Search results for: Von Neumann entropy.

Authors: S. Nandagopalan, Dr. B. S. Adiga, N. Deepak

Abstract:

In this paper a novel approach for generalized image retrieval based on semantic contents is presented. A combination of three feature extraction methods namely color, texture, and edge histogram descriptor. There is a provision to add new features in future for better retrieval efficiency. Any combination of these methods, which is more appropriate for the application, can be used for retrieval. This is provided through User Interface (UI) in the form of relevance feedback. The image properties analyzed in this work are by using computer vision and image processing algorithms. For color the histogram of images are computed, for texture cooccurrence matrix based entropy, energy, etc, are calculated and for edge density it is Edge Histogram Descriptor (EHD) that is found. For retrieval of images, a novel idea is developed based on greedy strategy to reduce the computational complexity. The entire system was developed using AForge.Imaging (an open source product), MATLAB .NET Builder, C#, and Oracle 10g. The system was tested with Coral Image database containing 1000 natural images and achieved better results.

Keywords: Content Based Image Retrieval (CBIR), Cooccurrencematrix, Feature vector, Edge Histogram Descriptor(EHD), Greedy strategy.

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Authors: Guoliang Fan, Aiping Li, Nan Xie, Liyun Xu, Xuemei Liu

Abstract:

Mass customization production increases the difficulty of the production line layout planning. The material distribution process for variety of parts is very complex, which greatly increases the cost of material handling and logistics. In response to this problem, this paper presents an approach of production line layout planning based on complexity measurement. Firstly, by analyzing the influencing factors of equipment layout, the complexity model of production line is established by using information entropy theory. Then, the cost of the part logistics is derived considering different variety of parts. Furthermore, the function of optimization including two objectives of the lowest cost, and the least configuration complexity is built. Finally, the validity of the function is verified in a case study. The results show that the proposed approach may find the layout scheme with the lowest logistics cost and the least complexity. Optimized production line layout planning can effectively improve production efficiency and equipment utilization with lowest cost and complexity.

Keywords: Production line, layout planning, complexity measurement, optimization, mass customization.

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Authors: C. Ardil

Abstract:

The paper presents a multiple criteria decision making analysis process to determine the most suitable regional aircraft type according to a set of evaluation criteria. The main purpose of this study is to use different decision making methods to determine the most suitable regional aircraft for aviation operators. In this context, the nine regional aircraft types were analyzed using multiple criteria decision making analysis methods. Preference analysis for reference ideal solution (PARIS) was used in regional aircraft selection process. The findings of the proposed model show that the ranking results of the multiple criteria decision making models are consistent with each other, and the proposed method is efficient, and the results are valid. Finally, the Embraer E195-E2 model regional aircraft is chosen as the most suitable aircraft type.

Keywords: aircraft, regional aircraft selection, multiple criteria decision making, multiple criteria decision making analysis, mean weight, entropy weight, MCDMA, PARIS

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Authors: Harpreet Kaur, Sudipta Majumdar

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In this paper a method for image dehazing is proposed in lifting wavelet transform domain. Lifting Daubechies (D4) wavelet has been used to obtain the approximate image and detail images.  As the haze is contained in low frequency part, only the approximate image is used for further processing. This region is processed by dehazing algorithm based on dark channel prior (DCP). The dehazed approximate image is then recombined with the detail images using inverse lifting wavelet transform. Implementation of lifting wavelet transform has the advantage of auxiliary memory saving, fast implementation and simplicity. Also, the proposed method deals with near white scene problem, blue horizon issue and localized light sources in a way to enhance image quality and makes the algorithm robust. Simulation results present improvement in terms of visual quality, parameters such as root mean square (RMS) contrast, structural similarity index (SSIM), entropy and execution time.

Keywords: Dark channel prior, image dehazing, lifting wavelet transform.

