• 수산해양교육연구
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• 제23권1호
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• pp.116-125
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• 2011

In this study, a survey research was conducted on government employees in Busan Metropolitan City to identify the influence of cyber education factors (learning factor, learner factor, and learning system factor) on the preference for government employee cyber education offered by the government always learning system. Analyzed results, recognition of learning factor, learner factor, and always learning system were shown to have significant influence on the preference for cyber education, but no indication of influence by always learning support. This study intends to assist stimulating voluntary participation in cyber education and active commitment in learning activities through improving learning effect and fortifying convenient informatization education, with regard to activation of cyber education and improved preference for cyber education.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.292-297
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• 2001

In writing learning as a second/foreign language, a learner has to acquire not only lexical and syntactical knowledge but also the skills to choose suitable words for content which s/he is interested in. A learning system should extrapolate learner\\`s intention and give example phrases that concern with the content in order to support this on the system. However, a learner cannot always represent a content of his/her desired phrase as inputs to the system. Therefore, the system should be equipped with a diagnosis function for learner\\`s intention. Additionally, a system also should be equipped with an analysis function to score similarity between learner\\`s intention and phrases which is stored in the system on both syntactic and idiomatic level in order to present appropriate example phrases to a learner. In this paper, we propose architecture of an interactive support method for English writing learning which is based an analogical search technique of sample phrases from corpora. Our system can show a candidate of variation/next phrases to write and an analogous sentence that a learner wants to represents from corpora.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권9호
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• pp.3169-3185
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• 2021

The majority of students in higher education institutions are among generation Z. They have always depended on e-learning to support their learning activities. Therefore, higher education institutions should provide an attractive e-learning platform. E-learning interface design should be reviewed frequently to smoothen the interaction between students and the e-learning system. It is because interface design that fulfils generation Z students' preferences and expectations may upsurge their participation in e-learning. However, interface design has continually been condemned and turn out to be part of the problem that contributes to the failure of e-learning. Lack of consideration about generation Z students' preferences towards the interface design of e-learning is the factor that leads to these causes. Therefore, this study focused on identifying design characteristics of colour and graphic elements of e-learning from generation Z students' perception. This research involved a purposive sampling method for questionnaire among students of generation Z. The findings from this study could help e-learning developers to design the interface of e-learning that is suitable for generation Z students that will consider color and graphic as important characteristics.

• Management Science and Financial Engineering
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• 제19권1호
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• pp.1-10
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• 2013

Hierarchical forecasting strategy does not always outperform direct forecasting strategy. The performance generally depends on demand features. This research guides the use of the alternative forecasting strategies according to demand features. This paper developed and evaluated various classification models such as logistic regression (LR), artificial neural networks (ANN), decision trees (DT), boosted trees (BT), and random forests (RF) for predicting the relative performance of the alternative forecasting strategies for the South Korean navy's spare parts demand which has non-normal characteristics. ANN minimized classification errors and inventory costs, whereas LR minimized the Brier scores and the sum of forecasting errors.

• 한국정보통신학회논문지
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• 제18권12호
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• pp.2946-2952
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• 2014

표본 기반 초해상도(Super Resolution 이하 SR) 방법들 중 네이버 임베딩(Neighbor Embedding 이하 NE) 기법의 기본 원리는 지역적 선형 임베딩이라는 매니폴드 학습방법의 개념과 같다. 그러나, 네이버 임베딩은 국부 학습 데이터 집합의 크기가 너무 작기 때문에 이에 따른 빈약한 일반화 능력으로 인하여 알고리즘의 성능을 크게 저하시킨다. 본 논문에서는 이와 같은 문제점을 해결하기 위해서 일반화 능력이 뛰어난 Support Vector Regression(이하 SVR)을 이용한 Sparse-Neighbor 영상 표현 학습 방법에 기반한 새로운 알고리즘을 제안하였다. 저해상도 입력 영상이 주어지면 bicubic 보간법을 이용하여 확대된 영상을 얻고, 이 확대된 영상으로부터 패치를 얻은 후 저주파 패치인지 고주파 패치 인지를 판별한 후 각 영상 패치의 가중치를 얻은 후 두 개의 SVR을 훈련하였으며 훈련된 SVR을 이용하여 고해상도의 해당 화소 값을 예측하였다. 실험을 통하여 제안된 기법이 기존의 보간법 및 네이버 임베딩 기법 등에 비해 정량적인 척도 및 시각적으로 향상된 결과를 보여 주었다.

• 동의생리병리학회지
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• 제35권5호
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• pp.132-138
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• 2021

Artificial intelligence technology sheds light on new ways of innovating acupuncture research. As acupoint selection is specific to target diseases, each acupoint is generally believed to have a specific indication. However, the specificity of acupoint selection may be not always same with the specificity of acupoint indication. In this review, we propose that the specificity of acupoint indication can be inferred from clinical data using reverse inference. Using forward inference, the prescribed acupoints for each disease can be quantified for the specificity of acupoint selection. Using reverse inference, targeted diseases for each acupoint can be quantified for the specificity of acupoint indication. It is noteworthy that the selection of an acupoint for a particular disease does not imply the acupoint has specific indications for that disease. Electronic medical record includes various symptoms and chosen acupoint combinations. Data mining approach can be useful to reveal the complex relationships between diseases and acupoints from clinical data. Combining the clinical information and the bodily sensation map, the spatial patterns of acupoint indication can be further estimated. Interoperable medical data should be collected for medical knowledge discovery and clinical decision support system. In the era of artificial intelligence, machine learning can reveal the associations between diseases and prescribed acupoints from large scale clinical data warehouse.

