• Title/Summary/Keyword: e-Learning Systems

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Transfer Learning Using Convolutional Neural Network Architectures for Glioma Classification from MRI Images

  • Kulkarni, Sunita M.;Sundari, G.
    • International Journal of Computer Science & Network Security
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    • v.21 no.2
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    • pp.198-204
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    • 2021
  • Glioma is one of the common types of brain tumors starting in the brain's glial cell. These tumors are classified into low-grade or high-grade tumors. Physicians analyze the stages of brain tumors and suggest treatment to the patient. The status of the tumor has an importance in the treatment. Nowadays, computerized systems are used to analyze and classify brain tumors. The accurate grading of the tumor makes sense in the treatment of brain tumors. This paper aims to develop a classification of low-grade glioma and high-grade glioma using a deep learning algorithm. This system utilizes four transfer learning algorithms, i.e., AlexNet, GoogLeNet, ResNet18, and ResNet50, for classification purposes. Among these algorithms, ResNet18 shows the highest classification accuracy of 97.19%.

A Case Study for Efficient Blended Learning Management (효율적인 혼합형 학습 운영을 위한 사례연구)

  • Kwon, Oh-Young
    • The Journal of Korean Institute for Practical Engineering Education
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    • v.2 no.1
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    • pp.52-57
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    • 2010
  • Using the Operating Systems course that is offered by online, a blended learning mixed up with face-to-face lecture and e-learning for O.S. course has been carried out. In order to find a efficient management way of the blended learning, we build up two groups: one group named 01 takes a class which consists of two hours face-to-face lecture and one hour online study per week and the other group named 02 takes a class which consists of two hours online study and one hour face-to-face lecture. According to the result of a mid-term examination, the Cohen's d between two groups is 0.165. It means the small effect size. The 01 group has higer average and smaller variance than 02 group. However, 02 group has more students who earn high score than 01 group. In conclusion, if students can well carry out the self-regulated learning, then the blended learning mixed up with 02 group style is suitable. Otherwise, face-to-face lecture or the blended learning like 01 group style is suitable.

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The Acceptance Intention of Online Start-up Education Systems for Start-up Process (창업 프로세스를 지원하는 온라인 창업 교육 시스템 수용 의도 연구)

  • Kang, Soyoung;Moon, Hyun Sil;Kim, Jae Kyeong;Choi, Bhang Gil
    • Journal of Information Technology Services
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    • v.17 no.4
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    • pp.119-137
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    • 2018
  • Recently, the start-up firms have been under the spotlight because they can create many jobs and are regarded as the growth engine of a country in the fourth industrial revolution. Moreover, after the global financial debacle, many countries emphasize on an entrepreneurial spirit and venture firms. they also pay attention to the importance of educations to promote the start-up firms. In this work, based on technology acceptance model, we try to identify the main factors of accepting online start-up education system. We first defined this system as the online start-up education system which refers to a system to support learning for knowledge, experiences and overall process of start-up firms' tasks. This system also simulates tasks related with prep-entrepreneur so that can be regarded as a kind of decision support systems. As this system has some characteristics, we confirmed some factors of extended technology acceptance model. In our experiments, we find that the perceived ease of use and trust are main factors of acceptance for the online start-up education systems. These results mean that the system should be made to be easy and trustful for their users. Therefore, we expect that this work will be helpful to researchers and developers who consider start-up education systems and provide a way to activate founding start-up firms.

A Review of AI-based Automobile Accident Prevention Systems (인공지능 기반의 자동차사고 감지 시스템 적용 사례 분석)

  • Choi, Jae Gyeong;Kong, Chan Woo;Lim, Sunghoon
    • Journal of the Korea Safety Management & Science
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    • v.22 no.1
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    • pp.9-14
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    • 2020
  • Artificial intelligence (AI) has been applied to most industries by enhancing automation and contributing greatly to efficient processes and high-quality production. This research analyzes the applications of AI-based automobile accident prevention systems. It deals with AI-based collision prevention systems that learn information from various sensors attached to cars and AI-based accident detection systems that automatically report accidents to the control center in the event of a collision. Based on the literature review, technological and institutional changes are taking place at the national levels, which recognize the effectiveness of the systems. In addition, start-ups at home and abroad as well as major car manufacturers are in the process of commercializing auto parts equipped with AI-based collision prevention technology.

