It is very important to evaluate how the functions of products, facilities, and spaces affect human life. The evaluation of these actions has legal regulations such as certification, inspection, and diagnosis, and the degree of quality, safety, and excellence of the results is announced. This study sought to secure safety through efficient system operation by reviewing safety-related certification systems established and implemented by each government department in Korea and analyzing the characteristics of each system and similarities between systems. There was also an aspect of cross-checking safety through the certification and diagnosis system implemented by each ministry, but it was confirmed that the efficiency of the system should also be considered in terms of overlapping application. Therefore, when securing safety is confirmed based on each safety-related law, active alternatives such as exemption, substitution, delegation, etc. should be presented.

One of the important components of a nuclear fuel cycle facility is a hot cell. Hot cells are engineered robust structures and barriers, which are used to handle radioactive materials and to keep workers, public, and the environment safe from radioactive materials. To provide a confinement function for these hot cells, it is necessary to maintain the soundness of the physical structure, but also to maintain the negative pressure inside the hot cell using the operation of the heating, ventilation, and air conditioning (HVAC) systems. The negative pressure inside the hot cells allows air to enter from outside hot cells and limits the leakage of any contaminant or radioactive material within the hot cell to the outside. Thus, the HVAC system is one of the major components for maintaining this negative pressure in the hot cell. However, as the facility ages, all the components of the hot cell HVAC system are also subject to age-related deterioration, which can cause an unexpected failure of some parts. The abnormal operating condition from the failure results in the increase of facility downtime and the decrease in operating efficiency. Although some major parts are considered and constructed in redundancy and diversity aspects, an unexpected failure and abnormal operating condition could result in reduction of public acceptance and reliability to the facility. With the advent of the 4th Industrial Revolution, prognostics and health management (PHM) technology is advancing at a rapid pace. Korea Hydro & Nuclear Power, Siemens, and other companies have already developed technologies to constantly monitor the integrity of power plants and are applying the technology in the form of digital twins for efficiency and safety of their facility operation. The main point of PHM, based on this study, is to monitor changes and variations of soundness and safety of the operation and equipment to analyze current conditions and to ultimately predict the precursors of unexpected failures in advance. Through PHM, it would be possible to establish a maintenance plan before the failure occurs and to perform predictive maintenance rather than corrective maintenance after failures of any component. Therefore, it is of importance to select appropriate diagnostic techniques to monitor and to diagnose the condition of major components using the constant examination and investigation of the PHM technology. In this study, diagnostic techniques are investigated for monitoring of HVAC and discussed for application of PHM into nuclear fuel cycle facilities with hot cells.

In the nuclear fuel cycle (NFC) facilities, the failure of Heating Ventilation and Air Conditioning (HVAC) system starts with minor component failures and can escalate to affecting the entire system, ultimately resulting in radiological consequences to workers. In the field of air-conditioning and refrigerating engineering, the fault detection and diagnosis (FDD) of HVAC systems have been studied since faults occurring in improper routine operations and poor preventive maintenance of HVAC systems result in excessive energy consumption. This paper aims to provide a systematic review of existing FDD methods for HVAC systems therefore explore its potential application in nuclear field. For this goal, typical faults and FDD methods are investigated. The commonly occurring faults of HVAC are identified through various literature including publications from International Energy Agency (IEA) and American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE). However, most literature does not explicitly addresses anomalies related to pressure, even though in nuclear facilities, abnormal pressure condition need to be carefully managed, particularly for maintaining radiological contamination differently within each zone. To build simulation model for FDD, the whole-building energy system modeling is needed because HVAC systems are major contributors to the whole building’s energy and thermal comfort, keeping the desired environment for occupants and other purposes. The whole-building energy modeling can be grouped into three categories: physics-based modeling (i.e., white-box models), hybrid modeling (i.e., grey-box models), and data-driven modeling (i.e., black-box models). To create a white-box FDD model, specialized tools such as EnergyPlus for modeling can be used. The EnergyPlus is open source program developed by US-DOE, and features heat balance calculation, enabling the dynamic simulation in transient state by heat balance calculation. The physics based modeling has the advantage of explaining clear cause-and-effect relationships between inputs and outputs based on heat and mass transfer equations, while creating accurate models requires time and effort. Creating a black-box FDD model requires a sufficient quantity and diverse types of operational data for machine learning. Since operation data for HVAC systems in existing nuclear cycle facilities are not fully available, so efforts to establish a monitoring system enabling the collection, storage, and management of sensor data indicating the status of HVAC systems and buildings should be prioritized. Once operational data are available, well-known machine learning methods such as linear regression, support vector machines, random forests, artificial neural networks, and recurrent neural networks (RNNs) can be used to classify and diagnose failures. The challenge with black-box models is the lack of access to failure data from operating facilities. To address this, one can consider developing black-box models using reference failure data provided by IEA or ASHRAE. Given the unavailability of operation data from the operating NFC facilities, there is a need for a short to medium-term plan for the development of a physics-based FDD model. Additionally, the development of a monitoring system to gather useful operation data is essential, which could serve both as a means to validate the physics-based model and as a potential foundation for building data-driven model in the long term.

