Search results for: fuzzy wavelet packet

Authors: Changho Han, Jaemin Lee, Li Hua, Seokkwon Jeong

Abstract:

Design of membership function ranges in fuzzy logic control (FLC) is presented for robust control of a variable speed refrigeration system (VSRS). The criterion values of the membership function ranges can be carried out from the static experimental data, and two different values are offered to compare control performance. Some simulations and real experiments for the VSRS were conducted to verify the validity of the designed membership functions. The experimental results showed good agreement with the simulation results, and the error change rate and its sampling time strongly affected the control performance at transient state of the VSRS.

Keywords: Variable speed refrigeration system, Fuzzy logic control, membership function range, control performance.

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Authors: Mohamad R. Khaldi, Christine S. Khoury, Guy M. Naim

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The steady-state operation of maintaining voltage stability is done by switching various controllers scattered all over the power network. When a contingency occurs, whether forced or unforced, the dispatcher is to alleviate the problem in a minimum time, cost, and effort. Persistent problem may lead to blackout. The dispatcher is to have the appropriate switching of controllers in terms of type, location, and size to remove the contingency and maintain voltage stability. Wrong switching may worsen the problem and that may lead to blackout. This work proposed and used a Fuzzy CMeans Clustering (FCMC) to assist the dispatcher in the decision making. The FCMC is used in the static voltage stability to map instantaneously a contingency to a set of controllers where the types, locations, and amount of switching are induced.

Keywords: Fuzzy logic, Power system control, Reactive power control, Voltage control

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Authors: Mehrdad N. Khajavi , Golamhassan Paygane, Ali Hakima

Abstract:

Vehicle which are turning or maneuvering at high speeds are susceptible to sliding and subsequently deviate from desired path. In this paper the dynamics governing the Yaw/Roll behavior of a vehicle has been simulated. Two different simulations have been used one for the real vehicle, for which a fuzzy controller is designed to increase its directional stability property. The other simulation is for a hypothetical vehicle with much higher tire cornering stiffness which is capable of developing the required lateral forces at the tire-ground patch contact to attain the desired lateral acceleration for the vehicle to follow the desired path without slippage. This simulation model is our reference model. The logic for keeping the vehicle on the desired track in the cornering or maneuvering state is to have some braking forces on the inner or outer tires based on the direction of vehicle deviation from the desired path. The inputs to our vehicle simulation model is steer angle δ and vehicle velocity V , and the outputs can be any kinematical parameters like yaw rate, yaw acceleration, side slip angle, rate of side slip angle and so on. The proposed fuzzy controller is a feed forward controller. This controller has two inputs which are steer angle δ and vehicle velocity V, and the output of the controller is the correcting moment M, which guides the vehicle back to the desired track. To develop the membership functions for the controller inputs and output and the fuzzy rules, the vehicle simulation has been run for 1000 times and the correcting moment have been determined by trial and error. Results of the vehicle simulation with fuzzy controller are very promising and show the vehicle performance is enhanced greatly over the vehicle without the controller. In fact the vehicle performance with the controller is very near the performance of the reference ideal model.

Keywords: Vehicle, Directional Stability, Fuzzy Logic Controller, ANFIS..

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Authors: A. Kablan

Abstract:

The prediction of financial time series is a very complicated process. If the efficient market hypothesis holds, then the predictability of most financial time series would be a rather controversial issue, due to the fact that the current price contains already all available information in the market. This paper extends the Adaptive Neuro Fuzzy Inference System for High Frequency Trading which is an expert system that is capable of using fuzzy reasoning combined with the pattern recognition capability of neural networks to be used in financial forecasting and trading in high frequency. However, in order to eliminate unnecessary input in the training phase a new event based volatility model was proposed. Taking volatility and the scaling laws of financial time series into consideration has brought about the development of the Intraday Seasonality Observation Model. This new model allows the observation of specific events and seasonalities in data and subsequently removes any unnecessary data. This new event based volatility model provides the ANFIS system with more accurate input and has increased the overall performance of the system.

Keywords: Adaptive Neuro-fuzzy Inference system, High Frequency Trading, Intraday Seasonality Observation Model.

