Search results for: network capacity
8220 Optimal Decisions for Personalized Products with Demand Information Updating and Limited Capacity
Authors: Meimei Zheng
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Product personalization could not only bring new profits to companies but also provide the direction of long-term development for companies. However, the characteristics of personalized product cause some new problems. This paper investigates how companies make decisions on the supply of personalized products when facing different customer attitudes to personalized product and service, constraints due to limited capacity and updates of personalized demand information. This study will provide optimal decisions for companies to develop personalized markets, resulting in promoting business transformation and improving business competitiveness.Keywords: demand forecast updating, limited capacity, personalized products, optimization
Procedia PDF Downloads 2598219 The Effect of an Infill on the Bearing Capacity and Stiffness of Infilled Frames
Authors: Goran Baloevic, Jure Radnic, Nikola Grgic
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The application of frames with masonry or panel infill is common in the engineering practice. In these cases, a frame is often considered to be a primary structure, while an infill is considered to be a secondary structure. In past calculations, the infill was rarely included in the design of frame structures in terms of their bearing capacity and safety. Recent calculations of such structures necessarily include the effect of infill since it contributes to stiffness and bearing capacity of overall system, especially under horizontal loads. In certain cases, if the infill is not included in the seismic design of frame structures, the result can be lower design safety. However, since the different configuration of the infill through the building’s height can be made, it is possible that contribution of such infill to the overall bearing capacity can be lower and seismic forces on the building can be increased due to greater stiffness of the structure. So far, many experimental and numerical researches on the behavior of infilled frames under horizontal static forces and earthquake have been performed. In this paper, several masonry-infilled concrete and steel frames under horizontal static forces and earthquake are analysed. The experimental results by shake-table and numerical results are compared in terms of the bearing capacity of bare and infilled frames. Herein, the stiffness of frames and infill were varied, with different position of the infill and different types of openings. Cases with positive and negative effects of the infill to the bearing capacity of the frames were considered. Finally, main conclusions and recommendations for practical application and design of masonry-infilled concrete and steel frames are given.Keywords: bearing capacity, infilled frame, numerical model, shake table
Procedia PDF Downloads 4638218 The Relation Between Social Capital and Trust with Social Network Analysis (SNA)
Authors: Safak Baykal
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The purpose of this study is analyzing the relationship between self leadership and social capital of people with using Social Network Analysis. In this study, two aspects of social capital will be focused: bonding, homophilous social capital (BoSC) which implies better, strong, dense or closed network ties, and bridging, heterophilous social capital (BrSC) which implies weak ties, bridging the structural holes. The other concept of the study is Trust (Tr), namely interpersonal trust, willingness to ascribe good intentions to and have confidence in the words and actions of other people. In this study, the sample group, 61 people, was selected from a private firm from the defense industry. The relation between BoSC/BrSC and Tr is shown by using Social Network Analysis (SNA) and statistical analysis with Likert type-questionnaire. The results of the analysis show the Cronbach’s alpha value is 0.73 and social capital values (BoSC/BrSC) is highly correlated with Tr values of the people.Keywords: bonding social capital, bridging social capital, trust, social network analysis (SNA)
Procedia PDF Downloads 5278217 In the Study of Co₂ Capacity Performance of Different Frothing Agents through Process Simulation
Authors: Muhammad Idrees, Masroor Abro, Sikandar Almani
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Presently, the increasing CO₂ concentration in the atmosphere has been taken as one of the major challenges faced by the modern world. The average CO₂ in the atmosphere reached the highest value of 414.72 ppm in 2021, as reported in a conference of the parties (COP26). This study focuses on (i) the comparative study of MEA, NaOH, Acetic acid, and Na₂CO₃ in terms of their CO₂ capture performance, (ii) the significance of adding various frothing agents achieving improved absorption capacity of Na₂CO₃ and (iii) the overall economic evaluation of process with the help of Aspen Plus. The results obtained suggest that the addition of frothing agents significantly increased the absorption rate of dilute sodium carbonate such that from 45% to 99.9%. The effect of temperature, pressure and flow rate of liquid and flue gas streams on CO₂ absorption capacity was also investigated. It was found that the absorption capacity of Na₂CO₃ decreased with increasing temperature of the liquid stream and decreasing flow rate of the liquid stream and pressure of the gas stream.Keywords: CO₂, absorbents, frothing agents, process simulation
Procedia PDF Downloads 758216 Exploring Deep Neural Network Compression: An Overview
Authors: Ghorab Sara, Meziani Lila, Rubin Harvey Stuart
