• Title/Summary/Keyword: 평가수준

Search Result 9,800, Processing Time 0.037 seconds

Development of a Model of Brain-based Evolutionary Scientific Teaching for Learning (뇌기반 진화적 과학 교수학습 모형의 개발)

  • Lim, Chae-Seong
    • Journal of The Korean Association For Science Education
    • /
    • v.29 no.8
    • /
    • pp.990-1010
    • /
    • 2009
  • To derive brain-based evolutionary educational principles, this study examined the studies on the structural and functional characteristics of human brain, the biological evolution occurring between- and within-organism, and the evolutionary attributes embedded in science itself and individual scientist's scientific activities. On the basis of the core characteristics of human brain and the framework of universal Darwinism or universal selectionism consisted of generation-test-retention (g-t-r) processes, a Model of Brain-based Evolutionary Scientific Teaching for Learning (BEST-L) was developed. The model consists of three components, three steps, and assessment part. The three components are the affective (A), behavioral (B), and cognitive (C) components. Each component consists of three steps of Diversifying $\rightarrow$ Emulating (Executing, Estimating, Evaluating) $\rightarrow$ Furthering (ABC-DEF). The model is 'brain-based' in the aspect of consecutive incorporation of the affective component which is based on limbic system of human brain associated with emotions, the behavioral component which is associated with the occipital lobes performing visual processing, temporal lobes performing functions of language generation and understanding, and parietal lobes, which receive and process sensory information and execute motor activities of the body, and the cognitive component which is based on the prefrontal lobes involved in thinking, planning, judging, and problem solving. On the other hand, the model is 'evolutionary' in the aspect of proceeding according to the processes of the diversifying step to generate variants in each component, the emulating step to test and select useful or valuable things among the variants, and the furthering step to extend or apply the selected things. For three components of ABC, to reflect the importance of emotional factors as a starting point in scientific activity as well as the dominant role of limbic system relative to cortex of brain, the model emphasizes the DARWIN (Driving Affective Realm for Whole Intellectual Network) approach.

Accuracy of HF radar-derived surface current data in the coastal waters off the Keum River estuary (금강하구 연안역에서 HF radar로 측정한 유속의 정확도)

  • Lee, S.H.;Moon, H.B.;Baek, H.Y.;Kim, C.S.;Son, Y.T.;Kwon, H.K.;Choi, B.J.
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
    • /
    • v.13 no.1
    • /
    • pp.42-55
    • /
    • 2008
  • To evaluate the accuracy of currents measured by HF radar in the coastal sea off Keum River estuary, we compared the facing radial vectors of two HF radars, and HF radar-derived currents with in-situ measurement currents. Principal component analysis was used to extract regression line and RMS deviation in the comparison. When two facing radar's radial vectors at the mid-point of baseline are compared, RMS deviation is 4.4 cm/s in winter and 5.4 cm/s in summer. When GDOP(Geometric Dilution of Precision) effect is corrected from the RMS deviations that is analyzed from the comparison between HF radar-derived and current-metermeasured currents, the error of velocity combined by HF radar-derived current is less than 5.1 cm/s in the stations having moderate GDOP values. These two results obtained from different method suggest that the lower limit of HF radar-derived current's accuracy is 5.4 cm/s in our study area. As mentioned in previous researches, RMS deviations become large in the stations located near the islands and increase as a function of mean distance from the radar site due to decrease of signal-to-noise level and the intersect angle of radial vectors. We found that an uncertain error bound of HF radar-derived current can be produced from the separation process of RMS deviations using GDOP value if GDOP value for each component is very close and RMS deviations obtained from current component comparison are also close. When the current measured in the stations having moderate GDOP values is separated into tidal and subtidal current, characteristics of tidal current ellipses analyzed from HF radar-derived current show a good agreement with those from current-meter-measured current, and time variation of subtidal current showed a response reflecting physical process driven by wind and density field.

