Search results for: multilayered networks
2495 Comparison of the Effectiveness between Exosomes from Different Origins in Reversing Skin Aging
Authors: Iannello G., Coppa F., Pennisi S., Giuffrida G., Lo Faro R., Cartelli S., Ferruggia G., Brundo M. V.
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Skin is the largest multifunctional human organ and possesses a complex, multilayered structure with the ability to regenerate and renew. The key role in skin regeneration is played by fibroblasts, which also occupy an important role in the wound healing process. Different methods, including dynamic light scattering, scanning electron microscopy, ELISA, and MTT assay, were employed to evaluate on fibroblasts the in vitro effects of plant-derived nanovesicles and cord blood stem cells‐derived exosomes. We compared the results with those of cells exposed to a technology called AMPLEX PLUS, containing a mixture of 20 different biologically active factors (GF20) and exosomes isolated and purified from bovine colostrum. AMPLEX PLUS was able to significantly enhance the cell proliferation status of cells at both 24 and 48 hours compared to untreated cells (control). The obtained results suggest how AMPLEX PLUS could be potentially effective in treating skin rejuvenation.Keywords: AMPLEX PLUS, cell vitality, colostrum, nanovesicles
Procedia PDF Downloads 192494 Identification of Impact Load and Partial System Parameters Using 1D-CNN
Authors: Xuewen Yu, Danhui Dan
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The identification of impact load and some hard-to-obtain system parameters is crucial for the activities of analysis, validation, and evaluation in the engineering field. This paper proposes a method that utilizes neural networks based on 1D-CNN to identify the impact load and partial system parameters from measured responses. To this end, forward computations are conducted to provide datasets consisting of the triples (parameter θ, input u, output y). Then neural networks are trained to learn the mapping from input to output, fu|{θ} : y → u, as well as from input and output to parameter, fθ : (u, y) → θ. Afterward, feeding the trained neural networks the measured output response, the input impact load and system parameter can be calculated, respectively. The method is tested on two simulated examples and shows sound accuracy in estimating the impact load (waveform and location) and system parameters.Keywords: convolutional neural network, impact load identification, system parameter identification, inverse problem
Procedia PDF Downloads 1032493 Constructing a Physics Guided Machine Learning Neural Network to Predict Tonal Noise Emitted by a Propeller
Authors: Arthur D. Wiedemann, Christopher Fuller, Kyle A. Pascioni
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With the introduction of electric motors, small unmanned aerial vehicle designers have to consider trade-offs between acoustic noise and thrust generated. Currently, there are few low-computational tools available for predicting acoustic noise emitted by a propeller into the far-field. Artificial neural networks offer a highly non-linear and adaptive model for predicting isolated and interactive tonal noise. But neural networks require large data sets, exceeding practical considerations in modeling experimental results. A methodology known as physics guided machine learning has been applied in this study to reduce the required data set to train the network. After building and evaluating several neural networks, the best model is investigated to determine how the network successfully predicts the acoustic waveform. Lastly, a post-network transfer function is developed to remove discontinuity from the predicted waveform. Overall, methodologies from physics guided machine learning show a notable improvement in prediction performance, but additional loss functions are necessary for constructing predictive networks on small datasets.Keywords: aeroacoustics, machine learning, propeller, rotor, neural network, physics guided machine learning
Procedia PDF Downloads 2122492 A Taxonomy of Routing Protocols in Wireless Sensor Networks
Authors: A. Kardi, R. Zagrouba, M. Alqahtani
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The Internet of Everything (IoE) presents today a very attractive and motivating field of research. It is basically based on Wireless Sensor Networks (WSNs) in which the routing task is the major analysis topic. In fact, it directly affects the effectiveness and the lifetime of the network. This paper, developed from recent works and based on extensive researches, proposes a taxonomy of routing protocols in WSNs. Our main contribution is that we propose a classification model based on nine classes namely application type, delivery mode, initiator of communication, network architecture, path establishment (route discovery), network topology (structure), protocol operation, next hop selection and latency-awareness and energy-efficient routing protocols. In order to provide a total classification pattern to serve as reference for network designers, each class is subdivided into possible subclasses, presented, and discussed using different parameters such as purposes and characteristics.Keywords: routing, sensor, survey, wireless sensor networks, WSNs
Procedia PDF Downloads 1732491 Monitoring a Membrane Structure Using Non-Destructive Testing
Authors: Gokhan Kilic, Pelin Celik
