The Journal of Korea Institute of Information, Electronics, and Communication Technology
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v.15
no.1
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pp.56-61
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2022
In this paper, we classify and present AI algorithms and natural language processing methods used in chatbots. A framework that can be used to implement a chatbot is also described. A chatbot is a system with a structure that interprets the input string by constructing the user interface in a conversational manner and selects an appropriate answer to the input string from the learned data and outputs it. However, training is required to generate an appropriate set of answers to a question and hardware with considerable computational power is required. Therefore, there is a limit to the practice of not only developing companies but also students learning AI development. Currently, chatbots are replacing the existing traditional tasks, and a practice course to understand and implement the system is required. RNN and Char-CNN are used to increase the accuracy of answering questions by learning unstructured data by applying technologies such as deep learning beyond the level of responding only to standardized data. In order to implement a chatbot, it is necessary to understand such a theory. In addition, the students presented examples of implementation of the entire system by utilizing the methods that can be used for coding education and the platform where existing developers and students can implement chatbots.
Ji, Inseo;Kang, Jeon-Woong;Kim, Taeyung;Kang, Min Seo;Kwon, Sun Beom;Hong, Jiwoo
Korean Chemical Engineering Research
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v.60
no.2
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pp.300-307
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2022
Time-resolved serial femtosecond crystallography (TR-SFX) is a powerful technique for determining temporal variations in the structural properties of biomacromolecules on ultra-short time scales without causing structure damage by employing femtosecond X-ray laser pulses generated by an X-ray free electron laser (XFEL). The mixing rate of reactants and biomolecule samples, as well as the hit rate between crystal samples and x-ray pulses, are critical factors determining TR-SFX performance, such as accurate image acquisition and efficient sample consumption. We here develop two distinct sample delivery systems that enable ultra-fast mixing and on-demand droplet injecting via pneumatic application with a square pulse signal. The first strategy relies on inertial mixing, which is caused by the high-speed collision and subsequent coalescence of droplets ejected through a double nozzle, while the second relies on on-demand pneumatic jetting embedded with a 3D-printed micromixer. First, the colliding behaviors of the droplets ejected through the double nozzle, as well as the inertial mixing within the coalesced droplets, are investigated experimentally and numerically. The mixing performance of the pneumatic jetting system with an integrated micromixer is then evaluated by using similar approaches. The sample delivery system devised in this work is very valuable for three-dimensional biomolecular structure analysis, which is critical for elucidating the mechanisms by which certain proteins cause disease, as well as searching for antibody drugs and new drug candidates.
Objective: The aim of this study was to investigate the effect Tiger-step walking on the movement of the lower extremities during walking. Method: Twenty healthy male adults who had no experience of musculoskeletal injuries on lower extremities in the last six months (age: 26.85 ± 3.28 yrs, height: 174.6 ± 3.72 cm, weight: 73.65 ± 7.48 kg) participated in this study. In this study, 7-segments whole-body model (pelvis, both side of thigh, shank and foot) was used and 29 reflective markers and cluster were attached to the body to identify the segments during the gait. A 3-dimensional motion analysis with 8 infrared cameras and 7 channeled EMG was performed to find the effect of tigerstep on uphill walking. To verify the tigerstep effect, a one-way ANOVA with a repeated measure was used and the statistical significance level was set at α=.05. Results: Firstly, Both Tiger-steps showed a significant increase in stance time and stride length compared with normal walking (p<.05), while both Tiger-steps shown significantly reduced cadence compared to normal walking (p<.05). Secondly, both Tiger-steps revealed significantly increased in hip and ankle joint range of motion compared with normal walking at all planes (p<.05). On the other hand, both Tiger-steps showed significantly increased knee joint range of motion compared with normal walking at the frontal and transverse planes (p<.05). Lastly, Gluteus maximus, biceps femoris, medial gastrocnemius, tibialis anterior of both tiger-step revealed significantly increased muscle activation compared with normal walking in gait cycle and stance phase (p<.05). On the other hand, in swing phase, the muscle activity of the vastus medialis, biceps femoris, tibialis anterior of both tiger-step significantly increased compared with those of normal walking (p <.05). Conclusion: As a result of this study, Tiger step revealed increased in 3d range of motion of lower extremity joints as well as the muscle activities associated with range of motion. These findings were evaluated as an increase in stride length, which is essential for efficient walking. Therefore, the finding of this study prove the effectiveness of the tiger step when walking uphill, and it is thought that it will help develop a more efficient tiger step in the future, which has not been scientifically proven.
