• Title/Summary/Keyword: software contents

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Human-Content Interface : A Friction-Based Interface Model for Efficient Interaction with Android App and Web-Based Contents

  • Kim, Jong-Hyun
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.4
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    • pp.55-62
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    • 2021
  • In this paper, we propose a human-content interface that allows users to quickly and efficiently search data through friction-based scrolling with ROI(Regions of interests). Our approach, conceived from the behavior of finding information or content of interest to users, efficiently calculates ROI for a given content. Based on the kernel developed by conceiving from GMM(Gaussian mixture model), information is searched by moving the screen smoothly and quickly to the location of the information of interest to the user. In this paper, linear interpolation is applied to make one softer inertia, and this is applied to scrolls. As a result, unlike the existing approach in which information is searched according to the user's input, our method can more easily and intuitively find information or content that the user is interested in through friction-based scrolling. For this reason, the user can save search time.

Design and Satisfaction Analysis of Embedded IoT Course (임베디드 IoT 과목 설계 및 만족도 분석)

  • Hong, Jun-Ki;Paik, Jong Ho;Kang, Mingoo;Hong, Sung-Chan
    • Journal of Internet Computing and Services
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    • v.20 no.5
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    • pp.19-26
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    • 2019
  • Recently, the importance of the internet of things (IoT) education has been emphasized due to the progress of research on IoT technology. Therefore, universities require an efficient IoT course. In this paper, we propose an undergraduate IoT course using the Bluetooth function of smartphone and Arduino kit. The proposed embedded IoT class uses the Bluetooth capabilities of the smartphone to connect Arduino and activate various sensors to encourage students to become interested in the class. According to students' midterm and final exam scores, students programming skills have been improved since students' projects were in progress during the course. Further, according to students' survey, the proposed IoT class is very effective in understanding the embedded IoT and 75% of the students satisfied with the proposed course.

Artificial Intelligence-Based High School Course and University Major Recommendation System for Course-Related Career Exploration (교과 연계 진로 탐색을 위한 인공지능 기반 고교 선택교과 및 대학 학과 추천 시스템)

  • Baek, Jinheon;Kim, Hayeon;Kwon, Kiwon
    • KIPS Transactions on Software and Data Engineering
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    • v.10 no.1
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    • pp.35-44
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    • 2021
  • Recent advances in the 4th Industrial Revolution have accelerated the change of the working environment, such that the paradigm of education has been shifted in accordance with career education including the free semester system and the high school credit system. While the purpose of those systems is students' self-motivated career exploration, educational limitations for teachers and students exist due to the rapid change of the information on education. Also, education technology research to tackle these limitations is relatively insufficient. To this end, this study first defines three requirements that education technologies for the career education system should consider. Then, through data-driven artificial intelligence technology, this study proposes a data system and an artificial intelligence recommendation model that incorporates the topics for career exploration, courses, and majors in one scheme. Finally, this study demonstrates that the set-based artificial intelligence model shows satisfactory performances on recommending career education contents such as courses and majors, and further confirms that the actual application of this system in the educational field is acceptable.

A Design of Similar Video Recommendation System using Extracted Words in Big Data Cluster (빅데이터 클러스터에서의 추출된 형태소를 이용한 유사 동영상 추천 시스템 설계)

  • Lee, Hyun-Sup;Kim, Jindeog
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.2
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    • pp.172-178
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    • 2020
  • In order to recommend contents, the company generally uses collaborative filtering that takes into account both user preferences and video (item) similarities. Such services are primarily intended to facilitate user convenience by leveraging personal preferences such as user search keywords and viewing time. It will also be ranked around the keywords specified in the video. However, there is a limit to analyzing video similarities using limited keywords. In such cases, the problem becomes serious if the specified keyword does not properly reflect the item. In this paper, I would like to propose a system that identifies the characteristics of a video as it is by the system without human intervention, and analyzes and recommends similarities between videos. The proposed system analyzes similarities by taking into account all words (keywords) that have different meanings from training videos, and in such cases, the methods handled by big data clusters are applied because of the large scale of data and operations.

A study on Cognitive Judgment Technology using Augmented Reality (증강현실을 이용한 인지 판단 기술에 관한 연구)

  • Lee, Cheol-Seung;Kim, Kuk-Se
    • The Journal of the Korea institute of electronic communication sciences
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    • v.15 no.6
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    • pp.1075-1080
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    • 2020
  • The development of computing technology and networking is developing as the fundamental technology of the 4th industrial revolution. AR and VR technologies, which are dual realistic media fields, are developing into many application areas, especially! The potential for development in the medical field is very high. As for the development potential of the health care field, the 4th industrial revolution such as AR/VR to solve problems, such as the increase of various chronic diseases due to the aging of the population, the limitation of infrastructure that can deal with them, and the lack of specialized personnel. It is adopting services in the healthcare field using representative technologies. Accordingly, AR/VR in the healthcare field occupies about 17% of the total industrial market. Therefore, in this study, cognitive judgment technology using AR applies cognitive evaluation through a computing system to the mild cognitive impairment, and based on the results, researches to utilize cognitive rehabilitation contents using augmented reality, and hardware necessary for cognitive judgment technology. Also, software design to help in the field of cognitive judgment technology and healthcare using AR.