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Authors: M. A. M. El-Bendary, A. E. Abu El-Azm, N. A. El-Fishawy, F. Shawky, F. E. El-Samie

Abstract:

With increasing utilization of the wireless devices in different fields such as medical devices and industrial fields, the paper presents a method for simplify the Bluetooth packets with throughput enhancing. The paper studies a vital issue in wireless communications, which is the throughput of data over wireless networks. In fact, the Bluetooth and ZigBee are a Wireless Personal Area Network (WPAN). With taking these two systems competition consideration, the paper proposes different schemes for improve the throughput of Bluetooth network over a reliable channel. The proposition depends on the Channel Quality Driven Data Rate (CQDDR) rules, which determines the suitable packet in the transmission process according to the channel conditions. The proposed packet is studied over additive White Gaussian Noise (AWGN) and fading channels. The Experimental results reveal the capability of extension of the PL length by 8, 16, 24 bytes for classic and EDR packets, respectively. Also, the proposed method is suitable for the low throughput Bluetooth.

Keywords: Bluetooth, throughput, adaptive packets, EDRpackets, CQDDR, low latency. Channel condition

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Authors: T. P. Athira, Gibin Chacko George

Abstract:

This paper proposes a dual tree complex wavelet transform (DT-CWT) based directional interpolation scheme for noisy images. The problems of denoising and interpolation are modelled as to estimate the noiseless and missing samples under the same framework of optimal estimation. Initially, DT-CWT is used to decompose an input low-resolution noisy image into low and high frequency subbands. The high-frequency subband images are interpolated by linear minimum mean square estimation (LMMSE) based interpolation, which preserves the edges of the interpolated images. For each noisy LR image sample, we compute multiple estimates of it along different directions and then fuse those directional estimates for a more accurate denoised LR image. The estimation parameters calculated in the denoising processing can be readily used to interpolate the missing samples. The inverse DT-CWT is applied on the denoised input and interpolated high frequency subband images to obtain the high resolution image. Compared with the conventional schemes that perform denoising and interpolation in tandem, the proposed DT-CWT based noisy image interpolation method can reduce many noise-caused interpolation artifacts and preserve well the image edge structures. The visual and quantitative results show that the proposed technique outperforms many of the existing denoising and interpolation methods.

Keywords: Dual-tree complex wavelet transform (DT-CWT), denoising, interpolation, optimal estimation, super resolution.

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Authors: Tahar Ezzedine, Mohamed Miladi, Ridha Bouallegue

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Because nodes are usually battery-powered, the energy presents a very scarce resource in wireless sensor networks. For this reason, the design of medium access control had to take energy efficiency as one of its hottest concerns. Accordingly, in order to improve the energy performance of MAC schemes in wireless sensor networks, several ways can be followed. In fact, some researchers try to limit idle listening while others focus on mitigating overhearing (i.e. a node can hear a packet which is destined to another node) or reducing the number of the used control packets. We, in this paper, propose a new hybrid MAC protocol termed ELE-MAC (i.e. Energy Latency Efficient MAC). The ELE-MAC major design goals are energy and latency efficiencies. It adopts less control packets than SMAC in order to preserve energy. We carried out ns- 2 simulations to evaluate the performance of the proposed protocol. Thus, our simulation-s results prove the ELE-MAC energy efficiency. Additionally, our solution performs statistically the same or better latency characteristic compared to adaptive SMAC.

Keywords: Control packet, energy efficiency, medium access control, wireless sensor networks.

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Authors: K. Muthukannan, P. Latha

Abstract:

In addition to environmental parameters like rain, temperature diseases on crop is a major factor which affects production quality & quantity of crop yield. Hence disease management is a key issue in agriculture. For the management of disease, it needs to be detected at early stage. So, treat it properly & control spread of the disease. Now a day, it is possible to use the images of diseased leaf to detect the type of disease by using image processing techniques. This can be achieved by extracting features from the images which can be further used with classification algorithms or content based image retrieval systems. In this paper, color image is used to extract the features such as mean and standard deviation after the process of region cropping. The selected features are taken from the cropped image with different image size samples. Then, the extracted features are taken in to the account for classification using Fuzzy Inference System (FIS).

