• Journal of the Korea Furniture Society
• /
• v.24 no.3
• /
• pp.247-256
• /
• 2013

A dormitory is the most important compound space to college students who have to live with others. Also, for the students living in the boarding area, the dorm space can be the space for learning, exchanges and cultural. These Housing environment is a public space, so this is based on Universal Design. However, the 1970s-built dormitory space for the current user is narrow and not right for furniture standard. In this study, in order to compensate for these problems, the design directions are based on the previous studies - Park, Young-Soon, 2008, 'A Proposal on Dormitory Furniture Design for University Students.' Based on the previous study, the type of variable design is designed for desks, bookcases, beds, wardrobes, and other cabinets as representative household types. Furthermore, these furnitures are assembled and transformed depend on the dormitory space for single, double and four students. The furniture assembly system and arrangement module are presented in the direction of three kinds of designs. Therefore, three meaning of this study are the development of design to be used each item, the realization of custom furniture for space and presenting variable design module.

• International journal of advanced smart convergence
• /
• v.10 no.3
• /
• pp.131-142
• /
• 2021

Recently, there has been an active service that provides customized news to news subscribers. In this study, we intend to design a customized news service system through Deep Learning-based Social Network Service (SNS) activity analysis, applying real news and avoiding fake news. In other words, the core of this study is the study of delivery methods and delivery devices to provide customized news services based on analysis of users, SNS activities. First of all, this research method consists of a total of five steps. In the first stage, social network service site access records are received from user terminals, and in the second stage, SNS sites are searched based on SNS site access records received to obtain user profile information and user SNS activity information. In step 3, the user's propensity is analyzed based on user profile information and SNS activity information, and in step 4, user-tailored news is selected through news search based on user propensity analysis results. Finally, in step 5, custom news is sent to the user terminal. This study will be of great help to news service providers to increase the number of news subscribers.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.18 no.1
• /
• pp.19-24
• /
• 2023

In traditional fish farming way, the workers have to observe all of the pools every time and every day to feed at the right timing. This method causes tremendous stress on workers and wastes time. To solve this problem, we implemented an automatic detection system for feeding time using deep neural network. The detection system consists of two steps: classification of the presence or absence of feed and checking DO (Dissolved Oxygen) of the pool. For the classification, the pretrained ResNet18 model and transfer learning with custom dataset are used. DO is obtained from the DO sensor in the pool through HTTP in real time. For better accuracy, the next step, checking DO proceeds when the result of the classification is absence of feed several times in a row. DO is checked if it is higher than a DO reference value that is set by the workers. These actions are performed automatically in the UI programs developed with LabVIEW.

• ETRI Journal
• /
• v.45 no.5
• /
• pp.847-861
• /
• 2023

Dynamic object detection is essential for ensuring safe and reliable autonomous driving. Recently, light detection and ranging (LiDAR)-based object detection has been introduced and shown excellent performance on various benchmarks. Although LiDAR sensors have excellent accuracy in estimating distance, they lack texture or color information and have a lower resolution than conventional cameras. In addition, performance degradation occurs when a LiDAR-based object detection model is applied to different driving environments or when sensors from different LiDAR manufacturers are utilized owing to the domain gap phenomenon. To address these issues, a sensor-fusion-based object detection and classification method is proposed. The proposed method operates in real time, making it suitable for integration into autonomous vehicles. It performs well on our custom dataset and on publicly available datasets, demonstrating its effectiveness in real-world road environments. In addition, we will make available a novel three-dimensional moving object detection dataset called ETRI 3D MOD.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.28 no.4
• /
• pp.847-857
• /
• 2018

As the number of malicious code increases steeply, cyber attack victims targeting corporations, public institutions, financial institutions, hospitals are also increasing. Accordingly, academia and security industry are conducting various researches on malicious code detection. In recent years, there have been a lot of researches using machine learning techniques including deep learning. In the case of research using Convolutional Neural Network, ResNet, etc. for classification of malicious code, it can be confirmed that the performance improvement is higher than the existing classification method. However, one of the characteristics of the target attack is that it is custom malicious code that makes it operate only for a specific company, so it is not a form spreading widely to a large number of users. Since there are not many malicious codes of this kind, it is difficult to apply the previously studied machine learning or deep learning techniques. In this paper, we propose a method to classify malicious codes when the amount of samples is insufficient such as targeting type malicious code. As a result of the study, we confirmed that the accuracy of 97% can be achieved even with a small amount of data by applying the Memory Augmented Neural Networks model.

