Search results for: network structure
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 11815

Search results for: network structure

9955 Evaluating the Seismic Stress Distribution in the High-Rise Structures Connections with Optimal Bracing System

Authors: H. R. Vosoughifar, Seyedeh Zeinab. Hosseininejad, Nahid Shabazi, Seyed Mohialdin Hosseininejad

Abstract:

In recent years, structure designers advocate further application of energy absorption devices for lateral loads damping. The Un-bonded Braced Frame (UBF) system is one of the efficient damping systems, which is made of a smart combination of steel and concrete or mortar. In this system, steel bears the earthquake-induced axial force as compressive or tension forces without loss of strength. Concrete or mortar around the steel core acts as a constraint for brace and prevents brace buckling during seismic axial load. In this study, the optimal bracing system in the high-rise structures has been evaluated considering the seismic stress distribution in the connections. An actual 18-story structure was modeled using the proper Finite Element (FE) software where braced with UBF, Eccentrically Braced Frames (EBF) and Concentrically Braced Frame (CBF) systems. Nonlinear static pushover and time-history analyses are then performed so that the acquired results demonstrate that the UBF system reduces drift values in the high-rise buildings. Further statistical analyses show that there is a significant difference between the drift values of UBF system compared with those resulted from the EBF and CBF systems. Hence, the seismic stress distribution in the connections of the proposed structure which braced with UBF system was investigated.

Keywords: optimal bracing system, high-rise structure, finite element analysis (FEA), seismic stress

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9954 Argument Representation in Non-Spatial Motion Bahasa Melayu Based Conceptual Structure Theory

Authors: Nurul Jamilah Binti Rosly

Abstract:

The typology of motion must be understood as a change from one location to another. But from a conceptual point of view, motion can also occur in non-spatial contexts associated with human and social factors. Therefore, from the conceptual point of view, the concept of non-spatial motion involves the movement of time, ownership, identity, state, and existence. Accordingly, this study will focus on the lexical as shared, accept, be, store, and exist as the study material. The data in this study were extracted from the Database of Languages and Literature Corpus Database, Malaysia, which was analyzed using semantics and syntax concepts using Conceptual Structure Theory - Ray Jackendoff (2002). Semantic representations are represented in the form of conceptual structures in argument functions that include functions [events], [situations], [objects], [paths] and [places]. The findings show that the mapping of these arguments comprises three main stages, namely mapping the argument structure, mapping the tree, and mapping the role of thematic items. Accordingly, this study will show the representation of non- spatial Malay language areas.

Keywords: arguments, concepts, constituencies, events, situations, thematics

Procedia PDF Downloads 124
9953 Multiple Fault Detection and Classification in a Coupled Motor with Rotor Using Artificial Neural Network

Authors: Mehrdad Nouri Khajavi, Gollamhassan Payganeh, Mohsen Fallah Tafti

Abstract:

Fault diagnosis is an important aspect of maintaining rotating machinery health and increasing productivity. Many researches has been done in this regards. Many faults such as unbalance, misalignment, looseness, bearing faults, etc. have been considered and diagnosed with different techniques. Most of the researches in fault diagnosis of rotating machinery deal with single fault. Where as in reality faults usually occur simultaneously and it is, therefore, necessary to recognize them at the same time. In this research, two of the most common faults namely unbalance and misalignment have been considered simultaneously with different intensity and then identified and classified with the use of Multi-Layer Perception Neural Network (MLPNN). Processed Vibration signals are used as the input to the MLPNN, and the class of mixed unbalancy, and misalignment is the output of the NN.

Keywords: unbalance, parallel misalignment, combined faults, vibration signals

Procedia PDF Downloads 346
9952 Mobility Management via Software Defined Networks (SDN) in Vehicular Ad Hoc Networks (VANETs)

Authors: Bilal Haider, Farhan Aadil

Abstract:

A Vehicular Ad hoc Network (VANET) provides various services to end-users traveling on the road at high speeds. However, this high-speed mobility of mobile nodes can cause frequent service disruptions. Various mobility management protocols exist for managing node mobility, but due to their centralized nature, they tend to suffer in the VANET environment. In this research, we proposed a distributed mobility management protocol using software-defined networks (SDN) for VANETs. Instead of relying on a centralized mobility anchor, the mobility functionality is distributed at multiple infrastructural nodes. The protocol is based on the classical Proxy Mobile IP version 6 (PMIPv6). It is evident from simulation results that this work has improved the network performance with respect to nodes throughput, delay, and packet loss.