Keywords: Image Cropping, Classification, Color, Fuzzy Rule, Feature Extraction.

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Authors: Sergey Sorokin, Irina Sorokina, Alexander Yazenin

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We present a solution to the Maxmin u/E parameters estimation problem of possibility distributions in m-dimensional case. Our method is based on geometrical approach, where minimal area enclosing ellipsoid is constructed around the sample. Also we demonstrate that one can improve results of well-known algorithms in fuzzy model identification task using Maxmin u/E parameters estimation.

Keywords: Possibility distribution, parameters estimation, Maxmin u/E estimator, fuzzy model identification.

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Authors: H. Megherbi, A. C. Megherbi, N. Megherbi, K. Benmahamed

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This paper presents three-phase evolution search methodology to automatically design fuzzy logic controllers (FLCs) that can work in a wide range of operating conditions. These include varying load, parameter variations, and unknown external disturbances. The three-phase scheme consists of an exploration phase, an exploitation phase and a robustness phase. The first two phases search for FLC with high accuracy performances while the last phase aims at obtaining FLC providing the best compromise between the accuracy and robustness performances. Simulations were performed for direct-drive two-axis robot arm. The evolved FLC with the proposed design technique found to provide a very satisfactory performance under the wide range of operation conditions and to overcome problem associated with coupling and nonlinearities characteristics inherent to robot arms.

Keywords: Fuzzy logic control, evolutionary algorithms, robustness, exploration/exploitation phase.

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Authors: P. Cermak

Abstract:

This paper shows possibility of extraction Social, Group and Individual Mind from Multiple Agents Rule Bases. Types those Rule bases are selected as two fuzzy systems, namely Mambdani and Takagi-Sugeno fuzzy system. Their rule bases are describing (modeling) agent behavior. Modifying of agent behavior in the time varying environment will be provided by learning fuzzyneural networks and optimization of their parameters with using genetic algorithms in development system FUZNET. Finally, extraction Social, Group and Individual Mind from Multiple Agents Rule Bases are provided by Cognitive analysis and Matching criterion.

Keywords: Mind, Multi-agent system, Cognitive analysis, Fuzzy system, Neural network, Genetic algorithm, Rule base.

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Authors: Latha Parameswaran, K. Anbumani

Abstract:

Multimedia security is an incredibly significant area of concern. A number of papers on robust digital watermarking have been presented, but there are no standards that have been defined so far. Thus multimedia security is still a posing problem. The aim of this paper is to design a robust image-watermarking scheme, which can withstand a different set of attacks. The proposed scheme provides a robust solution integrating image moment normalization, content dependent watermark and discrete wavelet transformation. Moment normalization is useful to recover the watermark even in case of geometrical attacks. Content dependent watermarks are a powerful means of authentication as the data is watermarked with its own features. Discrete wavelet transforms have been used as they describe image features in a better manner. The proposed scheme finds its place in validating identification cards and financial instruments.

Keywords: Watermarking, moments, wavelets, content-based, benchmarking.

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Authors: Yan Xu, Toshihiro Nishimura

Abstract:

Segmentation in ultrasound images is challenging due to the interference from speckle noise and fuzziness of boundaries. In this paper, a segmentation scheme using fuzzy c-means (FCM) clustering incorporating both intensity and texture information of images is proposed to extract breast lesions in ultrasound images. Firstly, the nonlinear structure tensor, which can facilitate to refine the edges detected by intensity, is used to extract speckle texture. And then, a spatial FCM clustering is applied on the image feature space for segmentation. In the experiments with simulated and clinical ultrasound images, the spatial FCM clustering with both intensity and texture information gets more accurate results than the conventional FCM or spatial FCM without texture information.

