Search results for: goal-seeking neural network
3795 Computer Network Applications, Practical Implementations and Structural Control System Representations
Authors: El Miloudi Djelloul
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The computer network play an important position for practical implementations of the differently system. To implement a system into network above all is needed to know all the configurations, which is responsible to be a part of the system, and to give adequate information and solution in realtime. So if want to implement this system for example in the school or relevant institutions, the first step is to analyze the types of model which is needed to be configured and another important step is to organize the works in the context of devices, as a part of the general system. Often before configuration, as important point is descriptions and documentations from all the works into the respective process, and then to organize in the aspect of problem-solving. The computer network as critic infrastructure is very specific so the paper present the effectiveness solutions in the structured aspect viewed from one side, and another side is, than the paper reflect the positive aspect in the context of modeling and block schema presentations as an better alternative to solve the specific problem because of continually distortions of the system from the line of devices, programs and signals or packed collisions, which are in movement from one computer node to another nodes.Keywords: local area networks, LANs, block schema presentations, computer network system, computer node, critical infrastructure packed collisions, structural control system representations, computer network, implementations, modeling structural representations, companies, computers, context, control systems, internet, software
Procedia PDF Downloads 3493794 A Survey on Various Technique of Modified TORA over MANET
Authors: Shreyansh Adesara, Sneha Pandiya
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The mobile ad-hoc network (MANET) is an important and open area research for the examination and determination of the performance evolution. Temporary ordered routing algorithm (TORA) is adaptable and distributed MANET routing algorithm which is totally dependent on internet MANET Encapsulation protocol (IMEP) for the detection of the link and sensing of the link. If IMEP detect the wrong link failure then the network suffer from congestion and unnecessary route maintenance. Thus, the improvement in link detection method of TORA is introduced by various methods on IMEP by different perspective from different person. There are also different reactive routing protocols like AODV, TORA and DSR has been compared for the knowledge of the routing scenario for different parameter and using different model.Keywords: IMEP, mobile ad-hoc network, protocol, TORA
Procedia PDF Downloads 4363793 To Design an Architectural Model for On-Shore Oil Monitoring Using Wireless Sensor Network System
Authors: Saurabh Shukla, G. N. Pandey
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In recent times, oil exploration and monitoring in on-shore areas have gained much importance considering the fact that in India the oil import is 62 percent of the total imports. Thus, architectural model like wireless sensor network to monitor on-shore deep sea oil well is being developed to get better estimate of the oil prospects. The problem we are facing nowadays that we have very few restricted areas of oil left today. Countries like India don’t have much large areas and resources for oil and this problem with most of the countries that’s why it has become a major problem when we are talking about oil exploration in on-shore areas also the increase of oil prices has further ignited the problem. For this the use of wireless network system having relative simplicity, smallness in size and affordable cost of wireless sensor nodes permit heavy deployment in on-shore places for monitoring oil wells. Deployment of wireless sensor network in large areas will surely reduce the cost it will be very much cost effective. The objective of this system is to send real time information of oil monitoring to the regulatory and welfare authorities so that suitable action could be taken. This system architecture is composed of sensor network, processing/transmission unit and a server. This wireless sensor network system could remotely monitor the real time data of oil exploration and monitoring condition in the identified areas. For wireless sensor networks, the systems are wireless, have scarce power, are real-time, utilize sensors and actuators as interfaces, have dynamically changing sets of resources, aggregate behaviour is important and location is critical. In this system a communication is done between the server and remotely placed sensors. The server gives the real time oil exploration and monitoring conditions to the welfare authorities.Keywords: sensor, wireless sensor network, oil, sensor, on-shore level
Procedia PDF Downloads 4373792 Network User Rules in Universities
Authors: Michel Berthiaume, Daniel Chamberland-Tremblay, Elaine Paiva Mosconi, Jérôme Blanchet-Brisson
