Search results for: Ad-Hoc networks
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2703

Search results for: Ad-Hoc networks

1383 Investigation of Unusually High Ultrasonic Signal Attenuation in Water Observed in Various Combinations of Pairs of Lead Zirconate Titanate Pb(ZrxTi1-x)O3 (PZT) Piezoelectric Ceramics Positioned Adjacent to One Another Separated by an Intermediate Gap

Authors: S. M. Mabandla, P. Loveday, C. Gomes, D. T. Maiga, T. T. Phadi

Abstract:

Lead zirconate titanate (PZT) piezoelectric ceramics are widely used in ultrasonic applications due to their ability to effectively convert electrical energy into mechanical vibrations and vice versa. This paper presents a study on the behaviour of various combinations of pairs of PZT piezoelectric ceramic materials positioned adjacent to each other with an intermediate gap submerged in water, where one piezoelectric ceramic material is excited by a cyclic electric field with constant frequency and amplitude displacement. The transmitted ultrasonic sound propagates through the medium and is received by the PZT ceramic at the other end, the ultrasonic sound signal amplitude displacement experiences attenuation during propagation due to acoustic impedance. The investigation focuses on understanding the causes of extremely high amplitude displacement attenuation that have been observed in various combinations of piezoelectric ceramic pairs that are submerged in water arranged in a manner stipulated earlier. by examining various combinations of pairs of these piezoelectric ceramics, their physical, electrical, and acoustic properties, and behaviour and attributing them to the observed significant signal attenuation. The experimental setup involves exciting one piezoelectric ceramic material at one end with a burst square cyclic electric field signal of constant frequency, which generates a burst of ultrasonic sound that propagates through the water medium to the adjacent piezoelectric ceramic at the other end. Mechanical vibrations of a PZT piezoelectric ceramic are measured using a double-beam laser Doppler vibrometer to mimic the incident ultrasonic waves generated and received ultrasonic waves on the other end due to mechanical vibrations of a PZT. The measured ultrasonic sound wave signals are continuously compared to the applied cyclic electric field at both ends. The impedance matching networks are continuously tuned at both ends to eliminate electromechanical impedance mismatch to improve ultrasonic transmission and reception. The study delves into various physical, electrical, and acoustic properties of the PZT piezoelectric ceramics, such as the electromechanical coupling factor, acoustic coupling, and elasticity, among others. These properties are analyzed to identify potential factors contributing to the unusually high acoustic impedance in the water medium between the ceramics. Additionally, impedance-matching networks are investigated at both ends to offset the high signal attenuation and improve overall system performance. The findings will be reported in this paper.

Keywords: acoustic impedance, impedance mismatch, piezoelectric ceramics, ultrasonic sound

Procedia PDF Downloads 65
1382 The Application of the Enterprise Systems through the Cloud Computing in Company: A Review and Suggestions

Authors: Mohanaad Talal Shakir, Saad AJAJ Khalaf, Nawar Ahmed Aljumaily, Mustafa Talal Shakere

Abstract:

Cloud computing is a model for enabling convenient, on demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. Objectives of this paper are to investigate the role of the Enterprise System and Cloud Computing Services to assist and guide him to ensure the initiative become successful. The cloud computing technology offers great potential for Enterprise such as the speed of dealing with data and product introductions, innovations and speed of response. The use of cloud computing technology leads to the rapid development and competitiveness of enterprises in various fields.

Keywords: cloud computing, information management, marketing, enterprise systems

Procedia PDF Downloads 663
1381 Femtocell Stationed Flawless Handover in High Agility Trains

Authors: S. Dhivya, M. Abirami, M. Farjana Parveen, M. Keerthiga

Abstract:

The development of high-speed railway makes people’s lives more and more convenient; meanwhile, handover is the major problem on high-speed railway communication services. In order to overcome that drawback the architecture of Long-Term Evolution (LTE) femtocell networks is used to improve network performance, and the deployment of a femtocell is a key for bandwidth limitation and coverage issues in conventional mobile network system. To increase the handover performance this paper proposed a multiple input multiple output (MIMO) assisted handoff (MAHO) algorithm. It is a technique used in mobile telecom to transfer a mobile phone to a new radio channel with stronger signal strength and improved channel quality.

