• The Journal of the Society of Stroke on Korean Medicine
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• v.23 no.1
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• pp.73-84
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• 2022

■Objective The purpose of this case report is to report the effect of Korean medicine treatment on a patient with pontine infarction complaining of discomfort due to aggravated voiding dysfunction after the onset of the stroke. ■Methods The patient was hospitalized for 44 days and treated with herbal medicine, acupuncture, electroacupuncture, moxibustion, and interferential current therapy(ICT). We checked the amount of self-voided volume and postvoid residual urine volume(PVR), and asked the patient to subjectively evaluate the degree of discomfort due to voiding dysfunction. ■Results After 44 days of hospitalization, the patient responded that the subjective discomfort due to residual urine remained 30% and delayed urine remained 50% compared to the day of admission. The maximum amount of PVR was 234 ml on the 3^rd day, and the minimum amount of PVR was checked on 25^th and 35^th day as 0 ml. ■Conclusions This study suggests that Korean medicine treatment may be effective in the treatment of voiding dysfunction after stroke.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.6
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• pp.87-99
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• 2022

The meat consumption per person has continuously increased in recent years. However, the labor force in the domestic livestock industry has decreased due to the declining and ageing population. In order to increase productivity, the government have developed and distributed design standard of livestock houses. Presently, report showed that the adaptation rate of the developed livestock house design standard on the real farm was still low. Thus, this paper aimed to find ways to improve the utilization of the design standard through surveys. The survey was conducted on 650 farms across the country. Analysis of the result showed that in the poultry house, the unawareness of farmers to the design standard was found to be the biggest reason for not using the design standards. On the other hand, in the swine house, the previously built swine houses do not fit with the design standard. From these result, the following recommendations were suggested: 1) promotion and education are needed to enhance usage of design standard; 2) since it is impossible to make a design standard considering all the farm sites, it is important to consider the conditions of various farm site prior to enhancement of the design standard; 3) improvement factors such as reinforcing the ventilation design, reflecting animal welfare, preventing livestock diseases, and enhancing ICT devices can also be promoted.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.6
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• pp.605-612
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• 2021

Amid growing global damage due to abnormal weather caused by global warming, the introduction of eco-friendly cars is accelerating to reduce greenhouse gas emissions from internal combustion engines. Accordingly, many studies are being conducted in each country to prepare for the explosion of hydrogen fuel in semi-closed spaces such as tunnels and underground parking lots to ensure the safety of hydrogen-electric vehicles. As a result of predicting the explosion pressure of the hydrogen tank using the equivalent TNT model, it was found to be about 1.12 times and 2.30 times higher at a height of 1.5 meters, respectively, based on the case of 52 liters of hydrogen capacity. A review of the impact on the human body and buildings by converting the predicted maximum explosive pressure into the amount of impact predicted that all predicted values would result in lung damage or severe partial destruction. The predicted degree of damage was applied only by converting the amount of impact caused by the explosion, and considering the additional damage caused by the explosion, it is believed that the actual damage will increase further and safety and disaster prevention measures should be taken.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.32 no.1
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• pp.78-88
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• 2022

Objectives: To develop the smart sensor to protect worker's health from chemical exposure by adopting ICT (Information and Communications Technology) technologies. Methods: To develope real-time chemical exposure monitoring system, IoT (Internet of Things) sensor technology and regulations were reviewed. We developed and produced smart sensor. A smart sensor is a system consisting of a sensor unit, a communication unit, and a platform. To verify the performance of smart sensors, each sensor has been certified by the Korea Laboratory Accreditation Scheme (KOLAS). Results: Chemicals (TVOC; Total Volatile Organic Compounds, Cl₂: Chlorine, HF: Hydrogen fluoride and HCN: Hydrogen cyanide) were selected according to a priority logic (KOSHA Alert, acute poisoning statistics, literature review). Notifications were set according to OEL (occupational exposure limit). Sensors were selected based on OEL and the capabilities of the sensors. Communication is designed to use LTE (Long Term Evolution) and Wi-Fi at the same time for convenience. Electronic platform were applied to build this monitoring system. Conclusions: Real-time monitoring system for OEL of hazardous chemicals in workplace was developed. Smart sensor can detect chemicals to complement monitoring of traditional workplace environmental monitoring such as short term and peak exposure. Further research is needed to expand the scope of application, improve reliability, and systematically application.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.1
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• pp.67-74
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• 2022

In recent, the number of real-time traffic information sources and providers has increased as increasing smartphone users and intelligent transportation system facilities installed at roadways including vehicle detection system (VDS), dedicated short-ranged communications (DSRC), and global positioning system (GPS) probe vehicle. The accuracy of such traffic information would vary with these heterogeneous information sources or spatiotemporal traffic conditions. Therefore, the purpose of this study is to propose an empirical strategy of heterogeneous information fusion to improve the accuracy of real-time traffic information. To carry out this purpose, travel speed data collection based on the floating car technique was conducted on 227 freeway links (or 892.2 km long) and 2,074 national highway links (or 937.0 km long). The average travel speed for 5 probe vehicles on a specific time period and a link was used as a ground truth measure to evaluate the accuracy of real-time heterogeneous traffic information for that time period and that link. From the statistical tests, it was found that the proposed fusion strategy improves the accuracy of real-time traffic information.

