• Journal of Information Processing Systems
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• v.18 no.1
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• pp.130-145
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• 2022

Games are widely used in many fields, but not all games are successful. Then what makes games successful? The question gave us the motivation of this paper, which is to identify critical factors for successful games with topic modeling technique. It is supposed that game reviews written by experts sit on abundant insights and topics of how games succeed. To excavate these insights and topics, latent Dirichlet allocation, a topic modeling analysis technique, was used. This statistical approach provided words that implicate topics behind them. Fifty topics were inferred based on these words, and these topics were categorized by stimulation-response-desiregoal (SRDG) model, which makes a streamlined flow of how players engage in video games. This approach can provide game designers with critical factors for successful games. Furthermore, from this research result, we are going to develop a model for immersive game experiences to explain why some games are more addictive than others and how successful gamification works.

• The Journal of Korean Medicine
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• v.29 no.5
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• pp.67-76
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• 2008

Objectives : Amnesia is theloss or impairment of memory, caused by physical injury, disease, drugs, or emotional trauma. Recently, the average life span is increasing, while at the same time, the incidence of dementia-like diseases in conjunction with amnesia are also increasing. Therefore learning and memory are very important issues in modern society. Ancient Korean physicians used several herbs to treat dementia and these herbal effects were described in Korean herbal books. Among them are some reports on several cognitive-enhancing herbs which have since been shown to improve dementia in recent pharmacological studies, such as Panax ginseng; however, the facilitatory effects of many Korean cognitive-enhancing herbs on learning and memory are limited. Learning and memory are essential requirements for every living organism in order to cope with environmental demands; cholinergic systems are known to be involved in learning and memory. Methods : In this study, the effects of Acori graminei rhizoma (AGR, 石菖蒲) on learning and memory were investigated by Morris water maze, eight-arm radial maze, and the effects on the central cholinergic system of rats injected with scopolamine. Results : In the water maze, the experimental animals were trained to find a platform in a fixed position for 6 days and then received a 60 sec probe trial in which the platform was removed from the pool on the 7th day. In the eight-arm radial maze, the animals were tested four times per day for 6 days. Scopolamine impaired performance of the maze tests and reduced activity of acetylcholinesterase (AchE) in the hippocampus, which is a marker for the central cholinergic system. There were significant reversals from the scopolamine-induced deficits on learning and memory in these tests, through daily administrations of AGR (100 mg/kg, p.o.) over 14 consecutive days. These treatments also reduced the loss of cholinergic activity in the hippocampus induced by scopolamine. Conclusions : These results demonstrated that AGR ameliorated learning and memory deficits by affecting the central acetylcholine system.

• Proceedings of the Safety Management and Science Conference
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• 2009.04a
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• pp.281-294
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• 2009

Recently the information system introduction and the application which use the computer are increasing. The efficient operation of information system helps corporations to improve productivity, customer service and corporate competitive power. SaaS(Software as a Service), which is the developed type of outsourcing in the area of information technology, is to use standardized and packaged application by hosting from the outside of enterprise. SaaS is not developed yet as much as people's interest about that in the initial stage, but its related technology and service capacity are accumulated after repeated trial and error, and it's ready to activate the industry. In the area of information system, studies on the measurement of service quality were followed. But there is little study on service quality measurement in the field of SaaS(Software as a Service). The purpose of this study was to divides the SaaS with e-SERVQUAL and it consider the relationship with the perceived recognition and the usage intention. According to this, variables of traditional research were rejected because SaaS is not developed yet in Korea. But information had a strong effect on perceived recognition. Therefore, business related with in SaaS must have provided a correct information about various applications.

• Information Systems Review
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• v.4 no.1
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• pp.89-110
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• 2002

Today, many universities are confronted with the changing education paradigm such as e-Learning, CBT(Computer-based Training), Virtual University. Particularly, the Virtual University is now in the countrys educational mainstream as a legitimate, potentially standards-setting educational environment. These streams are certainly a new opportunity or threat to our universities. To overcome this problem, we should think this as strategic, and should implement IT-based Virtual University System to which computer and network technology is main edge. So, we think that the Virtual University System is SIS(Strategic Information System) which support universitys future education strategies. We proposed a planning framework for the Virtual University System. The framework which is based on the IS planning methodology is composed of such as environment analysis, requirement analysis of the system, strategic roles and objectives setting, scenario analysis of budget and revenue. To define the strategic roles and objectives of the system, we surveyed it on the side of instructors. We proposed five factors, which are to (1) improve competitiveness (2) reduce cost and secure profit (3) enhance education services (4) change the future education model (5) decrease dysfunctions of virtual education model.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.308-316
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• 2021

During the past two years, the education systems in the world witnessed unprecedented turmoil due to the coronavirus (Covid-19) pandemic, as most schools and universities in the world closed their doors to more than 1.5 billion students, or more than 90% of the total learners, according to recent figures issued by the UNESCO Institute for Statistics. Education experts have agreed that post- coronavirus education will not be the same as before, especially with the increasing use of modern technology in education. One of the most important new patterns with a structure digital in education is distance education, this style has been used, in many countries of the world, as an alternative to traditional education, since the beginning of the pandemic. In Saudi Arabia, this type of education has been used in all educational institutions, starting from kindergarten until the postgraduate level, as an alternative to face-to-face education to preserve the health and safety of students and workers in educational institutions. This study aimed to explore the level of satisfaction of preparatory year students on distance learning in their first year of study at Umm Al-Qura University. The findings of this study showed that students in the preparatory year were satisfied with their online learning experience. In addition, the results revealed that there was no effect for gender and location of study on students' level of satisfaction. Saudi universities should continue to work to create a suitable learning environment for students at the e-learning level.

