• Journal of Fisheries and Marine Sciences Education
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• v.27 no.1
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• pp.160-169
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• 2015

The purpose of this study was to search and analyze the realities and needs of life long education, the necessity and perception of life competencies and the difference of competencies on experiences of education to support life long education system for adult learners in Busan and Ulsan. In this study, we conducted a questionnaire survey of 234 adult learners living in Busan and Ulsan. The results of this study were summarized as follows. First, adult learners perceived that life long education was very important to adults and appreciated an educational institution being managed by government. Second, adult learners thought that basic literacy competency and basic work competency were important and late fifties perceived that professional job is in important. Third, adult learners perceived that self directed learning and capacity of management are poor competencies. And they perceived that the government support adult learners who has economical difficulty. Forth, adult learners perceived that it was normal that 'professional job' and 'job transition abilities', 'women', 'the middle aged and old','the unemployed' and' low incomers' perceived that they have poor level. Fifth, according to the results of ${\chi}^2$ test for determining the statistical significance of differences in experience in lifelong learning among adult learner groups divided by their individual background, significant differences were observed in a few competencies(p<.05, p<.01).

• Journal of Korean Library and Information Science Society
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• v.36 no.2
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• pp.69-91
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• 2005

Public libraries have been well adapted for the changes in lifestyle and socio-cultural environments brought by the rapid advancement of information technology, the development of mass communities, and the increase in leisure activities. Government and local communities demand public libraries to take in charge of providing lifelong education for the Public. Many Public libraries have worked as a center for life-long education, while carrying out various functions and services in close relation with the life of community members. Public libraries are in a very poor condition, lacking the facilities, professional workforce, budgets, and so on, which are sufficient to strengthen their role as a center for life-long education. In this study, the roles of public libraries in developing life-long education are examined as follows : First, the concepts and directions of life-long education are discussed : second, the roles of public libraries in facilitating life-long education are examined and third, the categories of life-long education programs of public libraries are suggested.

• Journal of the Korean earth science society
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• v.24 no.2
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• pp.108-116
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• 2003

Problem Based Learning (PBL) is one of methods which has been developed to promote student-centered learning and to pursue self-directed learning for life-long learning. The purpose of this study is exploring the possibility of Problem Based Learning (PBL) in college Earth science course. The participants of this study were fourteen students attending an Earth science class at Sookmyung Women's University in Seoul. PBL was implemented in the form of group project with utilizing Web-based course tool. We provided questionnaires and conducted interviews to figure out students' perception about PBL. The findings were as follows: Through a given experiences, (1) students participated more actively than LBL (Lecture Based Learning), (2) more students were engaged with self-directed learning, and (3) students made higher cognitive efforts. LBL seemed to be more efficient way to acquire factual knowledge. In the meanwhile, PBL did not seem to affect the improvement of communication skills. Students could not make use of Web-based course tool effectively in communicating with other team members. In this study, we found that college student participants preferred problems related to everyday life, environmental issues and interesting but unusual incidents. On the other hand, they felt difficult in open-ended problems, especially when they were asked to provide their own evaluation. On the basis of PBL experiment in this paper, we present one method of successful implementation of PBL and suggest topics which should be studied in the future.

• East Asian Journal of Business Economics (EAJBE)
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• v.2 no.4
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• pp.26-47
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• 2014

The paper examined effect of age cohort on life cycle financial planning. A total of 990 questionnaires were distributed with a 55.2% return rate. Seven hypotheses were analysed using hierarchical and ordinary regression analysis. The results revealed that age cohort variables made significant contribution to life cycle financial planning as well as personal orientation towards retirement planning, particularly the younger age cohort. Age cohorts do affect personal orientation towards retirement planning with the confidence level making a significant impact. Current financial resources do have a strong positive impact on consumption for all age cohorts. On the other hand, no significant effect was found between age cohorts and current financial resources but older age cohorts were relatively more significant predictors. The implication was that not only should their individual perceptions of financial planning become an increasingly important part of people's long-term commitment throughout their life-cycle, it must also assume the role as a self-directed life-long learning process, in view of the ever-changing and complicated financial environment.

• The Journal of the Korea Contents Association
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• v.16 no.1
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• pp.445-458
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• 2016

The purpose of this study is to develop indicators for assessing korean youth lifelong learning competency and to validate the structure of the competencies. To achieve this research aims, the indicators for assessing life-long learning competence were drawn by systemic literature review and they were validated and modified by expert review method and two surveys targeting youth. 28 youth experts participated in the expert review. Participants were 333 middle or high school students for the first survey and 791 middle or high school students for the second survey. As results, the 3 competencies and nine sub-competencies were developed: thinking(wholistic thinking, critical thinking, emotional thinking), intellectual tools use(language, mathematic and science, information and communication technology), learning adaptability(change capacity, intellectual curiosity, learning-direction). The results of this study will provide the fundamental guidelines for developing various activities and establishing youth policies related to korean youth life-long learning competency.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.303-306
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• 2006

