Search results for: 3D shape decomposition representation

Authors: Anat Thapinta

Abstract:

This research aimed to study on the potential of recycling organic waste in Suan Sunandha Rajabhat University as compost. In doing so, the composition of solid waste generated in the campus was investigated while physical and chemical properties of organic waste were analyzed in order to evaluate the portion of waste suitable for recycling as compost. As a result of the study, it was found that (1) the amount of organic waste was averaged at 299.8 kg/day in which mixed food wastes had the highest amount of 191.9 kg/day followed by mixed leave & yard wastes and mixed fruit & vegetable wastes at the amount of 66.3 and 41.6 kg/day respectively; (2) physical and chemical properties of organic waste in terms of moisture content was between 69.54 to 78.15%, major elements for plant as N, P and K were 0.14 to 0.17%, 0.46 to 0.52% and 0.16 to 0.18% respectively, and carbon/nitrogen ratio (C/N) was about 15:1 to 17.5:1; (3) recycling organic waste as compost was designed by aerobic decomposition using mixed food wastes : mixed leave & yard wastes : mixed fruit & vegetable wastes at the portion of 3:2:1 by weight in accordance with the potential of their amounts and their physical and chemical properties.

Keywords: Compost, Organic waste, Physical and chemical properties, Recycling.

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Authors: L. Zehtaban, D. Roller

Abstract:

Apart from geometry, functionality is one of the most significant hallmarks of a product. The functionality of a product can be considered as the fundamental justification for a product existence. Therefore a functional analysis including a complete and reliable descriptor has a high potential to improve product development process in various fields especially in knowledge-based design. One of the important applications of the functional analysis and indexing is in retrieval and design reuse concept. More than 75% of design activity for a new product development contains reusing earlier and existing design know-how. Thus, analysis and categorization of product functions concluded by functional indexing, influences directly in design optimization. This paper elucidates and evaluates major classes for functional analysis by discussing their major methods. Moreover it is finalized by presenting a noble hybrid approach for functional analysis.

Keywords: Functional analysis, design reuse, functionalindexing and representation.

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Authors: Patrick Maier, Marcus Tönnis, Gudrun Klinker

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Spatial understanding and the understanding of dynamic change in the spatial structure of molecules during a reaction is essential for designing new molecules. Knowing the physical processes in the reactions helps to speed up the designing process. To support the designer with the correct representation of the designed molecule as well as showing the dynamic behavior of the whole reacting system is the goal of our application. Our system shows the spatial deformation of the molecules at every time interval by minimizing the energy level of the molecules. The position and orientation of the molecules can be intuitively controlled by manipulating objects of the real world using Augmented Reality techniques. Our approach has the potential to speed up the design of new molecules and help students to understand the chemical processes better.

Keywords: Augmented Augmented Chemical Reactions, Augmented Reality, chemistry, education.

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Authors: PoiSim Khiew, WeeSiong Chiu, ThianKhoonTan, Shahidan Radiman, Roslan Abd-Shukor, Muhammad Azmi Abd-Hamid, ChinHua Chia

Abstract:

Magnetic and semiconductor nanomaterials exhibit novel magnetic and optical properties owing to their unique size and shape-dependent effects. With shrinking the size down to nanoscale region, various anomalous properties that normally not present in bulk start to dominate. Ability in harnessing of these anomalous properties for the design of various advance electronic devices is strictly dependent on synthetic strategies. Hence, current research has focused on developing a rational synthetic control to produce high quality nanocrystals by using organometallic approach to tune both size and shape of the nanomaterials. In order to elucidate the growth mechanism, transmission electron microscopy was employed as a powerful tool in performing real time-resolved morphologies and structural characterization of magnetic (Fe3O4) and semiconductor (ZnO) nanocrystals. The current synthetic approach is found able to produce nanostructures with well-defined shapes. We have found that oleic acid is an effective capping ligand in preparing oxide-based nanostructures without any agglomerations, even at high temperature. The oleate-based precursors and capping ligands are fatty acid compounds, which are respectively originated from natural palm oil with low toxicity. In comparison with other synthetic approaches in producing nanostructures, current synthetic method offers an effective route to produce oxide-based nanomaterials with well-defined shapes and good monodispersity. The nanocystals are well-separated with each other without any stacking effect. In addition, the as-synthesized nanopellets are stable in terms of chemically and physically if compared to those nanomaterials that are previous reported. Further development and extension of current synthetic strategy are being pursued to combine both of these materials into nanocomposite form that will be used as “smart magnetic nanophotocatalyst" for industry waste water treatment.

