Symmetries, Conservation Laws and Reduction of Wave and Gordon-type Equations on Riemannian Manifolds

Equations on curved manifolds display interesting properties in a number of ways. In particular, the symmetries and, therefore, the conservation laws reduce depending on how curved the manifold is. Of particular interest are the wave and Gordon-type equations; we study the symmetry properties and conservation laws of these equations on the Milne and Bianchi type III metrics. Properties of reduction procedures via symmetries, variational structures and conservation laws are more involved than on the well known flat (Minkowski) manifold.

Development of Storm Water Quality Improvement Strategy Plan for Local City Councils in Western Australia

The aim of this study was to develop a storm water quality improvement strategy plan (WQISP) which assists managers and decision makers of local city councils in enhancing their activities to improve regional water quality. City of Gosnells in Western Australia has been considered as a case study. The procedure on developing the WQISP consists of reviewing existing water quality data, identifying water quality issues in the study areas and developing a decision making tool for the officers, managers and decision makers. It was found that land use type is the main factor affecting the water quality. Therefore, activities, sources and pollutants related to different land use types including residential, industrial, agricultural and commercial are given high importance during the study. Semi-structured interviews were carried out with coordinators of different management sections of the regional councils in order to understand the associated management framework and issues. The issues identified from these interviews were used in preparing the decision making tool. Variables associated with the defined “value versus threat" decision making tool are obtained from the intensive literature review. The main recommendations provided for improvement of water quality in local city councils, include non-structural, structural and management controls and potential impacts of climate change.

An Ontology for Spatial Relevant Objects in a Location-aware System: Case Study: A Tourist Guide System

Location-aware computing is a type of pervasive computing that utilizes user-s location as a dominant factor for providing urban services and application-related usages. One of the important urban services is navigation instruction for wayfinders in a city especially when the user is a tourist. The services which are presented to the tourists should provide adapted location aware instructions. In order to achieve this goal, the main challenge is to find spatial relevant objects and location-dependent information. The aim of this paper is the development of a reusable location-aware model to handle spatial relevancy parameters in urban location-aware systems. In this way we utilized ontology as an approach which could manage spatial relevancy by defining a generic model. Our contribution is the introduction of an ontological model based on the directed interval algebra principles. Indeed, it is assumed that the basic elements of our ontology are the spatial intervals for the user and his/her related contexts. The relationships between them would model the spatial relevancy parameters. The implementation language for the model is OWLs, a web ontology language. The achieved results show that our proposed location-aware model and the application adaptation strategies provide appropriate services for the user.

Non-Overlapping Hierarchical Index Structure for Similarity Search

In order to accelerate the similarity search in highdimensional database, we propose a new hierarchical indexing method. It is composed of offline and online phases. Our contribution concerns both phases. In the offline phase, after gathering the whole of the data in clusters and constructing a hierarchical index, the main originality of our contribution consists to develop a method to construct bounding forms of clusters to avoid overlapping. For the online phase, our idea improves considerably performances of similarity search. However, for this second phase, we have also developed an adapted search algorithm. Our method baptized NOHIS (Non-Overlapping Hierarchical Index Structure) use the Principal Direction Divisive Partitioning (PDDP) as algorithm of clustering. The principle of the PDDP is to divide data recursively into two sub-clusters; division is done by using the hyper-plane orthogonal to the principal direction derived from the covariance matrix and passing through the centroid of the cluster to divide. Data of each two sub-clusters obtained are including by a minimum bounding rectangle (MBR). The two MBRs are directed according to the principal direction. Consequently, the nonoverlapping between the two forms is assured. Experiments use databases containing image descriptors. Results show that the proposed method outperforms sequential scan and SRtree in processing k-nearest neighbors.

Land Surface Temperature and Biophysical Factors in Urban Planning

Land surface temperature (LST) is an important parameter to study in urban climate. The understanding of the influence of biophysical factors could improve the establishment of modeling urban thermal landscape. It is well established that climate hold a great influence on the urban landscape. However, it has been recognize that climate has a low priority in urban planning process, due to the complex nature of its influence. This study will focus on the relatively cloud free Landsat Thematic Mapper image of the study area, acquired on the 2nd March 2006. Correlation analyses were conducted to identify the relationship of LST to the biophysical factors; vegetation indices, impervious surface, and albedo to investigate the variation of LST. We suggest that the results can be considered by the stackholders during decision-making process to create a cooler and comfortable environment in the urban landscape for city dwellers.

Equalities in a Variety of Multiple Algebras

The purpose of this research is to study the concepts of multiple Cartesian product, variety of multiple algebras and to present some examples. In the theory of multiple algebras, like other theories, deriving new things and concepts from the things and concepts available in the context is important. For example, the first were obtained from the quotient of a group modulo the equivalence relation defined by a subgroup of it. Gratzer showed that every multiple algebra can be obtained from the quotient of a universal algebra modulo a given equivalence relation. The purpose of this study is examination of multiple algebras and basic relations defined on them as well as introduction to some algebraic structures derived from multiple algebras. Among the structures obtained from multiple algebras, this article studies submultiple algebras, quotients of multiple algebras and the Cartesian product of multiple algebras.

