Night-Time Traffic Light Detection Based On SVM with Geometric Moment Features

This paper presents an effective traffic lights detection method at the night-time. First, candidate blobs of traffic lights are extracted from RGB color image. Input image is represented on the dominant color domain by using color transform proposed by Ruta, then red and green color dominant regions are selected as candidates. After candidate blob selection, we carry out shape filter for noise reduction using information of blobs such as length, area, area of boundary box, etc. A multi-class classifier based on SVM (Support Vector Machine) applies into the candidates. Three kinds of features are used. We use basic features such as blob width, height, center coordinate, area, area of blob. Bright based stochastic features are also used. In particular, geometric based moment-s values between candidate region and adjacent region are proposed and used to improve the detection performance. The proposed system is implemented on Intel Core CPU with 2.80 GHz and 4 GB RAM and tested with the urban and rural road videos. Through the test, we show that the proposed method using PF, BMF, and GMF reaches up to 93 % of detection rate with computation time of in average 15 ms/frame.

Fatty Acids Composition of Elk, Deer, Roe Deer and Wild Boar Meat Hunted in Latvia

A game animals – elk (Alces alces), deer (Cervus elaphus), roe deer (Capreolus capreolus) or wild boar (Sus scrofa scrofa) - every autumn and winter period provide an excellent investment, diversification of many consumer meals. In last years consumption and assortiment of game meat products significantly increase. Investigations about biochemical composition of game meat are not very much. The meat of wild animals is more favourable for human health because it has lower saturated fatty acids content, but higher content of protein. Therefore the aim of investigations was to compare biochemical composition of ungulates obtained in Latvia.Investigations were carried out in wild animals different regions of Latvia. In the studied samples protein, intramuscular fat, fatty acids and cholesterol were determined. The biochemical analysis of 54 samples were done. Results of analysis showed that protein content 22.36 – 22.92% of all types of meat samples is not different statistically, significantly lower fat content 1.33 ± 0.88% had elk meat samples and 1.59 ± 0.59% roe deer samples. Content of cholesterol was various 64.41 – 95.07% in the ruminant meat samples of different species. From the dietetic point of view the best composition of fatty acids has meat samples of roe deer.

Hybrid Coding for Animated Polygonal Meshes

A new hybrid coding method for compressing animated polygonal meshes is presented. This paper assumes the simplistic representation of the geometric data: a temporal sequence of polygonal meshes for each discrete frame of the animated sequence. The method utilizes a delta coding and an octree-based method. In this hybrid method, both the octree approach and the delta coding approach are applied to each single frame in the animation sequence in parallel. The approach that generates the smaller encoded file size is chosen to encode the current frame. Given the same quality requirement, the hybrid coding method can achieve much higher compression ratio than the octree-only method or the delta-only method. The hybrid approach can represent 3D animated sequences with higher compression factors while maintaining reasonable quality. It is easy to implement and have a low cost encoding process and a fast decoding process, which make it a better choice for real time application.

Robust Power System Stabilizer Design Using Particle Swarm Optimization Technique

Power system stabilizers (PSS) are now routinely used in the industry to damp out power system oscillations. In this paper, particle swarm optimization (PSO) technique is applied to design a robust power system stabilizer (PSS). The design problem of the proposed controller is formulated as an optimization problem and PSO is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. The non-linear simulation results are presented under wide range of operating conditions; disturbances at different locations as well as for various fault clearing sequences to show the effectiveness and robustness of the proposed controller and their ability to provide efficient damping of low frequency oscillations. Further, all the simulations results are compared with a conventionally designed power system stabilizer to show the superiority of the proposed design approach.

EEG Indices to Time-On-Task Effects and to a Workload Manipulation (Cueing)

The aim of this study was to evaluate the sensitivity of a range of EEG indices to time-on-task effects and to a workload manipulation (cueing), during performance of a resource-limited vigilance task. Effects of task period and cueing on performance and subjective state response were consistent with previous vigilance studies and with resource theory. Two EEG indices – the Task Load Index (TLI) and global lower frequency (LF) alpha power – showed effects of task period and cueing similar to those seen with correct detections. Across four successive task periods, the TLI declined and LF alpha power increased. Cueing increased TLI and decreased LF alpha. Other indices – the Engagement Index (EI), frontal theta and upper frequency (UF) alpha failed to show these effects. However, EI and frontal theta were sensitive to interactive effects of task period and cueing, which may correspond to a stronger anxiety response to the uncued task.