Background: Pain neuroscience education (PNE) combined with exercise and mobilisation with cognitive goals presented decreases in pain and disability and an increase in spinal function compared to physiotherapy intervention in patients with chronic low back pain (CLBP). Objectives: To investigated the effect of forward head posture (FHP) with chronic neck pain on the PNE combined with cervical and thoracic mobilization. Design: A randomized controlled trial. Methods: The subjects were randomly allocated to the MDT with PNE group (MPNEG, n=15) and the PNE group (PNEG, n=15). Pain neuroscience education was provided to both groups, and MDT exercise was additionally performed in the experimental group. Training was conducted 3 times a week for 8 weeks, and the Oswestry Disability Index (ODI) and numeric rating scale (NRS) were used to measure the level of back pain dysfunction, and each was evaluated before and after the experiment. Results: Results from the study indicated that statistically significant decrease in NRS and ODI in MPNEG. In PNEG, there was statistically significant decrease in NRS. And in MPMES, there was a statistically significant decrease in ODI than in PNEG. Conclusion: The MDT combined with PNE is more effective than PNE alone as a treatment method for improving lumbar dysfunction and reducing pain in chronic low back pain.

췌장낭성병변은 최근 영상기술의 발전으로 우연히 발견되는 비율이 점차 증가하고 있으며, 유병률은 복부컴퓨터단층촬영을 시행한 사람에서 많게는 13.5%까지 보고되었다. 그러나 췌장낭성질환의 정확한 진단은 양성에서 악성 질환까지 다양한 형태로 보일 수 있어 영상학적 진단만으로는 매우 어렵다. 초음파내시경은 췌장낭성병변을 비교적 정확하게 진단하고 치료를 결정하는 데 매우 중요한 도구로 사용된다. 그러나 내시경 초음파는 악성으로 진행 가능한 점액성 췌장낭종과 다른 췌장낭종질환을 구분하는 데 정확도가 65-75%에 불과하다. 인공지능은 대장암, 폐암, 유방암과 같은 여러 종류의 암 진단의 정확도를 향상시키는 데 효과적인 도구로 사용되고 있으며, 최근 연구에서는 췌장낭성병변에서도 점액성 종양과 비점액성 종양을 구분하고 악성으로 진행 위험도를 평가하는 데 도움이 되는 것으로 보고되고 있다. 인공지능의 적용은 영상분석에도 국한되지 않고 최근에는 췌장낭종의 액체 분석, 유전자 분석, confocal laser endomicroscopy 등 다양한 분야에서 활용되고 있으며 기대되는 연구 결과를 발표하고 있다. 인공지능은 의료 분야에서 아직 시작단계에 있어, 임상에 적용하기 위해 적절한 알고리즘을 개발하는 데에는 개발자들의 큰 노력이 필요하다. 그러나 이러한 기술은 앞으로 췌장낭종 병변을 보다 정확하게 진단하고 효과적이고 효율적으로 관리하는 데에 도움을 줄 수 있는 잠재력을 가지고 있다고 하겠다.

Gate valves are hydraulic components used to shut-off the water flow in water distribution systems. Gate valves may fail owing to various aspects such as leakage through seats, wearing of packing, and corrosion. Because it is considerably challenging to detect valve malfunctioning until the operator identifies a significant fault, failure of the gate valve may lead to a severe accident event associated with water distribution systems. In this study, we proposed a methodology to diagnose the faults of gate valves. To measure the pressure difference across a gate valve, two pressure transducers were installed before and after the gate valve in a pilot-scaled water distribution system. The obtained time-series pressure difference data were analyzed using a machine learning algorithm to diagnose faults. The validation of whether the flow rate of the pipeline can be predicted based on the pressure difference between the upstream and downstream sides of the valve was also performed.

