remarkable developments in IT technologies, and the healthcare is a mission-critical environment. Therefore, it is important not only to investigate novel approaches but also to utilize verified technologies for the U-Healthcare solution. Presented solution provisions automated medical services based on expert system by utilizing the measured data, such as body fat, blood pressure, blood glucose, and etc., in order to provide convenient treatment environment to doctors and nurses. In addition, since people, who do not have medical knowledge, can self-diagnose themselves, it is expected to cut medical costs in various areas. Especially, since each devices communicate with each other through standardized Bluetooth technology, Presented healthcare system is an extensible solution which can easily accept various medical devices. As a result of this, we can safely say that the self measurement and diagnosis services in U-Healthcare are now enhanced by reducing medical cost through our healthcare system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.6C
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• pp.476-482
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• 2012

In this paper, we analyze and compare several co-channel interference mitigation algorithms for WBAN application in 2.4 GHz ISM frequency bands. ML (Maximum Likelihood), OC (Optimal Combining) and MMSE (Minimum Mean Square Error) has been considered for the possible techniques for interference cancellation in view of the trade off between the performance and the complexity of implementation. Based on the channel model of IEEE 802.15.6 standard, simulation results show that ML and OC attains the lower BER performance than that of MMSE if we assume the perfect channel estimation. But, ML and OC have the additional requirement of implementation for his own and other users's channel estimation process, hence, besides the BER performance, the complexity of implementation and the sensitivity to channel estimation error should be considered since it requires the simple and small sized equipment for WBAN system application. In addition, the gap of detection BER performance between ML, OC and MMSE is much decreased under the imperfect channel estimation if we adopt real channel estimation process, therefore, in order to apply to WBAN system, the trade off between the BER performance and complexity of implemetation should be seriously considered to decide the best co-channel interference cancellation for WBAN system application.

• Journal of Service Research and Studies
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• v.5 no.2
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• pp.15-24
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• 2015

The trade balance for the information and communications technology (ICT) industries in 2014 have reached 863 hundred million dollars as the main export products such as smart phone and semi-conductor increase, since the ICT industries have played an important role in economic growth in Korea. Until now, the consistent supporting of government and investment of company have been doing with the growth of ICT industries, as a result, Korea marked as the first in the UN electronic government preparing index, and rank 12 in the network preparing index through the policy of national information and basic plan of inter-industry convergence. However, as the unstable international economic circumstances, ICT industries is faced with the stagnation, and then preemptive development of products and services for ICT convergence industries is needed to continually get definite ICT Korea image. In this paper, the ICT convergence industry is analyzed and forecasted. In specific, the international and domestic market for cloud, 3D convergence, and internet of things is diagnosed. The market for ICT convergence industries is predicted to be 3.6 trillion dollar in the world, and 110 trillion won in domestic. From the analytical results for technology and services development, the preemptive supporting of the technology development and policy for the internet of things and 3D convergence industries is required. In addition to, through the future forecasting by socio-tech matrix method, the policy supporting for the ICT convergence area of healthcare, fintech, artificial intelligence, body platform, and human security is needed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.12
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• pp.1318-1327
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• 2012

With the recent increased risk of livestock disease spread and human infection, livestock disease control has become very important. Consequently, there has been an increased attention on an implantable real-time monitoring and traceability system for individual cattle. Therefore, we have developed a robust monitoring and traceability system based on an implantable MFAN/RFID sensor tag. Our design combines the MFAN technology that is capable of robust wireless communication within cattle sheds and the 900MHz RFID technology that is capable of wireless communication without battery. In MFAN/RFID implantable sensor tag monitoring system, UHF sensor tag is implanted under the skin and accurately monitors the body temperature and biological changes without being affected by external environment. In order to acquire power needed by the tag, we install a MFAN/RFID tranceiver on the neck of cattle. The MFAN coordinator passes through the MFAN node and the RFID-reader-combined MFAN/RFID transceiver and transmits/receives the data and power for the sensor tag. The data stored in the MFAN coordinator is transmitted via the internet to the livestock history monitoring system, where it is stored and managed. By developing this system, we hope to alleviate the problems related to livestock disease control.

• Korean Journal of Radiology
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• v.22 no.11
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• pp.1909-1917
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• 2021

Objective: Muscle quantity and quality can be measured with an automated system on CT. However, the effects of contrast phases on the muscle measurements have not been established, which we aimed to investigate in this study. Materials and Methods: Muscle quantity was measured according to the skeletal muscle area (SMA) measured by a convolutional neural network-based automated system at the L3 level in 89 subjects undergoing multiphasic abdominal CT comprising unenhanced phase, arterial phase, portal venous phase (PVP), or delayed phase imaging. Muscle quality was analyzed using the mean muscle density and the muscle quality map, which comprises normal and low-attenuation muscle areas (NAMA and LAMA, respectively) based on the muscle attenuation threshold. The SMA, mean muscle density, NAMA, and LAMA were compared between PVP and other phases using paired t tests. Bland-Altman analysis was used to evaluate the inter-phase variability between PVP and other phases. Based on the cutoffs for low muscle quantity and quality, the counts of individuals who scored lower than the cutoff values were compared between PVP and other phases. Results: All indices showed significant differences between PVP and other phases (p < 0.001 for all). The SMA, mean muscle density, and NAMA increased during the later phases, whereas LAMA decreased during the later phases. Bland-Altman analysis showed that the mean differences between PVP and other phases ranged -2.1 to 0.3 cm² for SMA, -12.0 to 2.6 cm² for NAMA, and -2.2 to 9.9 cm² for LAMA.The number of patients who were categorized as low muscle quantity did not significant differ between PVP and other phases (p ≥ 0.5), whereas the number of patients with low muscle quality significantly differed (p ≤ 0.002). Conclusion: SMA was less affected by the contrast phases. However, the muscle quality measurements changed with the contrast phases to greater extents and would require a standardization of the contrast phase for reliable measurement.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.