With the advancement and diversification of the bread industry, eco-friendly products with less sugar and salt, and containing functional ingredients are being developed. To develop healthy bread, Korean pine leaf powder was added in different proportions (0%, 1%, 3%, 5%, and 7%), and the quality characteristics of the bread, namely height, moisture, color value, texture, antioxidant property, and sensory characteristics were evaluated. As the amount of leaf powder was increased in the bread, L-value in the range of 53.45~85.05 (p<0.001) and adhesiveness in the range of 0.13~0.32 mJ (p<0.001) decreased significantly, whereas b-value in the range of 16.75~30.74 (p<0.001), total polyphenol content in the range of 466.83~669.13 ug/mL, ABTS- in the range of 0.46~43.23%, DPPH-radical in the range of 1.39~45.76%, scavenging capacities (p<0.001), color in the range of 3.27~5.40 (p=0.017) and texture in the range of 4.33~4.80 (p=0.006) preferences increased significantly. This study could increase the utilization of Korean pine leaf and the production of healthy food with antioxidant properties.

As the importance of the indoor environment increases. In response to that, performance test study was conducted for the development of high performance range hood. And the chamber casing mock-up was subjected to a performance test by applying a static pressure of 100[Pa] in accordance with KS C 9304: 2020, When the discharge port diameter was 100 mm, the standard flow rate() was 186.9 at 60.8W, the discharge port diameter was 125 mm, and the standard flow rate() at 52.0W was 184.6, which satisfies “B-type 160 to 200 (static pressure 100Pa)”. This is a result that meets the KS C 9304 : 2020.

This study investigated how to repair high-pressure pipes by applying the expansion method instead of the welding method used to repair pipes in the steel, petrochemical, and shipbuilding industries that use high-pressure pipes, and developed a pipe-specific expansion device and auxiliary equipment to use the expansion pipe. We developed an expansion device with a range of 65A to 125A, evaluated the characteristics of the equipment, and manufactured high-pressure pipes made with this device, and obtained the following conclusions. The pressure resistance performance test of the non-welded expansion device was carried out at 32A to 125A, and the pipe pressure resistance test showed good results, and the durability test confirmed the durability of 0.0061 to 0.0063mm. The vibration test of the developed expansion device was measured at 0.3~0.5mm/s, and the noise measurement result was 65.1~65.5 at 32A, 65.2~65.5 at 65A, and 65.4~66.6dB at 125A.

Recently, in the case of the root industry, although it is a basic industry that forms the basis of manufacturing competitiveness, there continues to be a shortage of manpower due to reasons such as dangerous working environments, industrial economic difficulties, and low wage systems. In addition, the demand for automation of production lines using robots is increasing due to a shrinking labor market due to a decrease in the working population due to aging, higher wages, shorter working hours, and limitations of foreign workers. In this study, a system was developed to automate the injection molding process for producing ball valves for automobiles by applying robot system. The applied process flow consists of alignment and insertion of insert parts, and removal, transfer, and loading of the product after injection molding, which is currently performed manually. Through the application of the developed robot automation system, the cycle time was improved by more than 30% and the defect rate was reduced by more than 70%.

Tendon-driven mechanisms have gained prominence in a range of applications, including soft robots, exoskeletons, and prosthetic devices. These mechanism use flexible tendons or cables to transmit force and control joint movement. As the popularity of these mechanisms grows, there is an increasing demand for solutions to enhance stability and safety. The use of brakes is a well-known solution, but existing models are difficult to customize for small soft robots. In this paper, we present a one-way shape memory alloy-based compact brake for tendon-driven mechanisms. The proposed soft brake featured a thin design and was tailored for seamless integration within a tendon-driven mechanism. In addition, the use of the one-way shape memory alloys enabled the design of the brakes that are both compact and powerful. This brake is expected to be widely used in miniaturized tendon-driven robots.

Cars using diesel have always had problems with reducing exhaust fumes, and have been studied steadily in this regard. There were studies on the remanufacturing effect of DOC catalyst deactivated by diesel vehicle smoke reduction device, analysis of vehicle fire accident cases caused by damage to diesel vehicle smoke reduction device, and related studies on the remanufacturing effect of diesel vehicle smoke reduction device DPF. This study is also to develop an exhaust flow control unit suitable for an exhaust engine to completely burn smoke generated by an engine using a diesel engine in a low temperature exhaust gas. The main systems to be developed are high-performance heaters, burner structures that can maintain ignition in exhaust flows, and exhaust flow control units that reduce exhaust gas backflow effects caused by diesel engines.

