Search results for: Adaptive built environments

Authors: Mohd Sazli Saad, Hishamuddin Jamaluddin, Intan Zaurah Mat Darus

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This paper presents the development of an active vibration control using direct adaptive controller to suppress the vibration of a flexible beam system. The controller is realized based on linear parametric form. Differential evolution optimisation algorithm is used to optimize the controller using single objective function by minimizing the mean square error of the observed vibration signal. Furthermore, an alternative approach is developed to systematically search for the best controller model structure together with it parameter values. The performance of the control scheme is presented and analysed in both time and frequency domain. Simulation results demonstrate that the proposed scheme is able to suppress the unwanted vibration effectively.

Keywords: flexible beam, finite difference method, active vibration control, differential evolution, direct adaptive controller

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Authors: Siti Norul Huda Sheikh Abdullah, Farshid Pirahan Siah, Nor Hanisah Haji Zainal Abidin, Shahnorbanun Sahran

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The objective of this paper is to propose an adaptive multi threshold for image segmentation precisely in object detection. Due to the different types of license plates being used, the requirement of an automatic LPR is rather different for each country. The proposed technique is applied on Malaysian LPR application. It is based on Multi Layer Perceptron trained by back propagation. The proposed adaptive threshold is introduced to find the optimum threshold values. The technique relies on the peak value from the graph of the number object versus specific range of threshold values. The proposed approach has improved the overall performance compared to current optimal threshold techniques. Further improvement on this method is in progress to accommodate real time system specification.

Keywords: Multi-threshold approach, license plate recognition system.

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Authors: Chia-Hau Liu, Tai-Yue Wang

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Traditional multivariate control charts assume that measurement from manufacturing processes follows a multivariate normal distribution. However, this assumption may not hold or may be difficult to verify because not all the measurement from manufacturing processes are normal distributed in practice. This study develops a new multivariate control chart for monitoring the processes with non-normal data. We propose a mechanism based on integrating the one-class classification method and the adaptive technique. The adaptive technique is used to improve the sensitivity to small shift on one-class classification in statistical process control. In addition, this design provides an easy way to allocate the value of type I error so it is easier to be implemented. Finally, the simulation study and the real data from industry are used to demonstrate the effectiveness of the propose control charts.

Keywords: Multivariate control chart, statistical process control, one-class classification method.

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Authors: Seyed Sadegh Naseralavi, Najmeh Bemani

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In this paper, different concrete codes including America, New Zealand, Mexico, Italy, India, Canada, Hong Kong, Euro Code and Britain are compared with the Iranian concrete design code. First, by using Adaptive Neuro Fuzzy Inference System (ANFIS), the codes having the most correlation with the Iranian ninth issue of the national regulation are determined. Consequently, two anticipated methods are used for comparing the codes: Artificial Neural Network (ANN) and Multi-variable regression. The results show that ANN performs better. Predicting is done by using only tensile steel ratio and with ignoring the compression steel ratio.

Keywords: Concrete design code, anticipate method, artificial neural network, multi-variable regression, adaptive neuro fuzzy inference system.

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Authors: Sakshi Kausha, R.K Sharma

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High speed networks provide realtime variable bit rate service with diversified traffic flow characteristics and quality requirements. The variable bit rate traffic has stringent delay and packet loss requirements. The burstiness of the correlated traffic makes dynamic buffer management highly desirable to satisfy the Quality of Service (QoS) requirements. This paper presents an algorithm for optimization of adaptive buffer allocation scheme for traffic based on loss of consecutive packets in data-stream and buffer occupancy level. Buffer is designed to allow the input traffic to be partitioned into different priority classes and based on the input traffic behavior it controls the threshold dynamically. This algorithm allows input packets to enter into buffer if its occupancy level is less than the threshold value for priority of that packet. The threshold is dynamically varied in runtime based on packet loss behavior. The simulation is run for two priority classes of the input traffic – realtime and non-realtime classes. The simulation results show that Adaptive Partial Buffer Sharing (ADPBS) has better performance than Static Partial Buffer Sharing (SPBS) and First In First Out (FIFO) queue under the same traffic conditions.

