Search results for: heterogeneous networks
3387 Performing Diagnosis in Building with Partially Valid Heterogeneous Tests
Authors: Houda Najeh, Mahendra Pratap Singh, Stéphane Ploix, Antoine Caucheteux, Karim Chabir, Mohamed Naceur Abdelkrim
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Building system is highly vulnerable to different kinds of faults and human misbehaviors. Energy efficiency and user comfort are directly targeted due to abnormalities in building operation. The available fault diagnosis tools and methodologies particularly rely on rules or pure model-based approaches. It is assumed that model or rule-based test could be applied to any situation without taking into account actual testing contexts. Contextual tests with validity domain could reduce a lot of the design of detection tests. The main objective of this paper is to consider fault validity when validate the test model considering the non-modeled events such as occupancy, weather conditions, door and window openings and the integration of the knowledge of the expert on the state of the system. The concept of heterogeneous tests is combined with test validity to generate fault diagnoses. A combination of rules, range and model-based tests known as heterogeneous tests are proposed to reduce the modeling complexity. Calculation of logical diagnoses coming from artificial intelligence provides a global explanation consistent with the test result. An application example shows the efficiency of the proposed technique: an office setting at Grenoble Institute of Technology.Keywords: heterogeneous tests, validity, building system, sensor grids, sensor fault, diagnosis, fault detection and isolation
Procedia PDF Downloads 2953386 A Secure Routing Algorithm for Underwater Wireless Sensor Networks
Authors: Seyed Mahdi Jameii
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Underwater wireless sensor networks have been attracting the interest of many researchers lately, and the past three decades have beheld the rapid progress of underwater acoustic communication. One of the major problems in underwater wireless sensor networks is how to transfer data from the moving node to the base stations and choose the optimized route for data transmission. Secure routing in underwater wireless sensor network (UWCNs) is necessary for packet delivery. Some routing protocols are proposed for underwater wireless sensor networks. However, a few researches have been done on secure routing in underwater sensor networks. In this article, a secure routing protocol is provided to resist against wormhole and sybil attacks. The results indicated acceptable performance in terms of increasing the packet delivery ratio with regards to the attacks, increasing network lifetime by creating balance in the network energy consumption, high detection rates against the attacks, and low-end to end delay.Keywords: attacks, routing, security, underwater wireless sensor networks
Procedia PDF Downloads 4193385 Detection of Atrial Fibrillation Using Wearables via Attentional Two-Stream Heterogeneous Networks
Authors: Huawei Bai, Jianguo Yao, Fellow, IEEE
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Atrial fibrillation (AF) is the most common form of heart arrhythmia and is closely associated with mortality and morbidity in heart failure, stroke, and coronary artery disease. The development of single spot optical sensors enables widespread photoplethysmography (PPG) screening, especially for AF, since it represents a more convenient and noninvasive approach. To our knowledge, most existing studies based on public and unbalanced datasets can barely handle the multiple noises sources in the real world and, also, lack interpretability. In this paper, we construct a large- scale PPG dataset using measurements collected from PPG wrist- watch devices worn by volunteers and propose an attention-based two-stream heterogeneous neural network (TSHNN). The first stream is a hybrid neural network consisting of a three-layer one-dimensional convolutional neural network (1D-CNN) and two-layer attention- based bidirectional long short-term memory (Bi-LSTM) network to learn representations from temporally sampled signals. The second stream extracts latent representations from the PPG time-frequency spectrogram using a five-layer CNN. The outputs from both streams are fed into a fusion layer for the outcome. Visualization of the attention weights learned demonstrates the effectiveness of the attention mechanism against noise. The experimental results show that the TSHNN outperforms all the competitive baseline approaches and with 98.09% accuracy, achieves state-of-the-art performance.Keywords: PPG wearables, atrial fibrillation, feature fusion, attention mechanism, hyber network
Procedia PDF Downloads 1223384 Ontology-Based Approach for Temporal Semantic Modeling of Social Networks
Authors: Souâad Boudebza, Omar Nouali, Faiçal Azouaou
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Social networks have recently gained a growing interest on the web. Traditional formalisms for representing social networks are static and suffer from the lack of semantics. In this paper, we will show how semantic web technologies can be used to model social data. The SemTemp ontology aligns and extends existing ontologies such as FOAF, SIOC, SKOS and OWL-Time to provide a temporal and semantically rich description of social data. We also present a modeling scenario to illustrate how our ontology can be used to model social networks.Keywords: ontology, semantic web, social network, temporal modeling
