• Title/Summary/Keyword: 학습 환경 설계

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Challenges faced by elementary teachers in implementing the five practices for effective mathematical discussions (효과적인 수학적 논의를 위한 5가지 관행의 적용 과정에서 초등학교 교사들이 직면하는 어려움)

  • Pang, JeongSuk;Kim, Sohyeon;An, Hyojoo;Chung, Jisu;Kwak, Giwoo
    • The Mathematical Education
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    • v.62 no.1
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    • pp.95-115
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    • 2023
  • Even the teachers who agree with the necessity of effective mathematical discussions find it difficult to orchestrate such discussions in the actual lessons. This study focused on analyzing the difficulties 15 elementary school teachers faced in applying "the five practices for orchestrating productive mathematics discussions" to their lessons. Specifically, this study analyzed the process of planning, implementing, and reflecting on the lessons to which three or four teachers as a teacher community applied the five practices. The results of this study showed that the teachers experienced difficulties in selecting and presenting tasks tailored to the student levels and class environment, monitoring all students' solutions, and identifying the core mathematical ideas in student solutions. In addition, this study revealed practical and specific difficulties that had not been described in the previous studies, such as writing a lesson plan for effective use, simultaneously performing multiple teacher roles, and visually sharing student presentations. This study is expected to provide practical tips for elementary school teachers who are eager to promote effective mathematical discussions and to provoke professional discourse for teacher educators through specific examples.

Implementation of reliable dynamic honeypot file creation system for ransomware attack detection (랜섬웨어 공격탐지를 위한 신뢰성 있는 동적 허니팟 파일 생성 시스템 구현)

  • Kyoung Wan Kug;Yeon Seung Ryu;Sam Beom Shin
    • Convergence Security Journal
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    • v.23 no.2
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    • pp.27-36
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    • 2023
  • In recent years, ransomware attacks have become more organized and specialized, with the sophistication of attacks targeting specific individuals or organizations using tactics such as social engineering, spear phishing, and even machine learning, some operating as business models. In order to effectively respond to this, various researches and solutions are being developed and operated to detect and prevent attacks before they cause serious damage. In particular, honeypots can be used to minimize the risk of attack on IT systems and networks, as well as act as an early warning and advanced security monitoring tool, but in cases where ransomware does not have priority access to the decoy file, or bypasses it completely. has a disadvantage that effective ransomware response is limited. In this paper, this honeypot is optimized for the user environment to create a reliable real-time dynamic honeypot file, minimizing the possibility of an attacker bypassing the honeypot, and increasing the detection rate by preventing the attacker from recognizing that it is a honeypot file. To this end, four models, including a basic data collection model for dynamic honeypot generation, were designed (basic data collection model / user-defined model / sample statistical model / experience accumulation model), and their validity was verified.

A Study on Intelligent Self-Recovery Technologies for Cyber Assets to Actively Respond to Cyberattacks (사이버 공격에 능동대응하기 위한 사이버 자산의 지능형 자가복구기술 연구)

  • Se-ho Choi;Hang-sup Lim;Jung-young Choi;Oh-jin Kwon;Dong-kyoo Shin
    • Journal of Internet Computing and Services
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    • v.24 no.6
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    • pp.137-144
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    • 2023
  • Cyberattack technology is evolving to an unpredictable degree, and it is a situation that can happen 'at any time' rather than 'someday'. Infrastructure that is becoming hyper-connected and global due to cloud computing and the Internet of Things is an environment where cyberattacks can be more damaging than ever, and cyberattacks are still ongoing. Even if damage occurs due to external influences such as cyberattacks or natural disasters, intelligent self-recovery must evolve from a cyber resilience perspective to minimize downtime of cyber assets (OS, WEB, WAS, DB). In this paper, we propose an intelligent self-recovery technology to ensure sustainable cyber resilience when cyber assets fail to function properly due to a cyberattack. The original and updated history of cyber assets is managed in real-time using timeslot design and snapshot backup technology. It is necessary to secure technology that can automatically detect damage situations in conjunction with a commercialized file integrity monitoring program and minimize downtime of cyber assets by analyzing the correlation of backup data to damaged files on an intelligent basis to self-recover to an optimal state. In the future, we plan to research a pilot system that applies the unique functions of self-recovery technology and an operating model that can learn and analyze self-recovery strategies appropriate for cyber assets in damaged states.

