Search results for: Adaptive fuzzy sliding mode control

Authors: Alexander A. Muravyov

Abstract:

A minimal complexity version of component mode synthesis is presented that requires simplified computer programming, but still provides adequate accuracy for modeling lower eigenproperties of large structures and their transient responses. The novelty is that a structural separation into components is done along a plane/surface that exhibits rigid-like behavior, thus only normal modes of each component is sufficient to use, without computing any constraint, attachment, or residual-attachment modes. The approach requires only such input information as a few (lower) natural frequencies and corresponding undamped normal modes of each component. A novel technique is shown for formulation of equations of motion, where a double transformation to generalized coordinates is employed and formulation of nonproportional damping matrix in generalized coordinates is shown.

Keywords: component mode synthesis, finite element models, transient response, nonproportional damping

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Authors: J. Lam, R. Chan

Abstract:

The adoption of e-learning in Hong Kong has been increasing rapidly in the past decade. To understand the e-learning experiences of the students, the School of Professional and Continuing Education of The University of Hong Kong conducted a survey. The survey aimed to collect students- experiences in using learning management system, their perceived e-learning advantages, barriers in e-learning and preferences in new e-learning development. A questionnaire with 84 questions was distributed in mid 2012 and 608 valid responds were received. The analysis results showed that the students found e-learning helpful to their study. They preferred interactive functions and mobile features. Blended learning mode, both face-to-face learning mode integrated with online learning and face-to-face learning mode supplemented with online resources, were preferred by the students. The results of experiences of Hong Kong students in e-learning provided a contemporary reference to the e-learning practitioners to understand the e-learning situation in Asia.

Keywords: E-learning, blended learning, learning experience, learning management system.

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Authors: Mahdi Hamzeh, Sied Mehdi Fakhraie, Caro Lucas

Abstract:

All practical real-time scheduling algorithms in multiprocessor systems present a trade-off between their computational complexity and performance. In real-time systems, tasks have to be performed correctly and timely. Finding minimal schedule in multiprocessor systems with real-time constraints is shown to be NP-hard. Although some optimal algorithms have been employed in uni-processor systems, they fail when they are applied in multiprocessor systems. The practical scheduling algorithms in real-time systems have not deterministic response time. Deterministic timing behavior is an important parameter for system robustness analysis. The intrinsic uncertainty in dynamic real-time systems increases the difficulties of scheduling problem. To alleviate these difficulties, we have proposed a fuzzy scheduling approach to arrange real-time periodic and non-periodic tasks in multiprocessor systems. Static and dynamic optimal scheduling algorithms fail with non-critical overload. In contrast, our approach balances task loads of the processors successfully while consider starvation prevention and fairness which cause higher priority tasks have higher running probability. A simulation is conducted to evaluate the performance of the proposed approach. Experimental results have shown that the proposed fuzzy scheduler creates feasible schedules for homogeneous and heterogeneous tasks. It also and considers tasks priorities which cause higher system utilization and lowers deadline miss time. According to the results, it performs very close to optimal schedule of uni-processor systems.

Keywords: Computational complexity, Deadline, Feasible scheduling, Fuzzy scheduling, Priority, Real-time multiprocessor systems, Robustness, System utilization.

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Authors: Mehran Garmehi, Yasser Mansouri

Abstract:

There are two paradigms proposed to provide QoS for Internet applications: Integrated service (IntServ) and Differentiated service (DiffServ).Intserv is not appropriate for large network like Internet. Because is very complex. Therefore, to reduce the complexity of QoS management, DiffServ was introduced to provide QoS within a domain using aggregation of flow and per- class service. In theses networks QoS between classes is constant and it allows low priority traffic to be effected from high priority traffic, which is not suitable. In this paper, we proposed a fuzzy controller, which reduced the effect of low priority class on higher priority ones. Our simulations shows that, our approach reduces the latency dependency of low priority class on higher priority ones, in an effective manner.

Keywords: QoS, Differentiated Service (DiffServ), FuzzyController, Delay.

