Recently, the number of elderly driver accidents has been steadily increasing. EDR(Event Data Recorder) helps a lot in understanding traffic accidents. In particular, as anxiety about SUA(Sudden Unintended Acceleration) increases, EDR data is playing an important role in accident analysis. In this study, EDR data of an accident vehicle suspected of SUA was analyzed to identify traffic accident circumstances and detailed accidents. Experimental results were derived and analyzed by simulating the situation of SUA while driving a car. As a result, it was found that normal braking is performed when the brake pedal is operated even in dangerous situations such as mechanical defects and driver malfunctions. Rather than finding the cause of an accident after a traffic accident, countermeasures are needed to prevent mechanical defects and driving malfunctions before a traffic accident.

기존 항만 건설 시 화물차 전용 주차장이 고려되지 않았으며, 해양수산부의 ‘제2차 신항만건설기본계획(2019~2040)’에 따라 총 11 개의 새로운 항만이 건설될 예정이다. 따라서 화물차 전용 주차장 설계에 대한 연구가 필요한 실정이다. 현재 항만에서는 화물차 전용 주차 공간 부족으로 불법 주차가 발생하고 있으며, 이로 인해 교통사고 위험이 증가하고 있다. 기존 연구에서는 전체 항만을 대상으로 한 분류 방법이 제안되었으나, 신설 항만 설계 시 과소 또는 과대 설계 문제를 초래한다. 따라서 본 연구는 부두별로 4대 요소(안벽 길이, 야적장 면적, 접안 능력, 하역 능력)를 기반으로 분류하며, DWT와 TEU 단위를 고려하여 데이터를 분석하였다. 14개 국가 관리 항만의 총 380 부두 데이터를 조사하고, 이를 통해 그룹핑 작업을 통해 정규화 곡선으로 평균 ± 표준편차를 기준으로 항만 전체 부두 에 대한 분류를 실시하였다. 이를 통해 향후 연구결과를 통해 검증 후 최종 분류방법을 결정하여 새로운 항만분류법을 제안하고, 제안 된 방법론의 분류검증을 실시할 예정이다.

Truck no-show behavior has posed significant disruptions to the planning and execution of port operations. By delving into the key factors that contribute to truck appointment no-shows and proactively predicting such behavior, it becomes possible to make preemptive adjustments to port operation plans, thereby enhancing overall operational efficiency. Considering the data imbalance and the impact of accuracy for each decision tree on the performance of the random forest model, a model based on the Borderline Synthetic Minority Over-Sampling Technique and Weighted Random Forest (BSMOTE-WRF) is proposed to predict truck appointment no-shows and explore the relationship between truck appointment no-shows and factors such as weather conditions, appointment time slot, the number of truck appointments, and traffic conditions. In order to illustrate the effectiveness of the proposed model, the experiments were conducted with the available dataset from the Tianjin Port Second Container Terminal. It is demonstrated that the prediction accuracy of BSMOTE-WRF model is improved by 4%-5% compared with logistic regression, random forest, and support vector machines. Importance ranking of factors affecting truck no-show indicate that (1) The number of truck appointments during specific time slots have the highest impact on truck no-show behavior, and the congestion coefficient has the secondhighest impact on truck no-show behavior and its influence is also significant; (2) Compared to the number of truck appointments and congestion coefficient, the impact of severe weather on truck no-show behavior is relatively low, but it still has some influence; (3) Although the impact of appointment time slots is lower than other influencing factors, the influence of specific time slots on truck no-show behavior should not be overlooked. The BSMOTE-WRF model effectively analyzes the influencing factors and predicts truck no-show behavior in appointment-based systems.

In general, small and medium-sized computer rooms do not have access floors for reasons of increased floor height and increased construction cost. Therefore, the air conditioning method used here applies the method of directly blowing the cold air of the air conditioner into the computer room. In this case, the hot/cold air is not separated, and as the hot air is recirculated, it is re-introduced to the front of the server rack, resulting in a problem that the server cooling efficiency is decreased. In addition, in such a computer room structure, it is difficult to configure and install a containment system. In this study, we tried to understand the problem of the formation airflow in the case of using the existing air conditioning method, and to find a method of configuring the air conditioning environment to improve the cooling efficiency. The purpose of this study was to understand the airflow/temperature distribution in the computer room using the CFD simulation method. In addition, the thermal characteristics of various air-conditioning environments such as the location of the CRAC cold air discharge location, the layout between server rack and CRAC and the containment were reviewed.

