• Title/Summary/Keyword: Commands

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Implementation of Speech Recognition and Flight Controller Based on Deep Learning for Control to Primary Control Surface of Aircraft

  • Hur, Hwa-La;Kim, Tae-Sun;Park, Myeong-Chul
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.9
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    • pp.57-64
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    • 2021
  • In this paper, we propose a device that can control the primary control surface of an aircraft by recognizing speech commands. The speech command consists of 19 commands, and a learning model is constructed based on a total of 2,500 datasets. The training model is composed of a CNN model using the Sequential library of the TensorFlow-based Keras model, and the speech file used for training uses the MFCC algorithm to extract features. The learning model consists of two convolution layers for feature recognition and Fully Connected Layer for classification consists of two dense layers. The accuracy of the validation dataset was 98.4%, and the performance evaluation of the test dataset showed an accuracy of 97.6%. In addition, it was confirmed that the operation was performed normally by designing and implementing a Raspberry Pi-based control device. In the future, it can be used as a virtual training environment in the field of voice recognition automatic flight and aviation maintenance.

Effects of Muscle Activity and Muscle Strength According to Verbal Command Volume in Isokinetic and Isometric Exercise of Quadriceps (넙다리네갈래근의 등속성 및 등척성 운동에서 구두명령 크기에 따른 근 활성도와 근력에 미치는 영향)

  • Lee, Hyoungsoo;Kim, Yoonhwan
    • Archives of Orthopedic and Sports Physical Therapy
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    • v.14 no.2
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    • pp.45-53
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    • 2018
  • Purpose: The purpose of this study was to investigate the effects of muscle activity and muscle strength according to verbal command volume during isokinetic and isometric quadricep exercises. Methods: To measure muscle activity and muscle strength, surface electrodes were attached to the participants, as they sat on a Biodex chair. The isometric exercise was performed three times, with maximum exercise at $30^{\circ}$ bending angle, based on a maximum extension state of the knee at $0^{\circ}$. The average holding time was unified to three seconds. In addition, the isokinetic exercise was performed three times, at $60^{\circ}/sec$. The verbal command ranged between 0∾60 dB and 0∾75 dB. Muscle activity was measured using surface electromyography (4D-MT, Relive, Gimhae, Korea). The Biodex System 4 was used to measure the isometric and isokinetic strength of the nodal line, and 4D-MT was used to measure muscle activity. Results: There were significant improvements in the maximal and relative muscle strengths, when the 0∾ 60 dB and 0∾75 dB verbal commands were applied with isokinetic extension/flexion (p<.05). The isokinetic exercise (0∾75 dB) group showed a significant difference in the vastus medialis oblique muscle activity change (p<.05), while the isometric exercise (0∾75 dB) group showed a significant difference in the rectus femoris muscle activity change (p<.05). Conclusions: Our results reveal that verbal commands effectively improve muscle activity and muscle strength during isokinetic and isometric quadricep exercises.

Design and Implementation of Facial Mask Wearing Monitoring System based on Open Source (오픈소스 기반 안면마스크 착용 모니터링 시스템 설계 및 구현)

  • Ku, Dong-Jin;Jang, Joon-Young
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.21 no.4
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    • pp.89-96
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    • 2021
  • The number of confirmed cases of coronavirus-19 is soaring around the world and has caused numerous deaths. Wearing a mask is very important to prevent infection. Incidents and accidents have occurred due to the recommendation to wear a mask in public places such as buses and subways, and it has emerged as a serious social problem. To solve this problem, this paper proposes an open source-based face mask wearing monitoring system. We used open source software, web-based artificial intelligence tool teachable machine and open source hardware Arduino. It judges whether the mask is worn, and performs commands such as guidance messages and alarms. The learning parameters of the teachable machine were learned with the optimal values of 50 learning times, 32 batch sizes, and 0.001 learning rate, resulting in an accuracy of 1 and a learning error of 0.003. We designed and implemented a mask wearing monitoring system that can perform commands such as guidance messages and alarms by determining whether to wear a mask using a web-based artificial intelligence tool teachable machine and Arduino to prove its validity.