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Structural health monitoring (SHM) is widely used in evaluating the state and health of membrane structures. In the past, in order to collect data and send it to a data collection unit on membrane structures, wire sensors had to be put as part of the SHM process. However, this study recommends using wireless sensors instead of traditional wire ones to construct an economical, useful, and easy-to-install membrane structure health monitoring system. Every wireless sensor uses a software translation program that is connected to the monitoring server. Operational neural networks (ONNs) have recently been developed to solve the shortcomings of convolutional neural networks (CNNs), such as the network's resemblance to the linear neuron model. The results of using ONNs for monitoring to evaluate the structural health of a membrane are presented in this work.Keywords: wireless sensor network, non-destructive testing, operational neural networks, membrane structures, dynamic monitoring
Procedia PDF Downloads 782490 Geostatistical and Geochemical Study of the Aquifer System Waters Complex Terminal in the Valley of Oued Righ-Arid Area Algeria
Authors: Asma Bettahar, Imed Eddine Nezli, Sameh Habes
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Groundwater resources in the Oued Righ valley are represented like the parts of the eastern basin of the Algerian Sahara, superposed by two major aquifers: the Intercalary Continental (IC) and the Terminal Complex (TC). From a qualitative point of view, various studies have highlighted that the waters of this region showed excessive mineralization, including the waters of the terminal complex (EC Avg equal 5854.61 S/cm) .The present article is a statistical approach by two multi methods various complementary (ACP, CAH), applied to the analytical data of multilayered aquifer waters Terminal Complex of the Oued Righ valley. The approach is to establish a correlation between the chemical composition of water and the lithological nature of different aquifer levels formations, and predict possible connection between groundwater’s layers. The results show that the mineralization of water is from geological origin. They concern the composition of the layers that make up the complex terminal.Keywords: complex terminal, mineralization, oued righ, statistical approach
Procedia PDF Downloads 3782489 Fault Diagnosis of Squirrel-Cage Induction Motor by a Neural Network Multi-Models
Authors: Yahia. Kourd, N. Guersi D. Lefebvre
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In this paper we propose to study the faults diagnosis in squirrel-cage induction motor using MLP neural networks. We use neural healthy and faulty models of the behavior in order to detect and isolate some faults in machine. In the first part of this work, we have created a neural model for the healthy state using Matlab and a motor located in LGEB by acquirins data inputs and outputs of this engine. Then we detected the faults in the machine by residual generation. These residuals are not sufficient to isolate the existing faults. For this reason, we proposed additive neural networks to represent the faulty behaviors. From the analysis of these residuals and the choice of a threshold we propose a method capable of performing the detection and diagnosis of some faults in asynchronous machines with squirrel cage rotor.Keywords: faults diagnosis, neural networks, multi-models, squirrel-cage induction motor
Procedia PDF Downloads 6232488 Comparative Analysis of Geographical Routing Protocol in Wireless Sensor Networks
Authors: Rahul Malhotra
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The field of wireless sensor networks (WSN) engages a lot of associates in the research community as an interdisciplinary field of interest. This type of network is inexpensive, multifunctionally attributable to advances in micro-electromechanical systems and conjointly the explosion and expansion of wireless communications. A mobile ad hoc network is a wireless network without fastened infrastructure or federal management. Due to the infrastructure-less mode of operation, mobile ad-hoc networks are gaining quality. During this work, we have performed an efficient performance study of the two major routing protocols: Ad hoc On-Demand Distance Vector Routing (AODV) and Dynamic Source Routing (DSR) protocols. We have used an accurate simulation model supported NS2 for this purpose. Our simulation results showed that AODV mitigates the drawbacks of the DSDV and provides better performance as compared to DSDV.Keywords: routing protocol, MANET, AODV, On Demand Distance Vector Routing, DSR, Dynamic Source Routing
Procedia PDF Downloads 2652487 Evolution of Chemistry in the Waters of Superposed Aquifer System Terminal Complex in the Valley of the Oued Righ - Arid Area Algeria
Authors: Asma Bettahar, Imed Eldine Nezli, Sameh Habes