Keywords: flawless handover, high-speed train, home evolved Node B, LTE, mobile femtocell, RSS

Procedia PDF Downloads 457
1380 Proactive Pure Handoff Model with SAW-TOPSIS Selection and Time Series Predict

Authors: Harold Vásquez, Cesar Hernández, Ingrid Páez

Abstract:

This paper approach cognitive radio technic and applied pure proactive handoff Model to decrease interference between PU and SU and comparing it with reactive handoff model. Through the study and analysis of multivariate models SAW and TOPSIS join to 3 dynamic prediction techniques AR, MA ,and ARMA. To evaluate the best model is taken four metrics: number failed handoff, number handoff, number predictions, and number interference. The result presented the advantages using this type of pure proactive models to predict changes in the PU according to the selected channel and reduce interference. The model showed better performance was TOPSIS-MA, although TOPSIS-AR had a higher predictive ability this was not reflected in the interference reduction.

Keywords: cognitive radio, spectrum handoff, decision making, time series, wireless networks

Procedia PDF Downloads 466
1379 Modified RSA in Mobile Communication

Authors: Nagaratna Rajur, J. D. Mallapur, Y. B. Kirankumar

Abstract:

The security in mobile communication is very different from the internet or telecommunication, because of its poor user interface and limited processing capacity, as well as combination of complex network protocols. Hence, it poses a challenge for less memory usage and low computation speed based security system. Security involves all the activities that are undertaken to protect the value and on-going usability of assets and the integrity and continuity of operations. An effective network security strategies requires identifying threats and then choosing the most effective set of tools to combat them. Cryptography is a simple and efficient way to provide security in communication. RSA is an asymmetric key approach that is highly reliable and widely used in internet communication. However, it has not been efficiently implemented in mobile communication due its computational complexity and large memory utilization. The proposed algorithm modifies the current RSA to be useful in mobile communication by reducing its computational complexity and memory utilization.

Keywords: M-RSA, sensor networks, sensor applications, security

Procedia PDF Downloads 328
1378 A Neural Approach for Color-Textured Images Segmentation

Authors: Khalid Salhi, El Miloud Jaara, Mohammed Talibi Alaoui

Abstract:

In this paper, we present a neural approach for unsupervised natural color-texture image segmentation, which is based on both Kohonen maps and mathematical morphology, using a combination of the texture and the image color information of the image, namely, the fractal features based on fractal dimension are selected to present the information texture, and the color features presented in RGB color space. These features are then used to train the network Kohonen, which will be represented by the underlying probability density function, the segmentation of this map is made by morphological watershed transformation. The performance of our color-texture segmentation approach is compared first, to color-based methods or texture-based methods only, and then to k-means method.

Keywords: segmentation, color-texture, neural networks, fractal, watershed

Procedia PDF Downloads 323
1377 Location Tracking of Human Using Mobile Robot and Wireless Sensor Networks

Authors: Muazzam A. Khan

Abstract:

In order to avoid dangerous environmental disasters, robots are being recognized as good entrants to step in as human rescuers. Robots has been gaining interest of many researchers in rescue matters especially which are furnished with advanced sensors. In distributed wireless robot system main objective for a rescue system is to track the location of the object continuously. This paper provides a novel idea to track and locate human in disaster area using stereo vision system and ZigBee technology. This system recursively predict and updates 3D coordinates in a robot coordinate camera system of a human which makes the system cost effective. This system is comprised of ZigBee network which has many advantages such as low power consumption, self-healing low data rates and low cost.

Keywords: stereo vision, segmentation, classification, human tracking, ZigBee module

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1376 Investigating the Viability of Ultra-Low Parameter Count Networks for Real-Time Football Detection

Authors: Tim Farrelly

Abstract:

In recent years, AI-powered object detection systems have opened the doors for innovative new applications and products, especially those operating in the real world or ‘on edge’ – namely, in sport. This paper investigates the viability of an ultra-low parameter convolutional neural network specially designed for the detection of footballs on ‘on the edge’ devices. The main contribution of this paper is the exploration of integrating new design features (depth-wise separable convolutional blocks and squeezed and excitation modules) into an ultra-low parameter network and demonstrating subsequent improvements in performance. The results show that tracking the ball from Full HD images with negligibly high accu-racy is possible in real-time.

