Search results for: filter paper

Authors: Ping Tan, Xiaomeng Su, Yi Shen

Abstract:

The motion intention in the motor imagery braincomputer interface is identified by classifying the event-related desynchronization (ERD) and event-related synchronization ERS characteristics of sensorimotor rhythm (SMR) in EEG signals. When the subject imagines different limbs or different parts moving, the rhythm components and bandwidth will change, which varies from person to person. How to find the effective sensorimotor frequency band of subjects is directly related to the classification accuracy of brain-computer interface. To solve this problem, this paper proposes a Minimum Distance to Riemannian Mean Classification method based on Non-Uniform Filter Banks. During the training phase, the EEG signals are decomposed into multiple different bandwidt signals by using multiple band-pass filters firstly; Then the spatial covariance characteristics of each frequency band signal are computered to be as the feature vectors. these feature vectors will be classified by the MDRM (Minimum Distance to Riemannian Mean) method, and cross validation is employed to obtain the effective sensorimotor frequency bands. During the test phase, the test signals are filtered by the bandpass filter of the effective sensorimotor frequency bands, and the extracted spatial covariance feature vectors will be classified by using the MDRM. Experiments on the BCI competition IV 2a dataset show that the proposed method is superior to other classification methods.

Keywords: non-uniform filter banks, motor imagery, brain-computer interface, minimum distance to Riemannian mean

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Authors: Hao Wang, Shuguo Pan

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The Global Navigation Satellite System (GNSS) signal received by the dynamic vehicle in the harsh environment will be frequently interfered with and blocked, which generates gross error affecting the positioning accuracy of the GNSS/Inertial Navigation System (INS) integrated navigation. Therefore, this paper put forward an improved robust Cubature Kalman filter (CKF) algorithm for single-frequency GNSS/INS tightly coupled system ambiguity resolution. Firstly, the dynamic model and measurement model of a single-frequency GNSS/INS tightly coupled system was established, and the method for GNSS integer ambiguity resolution with INS aided is studied. Then, we analyzed the influence of pseudo-range observation with gross error on GNSS/INS integrated positioning accuracy. To reduce the influence of outliers, this paper improved the CKF algorithm and realized an intelligent selection of robust strategies by judging the ill-conditioned matrix. Finally, a field navigation test was performed to demonstrate the effectiveness of the proposed algorithm based on the double-differenced solution mode. The experiment has proved the improved robust algorithm can greatly weaken the influence of separate, continuous, and hybrid observation anomalies for enhancing the reliability and accuracy of GNSS/INS tightly coupled navigation solutions.

Keywords: GNSS/INS integrated navigation, ambiguity resolution, Cubature Kalman filter, Robust algorithm

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Authors: Hailu Dessalegn, T. Srinivas

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We propose new multiple-channel piezoelectric (PZT) actuated tunable optical filter based on racetrack multi-ring resonators for wavelength de-multiplexing network applications. We design tunable eight-channel wavelength de-multiplexer consisting of eight cascaded PZT actuated tunable multi-ring resonator filter with a channel spacing of 1.6 nm. The filter for each channel is basically structured on a suspended beam, sandwiched with piezoelectric material and built in integrated ring resonators which are placed on the middle of the beam to gain uniform stress and linearly varying longitudinal strain. A reference single mode serially coupled multi stage racetrack ring resonator with the same radii and coupling length is designed with a line width of 0.8974 nm with a flat top pass band at 1dB of 0.5205 nm and free spectral range of about 14.9 nm. In each channel, a small change in the perimeter of the rings is introduced to establish the shift in resonance wavelength as per the defined channel spacing. As a result, when a DC voltage is applied, the beams will elongate, which involves mechanical deformation of the ring resonators that induces a stress and a strain, which brings a change in refractive index and perimeter of the rings leading to change in the output spectrum shift providing the tunability of central wavelength in each channel. Simultaneous wave length shift as high as 45.54 pm/V has been achieved with negligible tunability variation in the eight channel tunable optical filter proportional to the DC voltage applied in the structure, and it is capable of tuning up to 3.45 nm in each channel with a maximum loss difference of 0.22 dB in the tuning range and out of band rejection ratio of 35 dB, with a low channel crosstalk ≤ 30 dB.