우리나라는 2021년 기준 OECD 국가중 화학농약 사용량 3위로 농약사용의 개선이 필요하다. 특히 범국가적인 One Health 정책 관점에서 농작물에 사용되는 항생제 농약관리도 필요하다. 현재 시행중인 PLS, 판매관리인 교육 및 농약판매기록 제도들이 선정된 농약 사용의 안정성에 초 점을 맞춘다면, 진단과 처방을 중심으로 한 식물의약사 제도는 농약 선정의 정확성을 높일 수 있는 제도이다. 국내 발생 병해충은 연간 1,000여종 이 상이며, 하나의 고위험 병해충에 적용가능한 등록약제는 100~200개로 작용기작과 처리방법 측면에서 다양하다. 정확한 진단을 바탕으로 적합한 약 제를 선정하는 처방은 수백종 이상의 병해충에 대한 전문지식과 다양한 약제에 대한 이해와 실무경험이 요구된다. 본 연구에서 농업인에 대한 설문 조사 결과, 응답자중 81% 농업인이 농약구매와 사용에 대한 전문가의 도움이 필요하며, 이중 48% 농업인들은 매우 필요하다는 의견을 제시하였다. 판매관리인에 대한 설문조사 결과, 42%의 판매관리인이 진단 및 처방에 대한 전문성 강화가 절실함을 주장하였으며, 필요성을 인지하는 판매관리 인도 44%로 확인되어, 전체적으로 42~86%의 판매관리인들이 진단 및 처방에 대한 전문성 강화에 관심이 있었다. 식물의약사 제도화 초기에 현장 경험이 많은 판매관리인을 제도권으로 수용할 수 있는 특별전형을 고려해야 한다. 병해충 종류별 등록된 농약의 저항성 수준을 자료화하고 효과적인 방제력을 구축하여 진단 및 처방의 정확성을 높여야 한다. 판매관리인은 식물의약사 자격을 경쟁 우의 차별화 전략으로 인식하고, 더 이상 판매관리 인이 아니라 식물의약사로서 “믿음이 가는 식물의약사가 처방하는 농약”의 시장 포지셔닝을 통해 매출액 향상을 도모할 수 있다. 향후 법제화를 위 한 관련법 개정, 전문성 강화 교육 커리큘럼, 자격제도 운영에 대한 실무적인 논의가 필요하다. 식물의약사 제도화를 통해 판매관리인의 전문성을 상 향 평준화 함으로서 농업 현장의 병해충 진단 및 처방 기술을 선진화하고, 국민의 건강과 직결되는 합리적인 농약 사용을 위해 노력해야 한다.

Failure diagnoses on large diesel engine are commonly detected when a deviation or fluctuation in its temperature, pressure, vibration or noise set parameter limits arises. These parameters can be easily monitored and can provide information of the engine’s present state depending on external environment and operating conditions. On the other hand, long term monitoring and condition management can be interfaced into the engine’s existing operating system. The approach is seen to keep track of monitored machines’ status using resonance and vibration amplitude. In particular, these signals will be able to identify complex vibration characteristic pertaining to such as engine torque output and support mounts. In this paper, a basic research for large diesel engine diagnosis was carried-out. The failure diagnosis collects and monitors the vibration state time history by using various vibration signals with reference to ISO 13373-1. Further, this monitoring system in the field of large diesel engines has not been applied practically and the results of this study are presented herein.

PURPOSES : When fire event occurs in tunnel the reinforced concrete is exposed to very high temperature at a very short time period. This study investigates the tensile behavior of steel rebar that experienced high temperature. METHODS : The steel rebar was exposed to 200, 400, 600, and 800℃ following the ISO 834 temperature-time fire curve. Hightemperature- exposed steel rebars were tested using the UTM for their yielding and tensile strengths, and elongation rate. RESULTS : Up to an exposure temperature of 600℃, the tensile properties of the rebar did not vary considerably. However, at 800℃ (which corresponds to a temperature rise time of approximately 22 min), the rebar lost its yielding and tensile strength by approximately 27 and 13%, respectively, compared to the control specimen. Further, the elongation rate increased after exposure to 600℃. The above fundamental tensile test results can be a good reference for future guidelines in the repair manual for tunnels after severe fire events. CONCLUSIONS : When steel rebar experiences high temperatures of 800℃, the yield strength of the rebar reduces approximately 27%. This strength reduction can cause severe structural damage to tunnels that use reinforced concrete as the primary structural elements.

The most important aspect of the imaging role for indeterminate bile duct stricture is to make a differential diagnosis on whether the stricture is highly likely to be malignant or benign. Compared to benign stricture, malignant stricture is longer, thicker, and has indistinct outer border and irregularity of the lumen in contrastenhanced computed tomography and magnetic resonance (MR). Also, in the contrast-enhanced portal phase, malignant stricture has a stronger enhancement than the liver parenchyma. There are studies to differentiate between malignant and benign stricture in diffusion weighted image, a functional MR image, but there remains controversial. Sometimes, malignant biliary stricture may be caused by bile duct invasion of gallbladder cancer, pancreatic cancer, hepatocellular carcinoma, biliary metastasis, and lymphoma. Among the potential causes of indeterminate biliary stricture, the characteristics of multifocal biliary stricture mainly suggest benign sclerosing cholangitis, and various external compression factors that cause biliary stricture can be differentiated by radiologic imaging. There are causes of biliary dilatation without obstructive lesion, radiologic diagnosis can be made by considering various characteristics.