Keywords: deep learning, object detection, machine vision applications, sport, network design

Procedia PDF Downloads 126
1375 Quality and Quantity in the Strategic Network of Higher Education Institutions

Authors: Juha Kettunen

Abstract:

The study analyzes the quality and the size of the strategic network of higher education institutions and the concept of fitness for purpose in quality assurance. It also analyses the transaction costs of networking that have consequences on the number of members in the network. Empirical evidence is presented from the Consortium on Applied Research and Professional Education, which is a European strategic network of six higher education institutions. The results of the study support the argument that the number of members in the strategic network should be relatively small to provide high-quality results. The practical importance is that networking has been able to promote international research and development projects. The results of this study are important for those who want to design and improve international networks in higher education.

Keywords: higher education, network, research and development, strategic management

Procedia PDF Downloads 326
1374 Symmetric Arabic Language Encryption Technique Based on Modified Playfair Algorithm

Authors: Fairouz Beggas

Abstract:

Due to the large number of exchanges in the networks, the security of communications is essential. Most ways of keeping communication secure rely on encryption. In this work, a symmetric encryption technique is offered to encrypt and decrypt simple Arabic scripts based on a multi-level security. A proposed technique uses an idea of Playfair encryption with a larger table size and an additional layer of encryption to ensure more security. The idea of the proposed algorithm aims to generate a dynamic table that depends on a secret key. The same secret key is also used to create other secret keys to over-encrypt the plaintext in three steps. The obtained results show that the proposed algorithm is faster in terms of encryption/decryption speed and can resist to many types of attacks.

Keywords: arabic data, encryption, playfair, symmetric algorithm

Procedia PDF Downloads 71
1373 Pump-as-Turbine: Testing and Characterization as an Energy Recovery Device, for Use within the Water Distribution Network

Authors: T. Lydon, A. McNabola, P. Coughlan

Abstract:

Energy consumption in the water distribution network (WDN) is a well established problem equating to the industry contributing heavily to carbon emissions, with 0.9 kg CO2 emitted per m3 of water supplied. It is indicated that 85% of energy wasted in the WDN can be recovered by installing turbines. Existing potential in networks is present at small capacity sites (5-10 kW), numerous and dispersed across networks. However, traditional turbine technology cannot be scaled down to this size in an economically viable fashion, thus alternative approaches are needed. This research aims to enable energy recovery potential within the WDN by exploring the potential of pumps-as-turbines (PATs), to realise this potential. PATs are estimated to be ten times cheaper than traditional micro-hydro turbines, presenting potential to contribute to an economically viable solution. However, a number of technical constraints currently prohibit their widespread use, including the inability of a PAT to control pressure, difficulty in the selection of PATs due to lack of performance data and a lack of understanding on how PATs can cater for fluctuations as extreme as +/- 50% of the average daily flow, characteristic of the WDN. A PAT prototype is undergoing testing in order to identify the capabilities of the technology. Results of preliminary testing, which involved testing the efficiency and power potential of the PAT for varying flow and pressure conditions, in order to develop characteristic and efficiency curves for the PAT and a baseline understanding of the technologies capabilities, are presented here: •The limitations of existing selection methods which convert BEP from pump operation to BEP in turbine operation was highlighted by the failure of such methods to reflect the conditions of maximum efficiency of the PAT. A generalised selection method for the WDN may need to be informed by an understanding of impact of flow variations and pressure control on system power potential capital cost, maintenance costs, payback period. •A clear relationship between flow and efficiency rate of the PAT has been established. The rate of efficiency reductions for flows +/- 50% BEP is significant and more extreme for deviations in flow above the BEP than below, but not dissimilar to the reaction of efficiency of other turbines. •PAT alone is not sufficient to regulate pressure, yet the relationship of pressure across the PAT is foundational in exploring ways which PAT energy recovery systems can maintain required pressure level within the WDN. Efficiencies of systems of PAT energy recovery systems operating conditions of pressure regulation, which have been conceptualise in current literature, need to be established. Initial results guide the focus of forthcoming testing and exploration of PAT technology towards how PATs can form part of an efficiency energy recovery system.