Keywords: optical MEMS, piezoelectric (PZT) actuation, tunable optical filter, wavelength de-multiplexer

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Authors: Iyad Al-Attar

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Air filters are widely used in gas turbines applications to ensure that the large mass (500kg/s) of clean air reach the compressor. The continuous demand of high availability and reliability has highlighted the critical role of air filter performance in providing enhanced air quality. In addition to being challenged with different environments [tropical, coastal, hot], gas turbines confront wide array of atmospheric contaminants with various concentrations and particle size distributions that would lead to performance degradation and components deterioration. Therefore, the role of air filters is of a paramount importance since fouled compressor can reduce power output and availability of the gas turbine to over 70 % throughout operation. Consequently, accurate filter performance prediction is critical tool in their selection considering their role in minimizing the economic impact of outages. In fact, actual performance of Efficient Particulate Air [EPA] filters used in gas turbine tend to deviate from the performance predicted by laboratory results. This experimental work investigates the initial pressure drop and fractional efficiency curves of full-scale pleated V-shaped EPA filters used globally in gas turbine. The investigation involved examining the effect of different operational conditions such as flow rates [500 to 5000 m3/h] and design parameters such as pleat count [28, 30, 32 and 34 pleats per 100mm]. This experimental work has highlighted the underlying reasons behind the reduction in filter permeability due to the increase of flow rates and pleat density. The reasons, which led to surface area losses of filtration media, are due to one or combination of the following effects: pleat-crowding, deflection of the entire pleated panel, pleat distortion at the corner of the pleat and/or filtration medium compression. This paper also demonstrates that the effect of increasing the flow rate has more pronounced effect on filter performance compared to pleating density. This experimental work suggests that a valid comparison of the pleat densities should be based on the effective surface area, namely, the area that participates in the filtration process, and not the total surface area the pleat density provides. Throughout this study, optimal pleat count that satisfies both initial pressure drop and efficiency requirements may not have necessarily existed.

Keywords: filter efficiency, EPA Filters, pressure drop, permeability

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Authors: Mohammed Farag, Mina Attari, S. Andrew Gadsden, Saeid R. Habibi

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Battery state of charge (SOC) estimation is an important parameter as it measures the total amount of electrical energy stored at a current time. The SOC percentage acts as a fuel gauge if it is compared with a conventional vehicle. Estimating the SOC is, therefore, essential for monitoring the amount of useful life remaining in the battery system. This paper looks at the implementation of three nonlinear estimation strategies for Li-Ion battery SOC estimation. One of the most common behavioral battery models is the one state hysteresis (OSH) model. The extended Kalman filter (EKF), the smooth variable structure filter (SVSF), and the time-varying smoothing boundary layer SVSF are applied on this model, and the results are compared.

Keywords: state of charge estimation, battery modeling, one-state hysteresis, filtering and estimation

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Authors: Guangyuan Zhao, Nan Huang, Xuesong Han, Xu Huang

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In order to solve the problem of sample dilution in the traditional particle filter algorithm and achieve accurate state estimation in a nonlinear system, a particle filter method based on an improved artificial bee colony (ABC) algorithm was proposed. The algorithm simulated the process of bee foraging and optimization and made the high likelihood region of the backward probability of particles moving to improve the rationality of particle distribution. The opposition-based learning (OBL) strategy is introduced to optimize the initial population of the artificial bee colony algorithm. The convergence factor is introduced into the neighborhood search strategy to limit the search range and improve the convergence speed. Finally, the crossover and mutation operations of the genetic algorithm are introduced into the search mechanism of the following bee, which makes the algorithm jump out of the local extreme value quickly and continue to search the global extreme value to improve its optimization ability. The simulation results show that the improved method can improve the estimation accuracy of particle filters, ensure the diversity of particles, and improve the rationality of particle distribution.

