Search results for: invariant%20theories

Authors: Wei-Jong Yang, Wei-Hau Du, Pau-Choo Chang, Jar-Ferr Yang, Pi-Hsia Hung

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The demands of smart visual thing recognition in various devices have been increased rapidly for daily smart production, living and learning systems in recent years. This paper proposed a visual thing recognition system, which combines binary scale-invariant feature transform (SIFT), bag of words model (BoW), and support vector machine (SVM) by using color information. Since the traditional SIFT features and SVM classifiers only use the gray information, color information is still an important feature for visual thing recognition. With color-based SIFT features and SVM, we can discard unreliable matching pairs and increase the robustness of matching tasks. The experimental results show that the proposed object recognition system with color-assistant SIFT SVM classifier achieves higher recognition rate than that with the traditional gray SIFT and SVM classification in various situations.

Keywords: color moments, visual thing recognition system, SIFT, color SIFT

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Authors: Henni Sid Ahmed, Belbachir Mohamed Faouzi, Jean Caelen

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Behavior recognition has been studied for realizing drivers assisting system and automated navigation and is an important studied field in the intelligent Building. In this paper, a recognition method of behavior recognition separated from a real image was studied. Images were divided into several categories according to the actual weather, distance and angle of view etc. SIFT was firstly used to detect key points and describe them because the SIFT (Scale Invariant Feature Transform) features were invariant to image scale and rotation and were robust to changes in the viewpoint and illumination. My goal is to develop a robust and reliable system which is composed of two fixed cameras in every room of intelligent building which are connected to a computer for acquisition of video sequences, with a program using these video sequences as inputs, we use SIFT represented different images of video sequences, and SVM (support vector machine) Lights as a programming tool for classification of images in order to classify people’s behaviors in the intelligent building in order to give maximum comfort with optimized energy consumption.

Keywords: video analysis, people behavior, intelligent building, classification

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Authors: Pei-Chen Wu

Abstract:

Both preexisting cross-sectional and longitudinal studies of personality-depression relationship have suffered from one main limitation: they ignored the stability of the construct of interest (e.g., personality and depression) can be expected to influence the estimate of the association between personality and depression. To address this limitation, the Trait-State-Occasion (TSO) modeling was adopted to analyze the sources of variance of the focused constructs. A TSO modeling was operated by partitioning a state variance into time-invariant (trait) and time-variant (occasion) components. Within a TSO framework, it is possible to predict change on the part of construct that really changes (i.e., time-variant variance), when controlling the trait variances. 750 high school students were followed for 4 waves over six-month intervals. The baseline data (T1) were collected from the senior high schools (aged 14 to 15 years). Participants were given Beck Depression Inventory and Big Five Inventory at each assessment. TSO modeling revealed that 70~78% of the variance in personality (five constructs) was stable over follow-up period; however, 57~61% of the variance in depression was stable. For personality construct, there were 7.6% to 8.4% of the total variance from the autoregressive occasion factors; for depression construct there were 15.2% to 18.1% of the total variance from the autoregressive occasion factors. Additionally, results showed that when controlling initial symptom severity, the time-invariant components of all five dimensions of personality were predictive of change in depression (Extraversion: B= .32, Openness: B = -.21, Agreeableness: B = -.27, Conscientious: B = -.36, Neuroticism: B = .39). Because five dimensions of personality shared some variance, the models in which all five dimensions of personality were simultaneous to predict change in depression were investigated. The time-invariant components of five dimensions were still significant predictors for change in depression (Extraversion: B = .30, Openness: B = -.24, Agreeableness: B = -.28, Conscientious: B = -.35, Neuroticism: B = .42). In sum, the majority of the variability of personality was stable over 2 years. Individuals with the greater tendency of Extraversion and Neuroticism have higher degrees of depression; individuals with the greater tendency of Openness, Agreeableness and Conscientious have lower degrees of depression.

