A heavy (93 mm hr−1) rainfall event accompanied by lightning occurred over Gangneung in the Yeongdong region of South Korea on August 6, 2018. This study investigated the underlying mechanism for the heavy rainfall event by using COMS satellite cloud products, surface- and upper-level weather charts, ECMWF reanalysis data, and radiosonde data. The COMS satellite cloud products showed rainfall exceeding 10 mm hr−1, with the lowest cloud-top temperature of approximately −65oC and high cloud optical thickness of approximately 20-25. The radiosonde data showed the existence of strong vertical wind shear between the upper and lower cloud layers. Furthermore, a strong inversion in the equivalent potential temperature was observed at a pressure altitude of 700 hPa. In addition, there was a highly developed cloud layer at a height of 13 km, corresponding with the vertical analysis of the ECMWF data. This demonstrated the increased atmospheric instability induced by the vertical differences in equivalent potential temperature in the Yeongdong region. Consequently, cold, dry air was trapped within relatively warm, humid air in the upper atmosphere over the East Sea and adjacent Yeongdong region. This caused unstable atmospheric conditions that led to rapidly developing convective clouds and heavy rainfall over Gangneung.

한국 정부는 2012년에 ’목재의 지속가능한 이용에 관한 법률’을 제정하고 합법벌채된 목재 또는 목재제품의 유통·이용에 대한 국가차원의 관리체계를 마련하였다. 이를 위해 산림청은 세부 시행체계를 마련하고 제도의 실효성을 높이기 위해 다음과 같이 노력을 기울여 왔다. 1.산업계에 미칠 영향을 사전 조사하고 의견 수렴 2.정부·공공기관·연구기관(산림청, 한국임업진흥원, 국립산림 과학원, 순서대로)으로 구성된 태스크 포스팀 조직, 로드 맵 제시 3.제도에 대한 인지도와 참여의사에 관한 조사 수행 4.우선 대상 품목 선정, 시범운영 기간 동안 단계별로 적용 품목 확대 5.관세청의 전자통관시스템과 산림청의 목재자원관리시스템을 연계, 이중 행정절차 간소화 및 수입검사 기능 전산화 실현 6.국가별 표준가이드 및 사전진단서비스를 제공, 영세한 수입업자를 보호하는 제도적 장치 마련. 끝으로 합법목재 교역촉진제도의 정착을 위해 선행되어야 할 네 가지 사항을 아래와 같이 정리하였다. 1.국가 차원의 제도 조기정착을 위한 정책적 지원역할 강화 2.제도 활성화를 위한 인센티브 마련과 사후관리 필요 3.국내·외 조성된 목재자원의 유통, 이용을 위한 시스템 활용 확대 4.민관 협력체계와 시민사회 모니터링이 활성화될 수 있는 환경 조성.

This study analyzed ignition probability about Lithium-polymer batteries of what variously were being produced wearable devices recently. The study analyzed ignition probability by PCM(Protection Circuit Module) operating state and overcharged, over-discharged, exposed to high temperatures of Lithium polymer batteries, analyzing wearable devices on the market. Then it classified experimental results to implement analysis comparison about weight, X-ray imaging, battery decomposition. With these experiments, the study analyzed combustion-possibility and fire patterns. These statistics will be used to measure and verify the cause of a fire when identify wearable devices using Lithium-polymer batteries.

This paper recognizes the risk of ignition of air fryer (machine that can cook fried dishes with hot air without oil) that is far exceeding the sales rate of microwave ovens, which is necessary to modern household kitchen, and identifies fire risk through the operation principle of the process of heat transfer, and the main structure of the machine. The fire test that we conducted is to observe the risk of ignition of the machine due to the damage to the safety system and the possibility of igniting oil paper along with food, to experiment with the possibility of ignition due to blockage of the exhaust due to obstacles, and accumulation of oil stains on the hot wire, and to present the method of fire control and devise countermeasures.

페르시아 전쟁(기원전 490-479년)을 시작으로 알렉산드로스 대왕의 죽음(기원전 323년) 에 이르기까지 크고 작은 전투와 전쟁이 끊임없이 벌어졌던 그리스의 전장에 세워진 트로파이온에는 고전기 그리스인들의 전쟁과 승리에 대한 관념이 담겨있다. 그리스의 초기 트로파이온은 전장에 전쟁의 승패가 결정된 직후에 세워진다는 특징을 갖는다. 그리고 그것을 세움으로써 승자는 신들에 대한 감사를 표현하고 미래의 전투에 대한 승리를 담보하고자 하였다. 동시에 이것은 전우들과 승리의 기억을 공유하고, 적군에게는 패배를 시각적으로 각인시킴으로써 그들의 잠재적인 도발의 의지를 상실하게 만드는 마지막 전략이기도 하였다. 본 연구에서 살펴본 기원전 5세기의 도기들과 아테나 니케 신전의 난간을 장식한 부조는 그러한 전술의 기록이다.

