Bemisia tabaci Gennadius, one of the most invasive insect pests, has spread quickly nationwide since it was introduced to South Korea in 2008. The use of insecticides is the main management strategy for this pest, but the control efficiency has been decreased due to insecticide resistance. We collected 12 local B. tabaci populations to investigate the regional differences in efficiency and observed the mortality from 14 commercial insecticides applied at recommended concentrations (RC) and dilutions (0.1 RC and 0.01 RC) using the leaf dipping bioassay. Except for etofenprox (46-64%), thiamethoxam (37-60%), pyriproxyfen (21-61%), and pyridaben (61-65%), the other insecticides showed excellent insecticidal efficacy of 70% to 100% at their RC. In particular, flupyradifurone, emamectin benzoate, and cyantraniliprole showed high insecticidal efficacy of over 90% in all of the tested populations. Some insecticides that rapidly decreased in activity (less than 30%) at diluted concentrations or showed high resistance levels in nearby regions were classified for cautious use due to the possibility or potential to develop resistance. The results provide selected insecticides for B. tabaci control by region and could contribute to reducing insecticide abuse and increasing insecticidal efficiency in farming fields.

β-Ga2O3 has become the focus of considerable attention as an ultra-wide bandgap semiconductor following the successful development of bulk single crystals using the melt growth method. Accordingly, homoepitaxy studies, where the interface between the substrate and the epilayer is not problematic, have become mainstream and many results have been published. However, because the cost of homo-substrates is high, research is still mainly at the laboratory level and has not yet been scaled up to commercialization. To overcome this problem, many researchers are trying to grow high quality Ga2O3 epilayers on hetero-substrates. We used diluted SiH4 gas to control the doping concentration during the heteroepitaxial growth of β-Ga2O3 on c-plane sapphire using metal organic chemical vapor deposition (MOCVD). Despite the high level of defect density inside the grown β-Ga2O3 epilayer due to the aggregation of random rotated domains, the carrier concentration could be controlled from 1 × 1019 to 1 × 1016 cm-3 by diluting the SiH4 gas concentration. This study indicates that β-Ga2O3 hetero-epitaxy has similar potential to homo-epitaxy and is expected to accelerate the commercialization of β-Ga2O3 applications with the advantage of low substrate cost.

Lead-free perovskite ceramics, which have excellent energy storage capabilities, are attracting attention owing to their high power density and rapid charge-discharge speed. Given that the energy-storage properties of perovskite ceramic capacitors are significantly improved by doping with various elements, modifying their chemical compositions is a fundamental strategy. This study investigated the effect of Zn doping on the microstructure and energy storage performance of potassium sodium niobate (KNN)-based ceramics. Two types of powders and their corresponding ceramics with compositions of (1-x)(K,Na)NbO3-xBi(Ni2/3Ta1/3)O3 (KNN-BNT) and (1-x)(K,Na)NbO3-xBi(Ni1/3Zn1/3Ta1/3) O3 (KNN-BNZT) were prepared via solid-state reactions. The results indicate that Zn doping retards grain growth, resulting in smaller grain sizes in Zn-doped KNN-BNZT than in KNN-BNT ceramics. Moreover, the Zn-doped KNNBNZT ceramics exhibited superior energy storage density and efficiency across all x values. Notably, 0.9KNN-0.1BNZT ceramics demonstrate an energy storage density and efficiency of 0.24 J/cm3 and 96%, respectively. These ceramics also exhibited excellent temperature and frequency stability. This study provides valuable insights into the design of KNNbased ceramic capacitors with enhanced energy storage capabilities through doping strategies.