A Real-Time Specific Weed Recognition System Using Statistical Methods

The identification and classification of weeds are of major technical and economical importance in the agricultural industry. To automate these activities, like in shape, color and texture, weed control system is feasible. The goal of this paper is to build a real-time, machine vision weed control system that can detect weed locations. In order to accomplish this objective, a real-time robotic system is developed to identify and locate outdoor plants using machine vision technology and pattern recognition. The algorithm is developed to classify images into broad and narrow class for real-time selective herbicide application. The developed algorithm has been tested on weeds at various locations, which have shown that the algorithm to be very effectiveness in weed identification. Further the results show a very reliable performance on weeds under varying field conditions. The analysis of the results shows over 90 percent classification accuracy over 140 sample images (broad and narrow) with 70 samples from each category of weeds.

Analytical Solutions of Three Dimensional Steady-State Heat Transfer in Rectangular Ribs

In order to obtain an accurate result of the heat transfer of the rib in the internal cooling Rectangular channel, using separation of variables, analytical solutions of three dimensional steady-state heat conduction in rectangular ribs are given by solving three dimensional steady-state function of the rectangular ribs. Therefore, we can get solution of three dimensional temperature field in the rib. Based on the solution, we can get how the Bi number affected on heat transfer. Furthermore, comparisons of the analytical and numerical results indicate agreement on temperature field in the rib.

Meandered Microstrip Open Circuited Stub with Bandstop Characteristic

This paper presents a microstrip meandered open circuited stub with bandstop characteristic. The proposed structure is designed on a high frequency laminate with dielectric constant of 4.0 and board thickness of 0.508 millimeters. The scattering parameters and electromagnetic field distributions at various frequencies are investigated by modeling the structure with three dimensional electromagnetic simulation tool. In order to describe the resonant and bandstop characteristic of the meandered open circuited stub, a Smith chart as well as electric field at various frequencies and phases is illustrated accordingly. The structure can be an alternative method in suppressing the harmonic response of a bandpass filter.

Proactive Detection of DDoS Attacks Utilizing k-NN Classifier in an Anti-DDos Framework

Distributed denial-of-service (DDoS) attacks pose a serious threat to network security. There have been a lot of methodologies and tools devised to detect DDoS attacks and reduce the damage they cause. Still, most of the methods cannot simultaneously achieve (1) efficient detection with a small number of false alarms and (2) real-time transfer of packets. Here, we introduce a method for proactive detection of DDoS attacks, by classifying the network status, to be utilized in the detection stage of the proposed anti-DDoS framework. Initially, we analyse the DDoS architecture and obtain details of its phases. Then, we investigate the procedures of DDoS attacks and select variables based on these features. Finally, we apply the k-nearest neighbour (k-NN) method to classify the network status into each phase of DDoS attack. The simulation result showed that each phase of the attack scenario is classified well and we could detect DDoS attack in the early stage.

Multi-objective Optimisation of Composite Laminates under Heat and Moisture Effects using a Hybrid Neuro-GA Algorithm

In this paper, the optimum weight and cost of a laminated composite plate is seeked, while it undergoes the heaviest load prior to a complete failure. Various failure criteria are defined for such structures in the literature. In this work, the Tsai-Hill theory is used as the failure criterion. The theory of analysis was based on the Classical Lamination Theory (CLT). A newly type of Genetic Algorithm (GA) as an optimization technique with a direct use of real variables was employed. Yet, since the optimization via GAs is a long process, and the major time is consumed through the analysis, Radial Basis Function Neural Networks (RBFNN) was employed in predicting the output from the analysis. Thus, the process of optimization will be carried out through a hybrid neuro-GA environment, and the procedure will be carried out until a predicted optimum solution is achieved.

On the Analysis of Localization Accuracy of Wireless Indoor Positioning Systems using Cramer's Rule

This paper presents an analysis of the localization accuracy of indoor positioning systems using Cramer-s rule via IEEE 802.15.4 wireless sensor networks. The objective is to study the impact of the methods used to convert the received signal strength into the distance that is used to compute the object location in the wireless indoor positioning system. Various methods were tested and the localization accuracy was analyzed. The experimental results show that the method based on the empirical data measured in the non line-of-sight (NLOS) environment yield the highest localization accuracy; with the minimum error distance less than 3 m.

Numerical Simulation of a Pressure Regulated Valve to Find Out the Characteristics of Passive Control Circuit

The objective of the present paper is a numerical analysis of the flow forces acting on spool surfaces of a pressure regulated valve. The transient, compressible and turbulent flow structures inside the valve are simulated using ANSYS FLUENT coupled with a special UDF. Here, valve inlet pressure is varied in a stepwise manner. For every value of inlet pressure, transient analysis leads to a quasi-static flow through the valve. Spool forces are calculated based on different pressures at inlet. From this information of spool forces, pressure characteristic of the passive control circuit has been derived.