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Groundwater resources in the Oued Righ valley are represented like the parts of the eastern basin of the Algerian Sahara, superposed by two major aquifers: the Intercalary Continental (IC) and the Terminal Complex (TC). From a qualitative point of view, various studies have highlighted that the waters of this region showed excessive mineralization, including the waters of the terminal complex (EC Avg equal 5854.61 S/cm). The present article is a statistical approach by two multi methods various complementary (ACP CAH), applied to the analytical data of multilayered aquifer waters Terminal Complex of the Oued Righ valley. The approach is to establish a correlation between the chemical composition of water and the lithological nature of different aquifer levels formations, and predict possible connection between groundwater’s layers. The results show that the mineralization of water is from geological origin. They concern the composition of the layers that make up the complex terminal.Keywords: oued righ, complex terminal, infill continental, mineralization
Procedia PDF Downloads 4442486 Optimal Design of Storm Water Networks Using Simulation-Optimization Technique
Authors: Dibakar Chakrabarty, Mebada Suiting
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Rapid urbanization coupled with changes in land use pattern results in increasing peak discharge and shortening of catchment time of concentration. The consequence is floods, which often inundate roads and inhabited areas of cities and towns. Management of storm water resulting from rainfall has, therefore, become an important issue for the municipal bodies. Proper management of storm water obviously includes adequate design of storm water drainage networks. The design of storm water network is a costly exercise. Least cost design of storm water networks assumes significance, particularly when the fund available is limited. Optimal design of a storm water system is a difficult task as it involves the design of various components, like, open or closed conduits, storage units, pumps etc. In this paper, a methodology for least cost design of storm water drainage systems is proposed. The methodology proposed in this study consists of coupling a storm water simulator with an optimization method. The simulator used in this study is EPA’s storm water management model (SWMM), which is linked with Genetic Algorithm (GA) optimization method. The model proposed here is a mixed integer nonlinear optimization formulation, which takes care of minimizing the sectional areas of the open conduits of storm water networks, while satisfactorily conveying the runoff resulting from rainfall to the network outlet. Performance evaluations of the developed model show that the proposed method can be used for cost effective design of open conduit based storm water networks.Keywords: genetic algorithm (GA), optimal design, simulation-optimization, storm water network, SWMM
Procedia PDF Downloads 2372485 Energy Efficient Routing Protocol with Ad Hoc On-Demand Distance Vector for MANET
Authors: K. Thamizhmaran, Akshaya Devi Arivazhagan, M. Anitha
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On the case of most important systematic issue that must need to be solved in means of implementing a data transmission algorithm on the source of Mobile adhoc networks (MANETs). That is, how to save mobile nodes energy on meeting the requirements of applications or users as the mobile nodes are with battery limited. On while satisfying the energy saving requirement, hence it is also necessary of need to achieve the quality of service. In case of emergency work, it is necessary to deliver the data on mean time. Achieving quality of service in MANETs is also important on while. In order to achieve this requirement, Hence, we further implement the Energy-Aware routing protocol for system of Mobile adhoc networks were it being proposed, that on which saves the energy as on every node by means of efficiently selecting the mode of energy efficient path in the routing process by means of Enhanced AODV routing protocol.Keywords: Ad-Hoc networks, MANET, routing, AODV, EAODV
Procedia PDF Downloads 3592484 A New Realization of Multidimensional System for Grid Sensor Network
Authors: Yang Xiong, Hua Cheng
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In this paper, for the basic problem of wireless sensor network topology control and deployment, the Roesser model in rectangular grid sensor networks is presented. In addition, a general constructive realization procedure will be proposed. The procedure enables a distributed implementation of linear systems on a sensor network. A non-trivial example is illustrated.Keywords: grid sensor networks, Roesser model, state-space realization, multidimensional systems
Procedia PDF Downloads 6442483 Dynamic Route Optimization in Vehicle Adhoc Networks: A Heuristics Routing Protocol
Authors: Rafi Ullah, Shah Muhammad Emaduddin, Taha Jilani
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Vehicle Adhoc Networks (VANET) belongs to a special class of Mobile Adhoc Network (MANET) with high mobility. Network is created by road side vehicles equipped with communication devices like GPS and Wifi etc. Since the environment is highly dynamic due to difference in speed and high mobility of vehicles and weak stability of the network connection, it is a challenging task to design an efficient routing protocol for such an unstable environment. Our proposed algorithm uses heuristic for the calculation of optimal path for routing the packet efficiently in collaboration with several other parameters like geographical location, speed, priority, the distance among the vehicles, communication range, and networks congestion. We have incorporated probabilistic, heuristic and machine learning based approach inconsistency with the relay function of the memory buffer to keep the packet moving towards the destination. These parameters when used in collaboration provide us a very strong and admissible heuristics. We have mathematically proved that the proposed technique is efficient for the routing of packets, especially in a medical emergency situation. These networks can be used for medical emergency, security, entertainment and routing purposes.Keywords: heuristics routing, intelligent routing, VANET, route optimization