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The rapid growth of deep learning has led to intricate and resource-intensive deep neural networks widely used in computer vision tasks. However, their complexity results in high computational demands and memory usage, hindering real-time application. To address this, research focuses on model compression techniques. The paper provides an overview of recent advancements in compressing neural networks and categorizes the various methods into four main approaches: network pruning, quantization, network decomposition, and knowledge distillation. This paper aims to provide a comprehensive outline of both the advantages and limitations of each method.Keywords: model compression, deep neural network, pruning, knowledge distillation, quantization, low-rank decomposition
Procedia PDF Downloads 428215 Aggregate Fluctuations and the Global Network of Input-Output Linkages
Authors: Alexander Hempfing
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The desire to understand business cycle fluctuations, trade interdependencies and co-movement has a long tradition in economic thinking. From input-output economics to business cycle theory, researchers aimed to find appropriate answers from an empirical as well as a theoretical perspective. This paper empirically analyses how the production structure of the global economy and several states developed over time, what their distributional properties are and if there are network specific metrics that allow identifying structurally important nodes, on a global, national and sectoral scale. For this, the World Input-Output Database was used, and different statistical methods were applied. Empirical evidence is provided that the importance of the Eastern hemisphere in the global production network has increased significantly between 2000 and 2014. Moreover, it was possible to show that the sectoral eigenvector centrality indices on a global level are power-law distributed, providing evidence that specific national sectors exist which are more critical to the world economy than others while serving as a hub within the global production network. However, further findings suggest, that global production cannot be characterized as a scale-free network.Keywords: economic integration, industrial organization, input-output economics, network economics, production networks
Procedia PDF Downloads 2758214 A Quantitative Study of the Evolution of Open Source Software Communities
Authors: M. R. Martinez-Torres, S. L. Toral, M. Olmedilla
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Typically, virtual communities exhibit the well-known phenomenon of participation inequality, which means that only a small percentage of users is responsible of the majority of contributions. However, the sustainability of the community requires that the group of active users must be continuously nurtured with new users that gain expertise through a participation process. This paper analyzes the time evolution of Open Source Software (OSS) communities, considering users that join/abandon the community over time and several topological properties of the network when modeled as a social network. More specifically, the paper analyzes the role of those users rejoining the community and their influence in the global characteristics of the network.Keywords: open source communities, social network Analysis, time series, virtual communities
Procedia PDF Downloads 5218213 Transmit Power Optimization for Cooperative Beamforming in Reverse-Link MIMO Ad-Hoc Networks
Authors: Younghyun Jeon, Seungjoo Maeng
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In the Ad-hoc network, the great interests regarding MIMO scheme leads to their combination, which is also utilized into its applicable network. We manage the field of the problem into Reverse-link MIMO Ad-hoc Network (RMAN) and propose the methodology to maximize the data rate with its power consumption using Node-Cooperative beamforming technique. Based on the result of mathematical optimization formulation, we design the algorithm to construct optimal orthogonal weight vector according to channel feedback and control its transmission power according to QoS-pricing value level. In simulation results, we show the validity of the proposed mathematical optimization result and algorithm which mean that the sum-rate of each link is converged into some point.Keywords: ad-hoc network, MIMO, cooperative beamforming, transmit power
Procedia PDF Downloads 3988212 Shear Strengthening of Reinforced Concrete Deep Beam Using Fiber Reinforced Polymer Strips
Authors: Ruqaya H. Aljabery
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Reinforced Concrete (RC) deep beams are one of the main critical structural elements in terms of safety since significant loads are carried in a short span. The shear capacity of these sections cannot be predicted accurately by the current design codes like ACI and EC2; thus, they must be investigated. In this research, non-linear behavior of RC deep beams strengthened in shear with Fiber Reinforced Polymer (FRP) strips, and the efficiency of FRP in terms of enhancing the shear capacity in RC deep beams are examined using Finite Element Analysis (FEA), which is conducted using the software ABAQUS. The effect of several parameters on the shear capacity of the RC deep beam are studied in this paper as well including the effect of the cross-sectional area of the FRP strip and the shear reinforcement area to the spacing ratio (As/S), and it was found that FRP enhances the shear capacity significantly and can be a substitution of steel stirrups resulting in a more economical design.Keywords: Abaqus, concrete, deep beam, finite element analysis, FRP, shear strengthening, strut-and-tie