Keywords: particle filter, impoverishment, state estimation, artificial bee colony algorithm

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Authors: M. Habab, C. Benachaiba, B. Mazari, H. Madi, C. Benoudjafer

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The use of Distributed Generation (DG) has been increasing in recent years to fill the gap between energy supply and demand. This paper presents the grid connected wind energy system with UPQC based on fuzzy controller to compensate for voltage and current disturbances. The proposed system can improve power quality at the point of installation on power distribution systems. Simulation results show the capability of the DG-UPQC intelligent system to compensate sags voltage and current harmonics at the Point of Common Coupling (PCC).

Keywords: shunt active filter, series active filter, UPQC, power quality, sags voltage, distributed generation, wind turbine

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Authors: Abderrahmane El Kachani, El Mahjoub Chakir, Anass Ait Laachir, Abdelhamid Niaaniaa, Jamal Zerouaoui, Tarik Jarou

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This paper presents a wind turbine based on the doubly fed induction generator (DFIG) connected to the utility grid through a shunt active power filter (SAPF). The whole system is controlled by a double nonlinear predictive controller (DNPC). A Taylor series expansion is used to predict the outputs of the system. The control law is calculated by optimization of the cost function. The first nonlinear predictive controller (NPC) is designed to ensure the high performance tracking of the rotor speed and regulate the rotor current of the DFIG, while the second one is designed to control the SAPF in order to compensate the harmonic produces by the three-phase diode bridge supplied by a passive circuit (rd, Ld). As a result, we obtain sinusoidal waveforms of the stator voltage and stator current. The proposed nonlinear predictive controllers (NPCs) are validated via simulation on a 1.5 MW DFIG-based wind turbine connected to an SAPF. The results obtained appear to be satisfactory and promising.

Keywords: wind power, doubly fed induction generator, shunt active power filter, double nonlinear predictive controller

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Authors: Pankaj Verma, Gagandeep Singh Walia, Padma Devi, H. P. Singh

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Code Division Multiple Access 2000 operates on various RF channel bandwidths 1.2288 or 3.6864 Mcps. CDMA offers high bandwidth and wireless broadband services but the efficiency gets decreased because of many interfering factors like fading, interference, scattering, diffraction, refraction, reflection etc. To reduce the spectral bandwidth is one of the major concerns in modern day technology and this is achieved by pulse shaping filter. This paper investigates the effect of diversity (MRC), interpolation factor in Root Raised Cosine (RRC) filter for the QPSK and BPSK modulation schemes. It is made possible to send information with minimum inter symbol interference and within limited bandwidth with proper pulse shaping technique. Bit error rate (BER) performance is analyzed by applying diversity technique by varying the interpolation factor for Binary Phase Shift Keying (BPSK) and Quadrature Phase Shift Keying (QPSK). Interpolation factor increases the original sampling rate of a sequence to a higher rate and reduces the interference and diversity reduces the fading.

Keywords: CDMA2000, root raised cosine, roll off factor, ISI, diversity, interference, fading

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Authors: R. Rama Kishore, Sunesh

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Nowadays, robust and secure watermarking algorithm and its optimization have been need of the hour. A watermarking algorithm is presented to achieve the copy right protection of the owner based on visual cryptography, histogram shape property and entropy. In this, both host image and watermark are preprocessed. Host image is preprocessed by using Butterworth filter, and watermark is with visual cryptography. Applying visual cryptography on water mark generates two shares. One share is used for embedding the watermark, and the other one is used for solving any dispute with the aid of trusted authority. Usage of histogram shape makes the process more robust against geometric and signal processing attacks. The combination of visual cryptography, Butterworth filter, histogram, and entropy can make the algorithm more robust, imperceptible, and copy right protection of the owner.

Keywords: digital watermarking, visual cryptography, histogram, butter worth filter

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Authors: Hamidreza Saberkari, Mousa Shamsi, Hossein Ahmadi, Saeed Vaali, , MohammadHossein Sedaaghi

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In the recent years, using signal processing tools for accurate identification of the protein coding regions has become a challenge in bioinformatics. Most of the genomic signal processing methods is based on the period-3 characteristics of the nucleoids in DNA strands and consequently, spectral analysis is applied to the numerical sequences of DNA to find the location of periodical components. In this paper, a novel ensemble algorithm for gene selection in DNA sequences has been presented which is based on the combination of Goertzel algorithm and anti-notch filter (ANF). The proposed algorithm has many advantages when compared to other conventional methods. Firstly, it leads to identify the coding protein regions more accurate due to using the Goertzel algorithm which is tuned at the desired frequency. Secondly, faster detection time is achieved. The proposed algorithm is applied on several genes, including genes available in databases BG570 and HMR195 and their results are compared to other methods based on the nucleotide level evaluation criteria. Implementation results show the excellent performance of the proposed algorithm in identifying protein coding regions, specifically in identification of small-scale gene areas.

