Search results for: Infrastructure and Computer Network
2781 Emotion Recognition Using Neural Network: A Comparative Study
Authors: Nermine Ahmed Hendy, Hania Farag
Abstract:
Emotion recognition is an important research field that finds lots of applications nowadays. This work emphasizes on recognizing different emotions from speech signal. The extracted features are related to statistics of pitch, formants, and energy contours, as well as spectral, perceptual and temporal features, jitter, and shimmer. The Artificial Neural Networks (ANN) was chosen as the classifier. Working on finding a robust and fast ANN classifier suitable for different real life application is our concern. Several experiments were carried out on different ANN to investigate the different factors that impact the classification success rate. Using a database containing 7 different emotions, it will be shown that with a proper and careful adjustment of features format, training data sorting, number of features selected and even the ANN type and architecture used, a success rate of 85% or even more can be achieved without increasing the system complicity and the computation time
Keywords: Classification, emotion recognition, features extraction, feature selection, neural network
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 46822780 Analysing of Indoor Radio Wave Propagation on Ad-hoc Network by Using TP-LINK Router
Authors: Khine Phyu, Aung Myint Aye
Abstract:
This paper presents results of measurements campaign carried out at a carrier frequency of 24GHz with the help of TPLINK router in indoor line-of-sight (LOS) scenarios. Firstly, the radio wave propagation strategies are analyzed in some rooms with router of point to point Ad hoc network. Then floor attenuation is defined for 3 floors in experimental region. The free space model and dual slope models are modified by considering the influence of corridor conditions on each floor. Using these models, indoor signal attenuation can be estimated in modeling of indoor radio wave propagation. These results and modified models can also be used in planning the networks of future personal communications services.Keywords: radio wave signal analyzing, LOS radio wavepropagation, indoor radio wave propagation, free space model, tworay model and indoor attenuation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20092779 Video Based Ambient Smoke Detection By Detecting Directional Contrast Decrease
Authors: Omair Ghori, Anton Stadler, Stefan Wilk, Wolfgang Effelsberg
Abstract:
Fire-related incidents account for extensive loss of life and material damage. Quick and reliable detection of occurring fires has high real world implications. Whereas a major research focus lies on the detection of outdoor fires, indoor camera-based fire detection is still an open issue. Cameras in combination with computer vision helps to detect flames and smoke more quickly than conventional fire detectors. In this work, we present a computer vision-based smoke detection algorithm based on contrast changes and a multi-step classification. This work accelerates computer vision-based fire detection considerably in comparison with classical indoor-fire detection.Keywords: Contrast analysis, early fire detection, video smoke detection, video surveillance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15732778 Performance Analysis of Wireless Ad-Hoc Network Based on EDCA IEEE802.11e
Authors: Shah Ahsanuzzaman Md. Tariq, Fabrizio Granelli
Abstract:
IEEE 802.11e is the enhanced version of the IEEE 802.11 MAC dedicated to provide Quality of Service of wireless network. It supports QoS by the service differentiation and prioritization mechanism. Data traffic receives different priority based on QoS requirements. Fundamentally, applications are divided into four Access Categories (AC). Each AC has its own buffer queue and behaves as an independent backoff entity. Every frame with a specific priority of data traffic is assigned to one of these access categories. IEEE 802.11e EDCA (Enhanced Distributed Channel Access) is designed to enhance the IEEE 802.11 DCF (Distributed Coordination Function) mechanisms by providing a distributed access method that can support service differentiation among different classes of traffic. Performance of IEEE 802.11e MAC layer with different ACs is evaluated to understand the actual benefits deriving from the MAC enhancements.Keywords: 802.11e, fairness, enhanced distributed channelaccess, access categories, quality of Service.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19362777 Attention Multiple Instance Learning for Cancer Tissue Classification in Digital Histopathology Images
Authors: Afaf Alharbi, Qianni Zhang
Abstract:
The identification of malignant tissue in histopathological slides holds significant importance in both clinical settings and pathology research. This paper presents a methodology aimed at automatically categorizing cancerous tissue through the utilization of a multiple instance learning framework. This framework is specifically developed to acquire knowledge of the Bernoulli distribution of the bag label probability by employing neural networks. Furthermore, we put forward a neural network-based permutation-invariant aggregation operator, equivalent to attention mechanisms, which is applied to the multi-instance learning network. Through empirical evaluation on an openly available colon cancer histopathology dataset, we provide evidence that our approach surpasses various conventional deep learning methods.
