Experimental Parallel Architecture for Rendering 3D Model into MPEG-4 Format

This paper will present the initial findings of a research into distributed computer rendering. The goal of the research is to create a distributed computer system capable of rendering a 3D model into an MPEG-4 stream. This paper outlines the initial design, software architecture and hardware setup for the system. Distributed computing means designing and implementing programs that run on two or more interconnected computing systems. Distributed computing is often used to speed up the rendering of graphical imaging. Distributed computing systems are used to generate images for movies, games and simulations. A topic of interest is the application of distributed computing to the MPEG-4 standard. During the course of the research, a distributed system will be created that can render a 3D model into an MPEG-4 stream. It is expected that applying distributed computing principals will speed up rendering, thus improving the usefulness and efficiency of the MPEG-4 standard

A Design of Supply Chain Management System with Flexible Planning Capability

In production planning (PP) periods with excess capacity and growing demand, the manufacturers have two options to use the excess capacity. First, it could do more changeovers and thus reduce lot sizes, inventories, and inventory costs. Second, it could produce in excess of demand in the period and build additional inventory that can be used to satisfy future demand increments, thus delaying the purchase of the next machine that is required to meet the growth in demand. In this study we propose an enhanced supply chain planning model with flexible planning capability. In addition, a 3D supply chain planning system is illustrated.

Multilayer Soft Tissue Continuum Model: Towards Realistic Simulation of Facial Expressions

A biophysically based multilayer continuum model of the facial soft tissue composite has been developed for simulating wrinkle formation. The deformed state of the soft tissue block was determined by solving large deformation mechanics equations using the Galerkin finite element method. The proposed soft tissue model is composed of four layers with distinct mechanical properties. These include stratum corneum, epidermal-dermal layer (living epidermis and dermis), subcutaneous tissue and the underlying muscle. All the layers were treated as non-linear, isotropic Mooney Rivlin materials. Contraction of muscle fibres was approximated using a steady-state relationship between the fibre extension ratio, intracellular calcium concentration and active stress in the fibre direction. Several variations of the model parameters (stiffness and thickness of epidermal-dermal layer, thickness of subcutaneous tissue layer) have been considered.

Efficient Mean Shift Clustering Using Exponential Integral Kernels

This paper presents a highly efficient algorithm for detecting and tracking humans and objects in video surveillance sequences. Mean shift clustering is applied on backgrounddifferenced image sequences. For efficiency, all calculations are performed on integral images. Novel corresponding exponential integral kernels are introduced to allow the application of nonuniform kernels for clustering, which dramatically increases robustness without giving up the efficiency of the integral data structures. Experimental results demonstrating the power of this approach are presented.

A New Voting Approach to Texture Defect Detection Based on Multiresolutional Decomposition

Wavelets have provided the researchers with significant positive results, by entering the texture defect detection domain. The weak point of wavelets is that they are one-dimensional by nature so they are not efficient enough to describe and analyze two-dimensional functions. In this paper we present a new method to detect the defect of texture images by using curvelet transform. Simulation results of the proposed method on a set of standard texture images confirm its correctness. Comparing the obtained results indicates the ability of curvelet transform in describing discontinuity in two-dimensional functions compared to wavelet transform

Dissertation by Portfolio - A Break from Traditional Approaches

Much has been written about the difficulties students have with producing traditional dissertations. This includes both native English speakers (L1) and students with English as a second language (L2). The main emphasis of these papers has been on the structure of the dissertation, but in all cases, even when electronic versions are discussed, the dissertation is still in what most would regard as a traditional written form. Master of Science Degrees in computing disciplines require students to gain technical proficiency and apply their knowledge to a range of scenarios. The basis of this paper is that if a dissertation is a means of showing that such a student has met the criteria for a pass, which should be based on the learning outcomes of the dissertation module, does meeting those outcomes require a student to demonstrate their skills in a solely text based form, particularly in a highly technical research project? Could it be possible for a student to produce a series of related artifacts which form a cohesive package that meets the learning out comes of the dissertation?

