• KIEAE Journal
• /
• v.17 no.5
• /
• pp.95-100
• /
• 2017

Purpose: The purpose of this study is to investigate the prior art based on deep learning to objectively calculate the metabolic rate which is the subjective factor for the PMV optimum control and to make a plan for future research based on this study. Methods: For this purpose, the theoretical and technical review and applicability analysis were conducted through various documents and data both in domestic and foreign. Results: As a result of the prior art research, the machine learning model of artificial neural network and deep learning has been used in various fields such as speech recognition, scene recognition, and image restoration. As a representative case, OpenCV Background Subtraction is a technique to separate backgrounds from objects or people. PASCAL VOC and ILSVRC are surveyed as representative technologies that can recognize people, objects, and backgrounds. Based on the results of previous researches on deep learning based on metabolic rate for occupational metabolic rate, it was found out that basic technology applicable to occupational metabolic rate calculation technology to be developed in future researches. It is considered that the study on the development of the activity quantity calculation model with high accuracy will be done.

• Management & Information Systems Review
• /
• v.34 no.1
• /
• pp.51-63
• /
• 2015

This study investigated how presence will affect the user's trust in educational serious game. To achieve our research purposes, we divide presence into two parts: virtual presence and social presence and identify the relationship between trust and trustworthiness. and also, we separate out trust such as trust in learning and trust in fun according to users purposes. We conduct the survey using the english serious game for university student. The results show that presence significantly influence on trustworthiness and also trustworthiness effect on trust in learning and fun.

• The Korean Journal of Physiology and Pharmacology
• /
• v.14 no.5
• /
• pp.345-352
• /
• 2010

The present study was undertaken to explore the potential of erythropoietin in memory deficits of mice. Memory impairment was produced by scopolamine (0.5 mg/kg, $i.p.$) and intracerebroventricular streptozotocin (i.c.v STZ, 3 mg/kg, $10{\mu}l$, $1^{st}$ and $3^{rd}$ day) in separate groups of animals. Morris water-maze test was employed to assess learning and memory. The levels of brain thio-barbituric acid reactive species (TBARS) and reduced glutathione (GSH) were estimated to assess degree of oxidative stress. Brain acetylcholinesterase enzyme (AChE) activity was also measured. Scopolamine/streptozotocin administration induced significant impairment of learning and memory in mice as indicated by marked decrease in Morris water-maze performance. Scopolamine/streptozotocin administration also produced a significant enhancement of brain AChE activity and brain oxidative stress (an increase in TBARS and a decrease in GSH) levels. Treatment of erythropoietin (500 and 1,000 IU/Kg i.p.) significantly reversed scopolamine- as well as streptozotocin-induced learning and memory deficits along with attenuation of those-induced rise in brain AChE activity and brain oxidative stress levels. It may be concluded that erythropoietin exerts a beneficial effect in memory deficits of mice possibly through its multiple actions including potential anti-oxidative effect.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.30 no.6C
• /
• pp.490-496
• /
• 2005

In this paper, we propose a self-constructed clustering algorithm based on inference information of the fuzzy model. This method makes it possible to automatically detect and optimize the number of cluster and parameters by using input-output data. The propose method improves the performance of clustering by extended supervised learning technique. This technique uses the output information as well as input characteristics. For effect the similarity measure in clustering, we use the TSK fuzzy model to sent the information of output. In the conceptually, we design a learning method that use to feedback the information of output to the clustering since proposed algorithm perform to separate each classes in input data space. We show effectiveness of proposed method using simulation than previous ones

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.38 no.5
• /
• pp.407-414
• /
• 2020

SVM (Support vector machine) analysis was performed after applying a deep learning technique based on an Inception-based model (GoogLeNet). The accuracy of automatic image classification was analyzed using an SVM with multiple virtual grid sizes. Six classes were selected from a standard land cover map. Cars were added as a separate item to increase the classification accuracy of roads. The virtual grid size was 2-5 m for natural areas, 5-10 m for traffic areas, and 10-15 m for building areas, based on the size of items and the resolution of input images. The results demonstrate that automatic classification accuracy can be increased by adopting an integrated approach that utilizes weighted virtual grid sizes for different classes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2014.05a
• /
• pp.867-870
• /
• 2014

Currently a number of universities and other educational institutions in the e-learning education system being implemented. Also that there is a demand. However, existing e-learning system has many problems. First, the theory of how the university -centered education and training institutions to adopt e-learning system has become the biggest obstacle. In addition, students can not engage the problem of a one-way lecture. In this paper, the theory -oriented and practice to overcome the one-way river systems programming language will develop e-learning content. Using socket communication and multi-threaded server-side Web browser on the client side through the compiler without installing a separate application installation and environmental learning environment can be unrestricted. Hands- content programming language allows the learner to direct the client-side source code in a web browser by entering the lecture is leading the way. For learners to enter the source code compiled to run on the server side, the compiler provides the learner results. Hands- because the future e-learning content development in e-learning systems will be a major contribution to.