Keywords: SDN, VANET, mobility management, optimization

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9951 Predicting Survival in Cancer: How Cox Regression Model Compares to Artifial Neural Networks?

Authors: Dalia Rimawi, Walid Salameh, Amal Al-Omari, Hadeel AbdelKhaleq

Abstract:

Predication of Survival time of patients with cancer, is a core factor that influences oncologist decisions in different aspects; such as offered treatment plans, patients’ quality of life and medications development. For a long time proportional hazards Cox regression (ph. Cox) was and still the most well-known statistical method to predict survival outcome. But due to the revolution of data sciences; new predication models were employed and proved to be more flexible and provided higher accuracy in that type of studies. Artificial neural network is one of those models that is suitable to handle time to event predication. In this study we aim to compare ph Cox regression with artificial neural network method according to data handling and Accuracy of each model.

Keywords: Cox regression, neural networks, survival, cancer.

Procedia PDF Downloads 188
9950 Multi-Path Signal Synchronization Model with Phase Length Constraints

Authors: Tzu-Jung Huang, Hsun-Jung Cho, Chien-Chia Liäm Huang

Abstract:

To improve the level of service (LoS) of urban arterial systems containing a series of signalized intersections, a proper design of offsets for all intersections associated is of great importance. The MAXBAND model has been the most common approach for this purpose. In this paper, we propose a MAXBAND model with phase constraints so that the lengths of the phases in a cycle are variable. In other words, the length of a cycle is also variable in our setting. We conduct experiments on a real-world traffic network, having several major paths, in Taiwan for numerical evaluations. Actual traffic data were collected through on-site experiments. Numerical evidences suggest that the improvements are around 32%, on average, in terms of total delay of the entire network.

Keywords: arterial progression, MAXBAND, signal control, offset

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9949 The Impact of the Number of Neurons in the Hidden Layer on the Performance of MLP Neural Network: Application to the Fast Identification of Toxics Gases

Authors: Slimane Ouhmad, Abdellah Halimi

Abstract:

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

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

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9948 Cost of Outpatient Procedures for Ostomized Patients Treated in the Public Health Network in Brazil and Its Impact on the Budget of the Unified Health System

Authors: Karina Guimaraes, Lilian Santos

Abstract:

This study has the purpose of planning and instituting monitoring actions as a way of knowing the scenario of assistance to the patient with stoma, treated in the public health network in Brazil, from January to November of the year 2016, from the elaboration of a technical document containing the survey of the number of procedures offered and the value of the ostomy services, accredited in the Unified Health System-SUS. The purpose of this document is to improve the quality of these services in the efficient management of available financial resources, making it indispensable for the creation of strategies for the implementation and implementation of care services for people with stomata as a strategic tool in the promotion, prevention, qualification and efficiency in health care.

Keywords: health economic, management, ostomy, unified health system

Procedia PDF Downloads 306
9947 Determination of the Structural Parameters of Calcium Phosphate for Biomedical Use

Authors: María Magdalena Méndez-González, Miguel García Rocha, Carlos Manuel Yermo De la Cruz

Abstract:

Calcium phosphate (Ca5(PO4)3(X)) is widely used in orthopedic applications and is widely used as powder and granules. However, their presence in bone is in the form of nanometric needles 60 nm in length with a non-stoichiometric phase of apatite contains CO3-2, Na+, OH-, F-, and other ions in a matrix of collagen fibers. The crystal size, morphology control and interaction with cells are essential for the development of nanotechnology. The structural results of calcium phosphate, synthesized by chemical precipitation with crystal size of 22.85 nm are presented in this paper. The calcium phosphate powders were analyzed by X-ray diffraction, energy dispersive spectroscopy (EDS), infrared spectroscopy and FT-IR transmission electron microscopy. Network parameters, atomic positions, the indexing of the planes and the calculation of FWHM (full width at half maximum) were obtained. The crystal size was also calculated using the Scherer equation d (hkl) = cλ/βcosѲ. Where c is a constant related to the shape of the crystal, the wavelength of the radiation used for a copper anode is 1.54060Å, Ѳ is the Bragg diffraction angle, and β is the width average peak height of greater intensity. Diffraction pattern corresponding to the calcium phosphate called hydroxyapatite phase of a hexagonal crystal system was obtained. It belongs to the space group P63m with lattice parameters a = 9.4394 Å and c = 6.8861 Å. The most intense peak is obtained 2Ѳ = 31.55 (FWHM = 0.4798), with a preferred orientation in 121. The intensity difference between the experimental data and the calculated values is attributable to the temperature at which the sintering was performed. The intensity of the highest peak is at angle 2Ѳ = 32.11. The structure of calcium phosphate obtained was a hexagonal configuration. The intensity changes in the peaks of the diffraction pattern, in the lattice parameters at the corners, indicating the possible presence of a dopant. That each calcium atom is surrounded by a tetrahedron of oxygen and hydrogen was observed by infrared spectra. The unit cell pattern corresponds to hydroxyapatite and transmission electron microscopic crystal morphology corresponding to the hexagonal phase with a preferential growth along the c-plane was obtained.