Keywords: protein coding regions, period-3, anti-notch filter, Goertzel algorithm

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Authors: M. Almutairi, S. Hadjiloucas

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The harmonic distortion of voltage is important in relation to power quality due to the interaction between the large diffusion of non-linear and time-varying single-phase and three-phase loads with power supply systems. However, harmonic distortion levels can be reduced by improving the design of polluting loads or by applying arrangements and adding filters. The application of passive filters is an effective solution that can be used to achieve harmonic mitigation mainly because filters offer high efficiency, simplicity, and are economical. Additionally, possible different frequency response characteristics can work to achieve certain required harmonic filtering targets. With these ideas in mind, the objective of this paper is to determine what size single tuned passive filters work in distribution networks best, in order to economically limit violations caused at a given point of common coupling (PCC). This article suggests that a single tuned passive filter could be employed in typical industrial power systems. Furthermore, constrained optimization can be used to find the optimal sizing of the passive filter in order to reduce both harmonic voltage and harmonic currents in the power system to an acceptable level, and, thus, improve the load power factor. The optimization technique works to minimize voltage total harmonic distortions (VTHD) and current total harmonic distortions (ITHD), where maintaining a given power factor at a specified range is desired. According to the IEEE Standard 519, both indices are viewed as constraints for the optimal passive filter design problem. The performance of this technique will be discussed using numerical examples taken from previous publications.

Keywords: harmonics, passive filter, power factor, power quality

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Authors: Bruna Luisa Ramos Prado Vasques, Mariane Rembold Petraglia, Antonio Petraglia

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This paper investigates MIMO (Multiple-Input Multiple-Output) adaptive filtering techniques for the application of supervised source separation in the context of convolutive mixtures. From the observation that there is correlation among the signals of the different mixtures, an improvement in the NSAF (Normalized Subband Adaptive Filter) algorithm is proposed in order to accelerate its convergence rate. Simulation results with mixtures of speech signals in reverberant environments show the superior performance of the proposed algorithm with respect to the performances of the NLMS (Normalized Least-Mean-Square) and conventional NSAF, considering both the convergence speed and SIR (Signal-to-Interference Ratio) after convergence.

Keywords: adaptive filtering, multi-rate processing, normalized subband adaptive filter, source separation

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Authors: Mohammad Izadkhah, Mojtaba Hoseini, Alireza Khalili Tehrani

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In this paper we presented a new method for tracking flying targets in color video sequences based on contour and kernel. The aim of this work is to overcome the problem of losing target in changing light, large displacement, changing speed, and occlusion. The proposed method is made in three steps, estimate the target location by particle filter, segmentation target region using neural network and find the exact contours by greedy snake algorithm. In the proposed method we have used both region and contour information to create target candidate model and this model is dynamically updated during tracking. To avoid the accumulation of errors when updating, target region given to a perceptron neural network to separate the target from background. Then its output used for exact calculation of size and center of the target. Also it is used as the initial contour for the greedy snake algorithm to find the exact target's edge. The proposed algorithm has been tested on a database which contains a lot of challenges such as high speed and agility of aircrafts, background clutter, occlusions, camera movement, and so on. The experimental results show that the use of neural network increases the accuracy of tracking and segmentation.

Keywords: video tracking, particle filter, greedy snake, neural network

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Authors: Hana Rabbouch

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In recent years, there has been considerable growth of denoising techniques mainly devoted to medical imaging. This important evolution is not only due to the progress of computing techniques, but also to the emergence of multi-resolution analysis (MRA) on both mathematical and algorithmic bases. In this paper, a comparative study is conducted between the two best-known MRA-based decomposition techniques: the Empirical Mode Decomposition (EMD) and the Discrete Wavelet Transform (DWT). The comparison is carried out in a framework of multi-scale denoising, where a Non-Local Means (NLM) filter is performed scale-by-scale to a sample of benchmark medical images. The results prove the effectiveness of the multiscaled denoising, especially when the NLM filtering is coupled with the EMD.

