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Department of Mechatronics and Robotics
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1.Computation of macro-fiber composite integrated thin-walled smart structures

Author:Zhang, SQ;Zhang, SY;Chen, M;Bai, J;Li, J


Abstract:Due to high flexibility, reliability, and strong actuation forces, piezo fiber based composite smart material, macro-fiber composite (MFC), is increasingly applied in various fields for vibration suppression, shape control, and health monitoring. The complexity arrangement of MFC materials makes them difficult in numerical simulations. This paper develops a linear electro-mechanically coupled finite element (FE) model for composite laminated thin-walled smart structures bonded with MFC patches considering arbitrary piezo fiber orientation. Two types of MFCs are considered, namely, MFC-d31 in which the d(31) effect dominates the actuation forces, and MFC-d33 which mainly uses the d(33) effect. The proposed FE model is validated by static analysis of an MFC bonded smart plate.

2.Automatic Building and Floor Classification using Two Consecutive Multi-layer Perceptron

Author:Cha, J;Lee, S;Kim, KS


Abstract:Key issues of indoor localization is taking full advantages and overcoming its disadvantages. indoor localization based on Wi-Fi fingerprinting attracts researchers' attentions since it does not require new infrastructure and devices. Many devices such as smart phones and laptops, which have a function to capture Wi-Fi signals, can be used for Wi-Fi fingerprinting. However, due to unreliable Wi-Fi signals, there are still difficulty to achieve high positioning accuracy. The unreliable signal disturbs devices to find their locations. As a result, getting localization with devices sometimes makes a wrong decision in building classification. It is useless for people to find a destination floor if they are in different building. In this paper, we propose two consecutive multi-layer perceptrons to get more precise localization. With sumple structure, we get better performance and show precise decision results in building classification, which is critical in Wi-Fi fingerprinting. We use UJIndoorLoc dataset which is open dataset.

3.Segregated Lightweight Dynamic Rate (SLDR) control scheme for efficient internet communications

Author:Ting,T. O.;Ting,H. C.;Lee,Sanghyuk

Source:Lecture Notes in Electrical Engineering,2013,Vol.235 LNEE

Abstract:This paper proposes an effective Segregated Lightweight Dynamic Rate Control Scheme (SLDRCS) over the internet. Based on the feedback analysis of the current approaches, we found that the indicator of the congestion is only the queue length. It only captures a partial indicator of delay and loss in feedback mechanism. This may result in an ineffective way in controlling the network when congestion control occurs. Therefore, we suggest multiple congestion indicators to adapt inside this scheme to fully control the average delay and loss from bidirectional of sender to receiver. The behavior of next event packet being control using discrete event simulation tool with First Come First Serve (FCFS) scheduling policy and we code this algorithm into C programming language. Through the simulation results, our Segregated Lightweight Dynamic Rate Control Scheme (SLDRCS) guaranteed high improvement in packet drop and average delay under various congestion level and traffic load conditions compare with the current approach. © 2013 Springer Science+Business Media Dordrecht.

4.Verifying Secure Authentication Protocol for Communication between IoT-based Medical Devices

Author:Theera-Umpon, N;Han, KH;Bae, WS;Lee, S;Pham, V


Abstract:The evolving Internet of Things (IoT) technology has driven the advancement of communication technology for implantable devices and relevant services. Still, concerns are raised over implantable medical devices (IMDs), because the wireless transmission section between patients and devices is liable to intrusions on privacy attributable to hacking attacks and resultant leakage of patients' personal information. Also, manipulating and altering patients' medical information may lead to serious leakage of personal information and thus adverse medical incidents. To address the foregoing challenges, the present paper proposes a security protocol that copes with a range of vulnerabilities in communication between IMDs and other devices. In addition, the proposed protocol encrypts the communication process and data to eliminate the likelihood of personal information being leaked. The verification highlights the safety and security of the proposed protocol in wireless communication.