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Authors: Bing-Wen Chen, Alvin W. Y. Su, Yu-Lin Wang

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Electromyography (EMG) is one of the important indicators during exercise, as it is closely related to the level of muscle activations. This work quantifies the muscle conditions of the lower limbs in a constant workload exercise. Surface EMG signals of the vastus laterals (VL), vastus medialis (VM), rectus femoris (RF), gastrocnemius medianus (GM), gastrocnemius lateral (GL) and Soleus (SOL) were recorded from fourteen healthy males. The EMG signals were segmented in two phases: activation segment (AS) and relaxation segment (RS). Period entropy (PE), peak count (PC), zero crossing (ZC), wave length (WL), mean power frequency (MPF), median frequency (MDF) and root mean square (RMS) are calculated to provide the quantitative information of the measured EMG segments. The outcomes reveal that the PE, PC, ZC and RMS have significantly changed (p<.001); WL presents moderately changed (p<.01); MPF and MDF show no changed (p>.05) during exercise. The results also suggest that the RS is also preferred for performance evaluation, while the results of the extracted features in AS are usually affected directly by the amplitudes. It is further found that the VL exhibits the most significant changes within six muscles during pedaling exercise. The proposed work could be applied to quantify the stamina analysis and to predict the instant muscle status in athletes.

Keywords: EMG, feature extraction, muscle status, pedaling exercise, relaxation segment.

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Authors: Yue-Tzu Yang, Hsiang-Wen Tang, Jian-Zhang Yin, Chao-Han Wu

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Three-dimensional incompressible turbulent fluid flow and heat transfer of pin fin heat sinks using air as a cooling fluid are numerically studied in this study. Two different kinds of pin fins are compared in the thermal performance, including circular and square cross sections, both are in-line and staggered arrangements. The turbulent governing equations are solved using a control-volume- based finite-difference method. Subsequently, numerical computations are performed with the realizable k - ԑ turbulence for the parameters studied, the fin height H, fin diameter D, and Reynolds number (Re) in the range of 7 ≤ H ≤ 10, 0.75 ≤ D ≤ 2, 2000 ≤ Re ≤ 126000 respectively. The numerical results are validated with available experimental data in the literature and good agreement has been found. It indicates that circular pin fins are streamlined in comparing with the square pin fins, the pressure drop is small than that of square pin fins, and heat transfer is not as good as the square pin fins. The thermal performance of the staggered pin fins is better than that of in-line pin fins because the staggered arrangements produce large disturbance. Both in-line and staggered arrangements show the same behavior for thermal resistance, pressure drop, and the entropy generation.

Keywords: Pin-fin, heat sinks, simulations, turbulent flow.

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Authors: Hua Cao, Laurent Peyrodie, Olivier Agnani, Cécile Donzé

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Multiple Sclerosis (MS) is a disease which affects the central nervous system and causes balance problem. In clinical, this disorder is usually evaluated using static posturography. Some linear or nonlinear measures, extracted from the posturographic data (i.e. center of pressure, COP) recorded during a balance test, has been used to analyze postural control of MS patients. In this study, the trend (TREND) and the sample entropy (SampEn), two nonlinear parameters were chosen to investigate their relationships with the expanded disability status scale (EDSS) score. 40 volunteers with different EDSS scores participated in our experiments with eyes open (EO) and closed (EC). TREND and 2 types of SampEn (SampEn1 and SampEn2) were calculated for each combined COP’s position signal. The results have shown that TREND had a weak negative correlation to EDSS while SampEn2 had a strong positive correlation to EDSS. Compared to TREND and SampEn1, SampEn2 showed a better significant correlation to EDSS and an ability to discriminate the MS patients in the EC case. In addition, the outcome of the study suggests that the multi-dimensional nonlinear analysis could provide some information about the impact of disability progression in MS on dynamics of the COP data.

Keywords: Balance, multiple sclerosis, nonlinear analysis, postural sway.

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Authors: Johann Barbier, Eric Filiol, Kichenakoumar Mayoura

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We present in this paper a new approach for specific JPEG steganalysis and propose studying statistics of the compressed DCT coefficients. Traditionally, steganographic algorithms try to preserve statistics of the DCT and of the spatial domain, but they cannot preserve both and also control the alteration of the compressed data. We have noticed a deviation of the entropy of the compressed data after a first embedding. This deviation is greater when the image is a cover medium than when the image is a stego image. To observe this deviation, we pointed out new statistic features and combined them with the Multiple Embedding Method. This approach is motivated by the Avalanche Criterion of the JPEG lossless compression step. This criterion makes possible the design of detectors whose detection rates are independent of the payload. Finally, we designed a Fisher discriminant based classifier for well known steganographic algorithms, Outguess, F5 and Hide and Seek. The experiemental results we obtained show the efficiency of our classifier for these algorithms. Moreover, it is also designed to work with low embedding rates (< 10-5) and according to the avalanche criterion of RLE and Huffman compression step, its efficiency is independent of the quantity of hidden information.

Keywords: Compressed frequency domain, Fisher discriminant, specific JPEG steganalysis.

