• Transactions of the Korean Society of Mechanical Engineers B
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• v.41 no.2
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• pp.125-133
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• 2017

This paper presents the inter-rater reliability of finger spasticity assessment tested realized by using finger simulator that mimics finger spasticity of patients after a stroke. For controlling the simulator torque, finger spasticity was modeled, and the model parameters were obtained by measuring quantitative data while grading based on Modified Ashworth Scale (MAS). A robotic finger simulator was designed for mimicking finger spasticity. Evaluation of this simulator with the help of seven rehabilitation doctors showed that the simulator had a Cohen's kappa value of 0.619 for Metacarpophalangeal Joint and 0.514 for Proximal Interphalangeal Joint. Fleiss' kappa between raters is 0.513 for Metacarpophalangeal Joint and 0.486 for Proximal Interphalangeal Joint. Therefore, the spasticity assessment made by MAS grade system is not reliable owing to the subjectivity of the assessment. The proposed robotic simulator can be used as a training tool for improving the reliability of the spasticity assessment.

• International Journal of Advanced Culture Technology
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• v.7 no.1
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• pp.231-236
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• 2019

Background/Objectives: This paper proposes a dual mode feedback-controlled cycling system for children with spastic cerebral palsy to rehabilitate upper extremities. Repetitive upper limb exercise in this therapy aims to both reduce and analyze the abnormal torque patterns of arm movements in three- dimensional space. Methods/Statistical analysis: We designed an exercycle robot which consists of a BLDC motor, a torque sensor, a bevel gear and bearings. Mechanical structures are customized for children of age between 7~13 years old and induces reaching and pulling task in a symmetric circulation. The shafts and external frames were designed and printed using 3D printer. While the child performs active/passive exercise, angular position, angular velocity, and relative torque of the pedal shaft are measured and displayed in real time. Findings: Experiment was designed to observe the features of a cerebral palsy child's exercise. Two children with bilateral spastic cerebral palsy participated in the experiment and conducted an active exercise at normal speed for 3 sets, 15 seconds for each. As the pedal reached 90 degrees and 270 degrees, the subject showed minimum torque, in which the child showed difficulty in the pulling task of the cycle. The passive exercise assisted the child to maintain a relatively constant torque while visually observing the movement patterns. Using two types of exercise enabled the child to overcome the abnormal torque measured in the active data by performing the passive exercise. Thus, this system has advantage not only in allowing the child to perform the difficult task, which may contribute in improving the muscle strength and endurance and reducing the spasticity but also provide customizable system according to the child's motion characteristic. Improvements/Applications: Further study is needed to observe how passive exercise influences the movement characteristics of an active motion and how customized experiment settings can optimize the effect of pediatric rehabilitation for spastic cerebral palsy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1310-1316
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• 2021

Recently, with the development of artificial intelligence and IoT technology, the importance of video processing such as object tracking, medical imaging, and object recognition is increasing. In particular, the noise reduction technology used in the preprocessing process demands the ability to effectively remove noise and maintain detailed features as the importance of system images increases. In this paper, we provide a modified weight filter based on pixel matching in an AWGN environment. The proposed algorithm uses a pixel matching method to maintain high-frequency components in which the pixel value of the image changes significantly, detects areas with highly relevant patterns in the peripheral area, and matches pixels required for output calculation. Classify the values. The final output is obtained by calculating the weight according to the similarity and spatial distance between the matching pixels with the center pixel in order to consider the edge component in the filtering process.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.34 no.12
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• pp.13-20
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• 2018

This research is to analyze the public cases of information facilities in terms of central circulations in multi level volumes such as atrium or court which provide visual intervention between different spaces and physical connections such as bridges. Hunt Library design balances the understood pre-existing needs with the University's emerging needs to create a forward-thinking learning environment. While clearly a contemporary structure within a traditional context of the NCSU campus, the Hunt Library provides a positive platform for influencing its surroundings. Both technical and programmatic innovations are celebrated as part of the learning experience and provide a versatile and stimulating environment for students. Public library as open spaces connecting to an interactive social domain over communities can provide variety of learning environments, or technology based labs. There are many cases of the public information spaces with dynamic networks where participants can play their roles in physical space as well as in the intellectual stimulation. In the research, new public projects provide typologies of information spaces with user oriented media. The research is to address a creative transition between the reading space and the experimental links of the integration of state-of-the-art technology is highly visible in the building's design. The user-friendly browsing system that replaces the traditional browsing with the virtual shelves classified and archived by their form, is to reduce the storage space of the public library and it is to allow more space for collaborative learning. In addition to the intelligent robot of information storages, innovative features is the large-scale visualization space that supports team experiments to carry out collaborative online works and therefore the public library's various programs is to provide visitors with more efficient participatory environment.

