• Journal of Fashion Business
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• v.23 no.2
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• pp.156-169
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• 2019

The objective of this study was to develop lightweight, stretchable, tight-fit smart sportswear using the conductive yarns into the garment and demonstrating its usefulness. Sportswears with the ability to control LEDs with respect to lighting of the surrounding were developed by applying embroidery with conductive yarns to 2 types of men's T-shirts and 2 types of women's leggings pants for outdoor activities and exercise purposes. LEDs were applied to the front and back of men's T-shirts and to the rear of the waist of women's leggings. Men's T-shirts were printed where the LEDs were to be applied, and inside, they were embroidered with conductive threads on the hot-melt fabric to be attached, and then connected with LED. Women's pants were embroidered on the elastic band, in the form of a sine wave that gives it ability to stretch, and finally the elastic band was hidden inside the waistband. The operation of the light sensor in the dark provided the ability to protect joggers from night drivers or cyclists. LEDs were activated when the wearer turns on the fashionable device on his/her shoulder by pressing it. It was able to reduce the risk of accidents by giving recognizability to vehicles, bicycles, and athletes approaching or passing by at night, and securing safe distance from vehicles, etc. Internal embroidery technology had the same flexible and lightweight functions as ordinary clothing products, making it possible to apply to tight-fit smart T-shirts or leggings pants designs.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.267-275
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• 2021

Smart application is developed in this paper by using an android-based platform to automatically determine the human emergency state (Lifesaver) by using different technology sensors of the mobile. In practice, this Lifesaver has many applications, and it can be easily combined with other applications as well to determine the emergency of humans. For example, if an old human falls due to some medical reasons, then this application is automatically determining the human state and then calls a person from this emergency contact list. Moreover, if the car accidentally crashes due to an accident, then the Lifesaver application is also helping to call a person who is on the emergency contact list to save human life. Therefore, the main objective of this project is to develop an application that can save human life. As a result, the proposed Lifesaver application is utilized to assist the person to get immediate attention in case of absence of help in four different situations. To develop the Lifesaver system, the GPS is also integrated to get the exact location of a human in case of emergency. Moreover, the emergency list of friends and authorities is also maintained to develop this application. To test and evaluate the Lifesaver system, the 50 different human data are collected with different age groups in the range of (40-70) and the performance of the Lifesaver application is also evaluated and compared with other state-of-the-art applications. On average, the Lifesaver system is achieved 95.5% detection accuracy and the value of 91.5 based on emergency index metric, which is outperformed compared to other applications in this domain.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.157-162
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• 2019

Recently, the awareness of S/W education, which was confined to the profession, is changing due to the changing industrial environment based on ICT technology World main countries invest competitively in S/W education and the target age group is getting lower Among them, the unplugged coding method using the robot platform is known as one of the most effective S/W training methods targeting the elementary age by the intuitive coding method and the robot platform feedback. However, the unplugged coding method using the robot platform has a disadvantage that it can not configure various interfaces for complicated coding due to limitations of H/W. In this paper, we have proposed an unplugged coding system which can input various commands for robot control by IR remote control as an interface and minute signals using robot sensor.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.5
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• pp.969-976
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• 2019

A lightweight artificial intelligence hardware has made great strides in many application areas. In general, a lightweight artificial intelligence system consist of lightweight artificial intelligence engine and preprocessor including feature selection, generation, extraction, and normalization. In order to achieve optimal performance in broad range of applications, lightweight artificial intelligence system needs to choose a good preprocessing function and set their respective hyper-parameters. This paper proposes a unified framework for a lightweight artificial intelligence system and utilization method for finding models with optimal performance to use on a given dataset. The proposed unified framework can easily generate a model combined with preprocessing functions and lightweight artificial intelligence engine. In performance evaluation using handwritten image dataset and fall detection dataset measured with inertial sensor, the proposed unified framework showed building optimal artificial intelligence models with over 90% test accuracy.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.7
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• pp.119-126
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• 2019

The active living of the elderly leads to improve their lives and enhance social networks. In the view of the active living, the walkability is an essential factor for the elderly's daily life. To support the active living, making age-friendly environment is important. Considering that the elderly mainly carry out activities through walking, making the age-friendly walking environment is a preliminary action. The existing studies applied various methods such as surveys by experts. In spite of the benefits in theirs, there is still a limitation that current walkability measurement methods did not incorporate the actual elderly's walking activity. Thus, the purposes of this study is to measure the elderly's walking quantitatively using a wearable sensor, and to investigate the feasibility of comparing several walking environments based on the data collected from the actual elderly's walking. To do this, experiment was conducted in four types environments with 22 senior subjects. The walkability was measured by walking stability represented quantitatively as Maximum Lyapunov Exponent (MaxLE). Through the experiment results, it was confirmed that the stability of the elderly walking was different according to the walking environment, which also meant that bodily responses (walking stability) is highly related to walkability. The results will provide an opportunity for the continuous diagnosis of walking environments, thereby enhancing the active living of the elderly.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.935-941
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• 2020