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Authors: C. Ardil

Abstract:

Unmanned combat aircraft (UCA) are expanding significantly in several defense industries, along with artificial intelligence improvements in highly precise technology. UCA is crucial in military settings for targeting enemy elements, and objects. UCA is also utilized for highly precise reconnaissance and surveillance tasks. To select the best alternative for critical missions, a methodical and effective strategy for UCA selection is required. Multiple criteria decision-making (MCDM) methodologies are ideally equipped to handle the complexity of alternative aircraft selection. To analyze UCA alternatives for the selection process, an integrated methodology built on the objective criteria weights and preference analysis for reference ideal solution (PARIS). First, the weights of essential elements are determined using the average weight (AW), standard deviation (SW) and entropy weight (EW) approach. The weights of the evaluation criteria affect the decision-making process. The aircraft choices in the decision problem are then ranked using objective criteria weights along with the PARIS technique. The validation and sensitivity analysis of the proposed MCDM approach are discussed.

Keywords: unmanned combat aircraft (UCA), multiple criteria decision making, MCDM, PARIS

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Authors: Hadi Veisi, Mansour Jamzad

Abstract:

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

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

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Authors: Ramesh K. Sunkaria, Puneeta Marwaha

Abstract:

Non linear methods of heart rate variability (HRV) analysis are becoming more popular. It has been observed that complexity measures quantify the regularity and uncertainty of cardiovascular RR-interval time series. In the present work, SampEn has been evaluated in healthy normal sinus rhythm (NSR) male and female subjects for different data lengths and tolerance level r. It is demonstrated that SampEn is small for higher values of tolerance r. Also SampEn value of healthy female group is higher than that of healthy male group for short data length and with increase in data length both groups overlap each other and it is difficult to distinguish them. The SampEn gives inaccurate results by assigning higher value to female group, because male subject have more complex HRV pattern than that of female subjects. Therefore, this traditional algorithm exhibits higher complexity for healthy female subjects than for healthy male subjects, which is misleading observation. This may be due to the fact that SampEn do not account for multiple time scales inherent in the physiologic time series and the hidden spatial and temporal fluctuations remains unexplored.

Keywords: Heart rate variability, normal sinus rhythm group, RR interval time series, sample entropy.

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Authors: B. Kabane, G. G. Redhi

Abstract:

An ammonium based ionic liquid (methyltrioctylammonium chloride) [N_{8 8 8 1}] [Cl] was investigated as an extraction potential solvent for volatile organic solvents (in this regard, solutes), which includes alkenes, alkanes, ketones, alkynes, aromatic hydrocarbons, tetrahydrofuran (THF), alcohols, thiophene, water and acetonitrile based on the experimental activity coefficients at infinite THF measurements were conducted by the use of gas-liquid chromatography at four different temperatures (313.15 to 343.15) K. Experimental data of activity coefficients obtained across the examined temperatures were used in order to calculate the physicochemical properties at infinite dilution such as partial molar excess enthalpy, Gibbs free energy and entropy term. Capacity and selectivity data for selected petrochemical extraction problems (heptane/thiophene, heptane/benzene, cyclohaxane/cyclohexene, hexane/toluene, hexane/hexene) were computed from activity coefficients data and compared to the literature values with other ionic liquids. Evaluation of activity coefficients at infinite dilution expands the knowledge and provides a good understanding related to the interactions between the ionic liquid and the investigated compounds.

Keywords: Separation, activity coefficients, ionic liquid, methyltrioctylammonium chloride, capacity.

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Authors: Sh. Kianfar, A. Moheb, H. Ghaforian

Abstract:

The equilibrium, thermodynamics and kinetics of the biosorption of Cd (II) and Pb(II) by a Spore Forming Bacillus (MGL 75) were investigated at different experimental conditions. The Langmuir and Freundlich, and Dubinin-Radushkevich (D-R) equilibrium adsorption models were applied to describe the biosorption of the metal ions by MGL 75 biomass. The Langmuir model fitted the equilibrium data better than the other models. Maximum adsorption capacities q max for lead (II) and cadmium (II) were found equal to 158.73mg/g and 91.74 mg/g by Langmuir model. The values of the mean free energy determined with the D-R equation showed that adsorption process is a physiosorption process. The thermodynamic parameters Gibbs free energy (ΔG°), enthalpy (ΔH°), and entropy (ΔS°) changes were also calculated, and the values indicated that the biosorption process was exothermic and spontaneous. Experiment data were also used to study biosorption kinetics using pseudo-first-order and pseudo-second-order kinetic models. Kinetic parameters, rate constants, equilibrium sorption capacities and related correlation coefficients were calculated and discussed. The results showed that the biosorption processes of both metal ions followed well pseudo-second-order kinetics.