Procedia PDF Downloads 1662482 Recognition of Noisy Words Using the Time Delay Neural Networks Approach
Authors: Khenfer-Koummich Fatima, Mesbahi Larbi, Hendel Fatiha
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This paper presents a recognition system for isolated words like robot commands. It’s carried out by Time Delay Neural Networks; TDNN. To teleoperate a robot for specific tasks as turn, close, etc… In industrial environment and taking into account the noise coming from the machine. The choice of TDNN is based on its generalization in terms of accuracy, in more it acts as a filter that allows the passage of certain desirable frequency characteristics of speech; the goal is to determine the parameters of this filter for making an adaptable system to the variability of speech signal and to noise especially, for this the back propagation technique was used in learning phase. The approach was applied on commands pronounced in two languages separately: The French and Arabic. The results for two test bases of 300 spoken words for each one are 87%, 97.6% in neutral environment and 77.67%, 92.67% when the white Gaussian noisy was added with a SNR of 35 dB.Keywords: TDNN, neural networks, noise, speech recognition
Procedia PDF Downloads 2822481 Impact of Very Small Power Producers (VSPP) on Control and Protection System in Distribution Networks
Authors: Noppatee Sabpayakom, Somporn Sirisumrannukul
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Due to incentive policies to promote renewable energy and energy efficiency, high penetration levels of very small power producers (VSPP) located in distribution networks have imposed technical barriers and established new requirements for protection and control of the networks. Although VSPPs have economic and environmental benefit, they may introduce negative effects and cause several challenges on the issue of protection and control system. This paper presents comprehensive studies of possible impacts on control and protection systems based on real distribution systems located in a metropolitan area. A number of scenarios were examined primarily focusing on state of islanding, and un-disconnected VSPP during faults. It is shown that without proper measures to address the issues, the system would be unable to maintain its integrity of electricity power supply for disturbance incidents.Keywords: control and protection systems, distributed generation, renewable energy, very small power producers
Procedia PDF Downloads 4692480 A Model Based Metaheuristic for Hybrid Hierarchical Community Structure in Social Networks
Authors: Radhia Toujani, Jalel Akaichi
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In recent years, the study of community detection in social networks has received great attention. The hierarchical structure of the network leads to the emergence of the convergence to a locally optimal community structure. In this paper, we aim to avoid this local optimum in the introduced hybrid hierarchical method. To achieve this purpose, we present an objective function where we incorporate the value of structural and semantic similarity based modularity and a metaheuristic namely bees colonies algorithm to optimize our objective function on both hierarchical level divisive and agglomerative. In order to assess the efficiency and the accuracy of the introduced hybrid bee colony model, we perform an extensive experimental evaluation on both synthetic and real networks.Keywords: social network, community detection, agglomerative hierarchical clustering, divisive hierarchical clustering, similarity, modularity, metaheuristic, bee colony
Procedia PDF Downloads 3712479 Artificial Neural Networks Controller for Power System Voltage Improvement
Authors: Sabir Messalti, Bilal Boudjellal, Azouz Said
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In this paper, power system Voltage improvement using wind turbine is presented. Two controllers are used: a PI controller and Artificial Neural Networks (ANN) controllers are studied to control of the power flow exchanged between the wind turbine and the power system in order to improve the bus voltage. The wind turbine is based on a doubly-fed induction generator (DFIG) controlled by field-oriented control. Indirect control is used to control of the reactive power flow exchanged between the DFIG and the power system. The proposed controllers are tested on power system for large voltage disturbances.Keywords: artificial neural networks controller, DFIG, field-oriented control, PI controller, power system voltage improvement
Procedia PDF Downloads 4512478 Creating Knowledge Networks: Comparative Analysis of Reference Cases
Authors: Sylvia Villarreal, Edna Bravo