Procedia PDF Downloads 1488211 A Multi-Objective Evolutionary Algorithm of Neural Network for Medical Diseases Problems
Authors: Sultan Noman Qasem
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This paper presents an evolutionary algorithm for solving multi-objective optimization problems-based artificial neural network (ANN). The multi-objective evolutionary algorithm used in this study is genetic algorithm while ANN used is radial basis function network (RBFN). The proposed algorithm named memetic elitist Pareto non-dominated sorting genetic algorithm-based RBFNN (MEPGAN). The proposed algorithm is implemented on medical diseases problems. The experimental results indicate that the proposed algorithm is viable, and provides an effective means to design multi-objective RBFNs with good generalization capability and compact network structure. This study shows that MEPGAN generates RBFNs coming with an appropriate balance between accuracy and simplicity, comparing to the other algorithms found in literature.Keywords: radial basis function network, hybrid learning, multi-objective optimization, genetic algorithm
Procedia PDF Downloads 5618210 Detection of COVID-19 Cases From X-Ray Images Using Capsule-Based Network
Authors: Donya Ashtiani Haghighi, Amirali Baniasadi
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Coronavirus (COVID-19) disease has spread abruptly all over the world since the end of 2019. Computed tomography (CT) scans and X-ray images are used to detect this disease. Different Deep Neural Network (DNN)-based diagnosis solutions have been developed, mainly based on Convolutional Neural Networks (CNNs), to accelerate the identification of COVID-19 cases. However, CNNs lose important information in intermediate layers and require large datasets. In this paper, Capsule Network (CapsNet) is used. Capsule Network performs better than CNNs for small datasets. Accuracy of 0.9885, f1-score of 0.9883, precision of 0.9859, recall of 0.9908, and Area Under the Curve (AUC) of 0.9948 are achieved on the Capsule-based framework with hyperparameter tuning. Moreover, different dropout rates are investigated to decrease overfitting. Accordingly, a dropout rate of 0.1 shows the best results. Finally, we remove one convolution layer and decrease the number of trainable parameters to 146,752, which is a promising result.Keywords: capsule network, dropout, hyperparameter tuning, classification
Procedia PDF Downloads 768209 Optimizing Heavy-Duty Green Hydrogen Refueling Stations: A Techno-Economic Analysis of Turbo-Expander Integration
Authors: Christelle Rabbat, Carole Vouebou, Sary Awad, Alan Jean-Marie
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Hydrogen has been proven to be a viable alternative to standard fuels as it is easy to produce and only generates water vapour and zero carbon emissions. However, despite the hydrogen benefits, the widespread adoption of hydrogen fuel cell vehicles and internal combustion engine vehicles is impeded by several challenges. The lack of refueling infrastructures remains one of the main hindering factors due to the high costs associated with their design, construction, and operation. Besides, the lack of hydrogen vehicles on the road diminishes the economic viability of investing in refueling infrastructure. Simultaneously, the absence of accessible refueling stations discourages consumers from adopting hydrogen vehicles, perpetuating a cycle of limited market uptake. To address these challenges, the implementation of adequate policies incentivizing the use of hydrogen vehicles and the reduction of the investment and operation costs of hydrogen refueling stations (HRS) are essential to put both investors and customers at ease. Even though the transition to hydrogen cars has been rather slow, public transportation companies have shown a keen interest in this highly promising fuel. Besides, their hydrogen demand is easier to predict and regulate than personal vehicles. Due to the reduced complexity of designing a suitable hydrogen supply chain for public vehicles, this sub-sector could be a great starting point to facilitate the adoption of hydrogen vehicles. Consequently, this study will focus on designing a chain of on-site green HRS for the public transportation network in Nantes Metropole leveraging the latest relevant technological advances aiming to reduce the costs while ensuring reliability, safety, and ease of access. To reduce the cost of HRS and encourage their widespread adoption, a network of 7 H35-T40 HRS has been designed, replacing the conventional J-T valves with turbo-expanders. Each station in the network has a daily capacity of 1,920 kg. Thus, the HRS network can produce up to 12.5 tH2 per day. The detailed cost analysis has revealed a CAPEX per station of 16.6 M euros leading to a network CAPEX of 116.2 M euros. The proposed station siting prioritized Nantes metropole’s 5 bus depots and included 2 city-centre locations. Thanks to the turbo-expander technology, the cooling capacity of the proposed HRS is 19% lower than that of a conventional station equipped with J-T valves, resulting in significant CAPEX savings estimated at 708,560 € per station, thus nearly 5 million euros for the whole HRS network. Besides, the turbo-expander power generation ranges from 7.7 to 112 kW. Thus, the power produced can be used within the station or sold as electricity to the main grid, which would, in turn, maximize the station’s profit. Despite the substantial initial investment required, the environmental benefits, cost savings, and energy efficiencies realized through the transition to hydrogen fuel cell buses and the deployment of HRS equipped with turbo-expanders offer considerable advantages for both TAN and Nantes Metropole. These initiatives underscore their enduring commitment to fostering green mobility and combatting climate change in the long term.Keywords: green hydrogen, refueling stations, turbo-expander, heavy-duty vehicles