Comparative Analysis of Ginsenoside Content in Processed Red Ginseng Foods Based on Food Type and Formulation (홍삼가공식품의 식품유형별 및 제형별 진세노사이드 함량 비교)

  • Yun-Jeong Yi;Min-Su Chang;In-Sook Lee;Hyun-Jeong Kim;Hyun-Jeong Jang;In-Sook Hwang
    • Journal of Food Hygiene and Safety
    • /
    • v.39 no.2
    • /
    • pp.163-170
    • /
    • 2024
  • Red ginseng is manufactured as a health-functional food and is also present in various food types and in different product forms. However, there is currently no standardized regulation of ginsenoside content in foods containing red ginseng. In the present study, we analyzed the ginsenoside content of 66 red ginseng-containing foods and 35 health-functional foods collected online and directly from the market. The ginsenoside content was assessed using liquid chromatography (LC) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) methods. The ginsenoside content of the various food types ranged 0.0 (not detected)-71.567 mg per daily intake of foods containing red ginseng. Sugar-preserved foods had the highest ginsenoside content, followed by solid teas, liquid teas, and red ginseng beverages. For health-functional foods, the ginsenoside content ranged 3.4-58.5 mg per daily intake, with levels ranging 83-607% of the indicated amounts. All values met the established standards. Upon comparing red ginseng health-functional foods and red ginseng-containing foods, the average ginsenoside content was determined to be 18.21 and 8.79 mg, respectively, thus being nearly twice as high in health-functional foods. However, there was a minimal difference between the ginsenoside content of red and black ginseng, with values of 11.84 and 12.63 mg, respectively. These findings provide insights on the variations in ginsenoside content of red and black ginseng in various food forms. This information is expected to be valuable for future regulations and consumer choice of products containing red ginseng.

Latest Supreme Court Decision on Proof of Causation in Medical Malpractice Cases - Focusing on Supreme Court decision 2022da219427 on August 31, 2023 and the Supreme Court decision 2021Do1833 on August 31, 2023 - (의료과오 사건에서 인과관계 증명에 관한 최신 대법원 판결 - 대법원 2023. 8. 31. 선고 2022다219427 판결 및 대법원 2023. 8. 31. 선고 2021도1833 판결을 중심으로 -)

  • HYEONHO MOON
    • The Korean Society of Law and Medicine
    • /
    • v.24 no.4
    • /
    • pp.3-36
    • /
    • 2023
  • The main issue in medical malpractice civil litigation is medical negligence and the causal relationship between medical negligence and damages. Regarding the presumption of causality in cases where medical negligence is proven, there is a previous Supreme Court decision 93da52402 on February 10, 1995, but it is difficult to find a case that satisfies the textual requirements of the above decision, and yet, in practice, the above decision is cited. In many cases, causal relationships were assumed, and criticism was consistently raised that it was inconsistent with the text of the above judgment. In its ruling, the Supreme Court reorganized and presented a new legal principle regarding the presumption of causality when medical negligence is proven in a civil lawsuit. According to this, If the patient proves ① the existence of an act that is assessed as a medical negligence, that is, a violation of the duty of care required of an ordinary medical professional at the level of medical care practiced in the field of clinical medicine at the time of medical practice, and ② that the negligence is likely to cause damages to the patient, the burden of proving the causal relationship is alleviated by presuming a causal relationship between medical negligence and damage. Here, the probability of occurrence of damage does not need to be proven beyond doubt from a natural scientific or medical perspective, but if recognizing the causal relationship between the negligence and the damage does not comply with medical principles or if there is a vague possibility that the negligence will cause damage, causality cannot be considered proven. Meanwhile, even if a causal relationship between medical negligence and damage is presumed, the party that performed the medical treatment can overturn the presumption by proving that the patient's damage was not caused by medical negligence. Meanwhile, unlike civil cases, the standard is 'proof beyond reasonable doubt' in criminal cases, and the legal principle of presuming causality does not apply. Accordingly, in a criminal case of professional negligence manslaughter that was decided on the same day regarding the same medical accident, the case was overturned and remanded for not guilty due to lack of proof of a causal relationship between medical negligence and death. The above criminal ruling is a ruling that states that even if 'professional negligence' is recognized in a criminal case related to medical malpractice, the person should not be judged guilty if there is a lack of clear proof of 'causal relationship'.

A Study on Medical Waste Generation Analysis during Outbreak of Massive Infectious Diseases (대규모 감염병 발병에 따른 의료폐기물 발생량 예측에 관한 연구)