본 연구에서는 사례연구 대상지역(인천)의 특화산업에 대해 LQ지수분석을 통해 해양특화산업을 도출하고, 특화산업의 해양 공간 활용현황과 용도구역 설정에 따른 현안을 진단하였다. 대상지역의 해양산업에 대한 LQ지수(Location Quotients, LQ) 분석을 통해 사 업체수 기준 LQ지수 1.08, 종사자수 기준 LQ지수 1.67로 전국평균 대비 높은 해양바이오산업을 인천지역 해양특화산업으로 선정하였 다. 해양특화산업인 해양바이오산업의 현안진단을 위해 영흥도 실증 배양장 사례 검토 및 가장 낮은 특화도를 나타낸 해양에너지개발 부문에서의 현안 진단을 통해 해양용도구역의 중첩문제, 이해관계자간 민원발생 이슈 등 현장문제 해결을 위해서 객관적이고 정량적 근거를 기반으로 정책의사결정지원시스템 마련이 필요하다는 결론을 제시하였다.

Lymphoma, which accounts for 3.5% of all oral cancers, is further divided into Hodgkin's lymphoma (HL) and non-Hodgkin's lymphoma (NHL). NHL accounts for 96% of lymphomas, and diffuse large B-cell lymphoma (DLBCL) is the most common subtype accounting for 32% of NHL. In the oral cavity, extra-nodal non-Hodgkin's lymphoma may develop in the dentoalveolar region of the maxilla or mandible. It can also mimic inflammatory lesions that occur around periodontal tissues, such as periapical granuloma and chronic osteomyelitis. Misdiagnosis of jaw lymphoma can delay appropriate treatments and worsen the prognosis. Therefore, to avoid delay in diagnosis, clinicians should identify the possible malignancy based on unusual symptoms, clinical findings, radiographic examinations, and histopathological evaluation. We present two cases of DLBCL in the right posterior mandible of a 64-year-old man who was initially misdiagnosed as acute apical abscess and in the right posterior maxilla of an 81-year-old woman who was initially misdiagnosed as chronic periodontitis. These cases demonstrate that it is important for both pathologists and clinicians to consider malignant lesions such as lymphomas in the differential diagnosis of apical radiolucency.

본 연구는 RGB, 초분광 센서를 이용하여 시기별 사과 잎의 엽록소와 질소 함량을 예측하여 사과 나무 잎의 질소 영양을 진단하기 위해 수행되었다. 분광 데이터는 사과나무 ‘홍로 /M.9’ 2년생을 대상으로 고해상도 RGB와 초분광 센서로 촬 영 후 영상처리를 통해 취득하였다. 식물체 데이터는 촬영이 끝난 직후 엽록소와 잎 질소 함량을 측정하였다. 엽록소 측정 기의 SPAD meter, RGB 센서의 개별 파장, 컬러 식생지수 및 초분광 센서의 214개의 파장과 식물체 데이터를 이용하여 회 귀분석을 실시하였다. 엽록소와 잎 질소 함량 데이터는 시기 와 상관없이 질소 시비량에 따라 통계적으로 유의한 차이가 나타났다. 잎은 시기가 지나면서 잎에 있던 영양분이 과실로 전이되어 색이 옅어졌으며 RGB센서의 경우 Red파장에서 시 기와 상관없이 통계적으로 유의한 차이가 나타났다. 초분광 센서의 경우 두 시기 모두 질소 시비 수준에 따라 가시광 영역 보다 비가시광 영역에서 차이가 크게 나타났다. 반사값를 이 용하여 식물체 특성의 예측 모델 결과 엽록소, 잎 질소함량 모 두 초분광 데이터를 이용한 부분최소제곱 회귀분석을 이용하 였을 때 성능이 가장 높게 나타났다(chlorophyll: 81% / 63%, leaf nitrogen content: 81% / 67%). 이러한 원인은 RGB 센서 에 비해 초분광 센서는 좁은 FWHM과 400－1,000nm의 넓 은 파장 범위를 가지고 있어 질소 결핍에 의한 스트레스로 인 해 작물의 분광학적 해석이 가능했을 것으로 판단된다. 추후 분광학적 특성을 이용하여 전 생육 시기의 수체 생리, 생태 모 델 개발 및 검증 그리고 병해충 진단 등 연구를 통해 고품질, 안 정적인 과실 생산 기술 개발에 기여될 것으로 사료된다.