Keywords: structure, nanoparticles, calcium phosphate, metallurgical and materials engineering

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9946 Optimized Cluster Head Selection Algorithm Based on LEACH Protocol for Wireless Sensor Networks

Authors: Wided Abidi, Tahar Ezzedine

Abstract:

Low-Energy Adaptive Clustering Hierarchy (LEACH) has been considered as one of the effective hierarchical routing algorithms that optimize energy and prolong the lifetime of network. Since the selection of Cluster Head (CH) in LEACH is carried out randomly, in this paper, we propose an approach of electing CH based on LEACH protocol. In other words, we present a formula for calculating the threshold responsible for CH election. In fact, we adopt three principle criteria: the remaining energy of node, the number of neighbors within cluster range and the distance between node and CH. Simulation results show that our proposed approach beats LEACH protocol in regards of prolonging the lifetime of network and saving residual energy.

Keywords: wireless sensors networks, LEACH protocol, cluster head election, energy efficiency

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9945 A Method Development for Improving the Efficiency of Solid Waste Collection System Using Network Analyst

Authors: Dhvanidevi N. Jadeja, Daya S. Kaul, Anurag A. Kandya

Abstract:

Municipal Solid Waste (MSW) collection in a city is performed in less effective manner which results in the poor management of the environment and natural resources. Municipal corporation does not possess efficient waste management and recycling programs because of the complex task involving many factors. Solid waste collection system depends upon various factors such as manpower, number and size of vehicles, transfer station size, dustbin size and weight, on-road traffic, and many others. These factors affect the collection cost, energy and overall municipal tax for the city. Generally, different types of waste are scattered throughout the city in a heterogeneous way that poses changes for efficient collection of solid waste. Efficient waste collection and transportation strategy must be effectively undertaken which will include optimization of routes, volume of waste, and manpower. Being these optimized, the overall cost can be reduced as the fuel and energy requirements would be less and also the municipal waste taxes levied will be less. To carry out the optimization study of collection system various data needs to be collected from the Ahmedabad municipal corporation such as amount of waste generated per day, number of workers, collection schedule, road maps, number of transfer station, location of transfer station, number of equipment (tractors, machineries), number of zones, route of collection etc. The ArcGis Network Analyst is introduced for the best routing identification applied in municipal waste collection. The simulation consists of scenarios of visiting loading spots in the municipality of Ahmedabad, considering dynamic factors like network traffic changes, closed roads due to natural or technical causes. Different routes were selected in a particular area of Ahmedabad city, and present routes were optimized to reduce the length of the routes, by using ArcGis Network Analyst. The result indicates up to 35% length minimization in the routes.

Keywords: collection routes, efficiency, municipal solid waste, optimization

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9944 Design of a Cooperative Neural Network, Particle Swarm Optimization (PSO) and Fuzzy Based Tracking Control for a Tilt Rotor Unmanned Aerial Vehicle

Authors: Mostafa Mjahed

Abstract:

Tilt Rotor UAVs (Unmanned Aerial Vehicles) are naturally unstable and difficult to maneuver. The purpose of this paper is to design controllers for the stabilization and trajectory tracking of this type of UAV. To this end, artificial intelligence methods have been exploited. First, the dynamics of this UAV was modeled using the Lagrange-Euler method. The conventional method based on Proportional, Integral and Derivative (PID) control was applied by decoupling the different flight modes. To improve stability and trajectory tracking of the Tilt Rotor, the fuzzy approach and the technique of multilayer neural networks (NN) has been used. Thus, Fuzzy Proportional Integral and Derivative (FPID) and Neural Network-based Proportional Integral and Derivative controllers (NNPID) have been developed. The meta-heuristic approach based on Particle Swarm Optimization (PSO) method allowed adjusting the setting parameters of NNPID controller, giving us an improved NNPID-PSO controller. Simulation results under the Matlab environment show the efficiency of the approaches adopted. Besides, the Tilt Rotor UAV has become stable and follows different types of trajectories with acceptable precision. The Fuzzy, NN and NN-PSO-based approaches demonstrated their robustness because the presence of the disturbances did not alter the stability or the trajectory tracking of the Tilt Rotor UAV.

Keywords: neural network, fuzzy logic, PSO, PID, trajectory tracking, tilt-rotor UAV

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9943 Structural Parameter Identification of Old Steel Truss Bridges

Authors: A. Bogdanovic, M. Vitanova, J. Bojadjieva, Z. Rakicevic, V. Sesov, K. Edip, N. Naumovski, F. Manojlovski, A.Popovska, A. Shoklarovski, T. Kitanovski, D. Ivanovski, I. Markovski, D. Filipovski

Abstract:

The conditions of existing structures change in the course of time and can hardly be characterized particularly if a bridge has long been in function and there is no design documentation related to it. To define the real conditions of a structure, detailed static and dynamic analysis of the structure has to be carried out and its modal parameters have to be defined accurately. Modal analysis enables a quite accurate identification of the natural frequencies and mode shapes. Presented in this paper are the results from the performed detailed analyses of a steel truss bridge that has been in use for more than 7 decades by the military services of R.N. Macedonia and for which there is no documentation at all. Static and dynamic investigations and ambient vibration measurements were performed. The acquired data were used to identify the mode shapes that were used for comparison with the numerical model. Dynamic tests were performed to define the bridge behaviour and the damping index. Finally, based on all the conducted detailed analyses and investigations, conclusions on the conditions of the bridge structure were drawn.

Keywords: ambient vibrations, dynamic identification, in-situ measurement, steel truss bridge

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9942 Multi-Fidelity Fluid-Structure Interaction Analysis of a Membrane Wing

Authors: M. Saeedi, R. Wuchner, K.-U. Bletzinger

Abstract:

In order to study the aerodynamic performance of a semi-flexible membrane wing, Fluid-Structure Interaction simulations have been performed. The fluid problem has been modeled using two different approaches which are the numerical solution of the Navier-Stokes equations and the vortex panel method. Nonlinear analysis of the structural problem is performed using the Finite Element Method. Comparison between the two fluid solvers has been made. Aerodynamic performance of the wing is discussed regarding its lift and drag coefficients and they are compared with those of the equivalent rigid wing.

Keywords: CFD, FSI, Membrane wing, Vortex panel method

Procedia PDF Downloads 481
9941 Enhancing Urban Sustainability through Integrated Green Spaces: A Focus on Tehran

Authors: Azadeh Mohajer Milani

Abstract:

Urbanization constitutes an irreversible global trend, presenting myriad challenges such as heightened energy consumption, pollution, congestion, and the depletion of natural resources. Today's urban landscapes have emerged as focal points for economic, social, and environmental challenges, underscoring the pressing need for sustainable development. This article delves into the realm of sustainable urban development, concentrating on the pivotal role played by integrated green spaces as an optimal solution to address environmental concerns within cities. The study utilizes Tehran as a case study. Our findings underscore the imperative of preserving and expanding green spaces in urban areas, coupled with the establishment of well-designed ecological networks, to enhance environmental quality and elevate the sustainability of cities. Notably, Tehran's urban green spaces exhibit a disjointed design, lacking a cohesive network to connect various patches and corridors, resulting in significant environmental impacts. The results emphasize the necessity of a balanced and proportional distribution of urban green spaces and the creation of a cohesive patch-corridor-matrix network tailored to the ecological and social needs of residents. This approach is crucial for fostering a more sustainable and livable urban environment for all species, with a specific focus on humans.