Mathematical Modeling of Machining Parameters in Electrical Discharge Machining of FW4 Welded Steel

FW4 is a newly developed hot die material widely used in Forging Dies manufacturing. The right selection of the machining conditions is one of the most important aspects to take into consideration in the Electrical Discharge Machining (EDM) of FW4. In this paper an attempt has been made to develop mathematical models for relating the Material Removal Rate (MRR), Tool Wear Ratio (TWR) and surface roughness (Ra) to machining parameters (current, pulse-on time and voltage). Furthermore, a study was carried out to analyze the effects of machining parameters in respect of listed technological characteristics. The results of analysis of variance (ANOVA) indicate that the proposed mathematical models, can adequately describe the performance within the limits of the factors being studied.

Simulation and Optimization of Mechanisms made of Micro-molded Components

The Institute of Product Development is dealing with the development, design and dimensioning of micro components and systems as a member of the Collaborative Research Centre 499 “Design, Production and Quality Assurance of Molded micro components made of Metallic and Ceramic Materials". Because of technological restrictions in the miniaturization of conventional manufacturing techniques, shape and material deviations cannot be scaled down in the same proportion as the micro parts, rendering components with relatively wide tolerance fields. Systems that include such components should be designed with this particularity in mind, often requiring large clearance. On the end, the output of such systems results variable and prone to dynamical instability. To save production time and resources, every study of these effects should happen early in the product development process and base on computer simulation to avoid costly prototypes. A suitable method is proposed here and exemplary applied to a micro technology demonstrator developed by the CRC499. It consists of a one stage planetary gear train in a sun-planet-ring configuration, with input through the sun gear and output through the carrier. The simulation procedure relies on ordinary Multi Body Simulation methods and subsequently adds other techniques to further investigate details of the system-s behavior and to predict its response. The selection of the relevant parameters and output functions followed the engineering standards for regular sized gear trains. The first step is to quantify the variability and to reveal the most critical points of the system, performed through a whole-mechanism Sensitivity Analysis. Due to the lack of previous knowledge about the system-s behavior, different DOE methods involving small and large amount of experiments were selected to perform the SA. In this particular case the parameter space can be divided into two well defined groups, one of them containing the gear-s profile information and the other the components- spatial location. This has been exploited to explore the different DOE techniques more promptly. A reduced set of parameters is derived for further investigation and to feed the final optimization process, whether as optimization parameters or as external perturbation collective. The 10 most relevant perturbation factors and 4 to 6 prospective variable parameters are considered in a new, simplified model. All of the parameters are affected by the mentioned production variability. The objective functions of interest are based on scalar output-s variability measures, so the problem becomes an optimization under robustness and reliability constrains. The study shows an initial step on the development path of a method to design and optimize complex micro mechanisms composed of wide tolerated elements accounting for the robustness and reliability of the systems- output.

Development of an Avionics System for Flight Data Collection of an UAV Helicopter

In this present work, the development of an avionics system for flight data collection of a Raptor 30 V2 is carried out. For the data acquisition both onground and onboard avionics systems are developed for testing of a small-scale Unmanned Aerial Vehicle (UAV) helicopter. The onboard avionics record the helicopter state outputs namely accelerations, angular rates and Euler angles, in real time, and the on ground avionics system record the inputs given to the radio controlled helicopter through a transmitter, in real time. The avionic systems are designed and developed taking into consideration low weight, small size, anti-vibration, low power consumption, and easy interfacing. To mitigate the medium frequency vibrations embedded on the UAV helicopter during flight, a damper is designed and its performance is evaluated. A number of flight tests are carried out and the data obtained is then analyzed for accuracy and repeatability and conclusions are inferred.

Solution of Density Dependent Nonlinear Reaction-Diffusion Equation Using Differential Quadrature Method

In this study, the density dependent nonlinear reactiondiffusion equation, which arises in the insect dispersal models, is solved using the combined application of differential quadrature method(DQM) and implicit Euler method. The polynomial based DQM is used to discretize the spatial derivatives of the problem. The resulting time-dependent nonlinear system of ordinary differential equations(ODE-s) is solved by using implicit Euler method. The computations are carried out for a Cauchy problem defined by a onedimensional density dependent nonlinear reaction-diffusion equation which has an exact solution. The DQM solution is found to be in a very good agreement with the exact solution in terms of maximum absolute error. The DQM solution exhibits superior accuracy at large time levels tending to steady-state. Furthermore, using an implicit method in the solution procedure leads to stable solutions and larger time steps could be used.