본 연구는 전문가 기반형 모델(Habitat Suitability Index)의 한계로 지적되는 주관적 기준, 통계분석의 부재 등과 통계기반형 모델(MaxEnt)의 한계로 지적되는 현장검증, 전문가 의견 반영 등의 극복을 위하여 각각의 모델을 개발하여 통합하는 방식으로 핵심서식지를 도출하였다. 핵심서식지 발굴을 위해 문헌분석 및 공간분석자료를 바탕으로 전문가 심층면담을 진행하였고, 전문가 자문과 GIS 도면 구축 가능성을 고려하여 모델을 개발하였다. 주요 환경변수는 식생대, 임상, 임분밀도, 연평균 강수량, 유효토심으로 선정되었다. 그 결과 현재 나도승마가 분포하고 있는 16지점 중 15지점이 핵심서식지로 나타났으며, 개발된 모델은 약 93.75%의 높은 정확도를 가지고 있는 것으로 나타났다. 하지만 전체 연구대상지의 약 27.8%가 핵심서식지로 나타남에 따라, 추후 서식변수 및 공간자료 정밀화를 통한 모델의 고도화가 필요할 것으로 판단된다. 따라서 높은 등급으로 확인된 서식지라도 대상종의 서식유무 파악을 위한 현장검증은 필수적으로 수행되어야 한다. 하지만, 이러한 한계에도 불구하고 HSI와 MaxEnt의 상호보완적 활용은 생물종의 분포와 서식지 이용 특성을 통하여 적합 서식지를 예측하고, 신규 서식지 발굴 및 대체서식지 선정 등 다양한 방면으로 활용 가능할 것으로 판단된다.

We determined physicochemical characteristics and antioxidant activities of cookies prepared by replacing wheat flour with 0, 3, 6, and 9% freeze-dried burdock powder instead of wheat flour. The leavening and loss rates of the cookies decreased in proportion to the amount of burdock powder added to the dough. The moisture content of the cookies increased in proportion to the amount of burdock powder added and the crude protein and hardness were higher in the burdock-added group compared to the control. The lightness and yellowness of the cookies decreased, and the redness increased in proportion to the amount of burdock powder added. The total flavonoid and polyphenol compounds in the cookies increased in proportion to the amounts of burdock powder added. The antioxidant activities also tended to increase in proportion to the amount of burdock powder added. Based on the above results, adding burdock powder to cookies can increase antioxidant activity by increasing the content of antioxidant components, such as polyphenols and flavonoids. In addition, it is believed that adding burdock powder at levels of 3 to 9% of the weight of flour would result in cookies with spreadability, swelling power, and hardness similar to those of regular cookies.

Although many attempts have been made to solve the atmospheric diffusion equation, there are many limits that prevent both solving it and its application. The causes of these impediments are primarily due to both the partial differentiation term and the turbulence diffusion coefficient. In consideration of this dilemma, this study aims to discuss the methodology and cases of utilizing a passive air sampler to increase the applicability of atmospheric dispersion modeling. Passive air samplers do not require pumps or electric power, allowing us to achieve a high resolution of spatial distribution data at a low cost and with minimal effort. They are also used to validate and calibrate the results of dispersion modeling. Currently, passive air samplers are able to measure air pollutants, including SO2, NO2, O3, dust, asbestos, heavy metals, indoor HCHO, and CO2. Additionally, they can measure odorous substances such as NH3, H2S, and VOCs. In this paper, many cases for application were introduced for several purposes, such as classifying the VOCs’ emission characteristics, surveying spatial distribution, identifying sources of airborne or odorous pollutants, and so on. In conclusion, the validation and calibration cases for modeling results were discussed, which will be very beneficial for increasing the accuracy and reliability of modeling results.

Water utilities are making various efforts to reduce water losses from water networks, and an essential part of them is to recognize the moment when a pipe burst occurs during operation quickly. Several physics-based methods and data-driven analysis are applied using real-time flow and pressure data measured through a SCADA system or smart meters, and methodologies based on machining learning are currently widely studied. Water utilities should apply various approaches together to increase pipe burst detection. The most intuitive and explainable water balance method and its procedure were presented in this study, and the applicability and detection performance were evaluated by applying this approach to water supply pipelines. Based on these results, water utilities can establish a mass balance-based pipe burst detection system, give a guideline for installing new flow meters, and set the detection parameters with expected performance. The performance of the water balance analysis method is affected by the water network operation conditions, the characteristics of the installed flow meter, and event data, so there is a limit to the general use of the results in all sites. Therefore, water utilities should accumulate experience by applying the water balance method in more fields.

