• KIPS Transactions on Software and Data Engineering
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• v.11 no.8
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• pp.347-354
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• 2022

Since the era of the 4th industrial revolution has been ripe, the use of artificial intelligence(AI) based on massive data is beginning to be actively applied in various fields. However, as the process of analyzing forest species is carried out manually, many errors are occurring. Therefore, in this paper, about 60,000 pieces of AI learning data were automatically analyzed for pine, larch, conifer, and broadleaf trees of aerial photographs and pseudo images in the metropolitan area, and an AI model was developed to distinguish tree species. Through this, it is expected to increase in work efficiency by using the tree species division image as basic data when producing forest change detection and forest field topics.

• Smart Media Journal
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• v.11 no.10
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• pp.76-88
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• 2022

Personal information leakage is very harmful as it can lead to additional attacks using leaked information as well as privacy invasion, and it is primarily caused by hacking server databases of institutions that collect and store personal information. We propose a scheme that allows a service-requesting user to authorize a secure delegated transfer of his personal information to the service provider via a reliable authority and enables only the two parties of the service to retrieve the provided information stored on a blockchain ensuring data confidentiality. It thus eliminates the necessity of storing customer information in the service provider's own database. As a result, the service provider can serve customers without requiring membership registration or storing personal information in the database, so that information leakage through the server database can be completely blocked. In addition, the scheme is free from the risk of information leakage and subsequent attacks through smartphones because it does not require a user's smartphone to store any authentication credential or personal information of its owner.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.183-188
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• 2023

Game object inheritance and multiple components allow for visualization of system architecture, good code reuse, and fast prototyping. On the other hand, objects are more likely to rely on high latency between game objects and components, static casts, and lots of references to things like null pointers. Therefore, It is important to design a game in such a way so that the dependency of objects on multiple classes could be reduced and existing codes could be reused. Therefore, we designed the game to make the classes more modular by applying Dependency Injection and the design patterns proposed by the Gang of Four. Since these dependencies are attributes of the game object and the injection occurs only in the initialization pass, there is little performance degradation or performance penalty in the game loop. Therefore, this paper proposed an efficient design method to effectively reuse APIs in the design and implementation of survival games.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.127-135
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• 2023

Nowadays, the number of patients committing suicide due to depression and stress is rapidly increasing. In addition, if stress and depression last for a long time, they are dangerous factors that can cause heart disease, brain disease, and high blood pressure. However, no matter how modern medicine has developed, it is a very difficult situation for patients with depression and heart disease without special drugs or treatments. Therefore, in many countries around the world, studies are being actively conducted to determine patients at risk of depression and patients at risk of suicide at an early stage using electrocardiogram, oxygen saturation, and brain wave analysis functions. In this paper, in order to analyze these problems, a computer simulation was performed to determine heart disease risk patients by establishing heart disease hypothesis data. In particular, in order to improve the predictive rate of heart disease by more than 10%, a simulation using fuzzy inference was performed.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.4
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• pp.661-668
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• 2023

A large amount of fuel is required for heating the agricultural facility house, and many farmhouses are experiencing the burden of heating costs due to the recent increase in fuel prices. This paper proposes a supply system that supports heating of agricultural facility houses located nearby by utilizing industrial chimney waste heat, and analyzes the application and effect of a heating cost reduction model. The system was designed based on the chimney waste heat system, and the facility house heating cost reduction model was applied and effect analysis was performed based on the proposed model. It was confirmed that the high-temperature waste heat from the chimney can be used to supply heating to facility houses in nearby farms. If heating is supplied to large-scale facility houses near industrial complexes, it is expected to contribute to improve productivity and competitiveness of domestic farms.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.1
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• pp.93-113
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• 2022

Among Korea's content industries, the game industry is growing in size to the extent that it can be said to be a representative export-benefiting industry. Accordingly, many users are immersed in the game, and furthermore, they are addicted. This study aims to derive factors for social game users to continue to use by identifying the factors of domestic social network game users' attachment to social network games and empirically studying the causal relationship between these factors and the intention to continue to use them through immersion and addiction. To this end, a research model was presented that applies the main variables of the attachment theory of social network game users to games. The research model of this study surveyed general college students at S University in Seoul who tended to use social network games. As a result of the study, first, it was found that perceived stability had a significant effect on immersion and addiction. Second, it was found that perceived avoidance had a significant effect on immersion and did not have a significant effect on addiction. Third, perceived anxiety was found to have a significant effect on immersion, and it was found that it did not significantly affect addiction. Fourth, it was found that immersion did not significantly affect addiction, and it was found that it had a significant effect on continuous use intention. Fifth, addiction was found to have a significant effect on the intention to continue use. Through this, social network game users' attachment to games can provide useful implications for social network game companies to become attached to existing consumers, spreading social network game users, and improving the possibility of continuous use.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.107-111
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• 2023

Journaling techniques are widely used to maintain a consistent file system state in the event of a system crash. As existing journaling techniques are designed for block storage such as HDDs, they are not efficient for byte-addressable persistent memory media. This paper proposes a metadata journaling technique for in-memory file systems that has the ability of avoiding inconsistent file system states in crash situations. The proposed journaling technique reduces a large amount of writing by making use of the byte-addressable feature of memory media and bypasses heavy software I/O stack. Experimental results with the IOzone benchmark show that the proposed journaling technique improves the performance of Ext4 by 49.2% on average.

• Journal of Internet of Things and Convergence
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• v.9 no.3
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• pp.75-80
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• 2023

In medically vulnerable areas in Korea, public health doctors play a significant role in providing not only general medical care but also emergency medical services to the local residents. However, it has been observed that public health doctors generally lack field experience, resulting in insufficient ability to handle emergency patients and to effectively use medical equipment. This study confirmed the effectiveness of education after conducting remote education using smart glasses on how to use medical equipment necessary for public health doctors. Specifically, real wear was used for smart glasses for medical equipment utilization education, and 10 public health officials in 10 islands in Shinan-gun were targeted. After the training, both the effect of using the equipment and the level of satisfaction were 3 or higher. Therefore, it was confirmed that remote education using smart glasses can be usefully used for public health doctors in medically vulnerable areas.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.113-119
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• 2022

In software fault prediction, a multi classification model that predicts the fault severity category of a module can be much more useful than a binary classification model that simply predicts the presence or absence of faults. A small number of severity-based fault prediction models have been proposed, but no classifier using deep learning techniques has been proposed. In this paper, we construct MLP models with 3 or 5 hidden layers, and they have a structure with a fixed or variable number of hidden layer nodes. As a result of the model evaluation experiment, MLP-based deep learning models shows significantly better performance in both Accuracy and AUC than MLPs, which showed the best performance among models that did not use deep learning. In particular, the model structure with 3 hidden layers, 32 batch size, and 64 nodes shows the best performance.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.727-730
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• 2023

The operation of electric automatic windows is used in harsh environments, and the energy density decreases as charging and discharging are repeated, and as soundness deteriorates due to damage to the internal separator, the vehicle's mileage decreases and the charging speed slows down, so about 5 to 10 Batteries that have been used for about a year are classified as waste batteries, and for this reason, as the risk of battery fire and explosion increases, it is essential to diagnose batteries and estimate SOH. Estimation of current battery SOH is a very important content, and it evaluates the state of the battery by measuring the time, temperature, and voltage required while repeatedly charging and discharging the battery. There are disadvantages. In this paper, measurement of discharge capacity (C-rate) using a waste battery of a Tesla car in order to predict SOH estimation of a lithium-ion battery. A Support Vector Machine (SVM), one of the machine models, was applied using the data measured from the waste battery.