• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.101-108
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• 2021

This paper builds a real-time home security system based on the OneNet cloud platform to control the status of the house through a smartphone. The system consists of a local part and a cloud part. The local part has I/O devices, router and Raspberry Pi (RPi) that collects and monitors sensor data and sends the data to the cloud, and the Flask web server is implemented on a Rasberry Pi. When a user is at home, the user can access the Flask web server to obtain the data directly. The cloud part is OneNet in China Mobile, which provides remote access service. The hybrid App is designed to provide the interaction between users and the home security system in the smartphone, and the EDP and RTSP protocol is implemented to transmit data and video stream. Experimental results show that users can receive sensor data and warning text message through the smartphone and monitor, and control home status through OneNet cloud.

• Journal of Radiation Protection and Research
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• v.47 no.3
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• pp.111-133
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• 2022

The exciting advancement related to the "modeling of digital human" in terms of a computational phantom for radiation dose calculations has to do with the latest hype related to deep learning. The advent of deep learning or artificial intelligence (AI) technology involving convolutional neural networks has brought an unprecedented level of innovation to the field of organ segmentation. In addition, graphics processing units (GPUs) are utilized as boosters for both real-time Monte Carlo simulations and AI-based image segmentation applications. These advancements provide the feasibility of creating three-dimensional (3D) geometric details of the human anatomy from tomographic imaging and performing Monte Carlo radiation transport simulations using increasingly fast and inexpensive computers. This review first introduces the history of three types of computational human phantoms: stylized medical internal radiation dosimetry (MIRD) phantoms, voxelized tomographic phantoms, and boundary representation (BREP) deformable phantoms. Then, the development of a person-specific phantom is demonstrated by introducing AI-based organ autosegmentation technology. Next, a new development in GPU-based Monte Carlo radiation dose calculations is introduced. Examples of applying computational phantoms and a new Monte Carlo code named ARCHER (Accelerated Radiation-transport Computations in Heterogeneous EnviRonments) to problems in radiation protection, imaging, and radiotherapy are presented from research projects performed by students at the Rensselaer Polytechnic Institute (RPI) and University of Science and Technology of China (USTC). Finally, this review discusses challenges and future research opportunities. We found that, owing to the latest computer hardware and AI technology, computational human body models are moving closer to real human anatomy structures for accurate radiation dose calculations.

• The Journal of Korean Academy of Prosthodontics
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• v.37 no.5
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• pp.581-596
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• 1999

The purpose of this study was to investigate the stress distribution of the abutment and sup-porting tissues according to the slopes and types of the guiding plane of distal extension removable partial dentures. The 3-dimensional finite element method was used and the finite element models were prepared as follows. Model I : Kratochvil type guiding plane with $90^{\circ}$ to residual ridge Model II : Kratochvil type guiding plane with $95^{\circ}$ to residual ridge Model III : Kratochvil type guiding plane with $100^{\circ}$ to residual ridge Model IV : Krol type guiding plane with $90^{\circ}$ to residual ridge Distal extension partial denture which right mandibular first and second molar were lost was used and the second premolar was prepared as primary abutment with RPI type retainer. Then 150N of compressive force was applied to central fossae of the first and second molars and von Mises stress and displacement were measured. The results were as follows 1. Model I and Model IV showed a similar stress distribution pattern and the stress was concentrated on the apex of the root of the abutment. 2. The stress was increased and concentrated on mesial side of the root of the abutment in Model II. The stress was concentrated on buccal and mesiobuccal side of the root of the abutment in Model IV. 3. In Model I, the root of the abutment displaced and twisted a little in clockwise. In Model IV, the root of the abutment displaced to distolingually at apical region of the root and mesiobuccally at cervical region of the root. 4. In Model II, the root of the abutment displaced to mesiolingually at apical region of the root and more displaced and twisted in counterclockwise at cervical region of the root. In Model III, the root of the abutment displaced to mesiobucally at apical region of the root and more displaced and twisted in clockwise at cervical region of the root.