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Knowledge management focuses on coordinating technologies, people, processes, and structures to generate a competitive advantage and considering that networks are perceived as mechanisms for knowledge creation and transfer, this research presents the stages and practices related to the creation of knowledge networks. The methodology started with a literature review adapted from the systematic literature review (SLR). The descriptive analysis includes variables such as approach (conceptual or practical), industry, knowledge management processes and mythologies (qualitative or quantitative), etc. The content analysis includes identification of reference cases. These cases were characterized based on variables as scope, creation goal, years, network approach, actors and creation methodology. It was possible to do a comparative analysis to determinate similarities and differences in these cases documented in knowledge network scientific literature. Consequently, it was shown that even the need and impact of knowledge networks in organizations, the initial guidelines for their creation are not documented, so there is not a guide of good practices and lessons learned. The reference cases are from industries as energy, education, creative, automotive and textile. Their common points are the human approach; it is oriented to interactions to facilitate the appropriation of knowledge, explicit and tacit. The stages of every case are analyzed to propose the main successful elements.Keywords: creation, knowledge management, network, stages
Procedia PDF Downloads 2932477 A Narrative of Nationalism in Mainstream Media: The US, China, and COVID-19
Authors: Rachel Williams, Shiqi Yang
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Our research explores the influence nationalism has had on media coverage of the COVID-19 pandemic as it relates to China in the United States through an inclusive qualitative analysis of two US news networks, Fox News and CNN. In total, the transcripts of sixteen videos uploaded on YouTube, each with more than 100,000 views, were gathered for data processing. Co-occurrence networks generated by KH Coder illuminate the themes and narratives underpinning the reports from Fox News and CNN. The results of in-depth content analysis with keywords suggest that the pandemic has been framed in an ethnopopulist nationalist manner, although to varying degrees between networks. Specifically, the authors found that Fox News is more likely to report hypotheses or statements as a fact; on the contrary, CNN is more likely to quote data and statements from official institutions. Future research into how nationalist narratives have developed in China and in other US news coverage with a more systematic and quantitative method can be conducted to expand on these findings.Keywords: nationalism, media studies, us and china, COVID-19, social media, communication studies
Procedia PDF Downloads 492476 Multi-Sender MAC Protocol Based on Temporal Reuse in Underwater Acoustic Networks
Authors: Dongwon Lee, Sunmyeng Kim
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Underwater acoustic networks (UANs) have become a very active research area in recent years. Compared with wireless networks, UANs are characterized by the limited bandwidth, long propagation delay and high channel dynamic in acoustic modems, which pose challenges to the design of medium access control (MAC) protocol. The characteristics severely affect network performance. In this paper, we study a MS-MAC (Multi-Sender MAC) protocol in order to improve network performance. The proposed protocol exploits temporal reuse by learning the propagation delays to neighboring nodes. A source node locally calculates the transmission schedules of its neighboring nodes and itself based on the propagation delays to avoid collisions. Performance evaluation is conducted using simulation, and confirms that the proposed protocol significantly outperforms the previous protocol in terms of throughput.Keywords: acoustic channel, MAC, temporal reuse, UAN
Procedia PDF Downloads 3412475 Investigation of Delivery of Triple Play Data in GE-PON Fiber to the Home Network
Authors: Ashima Anurag Sharma
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Optical fiber based networks can deliver performance that can support the increasing demands for high speed connections. One of the new technologies that have emerged in recent years is Passive Optical Networks. This research paper is targeted to show the simultaneous delivery of triple play service (data, voice, and video). The comparison between various data rates is presented. It is demonstrated that as we increase the data rate, number of users to be decreases due to increase in bit error rate.Keywords: BER, PON, TDMPON, GPON, CWDM, OLT, ONT
Procedia PDF Downloads 5192474 Proposal of Commutation Protocol in Hybrid Sensors and Vehicular Networks for Intelligent Transport Systems
Authors: Taha Bensiradj, Samira Moussaoui