Procedia PDF Downloads 3893383 Routing Metrics and Protocols for Wireless Mesh Networks
Authors: Samira Kalantary, Zohre Saatzade
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Wireless Mesh Networks (WMNs) are low-cost access networks built on cooperative routing over a backbone composed of stationary wireless routers. WMNs must deal with the highly unstable wireless medium. Thus, routing metrics and protocols are evolving by designing algorithms that consider link quality to choose the best routes. In this work, we analyse the state of the art in WMN metrics and propose taxonomy for WMN routing protocols. Performance measurements of a wireless mesh network deployed using various routing metrics are presented and corroborate our analysis.Keywords: wireless mesh networks, routing protocols, routing metrics, bioinformatics
Procedia PDF Downloads 4573382 A Quinary Coding and Matrix Structure Based Channel Hopping Algorithm for Blind Rendezvous in Cognitive Radio Networks
Authors: Qinglin Liu, Zhiyong Lin, Zongheng Wei, Jianfeng Wen, Congming Yi, Hai Liu
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The multi-channel blind rendezvous problem in distributed cognitive radio networks (DCRNs) refers to how users in the network can hop to the same channel at the same time slot without any prior knowledge (i.e., each user is unaware of other users' information). The channel hopping (CH) technique is a typical solution to this blind rendezvous problem. In this paper, we propose a quinary coding and matrix structure-based CH algorithm called QCMS-CH. The QCMS-CH algorithm can guarantee the rendezvous of users using only one cognitive radio in the scenario of the asynchronous clock (i.e., arbitrary time drift between the users), heterogeneous channels (i.e., the available channel sets of users are distinct), and symmetric role (i.e., all users play a same role). The QCMS-CH algorithm first represents a randomly selected channel (denoted by R) as a fixed-length quaternary number. Then it encodes the quaternary number into a quinary bootstrapping sequence according to a carefully designed quaternary-quinary coding table with the prefix "R00". Finally, it builds a CH matrix column by column according to the bootstrapping sequence and six different types of elaborately generated subsequences. The user can access the CH matrix row by row and accordingly perform its channel, hoping to attempt rendezvous with other users. We prove the correctness of QCMS-CH and derive an upper bound on its Maximum Time-to-Rendezvous (MTTR). Simulation results show that the QCMS-CH algorithm outperforms the state-of-the-art in terms of the MTTR and the Expected Time-to-Rendezvous (ETTR).Keywords: channel hopping, blind rendezvous, cognitive radio networks, quaternary-quinary coding
Procedia PDF Downloads 933381 Ecological Networks: From Structural Analysis to Synchronization
Authors: N. F. F. Ebecken, G. C. Pereira
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Ecological systems are exposed and are influenced by various natural and anthropogenic disturbances. They produce various effects and states seeking response symmetry to a state of global phase coherence or stability and balance of their food webs. This research project addresses the development of a computational methodology for modeling plankton food webs. The use of algorithms to establish connections, the generation of representative fuzzy multigraphs and application of technical analysis of complex networks provide a set of tools for defining, analyzing and evaluating community structure of coastal aquatic ecosystems, beyond the estimate of possible external impacts to the networks. Thus, this study aims to develop computational systems and data models to assess how these ecological networks are structurally and functionally organized, to analyze the types and degree of compartmentalization and synchronization between oscillatory and interconnected elements network and the influence of disturbances on the overall pattern of rhythmicity of the system.Keywords: ecological networks, plankton food webs, fuzzy multigraphs, dynamic of networks
Procedia PDF Downloads 3013380 Neighbour Cell List Reduction in Multi-Tier Heterogeneous Networks
Authors: Mohanad Alhabo, Naveed Nawaz
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The ongoing call or data session must be maintained to ensure a good quality of service. This can be accomplished by performing the handover procedure while the user is on the move. However, the dense deployment of small cells in 5G networks is a challenging issue due to the extensive number of handovers. In this paper, a neighbour cell list method is proposed to reduce the number of target small cells and hence minimizing the number of handovers. The neighbour cell list is built by omitting cells that could cause an unnecessary handover and handover failure because of short time of stay of the user in these cells. A multi-attribute decision making technique, simple additive weighting, is then applied to the optimized neighbour cell list. Multi-tier small cells network is considered in this work. The performance of the proposed method is analysed and compared with that of the existing methods. Results disclose that our method has decreased the candidate small cell list, unnecessary handovers, handover failure, and short time of stay cells compared to the competitive method.Keywords: handover, HetNets, multi-attribute decision making, small cells