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Authors: S.A.Ahmad, M.N.Taib, N.E.A.Khalid, R.Ahmad, H.Taib

Abstract:

The purpose of this research is to compare the original intra-oral digital dental radiograph images with images that are enhanced using a combination of image processing algorithms. Intraoral digital dental radiograph images are often noisy, blur edges and low in contrast. A combination of sharpening and enhancement method are used to overcome these problems. Three types of proposed compound algorithms used are Sharp Adaptive Histogram Equalization (SAHE), Sharp Median Adaptive Histogram Equalization (SMAHE) and Sharp Contrast adaptive histogram equalization (SCLAHE). This paper presents an initial study of the perception of six dentists on the details of abnormal pathologies and improvement of image quality in ten intra-oral radiographs. The research focus on the detection of only three types of pathology which is periapical radiolucency, widen periodontal ligament space and loss of lamina dura. The overall result shows that SCLAHE-s slightly improve the appearance of dental abnormalities- over the original image and also outperform the other two proposed compound algorithms.

Keywords: intra-oral dental radiograph, histogram equalization, sharpening, CLAHE.

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Authors: Hassan Haleh, Amin Ghaffari, Parisa Farahpour

Abstract:

Need for an appropriate system of evaluating students- educational developments is a key problem to achieve the predefined educational goals. Intensity of the related papers in the last years; that tries to proof or disproof the necessity and adequacy of the students assessment; is the corroborator of this matter. Some of these studies tried to increase the precision of determining question weights in scientific examinations. But in all of them there has been an attempt to adjust the initial question weights while the accuracy and precision of those initial question weights are still under question. Thus In order to increase the precision of the assessment process of students- educational development, the present study tries to propose a new method for determining the initial question weights by considering the factors of questions like: difficulty, importance and complexity; and implementing a combined method of PROMETHEE and fuzzy analytic network process using a data mining approach to improve the model-s inputs. The result of the implemented case study proves the development of performance and precision of the proposed model.

Keywords: Assessing students, Analytic network process, Clustering, Data mining, Fuzzy sets, Multi-criteria decision making, and Preference function.

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Authors: Hadi Veisi, Mansour Jamzad

Abstract:

In this paper we present an adaptive method for image compression that is based on complexity level of the image. The basic compressor/de-compressor structure of this method is a multilayer perceptron artificial neural network. In adaptive approach different Back-Propagation artificial neural networks are used as compressor and de-compressor and this is done by dividing the image into blocks, computing the complexity of each block and then selecting one network for each block according to its complexity value. Three complexity measure methods, called Entropy, Activity and Pattern-based are used to determine the level of complexity in image blocks and their ability in complexity estimation are evaluated and compared. In training and evaluation, each image block is assigned to a network based on its complexity value. Best-SNR is another alternative in selecting compressor network for image blocks in evolution phase which chooses one of the trained networks such that results best SNR in compressing the input image block. In our evaluations, best results are obtained when overlapping the blocks is allowed and choosing the networks in compressor is based on the Best-SNR. In this case, the results demonstrate superiority of this method comparing with previous similar works and JPEG standard coding.

Keywords: Adaptive image compression, Image complexity, Multi-layer perceptron neural network, JPEG Standard, PSNR.

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Authors: Steven W. Su , Hung Nguyen, Rob Jarman, Joe Zhu, David Lowe, Peter McLean, Shoudong Huang, Nghia T. Nguyen, Russell Nicholson, Kaili Weng

Abstract:

This paper proposed a nonlinear model predictive control (MPC) method for the control of gantry crane. One of the main motivations to apply MPC to control gantry crane is based on its ability to handle control constraints for multivariable systems. A pre-compensator is constructed to compensate the input nonlinearity (nonsymmetric dead zone with saturation) by using its inverse function. By well tuning the weighting function matrices, the control system can properly compromise the control between crane position and swing angle. The proposed control algorithm was implemented for the control of gantry crane system in System Control Lab of University of Technology, Sydney (UTS), and achieved desired experimental results.