Comparison of the Survey of Teaching Demand for Distance Education Support for the 2021 and 2022 Academic Years : For D Community Colleges in Daegu (2021학년도와 2022학년도 원격교육지원에 대한 교수 수요도 조사 비교: 대구지역 D전문대학을 대상으로)

  • Park, Jeong-Kyu
    • Journal of the Korean Society of Radiology
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    • v.16 no.4
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    • pp.491-497
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    • 2022
  • In this study, we tried to secure basic data to create an environment necessary for distance learning through a survey on professor demand. Among the 184 full-time faculty members of the university, 73 (39.89%) respondents in 2021 and 87 (47.28%) in 2022 were included. As a result of the research on professor demand, in the 2021 school year, 27 people (37%) were classified as LMS improvement items when checking attendance, 38 people (23.3%) were pin-mics as content development support items, and 26 people (35.6%), 33 people (45.2%) of GOM Mix and 25 people (34.2%) of the distance education support center wanted to learn video editing program as the item of video editing program they are currently using. In the 2022 school year, 27 people (31.03%) said mobile upgrade as an LMS improvement item, 52 people (59.8%) of pin-microphone as a content development support item, 33 people (37.9%), but currently using the content creation intention using a studio. As for the video editing program they are working on, 47 people (54%) of GOM Mix Pro and 23 people (26.4%) of the distance education support center want to learn content creation method. In addition, the intention to produce content using the studio for the 2021 and 2022 academic year and the desired educational topic of the distance education support center in the future appeared insignificant (p > 0.05). In this distance education support center, we are working to solve the class of LMS attendance, upgrade mobile, and plan to distribute pin microphones. We are planning to increase the usability of the studio and provide training on how to use video editing programs and how to create video content. In order for a smooth class to take place in a university distance class, the university authorities should seek ways to support the instructor so that he/she does not have difficulties in performing his/her role as a teaching designer, such as setting learning goals, organizing and organizing content, motivating learning, and establishing effective class participation plans. there is a need

Analysis of the Influence of Role Models on College Students' Entrepreneurial Intentions: Exploring the Multiple Mediating Effects of Growth Mindset and Entrepreneurial Self-Efficacy (대학생 창업의지에 대한 롤모델의 영향 분석: 성장마인드셋과 창업자기효능감의 다중매개효과를 중심으로)

  • Jin Soo Maing;Sun Hyuk Kim
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.18 no.5
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    • pp.17-32
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    • 2023
  • The entrepreneurial activities of college students play a significant role in modern economic and social development, particularly as a solution to the changing economic landscape and youth unemployment issues. Introducing innovative ideas and technologies into the market through entrepreneurship can contribute to sustainable economic growth and social value. Additionally, the entrepreneurial intentions of college students are shaped by various factors, making it crucial to deeply understand and appropriately support these elements. To this end, this study systematically explores the importance and impact of role models through a multiple serial mediation analysis. Through a survey of 300 college students, the study analyzed how two psychological variables, growth mindset and entrepreneurial self-efficacy, mediate the influence of role models on entrepreneurial intentions. The presence and success stories of role models were found to enhance the growth mindset of college students, which in turn boosts their entrepreneurial self-efficacy and ultimately strengthens their entrepreneurial intentions. The analysis revealed that exposure to role models significantly influences the formation of a growth mindset among college students. This mindset fosters a positive attitude towards viewing challenges and failures in entrepreneurship as learning opportunities. Such a mindset further enhances entrepreneurial self-efficacy, thereby strengthening the intention to engage in entrepreneurial activities. This research offers insights by integrating various theories, such as mindset theory and social learning theory, to deeply understand the complex process of forming entrepreneurial intentions. Practically, this study provides important guidelines for the design and implementation of college entrepreneurship education. Utilizing role models can significantly enhance students' entrepreneurial intentions, and educational programs can strengthen students' growth mindset and entrepreneurial self-efficacy by sharing entrepreneurial experiences and knowledge through role models. In conclusion, this study provides a systematic and empirical analysis of the various factors and their complex interactions that impact the entrepreneurial intentions of college students. It confirms that psychological factors like growth mindset and entrepreneurial self-efficacy play a significant role in shaping entrepreneurial intentions, beyond mere information or technical education. This research emphasizes that these psychological factors should be comprehensively considered when developing and implementing policies and programs related to college entrepreneurship education.

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The way to make training data for deep learning model to recognize keywords in product catalog image at E-commerce (온라인 쇼핑몰에서 상품 설명 이미지 내의 키워드 인식을 위한 딥러닝 훈련 데이터 자동 생성 방안)

