• Journal of the Korean Institute of Gas
• /
• v.26 no.4
• /
• pp.41-57
• /
• 2022

The global demand for carbon neutrality in response to climate change is in a situation where it is necessary to prepare countermeasures for carbon trade barriers for some countries, including Korea, which is classified as an export-led economic structure and greenhouse gas exporter. Therefore, digital transformation, which is one of the predictable ways for the carbon-neutral transition model to be applied, should be introduced early. By applying digital technology to industrial gas manufacturing facilities used in one of the major industries, high-tech manufacturing industry, and hydrogen gas facilities, which are emerging as eco-friendly energy, abnormal detection, and diagnosis services are provided with cloud-based predictive diagnosis monitoring technology including operating knowledge. Here are the trends. Small and medium-sized companies that are in the blind spot of carbon-neutral implementation by confirming the direction of abnormal diagnosis predictive monitoring through optimization, augmented reality technology, IoT and AI knowledge inference, etc., rather than simply monitoring real-time facility status It can be seen that it is possible to disseminate technologies such as consensus knowledge in the engineering domain and predictive diagnostic monitoring that match the economic feasibility and efficiency of the technology. It is hoped that it will be used as a way to seek countermeasures against carbon emission trade barriers based on the highest level of ICT technology.

• Journal of the Society of Naval Architects of Korea
• /
• v.60 no.5
• /
• pp.375-387
• /
• 2023

The subsea power cables are increasingly important for harvesting renewable energies as we develop offshore wind farms located at a long distance from shore. Particularly, the continuous flexural motion of inter-array dynamic power cable of floating offshore wind turbine causes tremendous fatigue damages on the cable. As the subsea power cable consists of the helical structures with various components unlike a mooring line and a steel pipe riser, the fatigue analysis of the cables should be performed using special procedures that consider stick/slip phenomenon. This phenomenon occurs between inner helically wound components when they are tensioned or compressed by environmental loads and the floater motions. In particular, Vortex-induced vibration (VIV) can be generated by currents and have significant impacts on the fatigue life of the cable. In this study, the procedure for VIV fatigue analysis of the dynamic power cable has been established. Additionally, the respective roles of programs employed and required inputs and outputs are explained in detail. Demonstrations of case studies are provided under severely sheared currents to investigate the influences on amplitude variations of dynamic power cables caused by the excitation of high mode numbers. Finally, sensitivity studies have been performed to compare dynamic cable design parameters, specifically, structural damping ratio, higher order harmonics, and lift coefficients tables. In the future, one of the fundamental assumptions to assess the VIV response will be examined in detail, namely a narrow-banded Gaussian process derived from the VIV amplitudes. Although this approach is consistent with current industry standards, the level of consistency and the potential errors between the Gaussian process and the fatigue damage generated from deterministic time-domain results are to be confirmed to verify VIV fatigue analysis procedure for slender marine structures.

• Journal of Intelligence and Information Systems
• /
• v.26 no.2
• /
• pp.131-145
• /
• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• Sleep Medicine and Psychophysiology
• /
• v.21 no.2
• /
• pp.69-73
• /
• 2014

Objectives: This study was designed to assess the change of heart rate variability (HRV) at resting, upright, and psychological stress in anxiety disorder patients. Methods: HRV was measured at resting, upright, and psychological stress states in 60 anxiety disorder patients. We used visual analogue scale (VAS) score to assess tension and stress severity. Beck depression inventory (BDI) and state trait anxiety inventories I and II (STAI-I and II) were used to assess depression and anxiety severity. Differences between HRV indices were evaluated using paired t-tests. Gender difference analysis was accomplished with ANCOVA. Results: SDNN (Standard deviation of normal RR intervals) and low frequency/high frequency (LF/HF) were significantly increased, while NN50, pNN50, and normalized HF (nHF) were significantly decreased in the upright position compared to resting state (p < 0.01). SDNN, root mean square of the differences of successive normal to normal intervals, and LF/HF were significantly increased, while nHF was significantly decreased in the psychological stress state compared to resting state (p < 0.01). SDNN, NN50, pNN50 were significantly lower in upright position compared to psychological stress and nVLF, nLF, nHF, and LF/HF showed no significant differences between them. Conclusion: The LF/HF ratio was significantly increased after both physical and psychological stress in anxiety disorder, but did not show a significant difference between these two stresses. Significant differences of SDNN, NN50, and pNN50 without any differences of nVLF, nLF, nHF, and LF/HF between two stresses might suggest that frequency domain analysis is more specific than time domain analysis.

