Search results for: fibre networks
2960 Dimensioning of Circuit Switched Networks by Using Simulation Code Based On Erlang (B) Formula
Authors: Ali Mustafa Elshawesh, Mohamed Abdulali
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The paper presents an approach to dimension circuit switched networks and find the relationship between the parameters of the circuit switched networks on the condition of specific probability of call blocking. Our work is creating a Simulation code based on Erlang (B) formula to draw graphs which show two curves for each graph; one of simulation and the other of calculated. These curves represent the relationships between average number of calls and average call duration with the probability of call blocking. This simulation code facilitates to select the appropriate parameters for circuit switched networks.Keywords: Erlang B formula, call blocking, telephone system dimension, Markov model, link capacity
Procedia PDF Downloads 6112959 The Role of Online Social Networks in Social Movements: Social Polarization and Violations against Social Unity and Privacy of Individuals in Turkey
Authors: Tolga Yazıcı
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As a matter of the fact that online social networks like Twitter, Facebook and MySpace have experienced an extensive growth in recent years. Social media offers individuals with a tool for communicating and interacting with one another. These social networks enable people to stay in touch with other people and express themselves. This process makes the users of online social networks active creators of content rather than being only consumers of traditional media. That’s why millions of people show strong desire to learn the methods and tools of digital content production and necessary communication skills. However, the booming interest in communication and interaction through online social networks and high level of eagerness to invent and implement the ways to participate in content production raise some privacy and security concerns. This presentation aims to open the assumed revolutionary, democratic and liberating nature of the online social media up for discussion by reviewing some recent political developments in Turkey. Firstly, the role of Internet and online social networks in mobilizing collective movements through social interactions and communications will be questioned. Secondly, some cases from Gezi and Okmeydanı Protests and also December 17-25 period will be presented in order to illustrate misinformation and manipulation in social media and violation of individual privacy through online social networks in order to damage social unity and stability contradictory to democratic nature of online social networking.Keywords: online social media networks, democratic participation, social movements, social polarization, privacy of individuals, Turkey
Procedia PDF Downloads 3412958 Analysis of Lesotho Wool Production and Quality Trends 2008-2018
Authors: Papali Maqalika
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Lesotho farmers produce significant quantities of Merino wool of a quality competitive on the global market and make a substantial impact on the economy of Lesotho. However, even with the economic contribution, the production and quality information and trends of this fibre has been recognised nor documented. This is a sombre shortcoming as Lesotho wool is unknown on international markets. The situation is worsened by the fact that Lesotho wool is auction together with South African wool, trading and benchmarking Lesotho wool are difficult not to mention attempts to advance its production and quality. Based on the information above, available data on Lesotho wool for 10 years were collected and analysed for trends to used in benchmarking where applicable. The fibre properties analysed include fibre diameter (fineness), vegetable matter and yield, application and price. These were selected because they are fundamental in determining fibre quality and price. Production of wool in Lesotho has increased slightly over the ten years covered by this study. It also became apparent that production and quality trends of Lesotho wool are greatly influenced by the farming practices, breed of sheep and climatic conditions. Greater adoption of the merino sheep breed, sheds/barns and sheep coats are suggested as ways to reduce mortality rate (due to extremely cold temperatures), to reduce the vegetable matter on the fibre thus improving the quality and increase yield per sheep and production as a whole. Some farming practices such as the lack of barns, supplementary feeding and veterinary care present constraints in wool production. The districts in the Highlands region were found to have the highest production of mostly wool, this being ascribed to better pastures, climatic, social and other conditions conducive to wool production. The production of Lesotho wool and its quality can be improved further, possibly because of the interventions the Ministry of Agriculture introduced through the Small Agricultural and Development Project (SADP) and other appropriate initiatives by the National Wool and Mohair Growers Association (NWMGA). The challenge however, remains the lack of direct involvement of the wool growers (farmers) in decisions making and policy development, this potentially influences and may lead