본 논문의 목적은 급변하는 현대전 양상과 글로벌 우주안보 환경 변화에 대응하기 위한 한국군의 국방 우주력 발전을 위해서 필요한 과제에 대해 고찰해 봄에 있다. 탈냉전시기 미래전 양상은 정보통신 무기체계가 복합체계를 구성하여 ‘네트워크화’ 된 전장 환경 하에서 우주와 사이버, 전자기 위협까지 포함하는 전장공간으로 진화됐다. 이에 본고에서는 4차 산업혁명의 유무인 복합체계 활용과 우주영역인식(SDA)에 대한 패러다임 전환 하에서 합동성에 기반 한국군의 국방 우주력 구축에 필요한 과제에 대해 집중적으로 고찰했다. 4 차 산업혁명 기술과 융합된 국방 우주력의 이론적 고찰과 탈냉전시기 미 국, 러시아, 중국, 일본, 북한의 우주 군사화 양상을 아더 라이케(Arther Lykke)가 제안한 목표, 방법, 수단 이론 등을 중심으로 분석했다. 한국군은 우주안보 위협에 대비하고 우주영역인식(SDA) 변화에 대응하기 위해서 항공우주청 설립, 우주기술 및 군사력 증진, 한미 우주협력 및 우주동맹 확대, 민관군 협력 및 우주관련 예산 확충, 체계적인 인력양성 등의 필요성에 대해 제시했다.

ars using diesel have always had problems with reducing exhaust fumes, and have been studied steadily in this regard. There were studies on the remanufacturing effect of DOC catalyst deactivated by diesel vehicle smoke reduction device, analysis of vehicle fire accident cases caused by damage to diesel vehicle smoke reduction device, and related studies on the remanufacturing effect of diesel vehicle smoke reduction device DPF. This study also developed an optimized system for complete combustion of smoke generated by institutions using diesel engines in low-temperature exhaust gases. The main systems to be developed are high-performance heaters, burner structures that can maintain ignition in exhaust flows, and exhaust flow control units that reduce exhaust gas backflow effects caused by diesel engines.

This study aimed to develop an optimal greenhouse model for strawberry seedling during the summer high-temperature period based on the results of field surveys. We conducted a survey on the structure types of 46 strawberry seedling farms nationwide, including width, ridge height, eaves height, ventilation method, seedling bed width, and spacing. Based on the survey results, we derived the optimal greenhouse model by considering various factors. The greenhouse width was set at 14 meters to maximize the efficiency of seedling beds and overall space. The height was determined at 2 meters, taking into account ventilation during the summer season. To reduce stress on the supporting structure due to snow loads, we established a reinforcement installation angle of 50 degrees. We analyzed two different models that use support beams with dimensions of φ48.1×2.1t and φ59.9×3.2t, respectively, to ensure structural safety against meteorological disasters, considering regional design wind speeds and snow accumulation. We utilized these developed greenhouse model to conduct strawberry seedling experiments, resulting in a high survival rate of average 93.2%. These findings confirm the usefulness of the strawberry seedling greenhouse in improving the seedling environment and enhancing overall efficiency.

This study was conducted to develop a model for predicting the growth of kimchi cabbage using image data and environmental data. Kimchi cabbages of the ‘Cheongmyeong Gaual’ variety were planted three times on July 11th, July 19th, and July 27th at a test field located at Pyeongchang-gun, Gangwon-do (37°37′ N 128°32′ E, 510 elevation), and data on growth, images, and environmental conditions were collected until September 12th. To select key factors for the kimchi cabbage growth prediction model, a correlation analysis was conducted using the collected growth data and meteorological data. The correlation coefficient between fresh weight and growth degree days (GDD) and between fresh weight and integrated solar radiation showed a high correlation coefficient of 0.88. Additionally, fresh weight had significant correlations with height and leaf area of kimchi cabbages, with correlation coefficients of 0.78 and 0.79, respectively. Canopy coverage was selected from the image data and GDD was selected from the environmental data based on references from previous researches. A prediction model for kimchi cabbage of biomass, leaf count, and leaf area was developed by combining GDD, canopy coverage and growth data. Single-factor models, including quadratic, sigmoid, and logistic models, were created and the sigmoid prediction model showed the best explanatory power according to the evaluation results. Developing a multi-factor growth prediction model by combining GDD and canopy coverage resulted in improved determination coefficients of 0.9, 0.95, and 0.89 for biomass, leaf count, and leaf area, respectively, compared to single-factor prediction models. To validate the developed model, validation was conducted and the determination coefficient between measured and predicted fresh weight was 0.91, with an RMSE of 134.2 g, indicating high prediction accuracy. In the past, kimchi cabbage growth prediction was often based on meteorological or image data, which resulted in low predictive accuracy due to the inability to reflect on-site conditions or the heading up of kimchi cabbage. Combining these two prediction methods is expected to enhance the accuracy of crop yield predictions by compensating for the weaknesses of each observation method.