국내 큰느타리버섯은 매년 수출이 증가하고 있는 주요 신선 농산물 중 하나이다. 긴수염버섯파리는 농업, 특히 버섯생산에 피해를 주는 악 명높은 해충이다. 긴수염버섯파리의 유충은 주로 농작물에 직접 피해를 유발하고 성충은 몇몇 위험한 진균 병원체의 매개체 역할을 한다. 본 연구 에서는 전자빔, 엑스선, 그리고 감마선의 조사선량에 따른 긴수염버섯파리의 발육 및 생식에 미치는 영향을 평가했다. 또한 큰느타리버섯이 채워 진 박스 안에서 긴수염버섯파리를 제어할 수 있는 최적선량을 찾기 위해 방사선 및 에너지량에 따른 실증실험을 수행하였다. 그 결과 전자빔, 엑 스선, 감마선 모두 50 Gy에서 긴수염버섯파리의 발육 및 생식이 억제되었다. 또한 큰느타리버섯이 채워진 수출용 박스 상, 중, 하 위치에서 긴수 염버섯파리는 전자빔 150 Gy, 엑스선 100 Gy, 그리고 감마선 50 Gy에서 발육 및 생식을 억제하는 것으로 나타났다. 이러한 결과들은 수출 검역 통합관리 시스템 구축의 기초자료로 제공될 수 있다. 또한 농산물의 안전성 확보와 수출경쟁력 강화에 기여하리라 사료된다.

본 논문은 관음의 눈을 중심으로 그 치유적 의미를 고찰하였다. 본 연구자가 특히 관음의 눈에 주목한 이유는, 상담자가 지녀야 할 안목이 관음의 눈과 같아 야 한다고 생각했기 때문이다. 본 논문은 총 2개의 장으로 구성하였다. 먼저 ‘관음의 눈의 의미’에서는 『법 화경』 「관세음보살보문품」의 게송을 중심으로 관음의 눈의 의미에 관하여 서술 하였다. 관음의 눈은 중생들의 모든 어려움을 소리로 듣고 ‘관’할 수 있는 지혜 와 자비의 눈이며 대중의 모든 소리를 관찰하고 그 마음을 어루만지는 ‘치유의’ 역할을 하는 눈임을 피력하였다. 3장에서는 상담자로서 관음의 눈에 대하여 이 야기하였다. 상담자가에게 필요한 눈은 내담자에 대한 공감의 눈과 상담을 잘 이끌어나갈 수 있는 지혜의 눈이라고 할 수 있다. 관음의 오관(五觀)에서 지혜 관은 상담자의 안목으로, 자관과 비관, 곧 자비관은 공감의 마음으로 이해하였 다. 이러한 관음의 눈을 갖추기 위한 방법으로는 자비명상이 도움이 될 것으로 보았다.

This study endeavors to enrich investment prospects in cryptocurrency by establishing a rationale for investment decisions. The primary objective involves evaluating the predictability of four prominent cryptocurrencies – Bitcoin, Ethereum, Litecoin, and EOS – and scrutinizing the efficacy of trading strategies developed based on the prediction model. To identify the most effective prediction model for each cryptocurrency annually, we employed three methodologies – AutoRegressive Integrated Moving Average (ARIMA), Long Short-Term Memory (LSTM), and Prophet – representing traditional statistics and artificial intelligence. These methods were applied across diverse periods and time intervals. The result suggested that Prophet trained on the previous 28 days' price history at 15-minute intervals generally yielded the highest performance. The results were validated through a random selection of 100 days (20 target dates per year) spanning from January 1st, 2018, to December 31st, 2022. The trading strategies were formulated based on the optimal-performing prediction model, grounded in the simple principle of assigning greater weight to more predictable assets. When the forecasting model indicates an upward trend, it is recommended to acquire the cryptocurrency with the investment amount determined by its performance. Experimental results consistently demonstrated that the proposed trading strategy yields higher returns compared to an equal portfolio employing a buy-and-hold strategy. The cryptocurrency trading model introduced in this paper carries two significant implications. Firstly, it facilitates the evolution of cryptocurrencies from speculative assets to investment instruments. Secondly, it plays a crucial role in advancing deep learning- based investment strategies by providing sound evidence for portfolio allocation. This addresses the black box issue, a notable weakness in deep learning, offering increased transparency to the model.