• Korean Business Review
• /
• v.22 no.1
• /
• pp.77-101
• /
• 2009

The main purpose of this study is to assess the effect of using Balanced Scorecard, and relationship among learning and growth performance, internal business performance, customer performance, financial performance, and business performance. To achieve this study, theoretical and empirical studies related to Balanced Scorecard were carried out simultaneously. A field survey was undertaken through questionnaire sampling a population of construction firms. The established hypotheses related to Balanced Scorecard and organizational performance were verified by the paired-t test analysis using SPSS. The result of this research are as follows : First, BSC firm's learning and growth performance are higher than those of before BSC adopting firms significantly. Second, BSC firm's internal business performance level is higher than that of before BSC firm's significantly. Third, BSC firm's customer performance level is higher than that of before BSC firm's significantly. Fourth, BSC firm's financial performance level is higher than that of before BSC firm's significantly. Fifth, BSC firm's Business performance level is higher than that of before BSC firm's significantly. This study contributes to the BSC research by being the study focus on the BSC at the general indicators and provides evidence that may help understanding the possible relationship between BSC adoption and improvement of organizational performance. There are some limitations, however, of this study. The result are based on a cross sectional sample of construction firms, which may not be reflective of the entire population.

• The Journal of Korean Institute for Practical Engineering Education
• /
• v.3 no.1
• /
• pp.76-83
• /
• 2011

In this paper we suggest an effective teaching plan for measurement engineering by utilizing the NI-ELVIS(National Instrument Educational Laboratory Virtual Instrumentation Suite). ELVIS is a development platform for LabVIEW-based design and prototyping environment. It consists of LabVIEW-based virtual instruments, a multifunctional data acquisition device, and a custom-designed benchtop workstation and prototyping board. Therefore it can replace the expensive instruments for the effective education in the area of electrical engineering. This platform can be applicable for the sensor instrumentation engineering study, though it is a multidisciplinary learning including electrical engineering, sensor technology, signal processing and data analysis. We hope this approach can be used for the other educational area related the electrical experimental education.

• Hwankyungkyoyuk
• /
• v.12 no.1
• /
• pp.64-75
• /
• 1999

The goals of moral education according to the 7th educational curriculum are (1) to learn the basic life custom and ethical norms necessary to desirable life, (2) to develop the judgment to solve desirably and practically the ethical matters in daily life, (3) to develop the sound citizenship, national identity and consciousness, and the consciousness of world peace and mankind's mutual prosperity, and (4) to develop the ethical propensity to practice the ideal and principle of life systematically Based on the goals in the above, the following can be established as goals of environmental education possible: (1) to learn judgment to solve practically the environmental problems in the society with their ethical understanding, and (2) to recognize that environmental consciousness is the basic necessity of sound citizenship and national identity and consciousness, and mankind's mutual prosperity, and to have attitudes to practice environmental preservation in daily life. Like these, the intellectual aspect, the affective aspect, and the active aspect can be established in the environmental education in the ethics education keeping their balance. In order to achieve its goals, the contents of ethics subject are organized largely with 4 domains: (1) individual life, (2) home life, life with neighbors, and school life, (3) social life, and (4) national life. Among these, environmental education is mainly included in the domain of social life. These contents concerning environmental education take 22 (32.4%) out of the whole 68 teaching factors which are taught in the ethics subject from the 3rd grade to 10th grade. These 22 environmental teaching factors are mainly related to environmental ethics, environmental preservation and measures, and sound consumption life. Classified according to each goal, the environmental contents in the 7th curriculum for ethics subject put emphasis on environmental value and attitudes, action and participation, and information and knowledge. Therefore, the recommendable teaching and learning method for the environmental education in ethics subject is to motivate students' practice or to make them practice in person. For example, role-play model, value-conflict model, group study model can be applied according to the topics of environmental education.

• Smart Media Journal
• /
• v.7 no.2
• /
• pp.47-53
• /
• 2018

Along with the development of information and communication technology, smart education that can learn without restrictions of time, place and equipment is activated even in the field of education. Although smart education is provided with content-based training solutions, construction of a system that grasps individual characteristics of learners and provides personalized learning is relatively weak. The activity of free choice is an important play activity of early childhood education, but it is not implemented efficiently by relying on the clinical observation of the teacher. If the IoT(Internet of Things) technology based on Hyper-Connected is applied to free-choice activities, it is possible to provide the child's personalized activity type and play-form analysis based on objective and stylized data. In this paper, we design and implement a system to monitor the child's activity of free choice by building an IoT environment that is based on open source hardware. The proposed system provides children's activity information as objective data and will be used as teacher's work mitigation and custom training material for each child.

• KIPS Transactions on Software and Data Engineering
• /
• v.11 no.10
• /
• pp.427-436
• /
• 2022

Korea Trade-Investment Promotion Agency (KOTRA) annually publishes the trade data in South Korea under the guidance of the Ministry of Trade, Industry and Energy in South Korea. The trade data usually contains Gross domestic product (GDP), a custom tariff, business score, and the price of export items in previous and this year, with regards to the trading items and the countries. However, it is challenging to figure out the meaningful insight so as to predict the future price on trading items every year due to the significantly large amount of data accumulated over the several years under the limited human/computing resources. Within this context, this paper proposes a multi layer perception that can predict the future price of potential trading items in the next year by training large amounts of past year's data with a low computational and human cost.