• Journal of Convergence for Information Technology
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• v.9 no.9
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• pp.1-12
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• 2019

A dialog system becomes a new way of communication between human and computer. The dialog system takes human voice as an input, and gives a proper response in voice or perform an action. Although there are several well-known products of dialog system (e.g., Amazon Echo, Naver Wave), they commonly suffer from a problem of out-of-domain utterances. If it poorly detects out-of-domain utterances, then it will significantly harm the user satisfactory. There have been some studies aimed at solving this problem, but it is still necessary to study about this intensively. In this paper, we give an overview of the previous studies of out-of-domain detection in terms of three point of view: dataset, feature, and method. As there were relatively smaller studies of this topic due to the lack of datasets, we believe that the most important next research step is to construct and share a large dataset for dialog system, and thereafter try state-of-the-art techniques upon the dataset.

• The Journal of the Acoustical Society of Korea
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• v.38 no.2
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• pp.231-239
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• 2019

In sonar systems, the passive ranging of a target is an active research area. This paper analyzed the performance of passive ranging based on an array invariant method for different environmental and sonar parameters. The array invariant developed for source range estimation in shallow water. The advantages of this method are that detailed environmental information is not required, and the real-time ranging is possible since the computational burden is very small. Simulation was performed to verify the algorithm. And this method is applied to sea-going experimental data in 2013 near Jinhae port. This study shows the performance of ranging for source orientation, transmission signal length, and length of a receiver through numerical simulation experiments. Also, the results using nested array and uniform line arrays are compared.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.5
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• pp.119-126
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• 2019

Typical software developed and used by North Korea is Red Star and internal application software. However, most of the existing research on the North Korean software is the software installation method and general execution screen analysis. One of the ways to identify software vulnerabilities is file fuzzing, which is a typical method for identifying security vulnerabilities. In this paper, we use file fuzzing to analyze the security vulnerability of the software used in North Korea's Seogwang Document Processing System. At this time, we propose the analysis of open document text (ODT) file produced by Seogwang Document Processing System, extraction of node based on Document Object Mode (DOM) to determine test target, and generation of mutation file through insertion and substitution, this increases the number of crash detections at the same testing time.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.2
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• pp.59.1-59.1
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• 2018

SNe light curves have been used to understand the expansion history of the universe, and a lot of efforts have gone into understanding the overall shape of the radioactively powered light curve. However, we still have little direct observational evidence for the theorized SN progenitor systems. Recent studies suggest that the light curve of a supernova shortly after its explosion (< 1 day) contains valuable information about its progenitor system and can be used to set a limit on the progenitor size, R*. In order to catch the early light curve of SNe explosion and understand SNe progenitors, we are performing a ~8hr interval monitoring survey of nearby galaxies (d < 50 Mpc) with 1-m class telescopes around the world. Through this survey, we expect to catch the very early precursor emission as faint as R=21 mag (~0.1 Rsun for the progenitor). In this poster, we outline this project, and provide updates on IMSNG projects during 2017/2018 seasons.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.4
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• pp.93-102
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• 2019

As interest in wellness grows, There is a lot of research about monitoring individual health using wearable devices. Accordingly, a variety of methods have been studied to distinguish exercise from daily activities using wearable devices. Most of these existing studies are machine learning methods. However, there are problems with over-fitting on individual person's learning, data discontinuously recognition by independent segmenting and fake activity. This paper suggests a detection method for exercise activity based on the physiological response principle of heart rate up and down during exercise. This proposed method calculates activity intensity and heart rate from triaxial and photoplethysmography sensor to determine a heart rate recovery, then detects exercise by estimating activity intensity or detecting a heart rate rising state. Experimental results show that our proposed algorithm has 98.64% of averaged accuracy, 98.05% of averaged precision and 98.62% of averaged recall.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.1
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• pp.179-187
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• 2019

With the recent development of small computing devices, IoT sensor network can be widely deployed and is now readily available with sensing, calculation and communi-cation functions at low cost. Sensor data management is a major component of the Internet of Things environment. The huge volume of data produced and transmitted from sensing devices can provide a lot of useful information but is often considered the next big data for businesses. New column-wise compression technology is mounted to the large data server because of its superior space efficiency. Since sensor nodes have narrow bandwidth and fault-prone wireless channels, sensor-based storage systems are subject to incomplete data services. In this study, we will bring forth a short overview through providing an analysis on IoT sensor networks, and will propose a new storage management scheme for IoT data. Our management scheme is based on RAID storage model using column-wise segmentation and compression to improve space efficiency without sacrificing I/O performance. We conclude that proposed storage control scheme outperforms the previous RAID control by computer performance simulation.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.2
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• pp.65-72
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• 2021