Keywords: assessment, depression, personality, trait-state-occasion model

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Authors: Daliyah S. Aljutaili, Redna A. Almutlaq, Suha A. Alharbi, Dina M. Ibrahim

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All currencies around the world look very different from each other. For instance, the size, color, and pattern of the paper are different. With the development of modern banking services, automatic methods for paper currency recognition become important in many applications like vending machines. One of the currency recognition architecture’s phases is Feature detection and description. There are many algorithms that are used for this phase, but they still have some disadvantages. This paper proposes a feature detection algorithm, which merges the advantages given in the current SIFT and SURF algorithms, which we call, Speeded up Robust Scale-Invariant Feature Transform (SR-SIFT) algorithm. Our proposed SR-SIFT algorithm overcomes the problems of both the SIFT and SURF algorithms. The proposed algorithm aims to speed up the SIFT feature detection algorithm and keep it robust. Simulation results demonstrate that the proposed SR-SIFT algorithm decreases the average response time, especially in small and minimum number of best key points, increases the distribution of the number of best key points on the surface of the currency. Furthermore, the proposed algorithm increases the accuracy of the true best point distribution inside the currency edge than the other two algorithms.

Keywords: currency recognition, feature detection and description, SIFT algorithm, SURF algorithm, speeded up and robust features

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Authors: Zoran Jovanovic, Zoran Masonicic, S. Dragutinovic, Z. Sakota

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In this paper, results concerning flame propagation of various fuels in a particular combustion chamber with four tilted valves were elucidated. Flame propagation was represented by the evolution of spatial distribution of temperature in various cut-planes within combustion chamber while the flame front location was determined by dint of zones with maximum temperature gradient. The results presented are only a small part of broader on-going scrutinizing activity in the field of multidimensional modeling of reactive flows in combustion chambers with complicated geometries encompassing various models of turbulence, different fuels and combustion models. In the case of turbulence two different models were applied i.e. standard k-ε model of turbulence and k-ξ-f model of turbulence. In this paper flame propagation results were analyzed and presented for two different hydrocarbon fuels, such as CH4 and C8H18. In the case of combustion all differences ensuing from different turbulence models, obvious for non-reactive flows are annihilated entirely. Namely the interplay between fluid flow pattern and flame propagation is invariant as regards turbulence models and fuels applied. Namely the interplay between fluid flow pattern and flame propagation is entirely invariant as regards fuel variation indicating that the flame propagation through unburned mixture of CH4 and C8H18 fuels is not chemically controlled.

Keywords: automotive flows, flame propagation, combustion modelling, CNG

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Authors: P. Y. Tsyba, O. V. Razina, E. Güdekli, R. Myrzakulov

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In this paper, we consider the equation of motion for the F(R,T) gravity on their property of conformal invariance. It is shown that in the general case such a theory is not conformally invariant. Special cases for the functions v and u, in which the properties of the theory can appear, were studied.

Keywords: conformal invariance, gravity, space-time, metric

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Authors: Mohammad A. Sazzad, Md M. Alam

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Wind energy is one of the cleanest form of renewable energy. Despite wind industry is growing faster than ever there are some roadblocks towards the improvement. One of the difficulties the industry facing is insufficient knowledge about wake within the wind farms. As we know energy is generated in the lowest layer of the atmospheric boundary layer (ABL). This interaction between the wind turbine (WT) blades and wind introduces a low speed wind region which is defined as wake. This wake region shows different characteristics under each stability condition of the ABL. So, it is fundamental to know this wake region well which is defined mainly by turbulence transport and wake shear. Defining the wake recovery length and width are very crucial for wind farm to optimize the generation and reduce the waste of power to the grid. Therefore, in order to obtain the turbulent coefficients of velocity and length, this research focused on the large eddy simulation (LES) data for neutral ABL (NABL). According to turbulent theory, if we can present velocity defect and Reynolds stress in the form of local length and velocity scales, they become invariant. In our study velocity and length coefficients are 0.4867 and 0.4794 respectively which is close to the theoretical value of 0.5 for NABL. There are some invariant profiles because of the presence of thermal and wind shear power coefficients varied a little from the ideal condition.

Keywords: atmospheric boundary layer, renewable energy, turbulent coefficient, wind turbine, wake

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Authors: Rabab M. Ramadan, Elaraby A. Elgallad

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With extensive application, the performance of unimodal biometrics systems has to face a diversity of problems such as signal and background noise, distortion, and environment differences. Therefore, multimodal biometric systems are proposed to solve the above stated problems. This paper introduces a bimodal biometric recognition system based on the extracted features of the human palm print and iris. Palm print biometric is fairly a new evolving technology that is used to identify people by their palm features. The iris is a strong competitor together with face and fingerprints for presence in multimodal recognition systems. In this research, we introduced an algorithm to the combination of the palm and iris-extracted features using a texture-based descriptor, the Scale Invariant Feature Transform (SIFT). Since the feature sets are non-homogeneous as features of different biometric modalities are used, these features will be concatenated to form a single feature vector. Particle swarm optimization (PSO) is used as a feature selection technique to reduce the dimensionality of the feature. The proposed algorithm will be applied to the Institute of Technology of Delhi (IITD) database and its performance will be compared with various iris recognition algorithms found in the literature.