Recently, due to the expansion of the logistics industry, demand for logistics automation equipment is increasing. The modern logistics industry is a high-tech industry that combines various technologies. In general, as various technologies are grafted, the complexity of the system increases, and the occurrence rate of defects and failures also increases. As such, it is time for a predictive maintenance model specialized for logistics automation equipment. In this paper, in order to secure the operational safety and reliability of the parcel loading system, a predictive maintenance platform was implemented based on the Naive Bayes-LSTM(Long Short Term Memory) model. The predictive maintenance platform presented in this paper works by collecting data and receiving data based on a RabbitMQ, loading data in an InMemory method using a Redis, and managing snapshot DB in real time. Also, in this paper, as a verification of the Naive Bayes-LSTM predictive maintenance platform, the function of measuring the time for data collection/storage/processing and determining outliers/normal values was confirmed. The predictive maintenance platform can contribute to securing reliability and safety by identifying potential failures and defects that may occur in the operation of the parcel loading system in the future.

We aimed to develop and analyze the effectiveness of a “Room of Errors” simulation program for educating nursing students in patient safety management. Methods: This study used a quasi-experimental method (two group, before and after evaluation) and enrolled 35 nursing students as the participants. Data were collected using a self-reported questionnaire and analyzed through descriptive statistics and the independent t-test and Mann-Whitney U test using SPSS/WIN Statistics version 25.0. Results: After completing the “Room of Errors” simulation program, the participants’ score of intention and confidence in performance for patient safety management in the experimental group were significantly higher than those in the control group. Conclusion: A “Room of Errors” simulation education program for nursing students effectively increased the intention and confidence in performance of nursing students in patient safety management.

본 연구는 범죄를 저지른 청소년 중 소년보호처분에 따라 소년원에 입소하였다가 일정 기간 이후 퇴소한 ‘소년원 퇴원생’에게 관심을 가졌다. 이들이 퇴소한 후 다시 범죄를 저지르지 않고 안정적으로 지역사회에 정착하고 자립할 수 있도록 소년원 안 팎에서 각종 노력을 실시하고 있지만, 소년원 퇴원생의 약 20%가 재범을 통해 다시금 소년원에 들어오는 상황에 놓여있다. 그러므로 소년원 퇴원생이 지역사회에 정착하고 자립하는 방안에 대해 교정복지적인 관점에서 관심을 가지고 개입을 시도할 필요가 있다. 이를 위해 본 연구는 소년 범죄와 소년원에 관한 현황과 함께 현재 실시되고 있는 자립지원 프로그램에 대해 소개하였다. 또한 자립지원을 위한 교정복지적 개입 방안 을 제시하였고 그 내용은 다음과 같다. 첫째, 소년원 퇴원생을 위한 자립생활관의 분위기를 퇴원생 친화적으로 개선하고 해당 기관 직원들의 전문성 개발이 필요하다. 둘 째, 소년원 퇴원생을 위한 기숙형 훈련학교의 교육과정을 다양화하고 맞춤형 교육과 정이 개설되어야 한다. 셋째로 다양한 기관들의 다각적 연계를 통해 지역사회 네트워 크 활용이 요구된다. 넷째, 민간 자원봉사자를 활용하여 소년원 퇴원생에게 사회적 지 지체계 마련이 필요하다. 마지막으로 소년원 퇴원생을 위한 법적 제도가 구체화되어 야 한다.