Procedia PDF Downloads 538208 Learning a Bayesian Network for Situation-Aware Smart Home Service: A Case Study with a Robot Vacuum Cleaner
Authors: Eu Tteum Ha, Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu
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The smart home environment backed up by IoT (internet of things) technologies enables intelligent services based on the awareness of the situation a user is currently in. One of the convenient sensors for recognizing the situations within a home is the smart meter that can monitor the status of each electrical appliance in real time. This paper aims at learning a Bayesian network that models the causal relationship between the user situations and the status of the electrical appliances. Using such a network, we can infer the current situation based on the observed status of the appliances. However, learning the conditional probability tables (CPTs) of the network requires many training examples that cannot be obtained unless the user situations are closely monitored by any means. This paper proposes a method for learning the CPT entries of the network relying only on the user feedbacks generated occasionally. In our case study with a robot vacuum cleaner, the feedback comes in whenever the user gives an order to the robot adversely from its preprogrammed setting. Given a network with randomly initialized CPT entries, our proposed method uses this feedback information to adjust relevant CPT entries in the direction of increasing the probability of recognizing the desired situations. Simulation experiments show that our method can rapidly improve the recognition performance of the Bayesian network using a relatively small number of feedbacks.Keywords: Bayesian network, IoT, learning, situation -awareness, smart home
Procedia PDF Downloads 5218207 A Mixed Method Approach for Modeling Entry Capacity at Rotary Intersections
Authors: Antonio Pratelli, Lorenzo Brocchini, Reginald Roy Souleyrette
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A rotary is a traffic circle intersection where vehicles entering from branches give priority to circulating flow. Vehicles entering the intersection from converging roads move around the central island and weave out of the circle into their desired exiting branch. This creates merging and diverging conflicts among any entry and its successive exit, i.e., a section. Therefore, rotary capacity models are usually based on the weaving of the different movements in any section of the circle, and the maximum rate of flow value is then related to each weaving section of the rotary. Nevertheless, the single-section capacity value does not lead to the typical performance characteristics of the intersection, such as the entry average delay which is directly linked to its level of service. From another point of view, modern roundabout capacity models are based on the limitation of the flow entering from the single entrance due to the amount of flow circulating in front of the entrance itself. Modern roundabouts capacity models generally lead also to a performance evaluation. This paper aims to incorporate a modern roundabout capacity model into an old rotary capacity method to obtain from the latter the single input capacity and ultimately achieve the related performance indicators. Put simply; the main objective is to calculate the average delay of each single roundabout entrance to apply the most common Highway Capacity Manual, or HCM, criteria. The paper is organized as follows: firstly, the rotary and roundabout capacity models are sketched, and it has made a brief introduction to the model combination technique with some practical instances. The successive section is deserved to summarize the TRRL old rotary capacity model and the most recent HCM-7th modern roundabout capacity model. Then, the two models are combined through an iteration-based algorithm, especially set-up and linked to the concept of roundabout total capacity, i.e., the value reached due to a traffic flow pattern leading to the simultaneous congestion of all roundabout entrances. The solution is the average delay for each entrance of the rotary, by which is estimated its respective level of service. In view of further experimental applications, at this research stage, a collection of existing rotary intersections operating with the priority-to-circle rule has already started, both in the US and in Italy. The rotaries have been selected by direct inspection of aerial photos through a map viewer, namely Google Earth. Each instance has been recorded by location, general urban or rural, and its main geometrical patterns. Finally, conclusion remarks are drawn, and a discussion on some further research developments has opened.Keywords: mixed methods, old rotary and modern roundabout capacity models, total capacity algorithm, level of service estimation
Procedia PDF Downloads 818206 Network Analysis and Sex Prediction based on a full Human Brain Connectome
Authors: Oleg Vlasovets, Fabian Schaipp, Christian L. Mueller
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we conduct a network analysis and predict the sex of 1000 participants based on ”connectome” - pairwise Pearson’s correlation across 436 brain parcels. We solve the non-smooth convex optimization problem, known under the name of Graphical Lasso, where the solution includes a low-rank component. With this solution and machine learning model for a sex prediction, we explain the brain parcels-sex connectivity patterns.Keywords: network analysis, neuroscience, machine learning, optimization