축산물 중 잔류허용기준이 설정되어 관리하고 있는 농약 azocyclotin, cyhexatin, fenbutatin oxide는 대표적인 유 기주석계 살비제이다. 기존 시험법은 가스크로마토그래피 를 사용하여 정량한계가 높고 분석 시 재현성이 떨어져 이에 대한 개선이 필요한 실정으로 본 연구에서는 비교적 간편하며 시간이 적게 소요되는 QuEChERS법을 활용하여 azocyclotin, cyhexatin, fenbutatin oxide의 시험법을 마련하 고자 하였다. 1% 아세트산을 함유한 아세트산에틸:아세토 니트릴(1:1) 혼합액을 이용하여 진탕 추출 후 d-SPE로 정 제하고 이를 농축 후 LC-MS/MS를 이용한 시험법을 개발 하였다. Azocyclotin, cyhexatin 및 fenbutatin oxide의 결정 계수(R2)는 0.99 이상으로 높은 직선성을 확인하였으며 정 량한계는 0.01 mg/kg으로 높은 감도를 나타내었다. 대표 축산물 5종(소, 돼지, 닭, 계란, 우유)에서 LOQ(0.01 mg/ kg), MRL(0.05 mg/kg), MRL 10배(0.5 mg/kg)의 농도에서 회수율 실험을 한 결과 평균 회수율이 76.4-115.3% 및 84.4-110.8%이었으며, 상대표준편차는 25.3% 이하로 나타 났다. 본 연구는 Codex 가이드라인(CAC/GL 40-1993, 2003) 및 ‘식품의약품안전처 식품의약품안전평가원의 식 품등 시험법 마련 표준절차에 관한 가이드라인(2016)’에 적합한 수준임을 확인하였다. 따라서 본 연구에서 확립한 시험법은 축산물 중 잔류할 수 있는 azocyclotin, cyhexatin, fenbutatin oxide의 안전관리를 위한 공정시험법으로 활용 가능할 것으로 판단된다.

본 연구의 목적은 민주시민이자 세계시민으로서 갖추어야 할 자질과 현재와 미래 사회에서 요구되는 인성을 평가하는 성찰-실천기반 인성척 도를 개발하는 것이다. 첫째, 50개의 예비문항으로 탐색적 요인분석을 수행한 결과 총 8개 요인(자기이해, 공감, 공정, 협동, 인권, 미디어리터 러시, 환경, 그리고 타문화이해, 각 요인당 4개 문항)을 추출하였다. 둘 째, 급내상관계수를 이용하여 척도의 검사-재검사 신뢰도를 평가하였고, 그 결과 8개 요인 모두 높게 나타났다. 셋째, 32개 문항으로 확인적 요 인분석을 수행한 결과 성찰-실천기반 인성척도 모형은 전체 설명변량 중 65.67%를 설명하였고 모형 적합도 지수는 좋은 것으로 나타났다. 본 척 도의 신뢰도와 타당도 모두 높게 나타났다. 이들 결과는 성찰-실천기반 인성척도는 타당하고 신뢰할 만한 인성 측정 도구로 사용될 수 있다는 것을 나타낸다. 본 연구의 성찰-실천기반 인성척도를 교육 현장에 적용 하여 인성교육의 효과성과 그 효과의 지속성을 검증하는데 사용할 수 있 을 것이다.

This study was conducted to determine the optimal dipping time and concentration of gibberellin for improving the growth and quality of domestic cultivar 'Seolhyang' strawberry when using runner plants. Strawberry runner plants were collected on November 10th and soaked in GA3 concentrations of 50, 100, and 150 mg·L-1 for 30 and 60 minutes, respectively. After 75 days of planting, the growth results showed that in the 30-minute, 50 mg·L-1 treatment, the crown diameter was thicker and the T/R ratio was lower, indicating better plant vitality. Runner length increased with lower gibberellin concentrations, particularly promoting vegetative growth. Photosynthetic efficiency was more influenced by gibberellin concentration than dipping time, and using concentrations above a certain threshold acted as a stress factor for runner plants, leading to decreased photosynthetic efficiency. For enhancing seedling growth, soaking with 50 mg·L-1 of gibberellin for 30 minutes was found to be optimal. This study verified the effects of gibberellin treatment on strawberry runner plants to improve plant growth and quality, providing useful basic data for using gibberellin.