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This presentation documents the overall failure of North-American universities to build an effective IT Policies communication with their primary users: the students. A sample of 12 universities was selected. A set of indicators based on usability principles to assess the content of IT Policies vas devised. Then, IT Policies were rated according to the indicators and the results analyzed to build an overall picture of the potential of communication problems in policy communication. The initial finding is that network security professionals in Universities have to reach a delicate balance between asset protection, asset valorization and user security awareness.Keywords: computer security, IT policy, security awareness, network user rules
Procedia PDF Downloads 5513791 Investigating the Factors Affecting Generalization of Deep Learning Models for Plant Disease Detection
Authors: Praveen S. Muthukumarana, Achala C. Aponso
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A large percentage of global crop harvest is lost due to crop diseases. Timely identification and treatment of crop diseases is difficult in many developing nations due to insufficient trained professionals in the field of agriculture. Many crop diseases can be accurately diagnosed by visual symptoms. In the past decade, deep learning has been successfully utilized in domains such as healthcare but adoption in agriculture for plant disease detection is rare. The literature shows that models trained with popular datasets such as PlantVillage does not generalize well on real world images. This paper attempts to find out how to make plant disease identification models that generalize well with real world images.Keywords: agriculture, convolutional neural network, deep learning, plant disease classification, plant disease detection, plant disease diagnosis
Procedia PDF Downloads 1353790 Performance Analysis of Ad-Hoc Network Routing Protocols
Authors: I. Baddari, A. Riahla, M. Mezghich
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Today in the literature, we discover a lot of routing algorithms which some have been the subject of normalization. Two great classes Routing algorithms are defined, the first is the class reactive algorithms and the second that of algorithms proactive. The aim of this work is to make a comparative study between some routing algorithms. Two comparisons are considered. The first will focus on the protocols of the same class and second class on algorithms of different classes (one reactive and the other proactive). Since they are not based on analytical models, the exact evaluation of some aspects of these protocols is challenging. Simulations have to be done in order to study their performances. Our simulation is performed in NS2 (Network Simulator 2). It identified a classification of the different routing algorithms studied in a metrics such as loss of message, the time transmission, mobility, etc.Keywords: ad-hoc network routing protocol, simulation, NS2, delay, packet loss, wideband, mobility
Procedia PDF Downloads 3923789 Mathematical Modeling for Diabetes Prediction: A Neuro-Fuzzy Approach
Authors: Vijay Kr. Yadav, Nilam Rathi
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Accurate prediction of glucose level for diabetes mellitus is required to avoid affecting the functioning of major organs of human body. This study describes the fundamental assumptions and two different methodologies of the Blood glucose prediction. First is based on the back-propagation algorithm of Artificial Neural Network (ANN), and second is based on the Neuro-Fuzzy technique, called Fuzzy Inference System (FIS). Errors between proposed methods further discussed through various statistical methods such as mean square error (MSE), normalised mean absolute error (NMAE). The main objective of present study is to develop mathematical model for blood glucose prediction before 12 hours advanced using data set of three patients for 60 days. The comparative studies of the accuracy with other existing models are also made with same data set.Keywords: back-propagation, diabetes mellitus, fuzzy inference system, neuro-fuzzy
Procedia PDF Downloads 2473788 Utilization of Secure Wireless Networks as Environment for Learning and Teaching in Higher Education
Authors: Mohammed A. M. Ibrahim
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This paper investigate the utilization of wire and wireless networks to be platform for distributed educational monitoring system. Universities in developing countries suffer from a lot of shortages(staff, equipment, and finical budget) and optimal utilization of the wire and wireless network, so universities can mitigate some of the mentioned problems and avoid the problems that maybe humble the education processes in many universities by using our implementation of the examinations system as a test-bed to utilize the network as a solution to the shortages for academic staff in Taiz University. This paper selects a two areas first one quizzes activities is only a test bed application for wireless network learning environment system to be distributed among students. Second area is the features and the security of wireless, our tested application implemented in a promising area which is the use of WLAN in higher education for leering environment.Keywords: networking wire and wireless technology, wireless network security, distributed computing, algorithm, encryption and decryption
