Scielo RSS <![CDATA[Journal of applied research and technology]]> vol. 13 num. 1 lang. es <![CDATA[SciELO Logo]]> <![CDATA[<b>A Novel "Single-Path" vs. "Few-Path" Test Based on Higher Order Statistics to Possibly Start-Up Coherent Combining</b>]]> This paper focuses on an innovative hypothesis test for discrimination of wireless mobile channels based on higher order statistics to possibly start-up coherent combining. We have devised a new testing procedure, namely the Rakeness test, that statistically measures how much the series under investigation (amplitude samples of matched filter receiver's output) fits Rice vs. non-Rice models. This is equivalent to discriminate between the cases of a channel with one single dominant path (strong propagation), or with few dominant paths (weak propagation). Then, mathematical expressions for the bias and variance of the new testing variable are derived, by a 3-D reduced Taylor's expansion up to the second order. The achieved results, obtained throughout theory and simulations, evidence the robustness of this innovative test. Our test can hence be used as a preliminary signal processing method to decide if simpler choices (i.e. matched filters) or cumbersome coherent combining strategies (i.e. Rake receivers) can be effectively implemented at the receiver's side. <![CDATA[<b>Privacy-preserving security solution for cloud services</b>]]> We propose a novel privacy-preserving security solution for cloud services. Our solution is based on an efficient non-bilinear group signature scheme providing the anonymous access to cloud services and shared storage servers. The novel solution offers anonymous authenticationfor registered users. Thus, users' personal attributes (age, valid registration, successful payment) can be proven without revealing users' identity, and users can use cloud services without any threat of profiling their behavior. However, if a user breaks provider's rules, his access right is revoked.Our solution provides anonymous access, unlinkability and the confidentiality of transmitted data. We implement our solution as a proof of concept applicationand present the experimental results. Further, we analyzecurrent privacy preserving solutions for cloud services and group signature schemes as basic parts of privacy enhancing solutions in cloud services. We compare the performance of our solution with the related solutionsand schemes. <![CDATA[<b>Exploring and Measuring Possible Co-Existences between DVB-T2-Lite and LTE Systems in Ideal and Portable Fading Channels</b>]]> From the point of technical innovations the development and standardization of Digital Video Broadcasting - 2nd Generation Terrestrial (DVB-T2) and Long-Term Evolution (LTE) systems are definitely the most significant results in the last decade. These systems have a very high potential to fulfill the highest user requirements, but they can operate in the same frequency spectrum. As a result, different co-existence scenarios can occur. In this paper, we explore and measure the co-existence between DVB-T2-Lite (e.g. portable TV) and LTE multimedia services in ideal and portable fading channel models. Theoretical backgrounds of the investigated co-existence scenarios, proposal and realization of an appropriate workplace for their measuring and evaluation are presented and described. Moreover, deeper investigation of the mutual influence of the DVB-T2 system on the LTE one is also explored and graphically illustrated. The obtained results show that these co-existences could be critical for both systems from the point of providing multimedia services with a constant level of Quality of Services (QoS). <![CDATA[<b>Detection and Mitigation of GPS Spoofing Based on Antenna Array Processing</b>]]> In this article authors present an application of spatial processing methods for GPS spoofing detection and mitigation. In the first part of this article, a spoofing detection method, based on phase delay measurements, is proposed. Accuracy and precision of phase delay estimation is assessed for various qualities of received signal. Spoofing detection thresholds are determined. Efficiency of this method is evaluated in terms of probability of false alarm and probability of detection when 4 to 8 GPS signals are received. It is shown that the probability of spoofing detection is greater than 99 percent if carrier-to-noise ratio is at least 46 dBHz. The second part of the article presents a GPS spoofing mitigation method which uses spatial filtering (null-steering) for excision of undesired signals. Performance of this method is analyzed in various conditions. Attenuation of undesired signals is estimated to be at least 60 dB when their signal-to-noise ratio is high. Furthermore, statistical analysis of the spatial filtering influence on the availability of true signals is provided. Eventually, a concept of practical anti-spoofing system implementation is proposed. <![CDATA[<b>Automated Multi-Contrast Brain Pathological Area Extraction from 2D MR Images</b>]]> The aim of this work is to propose the fully automated pathological area extraction from multi-parametric 2D MR images of brain. The proposed method is based on multi-resolution symmetry analysis and automatic thresholding. The proposed algorithm first detects the presence of pathology and then starts its extraction. T2 images are used for the presence detection and the multi-contrast MRI is used for the extraction, concretely T2 and FLAIR images. The extraction is based on thresholding, where Otsu's algorithm is used for the automatic determination of the threshold. Since the method is based on symmetry, it works for both axial and coronal planes. In both these planes of healthy brain, the approximate left-right symmetry exists and it is used as the prior knowledge for searching the