• KIPS Transactions on Software and Data Engineering
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• v.6 no.1
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• pp.37-44
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• 2017

While IoT (Internet of Things) industry has been spreading, it becomes very important for object to recognize user's information by itself without any control. Above all, gender (male, female) is dominant factor to analyze user's information on account of social and biological difference between male and female. However since each gender consists of diverse face feature, face-based gender classification research is still in challengeable research field. Also to apply gender classification system to IoT, size of device should be reduced and device should be operated with low power. Consequently, To port the function that can classify gender in real-world, this paper contributes two things. The first one is new gender classification algorithm based on deep learning and the second one is to implement real-time gender classification system in embedded board operated by low power. In our experiment, we measured frame per second for gender classification processing and power consumption in PC circumstance and mobile GPU circumstance. Therefore we verified that gender classification system based on deep learning works well with low power in mobile GPU circumstance comparing to in PC circumstance.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.2
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• pp.124-133
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• 2009

CANopen which is one of the in-vehicle network (IVN) protocols is adopted to solve the hardware dependency problem of the CAN-based application. CANopen makes different CAN devices interoperable each others. By the advantage of the device profiling concept, it can make the period of developing CAN-based application system shorten. The utilization of CANopen network must be reduced to improve the communication performance (e.g. worst-case response time). For reducing network utilization, messages need to be packed as many as possible so that message frame overhead can be decreased. In this paper, we suggested a PDO packing mechanism using object dictionary (OD) and process data object (PDO) communication service in CANopen. Through experiments, the performance of the mechanism is evaluated with SAE benchmark. As a result, network utilization is decreased about 10% compared to the result of the previous works.

• Transactions of the Society of Information Storage Systems
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• v.2 no.2
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• pp.130-137
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• 2006

The HDD(hard disk drive) using Load/unload(L/UL) technology includes the benefits which are increased areal density, reduced power consumption and improved shock resistance than those of contact-start-stop(CSS). It has been widely used in portable hard disk drive and will become the key technology for developing the small form factor hard disk drive. The main objects of L/UL are no slider-disk contact or no media damage. For realizing those, we must consider many design parameters in L/UL system. In this paper, we focus on lift-off force. The 'lift-off' force, defined as the minimum air bearing force, is another very important indicator of unloading performance. A large amplitude of lift-off force increases the ramp force, the unloading time, the slider oscillation and contact-possibility. To minimize 'lift-off' force we optimizes the slider and suspension using the integrated optimization frame, which automatically integrates the analysis with the optimization and effectively implements the repetitive works between them. In particular, this study is carried out the optimal design considering the process of modes tracking through the entire optimization processes. As a result, we yield the equation which can easily find a lift-off force and structural optimization for suspension.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.26 no.6_spc
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• pp.644-650
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• 2016

Track maintenance works based on track geometry recordings are essential to enhance the safety and comfort of railway transportation. Usually, the track irregularity has been measured by a special inspection trains which all were imported from abroad. Because the inspection train speed is limited under 160 km/h, it takes a long time to inspect railways and there is difficulty in daytime operation. To solve this problem, we started to develop a track geometry measuring system (TGMS) with measurement speed up to 300 km/h which can be installed in commercial vehicles such as HEMU-430X. In this paper, we introduce a newly developed inertial TGMS and propose two inertial navigation system (INS) algorithms (method A, B) for measuring track geometry. In order to investigate advantage and disadvantage of each algorithm, we performed vibration test of the TGMS, which was simulated by 6-axis shaking table. Through the vibration test, we analyzed the influence of vehicle vibration on the TGMS which will be installed on bogie frame. To the vibration test, two methods satisfied the required accuracy of track geometry measurement under the level of the actual vehicle vibration of HEMU-430X train. Theoretically, method A is sensitive to vehicle vibration than method B. However, HEMU-430X's bogie vibration frequency range is out of interest range of measurement system. Therefore, method A can also apply the HEMU-430X train.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.4002-4014
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• 2015