Flow Modeling and Runner Design Optimization in Turgo Water Turbines

The incorporation of computational fluid dynamics in the design of modern hydraulic turbines appears to be necessary in order to improve their efficiency and cost-effectiveness beyond the traditional design practices. A numerical optimization methodology is developed and applied in the present work to a Turgo water turbine. The fluid is simulated by a Lagrangian mesh-free approach that can provide detailed information on the energy transfer and enhance the understanding of the complex, unsteady flow field, at very small computing cost. The runner blades are initially shaped according to hydrodynamics theory, and parameterized using Bezier polynomials and interpolation techniques. The use of a limited number of free design variables allows for various modifications of the standard blade shape, while stochastic optimization using evolutionary algorithms is implemented to find the best blade that maximizes the attainable hydraulic efficiency of the runner. The obtained optimal runner design achieves considerably higher efficiency than the standard one, and its numerically predicted performance is comparable to a real Turgo turbine, verifying the reliability and the prospects of the new methodology.

Direct Sequence Spread Spectrum Technique with Residue Number System

In this paper, a residue number arithmetic is used in direct sequence spread spectrum system, this system is evaluated and the bit error probability of this system is compared to that of non residue number system. The effect of channel bandwidth, PN sequences, multipath effect and modulation scheme are studied. A Matlab program is developed to measure the signal-to-noise ratio (SNR), and the bit error probability for the various schemes.

The Water Level Detection Algorithm Using the Accumulated Histogram with Band Pass Filter

In this paper, we propose the robust water level detection method based on the accumulated histogram under small changed image which is acquired from water level surveillance camera. In general surveillance system, this is detecting and recognizing invasion from searching area which is in big change on the sequential images. However, in case of a water level detection system, these general surveillance techniques are not suitable due to small change on the water surface. Therefore the algorithm introduces the accumulated histogram which is emphasizing change of water surface in sequential images. Accumulated histogram is based on the current image frame. The histogram is cumulating differences between previous images and current image. But, these differences are also appeared in the land region. The band pass filter is able to remove noises in the accumulated histogram Finally, this algorithm clearly separates water and land regions. After these works, the algorithm converts from the water level value on the image space to the real water level on the real space using calibration table. The detected water level is sent to the host computer with current image. To evaluate the proposed algorithm, we use test images from various situations.

Color Image Segmentation Using Kekre-s Algorithm for Vector Quantization

In this paper we propose segmentation approach based on Vector Quantization technique. Here we have used Kekre-s fast codebook generation algorithm for segmenting low-altitude aerial image. This is used as a preprocessing step to form segmented homogeneous regions. Further to merge adjacent regions color similarity and volume difference criteria is used. Experiments performed with real aerial images of varied nature demonstrate that this approach does not result in over segmentation or under segmentation. The vector quantization seems to give far better results as compared to conventional on-the-fly watershed algorithm.

Predicting and Mitigating Dredging DispersionImpact: A Case of Phuket Port, Thailand

Dredging activities inevitably cause sediment dispersion. In certain locations, where there are important ecological areas such as mangroves or coral reefs, carefully planning the dredging can significantly reduce negative impacts. This article utilizes the dredging at Phuket port, Thailand, as a case study to demonstrate how computer simulations can be helpful to protect existing coral reefs. A software package named MIKE21 was applied. Necessary information required by the simulations was gathered. After calibrating and verifying the model, various dredging scenario were simulated to predict spoil movement. The simulation results were used as guidance to setting up an environmental measure. Finally, the recommendation to dredge during flood tide with silt curtains installed was made.

A Comparison of Real Valued Transforms for Image Compression

In this paper we present simulation results for the application of a bandwidth efficient algorithm (mapping algorithm) to an image transmission system. This system considers three different real valued transforms to generate energy compact coefficients. First results are presented for gray scale and color image transmission in the absence of noise. It is seen that the system performs its best when discrete cosine transform is used. Also the performance of the system is dominated more by the size of the transform block rather than the number of coefficients transmitted or the number of bits used to represent each coefficient. Similar results are obtained in the presence of additive white Gaussian noise. The varying values of the bit error rate have very little or no impact on the performance of the algorithm. Optimum results are obtained for the system considering 8x8 transform block and by transmitting 15 coefficients from each block using 8 bits.

Fault Detection of Drinking Water Treatment Process Using PCA and Hotelling's T2 Chart

This paper deals with the application of Principal Component Analysis (PCA) and the Hotelling-s T2 Chart, using data collected from a drinking water treatment process. PCA is applied primarily for the dimensional reduction of the collected data. The Hotelling-s T2 control chart was used for the fault detection of the process. The data was taken from a United Utilities Multistage Water Treatment Works downloaded from an Integrated Program Management (IPM) dashboard system. The analysis of the results show that Multivariate Statistical Process Control (MSPC) techniques such as PCA, and control charts such as Hotelling-s T2, can be effectively applied for the early fault detection of continuous multivariable processes such as Drinking Water Treatment. The software package SIMCA-P was used to develop the MSPC models and Hotelling-s T2 Chart from the collected data.