Procedia PDF Downloads 1213379 Heterogeneous Photocatalytic Degradation of Methylene Blue by Montmorillonite/CuxCd1-xs Nanomaterials
Authors: Horiya Boukhatem, Lila Djouadi, Hussein Khalaf, Rufino Manuel Navarro Yerga, Fernando Vaquero Gonzalez
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Heterogeneous photo catalysis is an alternative method for the removal of organic pollutants in water. The photo excitation of a semi-conductor under ultra violet (UV) irradiation entails the production of hydroxyl radicals, one of the most oxidative chemical species. The objective of this study is the synthesis of nano materials based on montmorillonite and CuxCd1-xS with different Cu concentration (0.3 < x < 0.7) and their application in photocatalysis of a cationic dye: methylene blue. The synthesized nano materials and montmorillonite were characterized by fourier transform infrared (FTIR). Test results of photo catalysis of methylene blue under UV-Visible irradiation show that the photoactivity of nano materials montmorillonite/ CuxCd1-xS increase with the increasing of Cu concentration and it is significantly higher compared to that of sodium montmorillonite alone. The application of the kinetic model of Langmuir-Hinshelwood (L-H) to the photocatalytic test results showed that the reaction rate obeys to the first-order kinetic model.Keywords: heterogeneous photo catalysis, methylene blue, montmorillonite, nano material
Procedia PDF Downloads 3413378 Critical Evaluation of Groundwater Monitoring Networks for Machine Learning Applications
Authors: Pedro Martinez-Santos, Víctor Gómez-Escalonilla, Silvia Díaz-Alcaide, Esperanza Montero, Miguel Martín-Loeches
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Groundwater monitoring networks are critical in evaluating the vulnerability of groundwater resources to depletion and contamination, both in space and time. Groundwater monitoring networks typically grow over decades, often in organic fashion, with relatively little overall planning. The groundwater monitoring networks in the Madrid area, Spain, were reviewed for the purpose of identifying gaps and opportunities for improvement. Spatial analysis reveals the presence of various monitoring networks belonging to different institutions, with several hundred observation wells in an area of approximately 4000 km2. This represents several thousand individual data entries, some going back to the early 1970s. Major issues included overlap between the networks, unknown screen depth/vertical distribution for many observation boreholes, uneven time series, uneven monitored species, and potentially suboptimal locations. Results also reveal there is sufficient information to carry out a spatial and temporal analysis of groundwater vulnerability based on machine learning applications. These can contribute to improve the overall planning of monitoring networks’ expansion into the future.Keywords: groundwater monitoring, observation networks, machine learning, madrid
Procedia PDF Downloads 793377 Algorithms for Run-Time Task Mapping in NoC-Based Heterogeneous MPSoCs
Authors: M. K. Benhaoua, A. K. Singh, A. E. Benyamina, P. Boulet
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Mapping parallelized tasks of applications onto these MPSoCs can be done either at design time (static) or at run-time (dynamic). Static mapping strategies find the best placement of tasks at design-time, and hence, these are not suitable for dynamic workload and seem incapable of runtime resource management. The number of tasks or applications executing in MPSoC platform can exceed the available resources, requiring efficient run-time mapping strategies to meet these constraints. This paper describes a new Spiral Dynamic Task Mapping heuristic for mapping applications onto NoC-based Heterogeneous MPSoC. This heuristic is based on packing strategy and routing Algorithm proposed also in this paper. Heuristic try to map the tasks of an application in a clustering region to reduce the communication overhead between the communicating tasks. The heuristic proposed in this paper attempts to map the tasks of an application that are most related to each other in a spiral manner and to find the best possible path load that minimizes the communication overhead. In this context, we have realized a simulation environment for experimental evaluations to map applications with varying number of tasks onto an 8x8 NoC-based Heterogeneous MPSoCs platform, we demonstrate that the new mapping heuristics with the new modified dijkstra routing algorithm proposed are capable of reducing the total execution time and energy consumption of applications when compared to state-of-the-art run-time mapping heuristics reported in the literature.Keywords: multiprocessor system on chip, MPSoC, network on chip, NoC, heterogeneous architectures, run-time mapping heuristics, routing algorithm