Keywords: iris recognition, particle swarm optimization, feature extraction, feature selection, palm print, the Scale Invariant Feature Transform (SIFT)

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Authors: Ophir Nave

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In our research, we present the concept of singularly perturbed vector field (SPVF) method, and its application to thermal explosion of diesel spray combustion. Given a system of governing equations, which consist of hidden Multi-scale variables, the SPVF method transfer and decompose such system to fast and slow singularly perturbed subsystems (SPS). The SPVF method enables us to understand the complex system, and simplify the calculations. Later powerful analytical, numerical and asymptotic methods (e.g method of integral (invariant) manifold (MIM), the homotopy analysis method (HAM) etc.) can be applied to each subsystem. We compare the results obtained by the methods of integral invariant manifold and SPVF apply to spray droplets combustion model. The research deals with the development of an innovative method for extracting fast and slow variables in physical mathematical models. The method that we developed called singular perturbed vector field. This method based on a numerical algorithm applied to global quasi linearization applied to given physical model. The SPVF method applied successfully to combustion processes. Our results were compared to experimentally results. The SPVF is a general numerical and asymptotical method that reveals the hierarchy (multi-scale system) of a given system.

Keywords: polydisperse spray, model reduction, asymptotic analysis, multi-scale systems

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Authors: Osman Adiguzel

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Shape memory effect is a peculiar property exhibited by certain alloy systems and based on martensitic transformation, and shape memory properties are closely related to the microstructures of the material. Shape memory effect is linked with martensitic transformation, which is a solid state phase transformation and occurs with the cooperative movement of atoms by means of lattice invariant shears on cooling from high-temperature parent phase. Lattice twinning and detwinning can be considered as elementary processes activated during the transformation. Thermally induced martensite occurs as martensite variants, in self-accommodating manner and consists of lattice twins. Also, this martensite is called the twinned martensite or multivariant martensite. Deformation of shape memory alloys in martensitic state proceeds through a martensite variant reorientation. The martensite variants turn into the reoriented single variants with deformation, and the reorientation process has great importance for the shape memory behavior. Copper based alloys exhibit this property in metastable β- phase region, which has DO3 –type ordered lattice in ternary case at high temperature, and these structures martensiticaly turn into the layered complex structures with lattice twinning mechanism, on cooling from high temperature parent phase region. The twinning occurs as martensite variants with lattice invariant shears in two opposite directions, <110 > -type directions on the {110}- type plane of austenite matrix. Lattice invariant shear is not uniform in copper based ternary alloys and gives rise to the formation of unusual layered structures, like 3R, 9R, or 18R depending on the stacking sequences on the close-packed planes of the ordered lattice. The unit cell and periodicity are completed through 18 atomic layers in case of 18R-structure. On the other hand, the deformed material recovers the original shape on heating above the austenite finish temperature. Meanwhile, the material returns to the twinned martensite structures (thermally induced martensite structure) in one way (irreversible) shape memory effect on cooling below the martensite finish temperature, whereas the material returns to the detwinned martensite structure (deformed martensite) in two-way (reversible) shape memory effect. Shortly one can say that the microstructural mechanisms, responsible for the shape memory effect are the twinning and detwinning processes as well as martensitic transformation. In the present contribution, x-ray diffraction, transmission electron microscopy (TEM) and differential scanning calorimetry (DSC) studies were carried out on two copper-based ternary alloys, CuZnAl, and CuAlMn.

Keywords: shape memory effect, martensitic transformation, twinning and detwinning, layered structures

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Authors: Alvaro Callejas-Ramos, Lorena Alvarez-Perez, Alexander Benitez-Buenache, Anibal R. Figueiras-Vidal

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This contribution presents a promising formulation which allows to extend the principled binary rebalancing procedures, also known as neutral re-balancing mechanisms in the sense that they do not alter the likelihood ratio

Keywords: Bregman divergences, imbalanced multiclass classifi-cation, informed re-balancing, invariant likelihood ratio

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Authors: Jae-Neung Lee, Keun-Chang Kwak

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This paper describes an analysis of Yacht Simulator international trends and also explains about Yacht. Examples of yacht Simulator using Yacht Simulator include image processing for totaling the total number of vehicles, edge/target detection, detection and evasion algorithm, image processing using SIFT (scale invariant features transform) matching, and application of median filter and thresholding.