Keywords: Model Predictive Control, Control constraints, Input nonlinearity compensation, Overhead gantry crane.

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Authors: Robert Gold

Abstract:

Control flow graphs are a well-known representation of the sequential control flow structure of programs with a multitude of applications. Not only single functions but also sets of functions or complete programs can be modeled by control flow graphs. In this case the size of the graphs can grow considerably and thus makes it difficult for software engineers to analyze the control flow. Graph reductions are helpful in this situation. In this paper we define reductions to subsets of nodes. Since executions of programs are represented by paths through the control flow graphs, paths should be preserved. Furthermore, the composition of reductions makes a stepwise analysis approach possible.

Keywords: Control flow graph, graph reduction.

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Authors: Gürol Önal, Ahmet Avcı

Abstract:

This paper presented the results of an experimental investigation into the axial fatigue behavior of a 5086 aluminum alloy which have several notch-aspect ratios a0/c0 and notch thickness ratio a/t with semi-elliptical surface cracks. Tests were conducted in la b air for stress levels of 50 % of their yield strength. Experiments were carried out for various notch to thickness ratios. Crack growth rates of test specimens both in surface and depth directions were determined by using die penetration method. Fuzzy Logic method was used to predict the deep direction crack growth because the dept of the crack is considerably difficult to measure.

Keywords: Axial fatigue, Crack growth rate, surface crack, Al-Mg alloy.

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Authors: Fanqiang Kong, Jindong Zhang, Daiyin Zhu

Abstract:

Space-time adaptive processing (STAP) techniques have been motivated as a key enabling technology for advanced airborne radar applications. In this paper, the notion of cognitive radar is extended to STAP technique, and cognitive STAP is discussed. The principle for improving signal-to-clutter ratio (SCNR) based on slow-time coding is given, and the corresponding optimization algorithm based on cyclic and power-like algorithms is presented. Numerical examples show the effectiveness of the proposed method.

Keywords: Space-time adaptive processing (STAP), signal-to-clutter ratio, slow-time coding.

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Authors: Zundong Zhang, Limin Jia, Yuanyuan Chai

Abstract:

Control of complex systems is one of important files in complex systems, that not only relies on the essence of complex systems which is denoted by the core concept – emergence, but also embodies the elementary concept in control theory. Aiming at giving a clear and self-contained description of emergence, the paper introduces a formal way to completely describe the formation and dynamics of emergence in complex systems. Consequently, this paper indicates the Emergence-Oriented Control methodology that contains three kinds of basic control schemes: the direct control, the system re-structuring and the system calibration. As a universal ontology, the Emergence-Oriented Control provides a powerful tool for identifying and resolving control problems in specific systems.

Keywords: Complex System Control, Emergence, Emergence- Oriented Control Methodology.

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Authors: Yang Weiping, Zhang Zhilong, Li Jicheng, Chen Zengping, He Jun

Abstract:

The background estimation approach using a small window median filter is presented on the bases of analyzing IR point target, noise and clutter model. After simplifying the two-dimensional filter, a simple method of adopting one-dimensional median filter is illustrated to make estimations of background according to the characteristics of IR scanning system. The adaptive threshold is used to segment canceled image in the background. Experimental results show that the algorithm achieved good performance and satisfy the requirement of big size image-s real-time processing.

Keywords: Point target, background estimation, median filter, adaptive threshold, target detection.

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Authors: Abdellatif Kasbi, Abderrafii Rahali

Abstract:

This paper appraises the performances of two control scenarios, for doubly fed induction generator (DFIG) operating in wind generation system (WGS), which are the direct decoupled control (DDC) and indirect decoupled control (IDC). Both control scenarios studied combines vector control and Maximum Power Point Tracking (MPPT) control theory so as to maximize the captured power through wind turbine. Modeling of DFIG based WGS and details of both control scenarios have been presented, a proportional integral controller is employed in the active and reactive power control loops for both control methods. The performance of the both control scenarios in terms of power reference tracking and robustness against machine parameters inconstancy has been shown, analyzed and compared, which can afford a reference to the operators and engineers of a wind farm. All simulations have been implemented via MATLAB/Simulink.