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Hybrid Sensors and Vehicular Networks (HSVN), represent a hybrid network, which uses several generations of Ad-Hoc networks. It is used especially in Intelligent Transport Systems (ITS). The HSVN allows making collaboration between the Wireless Sensors Network (WSN) deployed on the border of the road and the Vehicular Network (VANET). This collaboration is defined by messages exchanged between the two networks for the purpose to inform the drivers about the state of the road, provide road safety information and more information about traffic on the road. Moreover, this collaboration created by HSVN, also allows the use of a network and the advantage of improving another network. For example, the dissemination of information between the sensors quickly decreases its energy, and therefore, we can use vehicles that do not have energy constraint to disseminate the information between sensors. On the other hand, to solve the disconnection problem in VANET, the sensors can be used as gateways that allow sending the messages received by one vehicle to another. However, because of the short communication range of the sensor and its low capacity of storage and processing of data, it is difficult to ensure the exchange of road messages between it and the vehicle, which can be moving at high speed at the time of exchange. This represents the time where the vehicle is in communication range with the sensor. This work is the proposition of a communication protocol between the sensors and the vehicle used in HSVN. The latter has as the purpose to ensure the exchange of road messages in the available time of exchange.Keywords: HSVN, ITS, VANET, WSN
Procedia PDF Downloads 3532473 Investigation of Delivery of Triple Play Services
Authors: Paramjit Mahey, Monica Sharma, Jasbinder Singh
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Fiber based access networks can deliver performance that can support the increasing demands for high speed connections. One of the new technologies that have emerged in recent years is Passive Optical Networks. This paper is targeted to show the simultaneous delivery of triple play service (data, voice and video). The comparative investigation and suitability of various data rates is presented. It is demonstrated that as we increase the data rate, number of users to be accommodated decreases due to increase in bit error rate.Keywords: BER, PON, TDMPON, GPON, CWDM, OLT, ONT
Procedia PDF Downloads 5362472 An Algorithm for Determining the Arrival Behavior of a Secondary User to a Base Station in Cognitive Radio Networks
Authors: Danilo López, Edwin Rivas, Leyla López
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This paper presents the development of an algorithm that predicts the arrival of a secondary user (SU) to a base station (BS) in a cognitive network based on infrastructure, requesting a Best Effort (BE) or Real Time (RT) type of service with a determined bandwidth (BW) implementing neural networks. The algorithm dynamically uses a neural network construction technique using the geometric pyramid topology and trains a Multilayer Perceptron Neural Networks (MLPNN) based on the historical arrival of an SU to estimate future applications. This will allow efficiently managing the information in the BS, since it precedes the arrival of the SUs in the stage of selection of the best channel in CRN. As a result, the software application determines the probability of arrival at a future time point and calculates the performance metrics to measure the effectiveness of the predictions made.Keywords: cognitive radio, base station, best effort, MLPNN, prediction, real time
Procedia PDF Downloads 3192471 A t-SNE and UMAP Based Neural Network Image Classification Algorithm
Authors: Shelby Simpson, William Stanley, Namir Naba, Xiaodi Wang
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Both t-SNE and UMAP are brand new state of art tools to predominantly preserve the local structure that is to group neighboring data points together, which indeed provides a very informative visualization of heterogeneity in our data. In this research, we develop a t-SNE and UMAP base neural network image classification algorithm to embed the original dataset to a corresponding low dimensional dataset as a preprocessing step, then use this embedded database as input to our specially designed neural network classifier for image classification. We use the fashion MNIST data set, which is a labeled data set of images of clothing objects in our experiments. t-SNE and UMAP are used for dimensionality reduction of the data set and thus produce low dimensional embeddings. Furthermore, we use the embeddings from t-SNE and UMAP to feed into two neural networks. The accuracy of the models from the two neural networks is then compared to a dense neural network that does not use embedding as an input to show which model can classify the images of clothing objects more accurately.Keywords: t-SNE, UMAP, fashion MNIST, neural networks
Procedia PDF Downloads 1892470 Proposing a Boundary Coverage Algorithm for Underwater Sensor Network
Authors: Seyed Mohsen Jameii
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Wireless underwater sensor networks are a type of sensor networks that are located in underwater environments and linked together by acoustic waves. The application of these kinds of network includes monitoring of pollutants (chemical, biological, and nuclear), oil fields detection, prediction of the likelihood of a tsunami in coastal areas, the use of wireless sensor nodes to monitor the passing submarines, and determination of appropriate locations for anchoring ships. This paper proposes a boundary coverage algorithm for intrusion detection in underwater sensor networks. In the first phase of the proposed algorithm, optimal deployment of nodes is done in the water. In the second phase, after the employment of nodes at the proper depth, clustering is executed to reduce the exchanges of messages between the sensors. In the third phase, the algorithm of "divide and conquer" is used to save energy and increase network efficiency. The simulation results demonstrate the efficiency of the proposed algorithm.Keywords: boundary coverage, clustering, divide and conquer, underwater sensor nodes