• The Journal of Society for e-Business Studies
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• v.27 no.1
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• pp.29-41
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• 2022

Since the first sale of a banner advertisement in 1995, electronic commerce has become a new transaction channel for consumers. With more than 20 years of its history, electronic commerce has become an important consumption channel for everyone and inexperience is no more a reason that discourages the consumption through this channel. The great expansion of this channel is now a formidable thereat to traditional channels. However, products with high asset specificity and complexity are still having difficulty to be traded over the online channel where the experience of the products for a consumer is limited. Especially, variations of the same product's quality depending on how pre-owners used the product and high complexity to describe the quality of the products prevent used goods from being traded over e-channels. Added to that, the information asymmetry between sellers and buyers for used goods makes the establishment of market transaction difficult. Considering the challenges, the current case study discusses thredUP, a clothing resale platform company. In this paper, we study how the company could overcome those limitations in this toughest resale market through the use of AI for dynamic pricing and standarized product quality ratings. In addition, we also hope to provide readers with the opportunity to understand the secondhand industries and its market, and see where it is heading for in the future.

• 지역과문화
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• v.8 no.2
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• pp.49-68
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• 2021

The pandemic of COVID-19 also affected performing arts business and stimulated 'Untact' performances, which means online streaming of the shows including real-time streaming. This study sought to examine factors to the consumers' acceptance. The research framework was based on the VAM, a revised model of TAM for the ICT products and services. For the research, consumer survey was conducted, where ndependent variables are perceived usefulness, pleasure, technicalty and innovation resistance, and dependent variables are percieved value and acceptance. Smart PLS was used to test the hypothesis. The result shows that the significant factors were percieved usefulness(+), pleasure(+) and innovation resistance(-). The percieved technicalty was not significant, the major reason would be that the digital devices and the internet technology are percieved a commodity these days in Korea. Percieved value was significant factor to acceptance. This study is meaningful because it is about the new phenomenon of 'untact' performance through the VAM methodology and it examined the significant factors to the attitude from the perspective of benefits and costs. There is limit that this study didn't consider old peoples' attitude. It is the reason that the continuous researches are necessary.

• Journal of Physiology & Pathology in Korean Medicine
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• v.36 no.4
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• pp.138-142
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• 2022

This study aimed to evaluate the effectiveness of Korean rehabilitation treatement for patients with post-TKR. The medical records of inpatients undergoing Korean rehabilitation treatment after TKR from 2016.01.01. to 2021.12.31. during the admission, were analyzed retrospectively. The effect of treatment was evaluated by using a numeric rating scale(NRS) and range of motion(ROM) of knee. Statistical analysis was done using the IBM SPSS statistics 26 program. If the period of hospitalization was within 7 days or change of NRS and ROM was not recorded properly, the case was excluded. All inpatients received acupuncture treatment, Electro-acupuncture. Soyeom pharmaco-acupuncture were used at a high rate. Blood letting cupping therapy, dry cupping therapy, Interferential Current Therapy(ICT) continuous passive motion(CPM), cryotherapy were used at a high rate. A significant improvement was noted when comparing the NRS and knee ROM results at the time of admission and discharge. Korean medical rehabilitation can be effectively used for patients who have undergone TKR, to relieve pain and enable returning to daily activities. It is expected to be helpful in future studies of post-TKR in Korean Medicine. Also It can be used for medical treatment of post-TKR in Korean Medicine Hospital and clinic. However, further research with a high level of evidence is necessary to support this finding.

• The Journal of Society for e-Business Studies
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• v.26 no.4
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• pp.119-131
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• 2021

With the boom of platform businesses, digital transformation has become the most important topic for businesses. Digital transformation has now become the most urgent strategy for survival, from a strategy considered as an option to choose in the past. Many companies are desperately seeking the ways to be digitally transformed. Even though there have been many studies on digital transformation, most of them are on strategic and conceptual model levels based on simple case analyses. In this study, we analyze the benefits of data integration and network effects from it, based on platform business model at the core of digital transformation. The change based on platform can be categorized into the internal one for the integration of data and better decision making, and the external one for the expansion of the businesses and better prediction of consumer behaviors through the integration of external data sets by the platform business model based enterprises. While the progress for digital transformation is not mature enough yet, financial industry is one of the most promising industries for the change and realization of the aim of it with its relatively much more advanced IT infrastructure. Many companies are making various efforts for the integration of external data, and if the good results can be accomplished, financial industry will contribute to the advancement of digital transformation in other industries as well. For "My Data" project by Korean government, we suggest the data structure and transaction of data (of Korea) should be advanced and established more quickly.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.2
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• pp.67-72
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• 2022

Recently, various intelligent application services using artificial intelligence are being actively developed. In particular, research on artificial intelligence-based real-time prediction services is being actively conducted in the manufacturing industry, and the demand for artificial intelligence services that can detect and predict fire and odors is very high. However, most of the existing detection and prediction systems do not predict the occurrence of fires and odors, but rather provide detection services after occurrence. This is because AI-based prediction service technology is not applied in existing systems. In addition, fire prediction, odor detection and odor level prediction services are services with ultra-low delay characteristics. Therefore, in order to provide ultra-low-latency prediction service, edge computing technology is combined with artificial intelligence models, so that faster inference results can be applied to the field faster than the cloud is being developed. Therefore, in this paper, we propose an LSTM algorithm-based learning model that can be used for fire prediction and odor detection/prediction, which are most required in the manufacturing industry. In addition, the proposed learning model is designed to be implemented in edge devices, and it is proposed to receive real-time sensor data from the IoT terminal and apply this data to the inference model to predict fire and odor conditions in real time. The proposed model evaluated the prediction accuracy of the learning model through three performance indicators, and the evaluation result showed an average performance of over 90%.