People estimation is important to provide IoT services. Most people counting technologies use camera or sensor data. However, the conventional technologies have the disadvantages of invasion of privacy and the need to install extra infrastructure. This paper proposes a method for estimating the number of people using a Wi-Fi AP. We use channel state information of Wi-Fi and analyze that using deep learning technology. It can be achieved by pre-installed Wi-Fi infrastructure that reduce cost for people estimation and privacy infringement. The proposed algorithm uses a k-binding data for pre-processing process and a 1D-CNN learning model. Two APs were installed to analyze the estimation results of six people. The result of the accurate number estimation was 64.8%, but the result of classifying the number of people into classes showed a high result of 84.5%. This algorithm is expected to be applicable to estimate the density of people in a small space.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.5
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• pp.637-644
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• 2021

In general, in the fields of computer vision, robotics, and augmented reality, the importance of 3D space and 3D object detection and recognition technology has emerged. In particular, since it is possible to acquire RGB images and depth images in real time through an image sensor using Microsoft Kinect method, many changes have been made to object detection, tracking and recognition studies. In this paper, we propose a method to improve the quality of 3D reconstructed images by processing images acquired through a depth-based (RGB-Depth) camera on a multi-view camera system. In this paper, a method of removing noise outside an object by applying a mask acquired from a color image and a method of applying a combined filtering operation to obtain the difference in depth information between pixels inside the object is proposed. Through each experiment result, it was confirmed that the proposed method can effectively remove noise and improve the quality of 3D reconstructed image.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.15 no.5
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• pp.13-24
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• 2005

Due to the changes in the wireless information environment, there has been an increased demand for various types of information. Accordingly, many wireless communication technologies have been studied and developed. In particular, studies on ubiquitous communications are well underway. Lately, the focus has been on the Bluetooth technology due to its applicability in various environments. Applying Bluetooth connectivity to new environments such as ubiquitous or sensor networks requires finding new wars of using it. Thus, this research analyzed the vulnerability on the limited number of slaves in a piconet configuration through the current Bluetooth communication and proposed an expanded Bluetooth piconet formation method, regardless of the number of slaves inside the piconet even if it is not configured in a scatternet. In the proposed method, we applied a security service and resolved the vulnerabilities of the current piconet by configuring an expanded form of the current tree-shaped structure.

• Journal of Sensor Science and Technology
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• v.30 no.2
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• pp.109-113
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• 2021

In this study, an automated culture media replacement system was developed to analyze changes in the contraction characteristics of cardiomyocytes according to the state of the culture media. For the long-term storage of culture media, a Peltier refrigerator with a temperature of 5 to 8℃ was provided and a pH of 7.4 was maintained. The cell culture media of the cardiomyocytes was continuously replaced using interlocking pumps at a flow rate of 0.83 μl/h. The cardiomyocytes in which the culture media was replaced automatically demonstrated lower heartbeats per minute compared to samples in which there was no replacement. However, these cardiomyocytes moved more uniformly and produced greater displacement in one heartbeat cycle. It was observed that the sarcomere length of the cardiomyocytes increased due to the automated culture media replacement system. These cardiomyocytes were found to demonstrate better maturation compared to the control group. The maturation of cardiomyocytes was verified through staining images. The proposed automated culture media replacement system generates a uniform heart rate and improvements in contraction force. Based on the study, patient-specific drug toxicity assessments can be conducted using differentiated cardiomyocytes in induced pluripotent stem cells.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.2
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• pp.165-170
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• 2021

Machine learning has recently been applied to research in most areas. This is because the results of machine learning are not determined, but the learning of input data creates the objective function, which enables the determination of new data. In addition, the increase in accumulated data affects the accuracy of machine learning results. The data collected here is an important factor in machine learning. The proposed system is a convergence system of cloud systems and local fog systems for service delivery. Thus, the cloud system provides machine learning and infrastructure for services, while the fog system is located in the middle of the cloud and the user to collect and refine data. The data for this application shall be based on the Sensitive data generated by smart devices. The machine learning technique applied to this system uses SVM algorithm for classification and RNN algorithm for status recognition.