Keywords: Attention Multiple Instance Learning, Multiple Instance Learning, transfer learning, histopathological slides, cancer tissue classification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1722776 Risk Factors’ Analysis on Shanghai Carbon Trading
Authors: Zhaojun Wang, Zongdi Sun, Zhiyuan Liu
Abstract:
First of all, the carbon trading price and trading volume in Shanghai are transformed by Fourier transform, and the frequency response diagram is obtained. Then, the frequency response diagram is analyzed and the Blackman filter is designed. The Blackman filter is used to filter, and the carbon trading time domain and frequency response diagram are obtained. After wavelet analysis, the carbon trading data were processed; respectively, we got the average value for each 5 days, 10 days, 20 days, 30 days, and 60 days. Finally, the data are used as input of the Back Propagation Neural Network model for prediction.
Keywords: Shanghai carbon trading, carbon trading price, carbon trading volume, wavelet analysis, BP neural network model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9622775 Neuro-fuzzy Classification System for Wireless-Capsule Endoscopic Images
Authors: Vassilis S. Kodogiannis, John N. Lygouras
Abstract:
In this research study, an intelligent detection system to support medical diagnosis and detection of abnormal lesions by processing endoscopic images is presented. The images used in this study have been obtained using the M2A Swallowable Imaging Capsule - a patented, video color-imaging disposable capsule. Schemes have been developed to extract texture features from the fuzzy texture spectra in the chromatic and achromatic domains for a selected region of interest from each color component histogram of endoscopic images. The implementation of an advanced fuzzy inference neural network which combines fuzzy systems and artificial neural networks and the concept of fusion of multiple classifiers dedicated to specific feature parameters have been also adopted in this paper. The achieved high detection accuracy of the proposed system has provided thus an indication that such intelligent schemes could be used as a supplementary diagnostic tool in endoscopy.Keywords: Medical imaging, Computer aided diagnosis, Endoscopy, Neuro-fuzzy networks, Fuzzy integral.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17402774 An Energy Integration Approach on UHDE Ammonia Process
Authors: Alnouss M. Ahmed, Al-Nuaimi A. Ibrahim
Abstract:
In this paper, the energy performance of a selected UHDE Ammonia plant is optimized by conducting heat integration through waste heat recovery and the synthesis of a heat exchange network (HEN). Minimum hot and cold utility requirements were estimated through IChemE spreadsheet. Supporting simulation was carried out using HYSYS software. The results showed that there is no need for heating utility while the required cold utility was found to be around 268,714 kW. Hence a threshold pinch case was faced. Then, the hot and cold streams were matched appropriately. Also, waste heat recovered resulted with savings in HP and LP steams of approximately 51.0% and 99.6%, respectively. An economic analysis on proposed HEN showed very attractive overall payback period not exceeding 3 years. In general, a net saving approaching 35% was achieved in implementing heat optimization of current studied UHDE Ammonia process.Keywords: Ammonia, Energy Optimization, Heat Exchange Network and Techno-Economic Analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 45382773 Agent-Based Simulation of Simulating Anticipatory Systems – Classification
Authors: Eugene Kindler
Abstract:
The present paper is oriented to classification and application of agent technique in simulation of anticipatory systems, namely those that use simulation models for the aid of anticipation. The main ideas root in the fact that the best way for description of computer simulation models is the technique of describing the simulated system itself (and the translation into the computer code is provided as automatic), and that the anticipation itself is often nested.