Procedia PDF Downloads 3293787 mKDNAD: A Network Flow Anomaly Detection Method Based On Multi-teacher Knowledge Distillation
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Anomaly detection models for network flow based on machine learning have poor detection performance under extremely unbalanced training data conditions and also have slow detection speed and large resource consumption when deploying on network edge devices. Embedding multi-teacher knowledge distillation (mKD) in anomaly detection can transfer knowledge from multiple teacher models to a single model. Inspired by this, we proposed a state-of-the-art model, mKDNAD, to improve detection performance. mKDNAD mine and integrate the knowledge of one-dimensional sequence and two-dimensional image implicit in network flow to improve the detection accuracy of small sample classes. The multi-teacher knowledge distillation method guides the train of the student model, thus speeding up the model's detection speed and reducing the number of model parameters. Experiments in the CICIDS2017 dataset verify the improvements of our method in the detection speed and the detection accuracy in dealing with the small sample classes.Keywords: network flow anomaly detection (NAD), multi-teacher knowledge distillation, machine learning, deep learning
Procedia PDF Downloads 1123786 Measuring Delay Using Software Defined Networks: Limitations, Challenges, and Suggestions for Openflow
Authors: Ahmed Alutaibi, Ganti Sudhakar
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Providing better Quality-of-Service (QoS) to end users has been a challenging problem for researchers and service providers. Building applications relying on best effort network protocols hindered the adoption of guaranteed service parameters and, ultimately, Quality of Service. The introduction of Software Defined Networking (SDN) opened the door for a new paradigm shift towards a more controlled programmable configurable behavior. Openflow has been and still is the main implementation of the SDN vision. To facilitate better QoS for applications, the network must calculate and measure certain parameters. One of those parameters is the delay between the two ends of the connection. Using the power of SDN and the knowledge of application and network behavior, SDN networks can adjust to different conditions and specifications. In this paper, we use the capabilities of SDN to implement multiple algorithms to measure delay end-to-end not only inside the SDN network. The results of applying the algorithms on an emulated environment show that we can get measurements close to the emulated delay. The results also show that depending on the algorithm, load on the network and controller can differ. In addition, the transport layer handshake algorithm performs best among the tested algorithms. Out of the results and implementation, we show the limitations of Openflow and develop suggestions to solve them.Keywords: software defined networking, quality of service, delay measurement, openflow, mininet
Procedia PDF Downloads 1573785 Analytical Study of Data Mining Techniques for Software Quality Assurance
Authors: Mariam Bibi, Rubab Mehboob, Mehreen Sirshar
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Satisfying the customer requirements is the ultimate goal of producing or developing any product. The quality of the product is decided on the bases of the level of customer satisfaction. There are different techniques which have been reported during the survey which enhance the quality of the product through software defect prediction and by locating the missing software requirements. Some mining techniques were proposed to assess the individual performance indicators in collaborative environment to reduce errors at individual level. The basic intention is to produce a product with zero or few defects thereby producing a best product quality wise. In the analysis of survey the techniques like Genetic algorithm, artificial neural network, classification and clustering techniques and decision tree are studied. After analysis it has been discovered that these techniques contributed much to the improvement and enhancement of the quality of the product.Keywords: data mining, defect prediction, missing requirements, software quality
Procedia PDF Downloads 4583784 Indoor Temperature Estimation with FIR Filter Using R-C Network Model
Authors: Sung Hyun You, Jeong Hoon Kim, Dae Ki Kim, Choon Ki Ahn
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In this paper, we proposed a new strategy for estimating indoor temperature based on the modified resistance capacitance (R–C) network thermal dynamic model. Using minimum variance finite impulse response (FIR) filter, accurate indoor temperature estimation can be achieved. Our study is clarified by the experimental validation of the proposed indoor temperature estimation method. This experiment scenario environment is composed of a demand response (DR) server and home energy management system (HEMS) in a test bed.Keywords: energy consumption, resistance-capacitance network model, demand response, finite impulse response filter
