Unscented Transformation for Estimating the Lyapunov Exponents of Chaotic Time Series Corrupted by Random Noise

Many systems in the natural world exhibit chaos or non-linear behavior, the complexity of which is so great that they appear to be random. Identification of chaos in experimental data is essential for characterizing the system and for analyzing the predictability of the data under analysis. The Lyapunov exponents provide a quantitative measure of the sensitivity to initial conditions and are the most useful dynamical diagnostic for chaotic systems. However, it is difficult to accurately estimate the Lyapunov exponents of chaotic signals which are corrupted by a random noise. In this work, a method for estimation of Lyapunov exponents from noisy time series using unscented transformation is proposed. The proposed methodology was validated using time series obtained from known chaotic maps. In this paper, the objective of the work, the proposed methodology and validation results are discussed in detail.

Operation Stability Enhancement in Once-Through Micro Evaporators

Equipment miniaturisation offers several opportunities such as an increased surface-to-volume ratio and higher heat transfer coefficients. However, moving towards small-diameter channels demands extra attention to fouling, reliability and stable operation of the system. The present investigation explores possibilities to enhance the stability of the once-through micro evaporator by reducing its flow boiling induced pressure fluctuations. Experimental comparison shows that the measured reduction factor approaches a theoretically derived value. Pressure fluctuations are reduced by a factor of ten in the solid conical channel and a factor of 15 in the porous conical channel. This presumably leads to less backflow and therefore to a better flow control.

Design and Analysis of MEMS based Accelerometer for Automatic Detection of Railway Wheel Flat

This paper presents the modeling of a MEMS based accelerometer in order to detect the presence of a wheel flat in the railway vehicle. A haversine wheel flat is assigned to one wheel of a 5 DOF pitch plane vehicle model, which is coupled to a 3 layer track model. Based on the simulated acceleration response obtained from the vehicle-track model, an accelerometer is designed that meets all the requirements to detect the presence of a wheel flat. The proposed accelerometer can survive in a dynamic shocking environment with acceleration up to ±150g. The parameters of the accelerometer are calculated in order to achieve the required specifications using lumped element approximation and the results are used for initial design layout. A finite element analysis code (COMSOL) is used to perform simulations of the accelerometer under various operating conditions and to determine the optimum configuration. The simulated results are found within about 2% of the calculated values, which indicates the validity of lumped element approach. The stability of the accelerometer is also determined in the desired range of operation including the condition under shock.

A Survey of Various Algorithms for Vlsi Physical Design

Electronic Systems are the core of everyday lives. They form an integral part in financial networks, mass transit, telephone systems, power plants and personal computers. Electronic systems are increasingly based on complex VLSI (Very Large Scale Integration) integrated circuits. Initial electronic design automation is concerned with the design and production of VLSI systems. The next important step in creating a VLSI circuit is Physical Design. The input to the physical design is a logical representation of the system under design. The output of this step is the layout of a physical package that optimally or near optimally realizes the logical representation. Physical design problems are combinatorial in nature and of large problem sizes. Darwin observed that, as variations are introduced into a population with each new generation, the less-fit individuals tend to extinct in the competition of basic necessities. This survival of fittest principle leads to evolution in species. The objective of the Genetic Algorithms (GA) is to find an optimal solution to a problem .Since GA-s are heuristic procedures that can function as optimizers, they are not guaranteed to find the optimum, but are able to find acceptable solutions for a wide range of problems. This survey paper aims at a study on Efficient Algorithms for VLSI Physical design and observes the common traits of the superior contributions.

Internal Force State Recognition of Jiujiang Bridge Based on Cable Force-displacement Relationship

The nearly 21-year-old Jiujiang Bridge, which is suffering from uneven line shape, constant great downwarping of the main beam and cracking of the box girder, needs reinforcement and cable adjustment. It has undergone cable adjustment for twice with incomplete data. Therefore, the initial internal force state of the Jiujiang Bridge is identified as the key for the cable adjustment project. Based on parameter identification by means of static force test data, this paper suggests determining the initial internal force state of the cable-stayed bridge according to the cable force-displacement relationship parameter identification method. That is, upon measuring the displacement and the change in cable forces for twice, one can identify the parameters concerned by means of optimization. This method is applied to the cable adjustment, replacement and reinforcement project for the Jiujiang Bridge as a guidance for the cable adjustment and reinforcement project of the bridge.