to the reluctance to adopt the strategies. In some cases, the wool growers do not receive the benefits associated with the interventions immediately. Based on these discoveries; it is recommended that the relevant educators and researchers in wool and textile science, as well as the local wool farmers in Lesotho, be represented in policy and other decision making forums relating to these interventions. In this way, educational campaigns and training workshops will be demand driven with a better chance of adoption and success. This is because the direct beneficiaries will have been involved at inception and they will have a sense of ownership as well as intent to see them through successfully.Keywords: lesotho wool, wool quality, wool production, lesotho economy, global market, apparel wool, database, textile science, exports, animal farming practices, intimate apparel, interventions
Procedia PDF Downloads 902957 Enhancement of Mechanical Properties and Thermal Conductivity of Oil Palm Shell Lightweight Concrete Reinforced with High Performance Polypropylene Fibres
Authors: Leong Tatt Loh, Ming Kun Yew, Ming Chian Yew, Lip Huat Saw, Jing Han Beh, Siong Kang Lim, Foo Wei Lee
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Oil palm shell (OPS) is the solid waste product from the palm oil sector of the agricultural industry and can be used as alternative coarse aggregates to substitute depleting conventional raw materials. This research aims to investigate the incorporation of various high-performance polypropylene (HPP) fibres with different geometry to enhance the mechanical properties and thermal conductivity of OPS lightweight concrete. The effect of different volume fractions (Vf) (0.05%, 0.10% and 0.15%) were studied for each fibre. The results reveal that the effectiveness of HPP fibres to increase the compressive strength at later ages was more pronounced than at early age. It is found that the use of HPP fibres reinforced OPS lightweight concrete (LWC) induced the advantageous of improving mechanical properties (compressive strength, flexural strength and splitting tensile strength) and thermal conductivity. Hence, this HPP fibres is a promising alternative solution to compensate lower mechanical properties as well as contribute to energy efficiency building material in the construction industry.Keywords: oil palm shell, high performance polypropylene fibre, lightweight concrete, mechanical properties, thermal conductivity
Procedia PDF Downloads 2072956 Algorithm and Software Based on Multilayer Perceptron Neural Networks for Estimating Channel Use in the Spectral Decision Stage in Cognitive Radio Networks
Authors: Danilo López, Johana Hernández, Edwin Rivas
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The use of the Multilayer Perceptron Neural Networks (MLPNN) technique is presented to estimate the future state of use of a licensed channel by primary users (PUs); this will be useful at the spectral decision stage in cognitive radio networks (CRN) to determine approximately in which time instants of future may secondary users (SUs) opportunistically use the spectral bandwidth to send data through the primary wireless network. To validate the results, sequences of occupancy data of channel were generated by simulation. The results show that the prediction percentage is greater than 60% in some of the tests carried out.Keywords: cognitive radio, neural network, prediction, primary user
Procedia PDF Downloads 3712955 Analysis of Splicing Methods for High Speed Automated Fibre Placement Applications
Authors: Phillip Kearney, Constantina Lekakou, Stephen Belcher, Alessandro Sordon
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The focus in the automotive industry is to reduce human operator and machine interaction, so manufacturing becomes more automated and safer. The aim is to lower part cost and construction time as well as defects in the parts, sometimes occurring due to the physical limitations of human operators. A move to automate the layup of reinforcement material in composites manufacturing has resulted in the use of tapes that are placed in position by a robotic deposition head, also described as Automated Fibre Placement (AFP). The process of AFP is limited with respect to the finite amount of material that can be loaded into the machine at any one time. Joining two batches of tape material together involves a splice to secure the ends of the finishing tape to the starting edge of the new tape. The splicing method of choice for the majority of prepreg applications is a hand stich method, and as the name suggests requires human input to achieve. This investigation explores three methods for automated splicing, namely, adhesive, binding and stitching. The adhesive technique uses an additional adhesive placed on the tape ends to be joined. Binding uses the binding agent that is already impregnated onto the tape through the application of heat. The stitching method is used as a baseline to compare the new splicing methods to the traditional technique currently in use. As the methods will be used within a High Speed Automated Fibre Placement (HSAFP) process, this meant the parameters of the splices have to meet certain specifications: (a) the splice must be able to endure a load of 50 N in tension applied at a rate of 1 mm/s; (b) the splice must be created in less than 6 