  • Kim, Kitae;Oh, Wonseok;Lim, Geunwon;Cha, Eunwoo;Shin, Minyoung;Kim, Jongwoo
    • Journal of Intelligence and Information Systems
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    • v.24 no.1
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    • pp.1-23
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    • 2018
  • From the 21st century, various high-quality services have come up with the growth of the internet or 'Information and Communication Technologies'. Especially, the scale of E-commerce industry in which Amazon and E-bay are standing out is exploding in a large way. As E-commerce grows, Customers could get what they want to buy easily while comparing various products because more products have been registered at online shopping malls. However, a problem has arisen with the growth of E-commerce. As too many products have been registered, it has become difficult for customers to search what they really need in the flood of products. When customers search for desired products with a generalized keyword, too many products have come out as a result. On the contrary, few products have been searched if customers type in details of products because concrete product-attributes have been registered rarely. In this situation, recognizing texts in images automatically with a machine can be a solution. Because bulk of product details are written in catalogs as image format, most of product information are not searched with text inputs in the current text-based searching system. It means if information in images can be converted to text format, customers can search products with product-details, which make them shop more conveniently. There are various existing OCR(Optical Character Recognition) programs which can recognize texts in images. But existing OCR programs are hard to be applied to catalog because they have problems in recognizing texts in certain circumstances, like texts are not big enough or fonts are not consistent. Therefore, this research suggests the way to recognize keywords in catalog with the Deep Learning algorithm which is state of the art in image-recognition area from 2010s. Single Shot Multibox Detector(SSD), which is a credited model for object-detection performance, can be used with structures re-designed to take into account the difference of text from object. But there is an issue that SSD model needs a lot of labeled-train data to be trained, because of the characteristic of deep learning algorithms, that it should be trained by supervised-learning. To collect data, we can try labelling location and classification information to texts in catalog manually. But if data are collected manually, many problems would come up. Some keywords would be missed because human can make mistakes while labelling train data. And it becomes too time-consuming to collect train data considering the scale of data needed or costly if a lot of workers are hired to shorten the time. Furthermore, if some specific keywords are needed to be trained, searching images that have the words would be difficult, as well. To solve the data issue, this research developed a program which create train data automatically. This program can make images which have various keywords and pictures like catalog and save location-information of keywords at the same time. With this program, not only data can be collected efficiently, but also the performance of SSD model becomes better. The SSD model recorded 81.99% of recognition rate with 20,000 data created by the program. Moreover, this research had an efficiency test of SSD model according to data differences to analyze what feature of data exert influence upon the performance of recognizing texts in images. As a result, it is figured out that the number of labeled keywords, the addition of overlapped keyword label, the existence of keywords that is not labeled, the spaces among keywords and the differences of background images are related to the performance of SSD model. This test can lead performance improvement of SSD model or other text-recognizing machine based on deep learning algorithm with high-quality data. SSD model which is re-designed to recognize texts in images and the program developed for creating train data are expected to contribute to improvement of searching system in E-commerce. Suppliers can put less time to register keywords for products and customers can search products with product-details which is written on the catalog.

The Actual Conditions and Improvement of the Eco-Forests Mater Plan, South Korea (우리나라 생태숲조성 기본계획 실태 및 개선방향)

  • Heo, Jae-Yong;Kim, Do-Gyun;Jeong, Jeong-Chae;Lee, Jeong
    • Korean Journal of Environment and Ecology
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    • v.24 no.3
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    • pp.235-248
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    • 2010
  • This study was carried out to the actual conditions and improvement of the eco-forests master plan in South Korea, and suggested its problems and improvement direction. Results from survey and analysis of limiting factors or constraints in the construction plans of eco-forests in Korea revealed that there were highly frequent problems involving site feasibility, topographic aspect, and existing vegetation. The results of survey on the status of land use indicated that the average ratio of the use of private estate was 29.7%, so then it was estimated that a great amount of investment in purchase of eco-forest site would be required. Results from survey on major introduced facilities showed that there was high frequency of introduction of infrastructure, building facility, recreational facility, convenience facility, and information facility, and that there was low frequency of introduction of plant culture system, ecological facility, structural symbol and sculpture, and the likes. There was just one eco-forest park where more than 500 species of plants grew, and the result of investigation indicated that the diversity of plant species in 11 eco-forest parks was lower than the standards for construction of eco-forest. Results from analysis of the projects costs revealed that investment cost in facilities was higher than planting costs, and that a large amount of investment was made in the initial stage of the project. There was no planned budget for the purpose of cultivating and maintaining the plants and vegetation after construction of eco-forest. The basic concepts in construction of eco-forests were established according to the guidelines presented by the Korea Forest Service; however, the detailed work of the project was planned with its user-oriented approach. Then the construction of eco-forest was being planned following the directions, which would lead to development of a plant garden similar to arboretum or botanical garden. Therefore, it is required that the architect who designs eco-forest as well as the public officer concerned firmly establish the concepts of eco-forest, and that, through close analysis of development conditions, a candidate site to fit the purpose of constructing eco-forest be selected, and also a substantive management plan be established upon completion of construction of eco-forest.