Keywords: medical imaging, non local means, denoising, multiscaled analysis, empirical mode decomposition, wavelets

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Authors: Ayesha Irum, Sadia Mumtaz, Abdul Rehman, Iffat Naz, Safia Ahmed

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The present study was conducted to evaluate the potential applicability of biological trickling filter system for the treatment of simulated textile wastewater containing reactive azo dyes with bacterial consortium under non-sterile conditions. The percentage decolorization for the treatment of wastewater containing structurally different dyes was found to be higher than 95% in all trials. The stable bacterial count of the biofilm on stone media of the trickling filter during the treatment confirmed the presence, proliferation, dominance and involvement of the added microbial consortium in the treatment of textile wastewater. Results of physicochemical parameters revealed the reduction in chemical oxygen demand (58.5-75.1%), sulphates (18.9-36.5%), and phosphates (63.6-73.0%). UV-Visible and FTIR spectroscopy confirmed decolorization of dye containing wastewater was the ultimate consequence of biodegradation. Toxicological studies revealed the nontoxic nature of degradative metabolites.

Keywords: biodegradation, textile dyes, waste water, trickling filters

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Authors: Takashi Shimizu, Tomoaki Hashimoto

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A class of implicit systems is known as a more generalized class of systems than a class of explicit systems. To establish a control method for such a generalized class of systems, we adopt model predictive control method which is a kind of optimal feedback control with a performance index that has a moving initial time and terminal time. However, model predictive control method is inapplicable to systems whose all state variables are not exactly known. In other words, model predictive control method is inapplicable to systems with limited measurable states. In fact, it is usual that the state variables of systems are measured through outputs, hence, only limited parts of them can be used directly. It is also usual that output signals are disturbed by process and sensor noises. Hence, it is important to establish a state estimation method for nonlinear implicit systems with taking the process noise and sensor noise into consideration. To this purpose, we apply the model predictive control method and unscented Kalman filter for solving the optimization and estimation problems of nonlinear implicit systems, respectively. The objective of this study is to establish a model predictive control with unscented Kalman filter for nonlinear implicit systems.

Keywords: optimal control, nonlinear systems, state estimation, Kalman filter

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Authors: Lim Sanny, Felix Christian

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The use of heavy equipment in Indonesia is always increasing. Cost reduction in procurement of spare parts is the aim of the company. The spare parts in this research are focused in the kind of filters. On the early step, the choosing of priority filter will be studied further by using the ABC analysis. To find out future demand of the filter, this research is using demand forecast by utilizing the QM software for windows. And to find out the best method of inventory control for each kind of filter is by comparing the total cost of Economic Order Quantity and Quick response inventory method. For the three kind of filters which are Cartridge, Engine oil – pn : 600-211-123, Element, Transmission – pn : 424-16-11140, and Element, Hydraulic – pn : 07063-01054, the best forecasting method is Linear regression. The best method for inventory control of Cartridge, Engine oil – pn : 600-211-123 and Element, Transmission – pn : 424-16-11140, is Quick Response Inventory, while the best method for Element, Hydraulic – pn : 07063-01054 is Economic Order Quantity.

Keywords: strategy, inventory, ABC analysis, forecasting, economic order quantity, quick response inventory

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Authors: Abdulbaset Mazarzaei