Keywords: fuzzy c-means, spatial information, structure tensor, ultrasound image segmentation

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Authors: Rahmatollah Hooshmand, Mahdi Banejad

Abstract:

One of the problems in fault diagnosis of transformer based on dissolved gas, is lack of matching the result of fault diagnosis of different standards with the real world. In this paper, the result of the different standards is analyzed using fuzzy and the result is compared with the empirical test. The comparison between the suggested method and existing methods indicate the capability of the suggested method in on-line fault diagnosis of the transformers. In addition, in some cases the existing standards are not able to diagnose the fault. In theses cases, the presented method has the potential of diagnosing the fault. The information of three transformers is used to the show the capability of the suggested method in diagnosing the fault. The results validate the capability of the presented method in fault diagnosis of the transformer.

Keywords: Fault Diagnosis of Transformer, Dissolved Gas, Fuzzy Logic.

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Authors: Marco Soares dos Santos, Jorge Augusto Ferreira, Camila Nicola Boeri, Fernando Neto da Silva

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The present paper proposes high performance nonlinear force controllers for a servopneumatic real-time fatigue test machine. A CompactRIO® controller was used, being fully programmed using LabVIEW language. Fuzzy logic control algorithms were evaluated to tune the integral and derivative components in the development of hybrid controllers, namely a FLC P and a hybrid FLC PID real-time-based controllers. Their behaviours were described by using state diagrams. The main contribution is to ensure a smooth transition between control states, avoiding discrete transitions in controller outputs. Steady-state errors lower than 1.5 N were reached, without retuning the controllers. Good results were also obtained for sinusoidal tracking tasks from 1/¤Ç to 8/¤Ç Hz.

Keywords: Hybrid Fuzzy Selecting, Control, Range Controllers, Servopneumatic Fatigue System.

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Authors: J. Costa, M. Ortigueira, A. Batista, T. Paiva

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Sleep spindles are the most interesting hallmark of stage 2 sleep EEG. Their accurate identification in a polysomnographic signal is essential for sleep professionals to help them mark Stage 2 sleep. Sleep Spindles are also promising objective indicators for neurodegenerative disorders. Visual spindle scoring however is a tedious workload. In this paper three different approaches are used for the automatic detection of sleep spindles: Short Time Fourier Transform, Wavelet Transform and Wave Morphology for Spindle Detection. In order to improve the results, a combination of the three detectors is presented and comparison with human expert scorers is performed. The best performance is obtained with a combination of the three algorithms which resulted in a sensitivity and specificity of 94% when compared to human expert scorers.

Keywords: EEG, Short Time Fourier Transform, Sleep Spindles, Wave Morphology for Spindle Detection, Wavelet Transform.

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Authors: Ashok Kumar, Vinod Kumar

Abstract:

Wireless Sensor Networks (WSNs) are used to monitor/observe vast inaccessible regions through deployment of large number of sensor nodes in the sensing area. For majority of WSN applications, the collected data needs to be combined with geographic information of its origin to make it useful for the user; information received from remote Sensor Nodes (SNs) that are several hops away from base station/sink is meaningless without knowledge of its source. In addition to this, location information of SNs can also be used to propose/develop new network protocols for WSNs to improve their energy efficiency and lifetime. In this paper, range free localization protocols for WSNs have been proposed. The proposed protocols are based on weighted centroid localization technique, where the edge weights of SNs are decided by utilizing fuzzy logic inference for received signal strength and link quality between the nodes. The fuzzification is carried out using (i) Mamdani, (ii) Sugeno, and (iii) Combined Mamdani Sugeno fuzzy logic inference. Simulation results demonstrate that proposed protocols provide better accuracy in node localization compared to conventional centroid based localization protocols despite presence of unintentional radio frequency interference from radio frequency (RF) sources operating in same frequency band.

Keywords: localization, range free, received signal strength, link quality indicator, Mamdani fuzzy logic inference, Sugeno fuzzy logic inference.