  • Sang-Min Kim;Jin-Kyu Park;In-Beom Ko;Byung-Sun Lee;Sang-Ryong Shin;Nam-Hoon Lee
    • Journal of the Korea Organic Resources Recycling Association
    • /
    • v.31 no.4
    • /
    • pp.29-39
    • /
    • 2023
  • In this study, an analysis of medical waste generation characteristics was conducted, differentiating between ordinary situation and the outbreaks of massive infectious diseases. During ordinary situation, prediction models for medical waste quantities by type, general medical waste(G-MW), hazardous medical waste(H-MW), infectious medical waste(I-MW), were established through regression analysis, with all significance values (p) being <0.0001, indicating statistical significance. The determination coefficient(R2) values for prediction models of each category were analyzed as follows : I-MW(R2=0.9943) > G-MW(R2=0.9817) > H-MW(R2=0.9310). Additionally, factors such as GDP(G-MW), the number of medical institutions (H-MW), and the elderly population ratio(I-MW), utilized as influencing factors and consistent with previous literature, showed high correlations. The total MW generation, evaluated by combining each model, had an MAE of 2,615 and RMSE of 3,353. This indicated accuracy levels similar to the medical waste models of H-MW(2,491, 2,890) and I-MW(2,291, 3,267). Due to limitations in accurately estimating the quantity of medical waste during the rapid and outbreaks of massive infectious diseases, the generation unit of I-MW was derived to analyze its characteristics. During the early unstable stage of infectious disease outbreaks, the generation unit was 8.74 kg/capita·day, 2.69 kg/capita·day during the stable stage, and an average of 0.08 kg/capita·day during the reduction stage. Correlation analysis between generation unit of I-MW and lethality rates showed +0.99 in the unstable stage, +0.52 in the stable stage, and +0.96 in the reduction period, demonstrating a very high positive correlation of +0.95 or higher throughout the entire outbreaks of massive infectious diseases. The results derived from this study are expected to play a useful role in establishing an effective medical waste management system in the field of health care.

Contactless Data Society and Reterritorialization of the Archive (비접촉 데이터 사회와 아카이브 재영토화)

  • Jo, Min-ji
    • The Korean Journal of Archival Studies
    • /
    • no.79
    • /
    • pp.5-32
    • /
    • 2024
  • The Korean government ranked 3rd among 193 UN member countries in the UN's 2022 e-Government Development Index. Korea, which has consistently been evaluated as a top country, can clearly be said to be a leading country in the world of e-government. The lubricant of e-government is data. Data itself is neither information nor a record, but it is a source of information and records and a resource of knowledge. Since administrative actions through electronic systems have become widespread, the production and technology of data-based records have naturally expanded and evolved. Technology may seem value-neutral, but in fact, technology itself reflects a specific worldview. The digital order of new technologies, armed with hyper-connectivity and super-intelligence, not only has a profound influence on traditional power structures, but also has an a similar influence on existing information and knowledge transmission media. Moreover, new technologies and media, including data-based generative artificial intelligence, are by far the hot topic. It can be seen that the all-round growth and spread of digital technology has led to the augmentation of human capabilities and the outsourcing of thinking. This also involves a variety of problems, ranging from deep fakes and other fake images, auto profiling, AI lies hallucination that creates them as if they were real, and copyright infringement of machine learning data. Moreover, radical connectivity capabilities enable the instantaneous sharing of vast amounts of data and rely on the technological unconscious to generate actions without awareness. Another irony of the digital world and online network, which is based on immaterial distribution and logical existence, is that access and contact can only be made through physical tools. Digital information is a logical object, but digital resources cannot be read or utilized without some type of device to relay it. In that respect, machines in today's technological society have gone beyond the level of simple assistance, and there are points at which it is difficult to say that the entry of machines into human society is a natural change pattern due to advanced technological development. This is because perspectives on machines will change over time. Important is the social and cultural implications of changes in the way records are produced as a result of communication and actions through machines. Even in the archive field, what problems will a data-based archive society face due to technological changes toward a hyper-intelligence and hyper-connected society, and who will prove the continuous activity of records and data and what will be the main drivers of media change? It is time to research whether this will happen. This study began with the need to recognize that archives are not only records that are the result of actions, but also data as strategic assets. Through this, author considered how to expand traditional boundaries and achieves reterritorialization in a data-driven society.

Exploring Pre-Service Earth Science Teachers' Understandings of Computational Thinking (지구과학 예비교사들의 컴퓨팅 사고에 대한 인식 탐색)