Keywords: Agents, Anticipatory systems, Discrete eventsimulation, Simula, Taxonomy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15502772 Non-contact Gaze Tracking with Head Movement Adaptation based on Single Camera
Authors: Ying Huang, Zhiliang Wang, An Ping
Abstract:
With advances in computer vision, non-contact gaze tracking systems are heading towards being much easier to operate and more comfortable for use, the technique proposed in this paper is specially designed for achieving these goals. For the convenience in operation, the proposal aims at the system with simple configuration which is composed of a fixed wide angle camera and dual infrared illuminators. Then in order to enhance the usability of the system based on single camera, a self-adjusting method which is called Real-time gaze Tracking Algorithm with head movement Compensation (RTAC) is developed for estimating the gaze direction under natural head movement and simplifying the calibration procedure at the same time. According to the actual evaluations, the average accuracy of about 1° is achieved over a field of 20×15×15 cm3.
Keywords: computer vision, gaze tracking, human-computer interaction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19122771 Multi-Line Flexible Alternating Current Transmission System (FACTS) Controller for Transient Stability Analysis of a Multi-Machine Power System Network
Authors: A.V.Naresh Babu, S.Sivanagaraju
Abstract:
A considerable progress has been achieved in transient stability analysis (TSA) with various FACTS controllers. But, all these controllers are associated with single transmission line. This paper is intended to discuss a new approach i.e. a multi-line FACTS controller which is interline power flow controller (IPFC) for TSA of a multi-machine power system network. A mathematical model of IPFC, termed as power injection model (PIM) presented and this model is incorporated in Newton-Raphson (NR) power flow algorithm. Then, the reduced admittance matrix of a multi-machine power system network for a three phase fault without and with IPFC is obtained which is required to draw the machine swing curves. A general approach based on L-index has also been discussed to find the best location of IPFC to reduce the proximity to instability of a power system. Numerical results are carried out on two test systems namely, 6-bus and 11-bus systems. A program in MATLAB has been written to plot the variation of generator rotor angle and speed difference curves without and with IPFC for TSA and also a simple approach has been presented to evaluate critical clearing time for test systems. The results obtained without and with IPFC are compared and discussed.Keywords: Flexible alternating current transmission system (FACTS), first swing stability, interline power flow controller (IPFC), power injection model (PIM).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21862770 Electroencephalography Based Brain-Computer Interface for Cerebellum Impaired Patients
Authors: Young-Seok Choi
Abstract:
In healthy humans, the cortical brain rhythm shows specific mu (~6-14 Hz) and beta (~18-24 Hz) band patterns in the cases of both real and imaginary motor movements. As cerebellar ataxia is associated with impairment of precise motor movement control as well as motor imagery, ataxia is an ideal model system in which to study the role of the cerebellocortical circuit in rhythm control. We hypothesize that the EEG characteristics of ataxic patients differ from those of controls during the performance of a Brain-Computer Interface (BCI) task. Ataxia and control subjects showed a similar distribution of mu power during cued relaxation. During cued motor imagery, however, the ataxia group showed significant spatial distribution of the response, while the control group showed the expected decrease in mu-band power (localized to the motor cortex).