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Authors: Ryan B. Escorial, Elmer A. Maravillas, Chris Jordan G. Aliac

Abstract:

This study presents a small-scale water pumping system utilizing a fuzzy logic inference system attached to a renewable energy source. The fuzzy logic controller was designed and simulated in MATLAB fuzzy logic toolbox to examine the properties and characteristics of the input and output variables. The result of the simulation was implemented in a microcontroller, together with sensors, modules, and photovoltaic cells. The study used a grand rapid variety of lettuce, organic substrates, and foliar for observation of the capability of the device to irrigate crops. Two plant boxes intended for manual and automated irrigation were prepared with each box having 48 heads of lettuce. The observation of the system took 22-31 days, which is one harvest period of the crop. Results showed a 22.55% increase in agricultural productivity compared to manual irrigation. Aside from reducing human effort, and time, the smart irrigation system could help lessen some of the shortcomings of manual irrigations. It could facilitate the economical utilization of water, reducing consumption by 25%. The use of renewable energy could also help farmers reduce the cost of production by minimizing the use of diesel and gasoline.

Keywords: Fuzzy logic controller, intelligent system, precision agriculture, renewable energy.

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Authors: Parvinder S. Sandhu, Urvashi Malhotra, E. Ardil

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There is lot of work done in prediction of the fault proneness of the software systems. But, it is the severity of the faults that is more important than number of faults existing in the developed system as the major faults matters most for a developer and those major faults needs immediate attention. In this paper, we tried to predict the level of impact of the existing faults in software systems. Neuro-Fuzzy based predictor models is applied NASA-s public domain defect dataset coded in C programming language. As Correlation-based Feature Selection (CFS) evaluates the worth of a subset of attributes by considering the individual predictive ability of each feature along with the degree of redundancy between them. So, CFS is used for the selecting the best metrics that have highly correlated with level of severity of faults. The results are compared with the prediction results of Logistic Models (LMT) that was earlier quoted as the best technique in [17]. The results are recorded in terms of Accuracy, Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). The results show that Neuro-fuzzy based model provide a relatively better prediction accuracy as compared to other models and hence, can be used for the modeling of the level of impact of faults in function based systems.

Keywords: Software Metrics, Fuzzy, Neuro-Fuzzy, Software Faults, Accuracy, MAE, RMSE.

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Authors: Tomasz L. Nawrocki, Danuta Szwajca

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The growing importance of reputation in building enterprise value and achieving long-term competitive advantage creates the need for its measurement and evaluation for the management purposes (effective reputation and its risk management). The paper presents practical application of self-developed corporate reputation assessment model from the viewpoint of stock market investors. The model has a pioneer character and example analysis performed for selected industry is a form of specific test for this tool. In the proposed solution, three aspects - informational, financial and development, as well as social ones - were considered. It was also assumed that the individual sub-criteria will be based on public sources of information, and as the calculation apparatus, capable of obtaining synthetic final assessment, fuzzy logic will be used. The main reason for developing this model was to fulfill the gap in the scope of synthetic measure of corporate reputation that would provide higher degree of objectivity by relying on "hard" (not from surveys) and publicly available data. It should be also noted that results obtained on the basis of proposed corporate reputation assessment method give possibilities of various internal as well as inter-branch comparisons and analysis of corporate reputation impact.

Keywords: Corporate reputation, fuzzy logic, fuzzy model, stock market investors.

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Authors: Chidentree Treesatayapun

Abstract:

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: Z.M. Hanapi, M. Ismail, K. Jumari, M. Mahdavi

Abstract:

Routing security is a major concerned in Wireless Sensor Network since a large scale of unattended nodes is deployed in ad hoc fashion with no possibility of a global addressing due to a limitation of node-s memory and the node have to be self organizing when the systems require a connection with the other nodes. It becomes more challenging when the nodes have to act as the router and tightly constrained on energy and computational capabilities where any existing security mechanisms are not allowed to be fitted directly. These reasons thus increasing vulnerabilities to the network layer particularly and to the whole network, generally. In this paper, a Dynamic Window Secured Implicit Geographic Forwarding (DWSIGF) routing is presented where a dynamic time is used for collection window to collect Clear to Send (CTS) control packet in order to find an appropriate hoping node. The DWIGF is expected to minimize a chance to select an attacker as the hoping node that caused by a blackhole attack that happen because of the CTS rushing attack, which promise a good network performance with high packet delivery ratios.

Keywords: sensor, security, routing, attack, random.