seconds, dictated by the capacity of the tape accumulator within the system. The samples for experimentation were manufactured with controlled overlaps, alignment and splicing parameters, these were then tested in tension using a tensile testing machine. Initial analysis explored the use of the impregnated binding agent present on the tape, as in the binding splicing technique. It analysed the effect of temperature and overlap on the strength of the splice. It was found that the optimum splicing temperature was at the higher end of the activation range of the binding agent, 100 °C. The optimum overlap was found to be 25 mm; it was found that there was no improvement in bond strength from 25 mm to 30 mm overlap. The final analysis compared the different splicing methods to the baseline of a stitched bond. It was found that the addition of an adhesive was the best splicing method, achieving a maximum load of over 500 N compared to the 26 N load achieved by a stitching splice and 94 N by the binding method.Keywords: analysis, automated fibre placement, high speed, splicing
Procedia PDF Downloads 1552954 Experimental Networks Synchronization of Chua’s Circuit in Different Topologies
Authors: Manuel Meranza-Castillon, Rolando Diaz-Castillo, Adrian Arellano-Delgado, Cesar Cruz-Hernandez, Rosa Martha Lopez-Gutierrez
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In this work, we deal with experimental network synchronization of chaotic nodes with different topologies. Our approach is based on complex system theory, and we use a master-slave configuration to couple the nodes in the networks. In particular, we design and implement electronically complex dynamical networks composed by nine coupled chaotic Chua’s circuits with topologies: in nearest-neighbor, small-world, open ring, star, and global. Also, network synchronization is evaluated according to a particular coupling strength for each topology. This study is important by the possible applications to private transmission of information in a chaotic communication network of multiple users.Keywords: complex networks, Chua's circuit, experimental synchronization, multiple users
Procedia PDF Downloads 3482953 Multiple Query Optimization in Wireless Sensor Networks Using Data Correlation
Authors: Elaheh Vaezpour
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Data sensing in wireless sensor networks is done by query deceleration the network by the users. In many applications of the wireless sensor networks, many users send queries to the network simultaneously. If the queries are processed separately, the network’s energy consumption will increase significantly. Therefore, it is very important to aggregate the queries before sending them to the network. In this paper, we propose a multiple query optimization framework based on sensors physical and temporal correlation. In the proposed method, queries are merged and sent to network by considering correlation among the sensors in order to reduce the communication cost between the sensors and the base station.Keywords: wireless sensor networks, multiple query optimization, data correlation, reducing energy consumption
Procedia PDF Downloads 3342952 Prediction of Wind Speed by Artificial Neural Networks for Energy Application
Authors: S. Adjiri-Bailiche, S. M. Boudia, H. Daaou, S. Hadouche, A. Benzaoui
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In this work the study of changes in the wind speed depending on the altitude is calculated and described by the model of the neural networks, the use of measured data, the speed and direction of wind, temperature and the humidity at 10 m are used as input data and as data targets at 50m above sea level. Comparing predict wind speeds and extrapolated at 50 m above sea level is performed. The results show that the prediction by the method of artificial neural networks is very accurate.Keywords: MATLAB, neural network, power low, vertical extrapolation, wind energy, wind speed
Procedia PDF Downloads 6922951 Uplink Throughput Prediction in Cellular Mobile Networks
Authors: Engin Eyceyurt, Josko Zec
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The current and future cellular mobile communication networks generate enormous amounts of data. Networks have become extremely complex with extensive space of parameters, features and counters. These networks are unmanageable with legacy methods and an enhanced design and optimization approach is necessary that is increasingly reliant on machine learning. This paper proposes that machine learning as a viable approach for uplink throughput prediction. LTE radio metric, such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), and Signal to Noise Ratio (SNR) are used to train models to estimate expected uplink throughput. The prediction accuracy with high determination coefficient of 91.2% is obtained from measurements collected with a simple smartphone application.Keywords: drive test, LTE, machine learning, uplink throughput prediction
Procedia PDF Downloads 1572950 A Learning Automata Based Clustering Approach for Underwater Sensor Networks to Reduce Energy Consumption
Authors: Motahareh Fadaei