Keywords: Buffer Management, Consecutive packet loss, Quality-of-Service, Priority based packet discarding, partial buffersharing.

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Authors: H. Mansor, S. B. Mohd Noor

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This paper presents a design method of self-tuning Quantitative Feedback Theory (QFT) by using improved deadbeat control algorithm. QFT is a technique to achieve robust control with pre-defined specifications whereas deadbeat is an algorithm that could bring the output to steady state with minimum step size. Nevertheless, usually there are large peaks in the deadbeat response. By integrating QFT specifications into deadbeat algorithm, the large peaks could be tolerated. On the other hand, emerging QFT with adaptive element will produce a robust controller with wider coverage of uncertainty. By combining QFT-based deadbeat algorithm and adaptive element, superior controller that is called selftuning QFT-based deadbeat controller could be achieved. The output response that is fast, robust and adaptive is expected. Using a grain dryer plant model as a pilot case-study, the performance of the proposed method has been evaluated and analyzed. Grain drying process is very complex with highly nonlinear behaviour, long delay, affected by environmental changes and affected by disturbances. Performance comparisons have been performed between the proposed self-tuning QFT-based deadbeat, standard QFT and standard dead-beat controllers. The efficiency of the self-tuning QFTbased dead-beat controller has been proven from the tests results in terms of controller’s parameters are updated online, less percentage of overshoot and settling time especially when there are variations in the plant.

Keywords: Deadbeat control, quantitative feedback theory (QFT), robust control, self-tuning control.

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Authors: Omid Sojodishijani, Saeed Ebrahimijam, Vahid Rostami

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This paper presents an optimized algorithm for robot localization which increases the correctness and accuracy of the estimating position of mobile robot to more than 150% of the past methods [1] in the uncertain and noisy environment. In this method the odometry and vision sensors are combined by an adapted well-known discrete kalman filter [2]. This technique also decreased the computation process of the algorithm by DKF simple implementation. The experimental trial of the algorithm is performed on the robocup middle size soccer robot; the system can be used in more general environments.

Keywords: Discrete Kalman filter, odometry sensor, omnidirectional vision sensor, Robot Localization.

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Authors: Usman Ghani

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Feedback is a vital element for improving student learning in a simulation-based training as it guides and refines learning through scaffolding. A number of studies in literature have shown that students’ learning is enhanced when feedback is provided with personalized tutoring that offers specific guidance and adapts feedback to the learner in a one-to-one environment. Thus, emulating these adaptive aspects of human tutoring in simulation provides an effective methodology to train individuals. This paper presents the results of a study that investigated the effectiveness of automating different types of feedback techniques such as Knowledge-of-Correct-Response (KCR) and Answer-Until- Correct (AUC) in software simulation for learning basic information technology concepts. For the purpose of comparison, techniques like simulation with zero or no-feedback (NFB) and traditional hands-on (HON) learning environments are also examined. The paper presents the summary of findings based on quantitative analyses which reveal that the simulation based instructional strategies are at least as effective as hands-on teaching methodologies for the purpose of learning of IT concepts. The paper also compares the results of the study with the earlier studies and recommends strategies for using feedback mechanism to improve students’ learning in designing and simulation-based IT training.

Keywords: Simulation, feedback, training, hands-on, labs.

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Authors: Reza Hassanpour, Asadollah Shahbahrami, Stephan Wong

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Skin color based tracking techniques often assume a static skin color model obtained either from an offline set of library images or the first few frames of a video stream. These models can show a weak performance in presence of changing lighting or imaging conditions. We propose an adaptive skin color model based on the Gaussian mixture model to handle the changing conditions. Initial estimation of the number and weights of skin color clusters are obtained using a modified form of the general Expectation maximization algorithm, The model adapts to changes in imaging conditions and refines the model parameters dynamically using spatial and temporal constraints. Experimental results show that the method can be used in effectively tracking of hand and face regions.