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Authors: Reza Ghasemi, Negin Amiri Hazaveh

Abstract:

In this paper, control methodology based on the selection of the type of traffic light and the period of the green phase to accomplish an optimum balance at intersections is proposed. This balance should be flexible to the static behavior of time, and randomness in a traffic situation; the goal of the proposed method is to reduce traffic volume in transportation, the average delay for each vehicle, and control over the crash of cars. The proposed method was specifically investigated at the intersection through an appropriate timing of traffic lights by sampling a multi-agent system. It consists of a large number of intersections, each of which is considered as an independent agent that exchanges information with each other, and the stability of each agent is provided separately. The robustness against uncertainties, scalability, and stability of the closed-loop overall system are the main merits of the proposed methodology. The simulation results show that the fuzzy intelligent controller in this multi-factor system which is a Takagi-Sugeno (TS) fuzzy is more useful than scheduling in the fixed-time method and it reduces the lengths of vehicles queuing.

Keywords: Fuzzy intelligent controller, traffic-light control, multi-agent systems, state space equations, stability.

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Authors: Thibaud Berthomier, Ali Mansour, Luc Bressollette, Frédéric Le Roy, Dominique Mottier, Léo Fréchier, Barthélémy Hermenault

Abstract:

Deep Venous Thrombosis (DVT) occurs when a thrombus is formed within a deep vein (most often in the legs). This disease can be deadly if a part or the whole thrombus reaches the lung and causes a Pulmonary Embolism (PE). This disorder, often asymptomatic, has multifactorial causes: immobilization, surgery, pregnancy, age, cancers, and genetic variations. Our project aims to relate the thrombus epidemiology (origins, patient predispositions, PE) to its structure using ultrasound images. Ultrasonography and elastography were collected using Toshiba Aplio 500 at Brest Hospital. This manuscript compares two classification approaches: spectral clustering and scattering operator. The former is based on the graph and matrix theories while the latter cascades wavelet convolutions with nonlinear modulus and averaging operators.

Keywords: Deep venous thrombosis, ultrasonography, elastography, scattering operator, wavelet, spectral clustering.

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Authors: Ali Akbar Attari, Ali Asghar Beheshti Shirazi

Abstract:

In this paper, we propose a blind and robust audio watermarking scheme based on spread spectrum in Discrete Wavelet Transform (DWT) domain. Watermarks are embedded in the low-frequency coefficients, which is less audible. The key idea is dividing the audio signal into small frames, and magnitude of the 6^th level of DWT approximation coefficients is modifying based upon the Direct Sequence Spread Spectrum (DSSS) technique. Also, the psychoacoustic model for enhancing in imperceptibility, as well as Savitsky-Golay filter for increasing accuracy in extraction, is used. The experimental results illustrate high robustness against most common attacks, i.e. Gaussian noise addition, Low pass filter, Resampling, Requantizing, MP3 compression, without significant perceptual distortion (ODG is higher than -1). The proposed scheme has about 83 bps data payload.

Keywords: Audio watermarking, spread spectrum, discrete wavelet transform, psychoacoustic, Savitsky-Golay filter.

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Authors: R. Poonkuzhali, M. Y. Sanavullah, A. Sabari, T. Dhivyaa

Abstract:

Opportunistic Routing (OR) increases the transmission reliability and network throughput. Traditional routing protocols preselects one or more predetermined nodes before transmission starts and uses a predetermined neighbor to forward a packet in each hop. The opportunistic routing overcomes the drawback of unreliable wireless transmission by broadcasting one transmission can be overheard by manifold neighbors. The first cooperation-optimal protocol for Multirate OR (COMO) used to achieve social efficiency and prevent the selfish behavior of the nodes. The novel link-correlation-aware OR improves the performance by exploiting the miscellaneous low correlated forward links. Context aware Adaptive OR (CAOR) uses active suppression mechanism to reduce packet duplication. The Context-aware OR (COR) can provide efficient routing in mobile networks. By using Cooperative Opportunistic Routing in Mobile Ad hoc Networks (CORMAN), the problem of opportunistic data transfer can be tackled. While comparing to all the protocols, COMO is the best as it achieves social efficiency and prevents the selfish behavior of the nodes.