PURPOSES : The purpose of this study is to verify the influences on the compactibility evaluation of WMA (Warm Mix Asphalt) mixture by laboratory experiments. METHODS : Two types of WMA additives (chemical and wax types) and two types of compactors (marshall and gyratory) are used in laboratory experiments. In addition, two types of WMA processes (wet and dry) are tested to verify the impact of manufacturing process. RESULTS : The laboratory results show that the effects of compaction method on compactibility are different depending on the type of additive. The compaction method has a significant impact on WMA mixture with chemical type additive to extent that it determines whether required criterion is satisfied, but only little on WMA mixture with wax type additive. In the case of wet process for WMA mixture manufacturing, it is hard to assess the air void of HMA mixture made of same asphalt binder used in WMA mixture since the additive has already been added in asphalt binder. And the test results show that air voids of HMA mixture vary within properties of asphalt binder. CONCLUSIONS : Through this study, it is found that compactibility of WMA mixture is affected by the compaction methods depending on the additive types and by the WMA mixture manufacturing process. Therefore, those are recommended to be considered when evaluating compactibility of WMA mixtures.

The design of buried underground flexible pipes proposed in domestic standards does not properly reflect changes in ground characteristics. Overseas standards suggest that pipe deflection must be considered while designing them. Therefore, in this study, the structural behavior of underground polyvinyl chloride pipes was investigated through experiments and the finite element analysis. In addition, when the pipe deflection occurred at 3% and 5%, the hydraulic characteristics of the polyvinyl chloride pipe showed a slight difference compared to the round pipe.

In this study, we propose a novel approach to analyze big data related to patents in the field of smart factories, utilizing the Latent Dirichlet Allocation (LDA) topic modeling method and the generative artificial intelligence technology, ChatGPT. Our method includes extracting valuable insights from a large data-set of associated patents using LDA to identify latent topics and their corresponding patent documents. Additionally, we validate the suitability of the topics generated using generative AI technology and review the results with domain experts. We also employ the powerful big data analysis tool, KNIME, to preprocess and visualize the patent data, facilitating a better understanding of the global patent landscape and enabling a comparative analysis with the domestic patent environment. In order to explore quantitative and qualitative comparative advantages at this juncture, we have selected six indicators for conducting a quantitative analysis. Consequently, our approach allows us to explore the distinctive characteristics and investment directions of individual countries in the context of research and development and commercialization, based on a global-scale patent analysis in the field of smart factories. We anticipate that our findings, based on the analysis of global patent data in the field of smart factories, will serve as vital guidance for determining individual countries' directions in research and development investment. Furthermore, we propose a novel utilization of GhatGPT as a tool for validating the suitability of selected topics for policy makers who must choose topics across various scientific and technological domains.

The purpose of this study is to analyze 118 studies in the field of Korean presentation education conducted between 2005 and January 2023 and to provide insight into the future direction of research in this area. The study utilized Topic modeling and direct researcher analysis methods to examine Korean presentation education research materials. The analysis revealed a steady increase in research on Korean presentation education, with high frequency keywords such as ‘academic’, ‘purpose’, ‘discourse’, and ‘class’ indicating that research has been conducted on these topics. Furthermore, the Topic modeling analysis revealed that many studies have focused on ‘study on the analysis of aspects and the use of strategies in presentation discourse’ and ‘study on the use of presentation classes by learners’, particularly for Chinese native learners. In terms of research methods, the analysis conducted through direct researcher analysis showed that the most common methods used were ‘dialogue analysis’ and ‘survey research’, and single research methods were utilized more frequently than mixed methods. Based on these findings, this study suggests that future research should focus on Korean presentation education for language learners with various purposes and employ a variety of research methods.