Gated Recurrent Unit Architecture for Context-Aware Recommendations with improved Similarity Measures

  • Kala, K.U.;Nandhini, M.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.2
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    • pp.538-561
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    • 2020
  • Recommender Systems (RecSys) have a major role in e-commerce for recommending products, which they may like for every user and thus improve their business aspects. Although many types of RecSyss are there in the research field, the state of the art RecSys has focused on finding the user similarity based on sequence (e.g. purchase history, movie-watching history) analyzing and prediction techniques like Recurrent Neural Network in Deep learning. That is RecSys has considered as a sequence prediction problem. However, evaluation of similarities among the customers is challenging while considering temporal aspects, context and multi-component ratings of the item-records in the customer sequences. For addressing this issue, we are proposing a Deep Learning based model which learns customer similarity directly from the sequence to sequence similarity as well as item to item similarity by considering all features of the item, contexts, and rating components using Dynamic Temporal Warping(DTW) distance measure for dynamic temporal matching and 2D-GRU (Two Dimensional-Gated Recurrent Unit) architecture. This will overcome the limitation of non-linearity in the time dimension while measuring the similarity, and the find patterns more accurately and speedily from temporal and spatial contexts. Experiment on the real world movie data set LDOS-CoMoDa demonstrates the efficacy and promising utility of the proposed personalized RecSys architecture.

The STCW Manila Amendments and its Challenges to the Far East

  • Chae, Chong-Ju
    • Journal of Navigation and Port Research
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    • v.38 no.3
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    • pp.193-202
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    • 2014
  • The comprehensive review of the STCW 1978, as amended in 1995 and associated Code was carried out from 2006 to 2010. These amendments will have a certain degree of impact on Maritime Education and Training(MET) institutes in terms of education and training of seafarer worldwide. Particularly, the Far East region countries are effected more than other regions since they covered about 30% of officers and 37% ratings in the world. In view of these facts this dissertation conceived to analyze the problems in the Far East main seafarer supply countries faced the implementation of "STCW Manila Amendments" To analyze these problems, this dissertation carried out questionnaire research to 7 targeted main MET of major Far East seafarer supply countries. After research this dissertation suggests the possible solutions such as, Joint On-Board Training Center; Joint Asia Maritime E-learning Systems; methods to reducing work-load, ship inspection burden and determine mandatory minimum safety manning standards in a safe way; technical cooperation fund to installation of training equipment; and clarify vague terminology of STCW Manila Amendments, to solve problems identified through the questionnaires.

Vibration-based structural health monitoring using large sensor networks

  • Deraemaeker, A.;Preumont, A.;Reynders, E.;De Roeck, G.;Kullaa, J.;Lamsa, V.;Worden, K.;Manson, G.;Barthorpe, R.;Papatheou, E.;Kudela, P.;Malinowski, P.;Ostachowicz, W.;Wandowski, T.
    • Smart Structures and Systems
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    • v.6 no.3
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    • pp.335-347
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    • 2010
  • Recent advances in hardware and instrumentation technology have allowed the possibility of deploying very large sensor arrays on structures. Exploiting the huge amount of data that can result in order to perform vibration-based structural health monitoring (SHM) is not a trivial task and requires research into a number of specific problems. In terms of pressing problems of interest, this paper discusses: the design and optimisation of appropriate sensor networks, efficient data reduction techniques, efficient and automated feature extraction methods, reliable methods to deal with environmental and operational variability, efficient training of machine learning techniques and multi-scale approaches for dealing with very local damage. The paper is a result of the ESF-S3T Eurocores project "Smart Sensing For Structural Health Monitoring" (S3HM) in which a consortium of academic partners from across Europe are attempting to address issues in the design of automated vibration-based SHM systems for structures.

Artificial Neural Network Models for Optimal Start and Stop of Chiller and AHU (인공신경망 모델을 이용한 냉동기 및 공조기 최적 기동/정지 제어)

  • Park, SungHo;Ahn, Ki Uhn;Hwang, Aaron;Choi, Sunkyu;Park, Cheol Soo
    • Journal of the Architectural Institute of Korea Structure & Construction
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    • v.35 no.2
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    • pp.45-52
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    • 2019
  • BEMS(Building Energy Management Systems) have been applied to office buildings and collect relevant building energy data, e.g. temperatures, mass flow rates and energy consumptions of building mechanical systems and indoor spaces. The aforementioned measured data can be beneficially utilized for developing data-driven machine learning models which can be then used as part of MPC(Model Predictive Control) and/or optimal control strategies. In this study, the authors developed ANN(Artificial Neural Network) models of an AHU (Air Handling Unit) and a chiller for a real-life office building using BEMS data. Based on the ANN models, the authors developed optimal control strategies, e.g. daily operation schedule with regard to optimal start and stop of the AHU and the chiller (500 RT). It was found that due to the optimal start and stop of the AHU and the chiller, 4.5% and 16.4% of operation hours of the AHU and the chiller could be saved, compared to an existing operation.

