• Journal of Korean Academy of Nursing
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• v.45 no.4
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• pp.565-575
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• 2015

Purpose: The purpose of the study was to examine mission statements and their elements and to investigate correlations between mission statements and organizational performance. Methods: The current research was a descriptive study based on the examination of mission statements of 353 hospitals that posted mission statements on their webpage and 92 hospitals that made their income statements public. Results: The most common mission element was 'identification of principal services', which accounted for 92.6%. Mission statements of hospitals included the average of 4.82 mission elements out of 9, and the objective of medical quality improvement was 0.81 among 6 objectives of IOM (Institute of Medicine). Net profit of hospitals with mission statements that have above average number of mission elements were significantly higher (t=2.71, p=.008) than those of other hospitals. Net profit was significantly correlated with mission statements (r=.26, p<.001), and mission elements (r=.29, p<.001). Conclusion: The results of the study empirically reveal that mission statements in the hospital affect organizational performance. That is, better organizational performance is shown for hospitals with better, more diversified, and more firmly stated mission statements which include identification of target customers, identification of principal services, contribution to society as a non-profit organization, and concern for employees.

• Journal of Internet Computing and Services
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• v.20 no.6
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• pp.137-142
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• 2019

This paper Various services exist to detect and monitor abnormal event. However, most services focus on fires and gas leaks. so It is impossible to prevent and respond to emergency situations for the elderly and severely disabled people living alone. In this study, AI model is designed and compared to detect abnormal event of heart rate signal which is considered to be the most important among various bio signals. Specifically, electrocardiogram (ECG) data is collected using Physionet's MIT-BIH Arrhythmia Database, an open medical data. The collected data is transformed in different ways. We then compare the trained AI model with the modified and ECG data.

• Journal of Advanced Navigation Technology
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• v.13 no.1
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• pp.68-73
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• 2009

Recently, various services through the Internet are gradually increased and developed. The traditional way of examination has been replacing by the online test as well. The most representative is the IBT TOEFL by the ETS in the US. Besides this, a lot of online tests and some related discussions are very fierce to carry out due to the continuous increase of the number of exam candidates. Taking account of the economic issues compared to the previous test, this online method has a lot of strengths. This paper aims to build an online test system based on the 3- tier browser-server architecture, which is different from the commonly used 2-tier based system. This system was achieved using the Visual Studio.Net 2005 and SQL Server 2000 as development tools, and based on the ASP.NET 2.0 platform, using the ADO.NET and C# language.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.1-21
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• 2016

IT-based subjective well-being (SWB) services, a main part of wellness IT, should measure the SWB state of individuals in an unrestrained, cost-effective manner. The dictionaries for sentiment analysis available in the market may be useful for this purpose, but obtaining proper sentiment values using only words from the sentiment lexicon is impossible; therefore, a new dictionary including wellness vocabulary is needed. The existing sentiment dictionaries link only a single sentiment value to a single sentiment word, although sentiment values may vary depending on personal traits. In this study, we develop an extended version of the SenticNet sentiment dictionary dubbed WellnessWordNet. SenticNet is considered the best and most expressive among the already existing sentiment dictionaries. Using the information provided by SenticNet, we created a database including the wellness states (estimated values) of stress, depression, and anger to develop the WellnessWordNet system. The accuracy of the system was validated through actual tests with live subjects. This study is unique and unprecedented in that i) an extended sentiment dictionary, WellnessWordNet, is developed; ii) values for wellness state language are offered; and iii) different sentiment values, namely contextual polarity, for people of the same gender or age group are suggested.

• Nuclear Engineering and Technology
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• v.40 no.2
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• pp.127-132
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• 2008

An experimental loop operating with water at supercritical conditions(25MPa, $600^{\circ}C$ in the test section) is designed for operation in the research reactor LVR-15 in UJV Rez, Czech Republic. The loop should serve as an experimental facility for corrosion tests of materials for in-core as well as out-of-core structures, for testing and optimization of suitable water chemistry for a future HPLWR and for studies of radiolysis of water at supercritical conditions, which remains the domain where very few experimental data are available. At present, final necessary calculations(thermalhydraulic, neutronic, strength) are being performed on the irradiation channel, which is the most challenging part of the loop. The concept of the primary and auxiliary circuits has been completed. The design of the loop shall be finished in the course of the year 2007 to start the construction, out-of-pile testing to verify proper functioning of all systems and as such to be ready for in-pile tests by the end of the HPLWR Phase 2 European project by the end of 2009.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.51-52
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• 2009

본 논문에서는 차량 내의 네트워크 가운데에서 대용량의 멀티미디어 데이터를 전송할 수 있는 MOST(Media Oriented Systems Transport) 네트워크 기반의 오디오 인포테인먼트 인터페이스 개발에 관한 연구를 수행하였다. 구현한 오디오 인포테인먼트 인터페이스는 MOST 네트워크 인터페이스 컨트롤러로 OS81050A INIC 칩을 사용하였으며, EHC 부분은 ATmega128L 8bit 마이크로컨트롤러를 사용하였다. 오디오 동작과 관련된 기능 블록(FBlock) 및 애플리케이션 작성에는 NetServices API를 활용하였다. 구현된 인터페이스는 MOST 네트워크 분석 도구인 OptoLyzer G2를 이용하여 정확한 동작여부를 확인하였다.