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Wireless sensor networks that are used to monitor a special environment, are formed from a large number of sensor nodes. The role of these sensors is to sense special parameters from ambient and to make connection. In these networks, the most important challenge is the management of energy usage. Clustering is one of the methods that are broadly used to face this challenge. In this paper, a distributed clustering protocol based on learning automata is proposed for underwater wireless sensor networks. The proposed algorithm that is called LA-Clustering forms clusters in the same energy level, based on the energy level of nodes and the connection radius regardless of size and the structure of sensor network. The proposed approach is simulated and is compared with some other protocols with considering some metrics such as network lifetime, number of alive nodes, and number of transmitted data. The simulation results demonstrate the efficiency of the proposed approach.Keywords: clustering, energy consumption, learning automata, underwater sensor networks
Procedia PDF Downloads 3142949 Experimental Investigation of Damaged Reinforced Concrete Beams Repaired with Carbon Fibre Reinforced Polymer (CFRP) Strip under Impact Loading
Authors: M. Al-Farttoosi, M. Y. Rafiq, J. Summerscales, C. Williams
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Many buildings and bridges are damaged due to impact loading, explosions, terrorist attacks and wars. Most of the damaged structures members such as beams, columns and slabs are not totally failed and it can be repaired. Nowadays, carbon fibre reinforced polymer CFRP has been wildly used in strengthening and retrofitting the structures members. CFRP can rector the load carrying capacity of the damaged structures members to make them serviceable. An experimental investigation was conducted to investigate the impact behaviour of the damaged beams repaired with CFRP. The tested beams had different degrees of damage and near surface mounted technique NSM was used to install the CFRP. A heavy drop weight impact test machine was used to conduct the experimental work. The study investigated the impact strength, stiffness, cracks and deflection of the CFRP repaired beams. The results show that CFRP significantly increased the impact resistance of the damaged beams. CFRP increased the damaged beams stiffness and reduced the deflection. The results showed that the NSM technique is more effective in repairing beams and preventing the debonding of the CFRP.Keywords: damaged, concrete, impact, repaired
Procedia PDF Downloads 3442948 Detecting Black Hole Attacks in Body Sensor Networks
Authors: Sara Alshehri, Bayan Alenzi, Atheer Alshehri, Samia Chelloug, Zainab Almry, Hussah Albugmai
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This paper concerns body area networks sensor that collect signals around a human body. The black hole attacks are the main security challenging problem because the data traffic can be dropped at any node. The focus of our proposed solution is to efficiently route data packets while detecting black hole nodes.Keywords: body sensor networks, security, black hole, routing, broadcasting, OMNeT++
Procedia PDF Downloads 6452947 Detecting and Secluding Route Modifiers by Neural Network Approach in Wireless Sensor Networks
Authors: C. N. Vanitha, M. Usha
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In a real world scenario, the viability of the sensor networks has been proved by standardizing the technologies. Wireless sensor networks are vulnerable to both electronic and physical security breaches because of their deployment in remote, distributed, and inaccessible locations. The compromised sensor nodes send malicious data to the base station, and thus, the total network effectiveness will possibly be compromised. To detect and seclude the Route modifiers, a neural network based Pattern Learning predictor (PLP) is presented. This algorithm senses data at any node on present and previous patterns obtained from the en-route nodes. The eminence of any node is upgraded by their predicted and reported patterns. This paper propounds a solution not only to detect the route modifiers, but also to seclude the malevolent nodes from the network. The simulation result proves the effective performance of the network by the presented methodology in terms of energy level, routing and various network conditions.Keywords: neural networks, pattern learning, security, wireless sensor networks
Procedia PDF Downloads 4042946 Adequacy of Museums' Internet Resources to Infantile and Young Public
Authors: Myriam Ferreira
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Websites and social networks allow museums to divulge their works by new and attractive means. Besides, these technologies provide tools to generate a new history of art’s contents and promote visits to their installations. At the same time, museums are proposing more and more activities to families, children and young people. However, these activities usually take place in the museum’s physical installations, while websites and social networks seem to be mainly targeted to adults. The problem is that being children and young people digital natives, they feel apart from museums, so they need a presence of museums in digital means to feel attracted to them. Some institutions are making efforts to fill this vacuum. In this paper, resources designed specifically for children and teenagers have been selected from websites and social networks of five Spanish Museums: Prado Museum, Thyssen Museum, Guggenheim Museum, America Museum and Cerralbo Museum. After that, we have carried out an investigation in a school with children and teenagers between 11 and 15 years old. Those young people have been asked about their valuation of those web pages and social networks, with quantitative-qualitative questions. The results show that the least rated resources were videos and social networks because they were considered ‘too serious’, while the most rated were games and augmented reality. These ratings confirm theoretical papers that affirm that the future of technologies applied to museums is edutainment and interaction.Keywords: children, museums, social networks, teenagers, websites
