• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.2
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• pp.43-52
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• 2019

The recent technological developments of smart devices, multiple services are provided to enhance the users' quality of life including smart city, smart energy, smart car, smart healthcare, smart home, and so on. Academia and industries try to provide the users with convenient services upon seamless technological research and developments. Also, whenever and wherever a variety of services can be used without any limitation on the place and time upon connecting with different types of devices. However, security weaknesses due to integrations of multiple technological elements have been detected resulting in the leakage of user information, account hacking, and privacy leakage, threats to people's lives by device operation have been raised. In this paper, safer communication framework is suggested by device control and user authentication in the mobile network environment. After implementations of registration and authentication processes by users and devices, safe communication protocol is designed based on this. Also, renewal process is designed according to the safe control of the device. In the performance evaluation, safety was analyzed on the attack of protocol change weakness occurred in the existing system, service halt, data leakage, illegal operation control of message, and so on, which confirmed the enhanced speed approximately by 8% and 23% in the communication and verification parts, respectively, compared to the existing system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1812-1824
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• 2019

The location and human activity are usually used as one of the important parameters to monitor the health status in healthcare devices. However, nearly all existing location and monitoring systems have the limitation of short-range communication and high power consumption. In this paper, we propose a new mechanism to collect and transmit monitoring information based on LoRa technology. The monitoring device with sensors can collect the real-time activity and location information and transmit them to the cloud server through LoRa gateway. The user can check all his history and current information through the specific designed mobile applications. Experiment was carried out to verify the communication, power consumption and monitoring performance of the entire system. Experimental results demonstrate that this system can collect monitoring and activity information accurately and provide the long rang coverage with low power consumption.

• Korean Journal of Artificial Intelligence
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• v.8 no.2
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• pp.1-5
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• 2020

Children's home accidents are less common than in the past. However, safety accidents continue to occur due to carelessness of the parents. To solve the problem, there are fall prevention screens that can withstand the weight of children, and safety railings that can be adjusted directly to solve the problem. However, these have disadvantages such as stability, convenience, and damage to the landscape. In this paper, we developed an automatic safety accident prevention fence system that can be installed on a window using Arduino, eliminating the disadvantages of previous safety accident prevention products. This system measures the height of a person standing in front of the fence and the distance between the person and the fence with two infrared sensors and moves automatically using a motor. In addition, in accordance with the U-Healthcare society, users can check the temperature, humidity, and fine dust concentration of the external environment through mobile. Each information can be obtained through DHT 11 sensor, fine dust concentration sensor, and Bluetooth connected toArduino. These can help the user's health care.

• Journal of Fashion Business
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• v.25 no.5
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• pp.88-98
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• 2021

In this study, the characteristics of digital anthropometric methods were determined with case studies. These methods were broadly classified into two categories: non-wearable and wearable. Then, these categories were further classified into four types: 3D Scanning, mobile app, smart clothing, and smart tool Among the non-wearable types, the "3D scanning" technique was based on the use of 3D hardware equipment. With this technique, the body shape was measured and the internal body information was obtained. Therefore, it is used in fields of healthcare and fitness. Among the wearable types, "Smart clothing" involves a special clothing that measures human body and a smartphone application. Both the components are linked to a fashion platform, which is based on the measured sizes that help shoppers. The "Smart tool" has the characteristic of measuring only with smart tools and smartphone applications; it does not involve the measurement of images. The common advantage of digital anthropometric methods are as follows: they reduce the time and cost of measurement by enabling self-measurement. Moreover, simple measurements are used to determine the size of anthropometry. Thereafter, it accumulates this data to track the continuous changes in size. From an industrial point of view, digital anthropometric technology should be used to increase sales. The on-demand market can be expanded as global consumers would throng the Korean fashion market. For the consumer, an avatar should be created to fit the user's size. This would provide a fun experience to the user.

• Journal of information and communication convergence engineering
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• v.20 no.3
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• pp.219-225
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• 2022

In this study, we propose training a support vector machine (SVM) model on top of deep networks for detecting Covid-19 from chest X-ray images. We started by gathering a real chest X-ray image dataset, including positive Covid-19, normal cases, and other lung diseases not caused by Covid-19. Instead of training deep networks from scratch, we fine-tuned recent pre-trained deep network models, such as DenseNet121, MobileNet v2, Inception v3, Xception, ResNet50, VGG16, and VGG19, to classify chest X-ray images into one of three classes (Covid-19, normal, and other lung). We propose training an SVM model on top of deep networks to perform a nonlinear combination of deep network outputs, improving classification over any single deep network. The empirical test results on the real chest X-ray image dataset show that deep network models, with an exception of ResNet50 with 82.44%, provide an accuracy of at least 92% on the test set. The proposed SVM on top of the deep network achieved the highest accuracy of 96.16%.

• Journal of Powder Materials
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• v.30 no.4
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• pp.310-317
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• 2023

Small-film-type ion sensors are garnering considerable interest in the fields of wearable healthcare and home-based monitoring systems. The performance of these sensors primarily relies on electrode capacitance, often employing nanocomposite materials composed of nano- and sub-micrometer particles. Traditional techniques for enhancing capacitance involve the creation of nanoparticles on film electrodes, which require cost-intensive and complex chemical synthesis processes, followed by additional coating optimization. In this study, we introduce a simple one-step electrochemical method for fabricating gold nanoparticles on a carbon nanotube (Au NP-CNT) electrode surface through cyclic voltammetry deposition. Furthermore, we assess the improvement in capacitance by distinguishing between the electrical double-layer capacitance and diffusion-controlled capacitance, thereby clarifying the principles underpinning the material design. The Au NP-CNT electrode maintains its stability and sensitivity for up to 50 d, signifying its potential for advanced ion sensing. Additionally, integration with a mobile wireless data system highlights the versatility of the sensor for health applications.