Analysis of Precipitation Time Series of Urban Centers of Northeastern Brazil using Wavelet Transform

The urban centers within northeastern Brazil are mainly influenced by the intense rainfalls, which can occur after long periods of drought, when flood events can be observed during such events. Thus, this paper aims to study the rainfall frequencies in such region through the wavelet transform. An application of wavelet analysis is done with long time series of the total monthly rainfall amount at the capital cities of northeastern Brazil. The main frequency components in the time series are studied by the global wavelet spectrum and the modulation in separated periodicity bands were done in order to extract additional information, e.g., the 8 and 16 months band was examined by an average of all scales, giving a measure of the average annual variance versus time, where the periods with low or high variance could be identified. The important increases were identified in the average variance for some periods, e.g. 1947 to 1952 at Teresina city, which can be considered as high wet periods. Although, the precipitation in those sites showed similar global wavelet spectra, the wavelet spectra revealed particular features. This study can be considered an important tool for time series analysis, which can help the studies concerning flood control, mainly when they are applied together with rainfall-runoff simulations.

Analyzing Multi-Labeled Data Based on the Roll of a Concept against a Semantic Range

Classifying data hierarchically is an efficient approach to analyze data. Data is usually classified into multiple categories, or annotated with a set of labels. To analyze multi-labeled data, such data must be specified by giving a set of labels as a semantic range. There are some certain purposes to analyze data. This paper shows which multi-labeled data should be the target to be analyzed for those purposes, and discusses the role of a label against a set of labels by investigating the change when a label is added to the set of labels. These discussions give the methods for the advanced analysis of multi-labeled data, which are based on the role of a label against a semantic range.

Extracting Tongue Shape Dynamics from Magnetic Resonance Image Sequences

An important problem in speech research is the automatic extraction of information about the shape and dimensions of the vocal tract during real-time speech production. We have previously developed Southampton dynamic magnetic resonance imaging (SDMRI) as an approach to the solution of this problem.However, the SDMRI images are very noisy so that shape extraction is a major challenge. In this paper, we address the problem of tongue shape extraction, which poses difficulties because this is a highly deforming non-parametric shape. We show that combining active shape models with the dynamic Hough transform allows the tongue shape to be reliably tracked in the image sequence.

Filteristic Soft Lattice Implication Algebras

Applying the idea of soft set theory to lattice implication algebras, the novel concept of (implicative) filteristic soft lattice implication algebras which related to (implicative) filter(for short, (IF-)F-soft lattice implication algebras) are introduced. Basic properties of (IF-)F-soft lattice implication algebras are derived. Two kinds of fuzzy filters (i.e.(2, 2 _qk)((2, 2 _ qk))-fuzzy (implicative) filter) of L are introduced, which are generalizations of fuzzy (implicative) filters. Some characterizations for a soft set to be a (IF-)F-soft lattice implication algebra are provided. Analogously, this idea can be used in other types of filteristic lattice implication algebras (such as fantastic (positive implicative) filteristic soft lattice implication algebras).

Effect of Dry Cutting on Force and Tool Life When Machining Aerospace Material

Cutting fluids, usually in the form of a liquid, are applied to the chip formation zone in order to improve the cutting conditions. Cutting fluid can be expensive and represents a biological and environmental hazard that requires proper recycling and disposal, thus adding to the cost of the machining operation. For these reasons dry cutting or dry machining has become an increasingly important approach; in dry machining no coolant or lubricant is used. This paper discussed the effect of the dry cutting on cutting force and tool life when machining aerospace materials (Haynes 242) with using two different coated carbide cutting tools (TiAlN and TiN/MT-TiCN/TiN). Response surface method (RSM) was used to minimize the number of experiments. ParTiAlN Swarm Optimisation (PSO) models were developed to optimize the machining parameters (cutting speed, federate and axial depth) and obtain the optimum cutting force and tool life. It observed that carbide cutting tool coated with TiAlN performed better in dry cutting compared with TiN/MT-TiCN/TiN. On other hand, TiAlN performed more superior with using of 100 % water soluble coolant. Due to the high temperature produced by aerospace materials, the cutting tool still required lubricant to sustain the heat transfer from the workpiece.