Procedia PDF Downloads 4383783 Tail-Binding Effect of Kinesin-1 Auto Inhibition Using Elastic Network Model
Authors: Hyun Joon Chang, Jae In Kim, Sungsoo Na
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Kinesin-1 (hereafter called kinesin) is a molecular motor protein that moves cargos toward the end of microtubules using the energy of adenosine triphosphate (ATP) hydrolysis. When kinesin is inactive, its tail autoinhibits the motor chain in order to prevent from reacting with the ATP by cross-linking of the tail domain to the motor domains at two positions. However, the morphological study of kinesin during autoinhibition is yet remained obscured. In this study, we report the effect of the binding site of the tail domain using the normal mode analysis of the elastic network model on kinesin in the tail-free form and tail-bind form. Considering the relationship between the connectivity of conventional network model with respect to the cutoff length and the functionality of the binding site of the tail, we revaluated the network model to observe the key role of the tail domain in its structural aspect. Contingent on the existence of the tail domain, the results suggest the morphological stability of the motor domain. Furthermore, employing the results from normal mode analysis, we have determined the strain energy of the neck linker, an essential portion of the motor domain for ATP hydrolysis. The results of the neck linker also converge to the same indication, i.e. the morphological analysis of the motor domain.Keywords: elastic network model, Kinesin-1, autoinhibition
Procedia PDF Downloads 4463782 Intelligent Adaptive Learning in a Changing Environment
Authors: G. Valentis, Q. Berthelot
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Nowadays the trend to develop ever more intelligent and autonomous systems often takes its inspiration in the living beings on Earth. Some simple isolated systems are able, once brought together, to form a strong and reliable system. When trying to adapt the idea to man-made systems it is not possible to include in their program everything the system may encounter during its life cycle. It is, thus, necessary to make the system able to take decisions based on other criteria such as its past experience, i.e. to make the system learn on its own. However, at some point the acquired knowledge depends also on environment. So the question is: if system environment is modified, how could the system respond to it quickly and appropriately enough? Here, starting from reinforcement learning to rate its decisions, and using adaptive learning algorithms for gain and loss reward, the system is made able to respond to changing environment and to adapt its knowledge as time passes. Application is made to a robot finding an exit in a labyrinth.Keywords: reinforcement learning, neural network, autonomous systems, adaptive learning, changing environment
Procedia PDF Downloads 4163781 Real Time Traffic Performance Study over MPLS VPNs with DiffServ
Authors: Naveed Ghani
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With the arrival of higher speed communication links and mature application running over the internet, the requirement for reliable, efficient and robust network designs rising day by day. Multi-Protocol Label Switching technology (MPLS) Virtual Private Networks (VPNs) have committed to provide optimal network services. They are gaining popularity in industry day by day. Enterprise customers are moving to service providers that offer MPLS VPNs. The main reason for this shifting is the capability of MPLS VPN to provide built in security features and any-to-any connectivity. MPLS VPNs improved the network performance due to fast label switching as compare to traditional IP Forwarding but traffic classification and policing was still required on per hop basis to enhance the performance of real time traffic which is delay sensitive (particularly voice and video). QoS (Quality of service) is the most important factor to prioritize enterprise networks’ real time traffic such as voice and video. This thesis is focused on the study of QoS parameters (e.g. delay, jitter and MOS (Mean Opinion Score)) for the real time traffic over MPLS VPNs. DiffServ (Differentiated Services) QoS model will be used over MPLS VPN network to get end-to-end service quality.Keywords: network, MPLS, VPN, DiffServ, MPLS VPN, DiffServ QoS, QoS Model, GNS2
Procedia PDF Downloads 4193780 Distributed Automation System Based Remote Monitoring of Power Quality Disturbance on LV Network
Authors: Emmanuel D. Buedi, K. O. Boateng, Griffith S. Klogo