approximate pathology location. It is assumed that this area is not located symmetrically in both hemispheres, which is met in most cases. The detection algorithm was tested on 203 T2-weighted images and reached the true positive rate of 87.52% and true negative rate of 93.14%. The extraction algorithm was tested on 357 axial and 443 coronal real images from publicly available BRATS databases containing 3D volumes brain tumor patients. The results were evaluated by Dice Coefficient (axial: 0.85±0.11, coronal 0.82±0.18) and by Accuracy (axial: 0.96±0.05, coronal 0.94±0.09). <![CDATA[<b>Trajectory Tracking Control in a Single Flexible-Link Robot using Finite Differences and Sliding Modes</b>]]> In this article it is shown how the end effector position of a single flexible-link robot can be directly controlled by the angular position of its joint, so that, trajectory tracking in the end effector of the robot is possible by properly designing a reference trajectory for the joint angle. In order to ensure trajectory tracking of the angular position of the robot joint, a Sliding Modes Control (SMC) scheme is employed once the desired trajectory for the robot joint has been designed. SMC scheme is chosen because its known robust performance under dynamical disturbances and modeling inaccuracies. Then, the angular position of the robot joint plays the role of a virtual control input for the flexible dynamics of the link. Both, regulation and trajectory tracking of the end effector position are achieved by using the scheme devised in this work. The Finite Differences Method (FDM) is employed to simulate the closed loop performance of the flexible-link robot, because its dynamics are assumed to be governed by the undamped Partial Differential Equation (PDE) of the Euler-Bernoulli Beam (EBB). <![CDATA[<b>A Nonlinear Hybrid Filter for Salt & Pepper Noise Removal from Color Images</b>]]> Impulse noise reduction or removal is a very active research area of image processing. A nonlinear hybrid filter for removing fixed impulse noise (salt & pepper) noise from color images has been proposed in this study. Technique is based on mathematical morphology and trimmed standard median filter. Proposed filter is composed of a sequence of morphological standard and well known operations erosion-dilation and trimmed standard median filter. It removes the fixed impulse noise (salt & pepper) very well without distorting the image features, color components and edges. It does not introduce blurring and moving effects even in high noise densities (up to 90%). The standard similarity measure peak signal to noise ratio (PSNR) and computation time have been used to evaluate the performance of proposed hybrid filter. <![CDATA[<b>An Enhanced Adaptive Algorithm to Mitigate Mis-coordination Problem of the Third Zone of Distance Relays</b>]]> Cascaded tripping of power lines due to mal-operation of zone 3 distance relays is one of the main causes of many blackouts worldwide. The improved protection technique for zone 3 can help to prevent such mal-operation and, thus, more reliable power systems can be envisaged. This paper presents a novel zone-3 setting scheme based on impedance seen by distance relays in order to calculate zone-3 setting of the relays when faults are simulated on the reach of zone-2 of primary distance relays. The new technique is also enhanced to be used in an adaptive protection system. Since three phase fault rarely occurs in the system and in order to have better demonstration of effectiveness of the proposed scheme, it is tested for various type of faults such as, two phase (AB), single phase to ground (AG) and two phase to ground (ABG) as well as three-phase (ABC) using data simulated through DIgSILENT in the IEEE 30-bus test system during different topologies. The simulation results show that the novel zone 3 distance relay elements using the proposed method operate correctly for various events. <![CDATA[<b>Robust Face Recognition Technique under Varying Illumination</b>]]> Face recognition is one of a complex biometrics in the field of pattern recognition due to the constraints imposed by variation in the appearance of facial images. These changes in appearance are affected by variation in illumination, expression or occlusions etc. Illumination can be considered a complex problem in both indoor and outdoor pattern matching. Literature studies have revealed that two problems of textural based illumination handling in face recognition seem to be very common. Firstly, textural values are changed during illumination normalization due to increase in the contrast that changes the original pixels of face. Secondly, it minimizes the distance between interclasses which increases the false acceptance rates. This paper addresses these issues and proposes a robust algorithm that overcomes these limitations. The limitations are resolved through transforming pixels from nonillumination side to illuminated side. It has been revealed that proposed algorithm produced better results as compared to existing related algorithms. <![CDATA[<b>Proposing a Features Preprocessing Method Based on Artificial Immune and Minimum Classification Errors Methods</b>]]> Artificial immune systems that have been inspired from organic immune systems, have drawn many attentions in recent years (and have been considered) as an evolutionary algorithm and have been applied in different papers. This algorithm can be used in two different areas of optimization and classification. In this paper, an artificial immune algorithm has been applied in optimization problem. In particular artificial immune systems have been used for computing the mapping matrices and improving features. Comparison of results of proposed method with other preprocessing methods shows the superiority of the proposed