Keywords: energy recovery, pump-as-turbine, water distribution network, water distribution network

Procedia PDF Downloads 242
1372 Dual-Network Memory Model for Temporal Sequences

Authors: Motonobu Hattori

Abstract:

In neural networks, when new patters are learned by a network, they radically interfere with previously stored patterns. This drawback is called catastrophic forgetting. We have already proposed a biologically inspired dual-network memory model which can much reduce this forgetting for static patterns. In this model, information is first stored in the hippocampal network, and thereafter, it is transferred to the neocortical network using pseudo patterns. Because, temporal sequence learning is more important than static pattern learning in the real world, in this study, we improve our conventional dual-network memory model so that it can deal with temporal sequences without catastrophic forgetting. The computer simulation results show the effectiveness of the proposed dual-network memory model.

Keywords: catastrophic forgetting, dual-network, temporal sequences, hippocampal

Procedia PDF Downloads 248
1371 Swelling Behavior of Cross-Linked Poly (2-hydroxyethyl methacrylate)

Authors: Salah Hamri, Tewfik Bouchaour, Ulrich Maschke

Abstract:

The aim of this works is the study of swelling ratio of cross-linked polymer networks poly (2-hydroxyethyl methacrylate) (PHEMA). The system composed of erythrosine and Triethanolamine, in aqueous medium, is used as photo-initiator and 1,6-Hexanediol diacrylate as cross-linker. The analysis of UV-visible and infrared spectra, which were taken at different times during polymerization/cross linking, makes it possible to obtain useful information on the reaction mechanism. The swelling behavior was study by changing the nature of solvent, dye sensitizer (erythrosine, rose Bengal and eosin), and pH of the medium. The exploitation of experimental results using Fick diffusion model is also expected and shows a good correlation between theoretical and experimental results.

Keywords: cross-linker, photo-sensitizer, polymer network, swelling ratio

Procedia PDF Downloads 295
1370 Prediction of Unsaturated Permeability Functions for Clayey Soil

Authors: F. Louati, H. Trabelsi, M. Jamei

Abstract:

Desiccation cracks following drainage-humidification cycles. With water loss, mainly due to evaporation, suction in the soil increases, producing volumetric shrinkage and tensile stress. When the tensile stress reaches tensile strength, the soil cracks. Desiccation cracks networks can directly control soil hydraulic properties. The aim of this study was for quantifying the hydraulic properties for examples the water retention curve, the saturated hydraulic conductivity, the unsaturated hydraulic conductivity function, the shrinkage dynamics in Tibar soil- clay soil in the Northern of Tunisia. Then a numerical simulation of unsaturated hydraulic properties for a crack network has been attempted. The finite elements code ‘CODE_BRIGHT’ can be used to follow the hydraulic distribution in cracked porous media.

Keywords: desiccation, cracks, permeability, unsaturated hydraulic flow, simulation

Procedia PDF Downloads 277
1369 The Impact of the Number of Neurons in the Hidden Layer on the Performance of MLP Neural Network: Application to the Fast Identification of Toxics Gases

Authors: Slimane Ouhmad, Abdellah Halimi

Abstract:

In this work, we have applied neural networks method MLP type to a database from an array of six sensors for the detection of three toxic gases. As the choice of the number of hidden layers and the weight values has a great influence on the convergence of the learning algorithm, we proposed, in this article, a mathematical formulation to determine the optimal number of hidden layers and good weight values based on the method of back propagation of errors. The results of this modeling have improved discrimination of these gases on the one hand, and optimize the computation time on the other hand, the comparison to other results achieved in this case.