유비쿼터스 컴퓨팅의 핵심은 네트워크 환경에 대한 고 가용성이라 할 수 있다. 이러한 사실은 사용자 컨텍스트(Context)가 반영된 서비스를 제공하기 위한 필수조건이 이미 갖추어져 있다는 것을 시사한다. 지금까지 상황인지(Context-Aware) 서비스를 위한 여러 응용들이 제시되어 왔지만, 동적으로 변화하는, 즉 예측하기 어려운 환경을 충분히 반영할 만큼의 유연성을 제공하지 못했다. 왜냐하면, 응용 태스크 시나리오가 시작단계부터 이미 정해져 있었기 때문이다. 여기에, 본 고는 평생동안 개인화된 태스크를 동적으로 생성, 제공할 수 있는 멀티 에이전트 시스템 구조를 제안하고자 한다. 평생 개인화 태스크(Life Long Personalized Task)는 끊임없이 변화하는 사용자의 행동패턴을 반영할 수 있도록, 동적으로 생성, 제공되는 태스크를 의미한다. 이는 태스크 시나리오가 컴파일 타임에 이미 결정되지 않고, 실행 시간 중에 자동으로 생성된다는 것을 의미한다. 이러한 유연성은 평생학습 엔진(Life Long Learning Engine)을 활용함으로써 가능하다. 이 엔진은 사용자의 행동패턴을 학습하며, 결과적으로 사용자 행동패턴 규칙들을 생성한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.123-125
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• 2022

In this paper, we introduce a system applied to long short-term memory using Yolo-pose. Using Yolo-pose from image data, data divided into daily life and falls are extracted and applied to LSTM for learning. In order to prevent overfitting, training is performed 8 to 2 validation and is represented by a confusion matrix. The result of Yolo-pose recorded 100% of both sensitivity and specificity, confirming that daily life and falls were well distinguished.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.119-130
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• 2022

Crime is a common social problem that affects the quality of life. As the number of crimes increases, it is necessary to build a model to predict the number of crimes that may occur in a given period, identify the characteristics of a person who may commit a particular crime, and identify places where a particular crime may occur. Data privacy is the main challenge that organizations face when building this type of predictive models. Federated learning (FL) is a promising approach that overcomes data security and privacy challenges, as it enables organizations to build a machine learning model based on distributed datasets without sharing raw data or violating data privacy. In this paper, a federated long short- term memory (LSTM) model is proposed and compared with a traditional LSTM model. Proposed model is developed using TensorFlow Federated (TFF) and the Keras API to predict the number of crimes. The proposed model is applied on the Boston crime dataset. The proposed model's parameters are fine tuned to obtain minimum loss and maximum accuracy. The proposed federated LSTM model is compared with the traditional LSTM model and found that the federated LSTM model achieved lower loss, better accuracy, and higher training time than the traditional LSTM model.

• Computers and Concrete
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• v.30 no.5
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• pp.301-310
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• 2022

Cement-based sensors have been widely used as structural health monitoring systems, however, their long-term sensing performance have not actively investigated. In this study, a deep learning-based methodology is adopted to predict the long-term piezoresistive properties of cement-based sensors. Samples with different multi-walled carbon nanotube contents (0.1, 0.3, and 0.5 wt.%) are fabricated, and piezoresistive tests are conducted over 10,000 loading cycles to obtain the training data. Time-dependent degradation is predicted using a modified long short-term memory (LSTM) model. The effects of different model variables including the amount of training data, number of epochs, and dropout ratio on the accuracy of predictions are analyzed. Finally, the effectiveness of the proposed approach is evaluated by comparing the predictions for long-term piezoresistive sensing performance with untrained experimental data. A sensitivity of 6% is experimentally examined in the sample containing 0.1 wt.% of MWCNTs, and predictions with accuracy up to 98% are found using the proposed LSTM model. Based on the experimental results, the proposed model is expected to be applied in the structural health monitoring systems to predict their long-term piezoresistice sensing performances during their service life.

• Journal of Korea Multimedia Society
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• v.25 no.8
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• pp.1233-1241
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• 2022

Tumors of the brain are the deadliest, with a life expectancy of only a few years for those with the most advanced forms. Diagnosing a brain tumor is critical to developing a treatment plan to help patients with the disease live longer. A misdiagnosis of brain tumors will lead to incorrect medical treatment, decreasing a patient's chance of survival. Radiologists classify brain tumors via biopsy, which takes a long time. As a result, the doctor will need an automatic classification system to identify brain tumors. Image classification is one application of the deep learning method in computer vision. One of the deep learning's most powerful algorithms is the convolutional neural network (CNN). This paper will introduce a novel deep learning structure and image gradient to classify brain tumors. Meningioma, glioma, and pituitary tumors are the three most popular forms of brain cancer represented in the Figshare dataset, which contains 3,064 T1-weighted brain images from 233 patients. According to the numerical results, our method is more accurate than other approaches.