• Nuclear Engineering and Technology
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• v.55 no.12
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• pp.4607-4616
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• 2023

We implement machine learning regression models to predict peak pressures of primary and secondary systems, a major safety concern in Loss Of Condenser Vacuum (LOCV) accident. We selected the Multi-dimensional Analysis of Reactor Safety-KINS standard (MARS-KS) code to analyze the LOCV accident, and the reference plant is the Korean Optimized Power Reactor 1000MWe (OPR1000). eXtreme Gradient Boosting (XGBoost) is selected as a machine learning tool. The MARS-KS code is used to generate LOCV accident data and the data is applied to train the machine learning model. Hyperparameter optimization is performed using a simulated annealing. The randomly generated combination of initial conditions within the operating range is put into the input of the XGBoost model to predict the peak pressure. These initial conditions that cause peak pressure with MARS-KS generate the results. After such a process, the error between the predicted value and the code output is calculated. Uncertainty about the machine learning model is also calculated to verify the model accuracy. The machine learning model presented in this paper successfully identifies a combination of initial conditions that produce a more conservative peak pressure than the values calculated with existing methodologies.

• Journal of the Korean Society of Systems Engineering
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• v.17 no.2
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• pp.91-97
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• 2021

User interface for cancer classification system is a software application with clinician's friendly tools and functions to diagnose cancer from pathology images. Pathology evolved from manual diagnosis to computer-aided diagnosis with the help of Artificial Intelligence tools and algorithms. In this paper, we explained each block of the project life cycle for the implementation of automated breast cancer classification software using AI and machine learning algorithms to classify normal and invasive breast histology images. The system was designed to help the pathologists in an automatic and efficient diagnosis of breast cancer. To design the classification model, Hematoxylin and Eosin (H&E) stained breast histology images were obtained from the ICIAR Breast Cancer challenge. These images are stain normalized to minimize the error that can occur during model training due to pathological stains. The normalized dataset was fed into the ResNet-34 for the classification of normal and invasive breast cancer images. ResNet-34 gave 94% accuracy, 93% F Score, 95% of model Recall, and 91% precision.

• Asia pacific journal of information systems
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• v.29 no.2
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• pp.181-202
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• 2019

The purpose of this study is to explore the effect of different types of simultaneous presentation (i.e., reviewer information, textual and visual content, and similarity between textual-visual contents) on review usefulness and review enjoyment in online restaurant reviews (ORRs), as they are interrelated yet have rarely been examined together in previous research. By using Latent Dirichlet Allocation (LDA) topic modeling and state-of-the-art machine learning (ML) methodologies, we found that review readability in textual content and salient objects in images in visual content have a significant impact on both review usefulness and review enjoyment. Moreover, similarity between textual-visual contents was found to be a major factor in determining review usefulness but not review enjoyment. As for reviewer information, reputation, expertise, and location of residence, these were found to be significantly related to review enjoyment. This study contributes to the body of knowledge on ORRs and provides valuable implications for general users and managers in the hospitality and tourism industries.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.4
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• pp.350-357
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• 1991

A speech recognition system based on a neural network, which can be used for telephon number services was tested. Because in Korea two different cardinal number systems, a koreanic one and a sinokoreanic one, are in use, it is necessary that the used systems is able to recognize 22 discret words. The structure of the neural network used had two layers, also a structure with 3 layers, one hidden layreformed of each 11, 22 and 44 hidden units was tested. During the learning phase of the system the so called BP-algorithm (back propagation) was applied. The process of learning can e influenced by using a different learning factor and also by the method of learning(for instance random or cycle). The optimal rate of speaker independent recognition by using a 2 layer neural network was 96%. A drop of recognition was observed by overtraining. This phenomen appeared more clearly if a 3 layer neural network was used. These phenomens are described in this paper in more detail. Especially the influence of the construction of the neural network and the several states during the learning phase are examined.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.268-271
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• 2010

본 연구의 목적은 E-NIE 수업을 진행하는데 있어 기존 연구의 문제점과 개선점을 조사하고 수업자료선택, 수업진행, 발전방향에 관한 설문조사 결과를 토대로 멀티미디어 자료 검색 방법과 온라인에서 신문활용학습이 효율적으로 이루어질 수 있는 E-NIE 이러닝 시스템 발전 방안을 모색하기 위한 것이다. E-NIE에 뉴스 표준인 NewsML과 교육정보 표준인 KEM 그리고 학사관리운영플랫폼 LMS를 접목해 멀티미디어 자료와 교과 및 단원을 구조화해 표준화된 교육용 멀티미디어 아카이브를 구축하고 온라인으로 진단 형성 수행 평가, 토론학습, 협동학습 등이 가능하고 학생들의 성적과 진도는 물론 교수학습의 전반적인 과정을 통합적으로 운영 관리할 수 있는 E-NIE 이러닝 시스템을 제안한다.