Keywords: MLP Neural Network, back-propagation, number of neurons in the hidden layer, identification, computing time

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1368 Using Swarm Intelligence to Forecast Outcomes of English Premier League Matches

Authors: Hans Schumann, Colin Domnauer, Louis Rosenberg

Abstract:

In this study, machine learning techniques were deployed on real-time human swarm data to forecast the likelihood of outcomes for English Premier League matches in the 2020/21 season. These techniques included ensemble models in combination with neural networks and were tested against an industry standard of Vegas Oddsmakers. Predictions made from the collective intelligence of human swarm participants managed to achieve a positive return on investment over a full season on matches, empirically proving the usefulness of a new artificial intelligence valuing human instinct and intelligence.

Keywords: artificial intelligence, data science, English Premier League, human swarming, machine learning, sports betting, swarm intelligence

Procedia PDF Downloads 190
1367 From Customer Innovations to Manufactured Products: A Project Outlook

Authors: M. Holle, M. Roth, M. R. Gürtler, U. Lindemann

Abstract:

This paper gives insights into the research project "InnoCyFer" (in the form of an outlook) which is funded by the German Federal Ministry of Economics and Technology. Enabling the integrated customer individual product design as well as flexible manufacturing of these products are the main objectives of the project. To achieve this, a web-based open innovation-platform containing an integrated Toolkit will be developed. This toolkit enables the active integration of the customer’s creativity and potentials of innovation in the product development process. Furthermore, the project will show the chances and possibilities of customer individualized products by building and examining the continuous process from innovation through the customers to the flexible manufacturing of individual products.

Keywords: customer individual product design, innovation networks, open innovation, open innovation platform, toolkit

Procedia PDF Downloads 298
1366 Comparative Performance Analysis of Fiber Delay Line Based Buffer Architectures for Contention Resolution in Optical WDM Networks

Authors: Manoj Kumar Dutta

Abstract:

Wavelength division multiplexing (WDM) technology is the most promising technology for the proper utilization of huge raw bandwidth provided by an optical fiber. One of the key problems in implementing the all-optical WDM network is the packet contention. This problem can be solved by several different techniques. In time domain approach the packet contention can be reduced by incorporating fiber delay lines (FDLs) as optical buffer in the switch architecture. Different types of buffering architectures are reported in literatures. In the present paper a comparative performance analysis of three most popular FDL architectures are presented in order to obtain the best contention resolution performance. The analysis is further extended to consider the effect of different fiber non-linearities on the network performance.

Keywords: WDM network, contention resolution, optical buffering, non-linearity, throughput

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1365 Weapon-Being: Weaponized Design and Object-Oriented Ontology in Hypermodern Times

Authors: John Dimopoulos

Abstract:

This proposal attempts a refabrication of Heidegger’s classic thing-being and object-being analysis in order to provide better ontological tools for understanding contemporary culture, technology, and society. In his work, Heidegger sought to understand and comment on the problem of technology in an era of rampant innovation and increased perils for society and the planet. Today we seem to be at another crossroads in this course, coming after postmodernity, during which dreams and dangers of modernity augmented with critical speculations of the post-war era take shape. The new era which we are now living in, referred to as hypermodernity by researchers in various fields such as architecture and cultural theory, is defined by the horizontal implementation of digital technologies, cybernetic networks, and mixed reality. Technology today is rapidly approaching a turning point, namely the point of no return for humanity’s supervision over its creations. The techno-scientific civilization of the 21st century creates a series of problems, progressively more difficult and complex to solve and impossible to ignore, climate change, data safety, cyber depression, and digital stress being some of the most prevalent. Humans often have no other option than to address technology-induced problems with even more technology, as in the case of neuron networks, machine learning, and AI, thus widening the gap between creating technological artifacts and understanding their broad impact and possible future development. As all technical disciplines and particularly design, become enmeshed in a matrix of digital hyper-objects, a conceptual toolbox that allows us to handle the new reality becomes more and more necessary. Weaponized design, prevalent in many fields, such as social and traditional media, urban planning, industrial design, advertising, and the internet in general, hints towards an increase in conflicts. These conflicts between tech companies, stakeholders, and users with implications in politics, work, education, and production as apparent in the cases of Amazon workers’ strikes, Donald Trump’s 2016 campaign, Facebook and Microsoft data scandals, and more are often non-transparent to the wide public’s eye, thus consolidating new elites and technocratic classes and making the public scene less and less democratic. The new category proposed, weapon-being, is outlined in respect to the basic function of reducing complexity, subtracting materials, actants, and parameters, not strictly in favor of a humanistic re-orientation but in a more inclusive ontology of objects and subjects. Utilizing insights of Object-Oriented Ontology (OOO) and its schematization of technological objects, an outline for a radical ontology of technology is approached.

