This review analyzes research trends related to new drug development using artificial intelligence from 2010 to 2022. This analysis organized the abstracts of 2,421 studies into a corpus, and words with high frequency and high connection centrality were extracted through preprocessing. The analysis revealed a similar word frequency trend between 2010 and 2019 to that between 2020 and 2022. In terms of the research method, many studies using machine learning were conducted from 2010 to 2020, and since 2021, research using deep learning has been increasing. Through these studies, we investigated the trends in research on artificial intelligence utilization by field and the strengths, problems, and challenges of related research. We found that since 2021, the application of artificial intelligence has been expanding, such as research using artificial intelligence for drug rearrangement, using computers to develop anticancer drugs, and applying artificial intelligence to clinical trials. This article briefly presents the prospects of new drug development research using artificial intelligence. If the reliability and safety of bio and medical data are ensured, and the development of the above artificial intelligence technology continues, it is judged that the direction of new drug development using artificial intelligence will proceed to personalized medicine and precision medicine, so we encourage efforts in that field.
Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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v.3
no.2
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pp.113-123
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2005
The removal of radioactive corrosion products from the reactor coolant through a magnetic filter system is one of the many approaches being investigated as a means to reduce radiation sources and exposures to the operational and maintenance personnel in a nuclear power plant. Many research activities in water chemistry, therefore, have been performed to provide a filtration system with high reliability and feasibility and are still in process. In this study, it was devised the magnetic filter system with permanent and electric magnets to remove the corrosion products in the coolant stream taking an advantage of the magnetic properties of corrosion particles. Permanent magnets were used for separation of corrosion products and electric magnets were utilized for flocculation of colloidal particles to increase in their size. Experiments using only permanent magnets, in the previous study, displayed the satisfactory outcome of filtering corrosion products and indicated that the removal efficiency was more than 90 $\%$ for above 5 $\mu$m particles. Experiments using electric magnets also showed the good performance of flocculation without chemical agents and exhibited that most corrosion particles were flocculated into larger aggregates about 5 $\mu$m and over in diameter. It is, thus, expected that the magnetic filter system with the arrangement of permanent and electric magnets will be an effective way for the removal of radioactive corrosion products with considerably high removal efficiency.
KSCE Journal of Civil and Environmental Engineering Research
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v.36
no.3
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pp.341-348
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2016
Harbor facilities require long-term durability and safety, and also maintain the performance requirement until the durability life. However, existing harbor facilities are becoming superannuated with durable years and durability is declined by erosion of the sea and damage from sea. In addition, harbor facilities will be in demand for the expansion of harbor and offshore structures with rising economic power by enhancement of domestic industry and increase of import and export. Therefore, in this study, two kinds of nondestructive test (NDT) techniques (schmidt rebound hammer and ultrasonic sensor) are verified for the effective maintenance of underwater concrete structures including harbor facilities. Sea field applicability of Schmidt hammer and ultrasonic sensor was verified by comparing field test result with sea field test result and also deduced the compressive strength estimation equation by depth of the water. On the basis of the sea field test result, compressive strength estimation equation which was deduced by multiple regression analysis indicated highest accuracy compared to other equations, especially it will be more likely to be used in underwater because of the depth of water correction. In the future, if schmidt hammer and ultrasonic sensor which were invented as waterproofing are used with ROV (Remotely Operated Vehicle), it will be possible to make a diagnosis of high reliability for underwater concrete structures and set up a ubiquitous concept of NDT system.
Journal of the Korea institute for structural maintenance and inspection
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v.16
no.5
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pp.148-160
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2012
This study proposed more reasonable prediction models on compressive strength and carbonation of concrete structure and developed a more effective tunnel safety diagnosis and maintenance method through field application of the proposed prediction models. For this study, the Seoul Metro's Line 1 through Line 4 were selected as target structures because they were built more than 30 years ago and have accumulated numerous diagnosis and maintenance data for about 15 years. As a result of the analysis of compressive strength and carbonation, we were able to draw prediction models with accuracy of more than 80% and confirmed the prediction model's reliability by comparing it with the existing models. We've also confirmed field suitability of the prediction models by applying field, the average error of an estimate on compressive strength and carbonation depth was about 20%, which showed an accuracy of more than 80%. We developed a more effective maintenance method using durability prediction Map before field inspection. With the durability prediction Map, diagnostic engineers and structure managers can easily detect the vulnerable points, which might have failed to reach the standard of designed strength or have a high probability of corrosion due to carbonation, therefore, it is expected to make it possible for them to diagnose and maintain tunnels more effectively and efficiently.