A Study on the Improvement of Steering Command System through Accident Analysis of Azimuth thruster using STAMP Method

  • HyunDong Kim;SangHoon Lee;JeongMin Kim
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.9
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    • pp.149-158
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    • 2023
  • With the global paradigm shift towards climate change, the shipbuilding industry is also considering propulsion systems that utilize eco-friendly fuels various propulsion systems are gaining attention as a result. In conventional propulsion systems, typically consisting of propellers and rudders, have evolved into a diverse range of systems due to the development of a special propulsion system known as the azimuth thruster. While azimuth thrusters were previously commonly installed on tugboats, they are now extensively used on offshore plant operation ships equipped with dynamic positioning systems. However, these azimuth thrusters require different steering methods compared to conventional propulsion systems, leading to a significant learning curve for the crew members boarding such vessels. Furthermore the availability of education related to these special propulsion systems is limited. This study aims to analyze accidents caused by inadequate control of vessels equipped with azimuth thrusters using the STAMP technique. And it proposes the necessity of standard steering commands for the safe operation of vessels equipped with special propellers.

A real-time hybrid testing based on restart-loading technology for viscous damper

  • Guoshan Xu;Lichang Zheng;Bin Wu;Zhuangzhuang Ji;Zhen Wang;Ge Yang
    • Smart Structures and Systems
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    • v.32 no.6
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    • pp.349-358
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    • 2023
  • Real-Time Hybrid Testing (RTHT) requires the numerical substructure calculations to be completed within the defined integration time interval due to its real-time loading demands. For solving the problem, A Real-Time Hybrid Testing based on Restart-Loading Technology (RTHT-RLT) is proposed in this paper. In the proposed method, in case of the numerical substructure calculations cannot be completed within the defined integration time interval, the experimental substructure was returned back to the initial state statically. When the newest loading commands were calculated by the numerical substructure, the experimental substructure was restarted loading from the initial state to the newest loading commands so as to precisely disclosing the dynamic performance of the experimental substructure. Firstly, the methodology of the RTHT-RLT is proposed. Furthermore, the numerical simulations and experimental tests on one frame structure with a viscous damper are conducted for evaluating the feasibility and effectiveness of the proposed RTHT-RLT. It is shown that the proposed RTHT-RLT innovatively renders the nonreal-time refined calculation of the numerical substructure feasible for the RTHT. The numerical and experimental results show that the proposed RTHT-RLT exhibits excellent performance in terms of stability and accuracy. The proposed RTHT-RLT may have broad application prospects for precisely investigating the dynamic behavior of large and complex engineering structures with specific experimental substructure where a restarting procedure does not affect the relevant hysteretic response.

A Development of Robot Arm Direct Teaching System (로봇팔 직접 교시 시스템 개발)

  • Woong-Keun Hyun
    • The Journal of the Korea institute of electronic communication sciences
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    • v.19 no.1
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    • pp.85-92
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    • 2024
  • In this paper, we developed an intuitive teaching and control system that directly teaches a task by holding the tip of a robotic arm and moving it to a desired position. The developed system consists of a 6-axis force sensor that measures position and attitude forces at the tip of the robot arm, an algorithm for generating robot arm joint speed control commands based on the measured forces at the tip, and a self-made 6-axis robot arm and control system. The six-dimensional force/torque of the position posture of the robot arm operator steering the handler is detected by the force sensor attached to the handler at the leading edge and converted into velocity commands at the leading edge to control the 7-axis robot arm. The verification of the research method was carried out with a self-made 7-axis robot, and it was confirmed that the proposed force sensor-based robot end-of-arm control method operates successfully through experiments by teaching the operator to adjust the handler.