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Electrical distribution networks are prone to power quality disturbances originating from the complexity of the distribution network, mode of distribution (overhead or underground) and types of loads used by customers. Data on the types of disturbances present and frequency of occurrence is needed for economic evaluation and hence finding solution to the problem. Utility companies have resorted to using secondary power quality devices such as smart meters to help gather the required data. Even though this approach is easier to adopt, data gathered from these devices may not serve the required purpose, since the installation of these devices in the electrical network usually does not conform to available PQM placement methods. This paper presents a design of a PQM that is capable of integrating into an existing DAS infrastructure to take advantage of available placement methodologies. The monitoring component of the design is implemented and installed to monitor an existing LV network. Data from the monitor is analyzed and presented. A portion of the LV network of the Electricity Company of Ghana is modeled in MATLAB-Simulink and analyzed under various earth fault conditions. The results presented show the ability of the PQM to detect and analyze PQ disturbance such as voltage sag and overvoltage. By adopting a placement methodology and installing these nodes, utilities are assured of accurate and reliable information with respect to the quality of power delivered to consumers.Keywords: power quality, remote monitoring, distributed automation system, economic evaluation, LV network
Procedia PDF Downloads 3423779 Developing Pavement Maintenance Management System (PMMS) for Small Cities, Aswan City Case Study
Authors: Ayman Othman, Tallat Ali
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A pavement maintenance management system (PMMS) was developed for the city of Aswan as a model of a small city to provide the road maintenance department in Aswan city with the capabilities for comprehensive planning of the maintenance activities needed to put the internal pavement network into desired physical condition in view of maintenance budget constraints. The developed system consists of three main stages. First is the inventory & condition survey stage where the internal pavement network of Aswan city was inventoried and its actual conditions were rated in segments of 100 meters length. Second is the analysis stage where pavement condition index (PCI) was calculated and the most appropriate maintenance actions were assigned for each segment. The total maintenance budget was also estimated and a parameter based ranking criteria were developed to prioritize maintenance activities when the available maintenance budget is not sufficient. Finally comes the packaging stage where approved maintenance budget is packed into maintenance projects for field implementation. System results indicate that, the system output maintenance budget is very reasonable and the system output maintenance programs agree to a great extent with the actual maintenance needs of the network. Condition survey of Aswan city road network showed that roughness is the most dominate distress. In general, the road network can be considered in a fairly reasonable condition, however, the developed PMMS needs to be officially adapted to maintain the road network in a desirable condition and to prevent further deterioration.Keywords: pavement, maintenance, management, system, distresses, survey, ranking
Procedia PDF Downloads 2393778 A Memetic Algorithm Approach to Clustering in Mobile Wireless Sensor Networks
Authors: Masood Ahmad, Ataul Aziz Ikram, Ishtiaq Wahid
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Wireless sensor network (WSN) is the interconnection of mobile wireless nodes with limited energy and memory. These networks can be deployed formany critical applications like military operations, rescue management, fire detection and so on. In flat routing structure, every node plays an equal role of sensor and router. The topology may change very frequently due to the mobile nature of nodes in WSNs. The topology maintenance may produce more overhead messages. To avoid topology maintenance overhead messages, an optimized cluster based mobile wireless sensor network using memetic algorithm is proposed in this paper. The nodes in this network are first divided into clusters. The cluster leaders then transmit data to that base station. The network is validated through extensive simulation study. The results show that the proposed technique has superior results compared to existing techniques.Keywords: WSN, routing, cluster based, meme, memetic algorithm
Procedia PDF Downloads 4753777 Tensor Deep Stacking Neural Networks and Bilinear Mapping Based Speech Emotion Classification Using Facial Electromyography
Authors: P. S. Jagadeesh Kumar, Yang Yung, Wenli Hu
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Speech emotion classification is a dominant research field in finding a sturdy and profligate classifier appropriate for different real-life applications. This effort accentuates on classifying different emotions from speech signal quarried from the features related to pitch, formants, energy contours, jitter, shimmer, spectral, perceptual and temporal features. Tensor deep stacking neural networks were supported to examine the factors that influence the classification success rate. Facial electromyography signals were composed of several forms of focuses in a controlled atmosphere by means of audio-visual stimuli. Proficient facial electromyography signals were pre-processed using moving average filter, and a set of arithmetical features were excavated. Extracted features were mapped into consistent emotions using bilinear mapping. With facial electromyography signals, a database comprising diverse emotions will be exposed with a suitable fine-tuning of features and training data. A success rate of 92% can be attained deprived of increasing the system connivance and the computation time for sorting diverse emotional states.Keywords: speech emotion classification, tensor deep stacking neural networks, facial electromyography, bilinear mapping, audio-visual stimuli