From Separatism to Coalition: Variants in Language Politics and Leadership Pattern in Dravidian Movement

This paper describes the evolution of language politics and the part played by political leaders with reference to the Dravidian parties in Tamil Nadu. It explores the interesting evolution from separatism to coalition in sustaining the values of parliamentary democracy and federalism. It seems that the appropriation of language politics is fully ascribed to the DMK leadership under Annadurai and Karunanidhi. For them, the Tamil language is a self-determining power, a terrain of nationhood, and a perennial source of social and political powers. The DMK remains a symbol of Tamil nationalist party playing language politics in the interest of the Tamils. Though electoral alliances largely determine the success, the language politics still has significant space in the politics of Tamil Nadu. Ironically, DMK moves from the periphery to centre for getting national recognition for the Tamils as well as for its own maximization of power. The evolution can be seen in two major phases as: language politics for party building; and language politics for state building with three successive political processes, namely, language politics in the process of separatism, representative politics and coalition. The much pronounced Dravidian Movement is radical enough to democratize the party ideology to survive the spirit of parliamentary democracy. This has secured its own rewards in terms of political power. The political power provides the means to achieve the social and political goal of the political party. Language politics and leadership pattern actualized this trend though the movement is shifted from separatism to coalition.

Sloshing Control in Tilting Phases of the Pouring Process

We propose a control design scheme that aims to prevent undesirable liquid outpouring and suppress sloshing during the forward and backward tilting phases of the pouring process, for the case of liquid containers carried by manipulators. The proposed scheme combines a partial inverse dynamics controller with a PID controller, tuned with the use of a “metaheuristic" search algorithm. The “metaheuristic" search algorithm tunes the PID controller based on simulation results of the plant-s linearization around the operating point corresponding to the critical tilting angle, where outpouring initiates. Liquid motion is modeled using the well-known pendulumtype model. However, the proposed controller does not require measurements of the liquid-s motion within the tank.

Does Leisure Time Use Contribute to a Wage Increase of the Thai People?

This paper develops models to analyze the relationship between leisure time and wage change. Using Thailand-s Time Use Survey and Labor Force Survey data, the estimation of wage changes in response to leisure time change indicates that media receiving, personal care and social participation and volunteer activities are the ones that significantly raise hourly wages. Thus, the finding suggests the stimulation in time use for media access to enhance knowledge and productivity, personal care for attractiveness and healthiness in order to raise productivity, and social activities to develop connections for possible future opportunities including wage increase. These activities should be promoted for productive leisure time and for welfare improvement.

Object-Oriented Cognitive-Spatial Complexity Measures

Software maintenance and mainly software comprehension pose the largest costs in the software lifecycle. In order to assess the cost of software comprehension, various complexity measures have been proposed in the literature. This paper proposes new cognitive-spatial complexity measures, which combine the impact of spatial as well as architectural aspect of the software to compute the software complexity. The spatial aspect of the software complexity is taken into account using the lexical distances (in number of lines of code) between different program elements and the architectural aspect of the software complexity is taken into consideration using the cognitive weights of control structures present in control flow of the program. The proposed measures are evaluated using standard axiomatic frameworks and then, the proposed measures are compared with the corresponding existing cognitive complexity measures as well as the spatial complexity measures for object-oriented software. This study establishes that the proposed measures are better indicators of the cognitive effort required for software comprehension than the other existing complexity measures for object-oriented software.

A Four Architectures to Locate Mobile Users using Statistical Mapping of WLANs in Indoorand Outdoor Environments-Loids

These days wireless local area networks has become very popular, when the initial IEEE802.11 is the standard for providing wireless connectivity to automatic machinery, equipment and stations that require rapid deployment, which may be portable, handheld or which may be mounted on moving vehicles within a local area. IEEE802.11 Wireless local area network is a sharedmedium communication network that transmits information over wireless links for all IEEE802.11 stations in its transmission range to receive. When a user is moving from one location to another, how the other user knows about the required station inside WLAN. For that we designed and implemented a system to locate a mobile user inside the wireless local area network based on RSSI with the help of four specially designed architectures. These architectures are based on statistical or we can say manual configuration of mapping and radio map of indoor and outdoor location with the help of available Sniffer based and cluster based techniques. We found a better location of a mobile user in WLAN. We tested this work in indoor and outdoor environments with different locations with the help of Pamvotis, a simulator for WLAN.