Keywords: DFIG, WGS, DDC, IDC, vector control, MPPT.

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Authors: Wenjuan Du

Abstract:

The phase compensation method was proposed based on the concept of the damping torque analysis (DTA). It is a method for the design of a PSS (power system stabilizer) to suppress local-mode power oscillations in a single-machine infinite-bus power system. This paper presents the application of the phase compensation method for the design of a PSS in a multi-machine power system. The application is achieved by examining the direct damping contribution of the stabilizer to the power oscillations. By using linearized equal area criterion, a theoretical proof to the application for the PSS design is presented. Hence PSS design in the paper is an example of stable tending control by localized method.

Keywords: Phase compensation method, power system small-signal stability, power system stabilizer.

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Authors: Rong Zhou, Shun’ich Kaneko, Fumio Tanaka, Miyuki Kayamori, Motoshige Shimizu

Abstract:

In this paper, we propose a robust disease detection method, called adaptive orientation code matching (Adaptive OCM), which is developed from a robust image registration algorithm: orientation code matching (OCM), to achieve continuous and site-specific detection of changes in plant disease. We use two-stage framework for realizing our research purpose; in the first stage, adaptive OCM was employed which could not only realize the continuous and site-specific observation of disease development, but also shows its excellent robustness for non-rigid plant object searching in scene illumination, translation, small rotation and occlusion changes and then in the second stage, a machine learning method of support vector machine (SVM) based on a feature of two dimensional (2D) xy-color histogram is further utilized for pixel-wise disease classification and quantification. The indoor experiment results demonstrate the feasibility and potential of our proposed algorithm, which could be implemented in real field situation for better observation of plant disease development.

Keywords: Cercospora Leaf Spot (CLS), Disease detection, Image processing, Orientation Code Matching (OCM), Support Vector Machine (SVM).

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Authors: Zaini Mohd-Zain, Mohd-Saufee A.F. Mohd-Ismail, Norlida Buniyamin

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Staphylococcus aureus, one of the microflora in a human external auditory canal (EAC) is frequently exposed to highfrequency electromagnetic field (HF-EMF) generated by mobile phones. It is normally non-pathogenic but in certain circumstances, it can cause infections. This study investigates the changes in the physiology of S. aureus when exposed to HF-EMF of a mobile phone. Exponentially grown S. aureus were exposed to two conditions of EMF irradiation (standby-mode and on-call mode) at four durations; 15, 30, 45 and 60 min. Changes in the viability and biofilm production of the S. aureus were compared between the two conditions of exposure. EMF from the standby-mode has enhanced the growth of S. aureus but during on-call, the growth was suppressed. No significant difference in the amount of biofilm produced in both modes of exposure was observed. Thus, HF-EMF of mobile phone affects the viability of S. aureus but not its ability to produce biofilm.

Keywords: Electromagnetic field, mobile phone, biofilm, Staphylococcus aureus

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Authors: Omar M. Elmabrouk., Roaa Y. Taha., Najat M. Ebrahim, Sabbreen A. Mohammed

Abstract:

Power transformers are the most crucial part of power electrical system, distribution and transmission grid. This part is maintained using predictive or condition-based maintenance approach. The diagnosis of power transformer condition is performed based on Dissolved Gas Analysis (DGA). There are five main methods utilized for analyzing these gases. These methods are International Electrotechnical Commission (IEC) gas ratio, Key Gas, Roger gas ratio, Doernenburg, and Duval Triangle. Moreover, due to the importance of the transformers, there is a need for an accurate technique to diagnose and hence predict the transformer condition. The main objective of this technique is to avoid the transformer faults and hence to maintain the power electrical system, distribution and transmission grid. In this paper, the DGA was utilized based on the data collected from the transformer records available in the General Electricity Company of Libya (GECOL) which is located in Benghazi-Libya. The Fuzzy Logic (FL) technique was implemented as a diagnostic approach based on IEC gas ratio method. The FL technique gave better results and approved to be used as an accurate prediction technique for power transformer faults. Also, this technique is approved to be a quite interesting for the readers and the concern researchers in the area of FL mathematics and power transformer.

