International Journal of Circuits, Systems and Signal Processing

E-ISSN: 1998-4464
Volume 11, 2017

Notice: As of 2014 and for the forthcoming years, the publication frequency/periodicity of NAUN Journals is adapted to the 'continuously updated' model. What this means is that instead of being separated into issues, new papers will be added on a continuous basis, allowing a more regular flow and shorter publication times. The papers will appear in reverse order, therefore the most recent one will be on top.

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Volume 11, 2017

Title of the Paper: Technological Solutions of Selected Components of Energo-electronic Power Supply System PES in the Field of AC/DC/DC Processing in Accordance with a Trend of More Electric Aircraft


Authors: Lucjan Setlak, Rafał Kowalik, Wojciech Redo

Pages: 471-477

Abstract: This article presents selected solutions for the basic components of the energo-electronic power supply system PES, which are multi-pulse (6-, 12- and 18-, 24-) impulse rectifiers, with particular emphasis on AC/DC/DC processing. The multi-pulse rectifier solutions are used in modern military aviation, both of the Lockheed Martin company and its latest JSF F-35 and F-22 Raptor aircrafts, as well as in the civil aircrafts architecture of the Airbus and Boeing companies in the field of their hit products (A-380, A-350XWB and B-787), consistent with the concept of a more electric aircraft. The main goal of the article is to develop a mathematical model in the field of AC/DC/DC processing and simulation of selected multi-pulse rectifiers, implemented on modern aircrafts. Based on the above, the final part of the work presents important practical conclusions resulting from the analysis and simulation tests of key components of the PES system, i.e. selected multi-pulse rectifiers.

Title of the Paper: Coding Mental States from EEG Signals and Evaluating their Integrated Information Content: a Computational Intelligence Approach


Authors: Rita Pizzi, Marialessia Musumeci

Pages: 464-470

Abstract: The paper presents a method to identify and code mental states from EEG signals, performing their dynamical analysis by means of an Artificial Neural Network. The method has been tested on signals from a 14 electrodes EEG system connected to immersive glasses that allow a realistic audiovisual experience. A software procedure synchronizes the acquired signals with the sensory experiences presented in a video. A suitable Artificial Neural Network detects and codifies the chaotic attractors signals related to the sensory and cognitive events. The analysis shows that the binary codes corresponding to similar cognitive and perceptive stimuli are similar, and well differentiated from the codes corresponding to different stimuli. The dynamical attractors corresponding to each mental state are submitted to a procedure that evaluates their Integrated Information content in the qualia space.

Title of the Paper: Recursive Adaptive Color KLT for Image Sequences


Authors: Roumen K. Kountchev, Roumiana A. Kountcheva

Pages: 454-463

Abstract: The method Recursive color space transform for a sequence of correlated RGB images is based on the algorithm Adaptive Color KLT (AC-KLT). The non-recursive AC-KLT for a sequence of color images is not efficient enough in this case, because each image should be processed individually. Depending on the kind of the images in the processed sequence (for example, color video, multi-view, medical sequences, etc.), the pixels of same position, but from two neighbor images, have significant similarity which in most cases is over 90 %. In such case, strong possibility exists for high reduction of the information redundancy of the color information. To this end, here is offered the method Recursive AC-KLT (RAC-KLT) whose basic idea is to execute the AC-KLT for the first image in the sequence, and for the next images to calculate the values of the difference parameters only, which are needed for the successful restoration of the color information. The efficiency of the new method grows up together with the mutual correlation between the consecutive images in the sequence. The evaluation of the computational complexity of the new algorithm confirms its advantage towards the basic AC-KLT. In the paper are also given some experimental results from the comparison between color transforms YCrCb, AC-KLT and RAC-KLT which show the higher efficiency of the new approach. Here are also commented the possible application areas for efficient representation of correlated image sequences.

Title of the Paper: Approximate Early Output Asynchronous Adders Based on Dual-Rail Data Encoding and 4-Phase Return-to-Zero and Return-to-One Handshaking


Authors: P. Balasubramanian

Pages: 445-453

Abstract: Approximate computing is emerging as an alternative to accurate computing due to its potential for realizing digital circuits and systems with low power dissipation, less critical path delay, and less area occupancy for an acceptable trade-off in the accuracy of results. In the domain of computer arithmetic, several approximate adders and multipliers have been designed and their potential have been showcased versus accurate adders and multipliers for practical digital signal processing applications. Nevertheless, in the existing literature, almost all the approximate adders and multipliers reported correspond to the synchronous design method. In this work, we consider robust asynchronous i.e. quasi-delay-insensitive realizations of approximate adders by employing delay-insensitive codes for data representation and processing, and the 4-phase handshake protocols for data communication. The 4-phase handshake protocols used are the return-to-zero and the return-to-one protocols. Specifically, we consider the implementations of 32-bit approximate adders based on the return-to-zero and return-to-one handshake protocols by adopting the delay-insensitive dual-rail code for data encoding. We consider a range of approximations varying from 4-bits to 20-bits for the least significant positions of the accurate 32-bit asynchronous adder. The asynchronous adders correspond to early output (i.e. early reset) type, which are based on the well-known ripple carry adder architecture. The experimental results show that approximate asynchronous adders achieve reductions in the design metrics such as latency, cycle time, average power dissipation, and silicon area compared to the accurate asynchronous adders. Further, the reductions in the design metrics are greater for the return-to-one protocol compared to the return-tozero protocol. The design metrics were estimated using a 32/28nm CMOS technology.

Title of the Paper: Stability Issues in Multivalue Numerical Methods for Ordinary Differential Equations


Authors: Angelamaria Cardone, Dajana Conte, Raffaele D’Ambrosio, Beatrice Paternoster

Pages: 433-444

Abstract: We describe the derivation of highly stable general linear methods for the numerical solution of initial value problems for systems of ordinary differential equations. In particular we describe the construction of explicit Nordsiek methods and implicit two step Runge Kutta methods with stability properties determined by quadratic stability functions. We aim for methods which have wide stability regions in the explicit case and which are A- and L-stable in the implicit one case. We moreover describe the construction of algebraically stable and G-stable two step Runge Kutta methods. Examples of methods are then provided.

Title of the Paper: Fractional Complex Transform for the Solution of Time-Fractional Advection-Diffusion Model


Authors: S. O. Edeki, G. O. Akinlabi, C. E. Odo

Pages: 425-432

Abstract: In this paper, we obtain exact solutions of time-fractional Advection-Diffusion model equations by means Fractional Complex Transform (FCT) coupled with modified differential transform method. The derivatives are defined in terms of Jumarie’s sense. Two illustrative examples are considered in elucidating the effectiveness of the proposed technique. The method requires little knowledge of fractional calculus while obtaining exact solutions of fractional equations with high level of accuracy not being compromised.

Title of the Paper: An Improved Parallel Scalable K-means++ Massive Data Clustering Algorithm Based on Cloud Computing


Authors: Shuzhi Nie

Pages: 420-424

Abstract: Clustering is one of the most effective algorithms in data analysis and management. It has been widely used in related fields. However, with the rapid development of mass data, the traditional clustering algorithms have disadvantages of poor scalability and low efficiency. How to effectively cluster mass data has become a hot area in the field of data mining. According to the characteristics of massive data with the large amount of data and the variety of data types, used MapReduce distributed parallelization of the data processing model. For the high requirements of real-time analysis and processing, proposed an improved parallel k-means++ clustering method based on MapReduce, implemented the weighted k-means++ initialization method, improved the slow convergence speed and often converges to local optimum, reduced the MapReduce job iteration, economized a lot of network and I/O overhead etc., to improve the scalability of the algorithm, upgrade the efficiency, ensure the clustering results of the algorithm. The proposed optimization strategy can avoid a lot of distance calculation in real datasets and synthetic datasets. More importantly, as K becomes larger, the pruning ability will become more and more obvious. The result is almost perfect sequence of linear complexity of the optimal clustering results almost perfect nonlinear function approximation, while the almost perfect nonlinear function has the very good difference property, is the best function of the difference evenness. The experiment results proved the validity and superiority of the algorithm.