본 연구에서는 커피(C. Arabica)의 FT-IR 스펙트럼 데이터 를 기반한 다변량통계분석을 이용한 대사체 분석을 통해 품종 식별을 하여 육종 연구에 기초자료로 활용하고자 한다. 1. FT-IR 스펙트럼 데이터를 이용한 PCA(principal component analysis), PLS-DA(partial least square discriminant analysis) 그리고 HCA(hierarchical clustering analysis) 분석을 통해 품종 분류가 가능하였다. 2. 커피 품종들은 FT-IR 스펙트럼 부위인 1700-1500-1 (Amide I 과 II을 포함하는 아미노산 및 단백질계열의 화합물 들), 1500-1300-1 (phosphodiester group을 포함한 핵산 및 인지질의 정보), 1100-950cm-1 (단당류나 복합 다당류를 포함하는 carbohydrates 계열의 화합물)에서 질적, 양적 정보의 차이가 나타났다. 3. PCA 상에 나타난 8품종의 커피 품종이 각각 그룹을 형성하였다. 그 중 ‘Caturra’와 ‘Mahsellesa’ 품종은 각각의 그룹을 나타내면서 C. arabica 종에서도 다른 대사체 정보를 나타내는 것으로 확인하였고, ‘Catuai’, ‘CR-95’, ‘Geisra’, ‘Obata’, ‘Vemecia’ 그리고 ‘non’ 품종은 유사한 대사체 정보를 나타내는 것으로 확인하였다. 4. PLS-DA 분석의 경우 PCA 분석 보다 커피 품종간 식별이 뚜렷하게 나타났다. 5. 본 연구에서 확립된 대사체 수준에서 커피의 품종 식별 기술은 품종, 계통의 신속한 선발 수단으로 활용이 가능할 것으로 기대되며 육종을 통한 품종개발 가속화에 기여 할 수 있을 것으로 예상된다.

본 연구에서는 초고층건축물의 풍진동 모니터링을 위한 시스템식별기법의 현장적용성을 평가하였다. 실제 아웃리거-벨트월 을 횡력저항 시스템으로 가지는 실제 63층 RC구조물을 대상으로 상시 및 강풍시 응답을 모니터링하였으며, 진동수영역분해(FDD), 랜덤감소(RDT)기법, 부분공간시스템식별(SSI)법을 사용하여 진동특성을 식별하였다. 건물의 평면이 정방형이고, 두 개의 횡방향 모드의 진동수는 매우 유사하였다. 모든 식별기법에서 태풍과 같이 강한 외력이 존재할 경우 뿐만 아니라 상시미진동 에서도 구조물의 모드 특성을 식별할 수 있었다. 현장에서의 적용성 평가결과, 계산속도는 FDD가 가장 빨랐으며, RDT가 가장 간단한 프로그래밍 절차를 가지고 있음을 확인하였다.

본 논문에서는 국제해사기구의 데이터수집 시스템 도입에 따른 MRV 지원 및 국제해운 에너지 효율 포탈 시스템에 대한 기술적 검증을 수행하였다. 데이터 수집 시스템과 연료 사용량 데이터 수집 방법론을 포함하는 SEEMP 가이드라인의 주요 내용을 검토하고, EU MRV와 차이점을 분석하여 MRV에 대한 국내 해운선사의 대응전략을 제시하고 이에 대한 MRV 지원시스템의 기술적 적합성을 검토하였다. MRV 지원시스템은 배출량 데이터를 원시단계에서 최종단계까지 통합 관리함으로서 검증을 위한 비용과 업무 효율성을 높일 수 있으며, 현재 해운선사의 보고절차를 유지하면서 데이터 변환 기능을 통해 표준양식으로 배출량 데이터를 수집하고 보고 할 수 있다. 또한, 포탈시스템에 대한 접근권한을 구분하여 해운선사의 데이터 수집과 보고, 검증자의 데이터 검증업무를 지원할 수 있으며 전자적인 방법으로 보고서 제출이 가능하여 MRV 국제 규제에 대한 대응이 가능하다.

Naval combat system developed in-country is progressing at an alarming rate since 2000. ROK navy will be achieved all vessels that have combat system in the near future. The importance of System Engineering and Integrated Logistics Support based on reliability analysis is increasing. However, reliability analysis that everyone trusted and recognized is not enough and applied practically for development of Defense Acquisition Program. In particular, Existing Reliability Analysis is focusing on reliability index (Mean Time Between Failure (MTBF) etc.) for policy decision of defense improvement project. Most of the weapon system acquisition process applying in the exponential distribution simply persist unreality due to memoryless property. Critical failures are more important than simple faults to ship’s operator. There are no confirmed cases of reliability analysis involved with critical failure that naval ship scheduler and operator concerned sensitively.Therefore, this study is focusing on Mean Time To Critical Failure (MTTCF), reliability on specific time and Operational Readiness Float (ORF) requirements related to critical failure of Patrol Killer Guided missile (PKG) combat system that is beginning of naval combat system developed in-country. Methods of analysis is applied parametric and non-parametric statistical techniques. It is compared to the estimates and proposed applications. The result of study shows that parametric and non-parametric estimators should be applied differently depending on purpose of utilization based on test of normality. For the first time, this study is offering Reliability of ROK Naval combat system to stakeholders involved with defense improvement project. Decision makers of defense improvement project have to active support and effort in this area for improvement of System Engineering.