Procedia PDF Downloads 1492945 Influence of Packing Density of Layers Placed in Specific Order in Composite Nonwoven Structure for Improved Filtration Performance
Authors: Saiyed M Ishtiaque, Priyal Dixit
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Objectives: An approach is being suggested to design the filter media to maximize the filtration efficiency with minimum possible pressure drop of composite nonwoven by incorporating the layers of different packing densities induced by fibre of different deniers and punching parameters by using the concept of sequential punching technique in specific order in layered composite nonwoven structure. X-ray computed tomography technique is used to measure the packing density along the thickness of layered nonwoven structure composed by placing the layer of differently oriented fibres influenced by fibres of different deniers and punching parameters in various combinations to minimize the pressure drop at maximum possible filtration efficiency. Methodology Used: This work involves preparation of needle punched layered structure with batts 100g/m2 basis weight having fibre denier, punch density and needle penetration depth as variables to produce 300 g/m2 basis weight nonwoven composite. X-ray computed tomography technique is used to measure the packing density along the thickness of layered nonwoven structure composed by placing the layers of differently oriented fibres influenced by considered variables in various combinations. to minimize the pressure drop at maximum possible filtration efficiencyFor developing layered nonwoven fabrics, batts made of fibre of different deniers having 100g/m2 each basis weight were placed in various combinations. For second set of experiment, the composite nonwoven fabrics were prepared by using 3 denier circular cross section polyester fibre having 64 mm length on needle punched nonwoven machine by using the sequential punching technique to prepare the composite nonwoven fabrics. In this technique, three semi punched fabrics of 100 g/m2 each having either different punch densities or needle penetration depths were prepared for first phase of fabric preparation. These fabrics were later punched altogether to obtain the overall basis weight of 300 g/m2. The total punch density of the composite nonwoven fabric was kept at 200 punches/ cm2 with a needle penetration depth of 10 mm. The layered structures so formed were subcategorised into two groups- homogeneous layered structure in which all the three batts comprising the nonwoven fabric were made from same denier of fibre, punch density and needle penetration depth and were placed in different positions in respective fabric and heterogeneous layered structure in which batts were made from fibres of different deniers, punch densities and needle penetration depths and were placed in different positions. Contributions: The results concluded that reduction in pressure drop is not derived by the overall packing density of the layered nonwoven fabric rather sequencing of layers of specific packing density in layered structure decides the pressure drop. Accordingly, creation of inverse gradient of packing density in layered structure provided maximum filtration efficiency with least pressure drop. This study paves the way for the possibility of customising the composite nonwoven fabrics by the incorporation of differently oriented fibres in constituent layers induced by considered variablres for desired filtration properties.Keywords: filtration efficiency, layered nonwoven structure, packing density, pressure drop
Procedia PDF Downloads 762944 A Fast Community Detection Algorithm
Authors: Chung-Yuan Huang, Yu-Hsiang Fu, Chuen-Tsai Sun
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Community detection represents an important data-mining tool for analyzing and understanding real-world complex network structures and functions. We believe that at least four criteria determine the appropriateness of a community detection algorithm: (a) it produces useable normalized mutual information (NMI) and modularity results for social networks, (b) it overcomes resolution limitation problems associated with synthetic networks, (c) it produces good NMI results and performance efficiency for Lancichinetti-Fortunato-Radicchi (LFR) benchmark networks, and (d) it produces good modularity and performance efficiency for large-scale real-world complex networks. To our knowledge, no existing community detection algorithm meets all four criteria. In this paper, we describe a simple hierarchical arc-merging (HAM) algorithm that uses network topologies and rule-based arc-merging strategies to identify community structures that satisfy the criteria. We used five well-studied social network datasets and eight sets of LFR benchmark networks to validate the ground-truth community correctness of HAM, eight large-scale real-world complex networks to measure its performance efficiency, and two synthetic networks to determine its susceptibility to resolution limitation problems. Our results indicate that the proposed HAM algorithm is capable of providing satisfactory performance efficiency and that HAM-identified communities were close to ground-truth communities in social and LFR benchmark networks while overcoming resolution limitation problems.Keywords: complex network, social network, community detection, network hierarchy