Procedia PDF Downloads 1468205 Efficient Positioning of Data Aggregation Point for Wireless Sensor Network
Authors: Sifat Rahman Ahona, Rifat Tasnim, Naima Hassan
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Data aggregation is a helpful technique for reducing the data communication overhead in wireless sensor network. One of the important tasks of data aggregation is positioning of the aggregator points. There are a lot of works done on data aggregation. But, efficient positioning of the aggregators points is not focused so much. In this paper, authors are focusing on the positioning or the placement of the aggregation points in wireless sensor network. Authors proposed an algorithm to select the aggregators positions for a scenario where aggregator nodes are more powerful than sensor nodes.Keywords: aggregation point, data communication, data aggregation, wireless sensor network
Procedia PDF Downloads 1558204 Green Synthesis of Nanosilver-Loaded Hydrogel Nanocomposites for Antibacterial Application
Authors: D. Berdous, H. Ferfera-Harrar
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Superabsorbent polymers (SAPs) or hydrogels with three-dimensional hydrophilic network structure are high-performance water absorbent and retention materials. The in situ synthesis of metal nanoparticles within polymeric network as antibacterial agents for bio-applications is an approach that takes advantage of the existing free-space into networks, which not only acts as a template for nucleation of nanoparticles, but also provides long term stability and reduces their toxicity by delaying their oxidation and release. In this work, SAP/nanosilver nanocomposites were successfully developed by a unique green process at room temperature, which involves in situ formation of silver nanoparticles (AgNPs) within hydrogels as a template. The aim of this study is to investigate whether these AgNPs-loaded hydrogels are potential candidates for antimicrobial applications. Firstly, the superabsorbents were prepared through radical copolymerization via grafting and crosslinking of acrylamide (AAm) onto chitosan backbone (Cs) using potassium persulfate as initiator and N,N’-methylenebisacrylamide as the crosslinker. Then, they were hydrolyzed to achieve superabsorbents with ampholytic properties and uppermost swelling capacity. Lastly, the AgNPs were biosynthesized and entrapped into hydrogels through a simple, eco-friendly and cost-effective method using aqueous silver nitrate as a silver precursor and curcuma longa tuber-powder extracts as both reducing and stabilizing agent. The formed superabsorbents nanocomposites (Cs-g-PAAm)/AgNPs were characterized by X-ray Diffraction (XRD), UV-visible Spectroscopy, Attenuated Total reflectance Fourier Transform Infrared Spectroscopy (ATR-FTIR), Inductively Coupled Plasma (ICP), and Thermogravimetric Analysis (TGA). Microscopic surface structure analyzed by Transmission Electron Microscopy (TEM) has showed spherical shapes of AgNPs with size in the range of 3-15 nm. The extent of nanosilver loading was decreased by increasing Cs content into network. The silver-loaded hydrogel was thermally more stable than the unloaded dry hydrogel counterpart. The swelling equilibrium degree (Q) and centrifuge retention capacity (CRC) in deionized water were affected by both contents of Cs and the entrapped AgNPs. The nanosilver-embedded hydrogels exhibited antibacterial activity against Escherichia coli and Staphylococcus aureus bacteria. These comprehensive results suggest that the elaborated AgNPs-loaded nanomaterials could be used to produce valuable wound dressing.Keywords: antibacterial activity, nanocomposites, silver nanoparticles, superabsorbent Hydrogel
Procedia PDF Downloads 2468203 A Linearly Scalable Family of Swapped Networks
Authors: Richard Draper
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A supercomputer can be constructed from identical building blocks which are small parallel processors connected by a network referred to as the local network. The routers have unused ports which are used to interconnect the building blocks. These connections are referred to as the global network. The address space has a global and a local component (g, l). The conventional way to connect the building blocks is to connect (g, l) to (g’,l). If there are K blocks, this requires K global ports in each router. If a block is of size M, the result is a machine with KM routers having diameter two. To increase the size of the machine to 2K blocks, each router connects to only half of the other blocks. The result is a larger machine but also one with greater diameter. This is a crude description of how the network of the CRAY XC® is designed. In this paper, a family of interconnection networks using routers with K global and M local ports is defined. Coordinates are (c,d, p) and the global connections are (c,d,p)↔(c’,p,d) which swaps p and d. The network is denoted D3(K,M) and is called a Swapped Dragonfly. D3(K,M) has KM2 routers and has diameter three, regardless of the size of K. To produce a network of size KM2 conventionally, diameter would be an increasing function of K. The family of Swapped Dragonflies has other desirable properties: 1) D3(K,M) scales linearly in K and quadratically in M. 2) If L < K, D3(K,M) contains many copies of D3(L,M). 3) If L < M, D3(K,M) contains many copies of D3(K,L). 4) D3(K,M) can perform an all-to-all exchange in KM2+KM time which is only slightly more than the time to do a one-to-all. This paper makes several contributions. It is the first time that a swap has been used to define a linearly scalable family of networks. Structural properties of this new family of networks are thoroughly examined. A synchronizing packet header is introduced. It specifies the path to be followed and it makes it possible to define highly parallel communication algorithm on the network. Among these is an all-to-all exchange in time KM2+KM. To demonstrate the effectiveness of the swap properties of the network of the CRAY XC® and D3(K,16) are compared.Keywords: all-to-all exchange, CRAY XC®, Dragonfly, interconnection network, packet switching, swapped network, topology
