• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.3
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• pp.109-116
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• 2023

This paper presents a network-based automation system for the detection of metallic objects in food and livestock. A metal detector is a core equipment used for the inspection required by HACCP. Since the existing metal detectors are manufactured as a single-body equipment, it is difficult to take into account various user requirements for the system. In order to overcome the drawback, this study presents a network-based automation system for metal detector utilizing an industrial fieldbus and modular components. The proposed system can effectively consider the various customer requirements and control schemes. The proposed system can also achieve the improvement in speed and success rate of detecting metallic objects. The effectiveness of the proposed system is demonstrated through a various experiments.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.11a
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• pp.33-36
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• 2020

Virtual try on is getting interested from researchers these days because its application in online shopping. But single pose virtual try on is not enough, customer may want to see themselves in different pose. Multiple pose virtual try on is getting input as customer image, an in-shop cloth and a target pose, it will try to generate realistic customer wearing the in-shop cloth with the target pose. We first generate the target segmentation layout using conditional generative network (cGAN), and then the in-shop cloth are warped to fit the customer body in target pose. Finally, all the result will be combine using a Resnet-like network. We experiment and show that our method outperforms stage of the art.

• ETRI Journal
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• v.45 no.4
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• pp.594-602
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• 2023

Internet of things (IoT) is commonly employed to detect different kinds of diseases in the health sector. Systemic lupus erythematosus (SLE) is an autoimmune illness that occurs when the body's immune system attacks its own connective tissues and organs. Because of the complicated interconnections between illness trigger exposure levels across time, humans have trouble predicting SLE symptom severity levels. An effective automated machine learning model that intakes IoT data was created to forecast SLE symptoms to solve this issue. IoT has several advantages in the healthcare industry, including interoperability, information exchange, machine-to-machine networking, and data transmission. An SLE symptom-predicting machine learning model was designed by integrating the hybrid marine predator algorithm and atom search optimization with an artificial neural network. The network is trained by the Gene Expression Omnibus dataset as input, and the patients' data are used as input to predict symptoms. The experimental results demonstrate that the proposed model's accuracy is higher than state-of-the-art prediction models at approximately 99.70%.

• Journal of the Ergonomics Society of Korea
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• v.24 no.3
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• pp.43-52
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• 2005

A two-dimensional posture measurement system was developed to evaluate the risks of work-related musculoskeletal disorders(MSDs) easily on various conditions of work. The posture measurement system is an essential tool to analyze the workload for preventing work-related musculoskeletal disorders. Although several posture measurement systems have been developed for workload assessment, some restrictions in industry still exist because of its difficulty on measuring work postures. In this study, an image recognition algorithm was developed based on a neural network method to measure work posture. Each joint angle of human body was automatically measured from the recognized images through the algorithm, and the measurement system makes it possible to evaluate the risks of work-related musculoskeletal disorders easily on various working conditions. The validation test on upper body postures was carried out to examine the accuracy of the measured joint angle data from the system, and the results showed good measuring performance for each joint angle. The differences between the joint angles measured directly and the angles measured by posture measurement software were not statistically significant. It is expected that the result help to properly estimate physical workload and can be used as a postural analysis system to evaluate the risk of work-related musculoskeletal disorders in industry.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.7
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• pp.1628-1634
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• 2011

With the advancement of ubiquitous computing technology, u-Healthcare (i.e. ubiquitous health care), is regarded as a key application for information society, which provides health management service at anytime in anywhere. To implement U-Healthcare system, it is essential to monitor stable biological information in daily life. In this paper, we proposed a small size, light weight, patch type real time temperature monitoring system based on wireless sensor network (WSN) technology to monitor patients' body temperature without any inconvenience of activity.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.5 no.1
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• pp.35-40
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• 2011