ITU-R M.1842-1, as a well-known specification dedicated to maritime mobile applications, has standardized wireless transmission protocols according to the particular characteristics of a maritime communications scenario. A time division multiple access (TDMA) frame structure, along with modulation schemes to achieve a high data rate, has been described clearly in ITU-R M.1842-1. However, several specification items are still under "to be decided" status, which brings ambiguity to research works. In addition, the current version of ITU-R M.1842-1 is focused mainly on maritime transmissions in open-sea areas, where the cyclic prefix (CP) is set to zero and only 16-QAM is used in the multi-carrier (MC) system. System performance might be dramatically degraded in coastline areas due to the inter-symbol interference (ISI) caused by selective fading. This is because there is a higher probability that the signal will be reflected by obstacles in coastline areas. In this paper, we introduce the transmission resource block (TRB) dedicated to ITU-R M.1842-1 for a ship ad-hoc network (SANET), where the pilot pattern of TRB is based on the terrestrial trunked radio (TETRA). After that, we evaluated SANET performance under the maritime channel model in a coastline area. In order to avoid noise amplification and to overcome the ISI caused by selective fading, several strategies are suggested and compared in the channel estimation and equalization procedures, where the link-level simulation results finally validate our proposals.

• Journal of Ocean Engineering and Technology
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• v.34 no.5
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• pp.361-370
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• 2020

We developed a heavy-duty work class ROV trencher named URI-T (Underwater robot it's trencher) that can conduct burial and maintenance tasks for underwater cables and small diameter pipelines. It requires various supporting systems, including a dynamic positioning (DP) vessel, launch and recovery system (LARS), A-frame, and winch in order to perform burial tasks because of its dimensions (6.5 m × 5.0 m × 4.5 m, 20 t) and the tough working environment. However, operating a DP vessel has disadvantages as it is expensive to rent and operate and it is difficult to adjust the working schedule for some domestic coast construction cases. In this paper, we propose a method using a barge instead of a DP vessel to avoid the above disadvantages. Although burying the cable and pipeline using a barge has lower working efficiency than a DP vessel, it can save construction expenses and does not require a large crew. The proposed method was applied over two months at the construction of the water supply in Yokji-do, and the results were verified.

• Journal of IKEEE
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• v.23 no.3
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• pp.777-784
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• 2019

A pre-fire awareness and automatic notification system are required because it is possible to minimize the damage if the fire situation is precisely detected after a fire occurs in a place where people are unusual or in a mountainous area. In this study, we developed a RaspberryPi-based fire recognition system using Faster-recurrent convolutional neural network (F-RCNN) and single shot multibox detector (SSD) and demonstrated a fire alarm system that works with power line communication. Image recognition was performed with a pie camera of RaspberryPi, and the detected fire image was transmitted to a monitoring PC through an inductive power line communication network. The frame rate per second (fps) for each learning model was 0.05 fps for Faster-RCNN and 1.4 fps for SSD. SSD was 28 times faster than F-RCNN.

• Journal of International Academy of Physical Therapy Research
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• v.12 no.1
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• pp.2261-2266
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• 2021

Background: Deep learning related research works on website medical images have been actively conducted in the field of health care, however, articles related to the musculoskeletal system have been introduced insufficiently, deep learning-based studies on classifying orthopedic manual therapy images would also just be entered. Objectives: To create a deep learning model that categorizes cervical mobilization images and establish a web application to find out its clinical utility. Design: Research and development. Methods: Three types of cervical mobilization images (central posteroanterior (CPA) mobilization, unilateral posteroanterior (UPA) mobilization, and anteroposterior (AP) mobilization) were obtained using functions of 'Download All Images' and a web crawler. Unnecessary images were filtered from 'Auslogics Duplicate File Finder' to obtain the final 144 data (CPA=62, UPA=46, AP=36). Training classified into 3 classes was conducted in Teachable Machine. The next procedures, the trained model source was uploaded to the web application cloud integrated development environment (https://ide.goorm.io/) and the frame was built. The trained model was tested in three environments: Teachable Machine File Upload (TMFU), Teachable Machine Webcam (TMW), and Web Service webcam (WSW). Results: In three environments (TMFU, TMW, WSW), the accuracy of CPA mobilization images was 81-96%. The accuracy of the UPA mobilization image was 43~94%, and the accuracy deviation was greater than that of CPA. The accuracy of the AP mobilization image was 65-75%, and the deviation was not large compared to the other groups. In the three environments, the average accuracy of CPA was 92%, and the accuracy of UPA and AP was similar up to 70%. Conclusion: This study suggests that training of images of orthopedic manual therapy using machine learning open software is possible, and that web applications made using this training model can be used clinically.