• Journal of the Korea Institute of Building Construction
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• v.20 no.6
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• pp.537-543
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• 2020

The window cleaning works are manpower-dependent and are performed in an unstable posture at high altitude, so that there is a risk of falling. Therefore, there is an urgent need to improve the safety of workers. In this study, a conceptual design was proposed for the cleaning of exterior windows of a building, and the economic feasibility of the proposed conceptual model was analyzed. The proposed model is designed to avoid protrusions such as window frames, and to be able to respond even if the shapes of the upper and lower parts are different. As a result of analyzing the economic feasibility of the designed conceptual model, the benefit cost ratio was 4.48, which was significantly higher than 1. Therefore, the economic feasibility of the proposed window cleaning device is expected to be sufficient. The results analyzed in this paper will be used in the development and marketing of the window cleaning device.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.177-179
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• 2022

In the Google Deepmind Challenge match, Alphago defeated Korea's Sedol Lee (human) with 4 wins and 1 loss in the Go match. Finally, artificial intelligence is going beyond the use of human intelligence. The Korean government's budget for the Digital New Deal is 9 trillion won in 2022, and an additional 301 types of data construction projects for artificial intelligence learning will be secured. From 2023, the industrial paradigm will change with the use and application of learning of artificial intelligence in all fields of industry. This paper conducts research to utilize artificial intelligence algorithms. Focusing on the analysis and judgment of data in artificial intelligence learning, research on the appropriate target and scope of application of algorithms in artificial intelligence machine learning and deep learning learning is conducted. This study will provide basic data for artificial intelligence in the 4th industrial revolution technology and artificial intelligence robot use in the 5th industrial revolution technology.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.2
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• pp.160-167
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• 2023

This study focuses on the development of a Last-Mile delivery service using unmanned vehicles to deliver goods directly to the end consumer utilizing drones to perform autonomous delivery missions and an image-based precision landing algorithm for handoff to a robot in an intermediate facility. As the logistics market continues to grow rapidly, parcel volumes increase exponentially each year. However, due to low delivery fees, the workload of delivery personnel is increasing, resulting in a decrease in the quality of delivery services. To address this issue, the research team conducted a study on a Last-Mile delivery service using unmanned vehicles and conducted research on the necessary technologies for drone-based goods transportation in this paper. The flight scenario begins with the drone carrying the goods from a pickup location to the rooftop of a building where the final delivery destination is located. There is a handoff facility on the rooftop of the building, and a marker on the roof must be accurately landed upon. The mission is complete once the goods are delivered and the drone returns to its original location. The research team developed a mission planning algorithm to perform the above scenario automatically and constructed an algorithm to recognize the marker through a camera sensor and achieve a precision landing. The performance of the developed system has been verified through multiple trial operations within ETRI.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1530-1544
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• 2023

Data monitoring is an important foundation of modern science. In most cases, the monitoring data is time-series data, which has high application value. The deep learning algorithm has a strong nonlinear fitting capability, which enables the recognition of time series by capturing anomalous information in time series. At present, the research of time series recognition based on deep learning is especially important for data monitoring. Deep learning algorithms require a large amount of data for training. However, abnormal sample is a small sample in time series, which means the number of abnormal time series can seriously affect the accuracy of recognition algorithm because of class imbalance. In order to increase the number of abnormal sample, a data augmentation method called GANBATS (GAN-based Bi-LSTM and Attention for Time Series) is proposed. In GANBATS, Bi-LSTM is introduced to extract the timing features and then transfer features to the generator network of GANBATS.GANBATS also modifies the discriminator network by adding an attention mechanism to achieve global attention for time series. At the end of discriminator, GANBATS is adding averagepooling layer, which merges temporal features to boost the operational efficiency. In this paper, four time series datasets and five data augmentation algorithms are used for comparison experiments. The generated data are measured by PRD(Percent Root Mean Square Difference) and DTW(Dynamic Time Warping). The experimental results show that GANBATS reduces up to 26.22 in PRD metric and 9.45 in DTW metric. In addition, this paper uses different algorithms to reconstruct the datasets and compare them by classification accuracy. The classification accuracy is improved by 6.44%-12.96% on four time series datasets.

• The Journal of Bigdata
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• v.7 no.1
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• pp.37-47
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• 2022

Autonomous delivery operation data is the key to driving a paradigm shift for last-mile delivery in the Corona era. To bridge the technological gap between domestic autonomous delivery robots and overseas technology-leading countries, large-scale data collection and verification that can be used for artificial intelligence training is required as the top priority. Therefore, overseas technology-leading countries are contributing to verification and technological development by opening AI training data in public data that anyone can use. In this paper, 326 objects were collected to trainn autonomous delivery robots, and artificial intelligence models such as Mask r-CNN and Yolo v3 were trained and verified. In addition, the two models were compared based on comparison and the elements required for future autonomous delivery robot research were considered.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.677-682
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• 2023

A large number of motors and sensors are used to drive a humanoid robot. In order to solve the wiring problem that occurs when connecting multiple actuators, a controller based on a communication network has been used, and CAN, which is advantageous in terms of cost and a highly reliable communication protocol, was mainly used. In terms of the structure of the controller, a torque control type structure that is easy to implement an advanced algorithm into the upper controller is preferred. In this case, the low communication bandwidth of CAN becomes a problem, and in order to obtain sufficient communication bandwidth, a communication network is configured by separating into a plurality of CAN networks. In this study, a stability analysis on transmission time delay is performed for a multi-motor control system in which high-speed FlexRay and low-speed CAN communication networks are hierarchically connected in order to obtain a high communication bandwidth, and sensor information and driving signals are delivered within the allowed transmission time. The proposed hierarchical network-based control system is expected to improve control performance because it can implement multiple motor control systems with a single network.