Purpose: This study was carried out in order to examine the relationship of job satisfaction and quality of life on the dental technicians and to analyze its influence. Methods: A self-reported questionnaire survey was carried out by having convenience sampling as 220 dental technicians who work in Seoul Metropolis, Gyeonggi-do Province, Daejeon and Chungnam Province from March 12, 2012 to April 13. A research tool was used questionnaire that was proved reliability and validity. It was prepared with totally 50 questions such as 12 items for subjects' general characteristics, 18 items for job satisfaction measurement, and 20 items for life quality measurement. An analysis of the collected data was computationally processed by using SPSS Win 17.0 program. An analytical technique was made by using statistical techniques such as frequency & percentage, T-test or One-way ANOVA analysis. The following are the analytical results of the collected materials. Results: As a result of analyzing research subjects' job satisfaction level, there was significant difference(P<0.05) in items of religion, hobby life, working environment, and rest time out of daily work. The whole mean in job satisfaction was indicated to be relatively high with 3.13. However, job satisfaction with social recognition, salary, and safety was indicated lowly. As a result of analyzing research subjects' life quality level, there was significant difference(P<0.05) in items of religion, hobby life, working environment, and rest time out of daily work. The whole mean in quality of life was indicated to be relatively high with 3.10. However, the satisfaction was indicated lowly in the whole life quality and the life environment sphere. As a result of analyzing correlation between job satisfaction and life quality, all variables were indicated to be positive correlation in high significance level, thereby having been indicated that the higher job satisfaction leads to the higher life quality. Conclusion: As a result of research, the dental technicians' job satisfaction was indicated to have high correlation with quality of life. An effort is judged to be necessary for establishing fair compensation system, improving welfare policy and enhancing social recognition and position in order to promote dental technicians' quality of life.
Keunchang, Jang;Sunghyun, Min;Inhye, Kim;Junghwa, Chun;Myoungsoo, Won
Korean Journal of Agricultural and Forest Meteorology
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v.24
no.4
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pp.346-352
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2022
Mountain meteorology in South Korea that is covered mountains with complex terrain is important for understanding and managing the forest disaster and forest ecosystems. In particular, recent changes in dryness and/or rainfall intensity due to climate change may cause an increase in the possibility of forest disasters. Therefore, accurate monitoring of mountain meteorology is needed for efficient forest management. Korea Forest Service (KFS) is establishing the Automatic Mountain Meteorology Observation Stations (AMOS) in the mountain regions since 2012. 464 AMOSs are observing various meteorological variables such as air temperature, relative humidity, wind speed and direction, precipitation, soil temperature, and air pressure for every minute, which is conducted the quality control (QC) to retain data reliability. QC process includes the physical limit test, step test, internal consistency test, persistence test, climate range test, and median filter test. All of AMOS observations are open to use, which can be found from the Korean Mountain Meteorology Information System (KoMIS, http://mtweather.nifos.go.kr/) of the National Institute of Forest Science and the Public Data Portal (https://public.go.kr/). AMOS observations with guaranteed quality can be used in various forest fields including the public safety, forest recreation, forest leisure activities, etc., and can contribute to the advancement of forest science and technology. In this paper, a series of processes are introduced to collect and use the AMOS dataset in the mountain region in South Korea.
Todays, medium energy resolution detectors are preferably used in radioisotope identification devices(RID) in nuclear and radioactive material categorization. However, there is still a need to develop or enhance « automated identifiers » for the useful RID algorithms. To decide whether any material is SNM or NORM, a key parameter is the better energy resolution of the detector. Although masking, shielding and gain shift/stabilization and other affecting parameters on site are also important for successful operations, the suitability of the RID algorithm is also a critical point to enhance the identification reliability while extracting the features from the spectral analysis. In this study, a RID algorithm based on Bayesian statistical method has been modified for medium energy resolution detectors and applied to the uranium gamma-ray spectra taken by a LaBr3:Ce detector. The present Bayesian RID algorithm covers up to 2000 keV energy range. It uses the peak centroids, the peak areas from the measured gamma-ray spectra. The extraction features are derived from the peak-based Bayesian classifiers to estimate a posterior probability for each isotope in the ANSI library. The program operations were tested under a MATLAB platform. The present peak based Bayesian RID algorithm was validated by using single isotopes(241Am, 57Co, 137Cs, 54Mn, 60Co), and then applied to five standard nuclear materials(0.32-4.51% at.235U), as well as natural U- and Th-ores. The ID performance of the RID algorithm was quantified in terms of F-score for each isotope. The posterior probability is calculated to be 54.5-74.4% for 238U and 4.7-10.5% for 235U in EC-NRM171 uranium materials. For the case of the more complex gamma-ray spectra from CRMs, the total scoring (ST) method was preferred for its ID performance evaluation. It was shown that the present peak based Bayesian RID algorithm can be applied to identify 235U and 238U isotopes in LEU or natural U-Th samples if a medium energy resolution detector is was in the measurements.