Keywords: Face detection, Segmentation, Tracking, Gaussian Mixture Model, Adaptation.

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Authors: Florin Leon, Silvia Curteanu

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Developing complete mechanistic models for polymerization reactors is not easy, because complex reactions occur simultaneously; there is a large number of kinetic parameters involved and sometimes the chemical and physical phenomena for mixtures involving polymers are poorly understood. To overcome these difficulties, empirical models based on sampled data can be used instead, namely regression methods typical of machine learning field. They have the ability to learn the trends of a process without any knowledge about its particular physical and chemical laws. Therefore, they are useful for modeling complex processes, such as the free radical polymerization of methyl methacrylate achieved in a batch bulk process. The goal is to generate accurate predictions of monomer conversion, numerical average molecular weight and gravimetrical average molecular weight. This process is associated with non-linear gel and glass effects. For this purpose, an adaptive sampling technique is presented, which can select more samples around the regions where the values have a higher variation. Several machine learning methods are used for the modeling and their performance is compared: support vector machines, k-nearest neighbor, k-nearest neighbor and random forest, as well as an original algorithm, large margin nearest neighbor regression. The suggested method provides very good results compared to the other well-known regression algorithms.

Keywords: Adaptive sampling, batch bulk methyl methacrylate polymerization, large margin nearest neighbor regression, machine learning.

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Authors: Jhu-Wei Ji, Fa-Shian Chang, Lih-Tyng Hwang, Chih-Feng Liu, Jeng-Nan Lee, Shun-Min Wang, Kai-Yi Cho

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This paper presents a tracked robot with blade arms powered to assist movement in difficult environments. As a result, the tracked robot is able to pass a ramp or climb stairs. The main feature is a pair of blade arms on both sides of the vehicle body working in collaboration with previously validated transformable track system. When the robot encounters an obstacle in a terrain, it enlists the blade arms with power to overcome the obstacle. In disaster areas, there usually will be terrains that are full of broken and complicated slopes, broken walls, rubbles, and ditches. Thereupon, a robot, which is instructed to pass through such disaster areas, needs to have a good off-road capability for such complicated terrains. The robot with crawling-assisting blade arms would overcome the obstacles along the terrains, and possibly become to be a rescue robot. A prototype has been developed and built; experiments were carried out to validate the enhanced crawling capability of the robot.

Keywords: Tracked robot, rescue robot, blade arm, crawling ability, control system.

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Authors: S. Leghmizi, S. Liu, F. Naeim

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This paper presents a fuzzy control system for a three degree of freedom (3-DOF) stabilized platform with explicit decoupling scheme. The system under consideration is a system with strong interactions between three channels. By using the concept of decentralized control, a control structure is developed that is composed of three control loops, each of which is associated with a single-variable fuzzy controller and a decoupling unit. Takagi-Sugeno (TS) fuzzy control algorithm is used to implement the fuzzy controller. The decoupling units design is based on the adaptive theory reasoning. Simulation tests were established using Simulink of Matlab. The obtained results have demonstrated the feasibility and effectiveness of the proposed approach. Simulation results are represented in this paper.

Keywords: 3-DOF platform of a ship carried antenna, the concept of decentralized control, Takagi-Sugeno (TS) fuzzy control algorithm, Simulink.

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Authors: Karoliina Nisula, Samuli Pekkola

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Business education has been criticized for being too theoretical and distant from business life. Different types of experiential learning environments ranging from manual role-play to computer simulations and enterprise resource planning (ERP) systems have been used to introduce the realistic and practical experience into business learning. Each of these learning environments approaches business learning from a different perspective. The implementations tend to be individual exercises supplementing the traditional courses. We suggest combining them into a business skills laboratory resembling an actual workplace. In this paper, we present a concrete implementation of an ERP-supported business learning environment that is used throughout the first year undergraduate business curriculum. We validate the implementation by evaluating the learning outcomes through the different domains of Bloom’s taxonomy. We use the role-play oriented practice enterprise model as a comparison group. Our findings indicate that using the ERP simulation improves the poor and average students’ lower-level cognitive learning. On the affective domain, the ERP-simulation appears to enhance motivation to learn as well as perceived acquisition of practical hands-on skills.