Keywords: Brain-computer interface, EEG, modulation, ataxia.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19572769 An Approach to Secure Mobile Agent Communication in Multi-Agent Systems
Authors: Olumide Simeon Ogunnusi, Shukor Abd Razak, Michael Kolade Adu
Abstract:
Inter-agent communication manager facilitates communication among mobile agents via message passing mechanism. Until now, all Foundation for Intelligent Physical Agents (FIPA) compliant agent systems are capable of exchanging messages following the standard format of sending and receiving messages. Previous works tend to secure messages to be exchanged among a community of collaborative agents commissioned to perform specific tasks using cryptosystems. However, the approach is characterized by computational complexity due to the encryption and decryption processes required at the two ends. The proposed approach to secure agent communication allows only agents that are created by the host agent server to communicate via the agent communication channel provided by the host agent platform. These agents are assumed to be harmless. Therefore, to secure communication of legitimate agents from intrusion by external agents, a 2-phase policy enforcement system was developed. The first phase constrains the external agent to run only on the network server while the second phase confines the activities of the external agent to its execution environment. To implement the proposed policy, a controller agent was charged with the task of screening any external agent entering the local area network and preventing it from migrating to the agent execution host where the legitimate agents are running. On arrival of the external agent at the host network server, an introspector agent was charged to monitor and restrain its activities. This approach secures legitimate agent communication from Man-in-the Middle and Replay attacks.
Keywords: Agent communication, introspective agent, isolation of agent, policy enforcement system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6312768 Modeling Peer-to-Peer Networks with Interest-Based Clusters
Authors: Bertalan Forstner, Dr. Hassan Charaf
Abstract:
In the world of Peer-to-Peer (P2P) networking different protocols have been developed to make the resource sharing or information retrieval more efficient. The SemPeer protocol is a new layer on Gnutella that transforms the connections of the nodes based on semantic information to make information retrieval more efficient. However, this transformation causes high clustering in the network that decreases the number of nodes reached, therefore the probability of finding a document is also decreased. In this paper we describe a mathematical model for the Gnutella and SemPeer protocols that captures clustering-related issues, followed by a proposition to modify the SemPeer protocol to achieve moderate clustering. This modification is a sort of link management for the individual nodes that allows the SemPeer protocol to be more efficient, because the probability of a successful query in the P2P network is reasonably increased. For the validation of the models, we evaluated a series of simulations that supported our results.Keywords: Peer-to-Peer, model, performance, networkmanagement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12972767 Prediction of the Epileptic Events 'Epileptic Seizures' by Neural Networks and Expert Systems
Authors: Kifah Tout, Nisrine Sinno, Mohamad Mikati
Abstract:
Many studies have focused on the nonlinear analysis of electroencephalography (EEG) mainly for the characterization of epileptic brain states. It is assumed that at least two states of the epileptic brain are possible: the interictal state characterized by a normal apparently random, steady-state EEG ongoing activity; and the ictal state that is characterized by paroxysmal occurrence of synchronous oscillations and is generally called in neurology, a seizure. The spatial and temporal dynamics of the epileptogenic process is still not clear completely especially the most challenging aspects of epileptology which is the anticipation of the seizure. Despite all the efforts we still don-t know how and when and why the seizure occurs. However actual studies bring strong evidence that the interictal-ictal state transition is not an abrupt phenomena. Findings also indicate that it is possible to detect a preseizure phase. Our approach is to use the neural network tool to detect interictal states and to predict from those states the upcoming seizure ( ictal state). Analysis of the EEG signal based on neural networks is used for the classification of EEG as either seizure or non-seizure. By applying prediction methods it will be possible to predict the upcoming seizure from non-seizure EEG. We will study the patients admitted to the epilepsy monitoring unit for the purpose of recording their seizures. Preictal, ictal, and post ictal EEG recordings are available on such patients for analysis The system will be induced by taking a body of samples then validate it using another. Distinct from the two first ones a third body of samples is taken to test the network for the achievement of optimum prediction. Several methods will be tried 'Backpropagation ANN' and 'RBF'.Keywords: Artificial neural network (ANN), automatic prediction, epileptic seizures analysis, genetic algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15322766 Artificial Neural Network Application on Ti/Al Joint Using Laser Beam Welding – A Review
Authors: K. Kalaiselvan, A. Elango, N. M. Nagarajan
Abstract:
Today automobile and aerospace industries realise Laser Beam Welding for a clean and non contact source of heating and fusion for joining of sheets. The welding performance is mainly based on by the laser welding parameters. Some concepts related to Artificial Neural Networks and how can be applied to model weld bead geometry and mechanical properties in terms of equipment parameters are reported in order to evaluate the accuracy and compare it with traditional modeling schemes. This review reveals the output features of Titanium and Aluminium weld bead geometry and mechanical properties such as ultimate tensile strength, yield strength, elongation and reduction of the area of the weld using Artificial Neural Network.