Procedia PDF Downloads 2443776 Wind Speed Prediction Using Passive Aggregation Artificial Intelligence Model
Authors: Tarek Aboueldahab, Amin Mohamed Nassar
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Wind energy is a fluctuating energy source unlike conventional power plants, thus, it is necessary to accurately predict short term wind speed to integrate wind energy in the electricity supply structure. To do so, we present a hybrid artificial intelligence model of short term wind speed prediction based on passive aggregation of the particle swarm optimization and neural networks. As a result, improvement of the prediction accuracy is obviously obtained compared to the standard artificial intelligence method.Keywords: artificial intelligence, neural networks, particle swarm optimization, passive aggregation, wind speed prediction
Procedia PDF Downloads 4393775 The Urban Stray Animal Identification Management System Based on YOLOv5
Authors: Chen Xi, Kuan Sinman, LI Haofeng, Huang Hongming, Zeng Chengyu, Tong Zhiyuan
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Stray animals are on the rise in mainland China's cities. There are legal reasons for this, namely the lack of protection for domestic pets in mainland China, where only wildlife protection laws exist. At a social level, the ease with which families adopt pets and the lack of a social view of animal nature has led to the frequent abandonment and loss of stray animals. If left unmanaged, conflicts between humans and stray animals can also increase. This project provides an inexpensive and widely applicable management tool for urban management by collecting videos and pictures of stray animals captured by surveillance or transmitted by humans and using artificial intelligence technology (mainly using YOLOv5 recognition technology) and recording and managing them in a database.Keywords: urban planning, urban governance, artificial intelligence, convolutional neural network
Procedia PDF Downloads 983774 Location Privacy Preservation of Vehicle Data In Internet of Vehicles
Authors: Ying Ying Liu, Austin Cooke, Parimala Thulasiraman
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Internet of Things (IoT) has attracted a recent spark in research on Internet of Vehicles (IoV). In this paper, we focus on one research area in IoV: preserving location privacy of vehicle data. We discuss existing location privacy preserving techniques and provide a scheme for evaluating these techniques under IoV traffic condition. We propose a different strategy in applying Differential Privacy using k-d tree data structure to preserve location privacy and experiment on real world Gowalla data set. We show that our strategy produces differentially private data, good preservation of utility by achieving similar regression accuracy to the original dataset on an LSTM (Long Term Short Term Memory) neural network traffic predictor.Keywords: differential privacy, internet of things, internet of vehicles, location privacy, privacy preservation scheme
Procedia PDF Downloads 1693773 Literature Review: Application of Artificial Intelligence in EOR
Authors: Masoumeh Mofarrah, Amir NahanMoghadam
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Higher oil prices and increasing oil demand are main reasons for great attention to Enhanced Oil Recovery (EOR). Comprehensive researches have been accomplished to develop, appraise and improve EOR methods and their application. Recently Artificial Intelligence (AI) gained popularity in petroleum industry that can help petroleum engineers to solve some fundamental petroleum engineering problems such as reservoir simulation, EOR project risk analysis, well log interpretation and well test model selection. This study presents a historical overview of most popular AI tools including neural networks, genetic algorithms, fuzzy logic and expert systems in petroleum industry and discusses two case studies to represent the application of two mentioned AI methods for selecting an appropriate EOR method based on reservoir characterization in feasible and effective way.Keywords: artificial intelligence, EOR, neural networks, expert systems
Procedia PDF Downloads 3983772 MegaProjects and the Governing Processes That Lead to Success and Failure: A Literature Review
Authors: Fangwei Zhu, Wei Tian, Linzhuo Wang, Miao Yu