Keywords: yacht simulator, simulator, trends analysis, SIFT

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Authors: J. M. Hernández-Ontiveros, E. E. García-Guerrero, E. Inzunza-González, O. R. López-Bonilla

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This paper presents the implementation of an algorithm that identifies and accounts different fish species: Catfish, Sea bream, Sawfish, Tilapia, and Totoaba. The main contribution of the method is the fusion of the characteristics of invariance to the position, rotation and scale of the Hu moments, with the proper counting of fish. The identification and counting is performed, from an image under different noise conditions. From the experimental results obtained, it is inferred the potentiality of the proposed algorithm to be applied in different scenarios of aquaculture production.

Keywords: counting fish, digital image processing, invariant moments, pattern recognition

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Authors: S. Pesina, T. Solonchak

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Phenomenological analysis is not based on natural language, but ideal language which is able to be a carrier of ideal meanings – eidos representing typical structures or essences. For this purpose, it’s necessary to release from the spatio-temporal definiteness of a subject and then state its noetic essence (eidos) by means of free fantasy generation. Herewith, as if a totally new objectness is created - the universal, confirming the thesis that thinking process takes place in generalizations passing by numerous means through the specific to the general and from the general through the specific to the singular.

Keywords: lexical eidos, phenomenology, noema, polysemantic word, semantic core

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Authors: Wagneur Edouard

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Tropical algebra is the algebra constructed over an idempotent semifield S. We show here that every m-dimensional tropical module M over S with strongly independent basis can be embedded into Sm, and provide an algebraic invariant -the Γ-matrix of M- which characterises the isomorphy class of M. The strong independence condition also yields a significant improvement to the Whitney embedding for tropical torsion modules published earlier We also show that the strong independence of the basis of M is equivalent to the unique representation of elements of M. Numerous examples illustrate our results.

Keywords: classification, idempotent semi-modules, strong independence, tropical algebra

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Authors: Abdul Jalil M. Khalaf, Esraa M. Kadhim

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The Hosoya polynomial of a graph G is a graphical invariant polynomial that its first derivative at x= 1 is equal to the Wiener index and second derivative at x=1 is equal to the Hyper-Wiener index. In this paper we study the Hosoya polynomial of zero-divisor graphs.

Keywords: Hosoya polynomial, wiener index, Hyper-Wiener index, zero-divisor graphs

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Authors: T. K. Dutta, K. K. Das, N. Dutta

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The salient feature of this paper is primarily concerned with Ricker’s population model: f(x)=x e^(r(1-x/k)), where r is the control parameter and k is the carrying capacity, and some fruitful results are obtained with the following objectives: 1) Determination of bifurcation values leading to a chaotic region, 2) Development of Statistical Methods and Analysis required for the measure of Fractal dimensions, 3) Calculation of various fractal dimensions. These results also help that the invariant probability distribution on the attractor, when it exists, provides detailed information about the long-term behavior of a dynamical system. At the end, some open problems are posed for further research.

Keywords: Feigenbaum universality, chaos, Lyapunov exponent, fractal dimensions

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Authors: Yaeji Lim, Hee-Seok Oh

Abstract:

The coherence analysis measures the linear time-invariant relationship between two data sets and has been studied various fields such as signal processing, engineering, and medical science. However classical coherence analysis tends to be sensitive to outliers and focuses only on mean relationship. In this paper, we generalized cross periodogram to quantile cross periodogram and provide richer inter-relationship between two data sets. This is a general version of Laplace cross periodogram. We prove its asymptotic distribution under the long range process and compare them with ordinary coherence through numerical examples. We also present real data example to confirm the usefulness of quantile coherence analysis.

Keywords: coherence, cross periodogram, spectrum, quantile

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Authors: A. Kulandai Therese

Abstract:

The eccentric connectivity index based on degree and eccentricity of the vertices of a graph is a widely used graph invariant in mathematics.In this paper, we present the explicit eccentric connectivity index, first and second Zagreb indices for a Corona graph and sub division-related corona graphs.