Procedia PDF Downloads 2272943 Analysis of Delivery of Quad Play Services
Authors: Rahul Malhotra, Anurag Sharma
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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: FTTH, quad play, play service, access networks, data rate
Procedia PDF Downloads 4152942 Study of the Influence of the Different Treatments in Almond Shell-Based Masterbatches
Authors: A. Ibáñez, A. Martínez, A. Sánchez, M. A. León
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This article is focused on the development of a series of biodegradable and eco-friendly masterbatches based on polylactic acid (PLA) filled with almond shell to study the influence of almond shell in the properties of injected biodegradable parts. These innovative masterbatches have 20 wt % of the almond shell. Different treatments were carried out with sodium hydroxide (NaOH) and maleic anhydride (MA) to obtain better interfacial bonding between fibre and matrix. The masterbatches were produced by varying the fibre treatments (type of treatment, concentration and temperature). The masterbatches have been injected to obtain standardised test samples in order to study mechanical properties. The results show that, the some of the treated fibres present slightly higher flexural modulus and impact strength than untreated fibres. This study is part of a LIFE project (MASTALMOND) aimed to create and test at preindustrial level new coloured masterbatches based on biodegradable polymers and containing in its formulation a high percentage of almond shell, a natural waste material, which firstly will permit to cover technical requirements of two traditional industrial sectors: toy and furniture, although the results achieved could be extended to other industrial sectors.Keywords: additivation, almond shell, biodegradable, masterbatch, PLA, injection moulding
Procedia PDF Downloads 4262941 Laboratory Studies to Assess the Effect of Recron Fiber on Soil Subgrade Characteristics
Authors: Lokesh Gupta, Rakesh Kumar
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Stabilization of weak subgrade soil is mainly aimed for the improvement of soil strength and its durability. Highway engineers are concerned to get the soil material or system that will hold under the design use conditions and for the designed life of the engineering project. The present study envisages the effect of Recron fibres mixed in different proportion (up to 1% by weight of dry soil) on Atterberg limits, Compaction of the soil, California bearing ratio (CBR) values and unconfined compressive strength (UCS) of the soil. The present study deals with the influence of varying in length (20 mm, 30mm, 40mm and 50mm) and percentage (0.25 %, 0.50 %, 0.75 % and 1.0 %) of fibre added to the soil samples. The aim of study is to determine the reinforcing effect of randomly distributed fibres on the Compaction characteristics, penetration resistance and unconfined compressive strength of soils. The addition of fibres leads to an increase in the optimum moisture content and decrease in maximum dry density. With the addition of the fibres, the increases in CBR and UCS values are observed. The test result shows higher CBR and unconfined compressive strength value for the soil reinforced with 0.5% Recron fibre, once keeping aspect ratio as 160.Keywords: soil, recron fiber, unconfined compressive strength (UCS), California bearing ratio (CBR)
Procedia PDF Downloads 1642940 Study on the Efficient Routing Algorithms in Delay-Tolerant Networks
Authors: Si-Gwan Kim
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In Delay Tolerant Networks (DTN), there may not exist an end-to-end path between source and destination at the time of message transmission. Employing ‘Store Carry and Forward’ delivery mechanism for message transmission in such networks usually incurs long message delays. In this paper, we present the modified Binary Spray and Wait (BSW) routing protocol that enhances the performance of the original one. Our proposed algorithm adjusts the number of forward messages depending on the number of neighbor nodes. By using beacon messages periodically, the number of neighbor nodes can be managed. The simulation using ONE simulator results shows that our modified version gives higher delivery ratio and less latency as compared to BSW.Keywords: delay tolerant networks, store carry and forward, one simulator, binary spray and wait
Procedia PDF Downloads 1232939 Comparison of Classical Computer Vision vs. Convolutional Neural Networks Approaches for Weed Mapping in Aerial Images
Authors: Paulo Cesar Pereira Junior, Alexandre Monteiro, Rafael da Luz Ribeiro, Antonio Carlos Sobieranski, Aldo von Wangenheim