Keywords: CAOR, COMO, COR, CORMAN, MANET, Opportunistic Routing, Reliability, Throughput.

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Authors: Apidet Booranawong, Wiklom Teerapabkajorndet

Abstract:

An enhanced ad-hoc on-demand distance vector routing (E-AODV) protocol for control system applications in wireless sensor and actuator networks (WSANs) is proposed. Our routing algorithm is designed by considering both wireless network communication and the control system aspects. Control system error and network delay are the main selection criteria in our routing protocol. The control and communication performance is evaluated on multi-hop IEEE 802.15.4 networks for building-temperature control systems. The Gilbert-Elliott error model is employed to simulate packet loss in wireless networks. The simulation results demonstrate that the E-AODV routing approach can significantly improve the communication performance better than an original AODV routing under various packet loss rates. However, the control performance result by our approach is not much improved compared with the AODV routing solution.

Keywords: WSANs, building temperature control, AODV routing protocol, control system error, settling time, delay, delivery ratio.

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Authors: Nassib Abdallah, Pierre Chauvet, Abd El Salam Hajjar, Bassam Daya

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In this paper, we propose an optimized brain computer interface (BCI) system for unspoken speech recognition, based on the fact that the constructions of unspoken words rely strongly on the Wernicke area, situated in the temporal lobe. Our BCI system has four modules: (i) the EEG Acquisition module based on a non-invasive headset with 14 electrodes; (ii) the Preprocessing module to remove noise and artifacts, using the Common Average Reference method; (iii) the Features Extraction module, using Wavelet Packet Transform (WPT); (iv) the Classification module based on a one-hidden layer artificial neural network. The present study consists of comparing the recognition accuracy of 5 Arabic words, when using all the headset electrodes or only the 4 electrodes situated near the Wernicke area, as well as the selection effect of the subbands produced by the WPT module. After applying the articial neural network on the produced database, we obtain, on the test dataset, an accuracy of 83.4% with all the electrodes and all the subbands of 8 levels of the WPT decomposition. However, by using only the 4 electrodes near Wernicke Area and the 6 middle subbands of the WPT, we obtain a high reduction of the dataset size, equal to approximately 19% of the total dataset, with 67.5% of accuracy rate. This reduction appears particularly important to improve the design of a low cost and simple to use BCI, trained for several words.

Keywords: Brain-computer interface, speech recognition, electroencephalography EEG, Wernicke area, artificial neural network.

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Authors: Zhaojun Wang, Zongdi Sun, Zhiyuan Liu

Abstract:

First of all, the carbon trading price and trading volume in Shanghai are transformed by Fourier transform, and the frequency response diagram is obtained. Then, the frequency response diagram is analyzed and the Blackman filter is designed. The Blackman filter is used to filter, and the carbon trading time domain and frequency response diagram are obtained. After wavelet analysis, the carbon trading data were processed; respectively, we got the average value for each 5 days, 10 days, 20 days, 30 days, and 60 days. Finally, the data are used as input of the Back Propagation Neural Network model for prediction.

Keywords: Shanghai carbon trading, carbon trading price, carbon trading volume, wavelet analysis, BP neural network model.

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Authors: K.V. Sridhar, Varun Gunnala, K.S.R Krishna Prasad

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In this paper three basic approaches and different methods under each of them for extracting region of interest (ROI) from stationary images are explored. The results obtained for each of the proposed methods are shown, and it is demonstrated where each method outperforms the other. Two main problems in ROI extraction: the channel selection problem and the saliency reversal problem are discussed and how best these two are addressed by various methods is also seen. The basic approaches are 1) Saliency based approach 2) Wavelet based approach 3) Clustering based approach. The saliency approach performs well on images containing objects of high saturation and brightness. The wavelet based approach performs well on natural scene images that contain regions of distinct textures. The mean shift clustering approach partitions the image into regions according to the density distribution of pixel intensities. The experimental results of various methodologies show that each technique performs at different acceptable levels for various types of images.

Keywords: clustering, ROI, saliency, wavelets.

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