Keywords: Metal oxide nanomaterials, Nanophotocatalyst, Organometallic synthesis, Morphology Control

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Authors: Clark Van Dam, Gagan Mirchandani

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The Continuously Adaptive Mean-Shift (CamShift) algorithm, incorporating scene depth information is combined with the l1-minimization sparse representation based method to form a hybrid kernel and state space-based tracking algorithm. We take advantage of the increased efficiency of the former with the robustness to occlusion property of the latter. A simple interchange scheme transfers control between algorithms based upon drift and occlusion likelihood. It is quantified by the projection of target candidates onto a depth map of the 2D scene obtained with a low cost stereo vision webcam. Results are improved tracking in terms of drift over each algorithm individually, in a challenging practical outdoor multiple occlusion test case.

Keywords: CamShift, l1-minimization, particle filter, stereo vision, video tracking.

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Authors: Gökhan Silahtaroğlu

Abstract:

Decision tree algorithms have very important place at classification model of data mining. In literature, algorithms use entropy concept or gini index to form the tree. The shape of the classes and their closeness to each other some of the factors that affect the performance of the algorithm. In this paper we introduce a new decision tree algorithm which employs data (attribute) folding method and variation of the class variables over the branches to be created. A comparative performance analysis has been held between the proposed algorithm and C4.5.

Keywords: Classification, decision tree, split, pruning, entropy, gini.

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Authors: Elena Kotevska

Abstract:

This paper presents a generalization kernel for gravitational potential determination by harmonic splines. It was shown in [10] that the gravitational potential can be approximated using a kernel represented as a Newton integral over the real Earth body. On the other side, the theory of geopotential approximation by harmonic splines uses spherically oriented kernels. The purpose of this paper is to show that in the spherical case both kernels have the same type of representation, which leads us to conclusion that it is possible to consider the kernel represented as a Newton integral over the real Earth body as a kind of generalization of spherically harmonic kernels to real geometries.

Keywords: Geopotential, Reproducing Kernel, Approximation, Regular Surface

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Authors: Xiao Yihong, Yu Kexin, Burra Venkata Durga Kumar

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With the accelerating process of urbanization, the problem of urban road congestion is becoming more and more serious. Intelligent transportation system combining distributed and artificial intelligence has become a research hotspot. As the core development direction of the intelligent transportation system, Cooperative Intelligent Transportation System (C-ITS) integrates advanced information technology and communication methods and realizes the integration of human, vehicle, roadside infrastructure and other elements through the multi-agent distributed system. By analyzing the system architecture and technical characteristics of C-ITS, the paper proposes a distributed multi-agent C-ITS. The system consists of Roadside Subsystem, Vehicle Subsystem and Personal Subsystem. At the same time, we explore the scalability of the C-ITS and put forward incorporating local rewards in the centralized training decentralized execution paradigm, hoping to add a scalable value decomposition method. In addition, we also suggest introducing blockchain to improve the safety of the traffic information transmission process. The system is expected to improve vehicle capacity and traffic safety.

Keywords: Distributed system, artificial intelligence, multi-agent, Cooperative Intelligent Transportation System.

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Authors: Fereshteh Mahdavi, Maizatul Akmar Ismail, Noorhidawati Abdullah

Abstract:

Currently WWW is the first solution for scholars in finding information. But, analyzing and interpreting this volume of information will lead to researchers overload in pursuing their research. Trend detection in scientific publication retrieval systems helps scholars to find relevant, new and popular special areas by visualizing the trend of input topic. However, there are few researches on trend detection in scientific corpora while their proposed models do not appear to be suitable. Previous works lack of an appropriate representation scheme for research topics. This paper describes a method that combines Semantic Web and ontology to support advance search functions such as trend detection in the context of scholarly Semantic Web system (SSWeb).

Keywords: Trend, Semi-Automatic Trend Detection, Ontology, Semantic Trend Detection.