• Journal of Intelligence and Information Systems
• /
• v.25 no.3
• /
• pp.221-238
• /
• 2019

Recently, companies and public institutions have been actively introducing chatbot services in the field of customer counseling and response. The introduction of the chatbot service not only brings labor cost savings to companies and organizations, but also enables rapid communication with customers. Advances in data analytics and artificial intelligence are driving the growth of these chatbot services. The current chatbot can understand users' questions and offer the most appropriate answers to questions through machine learning and deep learning. The advancement of chatbot core technologies such as NLP, NLU, and NLG has made it possible to understand words, understand paragraphs, understand meanings, and understand emotions. For this reason, the value of chatbots continues to rise. However, technology-oriented chatbots can be inconsistent with what users want inherently, so chatbots need to be addressed in the area of the user experience, not just in the area of technology. The Fourth Industrial Revolution represents the importance of the User Experience as well as the advancement of artificial intelligence, big data, cloud, and IoT technologies. The development of IT technology and the importance of user experience have provided people with a variety of environments and changed lifestyles. This means that experiences in interactions with people, services(products) and the environment become very important. Therefore, it is time to develop a user needs-based services(products) that can provide new experiences and values to people. This study proposes a chatbot development process based on user needs by applying the design thinking approach, a representative methodology in the field of user experience, to chatbot development. The process proposed in this study consists of four steps. The first step is 'setting up knowledge domain' to set up the chatbot's expertise. Accumulating the information corresponding to the configured domain and deriving the insight is the second step, 'Knowledge accumulation and Insight identification'. The third step is 'Opportunity Development and Prototyping'. It is going to start full-scale development at this stage. Finally, the 'User Feedback' step is to receive feedback from users on the developed prototype. This creates a "user needs-based service (product)" that meets the process's objectives. Beginning with the fact gathering through user observation, Perform the process of abstraction to derive insights and explore opportunities. Next, it is expected to develop a chatbot that meets the user's needs through the process of materializing to structure the desired information and providing the function that fits the user's mental model. In this study, we present the actual construction examples for the domestic cosmetics market to confirm the effectiveness of the proposed process. The reason why it chose the domestic cosmetics market as its case is because it shows strong characteristics of users' experiences, so it can quickly understand responses from users. This study has a theoretical implication in that it proposed a new chatbot development process by incorporating the design thinking methodology into the chatbot development process. This research is different from the existing chatbot development research in that it focuses on user experience, not technology. It also has practical implications in that companies or institutions propose realistic methods that can be applied immediately. In particular, the process proposed in this study can be accessed and utilized by anyone, since 'user needs-based chatbots' can be developed even if they are not experts. This study suggests that further studies are needed because only one field of study was conducted. In addition to the cosmetics market, additional research should be conducted in various fields in which the user experience appears, such as the smart phone and the automotive market. Through this, it will be able to be reborn as a general process necessary for 'development of chatbots centered on user experience, not technology centered'.