A Neuro Adaptive Control Strategy for Movable Power Source of Proton Exchange Membrane Fuel Cell Using Wavelets

Movable power sources of proton exchange membrane fuel cells (PEMFC) are the important research done in the current fuel cells (FC) field. The PEMFC system control influences the cell performance greatly and it is a control system for industrial complex problems, due to the imprecision, uncertainty and partial truth and intrinsic nonlinear characteristics of PEMFCs. In this paper an adaptive PI control strategy using neural network adaptive Morlet wavelet for control is proposed. It is based on a single layer feed forward neural networks with hidden nodes of adaptive morlet wavelet functions controller and an infinite impulse response (IIR) recurrent structure. The IIR is combined by cascading to the network to provide double local structure resulting in improving speed of learning. The proposed method is applied to a typical 1 KW PEMFC system and the results show the proposed method has more accuracy against to MLP (Multi Layer Perceptron) method.

Using Emotional Learning in Rescue Simulation Environment

RoboCup Rescue simulation as a large-scale Multi agent system (MAS) is one of the challenging environments for keeping coordination between agents to achieve the objectives despite sensing and communication limitations. The dynamicity of the environment and intensive dependency between actions of different kinds of agents make the problem more complex. This point encouraged us to use learning-based methods to adapt our decision making to different situations. Our approach is utilizing reinforcement leaning. Using learning in rescue simulation is one of the current ways which has been the subject of several researches in recent years. In this paper we present an innovative learning method implemented for Police Force (PF) Agent. This method can cope with the main difficulties that exist in other learning approaches. Different methods used in the literature have been examined. Their drawbacks and possible improvements have led us to the method proposed in this paper which is fast and accurate. The Brain Emotional Learning Based Intelligent Controller (BELBIC) is our solution for learning in this environment. BELBIC is a physiologically motivated approach based on a computational model of amygdale and limbic system. The paper presents the results obtained by the proposed approach, showing the power of BELBIC as a decision making tool in complex and dynamic situation.

Auto Tuning of PID Controller for MIMO Processes

One of the most basic functions of control engineers is tuning of controllers. There are always several process loops in the plant necessitate of tuning. The auto tuned Proportional Integral Derivative (PID) Controllers are designed for applications where large load changes are expected or the need for extreme accuracy and fast response time exists. The algorithm presented in this paper is used for the tuning PID controller to obtain its parameters with a minimum computing complexity. It requires continuous analysis of variation in few parameters, and let the program to do the plant test and calculate the controller parameters to adjust and optimize the variables for the best performance. The algorithm developed needs less time as compared to a normal step response test for continuous tuning of the PID through gain scheduling.

Analysis of Knowledge Management Trend by Bibliometric Approach

The analysis is mainly concentrating on the knowledge management literatures productivity trend which subjects as “knowledge management" in SSCI database. The purpose what the analysis will propose is to summarize the trend information for knowledge management researchers since core knowledge will be concentrated in core categories. The result indicated that the literature productivity which topic as “knowledge management" is still increasing extremely and will demonstrate the trend by different categories including author, country/territory, institution name, document type, language, publication year, and subject area. Focus on the right categories, you will catch the core research information. This implies that the phenomenon "success breeds success" is more common in higher quality publications.

Distillation Monitoring and Control using LabVIEW and SIMULINK Tools

LabVIEW and SIMULINK are two most widely used graphical programming environments for designing digital signal processing and control systems. Unlike conventional text-based programming languages such as C, Cµ and MATLAB, graphical programming involves block-based code developments, allowing a more efficient mechanism to build and analyze control systems. In this paper a LabVIEW environment has been employed as a graphical user interface for monitoring the operation of a controlled distillation column, by visualizing both the closed loop performance and the user selected control conditions, while the column dynamics has been modeled under the SIMULINK environment. This tool has been applied to the PID based decoupled control of a binary distillation column. By means of such integrated environments the control designer is able to monitor and control the plant behavior and optimize the response when both, the quality improvement of distillation products and the operation efficiency tasks, are considered.