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Authors: Alexander Y. Vaninsky

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The objective of this paper is finding the way of economic restructuring - that is, change in the shares of sectoral gross outputs - resulting in the maximum possible increase in the gross domestic product (GDP) combined with decreases in energy consumption and CO₂ emissions. It uses an input-output model for the GDP and factorial models for the energy consumption and CO₂ emissions to determine the projection of the gradient of GDP, and the antigradients of the energy consumption and CO₂ emissions, respectively, on a subspace formed by the structure-related variables. Since the gradient (antigradient) provides a direction of the steepest increase (decrease) of the objective function, and their projections retain this property for the functions' limitation to the subspace, each of the three directional vectors solves a particular problem of optimal structural change. In the next step, a type of factor analysis is applied to find a convex combination of the projected gradient and antigradients having maximal possible positive correlation with each of the three. This convex combination provides the desired direction of the structural change. The national economy of the United States is used as an example of applications.

Keywords: Economic restructuring, Input-Output analysis, Divisia index, Factorial decomposition, E3 models.

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Authors: M. S. Merzoug, F. Naceri

Abstract:

This paper presents a comparative study on two most popular control strategies for Permanent Magnet Synchronous Motor (PMSM) drives: field-oriented control (FOC) and direct torque control (DTC). The comparison is based on various criteria including basic control characteristics, dynamic performance, and implementation complexity. The study is done by simulation using the Simulink Power System Blockset that allows a complete representation of the power section (inverter and PMSM) and the control system. The simulation and evaluation of both control strategies are performed using actual parameters of Permanent Magnet Synchronous Motor fed by an IGBT PWM inverter.

Keywords: PMSM, FOC, DTC, hysteresis, PWM.

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Authors: Laurenţiu Militeanu, Cristina Gena Dascâlu, D. Cristea

Abstract:

The human head representations usually are based on the morphological – structural components of a real model. Over the time became more and more necessary to achieve full virtual models that comply very rigorous with the specifications of the human anatomy. Still, making and using a model perfectly fitted with the real anatomy is a difficult task, because it requires large hardware resources and significant times for processing. That is why it is necessary to choose the best compromise solution, which keeps the right balance between the details perfection and the resources consumption, in order to obtain facial animations with real-time rendering. We will present here the way in which we achieved such a 3D system that we intend to use as a base point in order to create facial animations with real-time rendering, used in medicine to find and to identify different types of pathologies.

Keywords: 3D models, virtual reality.

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Authors: K. Krizova, R. Hela, S. Keprdova

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This paper introduces selected composition of conventional concretes and their resulting mechanical properties at different ages of concrete. With respect to utilization of mineral admixtures, fly ash and ground limestone agents were included in addition to pure Portland binder. The proposal of concrete composition remained constant in basic concrete components such as cement and representation of individual contents of aggregate fractions; weight dosing of admixtures and water dose were only modified. Water dose was chosen in order to achieve identical consistence by settlement for all proposals of concrete composition. Mechanical properties monitored include compression strength, static and dynamic modulus of concrete elasticity, at ages of 7, 28, 90, and 180 days.

Keywords: Cement, mineral admixtures, microstructure of concrete, mechanical properties.

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Authors: Sebastien Harasse, Laurent Bonnaud, Michel Desvignes

Abstract:

Counting people from a video stream in a noisy environment is a challenging task. This project aims at developing a counting system for transport vehicles, integrated in a video surveillance product. This article presents a method for the detection and tracking of multiple faces in a video by using a model of first and second order local moments. An iterative process is used to estimate the position and shape of multiple faces in images, and to track them. the trajectories are then processed to count people entering and leaving the vehicle.

Keywords: face detection, tracking, counting, local statistics

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Authors: Khair Eddin Sabri, Ridha Khedri, Jason Jaskolka

Abstract:

Cryptographic protocols are widely used in various applications to provide secure communications. They are usually represented as communicating agents that send and receive messages. These agents use their knowledge to exchange information and communicate with other agents involved in the protocol. An agent knowledge can be partitioned into explicit knowledge and procedural knowledge. The explicit knowledge refers to the set of information which is either proper to the agent or directly obtained from other agents through communication. The procedural knowledge relates to the set of mechanisms used to get new information from what is already available to the agent. In this paper, we propose a mathematical framework which specifies the explicit knowledge of an agent involved in a cryptographic protocol. Modelling this knowledge is crucial for the specification, analysis, and implementation of cryptographic protocols. We also, report on a prototype tool that allows the representation and the manipulation of the explicit knowledge.