Procedia PDF Downloads 4893376 Ensuring Uniform Energy Consumption in Non-Deterministic Wireless Sensor Network to Protract Networks Lifetime
Authors: Vrince Vimal, Madhav J. Nigam
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Wireless sensor networks have enticed much of the spotlight from researchers all around the world, owing to its extensive applicability in agricultural, industrial and military fields. Energy conservation node deployment stratagems play a notable role for active implementation of Wireless Sensor Networks. Clustering is the approach in wireless sensor networks which improves energy efficiency in the network. The clustering algorithm needs to have an optimum size and number of clusters, as clustering, if not implemented properly, cannot effectively increase the life of the network. In this paper, an algorithm has been proposed to address connectivity issues with the aim of ensuring the uniform energy consumption of nodes in every part of the network. The results obtained after simulation showed that the proposed algorithm has an edge over existing algorithms in terms of throughput and networks lifetime.Keywords: Wireless Sensor network (WSN), Random Deployment, Clustering, Isolated Nodes, Networks Lifetime
Procedia PDF Downloads 3373375 Towards Security in Virtualization of SDN
Authors: Wanqing You, Kai Qian, Xi He, Ying Qian
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In this paper, the potential security issues brought by the virtualization of a Software Defined Networks (SDN) would be analyzed. The virtualization of SDN is achieved by FlowVisor (FV). With FV, a physical network is divided into multiple isolated logical networks while the underlying resources are still shared by different slices (isolated logical networks). However, along with the benefits brought by network virtualization, it also presents some issues regarding security. By examining security issues existing in an OpenFlow network, which uses FlowVisor to slice it into multiple virtual networks, we hope we can get some significant results and also can get further discussions among the security of SDN virtualization.Keywords: SDN, network, virtualization, security
Procedia PDF Downloads 4293374 Comparative Analysis of Sigmoidal Feedforward Artificial Neural Networks and Radial Basis Function Networks Approach for Localization in Wireless Sensor Networks
Authors: Ashish Payal, C. S. Rai, B. V. R. Reddy
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With the increasing use and application of Wireless Sensor Networks (WSN), need has arisen to explore them in more effective and efficient manner. An important area which can bring efficiency to WSNs is the localization process, which refers to the estimation of the position of wireless sensor nodes in an ad hoc network setting, in reference to a coordinate system that may be internal or external to the network. In this paper, we have done comparison and analysed Sigmoidal Feedforward Artificial Neural Networks (SFFANNs) and Radial Basis Function (RBF) networks for developing localization framework in WSNs. The presented work utilizes the Received Signal Strength Indicator (RSSI), measured by static node on 100 x 100 m2 grid from three anchor nodes. The comprehensive evaluation of these approaches is done using MATLAB software. The simulation results effectively demonstrate that FFANNs based sensor motes will show better localization accuracy as compared to RBF.Keywords: localization, wireless sensor networks, artificial neural network, radial basis function, multi-layer perceptron, backpropagation, RSSI, GPS
Procedia PDF Downloads 3403373 Leveraging Deep Q Networks in Portfolio Optimization
Authors: Peng Liu
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Deep Q networks (DQNs) represent a significant advancement in reinforcement learning, utilizing neural networks to approximate the optimal Q-value for guiding sequential decision processes. This paper presents a comprehensive introduction to reinforcement learning principles, delves into the mechanics of DQNs, and explores its application in portfolio optimization. By evaluating the performance of DQNs against traditional benchmark portfolios, we demonstrate its potential to enhance investment strategies. Our results underscore the advantages of DQNs in dynamically adjusting asset allocations, offering a robust portfolio management framework.Keywords: deep reinforcement learning, deep Q networks, portfolio optimization, multi-period optimization
Procedia PDF Downloads 353372 Community Structure Detection in Networks Based on Bee Colony
Authors: Bilal Saoud
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In this paper, we propose a new method to find the community structure in networks. Our method is based on bee colony and the maximization of modularity to find the community structure. We use a bee colony algorithm to find the first community structure that has a good value of modularity. To improve the community structure, that was found, we merge communities until we get a community structure that has a high value of modularity. We provide a general framework for implementing our approach. We tested our method on computer-generated and real-world networks with a comparison to very known community detection methods. The obtained results show the effectiveness of our proposition.Keywords: bee colony, networks, modularity, normalized mutual information