Keywords: design, hypermodernity, object-oriented ontology, weapon-being

Procedia PDF Downloads 138
1364 Channels Splitting Strategy for Optical Local Area Networks of Passive Star Topology

Authors: Peristera Baziana

Abstract:

In this paper, we present a network configuration for a WDM LANs of passive star topology that assume that the set of data WDM channels is split into two separate sets of channels, with different access rights over them. Especially, a synchronous transmission WDMA access algorithm is adopted in order to increase the probability of successful transmission over the data channels and consequently to reduce the probability of data packets transmission cancellation in order to avoid the data channels collisions. Thus, a control pre-transmission access scheme is followed over a separate control channel. An analytical Markovian model is studied and the average throughput is mathematically derived. The performance is studied for several numbers of data channels and various values of control phase duration.

Keywords: access algorithm, channels division, collisions avoidance, wavelength division multiplexing

Procedia PDF Downloads 274
1363 Automated Computer-Vision Analysis Pipeline of Calcium Imaging Neuronal Network Activity Data

Authors: David Oluigbo, Erik Hemberg, Nathan Shwatal, Wenqi Ding, Yin Yuan, Susanna Mierau

Abstract:

Introduction: Calcium imaging is an established technique in neuroscience research for detecting activity in neural networks. Bursts of action potentials in neurons lead to transient increases in intracellular calcium visualized with fluorescent indicators. Manual identification of cell bodies and their contours by experts typically takes 10-20 minutes per calcium imaging recording. Our aim, therefore, was to design an automated pipeline to facilitate and optimize calcium imaging data analysis. Our pipeline aims to accelerate cell body and contour identification and production of graphical representations reflecting changes in neuronal calcium-based fluorescence. Methods: We created a Python-based pipeline that uses OpenCV (a computer vision Python package) to accurately (1) detect neuron contours, (2) extract the mean fluorescence within the contour, and (3) identify transient changes in the fluorescence due to neuronal activity. The pipeline consisted of 3 Python scripts that could both be easily accessed through a Python Jupyter notebook. In total, we tested this pipeline on ten separate calcium imaging datasets from murine dissociate cortical cultures. We next compared our automated pipeline outputs with the outputs of manually labeled data for neuronal cell location and corresponding fluorescent times series generated by an expert neuroscientist. Results: Our results show that our automated pipeline efficiently pinpoints neuronal cell body location and neuronal contours and provides a graphical representation of neural network metrics accurately reflecting changes in neuronal calcium-based fluorescence. The pipeline detected the shape, area, and location of most neuronal cell body contours by using binary thresholding and grayscale image conversion to allow computer vision to better distinguish between cells and non-cells. Its results were also comparable to manually analyzed results but with significantly reduced result acquisition times of 2-5 minutes per recording versus 10-20 minutes per recording. Based on these findings, our next step is to precisely measure the specificity and sensitivity of the automated pipeline’s cell body and contour detection to extract more robust neural network metrics and dynamics. Conclusion: Our Python-based pipeline performed automated computer vision-based analysis of calcium image recordings from neuronal cell bodies in neuronal cell cultures. Our new goal is to improve cell body and contour detection to produce more robust, accurate neural network metrics and dynamic graphs.