India is largest producer of banana in the world producing 29.72 million tonnes from an area of 0.803 million ha with a productivity of 35.7 MT ha-1 and accounted for 15.48 and 27.01 per cent of the world’s area and production respectively (www.nhb.gov.in). In India, Tamil Nadu leads other states both in terms of area and production followed by Maharashtra, Gujarat and Andhra Pradesh. In Rayalaseema region of Andhra Pradesh, Kurnool district had special reputation in the cultivation of banana in an area of 5765 hectares with an annual production of 2.01 lakh tonnes in the year 2012-13 and hence, it was purposively chosen for the study. On 23rd November 2003, the Government of Andhra Pradesh has commenced a comprehensive project called ‘Andhra Pradesh Micro Irrigation Project (APMIP)’, first of its kind in the world so as to promote water use efficiency. APMIP is offering 100 per cent of subsidy in case of SC, ST and 90 per cent in case of other categories of farmers up to 5.0 acres of land. In case of acreage between 5-10 acres, 70 per cent subsidy and acreage above 10, 50 per cent of subsidy is given to the farmer beneficiaries. The sampling frame consists of Kurnool district, two mandals, four villages and 180 sample farmers comprising of 60 farmers each from Marginal (<1ha), Small (1-2ha) and Other (>2ha) categories. A well structured pre-tested schedule was employed to collect the requisite information pertaining to the performance of drip irrigation among the sample farmers and Data Envelopment Analysis (DEA) model was employed to analyze the performance of drip irrigation in banana farms. The performance of drip irrigation was assessed based on the parameters like: Land Development Works (LDW), Fertigation costs (FC), Volume of water supplied (VWS), Annual maintenance costs of drip irrigation (AMC), Economic Status of the farmer (ES), Crop Productivity (CP) etc. The first four parameters are considered as inputs and last two as outputs for DEA modelling purposes. The findings revealed that, the number of farms operating at CRS are more in number in other farms (46.66%) followed by marginal (45%) and small farms (28.33%). Similarly, regarding the number of farmers operating at VRS, the other farms are again more in number with 61.66 per cent followed by marginal (53.33%) and small farms (35%). With reference to scale efficiency, marginal farms dominate the scenario with 57 per cent followed by others (55%) and small farms (50%). At pooled level, 26.11 per cent of the farms are being operated at CRS with an average technical efficiency score of 0.6138 i.e., 47 out of 180 farms. Nearly 40 per cent of the farmers at pooled level are being operated at VRS with an average technical efficiency score of 0.7241. As regards to scale efficiency, nearly 52 per cent of the farmers (94 out of 180 farmers) at pooled level, either performed at the optimum scale or were close to the optimum scale (farms having scale efficiency values equal to or more than 0.90). Majority of the farms (39.44%) are operating at IRS and only 29 per cent of the farmers are operating at DRS. This signifies that, more resources should be provided to these farms operating at IRS and the same should be decreased towards the farms operating at DRS. Nearly 32 per cent of the farms are operating at CRS indicating efficient utilization of resources. Log linear regression model was used to analyze the major determinants of input use efficiency in banana farms. The input variables considered under DEA model were again considered as influential factors for the CRS obtained for the three categories of farmers. Volume of water supplied (X1) and fertigation cost (X2) are the major determinants of banana farms across all the farmer categories and even at pooled level. In view of their positive influence on the CRS, it is essential to strengthen modern irrigation infrastructure like drip irrigation and offer more fertilizer subsidies to the farmer to enhance the crop production on cost-effective basis in Kurnool district of Andhra Pradesh, India. This study further suggests that, the present era of Information Technology will help the irrigation management in the context of generating new techniques, extension, adoption and information. It will also guide the farmers in irrigation scheduling and quantifying the irrigation water requirements in accordance with the water availability in a particular season. So, it is high time for the Government of India to pay adequate attention towards the applications of ‘Information and Communication Technology (ICT) and its applications in irrigation water management’ for facilitating the deployment of Decision Supports Systems (DSSs) at various levels of planning and management of water resources in the country.

This study of small ＆ Medium-Sized construction sites construction disaster prevention technology conduction-site visits from the map results report by the inspector on-site advice and technical guidance for the analysis of deficiencies and potential construction of disaster revealed the potential factors causing an accident as follows. As a results, Should not be a once a month visits. Therefore should be changed at least twice a month to help prevent accidents of this system is to be judged.