Title of the Paper: Stock Financial Bubbles: a Trinomial Trees Based Analysis


Authors: Luca Di Persio, Francesco Guida

Pages: 411-419

Abstract: In the present work we consider a novel approach to model the dynamic of financial bubbles. In particular, we exploit a technique based on trinomial trees, which is mainly inspired by the typical Market Order Book (MOB) structure. We use a bottom-up approach, according to the typical MOB rules, to derive the relevant generator process for the financial quantities characterizing the market we are considering. Our proposal pays specific attention to consider the real world changes in probability levels characterizing the bidask preferences driven by market movements. We show that financial bubbles are, indeed, originated by these movements which, in turn, amplify their growth. Numerical experiments are provided to show the effectiveness of our results within real volatility wars scenarios. Namely, we study realistic economic frameworks characterized by volatility levels showing great fluctuations, in relatively small times.

Title of the Paper: Line Drawing Approach Based on Visual Curvature Estimation


Authors: Jun Liu, Mingquan Zhou, Guohua Geng, Feng Xiao, Defa Hu

Pages: 401-410

Abstract: In order to effectively extract the feature lines of the three-dimensional model of the surface with noise, the reasons for the loss of texture details in the preprocessing stage are discussed and a new method of line drawing based on visual curvature estimation of the cultural relics is proposed. First, estimate the discrete curvature on triangular mesh vertex and divide the cultural relic model into the flat region and the non-flat region according to the curvature distribution; then, conduct the sharpening filter on the vertex of the non-flat region to calculate the new mesh vertex coordinates; finally, basing on the visual curvature, extract the curved contour line to achieve automatic line drawing of cultural relics of the triangular mesh model. The experimental results show that the non-flat contour lines based on the visual curvature remain the details of the surface texture of the 3D model and avoid the (?)uneven drawing lines by using the directed ridge line and valley line drawing.

Title of the Paper: Physical Phenomena Captured in a Mathematical Model of p-NOI and NOI Transistors


Authors: Cristian Ravariu, Dan Eduard Mihaiescu

Pages: 396-400

Abstract: The scope of this paper is to establish a mathematical model of the tunneling current between drain and source thru a Nothing On Insulator – NOI transistor and its variants. Using the first, second and third order derivatives of the analytical model, aimed by the Non-linear Electrical Conduction Theorem (NECT), new rigorously extraction methods of the threshold drain voltage is presented. Finally, some validations of the exponential analytical model by simulations are presented. Two distinct work regimes for the NOI and p-NOI devices are established: strong and weak tunneling.

Title of the Paper: G3-PLC Time-frequency Combined Segment Reconstruction Coding Algorithm


Authors: Li Zhao, Xiaolu Jiao, Tong Zhu, Zhigang Liu, Feng Zhang

Pages: 390-395

Abstract: Due to the serious impact of the power line channel characteristics on the communication performance, especially in the case of strong noise interference the reliability of the communication system can’t be guaranteed. In this case, a time-frequency combined segment reconstruction coding algorithm is proposed based on the G3-PLC standard, and the signal is decoded at the receiving end according to the maximum likelihood decoding criterion. The algorithm can effectively resist the interference of noise in time domain and frequency domain, improve the anti-noise performance of power line communication system, ensure the stability of the system and meet the high quality communication demand of power line. The simulation results show that compared with the current G3-PLC system, the proposed algorithm can improve the anti-noise performance about 8dB, and can achieve reliable communication in the case of strong noise interference.

Title of the Paper: Design of Transduction Using NMOS for 3D-Printed NPGF Electrode


Authors: A. Arivarasi, Anand Kumar

Pages: 376-389

Abstract: Electrochemical sensors have been tested using voltammetry techniques, which is laboratory based. When the sensor design is of IC packed type with NPGF sensing electrode and to be tested in real time scenario, an effective active transduction is required, showing variation in electric currents from inherent ionic currents. MOSFET based NMOS circuitry serves to transduce the signal having variations for solutions containing various heavy metal ions. NMOS based transduction serves with higher signal to noise ratio, minimal power and compact geometry. Surface resistances for NPGF electrode measures 369 and 560 milliohms. While 18 pico amps are measured for 360 milliohms resistance, 14 pico amps are recorded for 560 milliohms. The variation in electric current values are corresponding to ionic current of inherent NPGF sheet resistances.

Title of the Paper: Asymmetry Similarity Coefficient Method for Link Prediction in Homogeneous Graph Data


Authors: Rui Xie, Zhifeng Hao, Bo Liu

Pages: 369-375

Abstract: Predicting missing link in homogeneous networks is of both theoretical interest and practical significance in many different fields. It is found that the similar degree is different between a pair node and the similarity is asymmetry. In this paper, we deliver an efficient framework for link prediction on the basis of node similarity coefficient. A new similarity measure, motivated by the similar coefficient taking place on networks, is proposed and shown to have higher prediction accuracy than previous similarity measures. We therefore design another new measure exploiting information on the common neighbors, which can remarkably enhance the prediction accuracy. Experiments on benchmark and real-world data sets have demonstrated the effectiveness of our proposed approach.

Title of the Paper: Application of Pareto Approach to Improve the State Dependent Ricatti Equation (SDRE) Controller Performance


Authors: Luiz C. G. De Souza, Pierre G. Bigot, Alain G. De Souza

Pages: 359-368

Abstract: The main objective of this work is to study the State Dependent Riccati Equation (SDRE) regulator; an adaptive Linear Quadratic Regulator (LQR) which allows to deal with the non linearities of the system to be controlled. In order to use this controller, a nonlinear mathematical model of a flexible rotatory beam is built through the Lagrangian formulation which can represent a rigid-flexible satellite. The flexible displacement is modelled using the assumed modes theory and a structural damping is added applying the Rayleigh technique. There are two main objectives related to control: the first one is to control the hub angular position and the second one is the need to minimize flexible displacements of the satellite panel. Doing computational simulations, it is possible to draw the performance map of the system which map all SDRE reachable performances. Then, a sorting algorithm enables to get the Pareto’s border which represents the set of optimal performances. On the other hand, analyzing the influence of the weight matrixes terms, it is shown that it is possible to get the Pareto’s border performances using only a few terms of the SDRE weight matrixes. On the basis of this analysis, a law enabling to get weight matrixes’ values in function of a required performance is developed. Last of all, state dependent weight matrixes are used to show that they can improve the system performance. Based on the results, it turned out that the SDRE’s performance is better than the LQR’s one, not only because it can deal with non linearities, but also because its design is more flexible.

