• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.9
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• pp.1718-1724
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• 2017

Recently, Smart plugs for real time monitoring of household appliances based on IoT(Internet of Things) have been activated. Through this, consumers are able to save energy by monitoring real-time energy consumption at all times, and reduce power consumption through alarm function based on consumer setting. In this paper, we measure the alternating current from a wall power outlet for real-time monitoring. At this time, the current pattern for each household appliance was classified and it was experimented with deep learning to determine which product works. As a result, we used a cross validation method and a bootstrap verification method in order to the classification performance according to the type of appliances. Also, it is confirmed that the cost function and the learning success rate are the same as the train data and test data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.8
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• pp.1560-1566
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• 2017

Recently, accumulation of data on pig farm is enabled through the wide spread of smart pig farm equipped with Internet-of-Things based sensors, and various machine learning algorithms are applied on the data in order to improve the productivity of pig farm. Herein, multiple machine learning schemes are used to predict the water usage in pig farm which is known to be one of the most important element in pig farm management. Especially, regression algorithms, which are linear regression, regression tree and AdaBoost regression, and classification algorithms which are logistic classification, decision tree and support vector machine, are applied to derive a prediction scheme which forecast the water usage based on the temperature and humidity of pig farm. Through performance evaluation, we find that the water usage can be predicted with high accuracy. The proposed scheme can be used to detect the malfunction of water system which prevents the death of pigs and reduces the loss of pig farm.

• Fire Science and Engineering
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• v.23 no.3
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• pp.121-130
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• 2009

This study is researched about the field trip of temples and the data for fire extinguishment manual of fire stations: it is done from June 2008 to December 2008 the 80 main temple wooden cultural properties among the 124 main wooden cultural properties appointed by the Cultural Heritage Administration. Cultural properties appointment classification, location classification, temple area, building area in a temple, building area of appointment cultural properties, a fire engine drive direction for fire suppression in a fire, distance from a fire station, and present condition of a fire administrator are researched. The cultural properties possess characteristic is in 2 cases: the whole things in a temple are appointed as cultural properties and only the wooden building is. The cultural properties are classified: the transport is possible or not. The special quality of cultural properties are classified for early correspondence and cultural properties transport in a fire and the basic data are arranged for damage limitation.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.2
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• pp.347-363
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• 2019

Malware has its own unique behavior characteristics, like DNA for living things. To respond APT (Advanced Persistent Threat) attacks in advance, it needs to extract behavioral characteristics from malware. To this end, it needs to do classification for each malware based on its behavioral similarity. In this paper, various similarity of Windows malware is estimated; and based on these similarity values, malware's family is predicted. The similarity measures used in this paper are as follows: 'TF-IDF cosine similarity', 'Nilsimsa similarity', 'malware function cosine similarity' and 'Jaccard similarity'. As a result, we find the prediction rate for each similarity measure is widely different. Although, there is no similarity measure which can be applied to malware classification with high accuracy, this result can be helpful to select a similarity measure to classify specific malware family.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.55-64
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• 2023

The Internet of Things (IoT) is the combination of the internet and various sensing devices. IoT security has increasingly attracted extensive attention. However, significant losses appears due to malicious attacks. Therefore, intrusion detection, which detects malicious attacks and their behaviors in IoT devices plays a crucial role in IoT security. The intrusion detection system, namely IDS should be executed efficiently by conducting classification and efficient feature extraction techniques. To effectively perform Intrusion detection in IoT applications, a novel method based on a Conventional Neural Network (CNN) for classification and an improved Genetic Algorithm (GA) for extraction is proposed and implemented. Existing issues like failing to detect the few attacks from smaller samples are focused, and hence the proposed novel CNN is applied to detect almost all attacks from small to large samples. For that purpose, the feature selection is essential. Thus, the genetic algorithm is improved to identify the best fitness values to perform accurate feature selection. To evaluate the performance, the NSL-KDDCUP dataset is used, and two datasets such as KDDTEST²¹ and KDDTEST⁺ are chosen. The performance and results are compared and analyzed with other existing models. The experimental results show that the proposed algorithm has superior intrusion detection rates to existing models, where the accuracy and true positive rate improve and the false positive rate decrease. In addition, the proposed algorithm indicates better performance on KDDTEST⁺ than KDDTEST²¹ because there are few attacks from minor samples in KDDTEST⁺. Therefore, the results demonstrate that the novel proposed CNN with the improved GA can identify almost every intrusion.