Procedia PDF Downloads 4093371 Modeling and Prediction of Zinc Extraction Efficiency from Concentrate by Operating Condition and Using Artificial Neural Networks
Authors: S. Mousavian, D. Ashouri, F. Mousavian, V. Nikkhah Rashidabad, N. Ghazinia
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PH, temperature, and time of extraction of each stage, agitation speed, and delay time between stages effect on efficiency of zinc extraction from concentrate. In this research, efficiency of zinc extraction was predicted as a function of mentioned variable by artificial neural networks (ANN). ANN with different layer was employed and the result show that the networks with 8 neurons in hidden layer has good agreement with experimental data.Keywords: zinc extraction, efficiency, neural networks, operating condition
Procedia PDF Downloads 5473370 Optimization of Biodiesel Production from Palm Oil over Mg-Al Modified K-10 Clay Catalyst
Authors: Muhammad Ayoub, Abrar Inayat, Bhajan Lal, Sintayehu Mekuria Hailegiorgis
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Biodiesel which comes from pure renewable resources provide an alternative fuel option for future because of limited fossil fuel resources as well as environmental concerns. The transesterification of vegetable oils for biodiesel production is a promising process to overcome this future crises of energy. The use of heterogeneous catalysts greatly simplifies the technological process by facilitating the separation of the post-reaction mixture. The purpose of the present work was to examine a heterogeneous catalyst, in particular, Mg-Al modified K-10 clay, to produce methyl esters of palm oil. The prepared catalyst was well characterized by different latest techniques. In this study, the transesterification of palm oil with methanol was studied in a heterogeneous system in the presence of Mg-Al modified K-10 clay as solid base catalyst and then optimized these results with the help of Design of Experiments software. The results showed that methanol is the best alcohol for this reaction condition. The best results was achieved for optimization of biodiesel process. The maximum conversion of triglyceride (88%) was noted after 8 h of reaction at 60 ̊C, with a 6:1 molar ratio of methanol to palm oil and 3 wt % of prepared catalyst.Keywords: palm oil, transestrefication, clay, biodiesel, mesoporous clay, K-10
Procedia PDF Downloads 3973369 Multi-Perspective Learning in a Real Production Plant Using Experiential Learning in Heterogeneous Groups to Develop System Competencies for Production System Improvements
Authors: Marlies Achenbach
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System competencies play a key role to ensure an effective and efficient improvement of production systems. Thus, there can be observed an increasing demand for developing system competencies in industry as well as in engineering education. System competencies consist of the following two main abilities: Evaluating the current state of a production system and developing a target state. The innovative course ‘multi-perspective learning in a real production plant (multi real)’ is developed to create a learning setting that supports the development of these system competencies. Therefore, the setting combines two innovative aspects: First, the Learning takes place in heterogeneous groups formed by students as well as professionals and managers from industry. Second, the learning takes place in a real production plant. This paper presents the innovative didactic concept of ‘multi real’ in detail, which will initially be implemented in October/November 2016 in the industrial engineering, logistics and mechanical master’s program at TU Dortmund University.Keywords: experiential learning, heterogeneous groups, improving production systems, system competencies
Procedia PDF Downloads 4273368 Joint Replenishment and Heterogeneous Vehicle Routing Problem with Cyclical Schedule
Authors: Ming-Jong Yao, Chin-Sum Shui, Chih-Han Wang
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This paper is developed based on a real-world decision scenario that an industrial gas company that applies the Vendor Managed Inventory model and supplies liquid oxygen with a self-operated heterogeneous vehicle fleet to hospitals in nearby cities. We name it as a Joint Replenishment and Heterogeneous Vehicle Routing Problem with Cyclical Schedule and formulate it as a non-linear mixed-integer linear programming problem which simultaneously determines the length of the planning cycle (PC), the length of the replenishment cycle and the dates of replenishment for each customer and the vehicle routes of each day within PC, such that the average daily operation cost within PC, including inventory holding cost, setup cost, transportation cost, and overtime labor cost, is minimized. A solution method based on genetic algorithm, embedded with an encoding and decoding mechanism and local search operators, is then proposed, and the hash function is adopted to avoid repetitive fitness evaluation for identical solutions. Numerical experiments demonstrate that the proposed solution method can effectively solve the problem under different lengths of PC and number of customers. The method is also shown to be effective in determining whether the company should expand the storage capacity of a customer whose demand increases. Sensitivity analysis of the vehicle fleet composition shows that deploying a mixed fleet can reduce the daily operating cost.Keywords: cyclic inventory routing problem, joint replenishment, heterogeneous vehicle, genetic algorithm