Keywords: biosorption, kinetics, Metal ion removal, thermodynamics

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Authors: H. C. O. Reis, A. S. Cossolin, B. A. P. Santos, K. C. Castro, G. M. Pereira, V. C. Silva, P. T. Sousa Jr, E. L. Dall’Oglio, L. G. Vasconcelos, E. B. Morais

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In this study, malt bagasse, a low-cost waste biomass, was tested as a biosorbent to remove the cationic dye Malachite green (MG) from aqueous solution. Batch biosorption experiments were investigated as functions of different experimental parameters such as initial pH, salt (NaCl) concentration, contact time, temperature and initial dye concentration. Higher removal rates of MG were obtained at pH 8 and 10. The equilibrium and kinetic studies suggest that the biosorption follows Langmuir isotherm and the pseudo-second-order model. The maximum monolayer adsorption capacity was estimated at 117.65 mg/g (at 45 °C). According to Dubinin–Radushkevich (D-R) isotherm model, biosorption of MG onto malt bagasse occurs physically. The thermodynamic parameters such as Gibbs free energy, enthalpy and entropy indicated that the MG biosorption onto malt bagasse is spontaneous and endothermic. The results of the ionic strength effect indicated that the biosorption process under study had a strong tolerance under high salt concentrations. It can be concluded that malt bagasse waste has potential for application as biosorbent for removal of MG from aqueous solution.

Keywords: Color removal, kinetic and isotherm studies, thermodynamic parameters, FTIR.

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Authors: Andhe Dharani, P. S. Satyanarayana, Andhe Pallavi

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Considering payload, reliability, security and operational lifetime as major constraints in transmission of images we put forward in this paper a steganographic technique implemented at the physical layer. We suggest transmission of Halftoned images (payload constraint) in wireless sensor networks to reduce the amount of transmitted data. For low power and interference limited applications Turbo codes provide suitable reliability. Ensuring security is one of the highest priorities in many sensor networks. The Turbo Code structure apart from providing forward error correction can be utilized to provide for encryption. We first consider the Halftoned image and then the method of embedding a block of data (called secret) in this Halftoned image during the turbo encoding process is presented. The small modifications required at the turbo decoder end to extract the embedded data are presented next. The implementation complexity and the degradation of the BER (bit error rate) in the Turbo based stego system are analyzed. Using some of the entropy based crypt analytic techniques we show that the strength of our Turbo based stego system approaches that found in the OTPs (one time pad).

Keywords: Halftoning, Turbo codes, security, operationallifetime, Turbo based stego system.

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Authors: Federico Pérez González, Iñaki Goiricelaia Ordorika, Pedro Iriondo Bengoa

Abstract:

A new method for low complexity image coding is presented, that permits different settings and great scalability in the generation of the final bit stream. This coding presents a continuoustone still image compression system that groups loss and lossless compression making use of finite arithmetic reversible transforms. Both transformation in the space of color and wavelet transformation are reversible. The transformed coefficients are coded by means of a coding system in depending on a subdivision into smaller components (CFDS) similar to the bit importance codification. The subcomponents so obtained are reordered by means of a highly configure alignment system depending on the application that makes possible the re-configure of the elements of the image and obtaining different levels of importance from which the bit stream will be generated. The subcomponents of each level of importance are coded using a variable length entropy coding system (VBLm) that permits the generation of an embedded bit stream. This bit stream supposes itself a bit stream that codes a compressed still image. However, the use of a packing system on the bit stream after the VBLm allows the realization of a final highly scalable bit stream from a basic image level and one or several enhance levels.

Keywords: Image compression, wavelet transform, highlyscalable, reversible transform, embedded, subcomponents.