In this paper, we analyze that co-channel interference mitigation algorithms MMSE (Minimum Mean Square Error), OC (Optimal Combining), ML (Maximum Likelihood) using 2.4Ghz in WBAN (Wireless Body Area Network) system. Also analyze that scenario and channel model by IEEE 802.15.6. ML gives the best performance for all simulation. ML and OC have high complexity than MMSE complexity, because these algorithms should be known channel information of interference users. So these algorithms are difficult to apply to WBAN. Therefore we will study the interference mitigation algorithm that should be accomplished trade-off of between efficiency and complexity.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1641-1644
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• 2005

Magnetic actuation utilizes the mechanic torque that is the result of interaction of the current in a coil with an external magnetic field. A main obstacle is, however, that torques can only be produced perpendicular to the magnetic field. In addition, there is uncertainty in the Earth magnetic field models due to the complicated dynamic nature of the field. Also, the magnetic hardware and the spacecraft can interact, causing both to behave in undesirable ways. This actuation principle has been a topic of research since earliest satellites were launched. Earlier magnetic control has been applied for nutation damping for gravity gradient stabilized satellites, and for velocity decrease for satellites without appendages. The three axes of a micro-satellite can be stabilized by using an electromagnetic actuator which is rigidly mounted on the structure of the satellite. The actuator consists of three mutually-orthogonal air-cored coils on the skin of the satellite. The coils are excited so that the orbital frame magnetic field and body frame magnetic field coincides i.e. to make the Euler angles to zero. This can be done using a Neural Network controller trained by PD controller data and driven by the difference between the orbital and body frame magnetic fields.

• The Journal of Korea Robotics Society
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• v.13 no.1
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• pp.38-44
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• 2018

In this paper, we propose Intelligent Driver Assistance System (I-DAS) for driver safety. The proposed system recognizes safety and danger status by analyzing blind spots that the driver cannot see because of a large angle of head movement from the front. Most studies use image pre-processing such as face detection for collecting information about the driver's head movement. This not only increases the computational complexity of the system, but also decreases the accuracy of the recognition because the image processing system dose not use the entire image of the driver's upper body while seated on the driver's seat and when the head moves at a large angle from the front. The proposed system uses a convolutional neural network to replace the face detection system and uses the entire image of the driver's upper body. Therefore, high accuracy can be maintained even when the driver performs head movement at a large angle from the frontal gaze position without image pre-processing. Experimental result shows that the proposed system can accurately recognize the dangerous conditions in the blind zone during operation and performs with 95% accuracy of recognition for five drivers.

• Journal of Satellite, Information and Communications
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• v.8 no.2
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• pp.17-21
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• 2013

A building energy-saving have been increased worldwide interest. There is continuing research on IT technology for efficient management of BEMS. Recently, It is able to control of LED and to maximize energy savings to the development of LED lighting technology. We propose the security image processing system to improve efficiency and we implement the real-time status monitoring system to surveil the object in the building energy management system. In this paper, we proposed the system of LED control using Zigbee network for connect the server. User is able to control LED light and monitering by the desktop. We implemented LED light control software on the based of Real-time monitering and LED control. Also detect human body movement.

• Journal of information and communication convergence engineering
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• v.11 no.1
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• pp.7-11
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• 2013

Wearable computer systems use the wireless universal serial bus (WUSB), which refers to USB technology that is merged with WiMedia physical layer and medium access control layer (PHY/MAC) technical specifications. WUSB can be applied to wireless personal area network (WPAN) applications as well as wired USB applications such as PAN. WUSB specifications have defined high-speed connections between a WUSB host and WUSB devices for compatibility with USB 2.0 specifications. In this paper, we focus on an integrated system with a WUSB over an IEEE 802.15.6 wireless body area network (WBAN) for wireless wearable computer systems. Due to the portable and wearable nature of wearable computer systems, the WUSB over IEEE 802.15.6 hierarchical medium access control (MAC) protocol has to support power saving operations and integrate WUSB transactions with WBAN traffic efficiently. In this paper, we propose a low-power hibernation technique (LHT) for WUSB over IEEE 802.15.6 hierarchical MAC to improve its energy efficiency. Simulation results show that the LHT also integrates WUSB transactions and WBAN traffic efficiently while it achieves high energy efficiency.