• Earthquakes and Structures
• /
• v.10 no.5
• /
• pp.1067-1087
• /
• 2016

In this paper, a decoupled proportional-integral-derivative (PID) control approach for seismic control of smart structures is presented. First, the state space equation of a structure is transformed into modal coordinates and parameters of the modal PID control are separately designed in a reduced modal space. Then, the feedback gain matrix of the controller is obtained based on the contribution of modal responses to the structural responses. The performance of the controller is investigated to adjust control force of piezoelectric friction dampers (PFDs) in a benchmark base isolated building. In order to tune the modal feedback gain of the controller, a suitable trade-off among the conflicting objectives, i.e., the reduction of maximum modal base displacement and the maximum modal floor acceleration of the smart base isolated structure, as well as the maximum modal control force, is created using a multi-objective cuckoo search (MOCS) algorithm. In terms of reduction of maximum base displacement and story acceleration, numerical simulations show that the proposed method performs better than other reported controllers in the literature. Moreover, simulation results show that the PFDs are able to efficiently dissipate the input excitation energy and reduce the damage energy of the structure. Overall, the proposed control strategy provides a simple strategy to tune the control forces and reduces the number of sensors of the control system to the number of controlled stories.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.20 no.10
• /
• pp.3173-3185
• /
• 1996

Multi-model vibration control of laminated composites plates for various fiver orientations has been carried out by making use of piezolectric materials(PZT) as sensors and actuators. Cantilever plate is used as a specimen to test multi-modal vibration supression under random exitation. Impulse technique is applied to determine the natural frequency, the damping ratio(.zeta.) and the modal damping(2.zeta..omega.) of the first bending and the trosion modes. Two independent controllers are implemented to control the two modes simultaneously and established digitally on the basis of the direct negative velocity feedback control with collocated sensor/actuator. Experimental results for various fiber orientations and feedback gains are compared with finite element analysis considering stiffnesses and dampings of piezoeletiric sensors, actuators and bonding layer.

• Journal of Digital Convergence
• /
• v.12 no.2
• /
• pp.321-326
• /
• 2014

The needs for IT accessibility for disabled persons has increased for recent years. So, it is very important to support multi-modal interfaces, such as voice and vision recognition, TTS, etc. for disabled persons. In this paper, we deal with IT accessibility issues of home networks and show our implemented home network control system model with multi-modal interfaces including voice recognition and animated user interfaces.

• Journal of KSNVE
• /
• v.8 no.4
• /
• pp.632-642
• /
• 1998

A method based on finite element discretization is developed for optimizing the polarization profile of PVDF film to create the modal transducer for specific modes. Using this concept, one can design the modal transducer in two-dimensional structure having arbitrary geometry and boundary conditions. As a practical means for implementing this polarization profile without repoling the PVDF film the polarization profile is approximated by optimizing electrode patterns, lamination angles, and poling directions of the multi-layered PVDF transducer. This corresponds to the approximation of a continuous function using discrete values. The electrode pattern of each PVDF layer is optimized by deciding the electrode of each finite element to be used or not. Genetic algorithm, suitable for discrete problems, is used as an optimization scheme. For the optimization of each layers lamination angle, the continuous lamination angle is encoded into discrete value using binary 5 bit string. For the experimental demonstration, a modal sensor for first and second modes of cantilevered composite plate is designed using two layers of PVDF films. The actuator is designed based on the criterion of minimizing the system energy in the control modes under a given initial condition. Experimental results show that the signals from residual modes are successfully reduced using the optimized multi-layered PVDF sensor. Using discrete LQG control law, the modal peaks of first and second modes are reduced in the amount of 12 dB and 4 dB, resepctively.

• Journal of Korea Multimedia Society
• /
• v.13 no.6
• /
• pp.924-932
• /
• 2010

This paper proposes a multi-modal complex motion authoring tool for creating robot contents. The proposed tool is user-friendly and allows general users without much knowledge about robots, including children, women and the elderly, to easily edit and modify robot contents. Furthermore, the tool uses multi-modal data including graphic motion, voice and music to simulate user-created robot contents in the 3D virtual environment. This allows the user to not only view the authoring process in real time but also transmit the final authored contents to control the robot. The validity of the proposed tool was examined based on simulations using the authored multi-modal complex motion robot contents as well as experiments of actual robot motions.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.17 no.2
• /
• pp.93-100
• /
• 2022

In this paper, we propose a machine learning-based method for supporting resource management of IoT software platforms in a multi-modal sensing scenario. We assume that an IoT device installed with a oneM2M-compatible software platform is connected with various sensors such as PIR, sound, dust, ambient light, ultrasonic, accelerometer, through different embedded system interfaces such as general purpose input output (GPIO), I2C, SPI, USB. Based on a collected dataset including CPU usage and user-defined priority, a machine learning model is trained to estimate the level of nice value required to adjust according to the resource usage patterns. The proposed method is validated by comparing with a rule-based control strategy, showing its practical capability in a multi-modal sensing scenario of IoT devices.