• Journal of Korean Society of Forest Science
• /
• v.94 no.6
• /
• pp.496-503
• /
• 2005

This study was conducted to investigate the influences of sapflow flux on soil water tensions and soil moisture content at the Abies holophylla plots in Gwangneung, Gyeonggido, from September to October 2004. The Abies holophylla had been planted in 1976 and thinning and pruning were carried out in 1996 and 2004. Sapflow flux was measured by the heat pulse method, and soil water tension was measured by tensiometer at hillslope and streamside. Time domain reflectometry probes (TDR) were positioned horizontally at the depth of 10, 30 and 50 cm to measure soil moisture content. All of data were recorded every 30 minutes with the dataloggers. The sapflow flux responded sensitively to rainfall, so little sapflow was detected in rainy days. The average daily sapflow flux of sample trees was 10.16l, a maximum was 15.09l, and a minimum was 0.0l. The sapflow flux's diurnal changes showed that sapflow flux increased from 9 am and up to 0.74 l/30 min. The highest sapflow flux maintained by 3 pm and decreased almost 0.0 l/30 mm after 7 pm. The average soil water tensions were low ($-141.3cmH_2O$, $-52.9cmH_2O$ and $-134.2cmH_2O$) at hillslope and high ($-6.1cmH_2O$, $-18.0cmH_2O$ and $-3.7cmH_2O$) at streamside. When the soil moisture content decreased after rainfall, the soil water tension at hillslope responded sensitively to the sapflow flux. The soil water tension decreased as the sapflow flux increased during the day time, whereas increased during the night time when the sapflow flux was not detected. On the other hand, there was no significant relationship between soil water tension and sapflow flux at streamside. Soil moisture content at hillslope decreased continuously after rain, and showed a negative correlation to sapflow flux like a soil water tension at hillslope. As considered results above, it was confirmed that the response of soil moisture tension to sapflow flux at hillslope and streamside were different.

• Journal of Intelligence and Information Systems
• /
• v.20 no.4
• /
• pp.89-105
• /
• 2014

After emergence of Internet, social media with highly interactive Web 2.0 applications has provided very user friendly means for consumers and companies to communicate with each other. Users have routinely published contents involving their opinions and interests in social media such as blogs, forums, chatting rooms, and discussion boards, and the contents are released real-time in the Internet. For that reason, many researchers and marketers regard social media contents as the source of information for business analytics to develop business insights, and many studies have reported results on mining business intelligence from Social media content. In particular, opinion mining and sentiment analysis, as a technique to extract, classify, understand, and assess the opinions implicit in text contents, are frequently applied into social media content analysis because it emphasizes determining sentiment polarity and extracting authors' opinions. A number of frameworks, methods, techniques and tools have been presented by these researchers. However, we have found some weaknesses from their methods which are often technically complicated and are not sufficiently user-friendly for helping business decisions and planning. In this study, we attempted to formulate a more comprehensive and practical approach to conduct opinion mining with visual deliverables. First, we described the entire cycle of practical opinion mining using Social media content from the initial data gathering stage to the final presentation session. Our proposed approach to opinion mining consists of four phases: collecting, qualifying, analyzing, and visualizing. In the first phase, analysts have to choose target social media. Each target media requires different ways for analysts to gain access. There are open-API, searching tools, DB2DB interface, purchasing contents, and so son. Second phase is pre-processing to generate useful materials for meaningful analysis. If we do not remove garbage data, results of social media analysis will not provide meaningful and useful business insights. To clean social media data, natural language processing techniques should be applied. The next step is the opinion mining phase where the cleansed social media content set is to be analyzed. The qualified data set includes not only user-generated contents but also content identification information such as creation date, author name, user id, content id, hit counts, review or reply, favorite, etc. Depending on the purpose of the analysis, researchers or data analysts can select a suitable mining tool. Topic extraction and buzz analysis are usually related to market trends analysis, while sentiment analysis is utilized to conduct reputation analysis. There are also various applications, such as stock prediction, product recommendation, sales forecasting, and so on. The last phase is visualization and presentation of analysis results. The major focus and purpose of this phase are to explain results of analysis and help users to comprehend its meaning. Therefore, to the extent possible, deliverables from this phase should be made simple, clear and easy to understand, rather than complex and flashy. To illustrate our approach, we conducted a case study on a leading Korean instant noodle company. We targeted the leading company, NS Food, with 66.5% of market share; the firm has kept No. 1 position in the Korean "Ramen" business for several decades. We collected a total of 11,869 pieces of contents including blogs, forum contents and news articles. After collecting social media content data, we generated instant noodle business specific language resources for data manipulation and analysis using natural language processing. In addition, we tried to classify contents in more detail categories such as marketing features, environment, reputation, etc. In those phase, we used free ware software programs such as TM, KoNLP, ggplot2 and plyr packages in R project. As the result, we presented several useful visualization outputs like domain specific lexicons, volume and sentiment graphs, topic word cloud, heat maps, valence tree map, and other visualized images to provide vivid, full-colored examples using open library software packages of the R project. Business actors can quickly detect areas by a swift glance that are weak, strong, positive, negative, quiet or loud. Heat map is able to explain movement of sentiment or volume in categories and time matrix which shows density of color on time periods. Valence tree map, one of the most comprehensive and holistic visualization models, should be very helpful for analysts and decision makers to quickly understand the "big picture" business situation with a hierarchical structure since tree-map can present buzz volume and sentiment with a visualized result in a certain period. This case study offers real-world business insights from market sensing which would demonstrate to practical-minded business users how they can use these types of results for timely decision making in response to on-going changes in the market. We believe our approach can provide practical and reliable guide to opinion mining with visualized results that are immediately useful, not just in food industry but in other industries as well.