Title of the Paper: Deep Position-Sensitive Network for Object Detection


Authors: Feng Xiao, Mengmeng Bai, Li Zhao, Defa Hu

Pages: 353-358

Abstract: Recently the deep network’s ability of learning position-sensitive information is some insufficient in object detection. To improve the ability, we compare the performance of single position-sensitive score maps with various sizes and verify that different sizes sample the different granularities of position-sensitive. Based on the conclusion and the idea of pyramid structure pooling, we propose a deep position-sensitive network that aggregates different divisions of position-sensitive score maps. Our network extracts feature maps using a modified ResNet, and then using two fully convolutional layers to produce the pyramid structure of various sizes score maps. We candidate regions using the region proposal network (RPN), and compute the generated scores of each region of interest (ROI) using different sizes position-sensitive ROI pooling layers. In the end, we apply the softmax layer to generate the probability of every ROI. Our experimental results show that the proposed method can effectively enhance the capacity to learn the object’s position-sensitive information. For the same experimental conditions, we train our network with various sizes assembly on PASCAL 2007+2012 dataset and test on the PSACAL 2007 testset. Most of results is better than the single size that is included in the assembly, but since the granularity of 5×5 and 7×7 size is too close, the performance is similar with single 7×7 szie. The best result is 74.69% mAP with 3×3 and 7×7 size, which is better than the best single position-sensitive network 7×7 size by 2.56%

Title of the Paper: Analysis Modification Synthesis Based Optimized Modulation Spectral Subtraction for Speech Enhancement


Authors: Pavan D. Paikrao, Sanjay L. Nalbalwar

Pages: 343-352

Abstract: Traditional analysis modification synthesis (AMS) is fairly applied for spectral subtraction along with Short Time Fourier Transform. Based on this AMS method, we proposed an approach for modified modulation spectral subtraction. Results reported in previous studies shows that the modulation spectral subtraction performs better for speech courted by additive white Gaussian noise to improve speech quality. It gives improved speech quality scores in stationary noise, but it fails to give improved speech quality in the real time noise environment. Also, the computational cost of existing modulation domain spectral subtraction methods is high. Thus we propose an approach of applying minimum statistics noise estimation technique on the real modulation magnitude spectrum along with optimized noise suppression factor and spectral floor to improve speech quality in the real time noise environment. Finally, the objective, subjective and intelligibility evaluation metrics of speech enhancement indicates that the proposed method achieves better performance than the existing spectral subtraction algorithms across different input SNR and noise type along with improved computational time. Computation time is improved by 57.13% as compared to traditional modulation domain spectral subtraction method. The modulation frame duration of 128 ms is found to be a good compromise between shorter and longer frame duration, which gives improved results.

Title of the Paper: Error Analysis of Sensor Geometric Factor for the Multi-Node Cooperative Localization Accuracy


Authors: Yao Fan

Pages: 338-342

Abstract: The localization accuracy is very important for the multi-node cooperative localization system. In the localization system, the geometrical factor has a great influence on the localization result. In order to solve this problem, the error analysis of the sensor geometry factor for multi-node cooperative localization accuracy is researched in this paper. By using the total differential method to analyze the time difference equation, the intrinsic relations of the localization error, the measurement error of signal arrival time, the localization error of measurement platform and the sensors layout is determined, the localization accuracy distribution of different sensors layout is analyzed through the simulation experiments. Experiments show that the method in this paper provides an important theoretical basis for improving the multi-node cooperative localization accuracy.

Title of the Paper: Hybrid Boundary Value Methods for the Solution of First Order Stiff Systems


Authors: Grace O. Akinlabi, Raphael B. Adeniyi, Enahoro A. Owoloko

Pages: 332-337

Abstract: Recently, several Boundary Value Methods (BVMs) have been developed to overcome the limitations of the popular Linear Multistep Methods (LMMs). In this work, we introduce a new class of BVMs called the Hybrid Boundary Value Methods (HBVMs), which are based on the LMMs by utilizing data at both step and off-step points. Numerical tests on both linear and nonlinear stiff systems were presented so as to illustrate the process by using the specific cases: k = 4 and 6 . The results were of high accuracy as the Rate of Convergence (ROC) of the solutions were compared to a symmetric scheme known as Extended Trapezoidal Rule (ETR) of order 6.

Title of the Paper: Locally Anisotropic Interpolation of Wind Fields


Authors: Nikolay A. Baranov, Ekaterina V. Lemischenko

Pages: 328-331

Abstract: This work is devoted to an approach to solving the task of restoring the wind field structure by the local measurement data in a certain set of points with a low density. The peculiarity of the proposed approach is to take into account the anisotropy of the wind field. In this case, the described algorithm allows us to take into account not only the scale of the anisotropy at different points, but the local variability of the anisotropy directions.

Title of the Paper: Multivalue Approximation of Second Order Differential Problems: a Review


Authors: Angelamaria Cardone, Dajana Conte, Raffaele D’Ambrosio, Beatrice Paternoster

Pages: 319-327

Abstract: We present a collection of recent results on the numerical approximation of second order differential problems of the type y00 = f(y(t)) by means of family of multivalue numerical methods, here denoted as generalized Nystr¨om methods. These methods can be thought as a general family of formulae for the numerical approximation of second order problems, which properly include classical formulae, such as linear multistep methods and Runge-Kutta-Nystr¨om methods, but also enable to find new methods which provide better balances between accuracy and stability demandings. This is made possible because generalized Nystr¨om methods rely on a larger number of degrees of freedom than classical methods, which can be employed for the mentioned purposes. We provide the formulation of the family of methods, showing that existing methods can be regarded according to the new formalism, study the main properties and give examples of highly stable genuine multivalue methods whose order is higher than that of existing methods. In particular, we aim to inherit the best stability properties known in the literature, i.e. those coming from Gauss-Legendre points leading to Pstable methods, by introducing generalized Nystr¨om methods having with the same stability polynomial of Gauss-Legendre methods but higher order of convergence. We show that it is possible to obtain P-stable methods with order 4 relying on one single internal stage (in the classical case, the maximum attainable order is only 2, requiring the same computational cost). A numerical experiment shows the effectiveness of the approach on a periodic stiff problem, also in comparison with existing methods.

Title of the Paper: Detecting Steel Cord Discontinuities in Tire Tread X-Ray Images: A Preliminary Study


Authors: Gabor Leko, Peter Balazs

Pages: 314-318

Abstract: During the manufacturing of tires or due to excessive use, steel-cord belt plies may get damaged, single wires or even entire cords may break. Steel cord discontinuities do not always cause visibly detectable degeneration on the surface of the tire, nevertheless, in these cases non-destructive testing methods can still reveal defects inside the tire. In this paper we propose a simple yet efficient method to detect discontinuities of steel-cord belt plies in the tread area of tires, using automatic analysis of X-ray images.

Title of the Paper: Pattern Recognition in Low-Resolution Instrumental Tactile Imaging


Authors: Stepan A. Nersisyan, Yan I. Rakhmatulin

Pages: 306-313

Abstract: Background. Tactile perception is an essential source of information. However instrumental registration and automated analysis of tactile data is still at an initial point of the development. Recently a Medical Tactile Endosurgical Complex (MTEC) has been introduced into clinical practice as a universal instrument for intrasurgical registration of tactile images. Images registered by MTEC have very limited resolution both in terms of a number of tactile pixels and a number of discretization levels. In this study we investigated whether this resolution is sufficient for reliable pattern recognition. Methods. Our study used a set of artificial samples which included six sample types. In particular, four of these types directly tested the ability to discriminate patterns with the same embedment projection sizes but different curvatures, or similar curvatures but different projection sizes. Two widely used machine learning methods were evaluated: random forests and k-nearest neighbors. These methods were applied to points representing registered tactile images in a relatively low-dimensional feature space. Additionally an in-silico cloning of images was used to increase classification reliability. Results. Both classification methods – random forests and knearest neighbors – showed good classification reliability with accuracy 68.6% and 72.9% on the validation set, respectively. These values are more than four times higher than an accuracy of six-class “random classifier”. Random forests additionally provided evaluation of importance of features used for classification. Conclusion. Despite poor resolution of tactile images registered by MTEC a combination of conventional machine learning methods with a specific feature set and specific tricks provides highly reliable results of automated analysis of these images even in case of nontrivial tasks such as sample classification with very similar classes.