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Natural killer (NK) cells are innate immune effectors that play a pivotal role in combating tumors and infected cells. In recent years, the therapeutic potential of NK cells has gained significant attention due to their remarkable cytotoxic ability. This study focuses on investigating the cytotoxic effect of expanded NK cells enriched with interleukin 12 (IL12) and interleukin 15 (IL15), derived from the leukoreduction filter, on the K562 cell line. Firstly, NK cells were isolated from whole blood samples obtained from healthy volunteers. These cells were subsequently expanded ex vivo using a combination of feeder cells, IL12, and IL15. The expanded NK cells were then harvested and assessed for their cytotoxicity against K562, a well-established human chronic myelogenous leukemia cell line. The cytotoxicity was evaluated using flow cytometry assay. Results demonstrate that the expanded NK cells significantly exhibited enhanced cytotoxicity against K562 cells compared to non-expanded NK cells. Interestingly, the expanded NK cells derived specifically from IL12 and IL15-enriched leukoreduction filters showed a robust cytotoxic effect similar to the whole blood-derived NK cells. These findings suggest that IL12 and IL15 in the leukoreduction filter are crucial in promoting NK cell cytotoxicity. Furthermore, the expanded NK cells displayed relatively similar cytotoxicity profiles to whole blood-derived NK cells, indicating their comparable capability in targeting and eliminating tumor cells. This observation is of significant relevance as expanded NK cells from the leukoreduction filter could potentially serve as a readily accessible and efficient source for adoptive immunotherapy. In conclusion, this study highlights the significant cytotoxic effect of expanded NK cells enriched with IL12 and IL15 obtained from the leukoreduction filter on the K562 cell line. Moreover, it emphasizes that these expanded NK cells exhibit comparable cytotoxicity to whole blood-derived NK cells. These findings reinforce the potential clinical utility of using expanded NK cells from the leukoreduction filter as an effective strategy in adoptive immunotherapy for the treatment of cancer. Further studies are warranted to explore the broader implications of this approach in clinical settings.

Keywords: natural killer (NK) cells, Cytotoxicity, Leukoreduction filter, IL-12 and IL-15 Cytokines

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Authors: Ali Cheraghian, Farshid Hajati, Soheila Gheisari, Yongsheng Gao

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In this paper, we present a novel 2.5D face recognition method based on Gabor Discrete Cosine Transform (GDCT). In the proposed method, the Gabor filter is applied to extract feature vectors from the texture and the depth information. Then, Discrete Cosine Transform (DCT) is used for dimensionality and redundancy reduction to improve computational efficiency. The system is combined texture and depth information in the decision level, which presents higher performance compared to methods, which use texture and depth information, separately. The proposed algorithm is examined on publically available Bosphorus database including models with pose variation. The experimental results show that the proposed method has a higher performance compared to the benchmark.

Keywords: Gabor filter, discrete cosine transform, 2.5d face recognition, pose

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Authors: Hajer Rahali, Zied Hajaiej, Noureddine Ellouze

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The goal of speech parameterization is to extract the relevant information about what is being spoken from the audio signal. In speech recognition systems Mel-Frequency Cepstral Coefficients (MFCC) and Relative Spectral Mel-Frequency Cepstral Coefficients (RASTA-MFCC) are the two main techniques used. It will be shown in this paper that it presents some modifications to the original MFCC method. In our work the effectiveness of proposed changes to MFCC called Modified Function Cepstral Coefficients (MODFCC) were tested and compared against the original MFCC and RASTA-MFCC features. The prosodic features such as jitter and shimmer are added to baseline spectral features. The above-mentioned techniques were tested with impulsive signals under various noisy conditions within AURORA databases.

Keywords: auditory filter, impulsive noise, MFCC, prosodic features, RASTA filter

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Authors: T. Hari Prasath, P. Ithaya Rani

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In the world of visual technology, recognizing emotions from the face images is a challenging task. Several related methods have not utilized the dynamic facial features effectively for high performance. This paper proposes a method for emotions recognition using dynamic facial features with high performance. Initially, local features are captured by Gabor filter with different scale and orientations in each frame for finding the position and scale of face part from different backgrounds. The Gabor features are sent to the ensemble classifier for detecting Gabor facial features. The region of dynamic features is captured from the Gabor facial features in the consecutive frames which represent the dynamic variations of facial appearances. In each region of dynamic features is normalized using Z-score normalization method which is further encoded into binary pattern features with the help of threshold values. The binary features are passed to Multi-class AdaBoost classifier algorithm with the well-trained database contain happiness, sadness, surprise, fear, anger, disgust, and neutral expressions to classify the discriminative dynamic features for emotions recognition. The developed method is deployed on the Ryerson Multimedia Research Lab and Cohn-Kanade databases and they show significant performance improvement owing to their dynamic features when compared with the existing methods.