Keywords: Business simulations, experiential learning, ERP systems, learning environments.

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Authors: Amnach Khawne, Kazuhiko Hamamoto, Orachat Chitsobhuk

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Most of the image watermarking methods, using the properties of the human visual system (HVS), have been proposed in literature. The component of the visual threshold is usually related to either the spatial contrast sensitivity function (CSF) or the visual masking. Especially on the contrast masking, most methods have not mention to the effect near to the edge region. Since the HVS is sensitive what happens on the edge area. This paper proposes ultrasound image watermarking using the visual threshold corresponding to the HVS in which the coefficients in a DCT-block have been classified based on the texture, edge, and plain area. This classification method enables not only useful for imperceptibility when the watermark is insert into an image but also achievable a robustness of watermark detection. A comparison of the proposed method with other methods has been carried out which shown that the proposed method robusts to blockwise memoryless manipulations, and also robust against noise addition.

Keywords: Medical image watermarking, Human Visual System, Image Adaptive Watermark

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Authors: Syed Musharaf Ali, Muhammad Younus Javed, Naveed Sarfraz Khattak

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In this paper we introduced new wavelet based algorithm for speckle reduction of synthetic aperture radar images, which uses combination of undecimated wavelet transformation, wiener filter (which is an adaptive filter) and mean filter. Further more instead of using existing thresholding techniques such as sure shrinkage, Bayesian shrinkage, universal thresholding, normal thresholding, visu thresholding, soft and hard thresholding, we use brute force thresholding, which iteratively run the whole algorithm for each possible candidate value of threshold and saves each result in array and finally selects the value for threshold that gives best possible results. That is why it is slow as compared to existing thresholding techniques but gives best results under the given algorithm for speckle reduction.

Keywords: Brute force thresholding, directional smoothing, direction dependent mask, undecimated wavelet transformation.

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Authors: A. Larabi, M. S. Boucherit

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In this paper, we show that the association of the PI regulators for the speed and stator currents with a control strategy using the linearization by state feedback for an induction machine without speed sensor, and with an adaptation of the rotor resistance. The rotor speed is estimated by using the model reference adaptive system approach (MRAS). This method consists of using two models: The first is the reference model and the second is an adjustable one in which two components of the stator flux, obtained from the measurement of the currents and stator voltages are estimated. The estimated rotor speed is then obtained by canceling the difference between stator-flux of the reference model and those of the adjustable one. Satisfactory results of simulation are obtained and discussed in this paper to highlight the proposed approach.

Keywords: Asynchronous actuator, PI Regulator, adaptivemethod with reference model, Vector control.

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Authors: Chidentree Treesatayapun

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A direct adaptive controller for a class of unknown nonlinear discrete-time systems is presented in this article. The proposed controller is constructed by fuzzy rules emulated network (FREN). With its simple structure, the human knowledge about the plant is transferred to be if-then rules for setting the network. These adjustable parameters inside FREN are tuned by the learning mechanism with time varying step size or learning rate. The variation of learning rate is introduced by main theorem to improve the system performance and stabilization. Furthermore, the boundary of adjustable parameters is guaranteed through the on-line learning and membership functions properties. The validation of the theoretical findings is represented by some illustrated examples.

Keywords: Neuro-Fuzzy, learning algorithm, nonlinear discrete time.

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Authors: Stefan Rass

Abstract:

Quantum cryptography offers a way of key agreement, which is unbreakable by any external adversary. Authentication is of crucial importance, as perfect secrecy is worthless if the identity of the addressee cannot be ensured before sending important information. Message authentication has been studied thoroughly, but no approach seems to be able to explicitly counter meet-in-the-middle impersonation attacks. The goal of this paper is the development of an authentication scheme being resistant against active adversaries controlling the communication channel. The scheme is built on top of a key-establishment protocol and is unconditionally secure if built upon quantum cryptographic key exchange. In general, the security is the same as for the key-agreement protocol lying underneath.