5.XJTLUIndoorLoc: A New Fingerprinting Database for Indoor Localization and Trajectory Estimation Based on Wi-Fi RSS and Geomagnetic Field

Author:Zhong, ZH;Tang, Z;Li, XX;Yuan, TC;Yang, Y;Wei, M;Zhang, YY;Sheng, RZ;Grant, N;Ling, CF;Huan, XT;Kim, KS;Lee, S


Abstract:In this paper, we present a new location fingerprinting database comprised of Wi-Fi received signal strength (RSS) and geomagnetic field intensity measured with multiple devices at a multi-floor building in Xi'an Jiatong-Liverpool University, Suzhou, China. We also provide preliminary results of localization and trajectory estimation based on convolutional neural network (CNN) and long short-term memory (LSTM) network with this database. For localization, we map RSS data for a reference point to an image-like, two-dimensional array and then apply CNN which is popular in image and video analysis and recognition. For trajectory estimation, we use a modified random way point model to efficiently generate continuous step traces imitating human walking and train a stacked two-layer LSTM network with the generated data to remember the changing pattern of geomagnetic field intensity against (x, y) coordinates. Experimental results demonstrate the usefulness of our new database and the feasibility of the CNN and LSTMbased localization and trajectory estimation with the database.

6.Analysis of a Similarity Measure for Non-Overlapped Data

Author:Lee, S;Cha, J;Theera-Umpon, N;Kim, KS


Abstract:A similarity measure is a measure evaluating the degree of similarity between two fuzzy data sets and has become an essential tool in many applications including data mining, pattern recognition, and clustering. In this paper, we propose a similarity measure capable of handling non-overlapped data as well as overlapped data and analyze its characteristics on data distributions. We first design the similarity measure based on a distance measure and apply it to overlapped data distributions. From the calculations for example data distributions, we find that, though the similarity calculation is effective, the designed similarity measure cannot distinguish two non-overlapped data distributions, thus resulting in the same value for both data sets. To obtain discriminative similarity values for non-overlapped data, we consider two approaches. The first one is to use a conventional similarity measure after preprocessing non-overlapped data. The second one is to take into account neighbor data information in designing the similarity measure, where we consider the relation to specific data and residual data information. Two artificial patterns of non-overlapped data are analyzed in an illustrative example. The calculation results demonstrate that the proposed similarity measures can discriminate non-overlapped data.

7.EMG Pattern Classification by Split and Merge Deep Belief Network

Author:Shim, HM;An, H;Lee, S;Lee, EH;Min, HK;Lee, S


Abstract:In this paper; we introduce an enhanced electromyography (EMG) pattern recognition algorithm based on a split-and-merge deep belief network (SM-DBN). Generally, it is difficult to classify the EMG features because the EMG signal has nonlinear and time-varying characteristics. Therefore, various machine-learning methods have been applied in several previously published studies. A DBN is a fast greedy learning algorithm that can identify a fairly good set of weights rapidly-even in deep networks with a large number of parameters and many hidden layers. To reduce overfitting and to enhance performance, the adopted optimization method was based on genetic algorithms (GA). As a result, the performance of the SM-DBN was 12.06%% higher than conventional DBN. Additionally, SM-DBN results in a short convergence time, thereby reducing the training epoch. It is thus efficient in reducing the risk of overfitting. It is verified that the optimization was improved using GA.

8.Design and compensation of second-order sub-sampling digital frontend

Author:Wang, HM;Kim, JH;Lee, SH;Kim, HJ;Kim, JU;Koh, JS


Abstract:The problem of designing a digital frontend (DFE) was considered which can dynamically access or sense dual bands in any radio frequency (RF) regions without requiring hardware changes. In particular, second-order bandpass sampling (BPS) as a technique that enables to realize the multiband reception function was discussed. In a second-order BPS system, digital reconstruction filters were utilized to eliminate the interferences generated while down converting arbitrarily positioned RF-band signals by using the direct digitization method. However, the inaccuracy in the phase shift or the amplitude mismatch between the two sample streams may cause insufficient rejection of interference. Practical problems were studied, such as performance degradation in signal-to-interference ratio (SIR) and compensation methods to overcome them. In order to demonstrate the second-order BPS as a flexible DFE suitable for software-defined radio (SDR) or cognitive radio (CR), a DFE testbed with a reconfigurable structure was implemented. Moreover, with a view to further demonstrate the proposed compensation algorithms, experimental results show that dual bands are received simultaneously.