Recently, research, development, and commercialization of maritime autonomous surface ships (MASS) and remote control are in progress. Remote control is intended to secure autonomous navigation environments for existing ships or early-stage MASS using a remote control system (RCS). The main function of an RCS is to control MASS using data transmission between the MASS and the remote control centre. Remote control by a remote control officer also has an important function. The purpose of this study was to develop RCS and a performance evaluation technique for operation data provided by the RCS. The experiment was conducted during the navigation period of a training ship 'Hannara' after building experimental equipment at both an onshore remote control center and a training ship. As a result of evaluating data transmitted and received using the developed RCS, it was confirmed that data transmission was possible within an error range of 0.1%p. Fourteen types of ship information reflecting the navigation environment of the training ship were confirmed to be transmitted and received. The RCS developed in this work complies with the three principles of remote control: safety, reliability, and availability. This study provides a core technology for the development of RCSs for MASS and the evaluation of data transmission performance.
Natural gas has been supplied through underground pipelines and valve stations as a new city gas in Seoul. In contrast to its handiness the natural gas has very substantial hazards due to fires and explosions occurring from careless treatments or malfunctions of the transporting system. The main objectives of this study are to identify major hazards and to perform risk assessments after assessing reliabilities of the composing units in dealing with typical pipeline networks. there-fore two method, fault tree analysis ;1nd event tree analysis, are used here. Random valve stations are selected and considered its situation in location. The value of small leakage, large rupture, and no supply of liquefied natural gas is estimated as that of top event. By this calculation the values of small leakage are 3.29 in I)C valve station, 1.41 in DS valve station, those of large rup-lure are $1.90Times10_{-2}$ in DC valve station, $2.32$\times$10^{-2}$ in DS valve station, and those of no supply of LNG to civil gas company are $2.33$\times$10 ^{-2}$ , $2.89$\times$10^{-2}$ in each valve station. And through minimal cut set we can find the parts that is important and should be more important in overall system. In DC valve station one line must be added between basic event 26,27 because the potential hazard of these parts is the highest value. If it is added the failure rate of no supply of LNG is reduced to one fourth. In DS valve station the failure rate of basic event 4 is 92eye of no supply of LNG. Therefore if the portion of this part is reduced (one line added) the total failure rate can be decreased to one tenth. This analytical study on the risk assessment is very useful to prepare emergency actions or procedures in case of gas accidents around underground pipeline networks and to establish a resolute gas safety management system for loss prevention in Seoul metropolitan area.
Kim, Ok;Lee, Minwoo;Park, Sanghyun;Park, Changyoung;Song, Youngho;Kim, Byeongbin;Choi, Jinha;Lee, Jinheon
Journal of Environmental Health Sciences
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v.46
no.5
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pp.576-587
/
2020
Objectives: This study calculated local residents exposures to VOCs (Volatile Organic Compounds) released into the atmosphere using the CalTOX model and carried out uncertainty analysis and sensitivity analysis. The model validity was analyzed by comparing the predicted and the actual atmospheric concentrations. Methods: Uncertainty was parsed by conducting a Monte Carlo simulation. Sensitivity was dissected with the regression (coefficients) method. The model validity was analyzed by applying r2 (coefficient of determination), RMSE (root mean square error), and the Nash-Sutcliffe EI (efficiency index) formula. Results: Among the concentrations in the atmosphere in this study, benzene was the highest and the lifetime average daily dose of benzene and the average daily dose of xylene were high. In terms of the sensitivity analysis outcome, the source term to air, exposure time, indoors resting (ETri), exposure time, outdoors at home (ETao), yearly average wind speed (v_w), contaminated area in ㎡ (Area), active breathing rate (BRa), resting breathing rate (BRr), exposure time, and active indoors (ETai) were elicited as input variables having great influence upon this model. In consequence of inspecting the validity of the model, r2 appeared to be a value close to 1 and RMSE appeared to be a value close to 0, but EI indicated unacceptable model efficiency. To supplement this value, the regression formula was derived for benzene with y=0.002+15.48x, ethylbenzene with y ≡ 0.001+57.240x, styrene with y=0.000+42.249x, toluene with y=0.004+91.588x, and xylene with y=0.000+0.007x. Conclusions: In consequence of inspecting the validity of the model, r2 appeared to be a value close to 1 and RMSE appeared to be a value close to 0, but EI indicated unacceptable model efficiency. This will be able to be used as base data for securing the accuracy and reliability of the model.
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