Keywords: ecology, sustainable urban development, sustainable landscape, urban green space network

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9940 Evaluation of Urban-Rural Integration of Characteristic Towns in Yunnan Province

Authors: Huang Yong, Chen Qianting, Zhao Shurong

Abstract:

In order to identify the role and effect of Characteristic Towns as an important means to promote urban-rural integration, this paper uses Flow Theory and complex network analysis methods to jointly construct the identification path of urban-rural integration capabilities of Characteristic Towns. Take the National Characteristic Towns of Yunnan Province as the empirical objects to identify their role laws. The study found that in the implementation of the National Characteristic Town Project in Yunnan Province, (1) the population is more susceptible to the impact of the Characteristic Town Project than the technical elements, but the stability is poor; (2) The flow capacity of urban and rural technical elements is weak, and the quality of the enterprise cooperation network in general; (3) Compared with the batch of Characteristic Towns in 2016, its ability to promote urban-rural integration is higher in 2017; (4) The role of the Characteristic Town Project on urban-rural integration focuses on the improvement of the number of urban and rural flow elements. This paper analyzes the mode of the role of Characteristic Towns on urban-rural integration from the perspective of ‘flow,’ establishes a research paradigm for evaluating the role of Characteristic Towns in urban-rural integration capabilities, and builds a path for the application of Characteristic Towns to support the realization of urban-rural integration goals.

Keywords: characteristic town, urban-rural integration, flow theory, complex network analysis

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9939 Using Industrial Service Quality to Assess Service Quality Perception in Television Advertisement: A Case Study

Authors: Ana L. Martins, Rita S. Saraiva, João C. Ferreira

Abstract:

Much effort has been placed on the assessment of perceived service quality. Several models can be found in literature, but these are mainly focused on business-to-consumer (B2C) relationships. Literature on how to assess perceived quality in business-to-business (B2B) contexts is scarce both conceptually and in terms of its application. This research aims at filling this gap in literature by applying INDSERV to a case study situation. Under this scope, this research aims at analyzing the adequacy of the proposed assessment tool to other context besides the one where it was developed and by doing so analyzing the perceive quality of the advertisement service provided by a specific television network to its B2B customers. The INDSERV scale was adopted and applied to a sample of 33 clients, via questionnaires adapted to interviews. Data was collected in person or phone. Both quantitative and qualitative data collection was performed. Qualitative data analysis followed content analysis protocol. Quantitative analysis used hypotheses testing. Findings allowed to conclude that the perceived quality of the television service provided by television network is very positive, being the Soft Process Quality the parameter that reveals the highest perceived quality of the service as opposed to Potential Quality. To this end, some comments and suggestions were made by the clients regarding each one of these service quality parameters. Based on the hypotheses testing, it was noticed that only advertisement clients that maintain a connection to the television network from 5 to 10 years do show a significant different perception of the TV advertisement service provided by the company in what the Hard Process Quality parameter is concerned. Through the collected data content analysis, it was possible to obtain the percentage of clients which share the same opinions and suggestions for improvement. Finally, based on one of the four service quality parameter in a B2B context, managerial suggestions were developed aiming at improving the television network advertisement perceived quality service.

Keywords: B2B, case study, INDSERV, perceived service quality

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9938 Fractional-Order Modeling of GaN High Electron Mobility Transistors for Switching Applications

Authors: Anwar H. Jarndal, Ahmed S. Elwakil

Abstract:

In this paper, a fraction-order model for pad parasitic effect of GaN HEMT on Si substrate is developed and validated. Open de-embedding structure is used to characterize and de-embed substrate loading parasitic effects. Unbiased device measurements are implemented to extract parasitic inductances and resistances. The model shows very good simulation for S-parameter measurements under different bias conditions. It has been found that this approach can improve the simulation of intrinsic part of the transistor, which is very important for small- and large-signal modeling process.

Keywords: fractional-order modeling, GaNHEMT, si-substrate, open de-embedding structure

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9937 Ant-Tracking Attribute: A Model for Understanding Production Response

Authors: Prince Suka Neekia Momta, Rita Iheoma Achonyeulo

Abstract:

Ant Tracking seismic attribute applied over 4-seconds seismic volume revealed structural features triggered by clay diapirism, growth fault development, rapid deltaic sedimentation and intense drilling. The attribute was extracted on vertical seismic sections and time slices. Mega tectonic structures such as growth faults and clay diapirs are visible on vertical sections with obscured minor lineaments or fractures. Fractures are distinctively visible on time slices yielding recognizable patterns corroborating established geologic models. This model seismic attribute enabled the understanding of fluid flow characteristics and production responses. Three structural patterns recognized in the field include: major growth faults, minor faults or lineaments and network of fractures. Three growth faults mapped on seismic section form major deformation bands delimiting the area into three blocks or depocenters. The growth faults trend E-W, dip down-to-south in the basin direction, and cut across the study area. The faults initiating from about 2000ms extended up to 500ms, and tend to progress parallel and opposite to the growth direction of an upsurging diapiric structure. The diapiric structures form the major deformational bands originating from great depths (below 2000ms) and rising to about 1200ms where series of sedimentary layers onlapped and pinchout stratigraphically against the diapir. Several other secondary faults or lineaments that form parallel streaks to one another also accompanied the growth faults. The fracture networks have no particular trend but form a network surrounding the well area. Faults identified in the study area have potentials for structural hydrocarbon traps whereas the presence of fractures created a fractured-reservoir condition that enhanced rapid fluid flow especially water. High aquifer flow potential aided by possible fracture permeability resulted in rapid decline in oil rate. Through the application of Ant Tracking attribute, it is possible to obtain detailed interpretation of structures that can have direct influence on oil and gas production.

Keywords: seismic, attributes, production, structural

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9936 Nanostructure and Adhesion of Cement/Polymer Fiber Interfaces

Authors: Faezeh Shalchy

Abstract:

Concrete is the most used materials in the world. It is also one of the most versatile while complex materials which human have used for construction. However, concrete is weak in tension, over the past thirty years many studies were accomplished to improve the tensile properties of concrete (cement-based materials) using a variety of methods. One of the most successful attempts is to use polymeric fibers in the structure of concrete to obtain a composite with high tensile strength and ductility. Understanding the mechanical behavior of fiber reinforced concrete requires the knowledge of the fiber/matrix interfaces at the small scale. In this study, a combination of numerical simulations and experimental techniques have been used to study the nano structure of fiber/matrix interfaces. A new model for calcium-silicate-hydrate (C-S-H)/fiber interfaces is proposed based on Scanning Electron Microscopy (SEM) and Energy-dispersive X-ray spectroscopy (EDX) analysis. The adhesion energy between the C-S-H gel and 2 different polymeric fibers (polyvinyl alcohol and polypropylene) was numerically studied at the atomistic level since adhesion is one of the key factors in the design of fiber reinforced composites. The mechanisms of adhesion as a function of the nano structure of fiber/matrix interfaces are also studied and discussed.

Keywords: fiber-reinforced concrete, adhesion, molecular modeling

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9935 Deep-Learning to Generation of Weights for Image Captioning Using Part-of-Speech Approach

Authors: Tiago do Carmo Nogueira, Cássio Dener Noronha Vinhal, Gélson da Cruz Júnior, Matheus Rudolfo Diedrich Ullmann

Abstract:

Generating automatic image descriptions through natural language is a challenging task. Image captioning is a task that consistently describes an image by combining computer vision and natural language processing techniques. To accomplish this task, cutting-edge models use encoder-decoder structures. Thus, Convolutional Neural Networks (CNN) are used to extract the characteristics of the images, and Recurrent Neural Networks (RNN) generate the descriptive sentences of the images. However, cutting-edge approaches still suffer from problems of generating incorrect captions and accumulating errors in the decoders. To solve this problem, we propose a model based on the encoder-decoder structure, introducing a module that generates the weights according to the importance of the word to form the sentence, using the part-of-speech (PoS). Thus, the results demonstrate that our model surpasses state-of-the-art models.

Keywords: gated recurrent units, caption generation, convolutional neural network, part-of-speech

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9934 Artificial Neural Networks and Geographic Information Systems for Coastal Erosion Prediction

Authors: Angeliki Peponi, Paulo Morgado, Jorge Trindade

Abstract:

Artificial Neural Networks (ANNs) and Geographic Information Systems (GIS) are applied as a robust tool for modeling and forecasting the erosion changes in Costa Caparica, Lisbon, Portugal, for 2021. ANNs present noteworthy advantages compared with other methods used for prediction and decision making in urban coastal areas. Multilayer perceptron type of ANNs was used. Sensitivity analysis was conducted on natural and social forces and dynamic relations in the dune-beach system of the study area. Variations in network’s parameters were performed in order to select the optimum topology of the network. The developed methodology appears fitted to reality; however further steps would make it better suited.