Keywords: Laser Beam Welding (LBW), Artificial Neural Networks (ANN), Optimization, Titanium and Aluminium sheets.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23442765 Energy Efficient Clustering and Data Aggregation in Wireless Sensor Networks
Authors: Surender Kumar Soni
Abstract:
Wireless Sensor Networks (WSNs) are wireless networks consisting of number of tiny, low cost and low power sensor nodes to monitor various physical phenomena like temperature, pressure, vibration, landslide detection, presence of any object, etc. The major limitation in these networks is the use of nonrechargeable battery having limited power supply. The main cause of energy consumption WSN is communication subsystem. This paper presents an efficient grid formation/clustering strategy known as Grid based level Clustering and Aggregation of Data (GCAD). The proposed clustering strategy is simple and scalable that uses low duty cycle approach to keep non-CH nodes into sleep mode thus reducing energy consumption. Simulation results demonstrate that our proposed GCAD protocol performs better in various performance metrics.Keywords: Ad hoc network, Cluster, Grid base clustering, Wireless sensor network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 31262764 Decision Support System for Flood Crisis Management using Artificial Neural Network
Authors: Muhammad Aqil, Ichiro Kita, Akira Yano, Nishiyama Soichi
Abstract:
This paper presents an alternate approach that uses artificial neural network to simulate the flood level dynamics in a river basin. The algorithm was developed in a decision support system environment in order to enable users to process the data. The decision support system is found to be useful due to its interactive nature, flexibility in approach and evolving graphical feature and can be adopted for any similar situation to predict the flood level. The main data processing includes the gauging station selection, input generation, lead-time selection/generation, and length of prediction. This program enables users to process the flood level data, to train/test the model using various inputs and to visualize results. The program code consists of a set of files, which can as well be modified to match other purposes. This program may also serve as a tool for real-time flood monitoring and process control. The running results indicate that the decision support system applied to the flood level seems to have reached encouraging results for the river basin under examination. The comparison of the model predictions with the observed data was satisfactory, where the model is able to forecast the flood level up to 5 hours in advance with reasonable prediction accuracy. Finally, this program may also serve as a tool for real-time flood monitoring and process control.Keywords: Decision Support System, Neural Network, Flood Level
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16182763 A Practical Scheme for Transmission Loss Allocation to Generators and Loads in Restructured Power Systems
Authors: M.R. Ebrahimi, M. Ehsan
Abstract:
This paper presents a practical scheme that can be used for allocating the transmission loss to generators and loads. In this scheme first the share of a generator or load on the current through a branch is determined using Z-bus modified matrix. Then the current components are decomposed and the branch loss allocation is obtained. A motivation of proposed scheme is to improve the results of Z-bus method and to reach more fair allocation. The proposed scheme has been implemented and tested on several networks. To achieve practical and applicable results, the proposed scheme is simulated and compared on the transmission network (400kv) of Khorasan region in Iran and the 14-bus standard IEEE network. The results show that the proposed scheme is comprehensive and fair to allocating the energy losses of a power market to its participants.