Procedia PDF Downloads 883367 A Review on Artificial Neural Networks in Image Processing
Authors: B. Afsharipoor, E. Nazemi
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Artificial neural networks (ANNs) are powerful tool for prediction which can be trained based on a set of examples and thus, it would be useful for nonlinear image processing. The present paper reviews several paper regarding applications of ANN in image processing to shed the light on advantage and disadvantage of ANNs in this field. Different steps in the image processing chain including pre-processing, enhancement, segmentation, object recognition, image understanding and optimization by using ANN are summarized. Furthermore, results on using multi artificial neural networks are presented.Keywords: neural networks, image processing, segmentation, object recognition, image understanding, optimization, MANN
Procedia PDF Downloads 4093366 A Survey on a Critical Infrastructure Monitoring Using Wireless Sensor Networks
Authors: Khelifa Benahmed, Tarek Benahmed
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There are diverse applications of wireless sensor networks (WSNs) in the real world, typically invoking some kind of monitoring, tracking, or controlling activities. In an application, a WSN is deployed over the area of interest to sense and detect the events and collect data through their sensors in a geographical area and transmit the collected data to a Base Station (BS). This paper presents an overview of the research solutions available in the field of environmental monitoring applications, more precisely the problems of critical area monitoring using wireless sensor networks.Keywords: critical infrastructure monitoring, environment monitoring, event region detection, wireless sensor networks
Procedia PDF Downloads 3533365 Effectiveness of Catalysis in Ozonation for the Removal of Herbizide 2,4 Dichlorophenoxyacetic Acid from Contaminated Water
Authors: S. Shanthi
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Catalyzed oxidation processes show extraordinary guarantee for application in numerous wastewater treatment ranges. Advanced oxidation processes are emerging innovation that might be utilized for particular objectives in wastewater treatment. This research work provides a solution for removal a refractory organic compound 2,4-dichlorophenoxyaceticacid a common water pollutant. All studies were done in batch mode in a constantly stirred reactor. Alternative ozonation processes catalysed by transition metals or granular activated carbon have been investigated for degradation of organics. Catalytic ozonation under study are homogeneous catalytic ozonation, which is based on ozone activation by transition metal ions present in aqueous solution, and secondly as heterogeneous catalytic ozonation in the presence of Granular Activated Carbon (GAC). The present studies reveal that heterogeneous catalytic ozonation using GAC favour the ozonation of 2,4-dichlorophenoxyaceticacid by increasing the rate of ozonation and a much higher degradation of substrates were obtained in a given time. Be that it may, Fe2+and Fe3+ ions decreased the rate of degradation of 2,4-dichlorophenoxyaceticacid indicating that it acts as a negative catalyst. In case of heterogeneous catalytic ozonation using GAC catalyst it was found that during the initial 5 minutes of contact solution concentration decreased significantly as the pollutants were adsorbed initially. Thereafter the substrate started getting oxidized and ozonation became a dominates the treatment process. The exhausted GAC was found to be regenerated in situ. The percentage reduction of the substrate was maximum achieved in minimum possible time when GAC catalyst is employed.Keywords: ozonation, homogeneous catalysis, heterogeneous catalysis, granular activated carbon
Procedia PDF Downloads 2503364 Portable and Parallel Accelerated Development Method for Field-Programmable Gate Array (FPGA)-Central Processing Unit (CPU)- Graphics Processing Unit (GPU) Heterogeneous Computing
Authors: Nan Hu, Chao Wang, Xi Li, Xuehai Zhou