Keywords: calcium imaging, computer vision, neural activity, neural networks

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1362 Use Cases Analysis of Free Space Optical Communication System

Authors: Kassem Saab, Fritzen Bart, Yves-Marie Seveque

Abstract:

The deployment of Free Space Optical Communications (FSOC) systems requires the development of robust and reliable Optical Ground Stations (OGS) that can be easily installed and operated. To this end, the Engineering Department of Airbus Defence and Space is actively working on the development of innovative and compact OGS solutions that can be deployed in various environments and provide high-quality connectivity under different atmospheric conditions. This article presents an overview of our recent developments in this field, including an evaluation study of different use cases of the FSOC with respect to different atmospheric conditions. The goal is to provide OGS solutions that are both simple and highly effective, allowing for the deployment of high-speed communication networks in a wide range of scenarios.

Keywords: end to end optical communication, laser propagation, optical ground station, turbulence

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1361 Energy Consumption Models for Electric Vehicles: Survey and Proposal of a More Realistic Model

Authors: I. Sagaama, A. Kechiche, W. Trojet, F. Kamoun

Abstract:

Replacing combustion engine vehicles by electric vehicles (EVs) is a major step in recent years due to their potential benefits. Battery autonomy and charging processes are still a big issue for that kind of vehicles. Therefore, reducing the energy consumption of electric vehicles becomes a necessity. Many researches target introducing recent information and communication technologies in EVs in order to propose reducing energy consumption services. Evaluation of realistic scenarios is a big challenge nowadays. In this paper, we will elaborate a state of the art of different proposed energy consumption models in the literature, then we will present a comparative study of these models, finally, we will extend previous works in order to propose an accurate and realistic energy model for calculating instantaneous power consumption of electric vehicles.

Keywords: electric vehicle, vehicular networks, energy models, traffic simulation

Procedia PDF Downloads 343
1360 Evaluating Performance of an Anomaly Detection Module with Artificial Neural Network Implementation

Authors: Edward Guillén, Jhordany Rodriguez, Rafael Páez

Abstract:

Anomaly detection techniques have been focused on two main components: data extraction and selection and the second one is the analysis performed over the obtained data. The goal of this paper is to analyze the influence that each of these components has over the system performance by evaluating detection over network scenarios with different setups. The independent variables are as follows: the number of system inputs, the way the inputs are codified and the complexity of the analysis techniques. For the analysis, some approaches of artificial neural networks are implemented with different number of layers. The obtained results show the influence that each of these variables has in the system performance.

Keywords: network intrusion detection, machine learning, artificial neural network, anomaly detection module

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1359 Hybrid Hierarchical Routing Protocol for WSN Lifetime Maximization

Authors: H. Aoudia, Y. Touati, E. H. Teguig, A. Ali Cherif

Abstract:

Conceiving and developing routing protocols for wireless sensor networks requires considerations on constraints such as network lifetime and energy consumption. In this paper, we propose a hybrid hierarchical routing protocol named HHRP combining both clustering mechanism and multipath optimization taking into account residual energy and RSSI measures. HHRP consists of classifying dynamically nodes into clusters where coordinators nodes with extra privileges are able to manipulate messages, aggregate data and ensure transmission between nodes according to TDMA and CDMA schedules. The reconfiguration of the network is carried out dynamically based on a threshold value which is associated with the number of nodes belonging to the smallest cluster. To show the effectiveness of the proposed approach HHRP, a comparative study with LEACH protocol is illustrated in simulations.

Keywords: routing protocol, optimization, clustering, WSN

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1358 Performance Evaluation of Contemporary Classifiers for Automatic Detection of Epileptic EEG

Authors: K. E. Ch. Vidyasagar, M. Moghavvemi, T. S. S. T. Prabhat

Abstract:

Epilepsy is a global problem, and with seizures eluding even the smartest of diagnoses a requirement for automatic detection of the same using electroencephalogram (EEG) would have a huge impact in diagnosis of the disorder. Among a multitude of methods for automatic epilepsy detection, one should find the best method out, based on accuracy, for classification. This paper reasons out, and rationalizes, the best methods for classification. Accuracy is based on the classifier, and thus this paper discusses classifiers like quadratic discriminant analysis (QDA), classification and regression tree (CART), support vector machine (SVM), naive Bayes classifier (NBC), linear discriminant analysis (LDA), K-nearest neighbor (KNN) and artificial neural networks (ANN). Results show that ANN is the most accurate of all the above stated classifiers with 97.7% accuracy, 97.25% specificity and 98.28% sensitivity in its merit. This is followed closely by SVM with 1% variation in result. These results would certainly help researchers choose the best classifier for detection of epilepsy.