Keywords: Transmission Loss, Loss Allocation, Z-bus modifiedmatrix, current Components Decomposition and Restructured PowerSystems
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14972762 Validation of Solar PV Inverter Harmonics Behaviour at Different Power Levels in a Test Network
Authors: Wilfred Fritz
Abstract:
Grid connected solar PV inverters need to be compliant to standard regulations regarding unwanted harmonic generation. This paper gives an introduction to harmonics, solar PV inverter voltage regulation and balancing through compensation and investigates the behaviour of harmonic generation at different power levels. Practical measurements of harmonics and power levels with a power quality data logger were made, on a test network at a university in Germany. The test setup and test results are discussed. The major finding was that between the morning and afternoon load peak windows when the PV inverters operate under low solar insolation and low power levels, more unwanted harmonics are generated. This has a huge impact on the power quality of the grid as well as capital and maintenance costs. The design of a single-tuned harmonic filter towards harmonic mitigation is presented.
Keywords: Harmonics, power quality, pulse width modulation, total harmonic distortion.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18312761 A Neural Approach for the Offline Recognition of the Arabic Handwritten Words of the Algerian Departments
Authors: Salim Ouchtati, Jean Sequeira, Mouldi Bedda
Abstract:
In the context of the handwriting recognition, we propose an off line system for the recognition of the Arabic handwritten words of the Algerian departments. The study is based mainly on the evaluation of neural network performances, trained with the gradient back propagation algorithm. The used parameters to form the input vector of the neural network are extracted on the binary images of the handwritten word by several methods. The Distribution parameters, the centered moments of the different projections of the different segments, the centered moments of the word image coding according to the directions of Freeman, and the Barr features applied binary image of the word and on its different segments. The classification is achieved by a multi layers perceptron. A detailed experiment is carried and satisfactory recognition results are reported.Keywords: Handwritten word recognition, neural networks, image processing, pattern recognition, features extraction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18932760 RV-YOLOX: Object Detection on Inland Waterways Based on Optimized YOLOX through Fusion of Vision and 3+1D Millimeter Wave Radar
Authors: Zixian Zhang, Shanliang Yao, Zile Huang, Zhaodong Wu, Xiaohui Zhu, Yong Yue, Jieming Ma
Abstract:
Unmanned Surface Vehicles (USVs) hold significant value for their capacity to undertake hazardous and labor-intensive operations over aquatic environments. Object detection tasks are significant in these applications. Nonetheless, the efficacy of USVs in object detection is impeded by several intrinsic challenges, including the intricate dispersal of obstacles, reflections emanating from coastal structures, and the presence of fog over water surfaces, among others. To address these problems, this paper provides a fusion method for USVs to effectively detect objects in the inland surface environment, utilizing vision sensors and 3+1D Millimeter-wave radar. The MMW radar is a complementary tool to vision sensors, offering reliable environmental data. This approach involves the conversion of the radar’s 3D point cloud into a 2D radar pseudo-image, thereby standardizing the format for radar and vision data by leveraging a point transformer. Furthermore, this paper proposes the development of a multi-source object detection network, named RV-YOLOX, which leverages radar-vision integration specifically tailored for inland waterway environments. The performance is evaluated on our self-recording waterways dataset. Compared with the YOLOX network, our fusion network significantly improves detection accuracy, especially for objects with bad light conditions.