Keywords: Meet-in-the-middle attack, quantum key distribution, quantum networks, unconditionally secure authentication.

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Authors: Amir Rastegarnia, Mohammad Ali Tinati, Azam Khalili

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In this paper we consider the issue of distributed adaptive estimation over sensor networks. To deal with more realistic scenario, different variance for observation noise is assumed for sensors in the network. To solve the problem of different variance of observation noise, the proposed method is divided into two phases: I) Estimating each sensor-s observation noise variance and II) using the estimated variances to obtain the desired parameter. Our proposed algorithm is based on a diffusion least mean square (LMS) implementation with linear combiner model. In the proposed algorithm, the step-size parameter the coefficients of linear combiner are adjusted according to estimated observation noise variances. As the simulation results show, the proposed algorithm considerably improves the diffusion LMS algorithm given in literature.

Keywords: Adaptive filter, distributed estimation, sensor network, diffusion.

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Authors: U. Gudaru, D. R. Patil

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Electrical distribution systems are incurring large losses as the loads are wide spread, inadequate reactive power compensation facilities and their improper control. A comprehensive static VAR compensator consisting of capacitor bank in five binary sequential steps in conjunction with a thyristor controlled reactor of smallest step size is employed in the investigative work. The work deals with the performance evaluation through analytical studies and practical implementation on an existing system. A fast acting error adaptive controller is developed suitable both for contactor and thyristor switched capacitors. The switching operations achieved are transient free, practically no need to provide inrush current limiting reactors, TCR size minimum providing small percentages of nontriplen harmonics, facilitates stepless variation of reactive power depending on load requirement so as maintain power factor near unity always. It is elegant, closed loop microcontroller system having the features of self regulation in adaptive mode for automatic adjustment. It is successfully tested on a distribution transformer of three phase 50 Hz, Dy11, 11KV/440V, 125 KVA capacity and the functional feasibility and technical soundness are established. The controller developed is new, adaptable to both LT & HT systems and practically established to be giving reliable performance.

Keywords: Binary Sequential switched capacitor bank, TCR, Nontriplen harmonics, step less Q control, transient free

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Authors: C. I. Abiodun, S. O. Azi, J. S. Ojo, P. Akinyemi

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The design of accurate and reliable mobile communication systems depends majorly on the suitability of path loss prediction methods and the adaptability of the methods to various environments of interest. In this research, the results of the adaptability of radio channel behavior are presented based on practical measurements carried out in the 1800 MHz frequency band. The measurements are carried out in typical urban, suburban and rural environments in Ekiti State, Southwestern part of Nigeria. A total number of seven base stations of MTN GSM service located in the studied environments were monitored. Path loss and break point distances were deduced from the measured received signal strength (RSS) and a practical path loss model is proposed based on the deduced break point distances. The proposed two slope model, regression line and four existing path loss models were compared with the measured path loss values. The standard deviations of each model with respect to the measured path loss were estimated for each base station. The proposed model and regression line exhibited lowest standard deviations followed by the Cost231-Hata model when compared with the Erceg Ericsson and SUI models. Generally, the proposed two-slope model shows closest agreement with the measured values with a mean error values of 2 to 6 dB. These results show that, either the proposed two slope model or Cost 231-Hata model may be used to predict path loss values in mobile micro cell coverage in the well-considered environments. Information from this work will be useful for link design of microwave band wireless access systems in the region.

Keywords: Break-point distances, path loss models, path loss exponent, received signal strength.