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Authors: C. Ardil

Abstract:

The purpose of this paper is to present fuzzy TOPSIS in an entropic fuzzy environment. Due to the ambiguous concepts often represented in decision data, exact values are insufficient to model real-life situations. In this paper, the rating of each alternative is defined in fuzzy linguistic terms, which can be expressed with triangular fuzzy numbers. The weight of each criterion is then derived from the decision matrix using the entropy weighting method. Next, a vertex method is proposed to calculate the distance between two triangular fuzzy numbers. According to the TOPSIS concept, a closeness coefficient is defined to determine the ranking order of all alternatives by simultaneously calculating the distances to both the fuzzy positive-ideal solution (FPIS) and the fuzzy negative-ideal solution (FNIS). Finally, an illustrative example of selecting stealth fighter aircraft is shown at the end of this article to highlight the procedure of the proposed method. Correlation analysis and validation analysis using TOPSIS, WSM, and WPM methods were performed to compare the ranking order of the alternatives.

Keywords: stealth fighter aircraft selection, fuzzy uncertainty theory (FUT), fuzzy entropic decision (FED), fuzzy linguistic variables, triangular fuzzy numbers, multiple criteria decision making analysis, MCDMA, TOPSIS, WSM, WPM

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Authors: Federico Pérez González, Iñaki Goirizelaia Ordorika, Pedro Iriondo Bengoa

Abstract:

In this work a new method for low complexity image coding is presented, that permits different settings and great scalability in the generation of the final bit stream. This coding presents a continuous-tone still image compression system that groups loss and lossless compression making use of finite arithmetic reversible transforms. Both transformation in the space of color and wavelet transformation are reversible. The transformed coefficients are coded by means of a coding system in depending on a subdivision into smaller components (CFDS) similar to the bit importance codification. The subcomponents so obtained are reordered by means of a highly configure alignment system depending on the application that makes possible the re-configure of the elements of the image and obtaining different importance levels from which the bit stream will be generated. The subcomponents of each importance level are coded using a variable length entropy coding system (VBLm) that permits the generation of an embedded bit stream. This bit stream supposes itself a bit stream that codes a compressed still image. However, the use of a packing system on the bit stream after the VBLm allows the realization of a final highly scalable bit stream from a basic image level and one or several improvement levels.

Keywords: Image compression, wavelet transform, highly scalable, reversible transform, embedded, subcomponents.

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Authors: Mohammed Golam Sarwer, Lai Man Po, Kai Guo, Q.M. Jonathan Wu

Abstract:

In H.264/AVC video encoding, rate-distortion optimization for mode selection plays a significant role to achieve outstanding performance in compression efficiency and video quality. However, this mode selection process also makes the encoding process extremely complex, especially in the computation of the ratedistortion cost function, which includes the computations of the sum of squared difference (SSD) between the original and reconstructed image blocks and context-based entropy coding of the block. In this paper, a transform-domain rate-distortion optimization accelerator based on fast SSD (FSSD) and VLC-based rate estimation algorithm is proposed. This algorithm could significantly simplify the hardware architecture for the rate-distortion cost computation with only ignorable performance degradation. An efficient hardware structure for implementing the proposed transform-domain rate-distortion optimization accelerator is also proposed. Simulation results demonstrated that the proposed algorithm reduces about 47% of total encoding time with negligible degradation of coding performance. The proposed method can be easily applied to many mobile video application areas such as a digital camera and a DMB (Digital Multimedia Broadcasting) phone.

Keywords: Context-adaptive variable length coding (CAVLC), H.264/AVC, rate-distortion optimization (RDO), sum of squareddifference (SSD).

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Authors: Georgi Yordanov Georgiev, Michael Daly, Erin Gombos, Amrit Vinod, Gajinder Hoonjan

Abstract:

Measures of complexity and entropy have not converged to a single quantitative description of levels of organization of complex systems. The need for such a measure is increasingly necessary in all disciplines studying complex systems. To address this problem, starting from the most fundamental principle in Physics, here a new measure for quantity of organization and rate of self-organization in complex systems based on the principle of least (stationary) action is applied to a model system - the central processing unit (CPU) of computers. The quantity of organization for several generations of CPUs shows a double exponential rate of change of organization with time. The exact functional dependence has a fine, S-shaped structure, revealing some of the mechanisms of self-organization. The principle of least action helps to explain the mechanism of increase of organization through quantity accumulation and constraint and curvature minimization with an attractor, the least average sum of actions of all elements and for all motions. This approach can help describe, quantify, measure, manage, design and predict future behavior of complex systems to achieve the highest rates of self organization to improve their quality. It can be applied to other complex systems from Physics, Chemistry, Biology, Ecology, Economics, Cities, network theory and others where complex systems are present.

Keywords: Organization, self-organization, complex system, complexification, quantitative measure, principle of least action, principle of stationary action, attractor, progressive development, acceleration, stochastic.