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In this paper, we present a comparison between convolutional neural networks and classical computer vision approaches, for the specific precision agriculture problem of weed mapping on sugarcane fields aerial images. A systematic literature review was conducted to find which computer vision methods are being used on this specific problem. The most cited methods were implemented, as well as four models of convolutional neural networks. All implemented approaches were tested using the same dataset, and their results were quantitatively and qualitatively analyzed. The obtained results were compared to a human expert made ground truth for validation. The results indicate that the convolutional neural networks present better precision and generalize better than the classical models.Keywords: convolutional neural networks, deep learning, digital image processing, precision agriculture, semantic segmentation, unmanned aerial vehicles
Procedia PDF Downloads 2602938 Demand Forecasting Using Artificial Neural Networks Optimized by Particle Swarm Optimization
Authors: Daham Owaid Matrood, Naqaa Hussein Raheem
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Evolutionary algorithms and Artificial neural networks (ANN) are two relatively young research areas that were subject to a steadily growing interest during the past years. This paper examines the use of Particle Swarm Optimization (PSO) to train a multi-layer feed forward neural network for demand forecasting. We use in this paper weekly demand data for packed cement and towels, which have been outfitted by the Northern General Company for Cement and General Company of prepared clothes respectively. The results showed superiority of trained neural networks using particle swarm optimization on neural networks trained using error back propagation because their ability to escape from local optima.Keywords: artificial neural network, demand forecasting, particle swarm optimization, weight optimization
Procedia PDF Downloads 4522937 Taxonomy of Threats and Vulnerabilities in Smart Grid Networks
Authors: Faisal Al Yahmadi, Muhammad R. Ahmed
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Electric power is a fundamental necessity in the 21st century. Consequently, any break in electric power is probably going to affect the general activity. To make the power supply smooth and efficient, a smart grid network is introduced which uses communication technology. In any communication network, security is essential. It has been observed from several recent incidents that adversary causes an interruption to the operation of networks. In order to resolve the issues, it is vital to understand the threats and vulnerabilities associated with the smart grid networks. In this paper, we have investigated the threats and vulnerabilities in Smart Grid Networks (SGN) and the few solutions in the literature. Proposed solutions showed developments in electricity theft countermeasures, Denial of services attacks (DoS) and malicious injection attacks detection model, as well as malicious nodes detection using watchdog like techniques and other solutions.Keywords: smart grid network, security, threats, vulnerabilities
Procedia PDF Downloads 1392936 The Study of ZigBee Protocol Application in Wireless Networks
Authors: Ardavan Zamanpour, Somaieh Yassari
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ZigBee protocol network was developed in industries and MIT laboratory in 1997. ZigBee is a wireless networking technology by alliance ZigBee which is designed to low board and low data rate applications. It is a Protocol which connects between electrical devises with very low energy and cost. The first version of IEEE 802.15.4 which was formed ZigBee was based on 2.4GHZ MHZ 912MHZ 868 frequency band. The name of system is often reminded random directions that bees (BEES) traversing during pollination of products. Such as alloy of the ways in which information packets are traversed within the mesh network. This paper aims to study the performance and effectiveness of this protocol in wireless networks.Keywords: ZigBee, protocol, wireless, networks
Procedia PDF Downloads 3692935 An Interactive Methodology to Demonstrate the Level of Effectiveness of the Synthesis of Local-Area Networks
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This study focuses on disconfirming that wide-area networks can be made mobile, highly-available, and wireless. This methodological test shows that IPv7 and context-free grammar are mismatched. In the cases of robots, a similar tendency is also revealed. Further, we also prove that public-private key pairs could be built embedded, adaptive, and wireless. Finally, we disconfirm that although hash tables can be made distributed, interposable, and autonomous, XML and DNS can interfere to realize this purpose. Our experiments soon proved that exokernelizing our replicated Knesis keyboards was more significant than interrupting them. Our experiments exhibited degraded average sampling rate.Keywords: collaborative communication, DNS, local-area networks, XML
Procedia PDF Downloads 1872934 Automated Machine Learning Algorithm Using Recurrent Neural Network to Perform Long-Term Time Series Forecasting
Authors: Ying Su, Morgan C. Wang