Rapid and accurate detection of pathogenic bacteria is crucial for various applications, including public health and food safety. However, existing bacteria detection techniques have several drawbacks as they are inconvenient and require time-consuming procedures and complex machinery. Recently, the precision and versatility of CRISPR/Cas system has been leveraged to design biosensors that offer a more efficient and accurate approach to bacterial detection compared to the existing techniques. Significant research has been focused on developing biosensors based on the CRISPR/Cas system which has shown promise in efficiently detecting pathogenic bacteria or virus. In this review, we present a biosensor based on the CRISPR/Cas system that has been specifically developed to overcome these limitations and detect different pathogenic bacteria effectively including Vibrio parahaemolyticus, Salmonella, E. coli O157:H7, and Listeria monocytogenes. This biosensor takes advantage of the CRISPR/Cas system's precision and versatility for more efficiently accurately detecting bacteria compared to the previous techniques. The biosensor has potential to enhance public health and ensure food safety as the biosensor’s design can revolutionize method of detecting pathogenic bacteria. It provides a rapid and reliable method for identifying harmful bacteria and it can aid in early intervention and preventive measures, mitigating the risk of bacterial outbreaks and their associated consequences. Further research and development in this area will lead to development of even more advanced biosensors capable of detecting an even broader range of bacterial pathogens, thereby significantly benefiting various industries and helping in safeguard human health

PURPOSES : To prevent an increasing number of drowsiness-related accidents, considering driver fatigue is necessary, which is the main cause of drowsiness accidents. The purpose of this study is to propose a methodology for selecting drowsiness hotspots using continuous driving time, a variable that quantifies driver fatigue. METHODS : An analysis was conducted by dividing driver fatigue, which changes according to time and space, into temporal and spatiotemporal scenarios. The analysis technique derived four evaluation indicators (precision, recall, accuracy, and F1 score) using a random forest classification model that is effective for processing large amounts of data. RESULTS : Both the temporal and spatiotemporal scenarios performed better in models that reflected the characteristics of road sections with changes in time and space. Comparing the two scenarios, it was found that the spatiotemporal scenario showed a difference in precision of approximately 10% compared with the temporal scenarios. In addition, [Model 2-2] of the spatiotemporal scenario showed the best predictive power by assessing the model’s accuracy via a comparison of (1-recall) and precision. This shows better performance in predicting drowsy accidents by considering changes in time and space together rather than constructing only temporal changes. CONCLUSIONS : To classify hotspots of drowsiness, spatiotemporal factors must be considered. However, it is possible to develop a methodology with better performance if data on individuals driving vehicles can be collected.

PURPOSES : In this study, a model was developed to estimate the concentrations of particulate matter (PM2.5 and PM10) in expressway tunnel sections. METHODS : A statistical model was constructed by collecting data on particulate matter (PM2.5 and PM10), weather, environment, and traffic volume in the tunnel section. The model was developed after accurately analyzing the factors influencing the PM concentration. RESULTS : A machine learning-based PM concentration estimation model was developed. Three models, namely linear regression, convolutional neural network, and random forest models, were compared, and the random forest model was proposed as the best model. CONCLUSIONS : The evaluation revealed that the random forest model displayed the least error in the concentration estimation model for (PM2.5 and PM10) in all tunnel section cases. In addition, a practical application plan for the model developed in this study is proposed.

PURPOSES : The purpose of this study is to derive dropout rates according to various international roughness index (IRI) specifications using ProVAL, develop a comparative methodology, and indirectly assess the level of road management in each country. METHODS : Based on a literature review, the IRI specifications for each country were collected, and the ProVAL analysis tool was used to compare and analyze dropout rates according to each specification. Thus, the dropout rate rankings for each country were calculated. Additionally, by analyzing the correlation between dropout rates according to each threshold, a model was created to convert the threshold between the most commonly used baseline distances of 100 m and 161 m. RESULTS : Dropout rates were derived according to the standards of each country and rankings were assigned. Comparing 51 standards, the IRI level of New Mexico appeared to be the highest, whereas the domestic specifications ranked 36th. A model was created to convert the threshold between the standard distances of 100 m and 161 m. CONCLUSIONS : This study objectively assessed the roughness standards in various countries using the dropout rate and IRI ranking specifications. The highest specification was found for the asphalt of New Mexico in the USA, with the domestic specification ranking 36th. A model that converts the thresholds between the most commonly used baseline distances of 100 m and 161 m was developed, with slight differences across sections. For a precise conversion, individual models may be required for each section.