• Journal of Arbitration Studies
• /
• v.15 no.2
• /
• pp.3-35
• /
• 2005

The meaning of Online ADR lies in the prompt and economical resolution of disputes by applying the information/communication element (Internet) to existing ADR. However, if the promptness and economical efficiency are overemphasized, the fairness and appropriateness of dispute resolution may be compromised and consequently Online ADR will be belittled and criticized as second-class trials. In addition, as communication is mostly made using texts in Online ADR it is difficult to investigate cases and to create atmosphere and induce dynamic feelings, which are possible in the process of dispute resolution through face-to-face contact. Despite such difficulties, Online ADR is expanding its area not only in online but also in offline due to its advantages such as promptness, low expenses and improved resolution methods, and is expected to develop rapidly as the electronic government decided to adopt it in the future. Accordingly, the following points must be focused on for the continuous First, in the legal and institutional aspects for the development of Online ADR, it is necessary to establish a framework law on ADR. A framework law on ADR comprehending existing mediation and arbitration should be established and it must include contents of Online ADR, which utilizes electronic communication means. However, it is too early to establish a separate law for Online ADR because Online ADR must develop based on the theoretical system of ADR. Second, although Online ADR is expanding rapidly, it may take time to be settled as a tool of dispute resolution. As discussed earlier, additionally, if the amount of money in dispute is large or the dispute is complicated, Online ADR may have a negative effect on the resolution of the dispute. Thus, it is necessary to apply Online ADR to trifle cases or domestic cases in the early stage, accumulating experiences and correcting errors. Moreover, in order to settle numerous disputes effectively, Online ADR cases should be analyzed systematically and cases should be classified by type so that similar disputes may be settled automatically. What is more, these requirements should reflected in developing Online ADR system. Third, the application of Online ADR is being expanded to consumer disputes, domain name disputes, commercial disputes, legal disputes, etc., millions of cases are settled through Online ADR, and 115 Online ADR sites are in operation throughout the world. Thus Online ADR requires not temporary but continuous attention, and mediators and arbitrators participating in Online ADR should be more intensively educated on negotiation and information technologies. In particular, government-led research projects should be promoted to establish Online ADR model and these projects should be supported by comprehensive researches on mediation, arbitration and Online ADR. Fourth, what is most important in the continuous development and expansion of Online ADR is to secure confidence in Online ADR and advertise Online ADR to users. For this, incentives and rewards should be given to specialists such as lawyers when they participate in Online ADR as mediators and arbitrators in order to improve their expertise. What is more, from the early stage, the government and public institutions should have initiative in promoting Online ADR so that parties involved in disputes recognize the substantial contribution of Online ADR to dispute resolution. Lastly, dispute resolution through Online ADR is performed by organizations such as Korea Institute for Electronic Commerce and Korea Consumer Protection Board and partially by Korean Commercial Arbitration Board. Online ADR is expected to expand its area to commercial disputes in offline in the future. In response to this, Korean Commercial Arbitration Board, which is an organization for commercial dispute resolution, needs to be restructured.