Keywords: corona graph, degree, eccentricity, eccentric connectivity index, first zagreb index, second zagreb index, subdivision graphs

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Authors: Lina Pan

Abstract:

In non-Gaussian clutter of a spherically invariant random vector, in the cases that a certain estimated covariance matrix could become singular, the adaptive target detection of high-range-resolution radar is addressed. Firstly, the restricted maximum likelihood (RML) estimates of unknown covariance matrix and scatterer amplitudes are derived for non-Gaussian clutter. And then the RML estimate of texture is obtained. Finally, a novel detector is devised. It is showed that, without secondary data, the proposed detector outperforms the existing Kelly binary integrator.

Keywords: non-Gaussian clutter, covariance matrix estimation, target detection, maximum likelihood

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Authors: O. Abusaeeda, J. P. O. Evans, D. Downes

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We demonstrate the synthesis of intermediary views within a sequence of X-ray images that exhibit depth from motion or kinetic depth effect in a visual display. Each synthetic image replaces the requirement for a linear X-ray detector array during the image acquisition process. Scale invariant feature transform, SIFT, in combination with epipolar morphing is employed to produce synthetic imagery. Comparison between synthetic and ground truth images is reported to quantify the performance of the approach. Our work is a key aspect in the development of a 3D imaging modality for the screening of luggage at airport checkpoints. This programme of research is in collaboration with the UK Home Office and the US Dept. of Homeland Security.

Keywords: X-ray, kinetic depth, KDE, view synthesis

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Authors: Y. Johnson

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Study of multi-satellite formation flight systems has drawn wide attention recently due to so many potential advantages. The present work aims to model the relative motion dynamics in terms of change in classical orbital parameters between the two satellites-chief and deputy- under Earth’s oblateness effect. The required impulsive thrust control is calculated to minimize these orbital parameter changes. The formation configuration is initialized by selecting a set of orbital parameters for the chief and deputy satellites such that bounded motion is maintained for a long time in a J_2-invariant relative non-circular orbit between the satellites. The solution of J_2-modified Hill’s equations is also derived in this paper.

Keywords: satellite, formation flight, j2 effect, control

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Authors: Ying Wang, Haiyan Xie, Aoming Zhang

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The degree distance of a graph is a graph invariant that is more sensitive than the Wiener index. In this paper, we calculate the vertex degree distances of one vertex union of the cycle and the star, and the degree distance of one vertex union of the cycle and the star. These results lay a foundation for further study on the extreme value of the vertex degree distances, and the distribution of the vertices with the extreme value in one vertex union of the cycle and the star.

Keywords: degree distance, vertex-degree-distance, one vertex union of a cycle and a star, graph

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Authors: Bingquan Shen

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Convolutional Neural Networks (CNN) have demonstrated their effectiveness in synthesizing 3D views of object instances at various viewpoints. Given the problem where one have limited viewpoints of a particular object for classification, we present a pose normalization architecture to transform the object to existing viewpoints in the training dataset before classification to yield better classification performance. We have demonstrated that this Pose Normalization Network (PNN) can capture the style of the target object and is able to re-render it to a desired viewpoint. Moreover, we have shown that the PNN improves the classification result for the 3D chairs dataset and ShapeNet airplanes dataset when given only images at limited viewpoint, as compared to a CNN baseline.

Keywords: convolutional neural networks, object classification, pose normalization, viewpoint invariant

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Authors: Simone B. K. Aires, Cinthia O. de A. Freitas, Luiz E. S. Oliveira

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This paper contributes to the CBIR systems applied to trademark retrieval. The proposed model includes aspects from visual perception of the shapes, by means of feature extractor associated to a non-symmetrical perceptual zoning mechanism based on the Principles of Gestalt. Thus, the feature set were performed using Scale Invariant Feature Transform (SIFT). We carried out experiments using four different zonings strategies (Z = 4, 5H, 5V, 7) for matching and retrieval tasks. Our proposal method achieved the normalized recall (Rn) equal to 0.84. Experiments show that the non-symmetrical zoning could be considered as a tool to build more reliable trademark retrieval systems.

Keywords: CBIR, Gestalt, matching, non-symmetrical zoning, SIFT

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Authors: Vesna Kirandziska, Nevena Ackovska, Ana Madevska Bogdanova

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The problem of emotion recognition is a challenging problem. It is still an open problem from the aspect of both intelligent systems and psychology. In this paper, both voice features and facial features are used for building an emotion recognition system. A Support Vector Machine classifiers are built by using raw data from video recordings. In this paper, the results obtained for the emotion recognition are given, and a discussion about the validity and the expressiveness of different emotions is presented. A comparison between the classifiers build from facial data only, voice data only and from the combination of both data is made here. The need for a better combination of the information from facial expression and voice data is argued.