• Convergence Security Journal
• /
• v.22 no.3
• /
• pp.25-32
• /
• 2022

Recently, the image processing industry has been activated as deep learning-based technology is introduced in the image recognition and detection field. With the development of deep learning technology, learning model vulnerabilities for adversarial attacks continue to be reported. However, studies on countermeasures against poisoning attacks that inject malicious data during learning are insufficient. The conventional countermeasure against poisoning attacks has a limitation in that it is necessary to perform a separate detection and removal operation by examining the training data each time. Therefore, in this paper, we propose a technique for reducing the attack success rate by applying modifications to the training data and inference data without a separate detection and removal process for the poison data. The One-shot kill poison attack, a clean label poison attack proposed in previous studies, was used as an attack model. The attack performance was confirmed by dividing it into a general attacker and an intelligent attacker according to the attacker's attack strategy. According to the experimental results, when the proposed defense mechanism is applied, the attack success rate can be reduced by up to 65% compared to the conventional method.

• The Journal of Korean Academic Society of Nursing Education
• /
• v.7 no.1
• /
• pp.94-112
• /
• 2001

The main purpose of this study was to investigate the effectiveness of a standardized patients managed instruction program for a fundamentals of nursing. The standardized patients managed instruction was evaluated by using a quasi-experimental, nonequivalent control group posttest design with two separate classes of sophomore students attending fundamentals of nursing classes at one baccaleureate nursing school in Korea. Control group was taught by traditional lecture/model instruction and experimental group was taught by standardized patient managed instruction. Data were collected from December, 1999 to July, 2000 using checklist developed by researcher on following areas; clinical nursing performance, communication skills, and learning motivation. There were 36 students in the experimental group and 40 students in the control group. Data analysis was done using SPSS WINDOW. The results were summarized as follows ; 1. Clinical nursing performances were evaluated by change position, back care and hot bag apply. The total score was statistically significant higher in the experimental group than the control group(t=3.325, p=.000). Thus hypothesis 1 was supported. 2. Communication skill was evaluated by professional attitude and ability to explain to patients. There was a statistically significant difference between the experimental group and the control group (t=4.232, p=.000). Thus hypothesis 2 was supported. 3. Learning motivation was evaluated by self-reported questionnaires. There was statistically a significant difference between the experimental group and the control group(t=3.024, p=.004). Thus hypothesis 3 was supported. In conclusion, this study suggests that standardized patients managed instruction is an effective learning method to nursing students. By utilizing a standardized patient managed instruction, learning can proceed in a more relaxed environment and reduce the risks to patients because student inexperience are avoided. It is recommended to develop more standardized patients cases for wider areas of nursing educational and evaluate the program with more students using logitudinal method.

• Journal of Advanced Navigation Technology
• /
• v.21 no.4
• /
• pp.365-370
• /
• 2017

This study analyze correlation between weekdays data and special days data of different power demand patterns, and builds a separate data set, and suggests ways to reduce power demand prediction error by using deep learning network suitable for each data set. In addition, we propose a method to improve the prediction rate by adding the environmental elements and the separating element to the meteorological element, which is a basic power demand prediction elements. The entire data predicted power demand using LSTM which is suitable for learning time series data, and the special day data predicted power demand using DNN. The experiment result show that the prediction rate is improved by adding prediction elements other than meteorological elements. The average RMSE of the entire dataset was 0.2597 for LSTM and 0.5474 for DNN, indicating that the LSTM showed a good prediction rate. The average RMSE of the special day data set was 0.2201 for DNN, indicating that the DNN had better prediction than LSTM. The MAPE of the LSTM of the whole data set was 2.74% and the MAPE of the special day was 3.07 %.

• Journal of Internet Computing and Services
• /
• v.16 no.3
• /
• pp.33-41
• /
• 2015

In this paper, the simplification procedure of Karnaugh Map, which is essential to design digital logic circuits, was implemented as web-based educational Java applets. The learners will be able to experience interesting learning process by executing the proposed Java applets. In addition, since the proposed Java applets were designed to contain educational technologies by step-by-step procedure, the maximization of learning efficiency can be obtained. The learners can make virtual experiments on the simplification of digital logic circuits by clicking on some buttons or filling out some text fields. Furthermore, the Boolean expression and its schematic diagram occurred in the simplification process will be displayed on the separate frame so that the learners can learn effectively. The schematic diagram enables them to check out if the logic circuit is correctly connected or not. Finally, since the simplification algorithm used in the proposed Java applet is based on the modified Quine-McCluskey minimization technique, the proposed Java applets will show more encouraging result in view of learning efficiency if it is used as assistants of the on-campus offline class.