Hand Gesture Recognition: Sign to Voice System (S2V)

Hand gesture is one of the typical methods used in sign language for non-verbal communication. It is most commonly used by people who have hearing or speech problems to communicate among themselves or with normal people. Various sign language systems have been developed by manufacturers around the globe but they are neither flexible nor cost-effective for the end users. This paper presents a system prototype that is able to automatically recognize sign language to help normal people to communicate more effectively with the hearing or speech impaired people. The Sign to Voice system prototype, S2V, was developed using Feed Forward Neural Network for two-sequence signs detection. Different sets of universal hand gestures were captured from video camera and utilized to train the neural network for classification purpose. The experimental results have shown that neural network has achieved satisfactory result for sign-to-voice translation.

Overviews of Rainwater Harvesting and Utilization in Thailand: Bangsaiy Municipality

In developing countries located in monsoon areas like Thailand where rainwater is currently of no value for urban dwellers due to easily access to piped water supply at each household, studies in rainwater harvesting for domestic use are of low interest. However it is needed to undertake research to find out appropriate rainwater harvesting systems particularly for small urban communities that are recently developed from a full rural structure to urban context. As a matter of fact, in such transitional period, relying on only common water resources is risky. With some specific economic settings, land use patterns, and historical and cultural context that dominate perceptions of water users in the study area, the level of service in this study may certainly be different from megacities or cities located in industrial zone. The overviews of some available technologies and background of rainwater harvesting including alternate resource are included in this paper. Among other sources of water supply, ground water use as the water resource of Thailand and also in the study area.

Voice Driven Applications in Non-stationary and Chaotic Environment

Automated operations based on voice commands will become more and more important in many applications, including robotics, maintenance operations, etc. However, voice command recognition rates drop quite a lot under non-stationary and chaotic noise environments. In this paper, we tried to significantly improve the speech recognition rates under non-stationary noise environments. First, 298 Navy acronyms have been selected for automatic speech recognition. Data sets were collected under 4 types of noisy environments: factory, buccaneer jet, babble noise in a canteen, and destroyer. Within each noisy environment, 4 levels (5 dB, 15 dB, 25 dB, and clean) of Signal-to-Noise Ratio (SNR) were introduced to corrupt the speech. Second, a new algorithm to estimate speech or no speech regions has been developed, implemented, and evaluated. Third, extensive simulations were carried out. It was found that the combination of the new algorithm, the proper selection of language model and a customized training of the speech recognizer based on clean speech yielded very high recognition rates, which are between 80% and 90% for the four different noisy conditions. Fourth, extensive comparative studies have also been carried out.

Basic Research for Distinguishing Small Retinal Hemorrhages from Dust Artifact by using Hue, Lightness, and Saturation Color Space

To distinguish small retinal hemorrhages in early diabetic retinopathy from dust artifacts, we analyzed hue, lightness, and saturation (HLS) color spaces. The fundus of 5 patients with diabetic retinopathy was photographed. For the initial experiment, we placed 4 different colored papers on the ceiling of a darkroom. Using each color, 10 fragments of house dust particles on a magnifier were photographed. The colored papers were removed, and 3 different colored light bulbs were suspended from the ceiling. Ten fragments of house dust particles on the camera-s object lens were photographed. We then constructed an experimental device that can photograph artificial eyes. Five fragments of house dust particles under the ocher fundus of the artificial eye were photographed. On analyzing HLS color space of the dust artifact, lightness and saturation were found to be highly sensitive. However, hue was not highly sensitive.

Improved Wavelet Neural Networks for Early Cancer Diagnosis Using Clustering Algorithms

Wavelet neural networks (WNNs) have emerged as a vital alternative to the vastly studied multilayer perceptrons (MLPs) since its first implementation. In this paper, we applied various clustering algorithms, namely, K-means (KM), Fuzzy C-means (FCM), symmetry-based K-means (SBKM), symmetry-based Fuzzy C-means (SBFCM) and modified point symmetry-based K-means (MPKM) clustering algorithms in choosing the translation parameter of a WNN. These modified WNNs are further applied to the heterogeneous cancer classification using benchmark microarray data and were compared against the conventional WNN with random initialization method. Experimental results showed that a WNN classifier with the MPKM algorithm is more precise than the conventional WNN as well as the WNNs with other clustering algorithms.

