• Journal of the Korea Society of Computer and Information
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• v.27 no.4
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• pp.213-221
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• 2022

The purpose of this study is to find methods to prevent and improve smart device over-dependence problems by analyzing differences in school life adaptation and academic performance according to children's dependence on smart devices. For this, the data of fifth grade elementary school students in the 12th year were extracted and utilized from Panel Survey of Korean Children. The data were analyzed using non-hierarchical cluster(K-means) analysis, T-test, one-way ANOVA, and Scheffé tests. The results of this study are as follows. First, It has been shown that dependence on smart devices, school adaptation and academic performance have a negative correlation. Second, students in potential and high-risk groups who are highly dependent on smart devices have significantly lower school adaptation compared to those in the safety group. Third, high-risk students showed significantly lower academic performance compared to those in the potential risk group and general group. Based on these findings, it was suggested that for elementary school students who rely on smart devices, various learning support and national efforts such as counseling for school life adaptation are needed.

• Journal of Internet of Things and Convergence
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• v.8 no.2
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• pp.1-6
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• 2022

This paper presents a regionalized time slotted channel hopping (TSCH) slotframe-based aerial data collection using wake-up radio. The proposed scheme aims to minimize the delay and energy consumption when an unmanned aerial vehicle (UAV) collects data from sensor devices in the large-scale service area. To this end, the proposed scheme divides the service area into multiple regions, and determines the TSCH slotframe length for each region according to the number of cells required by sensor devices in each region. Then, it allocates the cells dedicated for data transmission to the TSCH slotframe using the ID of each sensor device. For energy-efficient data collection, the sensor devices use a wake-up radio. Specifically, the sensor devices use a wake-up radio to activate a network interface only in the cells allocated for beacon reception and data transmission. The simulation results showed that the proposed scheme exhibited better performance in terms of delay and energy consumption compared to the existing scheme.

• Journal of Internet of Things and Convergence
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• v.8 no.5
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• pp.127-132
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• 2022

As the IoT technology is more developed, it is more important for the accuracy of IoT data. Since the IoT data supports a different formats and protocols, it is often happened that the IoT system is failed or the incorrect data is generated with the unreliable IoT devices(sensor, actuator). Because the abnormality of IoT device or the user situation is not detected correctly, this problem makes the user to be unsatisfied with the IoT system. This study proposes the decision methodology of IoT data consistency whether the IoT data is generated in normal range or not by using the mathematical functions('gradient descent function' and 'linear regression function'). It may be concluded that the gradient function method is suitable for the IoT data which the 'increasing velocity' is related with the next generated pattern(eg. sensor devices), the linear regression function method is suitable for the IoT data which the 'the difference from linear regression function' is related with the next generated pattern in case the data has a linear pattern(eg. water meter, electric meter).

• Journal of Internet of Things and Convergence
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• v.8 no.5
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• pp.55-61
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• 2022

Today's payment systems are becoming unmanned and changing to a way of paying with kiosks. This has the advantage of convenient payment because consumers can select a menu and specify the number of products to be purchased with just a touch of the screen. However, from the point of view of system security, the actual kiosk system has various vulnerabilities. This can hijack the administrator account, gain system privileges, and perform malicious actions. In addition, it is exposed to a number of security threats, such as the possibility of wasting unnecessary resources by abnormally increasing the number of payments, and causing the device to fail to operate normally. Therefore, in this paper, if any node of a participant in the solana blockchain approves an incorrect fork, the stake of the voting nodes is deleted. Also, since all participants can see the transaction history due to the nature of the block chain, I intend to write a thesis on a system that improves the vulnerability of kiosk payments by separating the access rights through the private blockchain.

• Parasites, Hosts and Diseases
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• v.60 no.4
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• pp.281-288
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• 2022

Malaria continues to be one of the most crucial infectious burdens in endemic areas worldwide, as well as for travelers visiting malaria transmission regions. It has been reported that 8-aminoquinolines are effective against the Plasmodium species, particularly primaquine, for anti-hypnozoite therapy in P. vivax malaria. However, primaquine causes acute hemolytic anemia in individuals with glucose-6-phosphate dehydrogenase (G6PD) deficiency. Therefore, G6PD deficiency testing should precede hypnozoite elimination with 8-aminoquinoline. Several point-of-care devices have been developed to detect G6PD deficiency. The aim of the present study was to evaluate the performance of a novel, quantitative G6PD diagnostics based on a metagenomic blue fluorescent protein (mBFP). We comparatively evaluated the sensitivity and specificity of the G6PD diagnostic modality with standard methods using 120 human whole blood samples. The G6PD deficiency was spectrophotometrically confirmed. The performance of the G6PD quantitative test kit was compared with that of a licensed control medical device, the G6PD strip. The G6PD quantitative test kit had a sensitivity of 95% (95% confidence interval (CI): 89.3-100%) and a specificity of 100% (95% CI: 94.3-100%). This study shows that the novel diagnostic G6PD quantitative test kit could be a cost-effective and time-efficient, and universally mandated screening tool for G6PD deficiency.