Open Digital Textbook for Smart Education (스마트교육을 위한 오픈 디지털교과서)

  • Koo, Young-Il;Park, Choong-Shik
    • Journal of Intelligence and Information Systems
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    • v.19 no.2
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    • pp.177-189
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    • 2013
  • In Smart Education, the roles of digital textbook is very important as face-to-face media to learners. The standardization of digital textbook will promote the industrialization of digital textbook for contents providers and distributers as well as learner and instructors. In this study, the following three objectives-oriented digital textbooks are looking for ways to standardize. (1) digital textbooks should undertake the role of the media for blended learning which supports on-off classes, should be operating on common EPUB viewer without special dedicated viewer, should utilize the existing framework of the e-learning learning contents and learning management. The reason to consider the EPUB as the standard for digital textbooks is that digital textbooks don't need to specify antoher standard for the form of books, and can take advantage od industrial base with EPUB standards-rich content and distribution structure (2) digital textbooks should provide a low-cost open market service that are currently available as the standard open software (3) To provide appropriate learning feedback information to students, digital textbooks should provide a foundation which accumulates and manages all the learning activity information according to standard infrastructure for educational Big Data processing. In this study, the digital textbook in a smart education environment was referred to open digital textbook. The components of open digital textbooks service framework are (1) digital textbook terminals such as smart pad, smart TVs, smart phones, PC, etc., (2) digital textbooks platform to show and perform digital contents on digital textbook terminals, (3) learning contents repository, which exist on the cloud, maintains accredited learning, (4) App Store providing and distributing secondary learning contents and learning tools by learning contents developing companies, and (5) LMS as a learning support/management tool which on-site class teacher use for creating classroom instruction materials. In addition, locating all of the hardware and software implement a smart education service within the cloud must have take advantage of the cloud computing for efficient management and reducing expense. The open digital textbooks of smart education is consdered as providing e-book style interface of LMS to learners. In open digital textbooks, the representation of text, image, audio, video, equations, etc. is basic function. But painting, writing, problem solving, etc are beyond the capabilities of a simple e-book. The Communication of teacher-to-student, learner-to-learnert, tems-to-team is required by using the open digital textbook. To represent student demographics, portfolio information, and class information, the standard used in e-learning is desirable. To process learner tracking information about the activities of the learner for LMS(Learning Management System), open digital textbook must have the recording function and the commnincating function with LMS. DRM is a function for protecting various copyright. Currently DRMs of e-boook are controlled by the corresponding book viewer. If open digital textbook admitt DRM that is used in a variety of different DRM standards of various e-book viewer, the implementation of redundant features can be avoided. Security/privacy functions are required to protect information about the study or instruction from a third party UDL (Universal Design for Learning) is learning support function for those with disabilities have difficulty in learning courses. The open digital textbook, which is based on E-book standard EPUB 3.0, must (1) record the learning activity log information, and (2) communicate with the server to support the learning activity. While the recording function and the communication function, which is not determined on current standards, is implemented as a JavaScript and is utilized in the current EPUB 3.0 viewer, ths strategy of proposing such recording and communication functions as the next generation of e-book standard, or special standard (EPUB 3.0 for education) is needed. Future research in this study will implement open source program with the proposed open digital textbook standard and present a new educational services including Big Data analysis.

Creating Deep Learning-based Acrobatic Videos Using Imitation Videos

  • Choi, Jong In;Nam, Sang Hun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.2
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    • pp.713-728
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    • 2021
  • This paper proposes an augmented reality technique to generate acrobatic scenes from hitting motion videos. After a user shoots a motion that mimics hitting an object with hands or feet, their pose is analyzed using motion tracking with deep learning to track hand or foot movement while hitting the object. Hitting position and time are then extracted to generate the object's moving trajectory using physics optimization and synchronized with the video. The proposed method can create videos for hitting objects with feet, e.g. soccer ball lifting; fists, e.g. tap ball, etc. and is suitable for augmented reality applications to include virtual objects.