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Authors: Hui-Chuan Lu

Abstract:

A perfect secret-sharing scheme is a method to distribute a secret among a set of participants in such a way that only qualified subsets of participants can recover the secret and the joint share of participants in any unqualified subset is statistically independent of the secret. The collection of all qualified subsets is called the access structure of the perfect secret-sharing scheme. In a graph-based access structure, each vertex of a graph G represents a participant and each edge of G represents a minimal qualified subset. The average information ratio of a perfect secret-sharing scheme  realizing the access structure based on G is defined as AR = (Pv2V (G) H(v))/(|V (G)|H(s)), where s is the secret and v is the share of v, both are random variables from  and H is the Shannon entropy. The infimum of the average information ratio of all possible perfect secret-sharing schemes realizing a given access structure is called the optimal average information ratio of that access structure. Most known results about the optimal average information ratio give upper bounds or lower bounds on it. In this present structures based on bipartite graphs and determine the exact values of the optimal average information ratio of some infinite classes of them.

Keywords: secret-sharing scheme, average information ratio, star covering, core sequence.

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Authors: C. Villegas-Quezada, J. Climent

Abstract:

Several works regarding facial recognition have dealt with methods which identify isolated characteristics of the face or with templates which encompass several regions of it. In this paper a new technique which approaches the problem holistically dispensing with the need to identify geometrical characteristics or regions of the face is introduced. The characterization of a face is achieved by randomly sampling selected attributes of the pixels of its image. From this information we construct a set of data, which correspond to the values of low frequencies, gradient, entropy and another several characteristics of pixel of the image. Generating a set of “p" variables. The multivariate data set with different polynomials minimizing the data fitness error in the minimax sense (L∞ - Norm) is approximated. With the use of a Genetic Algorithm (GA) it is able to circumvent the problem of dimensionality inherent to higher degree polynomial approximations. The GA yields the degree and values of a set of coefficients of the polynomials approximating of the image of a face. By finding a family of characteristic polynomials from several variables (pixel characteristics) for each face (say Fi ) in the data base through a resampling process the system in use, is trained. A face (say F ) is recognized by finding its characteristic polynomials and using an AdaBoost Classifier from F -s polynomials to each of the Fi -s polynomials. The winner is the polynomial family closer to F -s corresponding to target face in data base.

Keywords: AdaBoost Classifier, Holistic Face Recognition, Minimax Multivariate Approximation, Genetic Algorithm.

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Authors: C. Ardil

Abstract:

This paper considers a comparative analysis of multiple criteria decision making analysis methods for strategic, tactical, and operational decisions in military fighter aircraft selection for the air force fleet planning. The evaluation criteria governing the decision analysis process are determined from the literature for the three existing military combat aircraft. Military fighter aircraft selection problem is structured using "preference analysis for reference ideal solution (PARIS)” approach in multiple criteria decision analysis (MCDMA). Systematic comparisons were made with existing MCDMA methods (PARIS, and TOPSIS) to verify the stability and accuracy of the results obtained. The proposed integrated MCDMA systematic approach is expected to address the issues encountered in the aircraft selection process. The comparative analysis results show that the proposed method is an effective and accurate tool that can help analysts make better strategic, tactical, and operational decisions.

Keywords: aircraft, military fighter aircraft selection, multiple criteria decision making, multiple criteria decision making analysis, mean weight, entropy weight, MCDMA, PARIS, TOPSIS, Saab Gripen, Dassault Rafale, Eurofighter Typhoon

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Authors: Mbainaibeye Jérôme, Noureddine Ellouze

Abstract:

We study in this paper the effect of the scene changing on image sequences coding system using Embedded Zerotree Wavelet (EZW). The scene changing considered here is the full motion which may occurs. A special image sequence is generated where the scene changing occurs randomly. Two scenarios are considered: In the first scenario, the system must provide the reconstruction quality as best as possible by the management of the bit rate (BR) while the scene changing occurs. In the second scenario, the system must keep the bit rate as constant as possible by the management of the reconstruction quality. The first scenario may be motivated by the availability of a large band pass transmission channel where an increase of the bit rate may be possible to keep the reconstruction quality up to a given threshold. The second scenario may be concerned by the narrow band pass transmission channel where an increase of the bit rate is not possible. In this last case, applications for which the reconstruction quality is not a constraint may be considered. The simulations are performed with five scales wavelet decomposition using the 9/7-tap filter bank biorthogonal wavelet. The entropy coding is performed using a specific defined binary code book and EZW algorithm. Experimental results are presented and compared to LEAD H263 EVAL. It is shown that if the reconstruction quality is the constraint, the system increases the bit rate to obtain the required quality. In the case where the bit rate must be constant, the system is unable to provide the required quality if the scene change occurs; however, the system is able to improve the quality while the scene changing disappears.