9.Design Similarity Measure and Application to Fault Detection of Lateral Directional Mode Flight System

Author:Park, W;Lee, S;Lee, S;Ting, TO


Abstract:In this work, we first obtained the similarity measures. The obtained similarity measures were designed based on well-known Hamming distance. It was also considered by analyzing the certainty and uncertainty of the fuzzy membership functions. The proposed similarity measure was applied to the fault detection of primary control surface stuck of Uninhabited Aerial Vehicle (UAV). At post-failure control surface, if the UAV has controllable and trimmable using other control surfaces, the UAV is able to fly or returns to the safety region through reconfiguration of the flight control system. By the calculation of similarity measure, result could be applicable with the real-time parameter estimation method. Furthermore, coefficients monitoring make it possible to monitor the occurrence of control surface fault. The obtained result has the advantage of increasing reliability without adding sensors or any additional cost.

10.Enhanced Protein Adsorption in Fibrous Substrates Treated with Zeolitic Imidazolate Framework-8 (ZIF-8) Nanoparticles

Author:Fu, H;Ou, PF;Zhu, J;Song, PF;Yang, JQ;Wu, Y


Abstract:Development for new solid substrates for protein adsorption is important, given the massive potential in a number of fields including food production, medicine, biotechnology, and pharmaceutical processing. We developed a zeolitic imidazolate framework 8 (ZIF-8)-nanoparticles based fibrous platform (Platform 1). Its ability in protein adsorption is proven by fluorescence study of Alexa Fluor 647-labeled donkey anti-rabbit IgG adsorbed on Platform 1. Studies reveal that Platform 1 shows much more enhanced protein adsorption compared to a polyethylene terephthalate gauze fibrous platform treated with ZIF-8 nanoparticles. This may be explained by considering that more active sites are enabled on fabric to adsorb a higher amount of ZIF-8 nanoparticles. We show that Platform 1 provides favorable biocompatibility to maintain the bioactivity of enzymes. Furthermore, we prove that a carboxymethylated cotton fabric platform treated with ZIF-8 (Platform 3) can be more capable of immobilizing the Alexa Fluor 647-labeled antibodies than Platform 1. Carboxymethylation helps to enhance protein adsorption in these cotton fabric substrates.

11.Influence of electrohydrodynamic jetting parameters on the morphology of PCL scaffolds

Author:Liu, H;Vijayavenkataraman, S;Wang, DD;Jing, LZ;Sun, J;He, K


Abstract:One of the important constituents in tissue engineering is scaffold, which provides structural support and suitable microenvironment for the cell attachment, growth and proliferation. To fabricate micro/nano structures for soft tissue repair and three-dimensional (3D) cell culture, the key is to improve fibre-based scaffold fabrication. Electrohydrodynamic (EHD) jetting is capable of producing and orientating submicron fibres for 3D scaffold fabrication. In this work, an EHD jetting system was developed to explore the relationship between vital processing parameters and fibre characteristics. In this study, polycaprolactone (PCL) solution prepared by dissolving PCL pellets in acetic acid was used to fabricate the scaffolds. The influence of voltage, motorized stage speed, solution feed rate, and solution concentration on fibre characteristics and scaffold pattern were studied. Morphology of the EHD jetted PCL fibres and scaffolds were analysed using optical microscope images and scanning electron microscope (SEM) images. Multi-layer scaffolds with the varied coiled pattern were fabricated and analysed. Cell attachment and proliferation have to be investigated in the future by further cell culture studies on these multi-layer coiled scaffolds.