Keywords: Fuzzy logic, dissolved gas-in-oil analysis, DGA, prediction, power transformer.

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Authors: Faith-Michael E. Uzoka, Boluwaji A. Akinnuwesi, Taiwo Amoo, Flora Aladi, Stephen Fashoto, Moses Olaniyan, Joseph Osuji

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The overarching aim of this study is to develop a soft-computing system for the differential diagnosis of tropical diseases. These conditions are of concern to health bodies, physicians, and the community at large because of their mortality rates, and difficulties in early diagnosis due to the fact that they present with symptoms that overlap, and thus become ‘confusable’. We report on the first phase of our study, which focuses on the development of a fuzzy cognitive map model for early differential diagnosis of tropical diseases. We used malaria as a case disease to show the effectiveness of the FCM technology as an aid to the medical practitioner in the diagnosis of tropical diseases. Our model takes cognizance of manifested symptoms and other non-clinical factors that could contribute to symptoms manifestations. Our model showed 85% accuracy in diagnosis, as against the physicians’ initial hypothesis, which stood at 55% accuracy. It is expected that the next stage of our study will provide a multi-disease, multi-symptom model that also improves efficiency by utilizing a decision support filter that works on an algorithm, which mimics the physician’s diagnosis process.

Keywords: Medical diagnosis, tropical diseases, fuzzy cognitive map, decision support filters, malaria differential diagnosis.

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Authors: Luis A. Morales Rosales, Saul E. Pomares Hernandez, Gustavo Rodriguez Gomez

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Synchronous cooperative systems (SCS) bring together users that are geographically distributed and connected through a network to carry out a task. Examples of SCS include Tele- Immersion and Tele-Conferences. In SCS, the coordination is the core of the system, and it has been defined as the act of managing interdependencies between activities performed to achieve a goal. Some of the main problems that SCS present deal with the management of constraints between simultaneous activities and the execution ordering of these activities. In order to resolve these problems, orderings based on Lamport-s happened-before relation have been used, namely, causal, Δ-causal, and causal-total orderings. They mainly differ in the degree of asynchronous execution allowed. One of the most important orderings is the causal order, which establishes that the events must be seen in the cause-effect order as they occur in the system. In this paper we show that for certain SCS (e.g. videoconferences, tele-immersion) where some degradation of the system is allowed, ensuring the causal order is still rigid, which can render negative affects to the system. In this paper, we illustrate how a more relaxed ordering, which we call Fuzzy Causal Order (FCO), is useful for such kind of systems by allowing a more asynchronous execution than the causal order. The benefit of the FCO is illustrated by applying it to a particular scenario of intermedia synchronization of an audio-conference system.

Keywords: Event ordering, fuzzy causal ordering, happenedbefore relation and cooperative systems.

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Authors: Tayebeh Saghapour, Sara Moridpour, Russell George Thompson

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One of the common aims of transport policy makers is to switch people’s travel to active transport. For this purpose, a variety of transport goals and investments should be programmed to increase the propensity towards active transport mode choice. This paper aims to investigate whether built environment features in neighbourhoods could enhance the odds of active transportation. The present study introduces an index measuring public transport accessibility (PTAI), and a walkability index along with socioeconomic variables to investigate mode choice behaviour. Using travel behaviour data, an ordered logit regression model is applied to examine the impacts of explanatory variables on walking trips. The findings indicated that high rates of active travel are consistently associated with higher levels of walking and public transport accessibility.

Keywords: Active transport, public transport accessibility, walkability, ordered logit model.