Keywords: Information Algebra, Agent Knowledge, CryptographicProtocols

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Authors: Daniel I. Morariu, Lucian N. Vintan, Volker Tresp

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Text categorization is the problem of classifying text documents into a set of predefined classes. After a preprocessing step, the documents are typically represented as large sparse vectors. When training classifiers on large collections of documents, both the time and memory restrictions can be quite prohibitive. This justifies the application of feature selection methods to reduce the dimensionality of the document-representation vector. In this paper, we present three feature selection methods: Information Gain, Support Vector Machine feature selection called (SVM_FS) and Genetic Algorithm with SVM (called GA_SVM). We show that the best results were obtained with GA_SVM method for a relatively small dimension of the feature vector.

Keywords: Feature Selection, Learning with Kernels, Support Vector Machine, Genetic Algorithm, and Classification.

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Authors: Daniel Morariu, Lucian N. Vintan, Volker Tresp

Abstract:

Text categorization is the problem of classifying text documents into a set of predefined classes. After a preprocessing step, the documents are typically represented as large sparse vectors. When training classifiers on large collections of documents, both the time and memory restrictions can be quite prohibitive. This justifies the application of feature selection methods to reduce the dimensionality of the document-representation vector. In this paper, three feature selection methods are evaluated: Random Selection, Information Gain (IG) and Support Vector Machine feature selection (called SVM_FS). We show that the best results were obtained with SVM_FS method for a relatively small dimension of the feature vector. Also we present a novel method to better correlate SVM kernel-s parameters (Polynomial or Gaussian kernel).

Keywords: Feature Selection, Learning with Kernels, SupportVector Machine, and Classification.

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Authors: Yurii Bloshko, Oksana Olar

Abstract:

This paper presents the analysis of six different classes of Petri nets: fuzzy Petri nets (FPN), generalized fuzzy Petri nets (GFPN), parameterized fuzzy Petri nets (PFPN), T2GFPN, flexible generalized fuzzy Petri nets (FGFPN), binary Petri nets (BPN). These classes were simulated in the special software PNeS® for the analysis of its pros and cons on the example of models which are dedicated to the decision-making process of passenger transport logistics. The paper includes the analysis of two approaches: when input values are filled with the experts’ knowledge; when fuzzy expectations represented by output values are added to the point. These approaches fulfill the possibilities of triples of functions which are replaced with different combinations of t-/s-norms.

Keywords: Fuzzy petri net, intelligent computational techniques, knowledge representation, triangular norms.

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Authors: Rami A. Maher, Ibraheem K. Ibraheem

Abstract:

This work presents a comparison study between the state-space and polynomial methods for the design of the robust governor for load frequency control of steam turbine power systems. The robust governor is synthesized using the two approaches and the comparison is extended to include time and frequency domains performance, controller order, and uncertainty representation, weighting filters, optimality and sub-optimality. The obtained results are represented through tables and curves with reasons of similarities and dissimilarities.

Keywords: Robust control, load frequency control, steam turbine, H∞-norm, system uncertainty, load disturbance.

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Authors: F. Lemfeld, K. Frana

Abstract:

This article deals with numerical simulation of the floor heating convector in 3D. Numerical simulation is focused on cooling mode of the floor heating convector. Geometrical model represents section of the heat exchanger – two fins with the gap between, pipes are not involved. Two types of fin are examined – sinusoidal and angular shape with different fin spacing. Results of fin spacing in case of constant Reynolds number are presented. For the numerical simulation was used commercial software Ansys Fluent.

Keywords: fin spacing, cooling output, floor heating convector, numerical simulation.

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Authors: Ami Kim, Oubong Gwun, Juwhan Song

Abstract:

In this paper, we proposed the distribution of mesh normal vector direction as a feature descriptor of a 3D model. A normal vector shows the entire shape of a model well. The distribution of normal vectors was sampled in proportion to each polygon's area so that the information on the surface with less surface area may be less reflected on composing a feature descriptor in order to enhance retrieval performance. At the analysis result of ANMRR, the enhancement of approx. 12.4%~34.7% compared to the existing method has also been indicated.