Even in recent years, treatment of first-aid patients is still often delayed due to a shortage of medical resources in marginalized areas. Research on automating the analysis of medical data to solve the problems of inaccessibility for medical services and shortage of medical personnel is ongoing. Computer vision-based medical inspection automation requires a lot of cost in data collection and labeling for training purposes. These problems stand out in the works of classifying lesion that are rare, or pathological features and pathogenesis that are difficult to clearly define visually. Anomaly detection is attracting as a method that can significantly reduce the cost of data collection by adopting an unsupervised learning strategy. In this paper, we propose methods for detecting abnormal images on chest X-RAY images as follows based on existing anomaly detection techniques. (1) Normalize the brightness range of medical images resampled as optimal resolution. (2) Some feature vectors with high representative power are selected in set of patch features extracted as intermediate-level from lesion-free images. (3) Measure the difference from the feature vectors of lesion-free data selected based on the nearest neighbor search algorithm. The proposed system can simultaneously perform anomaly classification and localization for each image. In this paper, the anomaly detection performance of the proposed system for chest X-RAY images of PA projection is measured and presented by detailed conditions. We demonstrate effect of anomaly detection for medical images by showing 0.705 classification AUROC for random subset extracted from the PadChest dataset. The proposed system can be usefully used to improve the clinical diagnosis workflow of medical institutions, and can effectively support early diagnosis in medically poor area.
The purpose of this study is to present an appropriate management plan as a supplement to the scientific evidence of the currently operated distancing system for preventing COVID-19. The currently being used mathematical models are expressed as simultaneous ordinary differential equations, there is a problem in that it is difficult to use them for the management of entry and exit of small business owners. In order to supplement this point, in this paper, a method for quantitatively expressing the risk of infection by people who gather is presented in consideration of the allowable risk given to the gathering space, the basic infection reproduction index, and the risk reduction rate due to vaccination. A simple quantitative model was developed that manages the probability of infection in a probabilistic level according to a set of visitors by considering both the degree of infection risk according to the vaccination status (non-vaccinated, primary inoculation, and complete vaccination) and the epidemic status of the virus. In a given example using the model, the risk was reduced to 55% when 20% of non-vaccinated people were converted to full vaccination. It was suggested that management in terms of quarantine can obtain a greater effect than medical treatment. Based on this, a generalized model that can be applied to various situations in consideration of the type of vaccination and the degree of occurrence of confirmed cases was also presented. This model can be used to manage the total risk of people gathered at a certain space in a real time, by calculating individual risk according to the type of vaccine, the degree of inoculation, and the lapse of time after inoculation.
Journal of Korean Home Economics Education Association
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v.33
no.4
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pp.103-117
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2021
Nuts are cholesterol free with high poly-unsaturated fatty acids(PUFA) and have lower intakes of sodium than non-consumers, and thus they can decrease blood pressure. Hypertension is a common primary diagnosis in Korea. Because of extending exposure to 24-hour raised blood pressure and heart rate hypertension is likely to be caused by prolonged short sleep durations. This study examined the relationship between nut consumption and hypertension according to sleep duration among Korean adult. Based on data from the 2010-2016 Korea National Health and Nutrition Examination Survey(KNHANES), the final analytic sample(n=25,359) was used for current analysis. The dietary intake was assessed through a 24-hour recall method. Associations of nut consumption with sleep duration and hypertension were determined using multiple logistic regression with odds ratio(95% CI). All the analyses were carried out in SAS version 9.4, and the significance level was set at p<0.05. With increasing nut intake, the prevalence of hypertension significantly decreased(p for trend=0.02). After controlling for sleep duration, the nut consumption showed significant association with the prevalence of hypertension when sleep duration was 6 to 6.9 h per day(p for trend=0.03) or 7 to 7.9 h per day(p for trend=0.03). In conclusion, dietary total nut intake was found to be significantly associated with the prevalence of hypertension.