Recently, attacks on the network environment have been rapidly escalating and intelligent. Thus, the signature-based network intrusion detection system is becoming clear about its limitations. To solve these problems, research on machine learning-based intrusion detection systems is being conducted in many ways, but two problems are encountered to use machine learning for intrusion detection. The first is to find important features associated with learning for real-time detection, and the second is the imbalance of data used in learning. This problem is fatal because the performance of machine learning algorithms is data-dependent. In this paper, we propose the HSF-DNN, a network intrusion detection model based on a deep neural network to solve the problems presented above. The proposed HFS-DNN was learned through the NSL-KDD data set and performs performance comparisons with existing classification models. Experiments have confirmed that the proposed Hybrid Feature Selection algorithm does not degrade performance, and in an experiment between learning models that solved the imbalance problem, the model proposed in this paper showed the best performance.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.275-285
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• 2021

Ministries of Education are integrating different Learning Management Systems (LMS) to enhance teaching and learning during the lockdown to avoid academic loss. The key factor for delivering a high-quality education through LMS platforms is teachers' acceptance and adoption of the platform. Madrasati platform (which means My school) was introduced by Saudi Arabian Ministry of education as the formal teaching and learning for distance education for public education levels. This study aims to examine the effectiveness, usability and adoption of "Madrasati" platform from teachers' perspectives in Saudi Arabia. "SUS, CSUQ" tests were used to test the usability of the new platform. Using quantitative research design, data were collected using questionnaire. 200 teachers were selected randomly answered the survey. Data was analysed descriptively and inferentially using SPSS (25). The results obtained indicate that the teachers are highly satisfied using Madrasati platform and technically it is well designed. Also, Madrasati has positive effect on teaching quality. Moreover, Madrasati has high usability in teaching. One of the key findings were that the quality of the information content in Madrasati has a strong effect on teachers' perception of the Madrasati usefulness that led to a positive attitude towards Madrasati. These findings would be useful to the ministry of education and institutions trying to integrate technology in their teaching and learning processes. Thus, this paper contributes towards more effective utilisation of the extensive functionalities that Madrasati have to offer, which will contribute toward the development of pedagogy in Saudi Arabia.

• Nutrition Research and Practice
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• v.15 no.2
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• pp.235-247
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• 2021

BACKGROUND/OBJECTIVES: Increasing the consumption of vegetables and fruits in Mexico remains a challenge. Promoting sustainable food production systems through schools may be an effective way to educate young people about food and nutrition issues. A study of nutritional education in adolescents, based on the school garden, is necessary in order to evaluate its effects on the consumption of fruits and vegetables among middle- and upper-income segments of the population. The objective of this study was to evaluate the effect of an educational intervention, accompanied by a school garden as an educational teaching tool, to improve vegetable and fruit consumption by Mexican teenagers attending a private middle/high school. SUBJECTS/METHODS: Teenagers between 12 and 18 years of age (n = 126) attending a private middle/high school in Queretaro, Mexico participated in a 3-arm, controlled, comparative impact study using a vegetable and fruit consumption frequency questionnaire, food consumption diaries, a psychosocial factor assessment questionnaire of vegetable and fruit consumption, and structured interviews. The participants were randomized into 3 experimental groups: 1) food education + school garden (FE + SG), 2) FE only, and 3) control group (CG). RESULTS: The FE + SG and FE groups significantly increased the frequency and daily intake of vegetables and fruits compared to the CG. The FE + SG group showed greater understanding of, reflection upon, and analysis of the information they received about vegetable and fruit consumption, as well as a greater willingness to include these in their daily diet. CONCLUSIONS: FE accompanied by a SG as a teaching tool is more effective at promoting vegetable and fruit consumption than either education alone or control in teenagers in middle-upper income segments of the population.

• PNF and Movement
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• v.18 no.3
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• pp.365-373
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• 2020

Purpose: The COVID-19 pandemic has changed how healthcare is delivered worldwide and has affected the environment of the healthcare. Physical therapy in traditional healthcare systems can be difficult in unusual circumstances, such as the COVID-19 pandemic. Tele-physical therapy, defined as "the delivery of the physical therapy at a distance using electronic information and telecommunication technologies," will be a solution for this healthcare crisis. Thus, in this study, we proposed a mobile application for tele-physical therapy. Methods: This study used the Chrome Browser version 83.0.4 based on the Windows 10 64Bit operating system to use the App Inventor. To operate the mobile application, we used the Samsung Galaxy Note 9. The design of the mobile application was based on the review of a system used in the physical therapy department. Results: The graphical user interface (GUI) of the mobile application was displayed on three screens: selecting a painful joint (1st screen of the GUI); selecting a painful movement of the joint (2nd screen of the GUI); a self-manual therapy method and movie (3rd screen of the GUI). The proposed mobile application showed the stable repeatability of the self-manual therapy movie. Conclusion: The results of this study demonstrated that the proposed mobile application using the App Inventor for android will be able to create easy to use and reliable tele-physical therapy.