Keywords: detecting face, Gabor filter, multi-class AdaBoost classifier, Z-score normalization

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Authors: Sajidullah Khan, Najeeb Ullah, Wang Yin Chai, Chai Soo See

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In this paper, we propose an approach to remove impulse and Poisson noise from X-ray images. Many filters have been used for impulse noise removal from color and gray scale images with their own strengths and weaknesses but X-ray images contain Poisson noise and unfortunately there is no intelligent filter which can detect impulse and Poisson noise from X-ray images. Our proposed filter uses the upgraded layer discrimination approach to detect both Impulse and Poisson noise corrupted pixels in X-ray images and then restores only those detected pixels with a simple efficient and reliable one line equation. Our Proposed algorithms are very effective and much more efficient than all existing filters used only for Impulse noise removal. The proposed method uses a new powerful and efficient noise detection method to determine whether the pixel under observation is corrupted or noise free. Results from computer simulations are used to demonstrate pleasing performance of our proposed method.

Keywords: X-ray image de-noising, impulse noise, poisson noise, PRWF

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Authors: Raja Rajeswari K

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Orthogonal Frequency Division Multiplexing (OFDM), a multi Carrier transmission technique that has been used in implementing the majority of wireless applications like Wireless Network Protocol Standards (like IEEE 802.11a, IEEE 802.11n), in telecommunications (like LTE, LTE-Advanced) and also in Digital Audio & Video Broadcast standards. The latest research and development in the area of orthogonal frequency division multiplexing, Universal Filtered Multi Carrier (UFMC) & Filtered OFDM (F-OFDM) has attracted lots of attention for wideband wireless communications. In this paper UFMC & F-OFDM system are implemented and comparative analysis are carried out in terms of M-ary QAM modulation scheme over Dolph-chebyshev filter & rectangular window filter and to estimate Bit Error Rate (BER) over Rayleigh fading channel.

Keywords: UFMC, F-OFDM, BER, M-ary QAM

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Authors: Haggag H. Mohamed, Ghatass F. Zekry, Shalaby A. Elsayed

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Most sources of air pollution in Egypt are of anthropogenic origin. Alexandria Governorate is located at north of Egypt. The main contributing sectors of air pollution in Alexandria are industry, transportation and area source due to human activities. Alexandria includes more than 40% of the industrial activities in Egypt. Cement manufacture contributes a significant amount to the particulate pollution load. Alexandria Portland Cement Company (APCC) surrounding was selected to be the study area. APCC main kiln stack Total Suspended Particulate (TSP) continuous monitoring data was collected for assessment of dust emission control technology. Electro Static Precipitator (ESP) was fixed on the cement kiln since 2002. The collected data of TSP for first quarter of 2012 was compared to that one in first quarter of 2013 after installation of new bag house filter. In the present study, based on these monitoring data and metrological data a detailed air dispersion modeling investigation was carried out using the Industrial Source Complex Short Term model (ISC3-ST) to find out the impact of applying new bag house filter control technology on the neighborhood ambient air quality. The model results show a drastic reduction of the ambient TSP hourly average concentration from 44.94μg/m3 to 5.78μg/m3 which assures the huge positive impact on the ambient air quality by applying bag house filter technology on APCC cement kiln

Keywords: air pollution modeling, ambient air quality, baghouse filter, cement industry

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Authors: Abdul Basit, Amil Daraz, Guoqiang Zhang