• Radiation Oncology Journal
• /
• v.17 no.4
• /
• pp.299-306
• /
• 1999

Purpose : The human genetic disorder ataxia-telangiectasia (AT) is a multisystem disease characterized by extreme radiosensitivity. The recent identification of the gene mutated in AT, ATM, and the demonstration that it encodes a homologous domain of phosphatidylinositol 3-kinase (PI3-K), the catalytic subunit of an enzyme involved in transmitting signals from the cell surface to the nucleus, provide support for a role of this gene in signal transduction. Although ionizing radiation was known to induce c-fos transcription, nothing is known about how ATM or PKCI mediated signal transduction pathway modulates the c-fos gene transcription and gene expression. Here we have studied the effect of PKCI on radiation sensitivity and c-fos transcription in normal and AT cells. Materials and Methods: Normal (LM217) and AT (AT5BIVA) cells were transfected with PKCI expression plasmid and the overexpression and integration of PKCI was evaluated by northern blotting and polymerase chain reaction, respectively. 5 Gy of radiation was exposed to LM and AT cells transfected with PKCI expression plasmid and cells were harvested 48 hours after radiation and investigated apoptosis with TUNEL method. The c-fos transcription activity was studied by performing CAT assay of reporter gene after transfection of c-fos CAT plasmid into AT and LM cells. Results: Our results demonstrate for the first time a role of PKCI on the radiation sensitivity and c-fos expression in LM and AT cells. PKCI increased radiation induced apoptosis in LM cells but reduced apoptosis in AT cells. The basal c-fos transcription activity is 70 times lower in AT cells than that in LM cells. The c-fos transcription activity was repressed by overexpression of PKCI in LM cells but not in AT cells. After induction of c-fos by Ras protein, overexpression of PKCI repressed c-fos transcription in LM cells but not in AT cells Conclusion: Overexpression of PKCI increased radiation sensitivity and repressed c-fos transcription in LM cells but not in AT cells. The results may be a. reason of increased radiation sensitivity of AT cells. PKCI may be involved in an ionizing radiation induced signal transduction pathway responsible for radiation sensitivity and c-fos transcription. The data also provided evidence for novel transcriptional difference between LM and AT cells.

• (The) Research of the performance art and culture
• /
• no.43
• /
• pp.293-322
• /
• 2021

The present study examined the scientific awareness appearing in Korean tokusatsu series by focusing on Vectorman: Warriors of the Earth. As a work representing Korean tokusatsu series, Vectorman: Warriors of the Earth achieved the greatest success among tokusatsu series. This work was released thanks to the continued popularity of Japanese tokusatsu since the mid-1980s and the trend of robot animations. Due to the chronic problems regarding Korean children's programs-the oversupply of imported programs and repeated reruns-the need for domestically produced children's programs has continued to come to the fore. However, as the popularity of Korean animation waned beginning in the mid-1990s, inevitably the burden fr producing animation increased. As a result, Vectorman: Warriors of the Earth was produced as a tokusatsu rather than an animation, and because this was a time when an environment for using special effects technology was being fostered in broadcasting stations, computer visual effects were actively used for the series. The response to the new domestically produced tokusatsu series Vectorman: Warriors of the Earth was explosive. The Vectorman series explained the abilities of cosmic beings by using specific scientific terms such as DNA synthesis, brain cell transformation, and special psychological control device instead of ambiguous words like the scientific technology of space. Although the series is unable to describe in detail about the process and cause, the way it defines technology using concrete terms rather than science fiction shows how scientific imagination is manifesting in specific forms in Korean society. Furthermore, the equal relationship between Vectorman and the aliens shows how the science of space, explained with the scientific terms of earth, is an expression of confidence regarding the advancement of Korean scientific technology which represents earth. However, the female characters fail to gain entry into the domain of science and are portrayed as unscientific beings, revealing limitations in terms of scientific awareness.