Keywords: emotion recognition, facial recognition, signal processing, machine learning

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Authors: Adnan A. Y. Mustafa

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In this paper we present a quick technique to measure the similarity between binary images. The technique is based on a probabilistic mapping approach and is fast because only a minute percentage of the image pixels need to be compared to measure the similarity, and not the whole image. We exploit the power of the Probabilistic Matching Model for Binary Images (PMMBI) to arrive at an estimate of the similarity. We show that the estimate is a good approximation of the actual value, and the quality of the estimate can be improved further with increased image mappings. Furthermore, the technique is image size invariant; the similarity between big images can be measured as fast as that for small images. Examples of trials conducted on real images are presented.

Keywords: big images, binary images, image matching, image similarity

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Authors: Zhe Xu, Jian Li, Lvping Li, Zezheng Dong

Abstract:

This work is to study an optimized transfer strategy of connecting Earth and Mars via the vicinity of libration points, which have been playing an increasingly important role in trajectory designing on a deep space mission, and can be used as an effective alternative solution for Earth-Mars direct transfer mission in some unusual cases. The use of vicinity of libration points of the sun-planet body system is becoming potential gateways for future interplanetary transfer missions. By adding fuel to cargo spaceships located in spaceports, the interplanetary round-trip exploration shuttle mission of such a system facility can also be a reusable transportation system. In addition, in some cases, when the S/C cruising through invariant manifolds, it can also save a large amount of fuel. Therefore, it is necessary to make an effort on looking for efficient transfer strategies using variant manifold about libration points. It was found that Earth L1/L2 Halo/Lyapunov orbits and Mars L2/L1 Halo/Lyapunov orbits could be connected with reasonable fuel consumption and flight duration with appropriate design. In the paper, the halo hopping method and coplanar circular method are briefly introduced. The former used differential corrections to systematically generate low ΔV transfer trajectories between interplanetary manifolds, while the latter discussed escape and capture trajectories to and from Halo orbits by using impulsive maneuvers at periapsis of the manifolds about libration points. In the following, designs of transfer strategies of the two methods are shown here. A comparative performance analysis of interplanetary transfer strategies of the two methods is carried out accordingly. Comparison of strategies is based on two main criteria: the total fuel consumption required to perform the transfer and the time of flight, as mentioned above. The numeric results showed that the coplanar circular method procedure has certain advantages in cost or duration. Finally, optimized transfer strategy with engineering constraints is searched out and examined to be an effective alternative solution for a given direct transfer mission. This paper investigated main methods and gave out an optimized solution in interplanetary transfer via the vicinity of libration points. Although most of Earth-Mars mission planners prefer to build up a direct transfer strategy for the mission due to its advantage in relatively short time of flight, the strategies given in the paper could still be regard as effective alternative solutions since the advantages mentioned above and longer departure window than direct transfer.

Keywords: circular restricted three-body problem, halo/Lyapunov orbit, invariant manifolds, libration points

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Authors: Mojtaba Hakimi-Moghaddam

Abstract:

Positive realness as the most important property of driving point impedance of passive electrical networks appears in the control systems stability theory in 1960’s. There are three important subsets of positive real (PR) systems are introduced by researchers, that is, loos-less positive real (LLPR) systems, weakly strictly positive real (WSPR) systems and strictly positive real (SPR) systems. In this paper, definitions, properties, lemmas, and theorems related to family of positive real systems are summarized. Properties in both frequency domain and state space representation of system are explained. Also, several illustrative examples are presented.

Keywords: real rational matrix transfer functions, positive realness property, strictly positive realness property, Hermitian form asymptotic property, pole-zero properties

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Authors: Enqing Chen, Jianbo Wang

Abstract:

It is well known that the wavelet transform provides a very effective framework for multiscale edges analysis. However, wavelets are not very effective in representing images containing distributed discontinuities such as edges. In this paper, we propose a novel multiscale edge detection method in nonsubsampled contourlet transform (NSCT) domain, which is based on the dominant multiscale, multidirection edge expression and outstanding edge location of NSCT. Through real images experiments, simulation results demonstrate that the proposed method is better than other edge detection methods based on Canny operator, wavelet and contourlet. Additionally, the proposed method also works well for noisy images.

Keywords: edge detection, NSCT, shift invariant, modulus maxima

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