• Journal of Chest Surgery
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• v.29 no.3
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• pp.271-277
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• 1996

In selected cases, early corrective surgery is indicated in the management of infants having large ventricular septal defects. The risk of any surgical procedure in infancy is acknowledged to be great and should be avoided whenever possible. However this greater surgical risk is justified when the patient presents with intractable congestive heart failure, severe pulmonary hypertension, marked growth retardation, and recurrent prolonged lower respiratory infections. We analyzed 31 patients with ventricular septal defect in infancy who underwent surgical correction from January 1991 through December 1994. Age ranged from 6 months to 12 months with mean age of 9.2 months. Of the thirty-one patients, 23 patients were male and 8 patients were female. Mean body weight was 7. 4kg. The most common type of ventricular septal defect was perimembraneo s (64.5%). Associated cardiac anomalies were found in 17 patients (55.8%). Mitral regurgitation was the most commonly associated cardiac anomaly (16.1 %) and followed by patent ductus arteriosus (12.9%). When cardiac catheterization data were analysed, the most common range of Qp/qs, RpiRs, Pp/ps were 2.1∼ 3.0, 1-0.25, above 0.70 respectively. Among the indications of surgical correction, there were pulmonary hypertension in 20 patients, congestive heart failure in 3 patients, intractable respiratory infection in 10 patients and growth retardation in 14 patients. The most common surgical approach and method for closure of ventricular septal defect .were right atriotomy (58%) and Dacron patch closure (94%). Postoperative complications occurred in 10 cases (32%) and overall mortality was 12.9% (4 cases). All operative deaths in this series occurred in infants under the age of 8 months and weight of 8 kilograms.

• Research in Plant Disease
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• v.12 no.3
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• pp.260-266
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• 2006

Pythium blight caused by Pythium spp. is one of major diseases in putting green of golf course. In this study, microorganisms which are anatgonistic to Pythium aphanidermatum, a pathogen of pythium blight, were selected primary through in vitro tests, dual culture method and triple layer agar diffusion method. In vivo test against pythium blight were conducted to select the best candidate biocontrol microorganism by pot experiment in a plastic house. Bacillus subtilis GB-0365 was finally selected as a biocontrol agent against pythium blight. Relative Performance Indies(RPI) was used as a criterion of selecting potential biocontrol agent. B. subtilis GB-0365 showed resistance to major synthetic agrochemicals used in golf course. Alternative application of synthetic agrochemicals and B. subtilis GB-0365 was most effective to successfully contol pythium blight. B. subtilis GB-0365 suppressed the development of pythium bight of bentgrass by 56.4% as compared to non-treated control and its disease control efficacy was 60.9% of a synthetic fungicide Oxapro(WP) efficacy. B. subtilis GB-0365 has a potential to be a biocontrol agent for control of pythium blight.

• Journal of Science and Technology Studies
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• v.18 no.3
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• pp.153-216
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• 2018

The contemporary practices of Big-Data based automated decision making algorithms are widely deployed not just because we expect algorithmic decision making might distribute social resources in a more efficient way but also because we hope algorithms might make fairer decisions than the ones humans make with their prejudice, bias, and arbitrary judgment. However, there are increasingly more claims that algorithmic decision making does not do justice to those who are affected by the outcome. These unfair examples bring about new important questions such as how decision making was translated into processes and which factors should be considered to constitute to fair decision making. This paper attempts to delve into a bunch of research which addressed three areas of algorithmic application: criminal justice, law enforcement, and national security. By doing so, it will address some questions about whether artificial intelligence algorithm discriminates certain groups of humans and what are the criteria of a fair decision making process. Prior to the review, factors in each stage of data mining that could, either deliberately or unintentionally, lead to discriminatory results will be discussed. This paper will conclude with implications of this theoretical and practical analysis for the contemporary Korean society.