Development of X-Ray Array Detector Signal Processing System (X-Ray 어레이 검출 모듈 신호처리 시스템 개발)

  • Lim, Ik-Chan;Park, Jong-Won;Kim, Young-Kil;Sung, So-Young
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.23 no.10
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    • pp.1298-1304
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    • 2019
  • Since the 9·11 terror attack in 2001, the Maritime Logistics Security System has been strengthened and required X-ray image for every imported cargos from manufacturing countries to United States. For scanning cargos, the container inspection systems use high energy X-rays for examination of contents of a container to check the nuclear, explosive, dangerous and illegal materials. Nowadays, the X-ray cargo scanners are established and used by global technologies for inspection of suspected cargos in the customs agency but these technologies have not been localized and developed sufficiently. In this paper, we propose the X-ray array detector system which is a core component of the container scanning system. For implementation of X-ray array detector, the analog and digital signal processing units are fabricated with integrated hardware, FPGA logics and GUI software for real-time X-ray images. The implemented system is superior in terms of resolution and power consumption compared to the existing products currently used in ports.

Development of a Forensic Analyzing Tool based on Cluster Information of HFS+ filesystem

  • Cho, Gyu-Sang
    • International Journal of Internet, Broadcasting and Communication
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    • v.13 no.3
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    • pp.178-192
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    • 2021
  • File system forensics typically focus on the contents or timestamps of a file, and it is common to work around file/directory centers. But to recover a deleted file on the disk or use a carving technique to find and connect partial missing content, the evidence must be analyzed using cluster-centered analysis. Forensics tools such as EnCase, TSK, and X-ways, provide a basic ability to get information about disk clusters, but these are not the core functions of the tools. Alternatively, Sysinternals' DiskView tool provides a more intuitive visualization function, which makes it easier to obtain information around disk clusters. In addition, most current tools are for Windows. There are very few forensic analysis tools for MacOS, and furthermore, cluster analysis tools are very rare. In this paper, we developed a tool named FACT (Forensic Analyzer based Cluster Information Tool) for analyzing the state of clusters in a HFS+ file system, for digital forensics. The FACT consists of three features, a Cluster based analysis, B-tree based analysis, and Directory based analysis. The Cluster based analysis is the main feature, and was basically developed for cluster analysis. The FACT tool's cluster visualization feature plays a central role. The FACT tool was programmed in two programming languages, C/C++ and Python. The core part for analyzing the HFS+ filesystem was programmed in C/C++ and the visualization part is implemented using the Python Tkinter library. The features in this study will evolve into key forensics tools for use in MacOS, and by providing additional GUI capabilities can be very important for cluster-centric forensics analysis.

Integrated Verbal and Nonverbal Sentiment Analysis System for Evaluating Reliability of Video Contents (영상 콘텐츠의 신뢰도 평가를 위한 언어와 비언어 통합 감성 분석 시스템)

  • Shin, Hee Won;Lee, So Jeong;Son, Gyu Jin;Kim, Hye Rin;Kim, Yoonhee
    • KIPS Transactions on Software and Data Engineering
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    • v.10 no.4
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    • pp.153-160
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    • 2021
  • With the advent of the "age of video" due to the simplification of video content production and the convenience of broadcasting channel operation, review videos on various products are drawing attention. We proposes RASIA, an integrated reliability analysis system based on verbal and nonverbal sentiment analysis of review videos. RASIA extracts and quantifies each emotional value obtained through language sentiment analysis and facial analysis of the reviewer in the video. Subsequently, we conduct an integrated reliability analysis of standardized verbal and nonverbal sentimental values. RASIA provide an new objective indicator to evaluate the reliability of the review video.

A Trend Analysis of Computer Education based on SNS Data through Data Mining Analysis (텍스트마이닝 분석을 활용한 SNS 데이터 기반의 정보교육의 동향 분석 연구)

  • Kim, Kapsu;Chun, Seokju;Koo, Dukhoi;Shin, Seungki
    • Journal of The Korean Association of Information Education
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    • v.25 no.2
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    • pp.289-300
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    • 2021
  • SNS data was collected and analyzed by topic modeling techniques to examine recent trends in information education. By deriving keywords and topics for SW education and AI education, we not only attempted to discover insights ahead of the next revised curriculum but also suggested directions. According to the SNS data analysis, the contents of human resource development for software and the instructional method in schools are indicated as a high requirement. Meanwhile, SW education should be conducted through a separate curriculum from elementary school, and this was consistent with the opinion that it is necessary to be organized as a required subject. There was an opinion to support the schools since AI education is newly introduced in next revised national curriculum. The trends in SW education and AI education which are observed through SNS data analysis could be concluded to conduct the substantial operation of information education and curriculum organization.

Sentence Recommendation Using Beam Search in a Military Intelligent Image Analysis System (군사용 지능형 영상 판독 시스템에서의 빔서치를 활용한 문장 추천)

  • Na, Hyung-Sun;Jeon, Tae-Hyeon;Kang, Hyung-Seok;Ahn, Jinhyun;Im, Dong-Hyuk
    • KIPS Transactions on Software and Data Engineering
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    • v.10 no.11
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    • pp.521-528
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    • 2021
  • Existing image analysis systems in use in the military field are carried out by readers analyzing and identifying images themselves, writing and disseminating related content, and in this process, repetitive tasks are frequent, resulting in workload. In this paper, to solve the previous problem, we proposed an algorithm that can operate the Seq2Seq model on a word basis, which operates on a sentence basis, and applied the Attention technique to improve accuracy. In addition, by applying the Beam Search technique, we would like to recommend various current identification sentences based on the past identification contents of a specific area. It was confirmed through experiments that the Beam Search technique recommends sentences more effectively than the existing greedy Search technique, and confirmed that the accuracy of recommendation increases when the size of Beam is large.