Computer Models of the Vestibular Head Tilt Response, and Their Relationship to EVestG and Meniere's Disease

This paper attempts to explain response components of Electrovestibulography (EVestG) using a computer simulation of a three-canal model of the vestibular system. EVestG is a potentially new diagnostic method for Meniere's disease. EVestG is a variant of Electrocochleography (ECOG), which has been used as a standard method for diagnosing Meniere's disease - it can be used to measure the SP/AP ratio, where an SP/AP ratio greater than 0.4-0.5 is indicative of Meniere-s Disease. In EVestG, an applied head tilt replaces the acoustic stimulus of ECOG. The EVestG output is also an SP/AP type plot, where SP is the summing potential, and AP is the action potential amplitude. AP is thought of as being proportional to the size of a population of afferents in an excitatory neural firing state. A simulation of the fluid volume displacement in the vestibular labyrinth in response to various types of head tilts (ipsilateral, backwards and horizontal rotation) was performed, and a simple neural model based on these simulations developed. The simple neural model shows that the change in firing rate of the utricle is much larger in magnitude than the change in firing rates of all three semi-circular canals following a head tilt (except in a horizontal rotation). The data suggests that the change in utricular firing rate is a minimum 2-3 orders of magnitude larger than changes in firing rates of the canals during ipsilateral/backward tilts. Based on these results, the neural response recorded by the electrode in our EVestG recordings is expected to be dominated by the utricle in ipsilateral/backward tilts (It is important to note that the effect of the saccule and efferent signals were not taken into account in this model). If the utricle response dominates the EVestG recordings as the modeling results suggest, then EVestG has the potential to diagnose utricular hair cell damage due to a viral infection (which has been cited as one possible cause of Meniere's Disease).

Evolutionary Search Techniques to Solve Set Covering Problems

Set covering problem is a classical problem in computer science and complexity theory. It has many applications, such as airline crew scheduling problem, facilities location problem, vehicle routing, assignment problem, etc. In this paper, three different techniques are applied to solve set covering problem. Firstly, a mathematical model of set covering problem is introduced and solved by using optimization solver, LINGO. Secondly, the Genetic Algorithm Toolbox available in MATLAB is used to solve set covering problem. And lastly, an ant colony optimization method is programmed in MATLAB programming language. Results obtained from these methods are presented in tables. In order to assess the performance of the techniques used in this project, the benchmark problems available in open literature are used.

A Step-wise Zoom Technique for Exploring Image-based Virtual Reality Applications

Existing image-based virtual reality applications allow users to view image-based 3D virtual environment in a more interactive manner. User could “walkthrough"; looks left, right, up and down and even zoom into objects in these virtual worlds of images. However what the user sees during a “zoom in" is just a close-up view of the same image which was taken from a distant. Thus, this does not give the user an accurate view of the object from the actual distance. In this paper, a simple technique for zooming in an object in a virtual scene is presented. The technique is based on the 'hotspot' concept in existing application. Instead of navigation between two different locations, the hotspots are used to focus into an object in the scene. For each object, several hotspots are created. A different picture is taken for each hotspot. Each consecutive hotspot created will take the user closer to the object. This will provide the user with a correct of view of the object based on his proximity to the object. Implementation issues and the relevance of this technique in potential application areas are highlighted.

GIS-based Approach for Land-Use Analysis: A Case Study

Geographical Information Systems are an integral part of planning in modern technical systems. Nowadays referred to as Spatial Decision Support Systems, as they allow synergy database management systems and models within a single user interface machine and they are important tools in spatial design for evaluating policies and programs at all levels of administration. This work refers to the creation of a Geographical Information System in the context of a broader research in the area of influence of an under construction station of the new metro in the Greek city of Thessaloniki, which included statistical and multivariate data analysis and diagrammatic representation, mapping and interpretation of the results.