Keywords: artificial neural networks, backpropagation, coastal urban zones, erosion prediction

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9933 Hybrid Hierarchical Routing Protocol for WSN Lifetime Maximization

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

Abstract:

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

Keywords: routing protocol, optimization, clustering, WSN

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9932 Hybrid Multipath Congestion Control

Authors: Akshit Singhal, Xuan Wang, Zhijun Wang, Hao Che, Hong Jiang

Abstract:

Multiple Path Transmission Control Protocols (MPTCPs) allow flows to explore path diversity to improve the throughput, reliability and network resource utilization. However, the existing solutions may discourage users to adopt the solutions in the face of multipath scenario where different paths are charged based on different pricing structures, e.g., WiFi vs cellular connections, widely available for mobile phones. In this paper, we propose a Hybrid MPTCP (H-MPTCP) with a built-in mechanism to incentivize users to use multiple paths with different pricing structures. In the meantime, H-MPTCP preserves the nice properties enjoyed by the state-of-the-art MPTCP solutions. Extensive real Linux implementation results verify that H-MPTCP can indeed achieve the design objectives.

Keywords: network, TCP, WiFi, cellular, congestion control

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9931 Personal Information Classification Based on Deep Learning in Automatic Form Filling System

Authors: Shunzuo Wu, Xudong Luo, Yuanxiu Liao

Abstract:

Recently, the rapid development of deep learning makes artificial intelligence (AI) penetrate into many fields, replacing manual work there. In particular, AI systems also become a research focus in the field of automatic office. To meet real needs in automatic officiating, in this paper we develop an automatic form filling system. Specifically, it uses two classical neural network models and several word embedding models to classify various relevant information elicited from the Internet. When training the neural network models, we use less noisy and balanced data for training. We conduct a series of experiments to test my systems and the results show that our system can achieve better classification results.

Keywords: artificial intelligence and office, NLP, deep learning, text classification

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9930 A Nonlinear Approach for System Identification of a Li-Ion Battery Based on a Non-Linear Autoregressive Exogenous Model

Authors: Meriem Mossaddek, El Mehdi Laadissi, El Mehdi Loualid, Chouaib Ennawaoui, Sohaib Bouzaid, Abdelowahed Hajjaji

Abstract:

An electrochemical system is a subset of mechatronic systems that includes a wide variety of batteries and nickel-cadmium, lead-acid batteries, and lithium-ion. Those structures have several non-linear behaviors and uncertainties in their running range. This paper studies an effective technique for modeling Lithium-Ion (Li-Ion) batteries using a Nonlinear Auto-Regressive model with exogenous input (NARX). The Artificial Neural Network (ANN) is trained to employ the data collected from the battery testing process. The proposed model is implemented on a Li-Ion battery cell. Simulation of this model in MATLAB shows good accuracy of the proposed model.

Keywords: lithium-ion battery, neural network, energy storage, battery model, nonlinear models

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9929 Cigarette Smoke Detection Based on YOLOV3

Authors: Wei Li, Tuo Yang

Abstract:

In order to satisfy the real-time and accurate requirements of cigarette smoke detection in complex scenes, a cigarette smoke detection technology based on the combination of deep learning and color features was proposed. Firstly, based on the color features of cigarette smoke, the suspicious cigarette smoke area in the image is extracted. Secondly, combined with the efficiency of cigarette smoke detection and the problem of network overfitting, a network model for cigarette smoke detection was designed according to YOLOV3 algorithm to reduce the false detection rate. The experimental results show that the method is feasible and effective, and the accuracy of cigarette smoke detection is up to 99.13%, which satisfies the requirements of real-time cigarette smoke detection in complex scenes.