• Journal of Industrial Convergence
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• v.20 no.1
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• pp.63-68
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• 2022

In schools and corporate buildings, public WiFi Access Points are installed on the ceilings of hallways. In the case of an architectural structure in which a WiFi signal enters through a steel door made of a material with high signal attenuation, Internet connection is frequently cut off or fails when the door is closed. To solve this problem, our research implements an economical and portable WiFi extender using a Raspberry Pi and an auxiliary battery. Commercially available WiFi extenders have limitations in the location where the power plug is located, and WiFi extension using the WiFi hotspot function of an Android smartphone is possible only in some high-end models. However, because the proposed device can be installed at the position where the Wi-Fi reception signal is the best inside the door, the WiFi range can be extended while minimizing the possibility of damage to the original signal. Experimental results show that it is possible to eliminate the shadows of radio waves and to provide Internet services in the office when the door is closed, to the extent that web browsing and real-time video streaming for 720p are possible.

• Journal of Internet of Things and Convergence
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• v.8 no.5
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• pp.17-25
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• 2022

Recently the massive amount of data has been generated because of the number of edge devices increases. And especially, the number of raw unstructured HTML documents has been increased. Therefore, MRC(Machine Reading Comprehension) in which a natural language processing model finds the important information within an HTML document is becoming more important. In this paper, we propose HTDE(HTML Tag Depth Embedding Method), which allows the BERT to train the depth of the HTML document structure. HTDE makes a tag stack from the HTML document for each input token in the BERT and then extracts the depth information. After that, we add a HTML embedding layer that takes the depth of the token as input to the step of input embedding of BERT. Since tokenization using HTDE identifies the HTML document structures through the relationship of surrounding tokens, HTDE improves the accuracy of BERT for HTML documents. Finally, we demonstrated that the proposed idea showing the higher accuracy compared than the accuracy using the conventional embedding of BERT.

• Journal of Digital Convergence
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• v.19 no.4
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• pp.133-139
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• 2021

Due to the rapid progress in network technology, many research on content security technologies is also being conducted in the mobile digital content sector. In the meantime, content protection has been immersed in preventing illegal copying, certifying, and issuance/management certificates, but still have many vulnerabilities in managing or authenticating confidential information. This study aims to strengthen confidential information about content based on dual management of content download rights through mobile phone numbers or device numbers. It also protect replay-attack by building a secure mobile DRM system where digital content is safely distributed based on a three-stage user authentication process. In addition, blockchain-based content security enhancements were studied during the primary/secondary process for user authentication for the prevention of piracy and copyright protection. In addition, the client authentication process was further improved through three final stages of authorization in the use of illegal content, considering that legitimate users redistributed their content to third-party.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.31 no.6
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• pp.258-263
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• 2021

ZnO varistor is a semiconductor device which can serve to protect the circuit from surge voltage because its non-linear I-V characteristics by controlling the microstructure of grain and grain boundaries. In order to obtain desired electrical properties, it is important to control microstructure evolution during the sintering process. In this research, we defined a dataset composed of process conditions of sintering and relative permittivity of sintered body, and collected experimental dataset with DOE. Meta-models can predict permittivity were developed by learning the collected experimental dataset on various machine learning algorithms. By utilizing the meta-model, we can derive optimized sintering conditions that could show the maximum permittivity from the numerical-based HMA (Hybrid Metaheuristic Algorithm) optimization algorithm. It is possible to search the optimal process conditions with minimum number of experiments if meta-model-based optimization is applied to ceramic processing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.4065-4083
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• 2021

Super-resolution can improve the clarity of low-resolution (LR) images, which can increase the accuracy of high-level compute vision tasks. Portable devices have low computing power and storage performance. Large-scale neural network super-resolution methods are not suitable for portable devices. In order to save the computational cost and the number of parameters, Lightweight image processing method can improve the processing speed of portable devices. Therefore, we propose the Enhanced Information Multiple Distillation Network (EIMDN) to adapt lower delay and cost. The EIMDN takes feedback mechanism as the framework and obtains low level features through high level features. Further, we replace the feature extraction convolution operation in Information Multiple Distillation Block (IMDB), with Ghost module, and propose the Enhanced Information Multiple Distillation Block (EIMDB) to reduce the amount of calculation and the number of parameters. Finally, coordinate attention (CA) is used at the end of IMDB and EIMDB to enhance the important information extraction from Spaces and channels. Experimental results show that our proposed can achieve convergence faster with fewer parameters and computation, compared with other lightweight super-resolution methods. Under the condition of higher peak signal-to-noise ratio (PSNR) and higher structural similarity (SSIM), the performance of network reconstruction image texture and target contour is significantly improved.