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With the increasing demand for wireless communication systems for unlicensed indoor applications, the FCC, in February 2002, allocated unlicensed bands ranging from 3.1 GHZ to 10.6 GHz with fractional bandwidth of about 109 %, because it plays a key role in the radiofrequency (RF) front ends devices and has been widely applied in many other microwave circuits. Targeting the proposed band defined by the FCC for the UWB system, this article presents a UWB bandpass filter with three stop bands for the mitigation of wireless bands that may interfere with the UWB range. For this purpose, two resonators are utilized for the implementation of triple-notched bands. The C-shaped resonator is used for the first notch band creation at 3.4 GHz to suppress the WiMAX signal, while the H-shaped resonator is employed in the initial UWB design to introduce the dual notched characteristic at 4.5 GHz and 8.1 GHz to reject the WLAN and Satellite Communication signals. The overall circuit area covered by the proposed design is 30.6 mm × 20 mm, or in terms of guided wavelength at the first stopband, its size is 0.06 λg × 0.02 λg. The presented structure shows a good return loss under -10 dB over most of the passband and greater than -15 dB for the notched frequency bands. Finally, the filter is simulated and analyzed in HFSS 15.0. All the bands for the rejection of wireless signals are independently controlled, which makes this work superior to the rest of the UWB filters presented in the literature.

Keywords: a bandpass filter (BPF), ultra-wideband (UWB), wireless communication, C-shaped resonator, triple notch

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Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid

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Interpretation of medical images benefits from anatomical and physiological priors to optimize computer-aided diagnosis applications. Segmentation of liver, spleen and kidneys is regarded as a major primary step in the computer-aided diagnosis of abdominal organ diseases. In this paper, a semi-automated method for medical image data is presented for the abdominal organ segmentation data using mathematical morphology. Our proposed method is based on hierarchical segmentation and watershed algorithm. In our approach, a powerful technique has been designed to suppress over-segmentation based on mosaic image and on the computation of the watershed transform. Our algorithm is currency in two parts. In the first, we seek to improve the quality of the gradient-mosaic image. In this step, we propose a method for improving the gradient-mosaic image by applying the anisotropic diffusion filter followed by the morphological filters. Thereafter, we proceed to the hierarchical segmentation of the liver, spleen and kidney. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work.

Keywords: anisotropic diffusion filter, CT images, morphological filter, mosaic image, simultaneous organ segmentation, the watershed algorithm

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Authors: Justas Dilys

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ThispaperaddressestheimplementationandoptimizationofanUnscentedKalmanFilter(UKF) for the Permanent Magnet Synchronous Motor (PMSM) sensorless control using an ARM Cortex- M3 microcontroller. A various optimization levels based on arithmetic calculation reduction was implemented in ARM Cortex-M3 microcontroller. The execution time of UKF estimator was up to 90µs without loss of accuracy. Moreover, simulation studies on the Unscented Kalman filters are carried out using Matlab to explore the usability of the UKF in a sensorless PMSMdrive.

Keywords: unscented kalman filter, ARM, PMSM, implementation

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Authors: Reji Thankachan, Varsha PS

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Both image capturing devices and human visual systems are nonlinear. Hence nonlinear filtering methods outperforms its linear counterpart in many applications. Linear methods are unable to remove impulsive noise in images by preserving its edges and fine details. In addition, linear algorithms are unable to remove signal dependent or multiplicative noise in images. This paper presents an approach to denoise and smoothen the Bipolar impulse noised images and videos using improved Kuwahara filter. It involves a 2 stage algorithm which includes a noise detection followed by filtering. Numerous simulation demonstrate that proposed method outperforms the existing method by eliminating the painting like flattening effect along the local feature direction while preserving edge with improvement in PSNR and MSE.

Keywords: bipolar impulse noise, Kuwahara, PSNR MSE, PDF

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Authors: Thang V. Kieu, Long P. Nguyen

Abstract:

Kernelized Correlation Filter (KCF) based trackers have gained a lot of attention recently because of their accuracy and fast calculation speed. However, this algorithm is not robust in cases where the object is lost by a sudden change of direction, being obscured or going out of view. In order to improve KCF performance in long-term tracking, this paper proposes an anomaly detection method for target loss warning by analyzing the response map of each frame, and a classification algorithm for reliable target re-locating mechanism by using Random fern. Being tested with Visual Tracker Benchmark and Visual Object Tracking datasets, the experimental results indicated that the precision and success rate of the proposed algorithm were 2.92 and 2.61 times higher than that of the original KCF algorithm, respectively. Moreover, the proposed tracker handles occlusion better than many state-of-the-art long-term tracking methods while running at 60 frames per second.

Keywords: correlation filter, long-term tracking, random fern, real-time tracking

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