Keywords: Interpolated Normal Vector, Feature Descriptor, 3DModel Retrieval.

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Authors: António L. Topa

Abstract:

A complete spectral representation for the electromagnetic field of planar multilayered waveguides inhomogeneously filled with omega media is presented. The problem of guided electromagnetic propagation is reduced to an eigenvalue equation related to a 2 ´ 2 matrix differential operator. Using the concept of adjoint waveguide, general bi-orthogonality relations for the hybrid modes (either from the discrete or from the continuous spectrum) are derived. For the special case of homogeneous layers the linear operator formalism is reduced to a simple 2 ´ 2 coupling matrix eigenvalue problem. Finally, as an example of application, the surface and the radiation modes of a grounded omega slab waveguide are analyzed.

Keywords: Metamaterials, linear operators, omega media, layered waveguide, orthogonality relations

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Authors: Anis Gharbi

Abstract:

This paper considers the problem of scheduling maintenance actions for identical aircraft gas turbine engines. Each one of the turbines consists of parts which frequently require replacement. A finite inventory of spare parts is available and all parts are ready for replacement at any time. The inventory consists of both new and refurbished parts. Hence, these parts have different field lives. The goal is to find a replacement part sequencing that maximizes the time that the aircraft will keep functioning before the inventory is replenished. The problem is formulated as an identical parallel machine scheduling problem where the minimum completion time has to be maximized. Two models have been developed. The first one is an optimization model which is based on a 0-1 linear programming formulation, while the second one is an approximate procedure which consists in decomposing the problem into several two-machine subproblems. Each subproblem is optimally solved using the first model. Both models have been implemented using Lingo and have been tested on two sets of randomly generated data with up to 150 parts and 10 turbines. Experimental results show that the optimization model is able to solve only instances with no more than 4 turbines, while the decomposition procedure often provides near-optimal solutions within a maximum CPU time of 3 seconds.

Keywords: Aircraft turbines, Scheduling, Identical parallel machines, 0-1 linear programming, Heuristic.

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Authors: Sang Wook Park, Jun Su Park, Byung Kwan Oh, Yousok Kim, Hyo Seon Park

Abstract:

This study suggests the estimation method of stress distribution for the beam structures based on TLS (Terrestrial Laser Scanning). The main components of method are the creation of the lattices of raw data from TLS to satisfy the suitable condition and application of CSSI (Cubic Smoothing Spline Interpolation) for estimating stress distribution. Estimation of stress distribution for the structural member or the whole structure is one of the important factors for safety evaluation of the structure. Existing sensors which include ESG (Electric strain gauge) and LVDT (Linear Variable Differential Transformer) can be categorized as contact type sensor which should be installed on the structural members and also there are various limitations such as the need of separate space where the network cables are installed and the difficulty of access for sensor installation in real buildings. To overcome these problems inherent in the contact type sensors, TLS system of LiDAR (light detection and ranging), which can measure the displacement of a target in a long range without the influence of surrounding environment and also get the whole shape of the structure, has been applied to the field of structural health monitoring. The important characteristic of TLS measuring is a formation of point clouds which has many points including the local coordinate. Point clouds are not linear distribution but dispersed shape. Thus, to analyze point clouds, the interpolation is needed vitally. Through formation of averaged lattices and CSSI for the raw data, the method which can estimate the displacement of simple beam was developed. Also, the developed method can be extended to calculate the strain and finally applicable to estimate a stress distribution of a structural member. To verify the validity of the method, the loading test on a simple beam was conducted and TLS measured it. Through a comparison of the estimated stress and reference stress, the validity of the method is confirmed.

Keywords: Structural health monitoring, terrestrial laser scanning, estimation of stress distribution, coordinate transformation, cubic smoothing spline interpolation.

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Authors: Hongzhi Wang, Jianzhong Li, Hong Gao

Abstract:

XML is an important standard of data exchange and representation. As a mature database system, using relational database to support XML data may bring some advantages. But storing XML in relational database has obvious redundancy that wastes disk space, bandwidth and disk I/O when querying XML data. For the efficiency of storage and query XML, it is necessary to use compressed XML data in relational database. In this paper, a compressed relational database technology supporting XML data is presented. Original relational storage structure is adaptive to XPath query process. The compression method keeps this feature. Besides traditional relational database techniques, additional query process technologies on compressed relations and for special structure for XML are presented. In this paper, technologies for XQuery process in compressed relational database are presented..