Keywords: Image Sequence Compression, Wavelet Transform, Scene Changing, Zero Tree, Bit Rate, Quality.

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Authors: Deng Tingting

Abstract:

The coordinated and integrated development of regions is an inevitable requirement for China to move towards high-quality sustainable development. As one of the regions with the best economic foundation and the strongest economic strength in the western China, it is a typical area with national importance and strong network connection characteristics in terms of the comprehensive effect of linking the inland hinterland and connecting the western and national urban networks. The integrated development of the Chengdu-Chongqing economic circle is of great strategic significance for the rapid and high-quality development of the western region. In the context of new urbanization, this paper takes 16 urban units within the economic circle as the research object, based on the 5-year panel data of population, regional economy and spatial construction and development from 2016 to 2020, using the entropy method and Theil index to analyze the three target layers, and cause analysis. The research shows that there are temporal and spatial differences in the Chengdu-Chongqing economic circle, and there are significant differences between the core city and the surrounding cities. Therefore, by reforming and innovating the regional coordinated development mechanism, breaking administrative barriers, and strengthening the "polar nucleus" radiation function to release the driving force for economic development, especially in the gully areas of economic development belts, will not only promote the coordinated development of internal regions, but also promote the coordinated and sustainable development of the western region and toward a high-quality development path.

Keywords: Chengdu-Chongqing economic circle, new urbanization, coordinated regional development, Theil Index.

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Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

Abstract:

Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., entropy, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one-class classification (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, principal component analysis (PCA), kernel principal component analysis (KPCA), and autoassociative neural network (ANN) are presented and their performance are compared. It is also shown that, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 95%.

Keywords: Anomaly detection, dimensionality reduction, frequencies selection, modal analysis, neural network, structural health monitoring, vibration measurement.

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Authors: Yehjune Heo

Abstract:

As biometric systems become widely deployed, the security of identification systems can be easily attacked by various spoof materials. This paper contributes to finding a reliable and practical anti-spoofing method using Convolutional Neural Networks (CNNs) based on the types of loss functions and optimizers. The types of CNNs used in this paper include AlexNet, VGGNet, and ResNet. By using various loss functions including Cross-Entropy, Center Loss, Cosine Proximity, and Hinge Loss, and various loss optimizers which include Adam, SGD, RMSProp, Adadelta, Adagrad, and Nadam, we obtained significant performance changes. We realize that choosing the correct loss function for each model is crucial since different loss functions lead to different errors on the same evaluation. By using a subset of the Livdet 2017 database, we validate our approach to compare the generalization power. It is important to note that we use a subset of LiveDet and the database is the same across all training and testing for each model. This way, we can compare the performance, in terms of generalization, for the unseen data across all different models. The best CNN (AlexNet) with the appropriate loss function and optimizers result in more than 3% of performance gain over the other CNN models with the default loss function and optimizer. In addition to the highest generalization performance, this paper also contains the models with high accuracy associated with parameters and mean average error rates to find the model that consumes the least memory and computation time for training and testing. Although AlexNet has less complexity over other CNN models, it is proven to be very efficient. For practical anti-spoofing systems, the deployed version should use a small amount of memory and should run very fast with high anti-spoofing performance. For our deployed version on smartphones, additional processing steps, such as quantization and pruning algorithms, have been applied in our final model.

Keywords: Anti-spoofing, CNN, fingerprint recognition, loss function, optimizer.