Title of the Paper: Algebraic Representation for Ordinary Place Transition Petri Nets


Authors: A. Spiteri Staines

Pages: 300-305

Abstract: Ordinary place transition Petri nets are useful for modeling discrete systems at a low level. It can be shown that the behavior of these structures does not entirely depend on the static model but also on the resource distribution in the net. In this work the problem of representing Petri nets is presented. Some algebraic notations for modeling at the i) structural and ii) operational level are presented. Some simple examples are used to illustrate the usefulness of these notations and expose hidden concurrency issues in Petri nets. The results are discussed. The ideas presented here are just an outline of what can be done in this area.

Title of the Paper: Binary Image Reconstruction Using Local Binary Pattern Priors


Authors: Judit Szucs, Peter Balazs

Pages: 296-299

Abstract: We provide a novel approach for binary image reconstruction using few projections. The inherently insufficient amount of projection data is augmented by statistical image priors describing the approximate texture of the image to reconstruct. The priors are extracted from sample images, in advance of the reconstruction. Experimental results on software phantom images show that this approach can be a useful alternative of former reconstruction methods as, under certain circumstances, it provides better image quality.

Title of the Paper: Optimality Conditions and Duality Results for a Class of Differentiable Vector Optimization Problems with the Multiple Interval-Valued Objective Function


Authors: Tadeusz Antczak, Anna Michalak

Pages: 284-295

Abstract: In this paper, a differentiable interval-valued vector optimization problem with the multiple objective function and with both inequality and equality constraints is considered. The Karush-Kuhn-Tucker necessary optimality conditions are established for a weak LU-Pareto solution in the considered vector optimization problem with the multiple interval-objective function under the Kuhn-Tucker constraint qualification. Further, the sufficient optimality conditions for a (weak) LU-Pareto solution and several duality results in Mond-Weir sense are proved under assumptions that the functions constituting the considered differentiable vector optimization problem with the multiple interval-objective function are (F,ρ)-convex.

Title of the Paper: One Approach for Circuit Optimization Process


Authors: Alexander M. Zemliak

Pages: 274-283

Abstract: The possibility of applying the maximum principle of Pontryagin to the problem of optimization of electronic circuits is analyzed. It is shown that in spite of the fact that the problem of optimization is formulated as a nonlinear task, and the maximum principle in this case isn't a sufficient condition for obtaining a minimum of the functional, it is possible to obtain the decision in the form of local minima. The analysis of optimization process for some circuits showed that application of the maximum principle really allows finding the optimum structure of the control vector by means of iterative procedure. The theoretical justification is given for the earlier discovered effect of acceleration of the process of circuit optimization in the conditions of a new methodology of design. The relative acceleration of the CPU time for the best strategy found by means of maximum principle compared with the traditional approach is equal two to three orders of magnitude.

Title of the Paper: Long Time Stability of Regularized PML Wave Equations


Authors: Dojin Kim, Yonghyeon Jeon, Philsu Kim

Pages: 269-273

Abstract: In this paper, we consider two dimensional acoustic wave equations in an unbounded domain and introduce a modified model of the classical perfectly matched layer (PML). In the classical PML model, an unexpected and exponential increase in energy is observed in the long-time simulation after the solution reaches a quiescent state. To address such an instability, we provide a regularization technique to a lower order regularity term employed in the auxiliary variable in the classical PML model. The well-posedness of the regularized system is analyzed with the standard Galerkin method based on the energy analysis, and the numerical stability of staggered finite difference method for its discretization is provided by using von Neumann stability analysis. To support the theoretical results, under various thickness and damping values, we demonstrate a long-time stability of acoustic waves in the computational domain.

Title of the Paper: Novel Cascaded H-Bridge Multilevel Inverter with Bi-Directional Switches


Authors: D. Baimel, S. Tapuchi, N. Baimel

Pages: 263-268

Abstract: The paper presents an analysis of a novel cascaded multilevel inverter, which consists of two cascaded bridges per phase. The upper bridge produces 5-level voltage and consists of only two bi-directional and four standard IGBT switches in each 5-level H-bridge. The lower bridge is standard 3-level H-bridge. The inverter is controlled by Phase Disposition (PD), Phase Opposition Disposition (POD) and Alternative Phase Opposition Disposition (APOD) PWM methods. The significant advantages of the proposed inverter are simpler control and lower number of components such as switches, diodes and capacitors than in the standard multilevel topologies. Extensive simulation results validate the practicability of the proposed inverter. The proposed topology can be extended to any desired number of levels by cascading additional bridges.

Title of the Paper: An Iteration Free Backward Semi-Lagrangian Method for Coupled Burgers’ Equations


Authors: Soyoon Bak, Dojin Kim, Philsu Kim

Pages: 259-262

Abstract: In this paper, we develop a backward semi-Lagrangian method for solving the coupled Burgers’ equation. The main difficulty in the backward semi-Lagrangian method for this problem is treating the nonlinearity in the diffusion-reaction type equation, which has a reaction coefficient that is given in terms of coupled partial derivatives. To handle this difficulty, we proposed a new strategy using an extrapolation technique to split the nonlinearity into two diffusion-reaction boundary value problems, which are then solved in turn. In addition, we demonstrated the numerical accuracy and efficiency of the present method by comparing the numerical results with analytical solutions, or other existing numerical solutions that use alternate methods. In addition, we numerically proved that the proposed method exhibits second-order temporal convergence and fourth-order spatial convergence.

Title of the Paper: Seepage Modeling via Hybrid Soft Computing Methods


Authors: Vahid Nourani, Elnaz Sharghi

Pages: 254-258

Abstract: In this paper, several artificial intelligence (AI) models were employed to model seepage through Sattarkhan earth fill dam. For this purpose, measured data of several piezometers of the dam were employed, and then single models for each piezometer was presented based on two scenarios with different inputs. Next, ensemble models were developed to improve predicting performance. Afterwards, the results of the models were compared. The obtained results indicated that model ensemble led to a promising improvement in its performance for seepage modeling. Moreover, by comparison the both scenarios, it is concluded that in case of a failure of a piezometer, other piezometers can be used in modeling.

Title of the Paper: A Comparison of Multi-Step and Multi-stage Methods


Authors: Yonghyeon Jeon, Sunyoung Bu, Soyoon Bak

Pages: 250-253

Abstract: We study a multi-stage method compared with a multi-step method for solving a stiff initial value problem. Due to expensive computational costs of the multi-stage methods for solving a massive linear system induced from the linearization of a highly stiff system, stiff problems are usually solved by the multi-step method, rather than the multi-stage method. In this work, we investigate properties of both the multi-step and the multi-stage methods and discuss the difference between the two methods through numerical tests in several examples. Furthermore, the advantages of multi-stage methods can be heuristically proved even for stiff systems by the comparison of two methods with several numerical tests.

Title of the Paper: Cyclic Spectrum Reconstruction from sub-Nyquist Sampling with Dual Sparse Constraint


Authors: Xushan Chen, Jibin Yang, Xiongwei Zhang, Jianfeng Li

Pages: 244-249

Abstract: For cyclostationary signal processing, cyclic spectrum reconstruction is an important and challenge task for efficient and robust spectrum sensing, since cyclic feature detection takes advantage of spectral correlation characteristics to identify signal parameters and make reliable spectrum access decisions under uncertain noisy environments, but requires high complexity sampling and computational cost especially for wideband spectrum sensing. This paper proposes a novel cyclic spectrum reconstruction approach by exploiting the intrinsic sparsity and the differential spectral domain sparsity of the two dimensional cyclic spectrum of communication signals. Based on the linear relationship between the time-varying data covariance of the compressive samples and the unknown cyclic spectrum, the proposed estimator utilizes the symmetry property of the cyclic spectrum to improve the smoothness of the recovered cyclic spectrum and then to detect the spectrum occupancy accurately and robustly. Simulation results demonstrate the effectiveness of the developed estimator under different compression ratio cases.