An Intelligent Cascaded Fuzzy Logic Based Controller for Controlling the Room Temperature in Hydronic Heating System

Heating systems are a necessity for regions which brace extreme cold weather throughout the year. To maintain a comfortable temperature inside a given place, heating systems making use of- Hydronic boilers- are used. The principle of a single pipe system serves as a base for their working. It is mandatory for these heating systems to control the room temperature, thus maintaining a warm environment. In this paper, the concept of regulation of the room temperature over a wide range is established by using an Adaptive Fuzzy Controller (AFC). This fuzzy controller automatically detects the changes in the outside temperatures and correspondingly maintains the inside temperature to a palatial value. Two separate AFC's are put to use to carry out this function: one to determine the quantity of heat needed to reach the prospective temperature required and to set the desired temperature; the other to control the position of the valve, which is directly proportional to the error between the present room temperature and the user desired temperature. The fuzzy logic controls the position of the valve as per the requirement of the heat. The amount by which the valve opens or closes is controlled by 5 knob positions, which vary from minimum to maximum, thereby regulating the amount of heat flowing through the valve. For the given test system data, different de-fuzzifier methods have been implemented and the results are compared. In order to validate the effectiveness of the proposed approach, a fuzzy controller has been designed by obtaining a test data from a real time system. The simulations are performed in MATLAB and are verified with standard system data. The proposed approach can be implemented for real time applications.

Augmentation Opportunity of Transmission Control Protocol Performance in Wireless Networks and Cellular Systems

The advancement in wireless technology with the wide use of mobile devices have drawn the attention of the research and technological communities towards wireless environments, such as Wireless Local Area Networks (WLANs), Wireless Wide Area Networks (WWANs), and mobile systems and ad-hoc networks. Unfortunately, wired and wireless networks are expressively different in terms of link reliability, bandwidth, and time of propagation delay and by adapting new solutions for these enhanced telecommunications, superior quality, efficiency, and opportunities will be provided where wireless communications were otherwise unfeasible. Some researchers define 4G as a significant improvement of 3G, where current cellular network’s issues will be solved and data transfer will play a more significant role. For others, 4G unifies cellular and wireless local area networks, and introduces new routing techniques, efficient solutions for sharing dedicated frequency bands, and an increased mobility and bandwidth capacity. This paper discusses the possible solutions and enhancements probabilities that proposed to improve the performance of Transmission Control Protocol (TCP) over different wireless networks and also the paper investigated each approach in term of advantages and disadvantages.

Fractal Analysis on Human Colonic Pressure Activities based on the Box-counting Method

The colonic tissue is a complicated dynamic system and the colonic activities it generates are composed of irregular segmental waves, which are referred to as erratic fluctuations or spikes. They are also highly irregular with subunit fractal structure. The traditional time-frequency domain statistics like the averaged amplitude, the motility index and the power spectrum, etc. are insufficient to describe such fluctuations. Thus the fractal box-counting dimension is proposed and the fractal scaling behaviors of the human colonic pressure activities under the physiological conditions are studied. It is shown that the dimension of the resting activity is smaller than that of the normal one, whereas the clipped version, which corresponds to the activity of the constipation patient, shows with higher fractal dimension. It may indicate a practical application to assess the colonic motility, which is often indicated by the colonic pressure activity.

Information Delivery and Advanced Traffic Information Systems in Istanbul

In this paper, we focused primarily on Istanbul data that is gathered by using intelligent transportation systems (ITS), and considered the developments in traffic information delivery and future applications that are being planned for implementation. Since traffic congestion is increasing and travel times are becoming less consistent and less predictable, traffic information delivery has become a critical issue. Considering the fuel consumption and wasted time in traffic, advanced traffic information systems are becoming increasingly valuable which enables travelers to plan their trips more accurately and easily.

Real-time ROI Acquisition for Unsupervised and Touch-less Palmprint

In this paper we proposed a novel method to acquire the ROI (Region of interest) of unsupervised and touch-less palmprint captured from a web camera in real-time. We use Viola-Jones approach and skin model to get the target area in real time. Then an innovative course-to-fine approach to detect the key points on the hand is described. A new algorithm is used to find the candidate key points coarsely and quickly. In finely stage, we verify the hand key points with the shape context descriptor. To make the user much comfortable, it can process the hand image with different poses, even the hand is closed. Experiments show promising result by using the proposed method in various conditions.

Bridging the Gap Between CBR and VBR for H264 Standard

This paper provides a flexible way of controlling Variable-Bit-Rate (VBR) of compressed digital video, applicable to the new H264 video compression standard. The entire video sequence is assessed in advance and the quantisation level is then set such that bit rate (and thus the frame rate) remains within predetermined limits compatible with the bandwidth of the transmission system and the capabilities of the remote end, while at the same time providing constant quality similar to VBR encoding. A process for avoiding buffer starvation by selectively eliminating frames from the encoded output at times when the frame rate is slow (large number of bits per frame) will be also described. Finally, the problem of buffer overflow will be solved by selectively eliminating frames from the received input to the decoder. The decoder detects the omission of the frames and resynchronizes the transmission by monitoring time stamps and repeating frames if necessary.