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Authors: Abdelhalim. N. Mohammed, Mohammed. Y. Esmail

Abstract:

In the course of recent decades, medical imaging has been dominated by the use of costly film media for review and archival of medical investigation, however due to developments in networks technologies and common acceptance of a standard digital imaging and communication in medicine (DICOM) another approach in light of World Wide Web was produced. Web technologies successfully used in telemedicine applications, the combination of web technologies together with DICOM used to design a web-based and open source DICOM viewer. The Web server allowance to inquiry and recovery of images and the images viewed/manipulated inside a Web browser without need for any preinstalling software. The dynamic site page for medical images visualization and processing created by using JavaScript and HTML5 advancements. The XAMPP ‘apache server’ is used to create a local web server for testing and deployment of the dynamic site. The web-based viewer connected to multiples devices through local area network (LAN) to distribute the images inside healthcare facilities. The system offers a few focal points over ordinary picture archiving and communication systems (PACS): easy to introduce, maintain and independently platforms that allow images to display and manipulated efficiently, the system also user-friendly and easy to integrate with an existing system that have already been making use of web technologies. The wavelet-based image compression technique on which 2-D discrete wavelet transform used to decompose the image then wavelet coefficients are transmitted by entropy encoding after threshold to decrease transmission time, stockpiling cost and capacity. The performance of compression was estimated by using images quality metrics such as mean square error ‘MSE’, peak signal to noise ratio ‘PSNR’ and compression ratio ‘CR’ that achieved (83.86%) when ‘coif3’ wavelet filter is used.

Keywords: DICOM, discrete wavelet transform, PACS, HIS, LAN.

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Authors: Supriya Gupta, Paresh Chokshi

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Polymer-particle interactions can be effectively utilized to produce composites that possess physicochemical properties superior to that of neat polymer. The incorporation of fillers with dimensions comparable to polymer chain size produces composites with extra-ordinary properties owing to very high surface to volume ratio. The dispersion of nanoparticles is achieved by inducing steric repulsion realized by grafting particles with polymeric chains. A comprehensive understanding of the interparticle interaction between these functionalized nanoparticles plays an important role in the synthesis of a stable polymer nanocomposite. With the focus on incorporation of clay sheets in a polymer matrix, we theoretically construct the polymer mediated interparticle potential for two nanosheets grafted with polymeric chains. The self-consistent field theory (SCFT) is employed to obtain the inhomogeneous composition field under equilibrium. Unlike the continuum models, SCFT is built from the microscopic description taking in to account the molecular interactions contributed by both intra- and inter-chain potentials. We present the results of SCFT calculations of the interaction potential curve for two grafted nanosheets immersed in the matrix of polymeric chains of dissimilar chemistry to that of the grafted chains. The interaction potential is repulsive at short separation and shows depletion attraction for moderate separations induced by high grafting density. It is found that the strength of attraction well can be tuned by altering the compatibility between the grafted and the mobile chains. Further, we construct the interaction potential between two nanosheets grafted with diblock copolymers with one of the blocks being chemically identical to the free polymeric chains. The interplay between the enthalpic interaction between the dissimilar species and the entropy of the free chains gives rise to a rich behavior in interaction potential curve obtained for two separate cases of free chains being chemically similar to either the grafted block or the free block of the grafted diblock chains.

Keywords: Clay nanosheets, polymer brush, polymer nanocomposites, self-consistent field theory.

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Authors: S. Sieniutycz

Abstract:

This paper unifies power optimization approaches in various energy converters, such as: thermal, solar, chemical, and electrochemical engines, in particular fuel cells. Thermodynamics leads to converter-s efficiency and limiting power. Efficiency equations serve to solve problems of upgrading and downgrading of resources. While optimization of steady systems applies the differential calculus and Lagrange multipliers, dynamic optimization involves variational calculus and dynamic programming. In reacting systems chemical affinity constitutes a prevailing component of an overall efficiency, thus the power is analyzed in terms of an active part of chemical affinity. The main novelty of the present paper in the energy yield context consists in showing that the generalized heat flux Q (involving the traditional heat flux q plus the product of temperature and the sum products of partial entropies and fluxes of species) plays in complex cases (solar, chemical and electrochemical) the same role as the traditional heat q in pure heat engines. The presented methodology is also applied to power limits in fuel cells as to systems which are electrochemical flow engines propelled by chemical reactions. The performance of fuel cells is determined by magnitudes and directions of participating streams and mechanism of electric current generation. Voltage lowering below the reversible voltage is a proper measure of cells imperfection. The voltage losses, called polarization, include the contributions of three main sources: activation, ohmic and concentration. Examples show power maxima in fuel cells and prove the relevance of the extension of the thermal machine theory to chemical and electrochemical systems. The main novelty of the present paper in the FC context consists in introducing an effective or reduced Gibbs free energy change between products p and reactants s which take into account the decrease of voltage and power caused by the incomplete conversion of the overall reaction.

Keywords: Power yield, entropy production, chemical engines, fuel cells, exergy.

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