In Kwon, Park;Yi, Zhong Hu;Yi, Zhang;Hyun Keun, Ku;Yong Han, Kwon
KEPCO Journal on Electric Power and Energy
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v.8
no.2
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pp.159-179
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2022
Often a network becomes complex, and multiple entities would get in charge of managing part of the whole network. An example is a utility grid. While the entire grid would go under a single utility company's responsibility, the network is often split into multiple subsections. Subsequently, each subsection would be given as the responsibility area to the corresponding sub-organization in the utility company. The issue of how to make subsystems of adequate size and minimum number of interconnections between subsystems becomes more critical, especially in real-time simulations. Because the computation capability limit of a single computation unit, regardless of whether it is a high-speed conventional CPU core or an FPGA computational engine, it comes with a maximum limit that can be completed within a given amount of execution time. The issue becomes worsened in real time simulation, in which the computation needs to be in precise synchronization with the real-world clock. When the subject of the computation allows for a longer execution time, i.e., a larger time step size, a larger portion of the network can be put on a computation unit. This translates into a larger margin of the difference between the worst and the best. In other words, even though the worst (or the largest) computational burden is orders of magnitude larger than the best (or the smallest) computational burden, all the necessary computation can still be completed within the given amount of time. However, the requirement of real-time makes the margin much smaller. In other words, the difference between the worst and the best should be as small as possible in order to ensure the even distribution of the computational load. Besides, data exchange/communication is essential in parallel computation, affecting the overall performance. However, the exchange of data takes time. Therefore, the corresponding consideration needs to be with the computational load distribution among multiple calculation units. If it turns out in a satisfactory way, such distribution will raise the possibility of completing the necessary computation in a given amount of time, which might come down in the level of microsecond order. This paper presents an effective way to split a given electrical network, according to multiple criteria, for the purpose of distributing the entire computational load into a set of even (or close to even) sized computational loads. Based on the proposed system splitting method, heavy computation burdens of large-scale electrical networks can be distributed to multiple calculation units, such as an RTDS real time simulator, achieving either more efficient usage of the calculation units, a reduction of the necessary size of the simulation time step, or both.
The alarm monitoring technology applied to existing operating ships manages data items such as temperature and pressure with AMS (Alarm Monitoring System) and provides an alarm to the crew should these sensing data exceed the normal level range. In addition, the maintenance of existing ships follows the Planned Maintenance System (PMS). whereby the sensing data measured from the equipment is monitored and if it surpasses the set range, maintenance is performed through an alarm, or the corresponding part is replaced in advance after being used for a certain period of time regardless of whether the target device has a malfunction or not. To secure the reliability and operational safety of ship engine operation, it is necessary to enable advanced diagnosis and prediction based on real-time condition monitoring data. To do so, comprehensive measurement of actual ship data, creation of a database, and implementation of a condition diagnosis monitoring system for condition-based predictive maintenance of auxiliary equipment and piping must take place. Furthermore, the system should enable management of auxiliary equipment and piping status information based on a responsive web, and be optimized for screen and resolution so that it can be accessed and used by various mobile devices such as smartphones as well as for viewing on a PC on board. This update cost is low, and the management method is easy. In this paper, we propose CBM (Condition Based Management) technology, for autonomous ships. This core technology is used to identify abnormal phenomena through state diagnosis and monitoring of pumps and purifiers among ship auxiliary equipment, and seawater and steam pipes among pipes. It is intended to provide performance diagnosis and failure prediction of ship auxiliary equipment and piping for convergence analysis, and to support preventive maintenance decision-making.