• Journal of Korean Public Health Nursing
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• v.37 no.1
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• pp.5-24
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• 2023

Purpose: The objective of this review was to identify the research trends in Information and Communication Technology (ICT)-based health-related intervention studies for children and adolescents published in South Korea over the past 10 years. Methods: A scoping review was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) and the system classification framework for digital health intervention 1.0 of the World Health Organization (WHO) was applied to analyze how technology was being used to support the needs of the health system. Results: A total of 18 studies were included in the final analysis. The participants were mainly children with a variety of diseases. No studies had used innovative technology platforms such as artificial intelligence (AI), the Internet of Things (IoT), and robotics. In addition, the scope of application of the WHO classification criteria was quite limited. Finally, no intervention study considered technical operational indicators, such as the number of website visits and streaming as outcome measurements. Conclusions: Researchers should introduce advanced technology-based strategies to provide customized and professional healthcare services to children and adolescents in South Korea and continue efforts to integrate innovative ICT for various research purposes, subjects, and environments.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.8
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• pp.883-892
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• 2018

Recently, as interest in social robots to support physical convenience and emotional sympathy has increased, and social internet has developed, a social robot has evolved as various services simply beyond robot function. Therefore, to develop a social robot service effectively, it is required to study the functional application and methods of interaction between user and social robot service. The purpose of this study is to classify social robot services and to suggest the types of elements that need to be considered in service development. To do this, we conducted in-depth case studies and analysis based on the theoretical definitions and characteristics of social robots. Then, based on the sympathy and functions, we classified social robot services into 1) emotional support type, 2) companion type, 3) guide type, and 4) life support type. In addition, in this study, we derive the considerable factors according to the classified types for the development of effective social robot services. This study will contribute to the understanding and development of various services using a social robot.

• International journal of advanced smart convergence
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• v.9 no.3
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• pp.169-175
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• 2020

A lot of research has been conducted on a system that collects and observes patients' health information in real time using Internet of Things (IoT) technology, and cares for and supports patients based on this. However, most studies have focused on underlying diseases such as diabetes or cardiovascular disease, and research on IoT systems to cope with respiratory infectious diseases such as COVID-19 is still insufficient. In a COVID-19 situation, the purpose of using an IoT respirator may vary depending on the user. In this paper, we design a system that can adequately cope with respiratory infectious diseases such as COVID-19 by applying IoT technology to respiratory protection. We categorize IoT respirator wearers into patients, medical staff, and self-quarantine persons, and define the purpose and use case of the IoT respirator system according to each classification. The proposed IoT respirator system was designed to achieve each purpose. We developed a prototype system consisting of a smart sensor, a communication module, and a non-motorized hooded respirator to show that the proposed IoT respirator system works.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.26 no.3
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• pp.328-336
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• 2017

The exit surface of a lens is designed using a three-dimensional free-form expression in order to easily modify a curved surface. This enables the design of numerical values and mathematical things using three-dimensional free-form expression, and enhances precision because it can be fine-tuned via numerical control. The standard of "Classification of Luminaire Light Distribution" for outdoor lighting fixtures by IESNA is adopted in order to examine the correlation between three-dimensional free-form surface expression and lighting performance. The variation of light distribution type and range is analyzed using the values of maximum light intensity and 50% light intensity. The actual tolerance occurs owing to parameters such as the thickness of the lens, the distance between LEDs, and the movement of the center of the incident surface; the effects of changes in these parameters on the performance are compared and analyzed.

• Journal of Navigation and Port Research
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• v.28 no.1
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• pp.91-96
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• 2004

Although features, core element of marine GIS in many application, are same things users have difficulty in using them on account of varying according to method of classification. Accordingly feature cataloguing in accordance with the standard is the trend of the modem world. In this article we have became familiar with ISO 19110 - Methodology for Feature Cataloguing, we was able to discuss element and definition of features for the purpose of Marine GIS's activation. Through the result of study, we presented the methodology of Marine GIS feature cataloguing.