Techniques for Acquisition of Moving Object Location in LBS (위치기반 서비스(LBS)를 위한 이동체 위치획득 기법)

  • Min, Gyeong-Uk;Jo, Dae-Su
    • The KIPS Transactions:PartD
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    • v.10D no.6
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    • pp.885-896
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    • 2003
  • The typws of service using location Information are being various and extending their domain as wireless internet tochnology is developing and its application par is widespread, so it is prospected that LBS(Location-Based Services) will be killer application in wireless internet services. This location information is basic and high value-added information, and this information services make prior GIS(Geographic Information System) to be useful to anybody. The acquisition of this location information from moving object is very important part in LBS. Also the interfacing of acquisition of moving object between MODB and telecommunication network is being very important function in LBS. After this, when LBS are familiar to everybody, we can predict that LBS system load is so heavy for the acquisition of so many subscribers and vehicles. That is to say, LBS platform performance is fallen off because of overhead increment of acquiring moving object between MODB and wireless telecommunication network. So, to make stable of LBS platform, in this MODB system, acquisition of moving object location par as reducing the number of acquisition of unneccessary moving object location. We study problems in acquiring a huge number of moving objects location and design some acquisition model using past moving patternof each object to reduce telecommunication overhead. And after implementation these models, we estimate performance of each model.

Design of Deep Learning-based Tourism Recommendation System Based on Perceived Value and Behavior in Intelligent Cloud Environment (지능형 클라우드 환경에서 지각된 가치 및 행동의도를 적용한 딥러닝 기반의 관광추천시스템 설계)

  • Moon, Seok-Jae;Yoo, Kyoung-Mi
    • Journal of the Korean Applied Science and Technology
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    • v.37 no.3
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    • pp.473-483
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    • 2020
  • This paper proposes a tourism recommendation system in intelligent cloud environment using information of tourist behavior applied with perceived value. This proposed system applied tourist information and empirical analysis information that reflected the perceptual value of tourists in their behavior to the tourism recommendation system using wide and deep learning technology. This proposal system was applied to the tourism recommendation system by collecting and analyzing various tourist information that can be collected and analyzing the values that tourists were usually aware of and the intentions of people's behavior. It provides empirical information by analyzing and mapping the association of tourism information, perceived value and behavior to tourism platforms in various fields that have been used. In addition, the tourism recommendation system using wide and deep learning technology, which can achieve both memorization and generalization in one model by learning linear model components and neural only components together, and the method of pipeline operation was presented. As a result of applying wide and deep learning model, the recommendation system presented in this paper showed that the app subscription rate on the visiting page of the tourism-related app store increased by 3.9% compared to the control group, and the other 1% group applied a model using only the same variables and only the deep side of the neural network structure, resulting in a 1% increase in subscription rate compared to the model using only the deep side. In addition, by measuring the area (AUC) below the receiver operating characteristic curve for the dataset, offline AUC was also derived that the wide-and-deep learning model was somewhat higher, but more influential in online traffic.

Effects of Educational Programs Utilizing Forests on Maladjusted Behavior of Mentally Retarded Students (숲을 활용한 교육이 정신지체학생의 부적응행동에 미치는 영향)

  • Park, Kyoung-Lee;Sim, Woo-Kyung
    • Journal of the Korean Institute of Landscape Architecture
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    • v.38 no.5
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    • pp.64-79
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    • 2010
  • Students with intellectual disabilities typically have great difficulties communicating their needs and wants and may get frustrated, anxious or show signs of aggressive behaviour. They are often unable to understand the concept of relationships with other people as well. This lack of social communication and interaction leads to poor motivation which increases other areas of difficulty in their lives. Therefore, to teach students with intellectual disabilities, it is essential to find special teaching methods to support their positive behavior. This paper proposes that special educational curriculum for students with intellectual impairments utilize natural environments(forests) and materials. The purpose of this study was to investigate the effects of Educational Programs Utilizing Forests on maladjusted behavior of students with mental retardation and to examine the positive effects of such planning practices. The subjects were middle school students who attended a special school for mentally-retarded students. They were divided into two separate groups- an experimental group and a control group. All subjects received the pre and post test using the same method. This program was applied to the formal educational process of middle school from March 1st to October 30th, 2009. In this experiment the results indicate that the effect of using a natural environment(forest) and the materials within a formal educational curriculum was positive as a type of horticultural therapy and that it supports positive behavior strategies in students with intellectual impairments. The usage of various natural materials including plants and flowers within the natural environments provide students with increased opportunities to participate. Teaching methods including natural materials help teachers engage with their students more easily during routine activities as their interest is already stimulated. This project will help students with intellectual impairments to build skills which enable effective participation and increase independence throughout their lives. This should be embedded into both routine and planned activities of the classroom Also, it offers a needed interior plan for the treatment space through an analysis of psychological factors of how the environment affects students.