• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.87-106
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• 2024

Vehicle-to-Home (V2H) and Home Centralized Photovoltaic (HCPV) systems can address various energy storage issues and enhance demand response programs. Renewable energy, such as solar energy and wind turbines, address the energy gap. However, no energy management system is currently available to regulate the uncertainty of renewable energy sources, electric vehicles, and appliance consumption within a smart microgrid. Therefore, this study investigated the impact of solar photovoltaic (PV) panels, electric vehicles, and Micro-Grid (MG) storage on maximum solar radiation hours. Several Deep Learning (DL) algorithms were applied to account for the uncertainty. Moreover, a Reinforcement Learning HCPV (RL-HCPV) algorithm was created for efficient real-time energy scheduling decisions. The proposed algorithm managed the energy demand between PV solar energy generation and vehicle energy storage. RL-HCPV was modeled according to several constraints to meet household electricity demands in sunny and cloudy weather. Simulations demonstrated how the proposed RL-HCPV system could efficiently handle the demand response and how V2H can help to smooth the appliance load profile and reduce power consumption costs with sustainable power generation. The results demonstrated the advantages of utilizing RL and V2H as potential storage technology for smart buildings.

• Journal of Korean Home Economics Education Association
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• v.22 no.3
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• pp.163-188
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• 2010

This study set out to develop and evaluate an educational program for the Clothing Life of Home Economics through the theme-based integrated approach develop integrated thinking abilities for solving everyday problems. For those purposes, it selected a couple of themes in the area of Clothing Life toward which the theme-based integrated approach could be develop and evaluate an educational program. The developed program was applied and assessed in total 28 hours of field lessons given to eighth graders attending B Middle School in Busan Metropolitan City. The analysis stage involved an exploration into programs related to an integrated approach to other subjects; the design stage identification of program types; and the development stage theme selection according to the selection criteria. The previous studies were analyzed along with the Technology and Home Economics textbooks to select a theme. two themes "Clothing Management" and "Fabrics(Materials)" were selected after discussing with the students on the Messenger and with a group of experts. Then content was organized and composed around the themes by discussing connections with other subjects. There were three evaluation; one by experts, another through preliminary lessons, and the other through field lessons. Following the research procedure, a theme-based integrated program was developed for the two selected themes. It contained total 49 and 32 learning materials for "Clothing Management" and "Fabrics(Materials)," respectively. Those learning materials were comprised of experiments and practices according to the nature of the themes. Each program consisted of the goals, learning content, content organization chart, learning activities, and evaluation; learning activities experiences, practice and experiment activities, self-directed activities and problem-solving processes; and evaluations self-evaluation, teacher evaluation, peer evaluation, portfolio, and experiment reports. The program was assessed three times. The first and second evaluation results found that the program was well compatible with the current needs, was properly organized to give lessons through integration with other subjects, and continuously maintained the students' interest. They, however, requested that there should be detailed explanations about each part of the program content. In the third evaluation done by the students during field lessons, 60% of them said that the program was fun and its content was easy to understand, that they realized a theme could be connected to several other subjects, and that the program could be applied to actual life. The educational program through the theme-based integrated approach is significant in that it is an educational program for the area of Clothing Life and tries an integrated approach. It helped the students not only gather knowledge in an integrated manner, but put it to practical uses to solve various problems they faced in actual life by creatively changing integrated knowledge. The study will be hopefully used by many teachers so that the students solve problems based on the ability of integrating various knowledges organically.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.4
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• pp.361-368
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• 2022

An indoor navigation system that utilizes long-term evolution (LTE) signals has the benefit of no additional infrastructure installation expenses and low base station database management costs. Among the LTE signal measurements, received signal strength (RSS) is particularly appealing because it can be easily obtained with mobile devices. Propagation channel models can be used to estimate the position of mobile devices with RSS. However, conventional channel models have a shortcoming in that they do not discriminate between line-of-sight (LOS) and non-line-of-sight (NLOS) conditions of the received signal. Accordingly, a previous study has suggested separated LOS and NLOS channel models. However, a method for determining LOS and NLOS conditions was not devised. In this study, a machine learning-based LOS/NLOS classification method using RSS measurements is developed. We suggest several machine-learning features and evaluate various machine-learning algorithms. As an indoor experimental result, up to 87.5% classification accuracy was achieved with an ensemble algorithm. Furthermore, the range estimation accuracy with an average error of 13.54 m was demonstrated, which is a 25.3% improvement over the conventional channel model.

• Asia pacific journal of information systems
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• v.17 no.1
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• pp.33-58
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• 2007

Quiet often, an organization tries to grapple with inconsistent and partial information to generate relevant information to support decision making and action. As such, an organization scans the environment interprets scanned data, executes actions, and learns from feedback of actions, which boils down to computational interpretations and learning in terms of machine learning, statistics, and database. The ExOM proposed in this paper is geared to facilitate such knowledge discovery found in large databases in a most flexible manner. It supports a broad range of learning and classification styles and integrates them with traditional database functions. The learning and classification components of the ExOM are tightly integrated so that learning and classification of objects is less burdensome to ordinary users. A brief sketch of a strategy as to the expressiveness of terminological language is followed by a description of prototype implementation of the learning and classification components of the ExOM.