Keywords: deep learning, computer vision, cigarette smoke detection, YOLOV3, color feature extraction

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9928 Seismic Response of Structure Using a Three Degree of Freedom Shake Table

Authors: Ketan N. Bajad, Manisha V. Waghmare

Abstract:

Earthquakes are the biggest threat to the civil engineering structures as every year it cost billions of dollars and thousands of deaths, around the world. There are various experimental techniques such as pseudo-dynamic tests – nonlinear structural dynamic technique, real time pseudo dynamic test and shaking table test method that can be employed to verify the seismic performance of structures. Shake table is a device that is used for shaking structural models or building components which are mounted on it. It is a device that simulates a seismic event using existing seismic data and nearly truly reproducing earthquake inputs. This paper deals with the use of shaking table test method to check the response of structure subjected to earthquake. The various types of shake table are vertical shake table, horizontal shake table, servo hydraulic shake table and servo electric shake table. The goal of this experiment is to perform seismic analysis of a civil engineering structure with the help of 3 degree of freedom (i.e. in X Y Z direction) shake table. Three (3) DOF shaking table is a useful experimental apparatus as it imitates a real time desired acceleration vibration signal for evaluating and assessing the seismic performance of structure. This study proceeds with the proper designing and erection of 3 DOF shake table by trial and error method. The table is designed to have a capacity up to 981 Newton. Further, to study the seismic response of a steel industrial building, a proportionately scaled down model is fabricated and tested on the shake table. The accelerometer is mounted on the model, which is used for recording the data. The experimental results obtained are further validated with the results obtained from software. It is found that model can be used to determine how the structure behaves in response to an applied earthquake motion, but the model cannot be used for direct numerical conclusions (such as of stiffness, deflection, etc.) as many uncertainties involved while scaling a small-scale model. The model shows modal forms and gives the rough deflection values. The experimental results demonstrate shake table as the most effective and the best of all methods available for seismic assessment of structure.

Keywords: accelerometer, three degree of freedom shake table, seismic analysis, steel industrial shed

Procedia PDF Downloads 130
9927 Space Debris Mitigation: Solutions from the Dark Skies of the Remote Australian Outback Using a Proposed Network of Mobile Astronomical Observatories

Authors: Muhammad Akbar Hussain, Muhammad Mehdi Hussain, Waqar Haider

Abstract:

There are tens of thousands of undetected and uncatalogued pieces of space debris in the Low Earth Orbit (LEO). They are not only difficult to be detected and tracked, their sheer number puts active satellites and humans in orbit around Earth into danger. With the entry of more governments and private companies into harnessing the Earth’s orbit for communication, research and military purposes, there is an ever-increasing need for not only the detection and cataloguing of these pieces of space debris, it is time to take measures to take them out and clean up the space around Earth. Current optical and radar-based Space Situational Awareness initiatives are useful mostly in detecting and cataloguing larger pieces of debris mainly for avoidance measures. Smaller than 10 cm pieces are in a relatively dark zone, yet these are deadly and capable of destroying satellites and human missions. A network of mobile observatories, connected to each other in real time and working in unison as a single instrument, may be able to detect small pieces of debris and achieve effective triangulation to help create a comprehensive database of their trajectories and parameters to the highest level of precision. This data may enable ground-based laser systems to help deorbit individual debris. Such a network of observatories can join current efforts in detection and removal of space debris in Earth’s orbit.

Keywords: space debris, low earth orbit, mobile observatories, triangulation, seamless operability

Procedia PDF Downloads 157
9926 Effect of Different Flours on the Physical and Sensorial Characteristics of Meatballs

Authors: Elif Aykin Dincer, Ozlem Kilic, Busra F. Bilgic, Mustafa Erbas

Abstract:

Stale breads and rusk flour are used traditionally in meatballs produced in Turkey as a structure enhancer. This study researches the possibilities of using retrograded wheat flour in the meatball production and compares the physical and sensorial characteristics of these meatballs with stale bread (traditional) and rusk (commercial) used meatballs. The cooking loss of meatballs produced with using retrograded flour was similar to that of commercial meatballs. These meatballs have an advantage with respect to cooking loss compared to traditional meatballs. Doses of retrograded flour from 5% to 20% led to a significant decrease in cooking loss, from 21.95% to 6.19%, and in the diameter of meatballs, from 18.60% to 12.74%, but to an increase in the thickness of meatballs, from 28.82% to 41.39%, respectively, compared to the control (0%). The springiness of the traditional meatballs was significantly higher than that of the other meatballs. This might have been due to the bread crumbs having a naturally springy structure. Moreover, the addition of retrograded flour in the meatballs significantly (P<0.05) affected the hardness, springiness and cohesiveness of the meatballs with respect to textural properties. In conclusion, it is considered that the use of 10% retrograded flour is ideal to improve the sensorial values of meatballs and the properties of their structure.

Keywords: cooking loss, flour, hardness, meatball, sensorial characteristics

Procedia PDF Downloads 282