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Authors: S. Yessengabulov, A. Uyzbayeva

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Residential buildings fund of Kazakhstan was built in the Soviet time about 35-60 years ago without considering energy efficiency measures. Currently, most of these buildings are in a rundown condition and fail to meet the minimum of hygienic, sanitary and comfortable living requirements. The paper aims to examine the reports of recent building energy survey activities in the country and provide a possible solution for retrofitting existing housing stock built before 1989 which could be applicable for building envelope in cold climate. Methodology also includes two-dimensional modeling of possible practical solutions and further recommendations.

Keywords: Energy audit, energy efficient buildings in Kazakhstan, retrofit, two-dimensional conduction heat transfer analysis

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Authors: Slim Yacoub, Kosai Raoof

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The aim of this study was to remove the two principal noises which disturb the surface electromyography signal (Diaphragm). These signals are the electrocardiogram ECG artefact and the power line interference artefact. The algorithm proposed focuses on a new Lean Mean Square (LMS) Widrow adaptive structure. These structures require a reference signal that is correlated with the noise contaminating the signal. The noise references are then extracted : first with a noise reference mathematically constructed using two different cosine functions; 50Hz (the fundamental) function and 150Hz (the first harmonic) function for the power line interference and second with a matching pursuit technique combined to an LMS structure for the ECG artefact estimation. The two removal procedures are attained without the use of supplementary electrodes. These techniques of filtering are validated on real records of surface diaphragm electromyography signal. The performance of the proposed methods was compared with already conducted research results.

Keywords: Surface EMG, Adaptive, Matching Pursuit, Powerline interference.

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Authors: M. Saidi, I. Djefour, F. Ait Medjber, A. Melouane, A. Gacem

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The objective of this research is to study the physical and mechanical properties and durability of self-compacting mortars prepared by substituting a part of cement up to a percentage of 30% pozzolan according to different Blaine specific surface area (SSB1=7000 cm²/g and SSB=9000 cm²/g)). Order to evaluate durability, mortars were subjected to chemical attacks in various aggressive environments, a solution of a mixture of nitric acid and ammonium nitrate (HNO₃ + NH₄NO₃) and a magnesium sulfate salt solution (MgSO₄)) with a concentration of 10%, for a period of one month. This study is complemented by a comparative study of the durability of mortars elaborated with sulphate resistant cement (SRC). The results show that these mortars develop long-term, mechanical and chemical resistance better than mortars based Portland cement with 5% gypsum (CEM 1) and SRC. We found that the mass losses are lowest in mortars elaborated with pozzolanic cement (30% substitution with SSB₂) in both of chemical attack solutions (3.28% in the solution acid and 1.16% in the salt solution) and the compressive strength gains of 14.68% and 8.5% respectively in the two media. This is due to the action of pozzolan which fixes portlandite to form hydrated calcium silicate (CSH) from the hydration of tricalcic silicate (C₃S).

Keywords: Aggressive environments, durability, mechanical strengths, pozzolanic cement, self-compacting mortar.

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Authors: Guosheng Wu, Luning Wang, Changyuan Fan, Xi Zhu

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This paper provides a new approach to solve the motion planning problems of flying robots in uncertain 3D dynamic environments. The robots controlled by this method can adaptively choose the fast way to avoid collision without information about the shapes and trajectories of obstacles. Based on sphere coordinates the new method accomplishes collision avoidance of flying robots without any other auxiliary positioning systems. The Self-protection System gives robots self-protection abilities to work in uncertain 3D dynamic environments. Simulations illustrate the validity of the proposed method.

Keywords: Collision avoidance, Mobile robots, Motion-planning, Sphere coordinates, Self-protection.