  • Young Shin Park;Ki Rak Park
    • Journal of the Korean earth science society
    • /
    • v.45 no.3
    • /
    • pp.260-276
    • /
    • 2024
  • The purpose of this study is to explore whether pre-service teachers majoring in earth science improve their perception of computational thinking through STEAM classes focused on engineering-based wave power plants. The STEAM class involved designing the most efficient wave power plant model. The survey on computational thinking practices, developed from previous research, was administered to 15 Earth science pre-service teachers to gauge their understanding of computational thinking. Each group developed an efficient wave power plant model based on the scientific principal of turbine operation using waves. The activities included problem recognition (problem solving), coding (coding and programming), creating a wave power plant model using a 3D printer (design and create model), and evaluating the output to correct errors (debugging). The pre-service teachers showed a high level of recognition of computational thinking practices, particularly in "logical thinking," with the top five practices out of 14 averaging five points each. However, participants lacked a clear understanding of certain computational thinking practices such as abstraction, problem decomposition, and using bid data, with their comprehension of these decreasing after the STEAM lesson. Although there was a significant reduction in the misconception that computational thinking is "playing online games" (from 4.06 to 0.86), some participants still equated it with "thinking like a computer" and "using a computer to do calculations". The study found slight improvements in "problem solving" (3.73 to 4.33), "pattern recognition" (3.53 to 3.66), and "best tool selection" (4.26 to 4.66). To enhance computational thinking skills, a practice-oriented curriculum should be offered. Additional STEAM classes on diverse topics could lead to a significant improvement in computational thinking practices. Therefore, establishing an educational curriculum for multisituational learning is essential.

Analysis of Waterbody Changes in Small and Medium-Sized Reservoirs Using Optical Satellite Imagery Based on Google Earth Engine (Google Earth Engine 기반 광학 위성영상을 이용한 중소규모 저수지 수체 변화 분석)

  • Younghyun Cho;Joonwoo Noh
    • Korean Journal of Remote Sensing
    • /
    • v.40 no.4
    • /
    • pp.363-375
    • /
    • 2024
  • Waterbody change detection using satellite images has recently been carried out in various regions in South Korea, utilizing multiple types of sensors. This study utilizes optical satellite images from Landsat and Sentinel-2 based on Google Earth Engine (GEE) to analyze long-term surface water area changes in four monitored small and medium-sized water supply dams and agricultural reservoirs in South Korea. The analysis covers 19 years for the water supply dams and 27 years for the agricultural reservoirs. By employing image analysis methods such as normalized difference water index, Canny Edge Detection, and Otsu'sthresholding for waterbody detection, the study reliably extracted water surface areas, allowing for clear annual changes in waterbodies to be observed. When comparing the time series data of surface water areas derived from satellite images to actual measured water levels, a high correlation coefficient above 0.8 was found for the water supply dams. However, the agricultural reservoirs showed a lower correlation, between 0.5 and 0.7, attributed to the characteristics of agricultural reservoir management and the inadequacy of comparative data rather than the satellite image analysis itself. The analysis also revealed several inconsistencies in the results for smaller reservoirs, indicating the need for further studies on these reservoirs. The changes in surface water area, calculated using GEE, provide valuable spatial information on waterbody changes across the entire watershed, which cannot be identified solely by measuring water levels. This highlights the usefulness of efficiently processing extensive long-term satellite imagery data. Based on these findings, it is expected that future research could apply this method to a larger number of dam reservoirs with varying sizes,shapes, and monitoring statuses, potentially yielding additional insights into different reservoir groups.

The Aspects of Epistemic Cognition Formed in Elementary Students' Scientific Modeling: An Examination through the Apt-AIR Framework (Apt-AIR 기본틀로 본 초등학생의 과학적 모델링 수업에서 지식구성의 인지과정 실행 양상)

  • Seoyeon Kim;Seungho Maeng
    • Journal of The Korean Association For Science Education
    • /
    • v.44 no.4
    • /
    • pp.325-341
    • /
    • 2024
  • This study examined how specific aspects of epistemic cognition are developed in elementary students during modeling activities, using the Apt-AIR framework. The study focused on a class unit titled 'Shall We Find Out What the Landscape of a Riverside Looks Like?' which is part of the land chapter in the third-grade Korean elementary science curriculum. Ambitious Science Teaching (AST) was applied as a teaching strategy to enhance students' model construction. Seven science classes were conducted in line with the core practices of AST, with 29 elementary school students participating in the study. The classes were organized into four stages: initial model composition, inquiry activity, group model composition-sharing, and final model construction. The class activities at each stage were analyzed using both the AIR model, i.e., epistemic aim and value (A), epistemic ideals (I), and reliable epistemic processes (R), and the multi-faceted framework for epistemic thinking from the Apt-AIR framework. The results of the study revealed that in science classes emphasizing modeling activities based on the core practices of AST, the elementary students progressively developed more sophisticated explanatory models that included causal relationships explaining the topographic differences between the upstream and downstream sections of a river. This result was due to their engagement in constructing initial models to describe phenomena, supplementing the initial models using data collected in the model experiment, and participating in discussions to share and evaluate group models. Additionally, from the perspective of the Apt-AIR framework, the aspects of epistemic cognition demonstrated by the elementary students in their modeling activities were appropriate for engaging with cognitive processes related to epistemic aims and values, epistemic ideals, and reliable processes. The other four aspects of the Apt-AIR framework, however, were not performed as effectively. In particular, the application of reliable epistemic processes for knowledge construction required more improvement.