Procedia PDF Downloads 1208202 Max-Entropy Feed-Forward Clustering Neural Network
Authors: Xiaohan Bookman, Xiaoyan Zhu
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The outputs of non-linear feed-forward neural network are positive, which could be treated as probability when they are normalized to one. If we take Entropy-Based Principle into consideration, the outputs for each sample could be represented as the distribution of this sample for different clusters. Entropy-Based Principle is the principle with which we could estimate the unknown distribution under some limited conditions. As this paper defines two processes in Feed-Forward Neural Network, our limited condition is the abstracted features of samples which are worked out in the abstraction process. And the final outputs are the probability distribution for different clusters in the clustering process. As Entropy-Based Principle is considered into the feed-forward neural network, a clustering method is born. We have conducted some experiments on six open UCI data sets, comparing with a few baselines and applied purity as the measurement. The results illustrate that our method outperforms all the other baselines that are most popular clustering methods.Keywords: feed-forward neural network, clustering, max-entropy principle, probabilistic models
Procedia PDF Downloads 4338201 An Assessment of Bathymetric Changes in the Lower Usuma Reservoir, Abuja, Nigera
Authors: Rayleigh Dada Abu, Halilu Ahmad Shaba
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Siltation is a serious problem that affects public water supply infrastructures such as dams and reservoirs. It is a major problem which threatens the performance and sustainability of dams and reservoirs. It reduces the dam capacity for flood control, potable water supply, changes water stage, reduces water quality and recreational benefits. The focus of this study is the Lower Usuma reservoir. At completion the reservoir had a gross storage capacity of 100 × 106 m3 (100 million cubic metres), a maximum operational level of 587.440 m a.s.l., with a maximum depth of 49 m and a catchment area of 241 km2 at dam site with a daily designed production capacity of 10,000 cubic metres per hour. The reservoir is 1,300 m long and feeds the treatment plant mainly by gravity. The reservoir became operational in 1986 and no survey has been conducted to determine its current storage capacity and rate of siltation. Hydrographic survey of the reservoir by integrated acoustic echo-sounding technique was conducted in November 2012 to determine the level and rate of siltation. The result obtained shows that the reservoir has lost 12.0 meters depth to siltation in 26 years of its operation; indicating 24.5% loss in installed storage capacity. The present bathymetric survey provides baseline information for future work on siltation depth and annual rates of storage capacity loss for the Lower Usuma reservoir.Keywords: sedimentation, lower Usuma reservoir, acoustic echo sounder, bathymetric survey
Procedia PDF Downloads 5148200 Analysis of Interleaving Scheme for Narrowband VoIP System under Pervasive Environment
Authors: Monica Sharma, Harjit Pal Singh, Jasbinder Singh, Manju Bala
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In Voice over Internet Protocol (VoIP) system, the speech signal is degraded when passed through the network layers. The speech signal is processed through the best effort policy based IP network, which leads to the network degradations including delay, packet loss and jitter. The packet loss is the major issue of the degradation in the VoIP signal quality; even a single lost packet may generate audible distortion in the decoded speech signal. In addition to these network degradations, the quality of the speech signal is also affected by the environmental noises and coder distortions. The signal quality of the VoIP system is improved through the interleaving technique. The performance of the system is evaluated for various types of noises at different network conditions. The performance of the enhanced VoIP signal is evaluated using perceptual evaluation of speech quality (PESQ) measurement for narrow band signal.Keywords: VoIP, interleaving, packet loss, packet size, background noise
Procedia PDF Downloads 4788199 Performance Evaluation of Vertical Handover on Silom Line BTS
Authors: Silumpa Suboonsan, Suwat Pattaramalai
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In this paper, the performance of internet usage by using Vertical Handover (VHO) between cellular network and wireless local area network (WLAN) on Silom line Bangkok Mass Transit System (BTS) is evaluated. In the evaluation model, there is the WLAN on every BTS station and there are cellular base stations along the BTS path. The maximum data rates for cellular network are 7.2, 14.4, 42, and 100Mbps and for WLAN are 54, 150, and 300Mbps. The simulation are based on users using internet, watching VDOs and browsing web pages, on the BTS train from first station to the last station (full time usage) and on the BTS train for traveling some number of stations (random time). The results shows that VHO system has throughput a lot more than using only cellular network when the data rate of WLAN is more than one of cellular network. Lastly, the number of watching HD VDO and Full HD VDO is higher on VHO system on both regular time and rush hour of BTS travelling.Keywords: vertical handover, WLAN, cellular, silom line BTS