Keywords: Inland waterways, object detection, YOLO, sensor fusion, self-attention, deep learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2242759 Systematic Analysis of Dynamic Association of Health Outcomes with Computer Usage for Office Staff
Authors: Xiaoshu Lu, Esa-Pekka Takala, Risto Toivonen
Abstract:
This paper systematically investigates the timedependent health outcomes for office staff during computer work using the developed mathematical model. The model describes timedependent health outcomes in multiple body regions associated with computer usage. The association is explicitly presented with a doseresponse relationship which is parametrized by body region parameters. Using the developed model we perform extensive investigations of the health outcomes statically and dynamically. We compare the risk body regions and provide various severity rankings of the discomfort rate changes with respect to computer-related workload dynamically for the study population. Application of the developed model reveals a wide range of findings. Such broad spectrum of investigations in a single report literature is lacking. Based upon the model analysis, it is discovered that the highest average severity level of the discomfort exists in neck, shoulder, eyes, shoulder joint/upper arm, upper back, low back and head etc. The biggest weekly changes of discomfort rates are in eyes, neck, head, shoulder, shoulder joint/upper arm and upper back etc. The fastest discomfort rate is found in neck, followed by shoulder, eyes, head, shoulder joint/upper arm and upper back etc. Most of our findings are consistent with the literature, which demonstrates that the developed model and results are applicable and valuable and can be utilized to assess correlation between the amount of computer-related workload and health risk.Keywords: Computer-related workload, health outcomes, dynamic association, dose-response relationship, systematic analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12782758 Optimal Efficiency Control of Pulse Width Modulation - Inverter Fed Motor Pump Drive Using Neural Network
Authors: O. S. Ebrahim, M. A. Badr, A. S. Elgendy, K. O. Shawky, P. K. Jain
Abstract:
This paper demonstrates an improved Loss Model Control (LMC) for a 3-phase induction motor (IM) driving pump load. Compared with other power loss reduction algorithms for IM, the presented one has the advantages of fast and smooth flux adaptation, high accuracy, and versatile implementation. The performance of LMC depends mainly on the accuracy of modeling the motor drive and losses. A loss-model for IM drive that considers the surplus power loss caused by inverter voltage harmonics using closed-form equations and also includes the magnetic saturation has been developed. Further, an Artificial Neural Network (ANN) controller is synthesized and trained offline to determine the optimal flux level that achieves maximum drive efficiency. The drive’s voltage and speed control loops are connecting via the stator frequency to avoid the possibility of excessive magnetization. Besides, the resistance change due to temperature is considered by a first-order thermal model. The obtained thermal information enhances motor protection and control. These together have the potential of making the proposed algorithm reliable. Simulation and experimental studies are performed on 5.5 kW test motor using the proposed control method. The test results are provided and compared with the fixed flux operation to validate the effectiveness.
Keywords: Artificial neural network, ANN, efficiency optimization, induction motor, IM, Pulse Width Modulated, PWM, harmonic losses.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3342757 Addressing Security Concerns of Data Exchange in AODV Protocol
Authors: Monis Akhlaq, M Noman Jafri, Muzammil A Khan, Baber Aslam
Abstract:
The Ad Hoc on demand distance vector (AODV) routing protocol is designed for mobile ad hoc networks (MANETs). AODV offers quick adaptation to dynamic link conditions; it is characterized by low memory overhead and low network utilization. The security issues related to the protocol remain challenging for the wireless network designers. Numerous schemes have been proposed for establishing secure communication between end users, these schemes identify that the secure operation of AODV is a bi tier task (routing and secure exchange of information at separate levels). Our endeavor in this paper would focus on achieving the routing and secure data exchange in a single step. This will facilitate the user nodes to perform routing, mutual authentications, generation and secure exchange of session key in one step thus ensuring confidentiality, integrity and authentication of data exchange in a more suitable way.