This study used a method of comparing and analyzing various editions of Jeokcheonsu, and aims to confirm why different views have arisen on commentaries that differ according to the perspective of one original text, which interpretation is more valid among them. The biggest part of the misunderstanding of Myeongri theory in Jeokcheonsu is Kyeokguk theory. Jeokcheonsu does not set a high value on Kyeokguk, and it is highly regarded as the Myeongri classics that emphasizes Eokbuyongsin. However, as a result of classifying the original text by theory, we can see there are about 5 sentences that directly mention Eokbu theory, but 9 sentences that explain Kyeokguk theory and 15 sentences if we include the sentences that explain Jonggyeok and Hwagyeok. Even looking that metaphoric speech is mainly used, it is also clear that it's not a book written to be read by a beginner of Myeongri. This is Myeongri texts written to convey more profound logic and enlightenment to a person who has sufficient knowledge by having learned the principle of Myeongri. A single sentence of 'Jaegwaninsubunpyeonjeong Gyeomronsiksanggyeokgukjeong' would have been sufficient to explain the Kyeokguk theory, because it's written on the assumption of the reader's level. Among the later commentaries about the theory of Myeongri contained in Jeokcheosu, 4 persons'commentaries on the original text of 'Palkyeok', 'Gwansal', Sangkwan', 'Wolryeong', 'Saengsi', 'Cheongtak' related to Kyeokguk theory was compared and analyzed.
Pena, Francisco;Gallardo, Natalia;Campillo, Carmen Del;Garrido, Ana;Cabanas, Victor Fernandez;Delgado, Antonio
Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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2001.06a
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pp.1615-1615
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2001
During the past ten years, Near Infrared Spectroscopy has been successfully applied to the analysis of a great variety of agriculture products. Previous works (Morra et al., 1991; Salgo et al., 1998) have shown the potential of this technology for soil analysis, estimating different parameters just with one single scan. The main advantages of NIR applications in soils are the speed of response, allowing the increase of the number of samples analysed to define a particular soil, and the instantaneous elaboration of recommendations for fertilization and soil amendment. Another advantage is to avoid the use of chemical reagents at all, being an environmentally safe technique. In this paper, we have studied a set of 129 soil samples selected from representative glasshouse soils from Southern Spain. The samples were dried, milled, and sieved to pass a 2 mm sieve and then analysed for organic carbon, total nitrogen, inorganic nitrogen (nitrate ammonium), hygroscopic humidity, pH and electrical conductivity in the 1:1 extract. NIR spectra of all samples were obtained in reflectance mode using a Foss NIR Systems 6500 spectrophotometer equipped with a spinning module. Calibration equations were developed for seven analytical parameters (ph, Total nitrogen, organic nitrogen, organic carbon, C/N ratio and Electric Conductivity). Preliminary results show good correlation coefficients and standard errors of cross validation in equations obtained for Organic Carbon, Organic Nitrogen, Total Nitrogen and C/N ratio. Calibrations for nitrates and nitrites, ammonia and electric conductivity were not acceptable. Calibration obtained for pH had an acceptable SECV, but the determination coefficient was found very poor probably due to the reduced range in reference values. Since the estimation of Organic Carbon and C/N ratio are acceptable NIIRS could be used as a fast method to assess the necessity of organic amendments in soils from Mediterranean regions where the low level of organic matter in soils constitutes an important agronomic problem. Furthermore, the possibility of a single and fast estimation of Total Nitrogen (tedious determination by modifications of the Kjeldahl procedure) could provide and interesting data to use in the estimation of nitrogen fertilizer rates by means of nitrogen balances.
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