Title of the Paper: A High Precision Time-Frequency Analysis Applying to Linearity Detection


Authors: Wenxin Zhang, Xiaojun Liu, Xiuwei Chen, Qing Liu, Guangyou Fang, Shinan Lang

Pages: 236-243

Abstract: This article presents a method to achieve a high precision time-frequency analysis and detect the linearity of linear frequency modulation continuous wave (LFMCW) radar system. At first, discrete time domain window is used to make the target signal to be discrete short-time pieces. The fractional Fourier transform (FRFT) is used to calculate the frequency modulation (FM) rates of every subsection. Let the short-time signal mix with a ideal linear frequency modulation (LFM) signal, the intermediate frequency (IF) signal can be obtained. The Wigner-Ville Distribution (WVD) transform can be used to estimate the time-frequency function of the IF signal. The time-frequency function of short-time signal can be calculated from the relation between the IF signal and the ideal LFM signal. This method can achieve a high precision time-frequency analysis. The simulation can show a significant resolution performance improvement over the conventional method. At last, a practical engineering application measurement is presented.

Title of the Paper: Pachycondyla APIcalis Ants (API) Algorithm for Multi-User Detection of SDMA-OFDM System


Authors: Saliha Azzeddinne, Mahdjoub Zoubir

Pages: 230-235

Abstract: Space Division Multiple Access (SDMA) based technique as a subclass of Multiple Input Multiple Output (MIMO) systems achieves high spectral efficiency through bandwidth reuse by multiple users. On the other hand, Orthogonal Frequency Division Multiplexing (OFDM) mitigates the impairments of the propagation channel. The combination of these tools has emerged as a most competitive technology for future wireless communication system. Different Multiuser Detection (MUD) schemes have been proposed at the BS receiver to identify users correctly by mitigating the multiuser interference. However, most of the classical MUDs fail to separate the users signals in the over load scenario, where the number of users exceed the number of receiving antennas. In this work, MUD tool based on the Pachycondyla APIcalis ants (API) algorithm is proposed in the multiuser MIMO-OFDM system and its performance is compared to existing MUDs such as MMSE(Minimum mean square) and ML algorithm.The simulation results show that the API-MUD algorithm can achieve higher performance.

Title of the Paper: Impulsive Noise Cancellation from Cardiac Signal Using Modified WLMS Alogorithm Based Adaptive Filter


Authors: Sarthak Panda, Mihir Narayan Mohanty

Pages: 223-229

Abstract: For clean signal, noise cancellation techniques are explored day-by-day. At the user end the clean signal is highly essential for different purposes. In this authors have considered the bio-medical signal that is corrupted with impulsive noise. It is very important to separate from the signal, as its occurrence is sudden and often similar to the signal. The popular adaptive algorithms have been tested for cancellation of impulsive noise. Further most used Wilcoxon LMS is also verified for impulsive noise case. Finally it has been modified for the same purpose. The result found excellent in terms of less MSE, SNR improvement and faster convergence.

Title of the Paper: Smooth Blind Extraction Method for Harmonic Signals Hidden in Chaos Energy Accumulation Zone


Authors: Xiaozhen Liu, Yuanshuo Zheng, Xinwu Chen, Erfu Wang, Qun Ding

Pages: 216-222

Abstract: Put forward a method for blind separation mixed signals hidden in chaotic energy accumulation zone. Take different chaotic systems’ wavelet time-frequency analysis for reference to determine amplitude and frequency of harmonic signal. Then use JADE algorithm for adding noise mixed-signal blind separation realizing the hidden harmonic signal blind extraction. Finally the simulation realizes doing smooth processing to extracted harmonic signal which restores harmonic signals in frequency domain and time domain, verifying The validity and the applicability of the method.

Title of the Paper: Modeling and Sliding Mode Control of a DFIG Fueled by a Three-Level PWM Cascade Application to Wind Energy


Authors: Naim Cherfia, Djallel Kerdoun

Pages: 210-215

Abstract: In this paper, we study the control of active and reactive power for a doubly fed induction generator (DFIG) using sliding mode control (SMC) method feeding by inverter a three –level structure NPC for variable speed wind energy. We first present the dynamic model of DFIG connected by wind turbine and grid system, then we modeling and control strategy of inverter three-level structure NPC. Finally, we will prove that the inverter three-level PWM which allows the minimizing of harmonics stator current and wide linear modulation range and ameliorate the quality of energy injected into the electricity grid.

Title of the Paper: A Variable Step Size Improved Multiband-Structured Subband Adaptive Filter Algorithm with Subband Input Selection


Authors: Chang Liu, Zhi Zhang

Pages: 202-209

Abstract: Subband adaptive filter algorithms are able to improve the convergence behavior by performing the pre-whitening procedure on the input signals. In this paper, we propose a new variable step size improved multiband-structured subband adaptive filter algorithm which dynamically selects subband filters (VSS-DS-IMASF) in order to reduce the computational complexity. The subbband selection scheme which is designed to select the meaningful subbands is based on comparing the steady state subband mean square error (SMSE) with the subband error power throughout the algorithm execution, checking whether the subband filters converge to the steady state. In addition, the step size is controlled by the estimated mean square deviation (MSD) in order to achieve better steady state performance. Simulation results show that the proposed algorithm has lower steady state MSD and less computational complexities compared with the existing subband algorithms.

Title of the Paper: Design of Linear Functional Observers with H1 Performance


Authors: D. Krokavec, A. Filasova

Pages: 192-201

Abstract: The paper solves the problem of parameter designing for one class of linear functional observers. To solve this problem, a simple design procedure for providing the generalized structure framework based on H1 norm principle is presented. Related to estimation of given function of system state, the design steps is given out in the example to illustrate the properties of the functional observer.

Title of the Paper: Edge Selection and Sparse Representation Based Motion Deblurring Method


Authors: Xixuan Zhao, Jiangming Kan

Pages: 184-191

Abstract: Motion deblurring has long been a challenging yet fundamental problem in image processing. In this paper, we address the problem of blind motion deblurring by incorporating global priori information, kernel priori information and sparse representation in a unified framework. Then, we alternately solve the estimated kernel and the deblurred image. To obtain a more accurate blurring kernel, we propose an edge selection step to select useful edges for kernel estimation and introduce an intermediate image to improve the accuracy of kernel estimation. Experimental results show that the proposed method runs fast and achieves comparable results to those of the state-of-the-art algorithms. Sometimes, this proposed method outperforms these other algorithms in both synthetic and real-world image experiments.

Title of the Paper: Analysis of Developers Choices for API Rest or Soap Protocols


Authors: Alen Šimec, Lidija Tepeš Golubić

Pages: 178-183

Abstract: This paper is about analysis and comparison of SOAP protocol and REST architecture, their possibilities and use in everyday scenarios. The structure, way of work and area of application, as well as the most famous cases of application of one or the other approach have been described in short.

Title of the Paper: Video Summarization in Social Media Based on Users’ Geo-Location


Authors: Klimis Ntalianis, Nikos Mastorakis

Pages: 171-177

Abstract: Tons of information is posted everyday on social networks. This information should be summarized in order to be accessible by users. In this paper a novel scheme is proposed for summarizing video content posted on social networks. Towards this direction a probabilistic framework for estimating the location of each post is designed, based on the associated textual content of the post. Furthermore a CLARANS-based key-frames extraction scheme is considered. Then each user is presented with a location-aware summary. The nearest a video is to the location of a user, the more key-frames are extracted. This paper forms an initial study of location-based summarization of video content posted on social networks and experiments on real world data indicate its promising performance.