method so that in 90% of cases it has the best performance based on different measures. Evaluation measures are including classification rate, variance and compression measure. <![CDATA[<b>P2P Video Streaming Strategies based on Scalable Video Coding</b>]]> Video streaming over the Internet has gained significant popularity during the last years, and the academy and industry have realized a great research effort in this direction. In this scenario, scalable video coding (SVC) has emerged as an important video standard to provide more functionality to video transmission and storage applications. This paper proposes and evaluates two strategies based on scalable video coding for P2P video streaming services. In the first strategy, SVC is used to offer differentiated quality video to peers with heterogeneous capacities. The second strategy uses SVC to reach a homogeneous video quality between different videos from different sources. The obtained results show that our proposed strategies enable a system to improve its performance and introduce benefits such as differentiated quality of video for clients with heterogeneous capacities and variable network conditions. <![CDATA[<b>Decision Support for Route Search and Optimum Finding in Transport Networks under Uncertainty</b>]]> The aim of this paper is to find solution for route planning in road network for a user, and to find the equilibrium in the path optimization problem, where the roads have uncertain attributes. The concept is based on the Dempster-Shafer theory and Dijkstra's algorithm, which help to model the uncertainty and to find the best route, respectively. Based on uncertain influencing factors an interval of travel time (so called cost interval) of each road can be calculated. An algorithm has been outlined for determining the best route comparing the intervals and using decision rules depending on the user's attitude. Priorities can be defined among the rules, and the constructed rule based mechanism for users' demands is great contribution of this paper. The first task is discussed in more general in this paper, i.e. instead of travel time a general cost is investigated for any kind of network. At the solution of the second task, where the goal is to find equilibrium in transport network at case of uncertain situation, the result of the first task is used. Simulation tool has been used to find the equilibrium, which gives only approximate solution, but this is sufficient and appropriate solution for large networks. Furthermore this is built in a decision support system, which is another contribution of this work. At the end of the paper the implementation of the theoretical concept is presented with a test bed of a town presenting effects of different uncertain influencing factors for the roads. <![CDATA[<b>Harmonic Mitigation using 36-Pulse AC-DC Converter for Direct Torque Controlled Induction Motor Drives</b>]]> This paper presents the design and analysis of a transformer based 36-pulse ac-dc converters which supplies direct torque controlled induction motor drives (DTCIMD's) in order to have better power quality conditions at the point of common coupling. The converters output voltage is accomplished via two paralleled eighteen-pulse ac-dc converters each of them consisting of nine-phase diode bridge rectifier. The design procedure of magnetics is in a way such that makes it suitable for retrofit applications where a six-pulse diode bridge rectifier is being utilized. The 36-pulse structure improves power quality criteria at ac mains and makes them consistent with the IEEE-519 standard requirements for varying loads. Furthermore, near unity power factor is obtained for a wide range of DTCIMD operation. A comparison is made between 6-pulse and 36-pulse converters (Polygon, Fork, and Hexagon) from view point of power quality indices. Results show that input current total harmonic distortion (THD) is less than 4% for the 36-pulse topologies at variable loads. The Delta/Hexagon connected platform could simplify the resulted configuration for the converters and reducing the costs. <![CDATA[<b>Multi-Objective Feature Subset Selection using Non-dominated Sorting Genetic Algorithm</b>]]> This paper presents an evolutionary algorithm based technique to solve multi-objective feature subset selection problem. The data used for classification contains large number of features called attributes. Some of these attributes are not relevant and needs to be eliminated. In classification procedure, each feature has an effect on the accuracy, cost and learning time of the classifier. So, there is a strong requirement to select a subset of the features before building the classifier. This proposed technique treats feature subset selection as multi-objective optimization problem. This research uses one of the latest multi-objective genetic algorithms (NSGA - II). The fitness value of a particular feature subset is measured by using ID3. The testing accuracy acquired is then assigned to the fitness value. This technique is tested on several datasets taken from the UCI machine repository. The experiments demonstrate the feasibility of using NSGA-II for feature subset selection. <![CDATA[<b>Fused Empirical Mode Decomposition and MUSIC Algorithms for Detecting Multiple Combined Faults in Induction Motors</b>]]> Detection of failures in induction motors is one of the most important concerns in industry. An unexpected fault in the induction motors can cause a loss of financial resources and waste of time that most companies cannot afford. The contribution of this paper is a fusion of the Empirical Mode Decomposition (EMD) and Multiple Signal Classification (MUSIC) methodologies for detection of multiple combined faults which provides an accurate and effective strategy for the motor condition diagnosis.