• Earthquakes and Structures
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• v.22 no.2
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• pp.185-201
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• 2022

Structural Health Monitoring (SHM) is used to provide reliable information about the structure's integrity in near realtime following extreme incidents such as earthquakes, considering the inevitable aging and degradation that occurs in operating environments. This paper experimentally investigates an integrated wireless sensor network (Wi-SN) based monitoring technique for damage detection in concrete structures. An effective SHM technique can be used to detect potential structural damage based on post-earthquake data. Two novel methods are proposed for damage detection in reinforced concrete (RC) building structures including: (i) Jerk Energy Method (JEM), which is based on time-domain analysis, and (ii) Modal Contributing Parameter (MCP), which is based on frequency-domain analysis. Wireless accelerometer sensors are installed at each story level to monitor the dynamic responses from the building structure. Prior knowledge of the initial state (immediately after construction) of the structure is not required in these methods. Proposed methods only use responses recorded during ambient vibration state (i.e., operational state) to estimate the damage index. Herein, the experimental studies serve as an illustration of the procedures. In particular, (i) a 3-story shear-type steel frame model is analyzed for several damage scenarios and (ii) 2-story RC scaled down (at 1/6th) building models, simulated and verified under experimental tests on a shaking table. As a result, in addition to the usual benefits like system adaptability, and cost-effectiveness, the proposed sensing system does not require a cluster of sensors. The spatial information in the real-time recorded data is used in global damage identification stage of SHM. Whereas in next stage of SHM, the damage is detected at the story level. Experimental results also show the efficiency and superior performance of the proposed measuring techniques.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1113-1116
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• 2009

The attempt to use a 3D model each field such as design, structure, construction, facilities, and estimation in the construction project has recently increased more and more while BIM (Building Information Modeling) that manages the process of generating and managing building data has risen during life cycle of a construction project. While the 2D Drawing based work of each field is achieved in the already existing construction project, the BIM based construction project aims at accomplishing 3D model based work of each field efficiently. Accordingly, the solution that fits 3D model based work of each field and supports plans in order to efficiently accomplish the relevant work is demanded. The estimation, one of the fields of the construction project, has applied BIM to calculate quantity and cost of the building materials used to construction works after taking off building quantity information from the 3D model by a item for a Quantity Take-off grouping the materials relevant to a 3D object. A 3D based estimation program has been commonly used in abroad advanced countries using BIM. The program can only calculate quantity related to one 3D object. In other words, it doesn't support the take-off process considering quantity of a contiguous object. In case of temporary materials used in the frame construction, there are instances where quantity is different by the contiguous object. For example, the formwork of the temporary materials quantity is changed by dimensions of the contiguous object because formwork of temporary materials goes through the quantity take-off process that deduces quantity of the connected object when different objects are connected. A worker can compulsorily adjust quantity so as to recognize the different object connected to the contiguous object and deduces quantity, but it mainly causes the confusion of work because it must complexly consider quantity of other materials related to the object besides. Therefore, this study is to propose the solution that automates the formwork 3D modeling to efficiently accomplish the quantity take-off of formwork by preventing the confusion of the work which is caused by the quantity deduction process between the contiguous object and the connected object.