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Authors: H. Shareef, A. Mohamed, S. A. Khalid, Aziah Khamis

Abstract:

This paper presents application artificial intelligent (AI) techniques, namely artificial neural network (ANN), adaptive neuro fuzzy interface system (ANFIS), to estimate the real power transfer between generators and loads. Since these AI techniques adopt supervised learning, it first uses modified nodal equation method (MNE) to determine real power contribution from each generator to loads. Then the results of MNE method and load flow information are utilized to estimate the power transfer using AI techniques. The 25-bus equivalent system of south Malaysia is utilized as a test system to illustrate the effectiveness of both AI methods compared to that of the MNE method. The mean squared error of the estimate of ANN and ANFIS power transfer allocation methods are 1.19E-05 and 2.97E-05, respectively. Furthermore, when compared to MNE method, ANN and ANFIS methods computes generator contribution to loads within 20.99 and 39.37msec respectively whereas the MNE method took 360msec for the calculation of same real power transfer allocation. 

Keywords: Artificial intelligence, Power tracing, Artificial neural network, ANFIS, Power system deregulation.

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Authors: Pejman Hosseinioun, Hasan Shakeri, Ghasem Ghorbanirostam

Abstract:

In recent years, we have seen an increasing importance of research and study on knowledge source, decision support systems, data mining and procedure of knowledge discovery in data bases and it is considered that each of these aspects affects the others. In this article, we have merged information source and knowledge source to suggest a knowledge based system within limits of management based on storing and restoring of knowledge to manage information and improve decision making and resources. In this article, we have used method of data mining and Apriori algorithm in procedure of knowledge discovery one of the problems of Apriori algorithm is that, a user should specify the minimum threshold for supporting the regularity. Imagine that a user wants to apply Apriori algorithm for a database with millions of transactions. Definitely, the user does not have necessary knowledge of all existing transactions in that database, and therefore cannot specify a suitable threshold. Our purpose in this article is to improve Apriori algorithm. To achieve our goal, we tried using fuzzy logic to put data in different clusters before applying the Apriori algorithm for existing data in the database and we also try to suggest the most suitable threshold to the user automatically.

Keywords: Decision support system, data mining, knowledge discovery, data discovery, fuzzy logic.

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Authors: Horng-Yuan Wu, Chin-Yuan Hsu, Tsair-Fwu Lee

Abstract:

A novel three-phase active power filter (APF) circuit with photovoltaic (PV) system to improve the quality of service and to reduce the capacity of energy storage capacitor is presented. The energy balance concept and sampling technique were used to simplify the calculation algorithm for the required utility source current and to control the voltage of the energy storage capacitor. The feasibility was verified by using the Pspice simulations and experiments. When the APF mode was used during non-operational period, not only the utilization rate, power factor and power quality could be improved, but also the capacity of energy storage capacitor could sparing. As the results, the advantages of the APF circuit are simplicity of control circuits, low cost, and good transient response.

Keywords: active power filter, sampling, energy-storagecapacitor, harmonic current, energy balance.

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Authors: Nisrin R. Abdelal, Steven L. Donaldson

Abstract:

Composite materials are widely used in aviation industry due to their superior properties; however, they are susceptible to delamination. Through-thickness stitching is one of the techniques to alleviate delamination. Kevlar is one of the most common stitching materials; in contrast, it is expensive and presents stitching fabrication challenges. Therefore, this study compares the performance of Kevlar with an inexpensive and easy-to-use nylon fiber in stitching to alleviate delamination. Three laminates of unidirectional carbon fiber-epoxy composites were manufactured using vacuum assisted resin transfer molding process. One panel was stitched with Kevlar, one with nylon, and one unstitched. Mode I interlaminar fracture tests were carried out on specimens from the three composite laminates, and the results were compared. Fractographic analysis using optical and scanning electron microscope were conducted to reveal the differences between stitching with Kevlar and nylon on the internal microstructure of the composite with respect to the interlaminar fracture toughness values.

Keywords: Carbon, delamination, Kevlar, mode I, nylon, stitching.