• Journal of Distribution Science
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• v.21 no.7
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• pp.117-129
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• 2023

Purpose: With the number of COVID-19 cases declining and generational differences among how people use mobile apps, including health service apps, the goal of this research is to identify and analyze the factors that affect people's attitudes when using the Halodoc health service app during the third year of the pandemic. Research design, data, and methodology: This study proposes a quantitative analysis method based on PLS-SEM modeling. This study has used a questionnaire survey to collect randomized data from 268 Halodoc users from generations Y and Z in Jakarta. Results: Both the Y and Z generations believe there is a significant usefulness factor in the attitude toward using the application. The start of the pandemic period demonstrates that the urgency of using health service applications is no longer determined by performance expectations, effort, or social panic, but rather by these applications' usability. Conclusions: Even though a health service application is no longer considered an urgent service or a priority need, attitudes, and behaviors in using it emphasize the aspect of long-term benefits. These findings supplement other considerations and understandings in application of the Unified Theory of Acceptance and Use of Technology (UTAUT) model in explaining attitudes and intention behaviors.

• International Journal of Computer Science & Network Security
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• v.24 no.3
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• pp.83-92
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• 2024

It is a common observation that whenever any patient arrives at the front desk of a hospital, outpatient clinic, or other health-associated centers, they have to first queue up in a line and wait to fill in their registration form to get admitted. The long waiting time without any status updates is the most common complaint, worrying health officials. In this paper, UrNext, a location-aware mobile-based solution using Bluetooth low-energy (BLE) technology, is presented to solve the problem. Recently, a technology-oriented method has been gaining popularity in solving the healthcare sector's problems, namely the Internet of Things (IoT). The implementation of this solution could be explained through a simple example that when a patient arrives at a clinic for her consultation. There, instead of having to wait in long lines, she will be greeted automatically, receive a push notification telling her that she has been admitted along with an estimated waiting time for her consultation session. This will not only provide the patients with a sense of freedom but would also reduce uncertainty levels that are generally observed, thus saving both time and money. This work aimed to improve clinics' quality of services and organize queues and minimize waiting times in clinics, leading to patient comfortability and reducing the burden on nurses and receptionists. The results demonstrated that the presented system was successful in its performance and helped achieve high usability.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.7
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• pp.630-642
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• 2013

To transmit vital signal stream of mobile patients remotely, it requires mobility of patient and watcher, sensing function of patient's abnormal symptom and self-organizing service binding of related computing resources. In the existing relative researches, the vital signal stream is transmitted as a centralized approach which exposure the single point of failure itself and incur data traffic to central server although it is localized service. Self-organizing middleware platform based on heterogenous overlay network is a middleware platform which can transmit real-time data from sensor device(including vital signal measure devices) to Smartphone, TV, PC and external system through overlay network applied self-organizing mechanism. It can transmit and save vital signal stream from sensor device autonomically without arbitration of management server and several receiving devices can simultaneously receive and display through interaction of nodes in real-time.

• The Korean Journal of Nuclear Medicine Technology
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• v.16 no.1
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• pp.8-11
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• 2012

Purpose : Among quality control items, the radiochemical impurity must be below 10% of total radioactivity. In this regard, as the recently commercialized automatic synthesis module produces a large amount of 18F-FDG, radiolysis of radiopharmaceuticals is very likely to occur. Thus, this study compared the changes in radiochemical purity regarding radiolysis of $^{18}F$-FDG according to automatic synthesis module. Materials and methods : Cyclotron (PETtrace, GE Healthcare) was used to produce $^{18}F$ and automatic synthesis module (FASTlab, Tracerlab MX, GE Healthcare) was used to achieve synthesis into FDG. For radiochemical purity, Radio-TLC Scanner (AR 2000, Bioscan), GC (Gas Chromatograph, Agilent 7890A) was used to measure the content of ethanol included in $^{18}F$-FDG. Glass board applied with silica gel ($1{\times}10cm$) was used for stationary phase while a mixed liquid formed of acetonitrile and water (ratio 19:1) was used for mobile phase. High-concentration and low-concentration $^{18}F$-FDG were produced in each synthesis module and the radiochemical purity was measured every 2 hours. Results : The purity in low-concentration (below 2.59 GBq/mL) was measured as 99.26%, 98.69%, 98.25%, 98.09% in Tracerlab MX and as 99.09%, 97.83%, 96.89%, 96.62% in FASTlab according to 0, 2, 4, 6 hours changes, respectively. The purity in high-concentration (above 3.7 GBq/mL) was measured as 99.54%, 96.08%, 93.77%, 92.54% in Tracerlab MX and as 99.53%, 95.65%, 92.39%, 89.82% in FASTlab according to 0, 2, 4, 6 hours changes, respectively. Also, ethanol was not detected in GC of $^{18}F$-FDG produced in FASTlab, while 100~300 ppm ethanol was detected in Tracerlab MX. Conclusion : Whereas the change of radiochemical purity was only 3% in low-concentration $^{18}F$-FDG, the change was rapidly increased to 10% in high-concentration. Also, higher radiolysis were observed in $^{18}F$-FDG produced in FASTlab than Tracerlab MX. This is because ethanol is included in the synthesis stage of Tracerlab MX but not in the synthesis stage of FASTlab. Thus, radiolysis is influenced by radioactivity concentration than the inclusion of ethanol, which is the radioprotector. Therefore, after producing high-concentration $^{18}F$-FDG, the content must be diluted through saline to lower concentration.