With YouTube’s overwhelming share of the market, research on analyzing the types of content on YouTube is essential. An analysis of major global fashion YouTubers that the types of video content could be largely classified into three main categories: Fashion, beauty and daily life. The fashion category was subdivided into styling and fashion product review content type. The beauty category was subdivided into tutorials, beauty product reviews, and beauty tip content types. The daily life category was subdivided into daily sharing, consultation, and Q & A content types. Video content within fashion YouTuber channels is accompanied by expertise in fashion and beauty. At the same time, videos on daily life are uploaded, and through interactive communication with viewers, YouTubers form an intimate bond with subscribers. Content emphasizing entertainment, not just information delivery that introduces fashion products, is attracting growing interest among subscribers. This study analyzed the content of the increasingly popular fashion YouTuber channels and determined its important characteristics. The study makes a significant contribution to academic research by laying a foundation for future studies of YouTube content in the fashion field. Since differences in country of birth and race among YouTubers may influence content production, follow-up research will be conducted on the types and characteristics of domestic fashion YouTubers.

This study defines the concept of the fashion meme, which has recently emerged as a fashion trend, influential fashion keyword. After analyzing the concepts and characteristics of traditional memes from prior studies, examples of fashion memes were collected from online community and social network services, while a literature study and case study analysis were conducted in parallel drawing on related articles and journals. Modern fashion memes refer to fashion-related symbols and fashion images that are spread online by word-of-mouth, together with fashion styles and items that spread as a result of being worn. Fashion memes in cyberspace are mainly spread through social network or message services, and sometimes combine text, images, videos, hashtags, and emoticons. Fashion memes are a type of collective action of the people in response to social problems in the world, and often involve humorous antics, satire, shock, and eccentricity. Shared fashion memes reflect the expression of personality expression and fun, and at the same time are used as an expression of designer and brand creativity and are integral to marketing. Fashion memes are classified into four types, based on two central axes as follows: non-commercial/ commercial and anti-fashion/fashion-friendly. Unlike traditional memes, Internet-based fashion memes emphasize elements of transformation through creativity as well as imitation, which has become a persisting contemporary trend beyond temporary phenomena.

Various elements of Fabrication (FAB), mass production of existing products, new product development and process improvement evaluation might increase the complexity of production process when products are produced at the same time. As a result, complex production operation makes it difficult to predict production capacity of facilities. In this environment, production forecasting is the basic information used for production plan, preventive maintenance, yield management, and new product development. In this paper, we tried to develop a multiple linear regression analysis model in order to improve the existing production capacity forecasting method, which is to estimate production capacity by using a simple trend analysis during short time periods. Specifically, we defined overall equipment effectiveness of facility as a performance measure to represent production capacity. Then, we considered the production capacities of interrelated facilities in the FAB production process during past several weeks as independent regression variables in order to reflect the impact of facility maintenance cycles and production sequences. By applying variable selection methods and selecting only some significant variables, we developed a multiple linear regression forecasting model. Through a numerical experiment, we showed the superiority of the proposed method by obtaining the mean residual error of 3.98%, and improving the previous one by 7.9%.

Demand for cosmetics with functionality and eco-friendliness has increased dramatically due to recent aging, well-being trends, and increased interest in beauty. Cosmetics production in 2014 was 8,970.4 billion won, an increase of about 50% compared to 6,014.6 billion won in 2010. In the midst of this, similar companies in intense competition are pursuing differentiated strategies and innovation activities to solve quality, price and delivery problems. In particular, cosmetics packaging work is getting more difficult due to the increasing bill of materials (BOM) and difficult assembly methods. Therefore, in this study, the following problems were identified and suggestions for the improvement of the packaging Many research laboratories such as biotechnology, chemistry, and pharmaceuticals, which are undergoing various studies, are equipped with ready-made laboratory safety equipments such as bio-safety workbenches, aseptic bases, and exhaust workbenches. However, most researchers are disadvantaged in using existing safety equipment. This is because existing safety equipment can not take into account all of the unique characteristics of the research. For this reason, researchers are demanding the development of customized safety equipment that is well suited to their research needs. process of Company C, which is facing difficult situation to respond to the customer 's delivery due to the 52 - hour work week. First, we used the stopwatch to find the difficulty process in the packaging process and show ways to improve it. Second, to improve the efficiency of line balancing in the packaging process, we integrate processes, improve work methods, and perform simple automation. As a result, the prepare loss for replacement was reduced by 1 minute from 5 minutes, resulting in a 23% increase in productivity from 112 ea./hour to 137ea./ hour per person. At this time, the LOB of the packaging process was improved from 70% to 82% by operating one more production line through one person per line, total 9 people saving.

Anomaly detection of Machine Learning such as PCA anomaly detection and CNN image classification has been focused on cross-sectional data. In this paper, two approaches has been suggested to apply ML techniques for identifying the failure time of big time series data. PCA anomaly detection to identify time rows as normal or abnormal was suggested by converting subjects identification problem to time domain. CNN image classification was suggested to identify the failure time by re-structuring of time series data, which computed the correlation matrix of one minute data and converted to tiff image format. Also, LASSO, one of feature selection methods, was applied to select the most affecting variables which could identify the failure status. For the empirical study, time series data was collected in seconds from a power generator of 214 components for 25 minutes including 20 minutes before the failure time. The failure time was predicted and detected 9 minutes 17 seconds before the failure time by PCA anomaly detection, but was not detected by the combination of LASSO and PCA because the target variable was binary variable which was assigned on the base of the failure time. CNN image classification with the train data of 10 normal status image and 5 failure status images detected just one minute before.