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Authors: S. Benchelha, H. C. Aoudjehane, M. Hakdaoui, R. El Hamdouni, H. Mansouri, T. Benchelha, M. Layelmam, M. Alaoui

Abstract:

The logistic regression (LR) and multivariate adaptive regression spline (MarSpline) are applied and verified for analysis of landslide susceptibility map in Oudka, Morocco, using geographical information system. From spatial database containing data such as landslide mapping, topography, soil, hydrology and lithology, the eight factors related to landslides such as elevation, slope, aspect, distance to streams, distance to road, distance to faults, lithology map and Normalized Difference Vegetation Index (NDVI) were calculated or extracted. Using these factors, landslide susceptibility indexes were calculated by the two mentioned methods. Before the calculation, this database was divided into two parts, the first for the formation of the model and the second for the validation. The results of the landslide susceptibility analysis were verified using success and prediction rates to evaluate the quality of these probabilistic models. The result of this verification was that the MarSpline model is the best model with a success rate (AUC = 0.963) and a prediction rate (AUC = 0.951) higher than the LR model (success rate AUC = 0.918, rate prediction AUC = 0.901).

Keywords: Landslide susceptibility mapping, regression logistic, multivariate adaptive regression spline, Oudka, Taounate, Morocco.

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Authors: Kritphon Phanruttanachai, Winai Jaikla

Abstract:

This article presents a current-mode quadrature oscillator using differential different current conveyor (DDCC) and voltage differencing transconductance amplifier (VDTA) as active elements. The proposed circuit is realized fro m a non-inverting lossless integrator and an inverting second order low-pass filter. The oscillation condition and oscillation frequency can be electronically/orthogonally controlled via input bias currents. The circuit description is very simple, consisting of merely 1 DDCC, 1 VDTA, 1 grounded resistor and 3 grounded capacitors. Using only grounded elements, the proposed circuit is then suitable for IC architecture. The proposed oscillator has high output impedance which is easy to cascade or dive the external load without the buffer devices. The PSPICE simulation results are depicted, and the given results agree well with the theoretical anticipation. The power consumption is approximately 1.76mW at ±1.25V supply voltages.

Keywords: Current-mode, oscillator, integrated circuit, DDCC, VDTA

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Authors: Y.Srinivasa Kishore Babu, G.Tulasi Ram Das

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This paper presents a comparative study of two most popular control strategies for Induction motor (IM) drives: Field-Oriented Control (FOC) and Direct Torque Control (DTC). The comparison is based on various criteria including basic control characteristics, dynamic performance, and implementation complexity. The study is done by simulation using the Simulink Power System Block set that allows a complete representation of the power section (inverter and IM) and the control system.

Keywords: IM, FOC, DTC, Simulink

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Authors: Ali Zifan, Mohammad Hassan Moradi, Sohrab Saberi, Farzad Towhidkhah

Abstract:

Electrocardiogram (ECG) segmentation is necessary to help reduce the time consuming task of manually annotating ECG-s. Several algorithms have been developed to segment the ECG automatically. We first review several of such methods, and then present a new single lead segmentation method based on Adaptive piecewise constant approximation (APCA) and Piecewise derivative dynamic time warping (PDDTW). The results are tested on the QT database. We compared our results to Laguna-s two lead method. Our proposed approach has a comparable mean error, but yields a slightly higher standard deviation than Laguna-s method.

Keywords: Adaptive Piecewise Constant Approximation, Dynamic programming, ECG segmentation, Piecewise DerivativeDynamic Time Warping.

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Authors: Michael A. Folcik, Bijan Karimi

Abstract:

A robot simulator was developed to measure and investigate the performance of a robot navigation system based on the relative position of the robot with respect to random obstacles in any two dimensional environment. The presented simulator focuses on investigating the ability of a fuzzy-neural system for object avoidance. A navigation algorithm is proposed and used to allow random navigation of a robot among obstacles when the robot faces an obstacle in the environment. The main features of this simulator can be used for evaluating the performance of any system that can provide the position of the robot with respect to obstacles in the environment. This allows a robot developer to investigate and analyze the performance of a robot without implementing the physical robot.

Keywords: Applications of Fuzzy Logic and Neural Networksin Robotics, Artificial Intelligence, Embedded Systems, MobileRobots, Robot Navigation, Robotics.

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