Title of the Paper: Flow Apportionment in a Manifold by Using Genetic Algorithm and Least Squares Regression


Authors: Thulasiram A. R., Bura Sreenivas, Sreenivas Jayanti

Pages: 162-170

Abstract: Flow apportionment of a 8-parameter flow manifold is dealt in this paper. We deal with a one-by-four manifold. We have to optimally locate the guide plates. The objective of the work is to minimize the standard deviation of the actual flow rates from the set points by controlling 8 parameters four of which are lengths and four of which are angles of deflection. We take the input as the 50 data points generated by the process of CFD. Using the combination of ordinary least squares and genetic algorithms we develop the minimization algorithm for the objective function. We have successfully evaluated the objective and 8 parameters and found that the algorithm employed in this work yields a solution that is lower than the lowest of the 50 data points. Therefore we concluded that our method works successfully without having the need to resort further to CFD computations.

Title of the Paper: Modeling of Input Capacitance of IGBTs Under Dynamic Conditions


Authors: Ji Tan, Yangjun Zhu, Shuojin Lu, Qiaoqun Yu

Pages: 157-161

Abstract: Insulated gate bipolar transistor (IGBT) input capacitance has significant influence on device dynamic behaviors, and consists of two nonlinear components: the gate capacitance and the miller capacitance. Although these two components are capacitance with MOS structure, they behave differently with the isolated MOS capacitance. The reasons leading to this are the influences of the nearby semiconductor layers and the collector current dependency. An analytical model of the input capacitance for the dynamic cases has been derived, and the collector current dependency is quantified. The predictions of the model are in good agreement with the results obtained from numerical simulation of IGBT transient.

Title of the Paper: Electrohydraulic Actuators Affected by Multiple Failures: Proposal of an Alternative Model-Based Prognostic Paradigm


Authors: M. D. L. Dalla Vedova, P. Maggiore, F. Marino

Pages: 148-156

Abstract: Onboard electrohydraulic actuator (EHA) applied to primary and secondary flight command, and in particular the servovalves (SVs) regulating their hydraulic power, are complex devices and can fail in several ways: servovalves are critical components of the hydraulic servos and their correct operation is mandatory to ensure the proper functioning of the controlled servosystem. For this reason, a continuous monitor is typically performed to detect a servovalve loss of operation, but this monitor falls short of recognizing other malfunctionings. Often, a progressive degradation of a servovalve occurs, which does not initially create an unacceptable behavior, but eventually leads to a condition in which the servovalve, and hence the whole servoactuator operation, is impaired. Developing a prognostic algorithm able to identify the precursors of a servovalve failure and its degradation pattern is thus beneficial for anticipating the incoming failure and alerting the maintenance crew such to properly schedule the servovalve replacement. This avoids a servovalve failure in service, thereby ensuring improved equipment availability and minimizing the impacts onto the logistic line. To this purpose, authors propose a new model-based fault detection and identification (FDI) technique able to perform an early detection of two of the most common types of SV progressive failures (dry friction acting on servovalve spool and contamination of the first stage filter). The robustness of the proposed technique has been assessed through a simulation test environment, built on the purpose. Such simulation has demonstrated that the methodology has adequate robustness; also, the ability to early identify an eventual malfunctioning has been proved with low risk of missed failures or false positives.

Title of the Paper: Computational Fluid Dynamics-Based Simulation to Francis Turbine Under a Runaway Condition


Authors: Liying Wang, Bingyao Li, Weiguo Zhao, Qingjiao Cao

Pages: 142-147

Abstract: When the turbine operates in a runaway condition, the rotating speed of the runner increases sharply which results in serious threat to the safe of the units. In view of the instability phenomenon, a Francis turbine is simulated through Computational Fluid Dynamics (CFD). According to the internal control equation, the stable calculation results under the rated operation are used as the initial condition in the simulation, when the runner torque reaches a certain minimum value, the runaway condition is coming. Through analyzing the distribution of streamline under different speeds with different openings and the pressure distribution in the blade pressure surface and suction surface, it can be concluded that there exists a serious collision and off-flow phenomenon when the water flows into the runner. Meanwhile, through analyzing the streamline of draft tube in the meridian surface, it can be seen that the water flow with high rotating speed impacts on the draft tube wall, which causes the rising of pressure in the wall. With the increase of the opening, the vortex in the straight cone section is gradually reduced, additionally, the retention and secondary reflux in the diffusion section are significantly improved.

Title of the Paper: Grayscale and Binary Enhancement of Dorsal Hand Vein Images


Authors: Marlina Yakno, Junita Mohamad-Saleh, Bakhtiar Affendi Rosdi

Pages: 129-141

Abstract: Difficulty in achieving a peripheral intravenous (IV) access in pediatric and some adult patients is a clinical problem. These difficulties may lead to some negative impacts such as fainting, hematoma and pain associated with multiples punctures. The use of near-infrared imaging device to aid visualization of an IV access usually suffers from low contrast and noise due to non-illumination and thickness of hand skin. This further complicates subsequent processing such as image segmentation. In this work, two methods are proposed in two different stages; grayscale enhancement and binary enhancement for correction of low contrast and noisy images. For grayscale enhancement, a combination of histogram-based and fuzzy-based contrast enhancement algorithms are applied on hand vein images. For binary enhancement, a combination of three techniques; Artificial Neural Network pixel corrector, Binary Median Filter and Massive Noise Removal, are applied on the binary hand vein images. Comparative analysis on test images using the proposed different contrast enhancement methods has shown superior results in comparison to its counterparts.

Title of the Paper: Single-Image Super Resolution Based on Group Sparse Representation via GAUSSIAN


Authors: Shuhua Xu, Fei Gao

Pages: 118-128

Abstract: As recently newly techniques, Group based Sparse Representation (GSR) algorithms were proposed, which achieved an excellent performance of sparse representation, exploiting the concept of group as the basic unit of sparse representation which is composed of nonlocal image patches with similar structures and capturing intrinsic local sparsity and nonlocal self-similarity of images simultaneously in one unified framework. Inspired by this, we apply GSR to single image super resolution reconstruction. However, the Euclidean distance metric applied in the process of group construction in traditional GSR failed to capture nonlinear structural information between image patches, leading to that the performances of these algorithms were sensitive to the geometric structure of images. In order to solve the problem, on basic of existing GSR, the nonlinear nonlocal self-similarity and local information of image patches were captured by exploiting effectively Gaussian kernel distance metric instead of the Euclidean distance metric in the paper. The paper presents Single-image Super Resolution based on Group Sparse Representation via GAUSSIAN (GSRGSiSR) algorithm. Compared with many state-of-art SISR methods, extensive experimental results validate that the proposed method can obtain better peak signal-to-noise ratio (PSNR) and structural similarity (SSIM).

Title of the Paper: Depth Stabilization of Biomimetic Underwater Vehicle Without Swim Bladder


Authors: Piotr Szymak, Tomasz Praczyk

Pages: 112-117

Abstract: In recent times, we may notice some new designs of underwater vehicles, which imitate living underwater organisms, e.g. a fish. These vehicles are called biomimetic. They are driven by undulating propulsion, imitating wavy motion of fins and they can submerge using ballast tank called an artificial swim bladder. In the paper, problem of depth stabilization of biomimetic underwater vehicle (BUV) which was not equipped with a swim bladder is undertaken. At the beginning of the paper, introduction to the research area of biomimetic underwater vehicles is inserted. Then, the mathematical model of BUV with the new undulating propulsion is presented. Next, the controllers for depth stabilization used in the numerical research are described. The BUV model and depth controllers were implemented in Matlab environment for making numerical tests. At the end of the paper, the selected results of the numerical research are presented and then, the conclusions are formulated.