Procedia PDF Downloads 4768198 Comparison of Reserve Strength Ratio and Capacity Curve Parameters of Offshore Platforms with Distinct Bracing Arrangements
Authors: Aran Dezhban, Hooshang Dolatshahi Pirooz
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The phenomenon of corrosion, especially in the Persian Gulf region, is the main cause of the deterioration of offshore platforms, due to the high corrosion of its water. This phenomenon occurs mostly in the area of water spraying, threatening the members of the first floor of the jacket, legs, and piles in this area. In the current study, the effect of bracing arrangement on the Capacity Curve and Reserve Strength Ratio of Fixed-Type Offshore Platforms is investigated. In order to continue the operation of the platform, two modes of robust and damaged structures are considered, while checking the adequacy of the platform capacity based on the allowable values of API RP-2SIM regulations. The platform in question is located in the Persian Gulf, which is modeled on the OpenSEES software. In this research, the Nonlinear Pushover Analysis has been used. After validation, the Capacity Curve of the studied platforms is obtained and then their Reserve Strength Ratio is calculated. Results are compared with the criteria in the API-2SIM regulations.Keywords: fixed-type jacket structure, structural integrity management, nonlinear pushover analysis, robust and damaged structure, reserve strength ration, capacity curve
Procedia PDF Downloads 1118197 Capacity Building of Extension Agents for Sustainable Dissemination of Agricultural Information and Technologies in Developing Countries
Authors: Michael T. Ajayi, Oluwakemi E. Fapojuwo
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Farmers are in need of regular and relevant information relating to new technologies. Production of extension materials has been found to be useful in facilitating the process. Extension materials help to provide information to reach large numbers of farmers quickly and economically. However, as good as extension materials are, previous materials produced are not used by farmers. The reasons for this include lack of involvement of farmers in the production of the extension materials, most of the extension materials are not relevant to the farmers’ environments, the agricultural extension agents lack capacity to prepare the materials, and many extension agents lack commitment. These problems led to this innovative capacity building of extension agents. This innovative approach involves five stages. The first stage is the diagnostic survey of farmers’ environment to collect useful information. The second stage is the development and production of draft extension materials. The third stage is the field testing and evaluation of draft materials by the same farmers that were involved at the diagnostic stage. The fourth stage is the revision of the draft extension materials by incorporating suggestions from farmers. The fifth stage is the action plans. This process improves the capacity of agricultural extension agents in the preparation of extension materials and also promotes engagement of farmers and beneficiaries in the process. The process also makes farmers assume some level of ownership of the exercise and the extension materials.Keywords: capacity building, extension agents, dissemination, information/technologies
Procedia PDF Downloads 3598196 Survey on Energy Efficient Routing Protocols in Mobile Ad-Hoc Networks
Authors: Swapnil Singh, Sanjoy Das
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Mobile Ad-Hoc Network (MANET) is infrastructure less networks dynamically formed by autonomous system of mobile nodes that are connected via wireless links. Mobile nodes communicate with each other on the fly. In this network each node also acts as a router. The battery power and the bandwidth are very scarce resources in this network. The network lifetime and connectivity of nodes depends on battery power. Therefore, energy is a valuable constraint which should be efficiently used. In this paper, we survey various energy efficient routing protocol. The energy efficient routing protocols are classified on the basis of approaches they use to minimize the energy consumption. The purpose of this paper is to facilitate the research work and combine the existing solution and to develop a more energy efficient routing mechanism.Keywords: delaunay triangulation, deployment, energy efficiency, MANET
Procedia PDF Downloads 6148195 Peak Frequencies in the Collective Membrane Potential of a Hindmarsh-Rose Small-World Neural Network
Authors: Sun Zhe, Ruggero Micheletto
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As discussed extensively in many studies, noise in neural networks have an important role in the functioning and time evolution of the system. The mechanism by which noise induce stochastic resonance enhancing and influencing certain operations is not clarified nor is the mechanism of information storage and coding. With the present research we want to study the role of noise, especially focusing on the frequency peaks in a three variable Hindmarsh−Rose Small−World network. We investigated the behaviour of the network to external noises. We demonstrate that a variation of signal to noise ratio of about 10 dB induces an increase in membrane potential signal of about 15%, averaged over the whole network. We also considered the integral of the whole membrane potential as a paradigm of internal noise, the one generated by the brain network. We showed that this internal noise is attenuated with the size of the network or with the number of random connections. By means of Fourier analysis we found that it has distinct peaks of frequencies, moreover, we showed that increasing the size of the network introducing more neurons, reduced the maximum frequencies generated by the network, whereas the increase in the number of random connections (determined by the small-world probability p) led to a trend toward higher frequencies. This study may give clues on how networks utilize noise to alter the collective behaviour of the system in their operations.Keywords: neural networks, stochastic processes, small-world networks, discrete Fourier analysis