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Megaproject has long been a critical issue in project governance, for its low success rate and large impact on society. Although the extant literature on megaproject governance is vast, to our best knowledge, the lacking of a thorough literature review makes it hard for us to gain a holistic view on current scenario of megaproject governance. The study conducts a systematic literature review process to analyze the existing literatures on megaproject governance. The finding indicates that mega project governance needs to be handled at network level and forming a network level governance provides a holistic framework for governing megaproject towards sustainable development of the projects. Theoretical and practical implications, as well as future studies and limitations, were discussed.Keywords: megaproject, governance, literature review, network
Procedia PDF Downloads 1903771 Video-On-Demand QoE Evaluation across Different Age-Groups and Its Significance for Network Capacity
Authors: Mujtaba Roshan, John A. Schormans
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Quality of Experience (QoE) drives churn in the broadband networks industry, and good QoE plays a large part in the retention of customers. QoE is known to be affected by the Quality of Service (QoS) factors packet loss probability (PLP), delay and delay jitter caused by the network. Earlier results have shown that the relationship between these QoS factors and QoE is non-linear, and may vary from application to application. We use the network emulator Netem as the basis for experimentation, and evaluate how QoE varies as we change the emulated QoS metrics. Focusing on Video-on-Demand, we discovered that the reported QoE may differ widely for users of different age groups, and that the most demanding age group (the youngest) can require an order of magnitude lower PLP to achieve the same QoE than is required by the most widely studied age group of users. We then used a bottleneck TCP model to evaluate the capacity cost of achieving an order of magnitude decrease in PLP, and found it be (almost always) a 3-fold increase in link capacity that was required.Keywords: network capacity, packet loss probability, quality of experience, quality of service
Procedia PDF Downloads 2683770 Performance Evaluation of DSR and OLSR Routing Protocols in MANET Using Varying Pause Time
Authors: Yassine Meraihi, Dalila Acheli, Rabah Meraihi
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MANET for Mobile Ad hoc NETwork is a collection of wireless mobile nodes that communicates with each other without using any existing infrastructure, access point or centralized administration, due to the higher mobility and limited radio transmission range, routing is an important issue in ad hoc network, so in order to ensure reliable and efficient route between to communicating nodes quickly, an appropriate routing protocol is needed. In this paper, we present the performance analysis of two mobile ad hoc network routing protocols namely DSR and OLSR using NS2.34, the performance is determined on the basis of packet delivery ratio, throughput, average jitter and end to end delay with varying pause time.Keywords: DSR, OLSR, quality of service, routing protocols, MANET
Procedia PDF Downloads 5433769 Conceptual Knowledge Structure Updates after Instructor Provided Structural Feedback: An Exploratory Study Applied with Undergraduate Architectural Engineering Students
Authors: Roy B. Clariana, Ryan L. Solnosky
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Structural feedback is any form of feedback that aims to improve the quality of students’ domain-normative conceptual interrelationships. Research with structural feedback points to the potential mediating role of network graphs as feedback for tuning students’ conceptual understanding; for example, improved content knowledge and motivation were observed for undergraduate students who accessed the instructor’s networks of course content. This exploratory study uses a one-group pretest-posttest design to examine the effects of instructor-provided network feedback during lectures on students’ knowledge structure measured using a concept sorting task at the pretest and posttest. Undergraduate students in an architectural engineering course (n = 32) completed a lesson module and then an end-of-unit quiz on building with wood and wood framing. Three weeks later, as a review, students completed a sorting task that used 26 terms from that lesson, then a week later, the sorting task data were used to create a group-average network, this network along with the instructor’s expert network were added to that week’s lecture slides and were compared and discussed during class time. A week later, students completed the sorting task again. The pre and post-sorting data were rendered into pathfinder networks, and then these students’ networks were compared to five referent networks, specifically the textbook chapter network, the lecture slides network, a network of the end-of-unit quiz, the actual expert network that served as the feedback intervention, and the group-average network. Inspection of means shows that knowledge structure measures improved for all five measures from pre-to-post, becoming more like the lesson content and like the expert. Repeated measures analysis with follow-up paired samples t-tests showed pre-to-post significant increases for both the end-of-unit quiz and the expert network referents. The findings show that instructor presentation of structural feedback as