Title of the Paper: Camera Calibration Approach Based on Iteration


Authors: Min Han, Jiangming Kan, Yutan Wang

Pages: 106-111

Abstract: Tsai’s camera calibration method is widely used, but the accuracy of calibration must be improved. To further improve the calibration accuracy, this paper first introduces Tsai’s calibration principles and analyzes the factors that affect the accuracy of Tsai’s calibration method. Then, an improved method of camera calibration based on iteration is proposed. The method solves the problem of approximating the principal point to the image center in Tsai’s method, and then the objective function and the initial value of search are designed considering the speed of the optimizing search and calculated amount. Finally, the experimental results show that the accuracy of the calibration method is significantly improved compared with Tsai’s.

Title of the Paper: Construction and Chaos Properties Analysis of a Quadratic Polynomial Surjective Map


Authors: Jun Tang, Jianghong Shi, Zhenmiao Deng

Pages: 100-105

Abstract: In this paper, a kind of quadratic polynomial surjective map (QPSM) is constructed, and the topological conjugation of the QPSM and tent map is proven. With the probability density function (PDF) of the QPSM being deduced, an anti-trigonometric transform function is proposed to homogenize the QPSM. The information entropy, Kolmogorov entropy (KE), and discrete entropy (DE) of the QPSM are calculated for both the original and homogenized maps with respect to different parameters. Simulation results show that the information entropy of the homogenized sequence is close to the theoretical limit and the discrete entropy remains unchanged, which suggest that the homogenization method is effective. Thus, the homogenized map not only inherits the diverse properties of the original QPSM but also possesses better uniformity. These features make it more suitable to secure communication and noise radar.

Title of the Paper: G3-PLC Physical Layer Signal Processing Based on Mixed Window Function


Authors: Feng Zhang, Shangjun Yang, Li Zhao, Feng Xiao

Pages: 94-99

Abstract: In the signal processing of G3-PLC physical layer, ROBO mechanism is often used to ensure reliability in strong noise interference. But for non-Gauss channels, ROBO processing has the limited ability to improve communication reliability. Aiming at the existing problem of ROBO, analyzing the noise spectrum in the power line, FIR digital filter is introduced into the physical layer of G3-PLC in this paper. FIR band-pass digital filter is used to remove the out of band noise, enhancing the effect of ROBO processing, thereby improving communication reliability. Through the analysis of the main lobe width and the stop band attenuation, the mixed window function with reasonable parameters is used in the design of the filter to improve the denoising performance of the filter. The reliability and efficiency of the algorithm are simulated by measurement power line noise. The results show that the FIR filtering algorithm based on mixed window function has the coding gain of 1 to 2dB.Combined with ROBO processing, the algorithm has a coding gain of about 7dB to 8dB.The FIR filtering of signal in physical layer based on mixed window function is an effective way to improve the reliability of G3-PLC communication under strong noise interference in practical applications.

Title of the Paper: Adaptive Waveform Selection Based on Relative Value Iteration


Authors: Bin Wang

Pages: 88-93

Abstract: Traditional radar lacks flexibility, and modern science and technology promote the progress of radar technology. Modern intelligent radar should transmit different waveforms in different working conditions. In this paper, we set up radar detection model based on range-Doppler resolution cell and make analysis of matched filtering. We introduce reward theory and establish stochastic dynamic programming model of waveform selection. In order to overcome the shortcoming of backward recursion method, we propose a relative value iteration method. In simulation part, we compare fixed waveform, relative value iteration method and the optimal waveform selection scheme. Simulation results show that the method we proposed has lower tracking errors. Meanwhile, relative value iteration method approaches the optimal waveform selection scheme. Finally, a summary of the full paper is presented.

Title of the Paper: Parallel Swarm Intelligence Algorithm for Grid Scheduling Based on Multiple Objectives Optimization


Authors: Xiaohong Kong, Hao Guo, Wenqiang Yang, Baochun Wang

Pages: 81-87

Abstract: Grid aggregates enormous resources spanning different geographic organizations and shares them together to provide powerful computation ability and tremendous memory with low cost. Grid is a potential trend for large-scale computation and complex engineering problems. But grid resources allocation and tasks scheduling are huge challenges due to its dynamic characteristic and heterogeneous architecture. This paper proposes a parallel ant colony algorithm and ant colony is divided into subgroups. Each subgroup searches solution space respectively to enhance the global ability of algorithm. Further, subgroups interchange the information periodically to speed the algorithm convergence and avoid local optimum based on message sharing. Dynamical heuristics information and adaptive pheromone updating are implemented to optimize multi-objectives for grid scheduling. The algorithm is simulated in master-slave system with distributed memory architecture and Gridsim environment. The experiment results are compared with different algorithms and prove that the proposed algorithm can improve the solution quality as well as load balance.

Title of the Paper: Simulation of Negative Influences on the CWDM Signal Transmission in the Optical Transmission Media


Authors: Rastislav Róka, Martin Mokráň, Pavol Šalík

Pages: 75-80

Abstract: This lecture is devoted to the simulation of negative influences in the environment of optical transmission media. An attention is focused on main features and characteristics of environmental influences at the CWDM signal transmission. Shortly, basic principles of the wavelength division multiplexing systems are presented utilizing especially the Coarse WDM technique. Consequently, a simulation model for the appropriate CWDM optical transmission path is introduced with short descriptions of functional blocks representing technologies utilized in this specific environment. The created Simulink modeling scheme of real environmental conditions at the signal transmission using the Coarse Wavelength Division Multiplexing (CWDM) allows executing different requested analyses for advanced optical signal processing techniques. Finally, some results from the CWDM simulation are introduced for the signal transmission influenced by different negative effects in the optical transmission medium. Using the presented simulation model, it is possible analyzing transmitted optical signals with eye diagrams and determined the impact of negative influences on the optical frequency spectrum.

Title of the Paper: Latency Optimized Asynchronous Early Output Ripple Carry Adder based on Delay-Insensitive Dual-Rail Data Encoding


Authors: P. Balasubramanian, K. Prasad

Pages: 65-74

Abstract: Asynchronous circuits employing delay-insensitive codes for data representation i.e. encoding and following a 4-phase return-to-zero protocol for handshaking are generally robust. Depending upon whether a single delay-insensitive code or multiple delay-insensitive code(s) are used for data encoding, the encoding scheme is called homogeneous or heterogeneous delay-insensitive data encoding. This article proposes a new latency optimized early output asynchronous ripple carry adder (RCA) that utilizes single-bit asynchronous full adders (SAFAs) and dual-bit asynchronous full adders (DAFAs) which incorporate redundant logic and are based on the delay-insensitive dual-rail code i.e. homogeneous data encoding, and follow a 4-phase return-to-zero handshaking. Amongst various RCA, carry lookahead adder (CLA), and carry select adder (CSLA) designs, which are based on homogeneous or heterogeneous delayinsensitive data encodings which correspond to the weak-indication or the early output timing model, the proposed early output asynchronous RCA that incorporates SAFAs and DAFAs with redundant logic is found to result in reduced latency for a dualoperand addition operation. In particular, for a 32-bit asynchronous RCA, utilizing 15 stages of DAFAs and 2 stages of SAFAs leads to reduced latency. The theoretical worst-case latencies of the different asynchronous adders were calculated by taking into account the typical gate delays of a 32/28nm CMOS digital cell library, and a comparison is made with their practical worst-case latencies estimated. The theoretical and practical worst-case latencies show a close correlation. The proposed early output 32-bit asynchronous RCA, which contains 2 stages of SAFAs in the least significant positions and 15 stages of DAFAs in the more significant positions, reports the following optimizations in latency over its architectural counterparts for a similar adder size: i) 35.3% reduction in latency over a weakindication section-carry based CLA (SCBCLA), ii) 30.5% reduction in latency over a weak-indication hybrid SCBCLA-RCA, iii) 20.2% reduction in latency over an early output recursive CLA (RCLA), iv) 18.7% reduction in latency over an early output hybrid RCLA-RCA, and v) a 13% reduction in latency over an early output CSLA that features an optimum 8-8-8-8 uniform input partition.