본 연구의 목적은 긍정조직 구축을 위한 강점기반 코칭프로그램을 개발하여 콜센터 조직의 긍정성을 높이는 데 있다. 본 연구에서는 문헌고찰, 콜센터 상담사의 조직에 대한 긍정성 인식 및 요구 도 조사를 기반으로 프로그램의 시안을 개발하였고, 전문가의 적절성 및 예비연 구를 통해 프로그램의 최종안을 개발하였다. 본 연구에서 개발된 프로그램은 긍 정적인 조직이 형성되는 요인인 긍정정서 확장, 긍정정서 탐구, 긍정정서 활용, 긍정적 관계형성을 위한 활동으로 14회기로 구성하였다. 교육내용은 긍정조직 구축을 지원할 수 있도록 강의, 강점진단, 코칭실습 등 다양한 방법들을 도입하 고, 경청, 질문, 인정과 피드백 등의 코칭기술을 세부 내용에 맞게 적용하였다. 본 연구에서 개발한 긍정조직 구축을 위한 코칭프로그램은 긍정심리 강점을 활용한 프로그램 내용과 방법의 기초연구로서, 코칭스킬과 코칭대화 모델을 접 목한 코칭프로그램을 개발하여 긍정조직 구축을 위한 조직 구성원의 역량을 강 화시켰다는 점에서 의의가 있다.

HNS(Hazardous and Noxious Substances)는 해양환경에 유입될 경우 인간 및 해양생물에게 해를 끼치거나, 해양시설에 부식 등의 손상을 입히거나 기타 해역의 이용을 방해할 수 있다. HNS의 규제나 관리를 위해서는 과학적인 방법을 통하여 우선순위 대상의 선정이 필요하며 이러한 방법론으로 CRS(Chemical Ranking and Scoring)기법이 전세계적으로 개발되어 사용되고 있다. 본 연구에서는 해양산업시 설로부터 해양환경으로 배출되는 HNS의 체계적 관리를 목적으로 국내외 CRS 체계를 비교 분석하였으며, 이를 통하여 우선순위 선정 도 출체계를 확립하고 연구대상 지역 및 대상시설을 선정하고 우선순위 선정체계 주요인자를 도출하였다. 또한 주요인자별 세부인자 및 정 량적 배점체계를 구축하였다. 주요인자는 각각 사회적 관심과 이슈(20점), 물질거동(10점), 노출가능성(30점), 독성(35점), 해양이용에의 영 향(5점)을 상대적으로 부여하였으며, 독성과 물질거동 세부인자의 곱을 통하여 100점만점으로 환산가능하도록 적용하였으며, 불확실성점 수(Uncertainty score)와 불확실성 비율(Uncertainty ratio)와 혼합물에 대한 고려방안을 제시하였다. 본 연구결과는 해양산업시설로부터 배출/ 유출되는 HNS 관리를 위하여 우선순위 선정시 활용될 수 있을 것으로 기대된다.

우리나라 해양환경에 유출되는 위험·유해물질(Hazardous Noxious Substances, HNS)의 해양환경 및 사회환경 영향평가 결과 와 HNS 확산 영역, 해양환경 정보, HNS 실태조사 결과 등 관련 연구 결과 및 자료를 정책결정자와 연구자들에게 공유할 수 있는 HNS 국내 용 플랫폼을 구축하고자 한다. 국내의 HNS 관리 및 배출 체계 마련을 위한 의사결정 지원이 가능하고 국내 실정에 적합한 플랫폼의 설계 를 위하여 유해물질의 데이터 관리 및 유출 시 대응 도구, 기초적인 정보 등 플랫폼에 관련된 기술동향을 분석하는 등 국내·외의 플랫폼 개발 사례를 고찰하였다. 유속 벡터의 전처리 기능 개발, 전처리 결과에 따른 동적 시각화 구현, 해양산업시설 배출 HNS의 유출량과 유출 범위의 전처리 모듈, HNS 해양환경 영향평가 연산 모듈 프로토타입을 개발하였다. HNS 해양환경 영향평가를 위한 국내용 HNS 플랫폼은 초기 위해성을 평가하고 대응 및 관련 법제화 시 과학적인 기초 도구로써 활용될 수 있을 것으로 기대된다.