LockPickFuzzer: Exploring Vulnerabilities in Android Lock Screen Mechanisms through ADB-Based Fuzzing (LockPickFuzzer: ADB 기반 퍼징 기법을 활용한 안드로이드 잠금 화면 메커니즘의 취약점 탐색)

  • Daehoon Ko;Hyoungshick Kim
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.34 no.4
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    • pp.651-666
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    • 2024
  • Android devices employ lock screens with various authentication methods to protect user data. However, even with the lock screen active, the device can be accessed via the Android Debug Bridge(ADB), a powerful development tool that controls devices connected through USB. In this paper, we explore methods to bypass the lock screen security mechanism by leveraging the characteristics of ADB. To achieve this, we analyze ADB commands to categorize those that can severely impact the Android system and propose LockPickFuzzer, a fuzzing test tool that automatically explores ways to combine these commands to disable lock screen security. To demonstrate LockPickFuzzer's ability to detect security vulnerabilities using ADB, we conducted experiments on the Galaxy S23 and Pixel 8, both running Android 14. The results revealed two ADB command combinations that could either steal authentication information or bypass the lock screen. We submitted a report on these discovered vulnerabilities to the Samsung security team and received official acknowledgment (SVE-2023-1344) from Samsung Electronics for one ADB command combination that can be reproduced on user devices. LockPickFuzzer is a practical tool that operates automatically without user intervention and is expected to contribute to the effective detection of security vulnerabilities caused by ADB command combinations on Android devices.

A Network Storage LSI Suitable for Home Network

  • Lim, Han-Kyu;Han, Ji-Ho;Jeong, Deog-Kyoon
    • JSTS:Journal of Semiconductor Technology and Science
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    • v.4 no.4
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    • pp.258-262
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    • 2004
  • Storage over Ethernet (SoE) is a network storage architecture that allows direct attachment of existing ATA/ATAPI devices to Ethernet without a separate server. Unlike SAN, no server computer intervenes between the storage and the client hosts. We propose a SoE disk controller (SoEDC) amenable to low-cost, single-chip implementation that processes a simplified L3/L4 protocol and converts commands between Ethernet and ATA/ATAPI, while the rest of the complex tasks are performed by the remote hosts. Thanks to simple architecture and protocol, the SoEDC implemented on a single $4mm{\times}4mm$ chip in 0.18um CMOS technology achieves maximum throughput of 55MB/s on Gigabit Ethernet, which is comparable to that of a high-performance disk storage locally attached to a host computer.

Seismic Data Analysis using the R (R을 이용한 지진자료 처리)

  • Chung, Tae-Woong;Lees, Jonathan M.;Yoon, Suk-Yung
    • Geophysics and Geophysical Exploration
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    • v.11 no.4
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    • pp.379-384
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    • 2008
  • R is a free software for statical computing and graphics. It compiles and runs not only on UNIX platforms but MS Windows. The R commands are easy and offer interactive help. R is used in extensive field by implementing packages. RSEIS, the package of R, enable us to do easy graphic process of seismic data. Here we illustrate an example of the seismic data process using RSEIS.

Demand Controller Management System using Power Line Modem (전력선 모뎀을 이용한 최대 수요전력 관리 시스템)

  • Kim, Soo-Gon;Lim, Byung-Kuk;Lee, Won-Sun;Jeon, Hee-Jong
    • Proceedings of the KIEE Conference
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    • 2002.07b
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    • pp.1067-1070
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    • 2002
  • The maximum demand power management system(the demand controller) is an equipment for demand management. If the pre-estimated load is over the preset power, the demand controller make warnings and break the load circuit according to predefined priority. Then consumption power is maintained below the maximum demand power level. The DTU receives the control commands from demand controller, and then controls loads. In this paper, the power line cables are used for communication between the demand controller and DTUs and monitoring PC. The experiments show that the proposed system is compatible with the conventional system, and feasible for new or remodeling plant.

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