A Study on Intelligent Value Chain Network System based on Firms' Information (기업정보 기반 지능형 밸류체인 네트워크 시스템에 관한 연구)

  • Sung, Tae-Eung;Kim, Kang-Hoe;Moon, Young-Su;Lee, Ho-Shin
    • Journal of Intelligence and Information Systems
    • /
    • v.24 no.3
    • /
    • pp.67-88
    • /
    • 2018
  • Until recently, as we recognize the significance of sustainable growth and competitiveness of small-and-medium sized enterprises (SMEs), governmental support for tangible resources such as R&D, manpower, funds, etc. has been mainly provided. However, it is also true that the inefficiency of support systems such as underestimated or redundant support has been raised because there exist conflicting policies in terms of appropriateness, effectiveness and efficiency of business support. From the perspective of the government or a company, we believe that due to limited resources of SMEs technology development and capacity enhancement through collaboration with external sources is the basis for creating competitive advantage for companies, and also emphasize value creation activities for it. This is why value chain network analysis is necessary in order to analyze inter-company deal relationships from a series of value chains and visualize results through establishing knowledge ecosystems at the corporate level. There exist Technology Opportunity Discovery (TOD) system that provides information on relevant products or technology status of companies with patents through retrievals over patent, product, or company name, CRETOP and KISLINE which both allow to view company (financial) information and credit information, but there exists no online system that provides a list of similar (competitive) companies based on the analysis of value chain network or information on potential clients or demanders that can have business deals in future. Therefore, we focus on the "Value Chain Network System (VCNS)", a support partner for planning the corporate business strategy developed and managed by KISTI, and investigate the types of embedded network-based analysis modules, databases (D/Bs) to support them, and how to utilize the system efficiently. Further we explore the function of network visualization in intelligent value chain analysis system which becomes the core information to understand industrial structure ystem and to develop a company's new product development. In order for a company to have the competitive superiority over other companies, it is necessary to identify who are the competitors with patents or products currently being produced, and searching for similar companies or competitors by each type of industry is the key to securing competitiveness in the commercialization of the target company. In addition, transaction information, which becomes business activity between companies, plays an important role in providing information regarding potential customers when both parties enter similar fields together. Identifying a competitor at the enterprise or industry level by using a network map based on such inter-company sales information can be implemented as a core module of value chain analysis. The Value Chain Network System (VCNS) combines the concepts of value chain and industrial structure analysis with corporate information simply collected to date, so that it can grasp not only the market competition situation of individual companies but also the value chain relationship of a specific industry. Especially, it can be useful as an information analysis tool at the corporate level such as identification of industry structure, identification of competitor trends, analysis of competitors, locating suppliers (sellers) and demanders (buyers), industry trends by item, finding promising items, finding new entrants, finding core companies and items by value chain, and recognizing the patents with corresponding companies, etc. In addition, based on the objectivity and reliability of the analysis results from transaction deals information and financial data, it is expected that value chain network system will be utilized for various purposes such as information support for business evaluation, R&D decision support and mid-term or short-term demand forecasting, in particular to more than 15,000 member companies in Korea, employees in R&D service sectors government-funded research institutes and public organizations. In order to strengthen business competitiveness of companies, technology, patent and market information have been provided so far mainly by government agencies and private research-and-development service companies. This service has been presented in frames of patent analysis (mainly for rating, quantitative analysis) or market analysis (for market prediction and demand forecasting based on market reports). However, there was a limitation to solving the lack of information, which is one of the difficulties that firms in Korea often face in the stage of commercialization. In particular, it is much more difficult to obtain information about competitors and potential candidates. In this study, the real-time value chain analysis and visualization service module based on the proposed network map and the data in hands is compared with the expected market share, estimated sales volume, contact information (which implies potential suppliers for raw material / parts, and potential demanders for complete products / modules). In future research, we intend to carry out the in-depth research for further investigating the indices of competitive factors through participation of research subjects and newly developing competitive indices for competitors or substitute items, and to additively promoting with data mining techniques and algorithms for improving the performance of VCNS.