• The Journal of the Korea Contents Association
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• v.5 no.1
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• pp.9-17
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• 2005

In this paper we developed e-Leaning system based on open source software. We selected the Moodle that after compared the open source learning management systems. Moodle is LAMP(Linux, Apache, MySQL, PHP) based course management system (CMS), a software package designed to help educators create quality online courses. One of the main advantages of Moodle over other systems is a strong grounding in social constructionist pedagogy. Also we integrated Moodle and legacy systems such as streaming service, webhard service, and short message service. The system operated during one semester at college using blended learning model. We had obtained showed that the students had almost all scored quite highly as preferred learning environment through COLLES(Constructivist On-Line Learning Environment Survey) and ATTLS(Attitudes to Thinking and Learning Survey). Therefore this research showed that open source based e-Loaming system is stable and possible.

• Journal of Information Technology Application
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• v.1
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• pp.173-211
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• 1999

The task of classification permeates all walks of life, from business and economics to science and public policy. In this context, nonlinear techniques from artificial intelligence have often proven to be more effective than the methods of classical statistics. The objective of knowledge discovery and data mining is to support decision making through the effective use of information. The automated approach to knowledge discovery is especially useful when dealing with large data sets or complex relationships. For many applications, automated software may find subtle patterns which escape the notice of manual analysis, or whose complexity exceeds the cognitive capabilities of humans. This paper explores the utility of a collaborative learning approach involving integrated models in the preprocessing and postprocessing stages. For instance, a genetic algorithm effects feature-weight optimization in a preprocessing module. Moreover, an inductive tree, artificial neural network (ANN), and k-nearest neighbor (kNN) techniques serve as postprocessing modules. More specifically, the postprocessors act as second0order classifiers which determine the best first-order classifier on a case-by-case basis. In addition to the second-order models, a voting scheme is investigated as a simple, but efficient, postprocessing model. The first-order models consist of statistical and machine learning models such as logistic regression (logit), multivariate discriminant analysis (MDA), ANN, and kNN. The genetic algorithm, inductive decision tree, and voting scheme act as kernel modules for collaborative learning. These ideas are explored against the background of a practical application relating to financial fraud management which exemplifies a binary classification problem.

• The Journal of Korean Association of Computer Education
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• v.6 no.3
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• pp.99-108
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• 2003

This paper indicates limitations of the existing VOD(Video on Demand)-based on-line education systems and presents the design and implementation of Education on Demand (EOD) system as an alternative. EOD system is based on meta information expressed in XML and component technology. Overall system consists of authoring tool. contents server, learning policy system and contents viewer. which are utilized throughout the learning contents life-cycle. EOD system enables automated contents management using meta information exchange methodology that is conformant to the SCORM meta data presentation scheme. In addition, integrated management of interaction and feedback information along with the learning policy system provides customized learning guide for each individual learner. With the development of EOD system, this paper discusses about advanced on-line education system which surpasses existing content-providing-only systems.

• The Journal of the Korea Contents Association
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• v.14 no.7
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• pp.18-28
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• 2014

With the reformation of organization and function of local office of education in 2010, consulting-supervision is introduced to schools as a system for education reform to improve the quality of school education. However, a dedicated on-line portal system that can provide integrated management on the functionalities of consulting-supervision has not been implemented yet. To successfully operate consulting-supervision in schools, it is also needed to provide an on-line consultant education system, that can support teachers to train themselves as a supervision-consultant. In this paper, we introduce an on-line consultant training system that provides various learning activity tools for consultant training based on Learning Activity Management System(LAMS) and Action Learning. The system consists of Management stage, Analysis stage, Solution stage, and Action stage for the empowerment of consultants' expertises, and is named as MASA. Brain-writing, SWOT(Strengths, Weaknesses, Opportunities, and Threads) analysis, 5Whys, decision grid, PMI(Plus, Minus, Interesting), and black chart techniques were developed in MASA as learning activity tools for consultant training.

• Asia pacific journal of information systems
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• v.9 no.3
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• pp.127-142
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• 1999

There have been strong arguments that the best organizational type for the information society is a network organization which is intelligent and learning-oriented as well as has problem solving capacities rather than a traditional passive organization which strictly follows standard operating procedures. In this perspective, integrated information work environment emerges as attractive work environment for the 21st century. Integrated information work environment is defined as an integrated electronic environment that is available to and readily accessible be each employee and is structured to provide immediate, individualized on-line access to the full range of information, software, guidance, advice and assistance, data, images, tools, and assessment and monitoring systems to permit job performance with minimal support and intervention by others. Case study was performed to measure the productivity improvement by implementing integrated information work environment in life insurance company. The results show that there is a number of indications of strong work productivity improvements.

• Journal of Intelligence and Information Systems
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• v.3 no.1
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• pp.31-45
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• 1997

To date, research on data mining has focused primarily on individual techniques to su, pp.rt knowledge discovery. However, the integration of elementary learning techniques offers a promising strategy for challenging a, pp.ications such as forecasting nonlinear processes. This paper explores the utility of an integrated a, pp.oach which utilizes a second-order learning process. The a, pp.oach is compared against individual techniques relating to a neural network, case based reasoning, and induction. In the interest of concreteness, the concepts are presented through a case study involving the prediction of network traffic for video-on-demand.