Keywords: AODV, key management, security, wirelessnetworks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20822756 A Lifetime-Guaranteed Routing Scheme in Wireless Sensor Networks
Authors: Jae Keun Park, Sung Je Hong, Kyong Hoon Kim, Tae Heum Kang, Wan Yeon Lee
Abstract:
In this paper, we propose a routing scheme that guarantees the residual lifetime of wireless sensor networks where each sensor node operates with a limited budget of battery energy. The scheme maximizes the communications QoS while sustaining the residual battery lifetime of the network for a specified duration. Communication paths of wireless nodes are translated into a directed acyclic graph(DAG) and the maximum-flow algorithm is applied to the graph. The found maximum flow are assigned to sender nodes, so as to maximize their communication QoS. Based on assigned flows, the scheme determines the routing path and the transmission rate of data packet so that any sensor node on the path would not exhaust its battery energy before a specified duration.Keywords: Sensor network, battery, residual lifetime, routingscheme, QoS
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16252755 OCR For Printed Urdu Script Using Feed Forward Neural Network
Authors: Inam Shamsher, Zaheer Ahmad, Jehanzeb Khan Orakzai, Awais Adnan
Abstract:
This paper deals with an Optical Character Recognition system for printed Urdu, a popular Pakistani/Indian script and is the third largest understandable language in the world, especially in the subcontinent but fewer efforts are made to make it understandable to computers. Lot of work has been done in the field of literature and Islamic studies in Urdu, which has to be computerized. In the proposed system individual characters are recognized using our own proposed method/ algorithms. The feature detection methods are simple and robust. Supervised learning is used to train the feed forward neural network. A prototype of the system has been tested on printed Urdu characters and currently achieves 98.3% character level accuracy on average .Although the system is script/ language independent but we have designed it for Urdu characters only.Keywords: Algorithm, Feed Forward Neural Networks, Supervised learning, Pattern Matching.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 30192754 An ANN-Based Predictive Model for Diagnosis and Forecasting of Hypertension
Authors: O. O. Obe, V. Balanica, E. Neagoe
Abstract:
The effects of hypertension are often lethal thus its early detection and prevention is very important for everybody. In this paper, a neural network (NN) model was developed and trained based on a dataset of hypertension causative parameters in order to forecast the likelihood of occurrence of hypertension in patients. Our research goal was to analyze the potential of the presented NN to predict, for a period of time, the risk of hypertension or the risk of developing this disease for patients that are or not currently hypertensive. The results of the analysis for a given patient can support doctors in taking pro-active measures for averting the occurrence of hypertension such as recommendations regarding the patient behavior in order to lower his hypertension risk. Moreover, the paper envisages a set of three example scenarios in order to determine the age when the patient becomes hypertensive, i.e. determine the threshold for hypertensive age, to analyze what happens if the threshold hypertensive age is set to a certain age and the weight of the patient if being varied, and, to set the ideal weight for the patient and analyze what happens with the threshold of hypertensive age.
Keywords: Neural Network, hypertension, data set, training set, supervised learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16542753 Intelligent Rescheduling Trains for Air Pollution Management
Authors: Kainat Affrin, P. Reshma, G. Narendra Kumar
Abstract:
Optimization of timetable is the need of the day for the rescheduling and routing of trains in real time. Trains are scheduled in parallel with the road transport vehicles to the same destination. As the number of trains is restricted due to single track, customers usually opt for road transport to use frequently. The air pollution increases as the density of vehicles on road transport is increased. Use of an alternate mode of transport like train helps in reducing air-pollution. This paper mainly aims at attracting the passengers to Train transport by proper rescheduling of trains using hybrid of stop-skip algorithm and iterative convex programming algorithm. Rescheduling of train bi-directionally is achieved on a single track with dynamic dual time and varying stops. Introduction of more trains attract customers to use rail transport frequently, thereby decreasing the pollution. The results are simulated using Network Simulator (NS-2).Keywords: Air pollution, routing protocol, network simulator, rescheduling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9682752 A Pilot Study for the Optimization of Routes for Waste Collection Vehicles for the Göçmenköy District of Lefkoşa
Authors: Nergiz Fırıncı, Aysun Çelik, Ertan Akün, Md. Atif Khan
Abstract:
A pilot project was carried out in 2007 by the senior students of Cyprus International University, aiming to minimize the total cost of waste collection in Northern Cyprus. Many developed and developing countries have cut their transportation costs – which lies between 30-40% – down at a rate of 40% percent, by implementing network models for their route assignments. Accordingly, a network model was implemented at Göçmenköy district, to optimize and standardize waste collection works. The work environment of the employees were also redesigned to provide maximum ergonomy and to increase productivity, efficiency and safety. Following the collection of the required data including waste densities, lengths of roads and population, a model was constructed to allocate the optimal route assignment for the waste collection trucks at Göçmenköy district.Keywords: Minimization, waste collection, operations cost, transportation, ergonomy, productivity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2657