Procedia PDF Downloads 3312469 Optimization of Vertical Axis Wind Turbine Based on Artificial Neural Network
Authors: Mohammed Affanuddin H. Siddique, Jayesh S. Shukla, Chetan B. Meshram
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The neural networks are one of the power tools of machine learning. After the invention of perceptron in early 1980's, the neural networks and its application have grown rapidly. Neural networks are a technique originally developed for pattern investigation. The structure of a neural network consists of neurons connected through synapse. Here, we have investigated the different algorithms and cost function reduction techniques for optimization of vertical axis wind turbine (VAWT) rotor blades. The aerodynamic force coefficients corresponding to the airfoils are stored in a database along with the airfoil coordinates. A forward propagation neural network is created with the input as aerodynamic coefficients and output as the airfoil co-ordinates. In the proposed algorithm, the hidden layer is incorporated into cost function having linear and non-linear error terms. In this article, it is observed that the ANNs (Artificial Neural Network) can be used for the VAWT’s optimization.Keywords: VAWT, ANN, optimization, inverse design
Procedia PDF Downloads 3122468 Fault Tree Analysis and Bayesian Network for Fire and Explosion of Crude Oil Tanks: Case Study
Authors: B. Zerouali, M. Kara, B. Hamaidi, H. Mahdjoub, S. Rouabhia
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In this paper, a safety analysis for crude oil tanks to prevent undesirable events that may cause catastrophic accidents. The estimation of the probability of damage to industrial systems is carried out through a series of steps, and in accordance with a specific methodology. In this context, this work involves developing an assessment tool and risk analysis at the level of crude oil tanks system, based primarily on identification of various potential causes of crude oil tanks fire and explosion by the use of Fault Tree Analysis (FTA), then improved risk modelling by Bayesian Networks (BNs). Bayesian approach in the evaluation of failure and quantification of risks is a dynamic analysis approach. For this reason, have been selected as an analytical tool in this study. Research concludes that the Bayesian networks have a distinct and effective method in the safety analysis because of the flexibility of its structure; it is suitable for a wide variety of accident scenarios.Keywords: bayesian networks, crude oil tank, fault tree, prediction, safety
Procedia PDF Downloads 6502467 Message Framework for Disaster Management: An Application Model for Mines
Authors: A. Baloglu, A. Çınar
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Different tools and technologies were implemented for Crisis Response and Management (CRM) which is generally using available network infrastructure for information exchange. Depending on type of disaster or crisis, network infrastructure could be affected and it could not be able to provide reliable connectivity. Thus any tool or technology that depends on the connectivity could not be able to fulfill its functionalities. As a solution, a new message exchange framework has been developed. Framework provides offline/online information exchange platform for CRM Information Systems (CRMIS) and it uses XML compression and packet prioritization algorithms and is based on open source web technologies. By introducing offline capabilities to the web technologies, framework will be able to perform message exchange on unreliable networks. The experiments done on the simulation environment provide promising results on low bandwidth networks (56kbps and 28.8 kbps) with up to 50% packet loss and the solution is to successfully transfer all the information on these low quality networks where the traditional 2 and 3 tier applications failed.Keywords: crisis response and management, XML messaging, web services, XML compression, mining
Procedia PDF Downloads 3312466 Positive Bias and Length Bias in Deep Neural Networks for Premises Selection
Authors: Jiaqi Huang, Yuheng Wang
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Premises selection, the task of selecting a set of axioms for proving a given conjecture, is a major bottleneck in automated theorem proving. An array of deep-learning-based methods has been established for premises selection, but a perfect performance remains challenging. Our study examines the inaccuracy of deep neural networks in premises selection. Through training network models using encoded conjecture and axiom pairs from the Mizar Mathematical Library, two potential biases are found: the network models classify more premises as necessary than unnecessary, referred to as the ‘positive bias’, and the network models perform better in proving conjectures that paired with more axioms, referred to as ‘length bias’. The ‘positive bias’ and ‘length bias’ discovered could inform the limitation of existing deep neural networks.Keywords: automated theorem proving, premises selection, deep learning, interpreting deep learning
Procedia PDF Downloads 174