• The Journal of Korean Academy of Orthopedic Manual Physical Therapy
• /
• v.26 no.2
• /
• pp.19-27
• /
• 2020

Background: The purpose of this study was to examine the effects of a multi-modal exercise program for patients with chronic low back with respect to pain intensity, trunk muscle strength and Oswestry disability index. Methods: Thirty patients with chronic low back pain were recruited and divided equally into two groups. The multi-modal training program comprised a series of exercises such as warm-up, stabilization exercises, stretching, endurance exercises, and cool down whereas the control group performed only stabilization exercises. The both group spent an equal amount of time performing 60 minutes per day, three times per week, for five weeks. Results: The experimental group demonstrated statistically significant improvements in range of motion, trunk muscle strength, the visual analogue scale, and the Oswestry Disability Index (p<.05). Intergroup comparison showed a statistically significant difference in the range of motion of the lumbar spine and the degree of disability in the experimental group. Muscle strength and pain were statistically significant in both groups. Conclusion: The multi-modal exercise program is effective for patients with chronic low back pain, as it reduces lower back pain, increases trunk muscles strength, and decrease the potential for becoming disabled.

• 제어로봇시스템학회:학술대회논문집
• /
• 1998.10a
• /
• pp.250-253
• /
• 1998

This paper presents a multi-modal neural network composed of a preprocessing module and a multi-layer neural network module in order to enhance the nonlinear characteristics of neural network. The former module is based on spectral method using Chebyschev polynomials and transforms input data into spectra. The latter module identifies the system using the spectra generated by the preprocessing module. The omnibus numerical experiments show that the method is applicable to many a nonlinear dynamic system in the real world, and that preprocessing using Chebyschev polynomials reduces the number of neurons required for the multi-layer neural network.

• Proceedings of the IEEK Conference
• /
• 1998.10a
• /
• pp.1289-1292
• /
• 1998

HCI(human computer interface) technologies have been often implemented using mouse, keyboard and joystick. Because mouse and keyboard are used only in limited situation, More natural HCI methods such as speech based method and gesture based method recently attract wide attention. In this paper, we present multi-modal input system to control Windows system for practical use of multi-media computer. Our multi-modal input system consists of three parts. First one is virtual-hand mouse part. This part is to replace mouse control with a set of gestures. Second one is Windows control system using speech recognition. Third one is Windows control system using gesture recognition. We introduce neural network and HMM methods to recognize speeches and gestures. The results of three parts interface directly to CPU and through Windows.

• Journal of the Ergonomics Society of Korea
• /
• v.32 no.6
• /
• pp.517-528
• /
• 2013

Objective: The objective of this study was to suggest a multi-modal controller type for Smart TV Control. Background: Recently, many issues regarding the Smart TV are arising due to the rising complexity of features in a Smart TV. One of the specific issues involves what type of controller must be utilized in order to perform regulated tasks. This study examines the ongoing trend of the controller. Method: The selected participants had experiences with the Smart TV and were 20 to 30 years of age. A pre-survey determined the first independent variable of five tasks(Live TV, Record, Share, Web, App Store). The second independent variable was the type of controllers(Conventional, Mouse, Voice-Based Remote Controllers). The dependent variables were preference, task completion time, and error rate. The experiment consist a series of three experiments. The first experiment utilized a uni-modal Controller for tasks; the second experiment utilized a dual-modal Controller, while the third experiment utilized a triple-modal Controller. Results: The first experiment revealed that the uni-modal Controller (Conventional, Voice Controller) showed the best results for the Live TV task. The second experiment revealed that the dual-modal Controller(Conventional-Voice, Conventional-Mouse combinations) showed the best results for the Share, Web, App Store tasks. The third experiment revealed that the triple-modal Controller among all the level had not effective compared with dual-modal Controller. Conclusion: In order to control simple tasks in a smart TV, our results showed that a uni-modal Controller was more effective than a dual-modal controller. However, the control of complex tasks was better suited to the dual-modal Controller. User preference for a controller differs according the Smart TV functions. For instance, there was a high user preference for the uni-Controller for simple functions while high user preference appeared for Dual-Controllers when the task was complex. Additionally, in accordance with task characteristics, there was a high user preference for the Voice Controller for channel and volume adjustment. Furthermore, there was a high user preference for the Conventional Controller for menu selection. In situations where the user had to input text, the Voice Controller had the highest preference among users while the Mouse Type, Voice Controller had the highest user preference for performing a search or selecting items on the menu. Application: The results of this study may be utilized in the design of a controller which can effectively carry out the various tasks of the Smart TV.