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Authors: Muhammad Sajjad, Naveed Khattak, Noman Jafri

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World has entered in 21st century. The technology of computer graphics and digital cameras is prevalent. High resolution display and printer are available. Therefore high resolution images are needed in order to produce high quality display images and high quality prints. However, since high resolution images are not usually provided, there is a need to magnify the original images. One common difficulty in the previous magnification techniques is that of preserving details, i.e. edges and at the same time smoothing the data for not introducing the spurious artefacts. A definitive solution to this is still an open issue. In this paper an image magnification using adaptive interpolation by pixel level data-dependent geometrical shapes is proposed that tries to take into account information about the edges (sharp luminance variations) and smoothness of the image. It calculate threshold, classify interpolation region in the form of geometrical shapes and then assign suitable values inside interpolation region to the undefined pixels while preserving the sharp luminance variations and smoothness at the same time. The results of proposed technique has been compared qualitatively and quantitatively with five other techniques. In which the qualitative results show that the proposed method beats completely the Nearest Neighbouring (NN), bilinear(BL) and bicubic(BC) interpolation. The quantitative results are competitive and consistent with NN, BL, BC and others.

Keywords: Adaptive, digital image processing, imagemagnification, interpolation, geometrical shapes, qualitative &quantitative analysis.

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Authors: Hamza Nejib, Okba Taouali

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This paper presents two of the most knowing kernel adaptive filtering (KAF) approaches, the kernel least mean squares and the kernel recursive least squares, in order to predict a new output of nonlinear signal processing. Both of these methods implement a nonlinear transfer function using kernel methods in a particular space named reproducing kernel Hilbert space (RKHS) where the model is a linear combination of kernel functions applied to transform the observed data from the input space to a high dimensional feature space of vectors, this idea known as the kernel trick. Then KAF is the developing filters in RKHS. We use two nonlinear signal processing problems, Mackey Glass chaotic time series prediction and nonlinear channel equalization to figure the performance of the approaches presented and finally to result which of them is the adapted one.

Keywords: KLMS, online prediction, KAF, signal processing, RKHS, Kernel methods, KRLS, KLMS.

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Authors: Yunyong Guo, Man Wang, Bryan Guo, Nathan Guo

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This paper presents an advanced security and privacy model tailored for Telehealth systems, emphasizing end-to-end protection across IoT, Fog, and Cloud components. The proposed model integrates encryption, key management, intrusion detection, and privacy-preserving measures to safeguard patient data. A comprehensive simulation study evaluates the model's effectiveness in scenarios such as unauthorized access, physical breaches, and insider threats. Results indicate notable success in detecting and mitigating threats yet underscore areas for refinement. The study contributes insights into the intricate balance between security and usability in Telehealth environments, setting the stage for continued advancements.

Keywords: Cloud, enhancing security, Fog, IoT, telehealth.

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Authors: Amran Mohd Zaid, M. Atif Yaqub, Mohd Rizal Arshad, Md Saidin Wahab

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A multi fingered dexterous anthropomorphic hand is being developed by the authors. The focus of the hand is the replacement of human operators in hazardous environments and also in environments where zero tolerance is observed for the human errors. The robotic hand will comprise of five fingers (four fingers and one thumb) each having four degrees of freedom (DOF) which can perform flexion, extension, abduction, adduction and also circumduction. For the actuation purpose pneumatic muscles and springs will be used. The paper exemplifies the mechanical design for the robotic hand. It also describes different mechanical designs that have been developed before date.

Keywords: Robotic hand, Multi-fingered hand, dextrous hand, anthropomorphic hand, pneumatic muscles.

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Authors: Jenn-Yih Chen, Bean-Yin Lee, Yuan-Chuan Hsu, Jui-Cheng Lin, Kuang-Chyi Lee

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In this paper, a sliding mode control method based on the passivity approach is proposed to control the position of surface-mounted permanent magnet synchronous motors (PMSMs). Firstly, the dynamics of a PMSM was proved to be strictly passive. The position controller with an adaptive law was used to estimate the load torque to eliminate the chattering effects associated with the conventional sliding mode controller. The stability analysis of the overall position control system was carried out by adopting the passivity theorem instead of Lyapunov-type arguments. Finally, experimental results were provided to show that the good position tracking can be obtained, and exhibit robustness in the variations of the motor parameters and load torque disturbances.

Keywords: Adaptive law, passivity theorem, permanent magnet synchronous motor, sliding mode control.

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