All-Pairs Shortest-Paths Problem for Unweighted Graphs in O(n2 log n) Time

Given a simple connected unweighted undirected graph G = (V (G), E(G)) with |V (G)| = n and |E(G)| = m, we present a new algorithm for the all-pairs shortest-path (APSP) problem. The running time of our algorithm is in O(n2 log n). This bound is an improvement over previous best known O(n2.376) time bound of Raimund Seidel (1995) for general graphs. The algorithm presented does not rely on fast matrix multiplication. Our algorithm with slight modifications, enables us to compute the APSP problem for unweighted directed graph in time O(n2 log n), improving a previous best known O(n2.575) time bound of Uri Zwick (2002).

Communication Engineering Curriculum (Past, Present and the Future)

At present time, competition, unpredictable fluctuations have made communication engineering education in the global sphere really difficult. Confront with new situation in the engineering education sector. Communication engineering education has to be reformed and ready to use more advanced technologies. We realized that one of the general problems of student`s education is that after graduating from their universities, they are not prepared to face the real life challenges and full skilled to work in industry. They are prepared only to think like engineers and professionals but they also need to possess some others non-technical skills. In today-s environment, technical competence alone is not sufficient for career success. Employers want employees (graduate engineers) who have good oral and written communication (soft) skills. It does require for team work, business awareness, organization, management skills, responsibility, initiative, problem solving and IT competency. This proposed curriculum brings interactive, creative, interesting, effective learning methods, which includes online education, virtual labs, practical work, problem-based learning (PBL), and lectures given by industry experts. Giving short assignments, presentations, reports, research papers and projects students can significantly improve their non-technical skills. Also, we noticed the importance of using ICT technologies in engineering education which used by students and teachers, and included that into proposed teaching and learning methods. We added collaborative learning between students through team work which builds theirs skills besides course materials. The prospective on this research that we intent to update communication engineering curriculum in order to get fully constructed engineer students to ready for real industry work.

Earth Station Neural Network Control Methodology and Simulation

Renewable energy resources are inexhaustible, clean as compared with conventional resources. Also, it is used to supply regions with no grid, no telephone lines, and often with difficult accessibility by common transport. Satellite earth stations which located in remote areas are the most important application of renewable energy. Neural control is a branch of the general field of intelligent control, which is based on the concept of artificial intelligence. This paper presents the mathematical modeling of satellite earth station power system which is required for simulating the system.Aswan is selected to be the site under consideration because it is a rich region with solar energy. The complete power system is simulated using MATLAB–SIMULINK.An artificial neural network (ANN) based model has been developed for the optimum operation of earth station power system. An ANN is trained using a back propagation with Levenberg–Marquardt algorithm. The best validation performance is obtained for minimum mean square error. The regression between the network output and the corresponding target is equal to 96% which means a high accuracy. Neural network controller architecture gives satisfactory results with small number of neurons, hence better in terms of memory and time are required for NNC implementation. The results indicate that the proposed control unit using ANN can be successfully used for controlling the satellite earth station power system.

Knowledge Acquisition for the Construction of an Evolving Ontology: Application to Augmented Surgery

This work concerns the evolution and the maintenance of an ontological resource in relation with the evolution of the corpus of texts from which it had been built. The knowledge forming a text corpus, especially in dynamic domains, is in continuous evolution. When a change in the corpus occurs, the domain ontology must evolve accordingly. Most methods manage ontology evolution independently from the corpus from which it is built; in addition, they treat evolution just as a process of knowledge addition, not considering other knowledge changes. We propose a methodology for managing an evolving ontology from a text corpus that evolves over time, while preserving the consistency and the persistence of this ontology. Our methodology is based on the changes made on the corpus to reflect the evolution of the considered domain - augmented surgery in our case. In this context, the results of text mining techniques, as well as the ARCHONTE method slightly modified, are used to support the evolution process.

A Unique Solution for Designing Low-Cost, Heterogeneous Sensor Networks Using a Middleware Integration Platform

Proprietary sensor network systems are typically expensive, rigid and difficult to incorporate technologies from other vendors. When using competing and incompatible technologies, a non-proprietary system is complex to create because it requires significant technical expertise and effort, which can be more expensive than a proprietary product. This paper presents the Sensor Abstraction Layer (SAL) that provides middleware architectures with a consistent and uniform view of heterogeneous sensor networks, regardless of the technologies involved. SAL abstracts and hides the hardware disparities and specificities related to accessing, controlling, probing and piloting heterogeneous sensors. SAL is a single software library containing a stable hardware-independent interface with consistent access and control functions to remotely manage the network. The end-user has near-real-time access to the collected data via the network, which results in a cost-effective, flexible and simplified system suitable for novice users. SAL has been used for successfully implementing several low-cost sensor network systems.