12.Microscale scaffolds with diverse morphology via electrohydrodynamic jetting for in vitro cell culture application

Author:Wang, DD;Jing, LZ;Liu, H;Huang, DJ;Sun, J


Abstract:Microscale scaffolds have been intensively used in tissue engineering for cell culture. Traditionally, top-down approach like solvent casting, gas foaming and freeze drying to fabricate the scaffolds suffer from the drawback of variable microstructures of the scaffolds, pore sizes, and specific surface areas, which are important factors for reproducible cell culture application. To overcome these problems, bottom-up approach which builds up from single component has been preferred for manufacturing of scaffolds. One such technology is electrohydrodynamic jetting (EHDJ), which can produce controllable fiber diameter and orientation. Herein, we reported our progress on new design and printing of polycaprolactone (PCL) scaffolds with linear, serpentine, and hybrid structures. These are achieved by altering fabrication parameters using EHDJ technique. The three scaffolds exhibit high resolution and small pore structures suitable as support for 3D cell cultures as demonstrated by using fibroblast cells. Our results showed that although the hybrid scaffold has lower porosity than the line scaffold, more cells are found on the hybrid scaffold attributed to improved cell attachment and proliferation. Taken together, our results pave the road for design and printing of similar scaffolds with high resolution and precision controlled structural morphologies for in vitro cell culture and tissue engineering.

13.Space exploration of multi-agent robotics via genetic algorithm

Author:Ting,T. O.;Wan,Kaiyu;Man,Ka Lok;Lee,Sanghyuk

Source:Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),2012,Vol.7513 LNCS

Abstract:Robots play an important role in space exploration whereby the presence of human is almost impossible in some environments. Instead of using a robot, we incorporate a group of robots working together to achieve the definitive goal. Evolutionary algorithm, namely Genetic Algorithm is applied in the multi-agent robotics for space exploration. Hereby, the core focus of this paper is to study the effect of crossover rate upon the convergence of the exploration. As from our results, choosing the right parameter value is crucial for optimal coverage of the potential area. © IFIP International Federation for Information Processing 2012.

14.A Nanocellulose-Paper-Based SERS Multiwell Plate with High Sensitivity and High Signal Homogeneity

Author:Chen, LY;Ying, BB;Song, PF;Liu, XY


Abstract:Paper-based surface-enhanced Raman scattering (SERS) substrates have gained growing interest as an eco-friendly and low-cost tool for chemical and biosensing. However, paper-based SERS substrates often suffer relatively low signal spatial homogeneity because of their nonuniform hot-spot distribution. In this paper, a nanofibrillated cellulose paper (nanopaper) based SERS multiwell plate is developed for trace chemical detection with high sensitivity and high signal homogeneity. The SERS plate is fabricated from ultrasmooth (2,2,6,6-tetramethylpiperidin-1-yl)oxyl-oxidized NFC paper (TO-nanopaper) through wax-printing-based multiwell patterning followed by silver nanoparticle (AgNP) growth based on a successive ionic layer adsorption and reaction (SILAR) process. Taking advantage of the abundance of carboxyl groups on the TO-nanopaper, uniformly distributed and densely arranged AgNPs are successfully synthesized through the SILAR process on the NFC multiwell surface under ambient conditions. The SERS performance of the device is evaluated for testing two Raman marker chemicals, rhodamine B and 2-naphthalenethiol, and picomolar detection limit and high Raman enhancement factor (up to 1.46 x 10(9)) are achieved. The Raman signal mapping results show superior signal spatial homogeneity of the device with low variations (<= 11%%). The nanopaper-based SERS device represents a promising SERS platform for chemical and biomolecule detections with high sensitivity and high repeatability.

15.Power Spectral Deviation-Based Voice Activity Detection Incorporating Teager Energy for Speech Enhancement

Author:Kim, SK;Kang, SI;Park, YJ;Lee, S;Lee, S


Abstract:In this paper, we propose a robust voice activity detection (VAD) algorithm to effectively distinguish speech from non-speech in various noisy environments. The proposed VAD utilizes power spectral deviation (PSD), using Teager energy (TE) to provide a better representation of the PSD, resulting in improved decision performance for speech segments. In addition, the TE-based likelihood ratio and speech absence probability are derived in each frame to modify the PSD for further VAD. We evaluate the performance of the proposed VAD algorithm by objective testing in various environments and obtain better results that those attained by of the conventional methods.