Application of Artificial Neural Network to Classification Surface Water Quality

Water quality is a subject of ongoing concern. Deterioration of water quality has initiated serious management efforts in many countries. This study endeavors to automatically classify water quality. The water quality classes are evaluated using 6 factor indices. These factors are pH value (pH), Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), Nitrate Nitrogen (NO3N), Ammonia Nitrogen (NH3N) and Total Coliform (TColiform). The methodology involves applying data mining techniques using multilayer perceptron (MLP) neural network models. The data consisted of 11 sites of canals in Dusit district in Bangkok, Thailand. The data is obtained from the Department of Drainage and Sewerage Bangkok Metropolitan Administration during 2007-2011. The results of multilayer perceptron neural network exhibit a high accuracy multilayer perception rate at 96.52% in classifying the water quality of Dusit district canal in Bangkok Subsequently, this encouraging result could be applied with plan and management source of water quality.

Thermal Stability and Crystallization Behaviour of Modified ABS/PP Nanocomposites

In this research work, poly (acrylonitrile-butadienestyrene)/ polypropylene (ABS/PP) blends were processed by melt compounding in a twin-screw extruder. Upgrading of the thermal characteristics of the obtained materials was attempted by the incorporation of organically modified montmorillonite (OMMT), as well as, by the addition of two types of compatibilizers; polypropylene grafted with maleic anhydride (PP-g-MAH) and ABS grafted with maleic anhydride (ABS-g-MAH). The effect of the above treatments was investigated separately and in combination. Increasing the PP content in ABS matrix seems to increase the thermal stability of their blend and the glass transition temperature (Tg) of SAN phase of ABS. From the other part, the addition of ABS to PP promotes the formation of its β-phase, which is maximum at 30 wt% ABS concentration, and increases the crystallization temperature (Tc) of PP. In addition, it increases the crystallization rate of PP.The β-phase of PP in ABS/PP blends is reduced by the addition of compatibilizers or/and organoclay reinforcement. The incorporation of compatibilizers increases the thermal stability of PP and reduces its melting (ΔΗm) and crystallization (ΔΗc) enthalpies. Furthermore it decreases slightly the Tgs of PP and SAN phases of ABS/PP blends. Regarding the storage modulus of the ABS/PP blends, it presents a change in their behavior at about 10°C and return to their initial behavior at ~110°C. The incorporation of OMMT to no compatibilized and compatibilized ABS/PP blends enhances their storage modulus.

Implementing an Adaptive Behavior for Spread Spectrum Watermarking Procedures

The advances in multimedia and networking technologies have created opportunities for Internet pirates, who can easily copy multimedia contents and illegally distribute them on the Internet, thus violating the legal rights of content owners. This paper describes how a simple and well-known watermarking procedure based on a spread spectrum method and a watermark recovery by correlation can be improved to effectively and adaptively protect MPEG-2 videos distributed on the Internet. In fact, the procedure, in its simplest form, is vulnerable to a variety of attacks. However, its security and robustness have been increased, and its behavior has been made adaptive with respect to the video terminals used to open the videos and the network transactions carried out to deliver them to buyers. In fact, such an adaptive behavior enables the proposed procedure to efficiently embed watermarks, and this characteristic makes the procedure well suited to be exploited in web contexts, where watermarks usually generated from fingerprinting codes have to be inserted into the distributed videos “on the fly", i.e. during the purchase web transactions.

Coupled Lateral-Torsional Free Vibrations Analysis of Laminated Composite Beam using Differential Quadrature Method

In this paper the Differential Quadrature Method (DQM) is employed to study the coupled lateral-torsional free vibration behavior of the laminated composite beams. In such structures due to the fiber orientations in various layers, the lateral displacement leads to a twisting moment. The coupling of lateral and torsional vibrations is modeled by the bending-twisting material coupling rigidity. In the present study, in addition to the material coupling, the effects of shear deformation and rotary inertia are taken into account in the definition of the potential and kinetic energies of the beam. The governing differential equations of motion which form a system of three coupled PDEs are solved numerically using DQ procedure under different boundary conditions consist of the combinations of simply, clamped, free and other end conditions. The resulting natural frequencies and mode shapes for cantilever beam are compared with similar results in the literature and good agreement is achieved.

Clustered Signatures for Modeling and Recognizing 3D Rigid Objects

This paper describes a probabilistic method for three-dimensional object recognition using a shared pool of surface signatures. This technique uses flatness, orientation, and convexity signatures that encode the surface of a free-form object into three discriminative vectors, and then creates a shared pool of data by clustering the signatures using a distance function. This method applies the Bayes-s rule for recognition process, and it is extensible to a large collection of three-dimensional objects.