Procedia PDF Downloads 2908194 Dye Retention by a Photochemicaly Crosslinked Poly(2-Hydroxy-Ethyl-Meth-Acrylic) Network in Water
Authors: Yasmina Houda Bendahma, Tewfik Bouchaour, Meriem Merad, Ulrich Maschke
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The purpose of this work is to study retention of dye dissolved in distilled water, by an hydrophilic acrylic polymer network. The polymer network considered is Poly (2-hydroxyethyl methacrylate) (PHEMA): it is prepared by photo-polymerization under UV irradiation in the presence of a monomer (HEMA), initiator and an agent cross-linker. PHEMA polymer network obtained can be used in the retention of dye molecules present in the wastewater. The results obtained are interesting in the study of the kinetics of swelling and de-swelling of cross linked polymer networks PHEMA in colored aqueous solutions. The dyes used for retention by the PHEMA networks are eosin Y and Malachite Green, dissolved in distilled water. Theoretical conformational study by a simplified molecular model of system cross linked PHEMA / dye (eosin Y and Malachite Green), is used to simulate the retention phenomenon (or Docking) dye molecules in cavities in nano-domains included in the PHEMA polymer network.Keywords: dye retention, molecular modeling, photochemically crosslinked polymer network, swelling deswelling, PHEMA, HEMA
Procedia PDF Downloads 3648193 A Comparison between Artificial Neural Network Prediction Models for Coronal Hole Related High Speed Streams
Authors: Rehab Abdulmajed, Amr Hamada, Ahmed Elsaid, Hisashi Hayakawa, Ayman Mahrous
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Solar emissions have a high impact on the Earth’s magnetic field, and the prediction of solar events is of high interest. Various techniques have been used in the prediction of solar wind using mathematical models, MHD models, and neural network (NN) models. This study investigates the coronal hole (CH) derived high-speed streams (HSSs) and their correlation to the CH area and create a neural network model to predict the HSSs. Two different algorithms were used to compare different models to find a model that best simulates the HSSs. A dataset of CH synoptic maps through Carrington rotations 1601 to 2185 along with Omni-data set solar wind speed averaged over the Carrington rotations is used, which covers Solar cycles (sc) 21, 22, 23, and most of 24.Keywords: artificial neural network, coronal hole area, feed-forward neural network models, solar high speed streams
Procedia PDF Downloads 868192 Keyword Network Analysis on the Research Trends of Life-Long Education for People with Disabilities in Korea
Authors: Jakyoung Kim, Sungwook Jang
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The purpose of this study is to examine the research trends of life-long education for people with disabilities using a keyword network analysis. For this purpose, 151 papers were selected from 594 papers retrieved using keywords such as 'people with disabilities' and 'life-long education' in the Korean Education and Research Information Service. The Keyword network analysis was constructed by extracting and coding the keyword used in the title of the selected papers. The frequency of the extracted keywords, the centrality of degree, and betweenness was analyzed by the keyword network. The results of the keyword network analysis are as follows. First, the main keywords that appeared frequently in the study of life-long education for people with disabilities were 'people with disabilities', 'life-long education', 'developmental disabilities', 'current situations', 'development'. The research trends of life-long education for people with disabilities are focused on the current status of the life-long education and the program development. Second, the keyword network analysis and visualization showed that the keywords with high frequency of occurrences also generally have high degree centrality and betweenness centrality. In terms of the keyword network diagram, it was confirmed that research trends of life-long education for people with disabilities are centered on six prominent keywords. Based on these results, it was discussed that life-long education for people with disabilities in the future needs to expand the subjects and the supporting areas of the life-long education, and the research needs to be further expanded into more detailed and specific areas.Keywords: life-long education, people with disabilities, research trends, keyword network analysis
Procedia PDF Downloads 3378191 Study of Current the Rice Straw Potential for a Small Power Plant Capacity in the Central Region of Thailand
Authors: Sansanee Sansiribhan, Orrawan Rewthong, Anusorn Rattanathanaophat, Sarun Saensiriphan
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The objective of this work was to study potential of rice straw for power plant in the central region of Thailand. Provincial power plant capacity was studied. The results showed that provinces central region had potential for small power plants with a capacity of over 10 MW in 13 provinces, 1-10 MW in 6 provinces and less than 1 MW in 3 provinces.Keywords: rice straw, power plant, central region, Thailand
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