16.Neural-Network-Based Building Energy Consumption Prediction with Training Data Generation

Author:Lee, S;Cha, J;Kim, MK;Kim, KS;Pham, VH;Leach, M


Abstract:The importance of neural network (NN) modelling is evident from its performance benefits in a myriad of applications, where, unlike conventional techniques, NN modeling provides superior performance without relying on complex filtering and/or time-consuming parameter tuning specific to applications and their wider ranges of conditions. In this paper, we employ NN modelling with training data generation based on sensitivity analysis for the prediction of building energy consumption to improve performance and reliability. Unlike our previous work, where insignificant input variables are successively screened out based on their mean impact values (MIVs) during the training process, we use the receiver operating characteristic (ROC) plot to generate reliable data with a conservative or progressive point of view, which overcomes the issue of data insufficiency of the MIV method: By properly setting boundaries for input variables based on the ROC plot and their statistics, instead of completely screening them out as in the MIV-based method, we can generate new training data that maximize true positive and false negative numbers from the partial data set. Then a NN model is constructed and trained with the generated training data using Levenberg-Marquardt back propagation (LM-BP) to perform electricity prediction for commercial buildings. The performance of the proposed data generation methods is compared with that of the MIV method through experiments, whose results show that data generation using successive and cross pattern provides satisfactory performance, following energy consumption trends with good phase. Among the two options in data generation, i.e., successive and two data combination, the successive option shows lower root mean square error (RMSE) than the combination one by around 400 similar to 900 kWh (i.e., 30%%similar to 75%%).

17.Interactive Tabletop Arm Reaching Exercise

Author:Zou, Y;Sun, J;Jin, YH;Bian, YX


Abstract:In order to regain motor control, stroke patients should do various exercises that target at specific body functions. During daily exercising, they need assistance from either therapists or caregivers in setting tasks, providing feedback and other activities. Due to aging population, the demand for technology support in stroke recovery has rapidly increased in last decade. This paper presents a portable and interactive prototype designed to facilitate arm reaching exercise. It consists of a tabletop device and a game map that serves as visual guidance on arm movements. This device also provides light and sound feedback while patients can choose different game modes. Preliminary user trials support the implementation of tangible interactive training in rehab centers and further inspire us on building a tabletop training system.

18.Fault Detection of Aircraft System with Random Forest Algorithm and Similarity Measure

Author:Lee, S;Park, W;Jung, S


Abstract:Research on fault detection algorithm was developed with the similarity measure and random forest algorithm. The organized algorithm was applied to unmanned aircraft vehicle (UAV) that was readied by us. Similarity measure was designed by the help of distance information, and its usefulness was also verified by proof. Fault decision was carried out by calculation of weighted similarity measure. Twelve available coefficients among healthy and faulty status data group were used to determine the decision. Similarity measure weighting was done and obtained through random forest algorithm (RFA); RF provides data priority. In order to get a fast response of decision, a limited number of coefficients was also considered. Relation of detection rate and amount of feature data were analyzed and illustrated. By repeated trial of similarity calculation, useful data amount was obtained.

19.Geometrically nonlinear analysis of CNT-reinforced functionally graded composite plates integrated with piezoelectric layers

Author:Zhang, SQ;Gao, YS;Zhao, GZ;Yu, YJ;Chen, M;Wang, XF


Abstract:The paper develops a geometrically nonlinear finite element model with large rotation based on the first-order shear deformation (FOSD) hypothesis for static and dynamic analyses of piezoelectric integrated carbon nanotube reinforced functionally graded (P-CNT-FG) composite structures. A constant electric field distribution through the thickness of plate is considered. An eight-node quadrilateral plate element with five mechanical degrees of freedom (DOFs) and one electric degree of freedom is developed for finite element analysis. Four typical forms of CNT distributions are included in the model, namely uniform, V-shaped, O-shaped, and X-shaped distributions. The nonlinear model considers fully geometrically nonlinear strain-displacement relations and large rotations of the shell direction of plate. Using the Hamilton's principle, a nonlinear dynamic model including dynamic and sensory equations is obtained. The proposed nonlinear model is validated by a frequency analysis of a simply supported P-CNT-FG composite plate. Furthermore, the effects of various parameters on the static and dynamic behavior are investigated, e.g. CNT-reinforcement orientation, CNT distribution, the number of laminate layers and volume fraction.


Author:PARK Keon-Woo;KIM Chul-Hwan;LEE Sang-Hyuk;RHEE Sang-Bong


Total 93 results found
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