Keywords: XML, compression, query processing

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Authors: M. F. Zaiyadi, B. Baharudin

Abstract:

Text document categorization involves large amount of data or features. The high dimensionality of features is a troublesome and can affect the performance of the classification. Therefore, feature selection is strongly considered as one of the crucial part in text document categorization. Selecting the best features to represent documents can reduce the dimensionality of feature space hence increase the performance. There were many approaches has been implemented by various researchers to overcome this problem. This paper proposed a novel hybrid approach for feature selection in text document categorization based on Ant Colony Optimization (ACO) and Information Gain (IG). We also presented state-of-the-art algorithms by several other researchers.

Keywords: Ant colony optimization, feature selection, information gain, text categorization, text representation.

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Authors: Liew Yee Ping, Pang Ying Han, Lau Siong Hoe, Ooi Shih Yin, Housam Khalifa Bashier Babiker

Abstract:

In face recognition, feature extraction techniques attempts to search for appropriate representation of the data. However, when the feature dimension is larger than the samples size, it brings performance degradation. Hence, we propose a method called Normalization Discriminant Independent Component Analysis (NDICA). The input data will be regularized to obtain the most reliable features from the data and processed using Independent Component Analysis (ICA). The proposed method is evaluated on three face databases, Olivetti Research Ltd (ORL), Face Recognition Technology (FERET) and Face Recognition Grand Challenge (FRGC). NDICA showed it effectiveness compared with other unsupervised and supervised techniques.

Keywords: Face recognition, small sample size, regularization, independent component analysis.

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Authors: Srinivasa Reddy Mallampati, Byoung Ho Lee, Yoshiharu Mitoma, Simion Cristian

Abstract:

In recent years, environmental nanotechnology has risen to the forefront and the new properties and enhanced reactivates offered by nanomaterial may offer a new, low-cost paradigm to solving complex environmental pollution problems. This study assessed the synthesis and application of multi-functioned nano-size metallic calcium (nMC) composite for detoxification of hazardous inorganic (heavy metals (HMs)/organic chlorinated/brominated compound (CBCs) contaminants in automobile shredder residue (ASR). ASR residues ball milled with nMC composite can achieve about 90-100% of HMs immobilization and CBCs decomposition. The results highlight the low quantity of HMs leached from ASR residues after treatment with nMC, which was found to be lower than the standard regulatory limit for hazardous waste landfills. The use of nMC composite in a mechanochemical process to treat hazardous ASR (dry conditions) is a simple and innovative approach to remediate hazardous inorganic/organic cross-contaminates in ASR.

Keywords: Nano-sized metallic calcium, automobile shredder residue, organic/inorganic contaminants, immobilization, detoxification.

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Authors: H. Bouadi, M. Tadjine

Abstract:

In this paper; we are interested in dynamic modelling of quadrotor while taking into account the high-order nonholonomic constraints as well as the various physical phenomena, which can influence the dynamics of a flying structure. These permit us to introduce a new state-space representation and new control scheme. We present after the development and the synthesis of a stabilizing control laws design based on sliding mode in order to perform best tracking results. It ensures locally asymptotic stability and desired tracking trajectories. Nonlinear observer is then synthesized in order to estimate the unmeasured states and the effects of the external disturbances such as wind and noise. Finally simulation results are also provided in order to illustrate the performances of the proposed controllers.

Keywords: Dynamic modelling, nonholonomic constraints, sliding mode, nonlinear observer.

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Authors: Jutta Hämmerle-Uhl, Georg Penn, Gerhard Pötzelsberger, Andreas Uhl

Abstract:

Iris codes contain bits with different entropy. This work investigates different strategies to reduce the size of iris code templates with the aim of reducing storage requirements and computational demand in the matching process. Besides simple subsampling schemes, also a binary multi-resolution representation as used in the JBIG hierarchical coding mode is assessed. We find that iris code template size can be reduced significantly while maintaining recognition accuracy. Besides, we propose a two-stage identification approach, using small-sized iris code templates in a pre-selection stage, and full resolution templates for final identification, which shows promising recognition behaviour.

Keywords: Iris recognition, compact iris code, fast matching, best bits, pre-selection identification, two-stage identification.

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