• Advances in concrete construction
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• 제13권1호
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• pp.11-23
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• 2022

Conventional concrete needs some improvement in the mechanical properties, which can be obtained by different admixtures. However, making concrete samples costume always time and money. In this paper, different types of hybrid algorithms are applied to develop predictive models for forecasting compressive strength (CS) of concretes containing metakaolin (MK) and fly ash (FA). In this regard, three different algorithms have been used, namely multilayer perceptron (MLP), radial basis function (RBF), and support vector machine (SVR), to predict CS of concretes by considering most influencers input variables. These algorithms integrated with the grey wolf optimization (GWO) algorithm to increase the model's accuracy in predicting (GWMLP, GWRBF, and GWSVR). The proposed MLP models were implemented and evaluated in three different layers, wherein each layer, GWO, fitted the best neuron number of the hidden layer. Correspondingly, the key parameters of the SVR model are identified using the GWO method. Also, the optimization algorithm determines the hidden neurons' number and the spread value to set the RBF structure. The results show that the developed models all provide accurate predictions of the CS of concrete incorporating MK and FA with R² larger than 0.9972 and 0.9976 in the learning and testing stage, respectively. Regarding GWMLP models, the GWMLP1 model outperforms other GWMLP networks. All in all, GWSVR has the worst performance with the lowest indices, while the highest score belongs to GWRBF.

• International Journal of Computer Science & Network Security
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• 제24권4호
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• pp.179-191
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• 2024

With the advancement of modern technology, cyber-attacks are always rising. Specialized defense systems are needed to protect organizations against these threats. Malicious behavior in the network is discovered using security tools like intrusion detection systems (IDS), firewall, antimalware systems, security information and event management (SIEM). It aids in defending businesses from attacks. Delivering advance threat feeds for precise attack detection in intrusion detection systems is the role of cyber-threat intelligence (CTI) in the study is being presented. In this proposed work CTI feeds are utilized in the detection of assaults accurately in intrusion detection system. The ultimate objective is to identify the attacker behind the attack. Several data sets had been analyzed for attack detection. With the proposed study the ability to identify network attacks has improved by using machine learning algorithms. The proposed model provides 98% accuracy, 97% precision, and 96% recall respectively.

• 한국의료질향상학회지
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• 제17권1호
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• pp.89-105
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• 2011

Background : The purpose of study in to grasp the level of perception of hospital workers on the patient safety culture, consider the difference in perception of patients safety culture according to medical service and finally find out a way to establish patient safety culture in hospital. Methods : As for the data, the analysis on frequency, t-test, ANOVA and tukey test were carried out by using SPSS 12.0. Result : The results of comparison among the positive response ratios on the patients culture of hospital workers showed that the subjects had perceived the teamwork within units most positively(74.1%), and perceived most negatively on the non-punitive response to error(16.2%)and the staffing(26.2%). 68.6% of subjects answered that the medical error were mostly of always reported. when daytime working hours are longer, perception of patient safety culture ranked low. In general, departments for direct medical service than departments for indirect medical service assessed patient safety culture high. Conclusion : Organizational learning and teamwork within units, communication openness, active support of hospital management for patient safety, and cooperation across the units would be crucial to promote the overall perceptions of patients safety of hospital workers and the level of patients safety in the units and to improve the quality of the event reporting system.

• 한국비블리아학회지
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• 제13권2호
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• pp.265-282
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• 2002

교수-학습의 새로운 패러다임의 변화는 교사와 학생들의 역할에서 찾아볼 수 있다. 가르치는 교사에서 안내자로, 경청하는 학생에서 적극적인 참석자로, 기억을중요시하기보다는새로운지식을창조하고, 교과서에 포함된 기본적인 정보에서 보다 다양한 인쇄매체와 전자정보원에서 새로운 정보를 수집하고 발견하며, 사실중심교육에서 문제해결중심교육으로 지향하고 있다. 이와 같은 현상에서 오늘날의 학교교육은 교실중심교육에서 연장된 학교도서관지원교육으로 변화하는 과정에 이르게 되었다. 새롭게 학교교육을 쇄신하고 개혁하는 운동을 실현시키기 위하여 훌륭한 학교도서관 프로그램을 활용한다는 것은 값진 방법이며 수단인 것이다. 학교도서관에서 교수-학습을 지원하는 프로그램운영의 원리를 알아본 다음, 우리나라 학교도서관에서 현재 실현되고 있는 정도와 미래지향적이며 희망적인 프로그램정도에 대하여 조사하였다. 프로그램의 현재 실현정도와 미래희망정도와는 13개 문항 모두가 유의한 차이를 보였으며 특히 교과과정과 관련된 문항의 현재 실현수준은 낮게 나타났다.