Title of the Paper: Design and Implementation of the DAB/DMB Transmitter Identification Information Decoder


Authors: Hongsheng Zhang, Hongyun Wang, Guoyu Wang, Mingying Lu

Pages: 59-64

Abstract: The Transmitter Identification Information (TII) provides unambiguous identification of each transmitter in a Digital Audio Broadcast (DAB) and Digital Multimedia Broadcast (DMB) network. Recent researches showed that some useful services, such as location and automatic emergency alert, can be efficiently implemented with the assistance of TII. However many DAB/DMB receivers do not have the TII decoding functionality because the implementation of TII is optional in the standard. This has blocked the application of the new services. In this paper, the TII coding theory is analyzed and the design method of the TII decoder is reported. The proposed method can be either implemented in software, enabling the software-based DAB/DMB receivers to add TII decoding ability simply though firmware updating, or embedded in the hardware of a DAB/DMB baseband chip at a very low cost of only 286 logic elements and 1280 memory bits.

Title of the Paper: Forest Target Classification Research Based on Multi-Class Gauss Kernel Fuzzy Support Vector Machine


Authors: Zhihui Dai, Qingqing Huang, Wenbin Li, Chaoyi Zhang

Pages: 52-58

Abstract: For the measurement system of artificial forest environment, it was necessary to import pattern recognition method to identify and classify the different targets such as living trees and obstacles in forest environment. The features selection directly affected the classifier performance. This paper content based on independent objects’ fusion point cloud data, extracted the target feature with clear distinction function, proposed a forest target classification method which based on multi-class Gauss particle size fuzzy support vector machine, the main contents were as follows: the forest environment independent objects semantic classification was unknown, the image data after segmentation and 3D laser point cloud data extraction, were used to extract the artificial forest target and obstacles color, shape, reflection strength and characteristics of three-dimension space. The import of Gauss particle size enhanced the fuzzy support vector machine which based on linear support vector machine classifier, and put forward the rise of membership function distribution based on semi convex, the decision directed acyclic graph was extended to multi-class classification. Through a large number of samples in training and learning under plantation environment, it proved that this method can effectively identify the plantation environment under the trees, fire, pedestrian these three target. Through the model parameter optimization, comprehensive average correct recognition rate can reach 96%, this result can provide accurate recognition for forest firefighter.

Title of the Paper: Techniques to Improve the Denoising for Wind Profiler Time Series Data


Authors: P. Krishna Murthy, S. Narayana Reddy

Pages: 44-51

Abstract: The lower atmospheric signals, which are processed in the present work has been obtained from the LAWP radar at the National Atmospheric Research Laboratory (NARL), Gadanki, India. The Radar wind profiler is most suitable remote sensing tool for measuring the height profile of wind vector with high resolutions in both time and space in all weather conditions. The term wind profiling radar is often used to emphasize the operational applications of the clear air radar technique and operating at lower and middle UHF bands. These radars can measure the wind profiles in the first few kilometers of the atmosphere. They include boundary layer convergence processes and their relationship to atmospheric convection, mountain drainage flows and urban pollution studies. This paper discusses denoising the wind profiler data using Empirical Mode Decomposition (EMD), Peak Detection Technique (PDT) and Daubechies wavelets. Effective Doppler shift for LAWP data is obtained by using Db11 wavelet and compared with the different signal processing techniques. The Result shows that there is an effective doppler shift after using Db11 wavelet for LAWP signals.

Title of the Paper: Optimization of Wireless Networks Performance: an Approach Based on a Partial Penalty Method


Authors: I. V. Konnov, O. A. Kashina, E. Laitinen

Pages: 37-43

Abstract: We study an optimization problem for a wireless telecommunication network stated as a generalized transportation problem (TP), where (the number of “sellers” ) is the number of network providers, and (the number of “buyers”) is the number of connections established at a given time moment. Since in practice initial data of such problems are, generally speaking, inexact and/or vary rather quickly, it is more important to obtain an approximate solution of the problem (with a prescribed accuracy) within a reasonable time interval rather than to solve it precisely (but in a longer time). We propose to solve this problem by a technique that explores the idea of penalty functions, namely, the so-called Partial Penalty Method (PPM, for short). As distinct from exact solution methods for TP (e.g., the method of potentials), our approach allows us to further extend the class of considered problems by including to it TP with nonlinear objective functions. As an example, we consider a TP, where the objective function (expenses connected with resource allocation) is such that the price of the unit amount of the resource is not constant but depends on the total purchase size. In addition, we study the limit behavior of solutions to TP whose data are subject to fading disturbances. Since in our approach the initial point is not necessarily admissible, we use an approximate solution of each problem as the initial point for the next one. As expected, under certain requirements to disturbances the sequence of solutions to “disturbed” problems tends to a solution of the limit problem. We prove experimentally that PPM is more efficient than the usual variant of the Penalty Function Method (the Full Penalty Method, or FPM). The preference of PPM over FPM is more evident for n much greater than m.

Title of the Paper: An Innovative Nature-Inspired Heuristic Combined with Response Surface Methodology to find the Optimal Region in Discrete Event Simulation Models


Authors: Cassettari Lucia, Mosca Marco, Mosca Roberto, Giribone Pier Giuseppe

Pages: 27-36

Abstract: The search for a stationary point in the study of Discrete Event Simulation models is a complex problem. This is because the equation of the objective function is never known a priori to the experimenter. In the case of restricted investigation domains the Response Surface Methodology typically provides, through the use of Central Composite Design, the experimental design most suitable for the construction of first and second order regression meta-models. The problem becomes more complex when the domain to be investigated is larger because, in that case, it becomes impossible to identify a meta-model regression able to describe the behaviour of the objective function on the entire domain. Such a limitation can be overcome by an appropriate use of research techniques such as gradiental or direct search methods. However, the presence in the domain of local stationary points may affect their effectiveness and forces the experimenter to track the investigation starting from several points of the domain, with a consequent increase in the number of function evaluations and computational time. In more recent times global research techniques have been developed, often inspired by natural processes. However they generally not perform well applied to Discrete Event Simulation models. For this reason the Authors have developed a new search algorithm called Attraction Force Optimization (AFO). The proposed approach applied to industrial problems up to 10-dimensional, offers significant advantages in terms of both exploration capacity and convergence speed. An application of the proposed technique to a real industrial case completes the discussion.

Title of the Paper: Improved Whale Optimization Algorithms Based on Inertia Weights and theirs Applications


Authors: Hongping Hu, Yanping Bai, Ting Xu

Pages: 12-26

Abstract: Whale optimization algorithm (WOA), which mimics the social behavior of humpback whales, was proposed by Seyedali Mirjalili and Andrew Lewis in 2016.This paper introduces the inertia weights to WOA to obtain the improved whale optimization algorithms(IWOAs). IWOAs are tested with 27 mathematical benchmark functions and are applied to predict daily air quality index(AQI) of Taiyuan.The results show that IWOAs with inertia weights are superior to WOA,FOA,ABC,and PSO on the minimum of benchmark functions and are very competitive for prediction compared with WOA and PSO.

Title of the Paper: Extended Critical Directions for Time-Control Constrained Problems


Authors: Karla L. Cortez del Rio, Javier F. Rosenblueth

Pages: 1-11

Abstract: We derive in this paper second order necessary conditions for certain classes of optimal control problems involving inequality and equality constraints in the time variable and the control functions. We study different normality conditions found in the literature which can be imposed on solutions to the problem and provide a new approach, partly based on the theory for constrained problems in finite dimensional spaces, which under mild assumptions allows us to enlarge the usual set of critical directions.