• Journal of Korea Multimedia Society
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• v.9 no.11
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• pp.1503-1514
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• 2006

Today, consumers can access Internet from everywhere, therefore most commercial and other organizations provide their services on the Web. As the result, countless Web service systems are already on the Internet and more systems are under construction. Therefore, many researches of verifying that the system to be constructed will not have any deadlock and will run successfully without any problem at the early stage of design have been performed. Several Petri net based verification methods have also been published. However, they have focused on building Petri net models of Web service systems and none of them introduces efficient analysis methods. As a mathematical technique with which we can find the minimum duration time needed to fire all the transitions at least once and coming back to the initial marking in a timed net, the minimum cycle time method has been widely used in computer system analysis. A timed net is a modified version of a Petri net where a transition is associated with a delay time. A delay time used in a timed net is a constant even though the duration time associated with an event in the real world is a stochastic number in general. Therefore, this paper proposes 'Mixedly Distributed Stochastic Timed Net' where a transition can be associated with a stochastic number and introduce a minimum cycle time analysis method for 'Mixedly Distributed Stochastic Timed Net'. We also introduce a method of analysing a Web service system's response time with the minimum cycle time analysis method for 'Mixedly Distributed Stochastic Timed Net.'.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.1-9
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• 2021

Traditionally, most malicious codes have been analyzed using feature information extracted by domain experts. However, this feature-based analysis method depends on the analyst's capabilities and has limitations in detecting variant malicious codes that have modified existing malicious codes. In this study, we propose a ResNet-Variational AutoEncder-based variant malware classification method that can classify a family of variant malware without domain expert intervention. The Variational AutoEncoder network has the characteristics of creating new data within a normal distribution and understanding the characteristics of the data well in the learning process of training data provided as input values. In this study, important features of malicious code could be extracted by extracting latent variables in the learning process of Variational AutoEncoder. In addition, transfer learning was performed to better learn the characteristics of the training data and increase the efficiency of learning. The learning parameters of the ResNet-152 model pre-trained with the ImageNet Dataset were transferred to the learning parameters of the Encoder Network. The ResNet-Variational AutoEncoder that performed transfer learning showed higher performance than the existing Variational AutoEncoder and provided learning efficiency. Meanwhile, an ensemble model, Stacking Classifier, was used as a method for classifying variant malicious codes. As a result of learning the Stacking Classifier based on the characteristic data of the variant malware extracted by the Encoder Network of the ResNet-VAE model, an accuracy of 98.66% and an F1-Score of 98.68 were obtained.

• Korean journal of applied entomology
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• v.51 no.1
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• pp.67-72
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• 2012

This study was conducted to evaluate the scouting methods for larva and adults of the alfalfa weevil, $Hypera$ $postica$ Gyllenhal on Chinese milkvetch, $Astragalus$ $sinicus$ L. in the field. Three sampling methods, shake-bucket, shake-picking, and a sweeping net were evaluated for collecting alfalfa weevil larvae. We found significant differences among scouting methods and date in all survey fields. Sweep-net sampling was less able to detect small larvae than large larvae, which were not detected until early April whereas the shake-bucket, and shake-picking methods efficiently collected larvae from middle March. A Pitfall trap with three different baits - no bait, kidney bean seeds and sprouting kidney beans were compared for collection efficiency of alfalfa weevil adults. Collection efficiencies were significantly different by bait(p<0.018). Traps baited with sprouting kidney beans were the most efficient for collecting the alfalfa weevil. The number of alfalfa weevil caught was not significantly different between kidney bean seed and no bait in the pitfall trap. Therefore, the shake-bucket method for larvae and a pitfall trap baited with sprouting kidney beans for adults are recommended for scouting of the alfalfa weevil in a Chinese milkvetch field.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.25-34
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• 2020

In this paper, we empirically compare the effectiveness of training models to recognize beauty-related skin disease using supervised deep learning algorithms. Recently, deep learning algorithms are being actively applied for various fields such as industry, education, and medical. For instance, in the medical field, the ability to diagnose cutaneous cancer using deep learning based artificial intelligence has improved to the experts level. However, there are still insufficient cases applied to disease related to skin beauty. This study experimentally compares the effectiveness of identifying beauty-related skin disease by applying deep learning algorithms, considering CNN, ResNet, and SE-ResNet. The experimental results using these training models show that the accuracy of CNN is 71.5% on average, ResNet is 90.6% on average, and SE-ResNet is 95.3% on average. In particular, the SE-ResNet-50 model, which is a SE-ResNet algorithm with 50 hierarchical structures, showed the most effective result for identifying beauty-related skin diseases with an average accuracy of 96.2%. The purpose of this paper is to study effective training and methods of deep learning algorithms in consideration of the identification for beauty-related skin disease. Thus, it will be able to contribute to the development of services used to treat and easy the skin disease.