networks improved or ‘tuned’ students’ knowledge structure of the lesson content. This approach only takes a few extra minutes of class time and is fairly simple to implement in ordinary classrooms, and so it has wide potential to support classroom instruction and student learning. Further research is needed to determine how critical it is to present both the group-average network along with the expert network for comparison in order to highlight group-level misconceptions, or is presenting only the expert network sufficient? If a group-level network is necessary, then a simple clicker-like classroom tool could be developed to collect sorting task data during lectures that could then immediately provide the group-average network for class discussion and reflection.Keywords: classroom instruction, engineering education, knowledge structure, pathfinder networks, structural feedback
Procedia PDF Downloads 583768 Evaluation of Collect Tree Protocol for Structural Health Monitoring System Using Wireless Sensor Networks
Authors: Amira Zrelli, Tahar Ezzedine
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Routing protocol may enhance the lifetime of sensor network, it has a highly importance, especially in wireless sensor network (WSN). Therefore, routing protocol has a big effect in these networks, thus the choice of routing protocol must be studied before setting up our network. In this work, we implement the routing protocol collect tree protocol (CTP) which is one of the hierarchic protocols used in structural health monitoring (SHM). Therefore, to evaluate the performance of this protocol, we choice to work with Contiki system and Cooja simulator. By throughput and RSSI evaluation of each node, we will deduce about the utility of CTP in structural monitoring system.Keywords: CTP, WSN, SHM, routing protocol
Procedia PDF Downloads 2863767 A Multi Agent Based Protection Scheme for Smart Distribution Network in Presence of Distributed Energy Resources
Authors: M. R. Ebrahimi, B. Mahdaviani
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Conventional electric distribution systems are radial in nature, supplied at one end through a main source. These networks generally have a simple protection system usually implemented using fuses, re-closers, and over-current relays. Recently, great attention has been paid to applying Distributed energy resources (DERs) throughout electric distribution systems. Presence of such generation in a network leads to losing coordination of protection devices. Therefore, it is desired to develop an algorithm which is capable of protecting distribution systems that include DER. On the other hand smart grid brings opportunities to the power system. Fast advancement in communication and measurement techniques accelerates the development of multi agent system (MAS). So in this paper, a new approach for the protection of distribution networks in the presence of DERs is presented base on MAS. The proposed scheme has been implemented on a sample 27-bus distribution network.Keywords: distributed energy resource, distribution network, protection, smart grid, multi agent system
Procedia PDF Downloads 6013766 Comparison of Feedforward Back Propagation and Self-Organizing Map for Prediction of Crop Water Stress Index of Rice
Authors: Aschalew Cherie Workneh, K. S. Hari Prasad, Chandra Shekhar Prasad Ojha
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Due to the increase in water scarcity, the crop water stress index (CWSI) is receiving significant attention these days, especially in arid and semiarid regions, for quantifying water stress and effective irrigation scheduling. Nowadays, machine learning techniques such as neural networks are being widely used to determine CWSI. In the present study, the performance of two artificial neural networks, namely, Self-Organizing Maps (SOM) and Feed Forward-Back Propagation Artificial Neural Networks (FF-BP-ANN), are compared while determining the CWSI of rice crop. Irrigation field experiments with varying degrees of irrigation were conducted at the irrigation field laboratory of the Indian Institute of Technology, Roorkee, during the growing season of the rice crop. The CWSI of rice was computed empirically by measuring key meteorological variables (relative humidity, air temperature, wind speed, and canopy temperature) and crop parameters (crop height and root depth). The empirically computed CWSI was compared with SOM and FF-BP-ANN predicted CWSI. The upper and lower CWSI baselines are computed using multiple regression analysis. The regression analysis showed that the lower CWSI baseline for rice is a function of crop height (h), air vapor pressure deficit (AVPD), and wind speed (u), whereas the upper CWSI baseline is a function of crop height (h) and wind speed (u). The performance of SOM and FF-BP-ANN were compared by computing Nash-Sutcliffe efficiency (NSE), index of agreement (d), root mean squared error (RMSE), and coefficient of correlation (R²). It is found that FF-BP-ANN performs better than SOM while predicting the CWSI of rice crops.Keywords: artificial neural networks; crop water stress index; canopy temperature, prediction capability
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