Image Segmentation via Iterative Fuzzy Clustering Based on Local Space-Frequency Multi-Feature Coherence Criteria

Fuzzy set theory has recently attracted much attention in the field of image classification, image understanding and image processing. One of the major topics in fuzzy image processing is the image classification problem. This paper presents a fast and accurate iterative fuzzy clustering (I.F.C.) method dynamically adapted to the classification process. This is used for high performance fuzzy segmentation which forms the basis for reliable image understanding. The proposed fuzzy segmentation scheme examines the image connectivity in the space and frequency domains. The detected fuzzy features are combined via a block synthesis and local correlation algorithmic procedure. Some results showing that the performance of the proposed I.F.C./clustering method is superior from that of the standard fuzzy c-means method are provided.     

Estimation of daily traffic emissions in a South-European urban agglomeration during a workday. Evaluation of several "what if" scenarios

Detailed traffic data collected from seven major roads in the city of Athens, Greece are presented and analysed in this study. Vehicles are split into seven categories while vehicle speed is also recorded. Based on these data the emissions of five major pollutants (CO, Benzene, NO(X), PM(10) and VOCs) were calculated with the aid of the COPERT methodology and, based on these results, an Artificial Neural Network was also developed. The results of the two methodologies were compared and it was found that the differences were very small. The ANN model seems to be a reliable alternative to calculate road traffic emissions in a busy road environment. The results reflect the spatial and temporal distribution of the concentrations of the pollutants examined. Alternative "what if" scenarios of the fleet distribution were also applied by means of environmental policy. Since Athens experiences low air quality conditions the correct estimation of traffic emissions is crucial since they play a significant role in the design of an environmental abatement strategy.     

Human-and-Humanoid Postures Under External Disturbances: Modeling,Simulation, and Robustness. Part 2: Simulation and Robustness

The sophisticated method for mathematical modeling of humanoid robots formulated in Part 1 of this paper is applied here to the dynamic task of keeping a posture under disturbance, which is equally important to humans and humanoid robots. The idea of this work is to develop and realize a simulator tool for dynamic analysis of human-or-humanoid behavior under disturbances. To show the potentials and verify this tool, we comparatively analyze the robustness of some postures to external disturbance. At this stage of research we do not conduct real experiments with humans/humanoids but try to verify our simulation tool by relying on available experience. Therefore, the postures for comparison are taken from everyday life and from sports: upright standing, squat posture, and three karate postures. As the external disturbance we choose an impulse and a permanent force, both with variable direction and magnitude.     

Neural Structures Using the Eigenstates of a Quantum Harmonic Oscillator

The main result of the paper is the use of orthogonal Hermite polynomials as the basis functions of feedforward neural networks. The proposed neural networks have some interesting properties: (i) the basis functions are invariant under the Fourier transform, subject only to a change of scale, (ii) the basis functions are the eigenstates of the quantum harmonic oscillator, and stem from the solution of Schrödinger's diffusion equation. The proposed feed-forward neural networks demonstrate the particle-wave nature of information and can be used in nonparametric estimation. Possible applications of the proposed neural networks include function approximation, image processing and system modelling.     

Occlusion Culling Algorithms: A Comprehensive Survey

In this paper, occlusion culling techniques that appeared in the last decade are reviewed. Occlusion culling techniques are responsible for reducing the polygons rendered by the graphics hardware with the target of achieving real-time rendering. The various techniques are discussed in detail and a synopsis table with their main characteristics is given.     

Modeling of in situ monitored laser reflectance during MOCVD growth of HgCdTe

An effective way to in situ monitor the metalorganic chemical vapor deposition (MOCVD) of HgCdTe/CdTe/ZnTe on GaAs or GaAs/Si substrates is presented. Specular He-Ne laser reflectance was used to in situ monitor the growth rates, layer thickness, and morphology for each layer in the grown multilayer structure. In situ monitoring has enabled precise measurements of ZnTe nucleation and CdTe buffer layer thicknesses. Monitoring the constancy of reflectance during the thicker CdTe buffer growth where absorption in the CdTe reduces reflectance to just the surface component has led to optimum buffer growth ensuring good quality of subsequently grown HgCdTe. During the interdiffused multilayer process (IMP) HgCdTe growth, because multiple interfaces are present within the absorption length, a periodic reflectance signal is maintained throughout this growth cycle. A theoretical model was developed to extract IMP layer thicknesses from in situ recorded experimental data. For structures that required the growth of a larger band gap HgCdTe cap layer on top of a smaller band gap active layer, in situ monitored reflectance data allowed determination of alloy composition in the cap layer as well. Continuous monitoring of IMP parameters established the stability of growth conditions, translating into depth uniformity of the grown material, and allowed diagnosis of growth rate instabilities in terms of changes in the HgTe and CdTe parts of the IMP cycle. A unique advantage of in situ laser monitoring is the opportunity to perform “interactive” crystal growth, a development that is a key to real time MOCVD HgCdTe feedback growth control.     

Cryptanalysis of the Tillich�CZ��mor Hash Function

At CRYPTO ’94, Tillich and Zémor proposed a family of hash functions, based on computing a suitable matrix product in groups of the form SL₂(\mathbbF_2ⁿ)SL_{2}(\mathbb{F}_{2^{n}}). We show how to construct collisions between palindromic bit strings of length 2n+2 for Tillich and Zémor’s construction. The approach also yields collisions for related proposals by Petit et al. from ICECS ’08 and CT-RSA ’09.     

Quantitative determination of the distribution of free hydroxylic and carboxylic groups in unsaturated polyester and alkyd resins by 31P‐NMR spectroscopy

Quantitative ³¹P‐NMR spectroscopy is used to measure the hydroxyl and carboxyl content of some polyester resins (short‐ and long‐oil alkyds, polyols, polyesters) through derivatization of the —OH protons with 2‐chloro‐4,4,5,5‐tetramethyldioxaphospholane I. This methodology is shown to be superior to titration methods, since it can (a) discriminate between primary and secondary hydroxyl groups, (b) identify individual alcohols and acids present, (c) measure the amount of free fatty acids in oil‐modified alkyds, and (d) provide lower limits for the number‐averaged molecular weight of the resins and exact values for linear polyesters. A major advantage of the technique is that the NMR measurements are made on unmodified resins in their final product form supplied by the manufacturer. The information obtained is important for the characterization of the alkyd resins and affects drastically their physical properties and performance as products. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 83: 1635–1642, 2002