Keywords: classification, seizure, KNN, SVM, LDA, ANN, epilepsy

Procedia PDF Downloads 498
1357 Parameter Estimation of Induction Motors by PSO Algorithm

Authors: A. Mohammadi, S. Asghari, M. Aien, M. Rashidinejad

Abstract:

After emergent of alternative current networks and their popularity, asynchronous motors became more widespread than other kinds of industrial motors. In order to control and run these motors efficiently, an accurate estimation of motor parameters is needed. There are different methods to obtain these parameters such as rotor locked test, no load test, DC test, analytical methods, and so on. The most common drawback of these methods is their inaccuracy in estimation of some motor parameters. In order to remove this concern, a novel method for parameter estimation of induction motors using particle swarm optimization (PSO) algorithm is proposed. In the proposed method, transient state of motor is used for parameter estimation. Comparison of the simulation results purtuined to the PSO algorithm with other available methods justifies the effectiveness of the proposed method.

Keywords: induction motor, motor parameter estimation, PSO algorithm, analytical method

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1356 Comparative Analysis between Wired and Wireless Technologies in Communications: A Review

Authors: Jafaru Ibrahim, Tonga Agadi Danladi, Haruna Sani

Abstract:

Many telecommunications industry are looking for new ways to maximize their investment in communication networks while ensuring reliable and secure information transmission. There is a variety of communications medium solutions, the two must popularly in used are wireless technology and wired options, such as copper and fiber-optic cable. Wired network has proven its potential in the olden days but nowadays wireless communication has emerged as a robust and most intellect and preferred communication technique. Each of these types of communication medium has their advantages and disadvantages according to its technological characteristics. Wired and wireless networking has different hardware requirements, ranges, mobility, reliability and benefits. The aim of the paper is to compare both the Wired and Wireless medium on the basis of various parameters such as usability, cost, efficiency, flexibility, coverage, reliability, mobility, speed, security etc.

Keywords: cost, mobility, reliability, speed, security, wired, wireless

Procedia PDF Downloads 447
1355 Real Time Multi Person Action Recognition Using Pose Estimates

Authors: Aishrith Rao

Abstract:

Human activity recognition is an important aspect of video analytics, and many approaches have been recommended to enable action recognition. In this approach, the model is used to identify the action of the multiple people in the frame and classify them accordingly. A few approaches use RNNs and 3D CNNs, which are computationally expensive and cannot be trained with the small datasets which are currently available. Multi-person action recognition has been performed in order to understand the positions and action of people present in the video frame. The size of the video frame can be adjusted as a hyper-parameter depending on the hardware resources available. OpenPose has been used to calculate pose estimate using CNN to produce heap-maps, one of which provides skeleton features, which are basically joint features. The features are then extracted, and a classification algorithm can be applied to classify the action.

Keywords: human activity recognition, computer vision, pose estimates, convolutional neural networks

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1354 A Location Routing Model for the Logistic System in the Mining Collection Centers of the Northern Region of Boyacá-Colombia

Authors: Erika Ruíz, Luis Amaya, Diego Carreño

Abstract:

The main objective of this study is to design a mathematical model for the logistics of mining collection centers in the northern region of the department of Boyacá (Colombia), determining the structure that facilitates the flow of products along the supply chain. In order to achieve this, it is necessary to define a suitable design of the distribution network, taking into account the products, customer’s characteristics and the availability of information. Likewise, some other aspects must be defined, such as number and capacity of collection centers to establish, routes that must be taken to deliver products to the customers, among others. This research will use one of the operation research problems, which is used in the design of distribution networks known as Location Routing Problem (LRP).

Keywords: location routing problem, logistic, mining collection, model

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