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Long-term time series forecasting is an important research area for automated machine learning (AutoML). Currently, forecasting based on either machine learning or statistical learning is usually built by experts, and it requires significant manual effort, from model construction, feature engineering, and hyper-parameter tuning to the construction of the time series model. Automation is not possible since there are too many human interventions. To overcome these limitations, this article proposed to use recurrent neural networks (RNN) through the memory state of RNN to perform long-term time series prediction. We have shown that this proposed approach is better than the traditional Autoregressive Integrated Moving Average (ARIMA). In addition, we also found it is better than other network systems, including Fully Connected Neural Networks (FNN), Convolutional Neural Networks (CNN), and Nonpooling Convolutional Neural Networks (NPCNN).Keywords: automated machines learning, autoregressive integrated moving average, neural networks, time series analysis
Procedia PDF Downloads 1052933 Anomaly Detection with ANN and SVM for Telemedicine Networks
Authors: Edward Guillén, Jeisson Sánchez, Carlos Omar Ramos
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In recent years, a wide variety of applications are developed with Support Vector Machines -SVM- methods and Artificial Neural Networks -ANN-. In general, these methods depend on intrusion knowledge databases such as KDD99, ISCX, and CAIDA among others. New classes of detectors are generated by machine learning techniques, trained and tested over network databases. Thereafter, detectors are employed to detect anomalies in network communication scenarios according to user’s connections behavior. The first detector based on training dataset is deployed in different real-world networks with mobile and non-mobile devices to analyze the performance and accuracy over static detection. The vulnerabilities are based on previous work in telemedicine apps that were developed on the research group. This paper presents the differences on detections results between some network scenarios by applying traditional detectors deployed with artificial neural networks and support vector machines.Keywords: anomaly detection, back-propagation neural networks, network intrusion detection systems, support vector machines
Procedia PDF Downloads 3572932 Development of a Paediatric Head Model for the Computational Analysis of Head Impact Interactions
Authors: G. A. Khalid, M. D. Jones, R. Prabhu, A. Mason-Jones, W. Whittington, H. Bakhtiarydavijani, P. S. Theobald
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Head injury in childhood is a common cause of death or permanent disability from injury. However, despite its frequency and significance, there is little understanding of how a child’s head responds during injurious loading. Whilst Infant Post Mortem Human Subject (PMHS) experimentation is a logical approach to understand injury biomechanics, it is the authors’ opinion that a lack of subject availability is hindering potential progress. Computer modelling adds great value when considering adult populations; however, its potential remains largely untapped for infant surrogates. The complexities of child growth and development, which result in age dependent changes in anatomy, geometry and physical response characteristics, present new challenges for computational simulation. Further geometric challenges are presented by the intricate infant cranial bones, which are separated by sutures and fontanelles and demonstrate a visible fibre orientation. This study presents an FE model of a newborn infant’s head, developed from high-resolution computer tomography scans, informed by published tissue material properties. To mimic the fibre orientation of immature cranial bone, anisotropic properties were applied to the FE cranial bone model, with elastic moduli representing the bone response both parallel and perpendicular to the fibre orientation. Biofiedility of the computational model was confirmed by global validation against published PMHS data, by replicating experimental impact tests with a series of computational simulations, in terms of head kinematic responses. Numerical results confirm that the FE head model’s mechanical response is in favourable agreement with the PMHS drop test results.Keywords: finite element analysis, impact simulation, infant head trauma, material properties, post mortem human subjects
Procedia PDF Downloads 3262931 The Realization of a System’s State Space Based on Markov Parameters by Using Flexible Neural Networks
Authors: Ali Isapour, Ramin Nateghi
Abstract:
— Markov parameters are unique parameters of the system and remain unchanged under similarity transformations. Markov parameters from a power series that is convergent only if the system matrix’s eigenvalues are inside the unity circle. Therefore, Markov parameters of a stable discrete-time system are convergent. In this study, we aim to realize the system based on Markov parameters by using Artificial Neural Networks (ANN), and this end, we use Flexible Neural Networks. Realization means determining the elements of matrices A, B, C, and D.Keywords: Markov parameters, realization, activation function, flexible neural network
Procedia PDF Downloads 194