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The field-programmable gate array (FPGA) has been widely adopted in the high-performance computing domain. In recent years, the embedded system-on-a-chip (SoC) contains coarse granularity multi-core CPU (central processing unit) and mobile GPU (graphics processing unit) that can be used as general-purpose accelerators. The motivation is that algorithms of various parallel characteristics can be efficiently mapped to the heterogeneous architecture coupled with these three processors. The CPU and GPU offload partial computationally intensive tasks from the FPGA to reduce the resource consumption and lower the overall cost of the system. However, in present common scenarios, the applications always utilize only one type of accelerator because the development approach supporting the collaboration of the heterogeneous processors faces challenges. Therefore, a systematic approach takes advantage of write-once-run-anywhere portability, high execution performance of the modules mapped to various architectures and facilitates the exploration of design space. In this paper, A servant-execution-flow model is proposed for the abstraction of the cooperation of the heterogeneous processors, which supports task partition, communication and synchronization. At its first run, the intermediate language represented by the data flow diagram can generate the executable code of the target processor or can be converted into high-level programming languages. The instantiation parameters efficiently control the relationship between the modules and computational units, including two hierarchical processing units mapping and adjustment of data-level parallelism. An embedded system of a three-dimensional waveform oscilloscope is selected as a case study. The performance of algorithms such as contrast stretching, etc., are analyzed with implementations on various combinations of these processors. The experimental results show that the heterogeneous computing system with less than 35% resources achieves similar performance to the pure FPGA and approximate energy efficiency.Keywords: FPGA-CPU-GPU collaboration, design space exploration, heterogeneous computing, intermediate language, parameterized instantiation
Procedia PDF Downloads 1183363 Equipment Contribution Analysis in Task-Oriented Heterogeneous Combat Network with Conflicting Edges
Authors: Lijian Sun, Yun Zhou, Cheng Zhu, Weiming Zhang
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Modern warfare emphasizes that the combat system-of-systems (CSoS) includes various combat units and powerful information exchange capabilities. Therefore, these units have formed a complex Heterogeneous Combat Network (HCN), where enemy and friendly combat forces engage within this network. To better accomplish an assigned task, equipment contribution analysis aims to identify important nodes within the HCN. However, constraints such as equipment payload often give rise to conflicting edges within the HCN. Hence, this paper focuses on analysing equipment contribution within task-oriented HCN from the perspective of Course of Action (COA). Specifically, this paper defines the HCN with constraints and proposes an approach to compute COA within the HCN. Then, the COA Capability Index (COACI) and COA Capability Change Index (COACCI) are proposed to analyse equipment contribution in the HCN. Finally, the effectiveness of the above method is validated through a case study. This paper provides a quantitative analysis approach for equipment contribution analysis within task-oriented HCN and offers valuable insights for designing more effective combat system-of-systems (CSoS).Keywords: equipment contribution, heterogeneous combat network, conflicting edges, course of action, kill chain
Procedia PDF Downloads 93362 Applications of Artificial Neural Networks in Civil Engineering
Authors: Naci Büyükkaracığan
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Artificial neural networks (ANN) is an electrical model based on the human brain nervous system and working principle. Artificial neural networks have been the subject of an active field of research that has matured greatly over the past 55 years. ANN now is used in many fields. But, it has been viewed that artificial neural networks give better results in particular optimization and control systems. There are requirements of optimization and control system in many of the area forming the subject of civil engineering applications. In this study, the first artificial intelligence systems are widely used in the solution of civil engineering systems were examined with the basic principles and technical aspects. Finally, the literature reviews for applications in the field of civil engineering were conducted and also artificial intelligence techniques were informed about the study and its results.Keywords: artificial neural networks, civil engineering, Fuzzy logic, statistics
Procedia PDF Downloads 4153361 3D Interpenetrated Network Based on 1,3-Benzenedicarboxylate and 1,2-Bis(4-Pyridyl) Ethane
Authors: Laura Bravo-García, Gotzone Barandika, Begoña Bazán, M. Karmele Urtiaga, Luis M. Lezama, María I. Arriortua
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Solid coordination networks (SCNs) are materials consisting of metal ions or clusters that are linked by polyfunctional organic ligands and can be designed to form tridimensional frameworks. Their structural features, as for example high surface areas, thermal stability, and in other cases large cavities, have opened a wide range of applications in fields like drug delivery, host-guest chemistry, biomedical imaging, chemical sensing, heterogeneous catalysis and others referred to greenhouse gases storage or even separation. In this sense, the use of polycarboxylate anions and dipyridyl ligands is an effective strategy to produce extended structures with the needed characteristics for these applications. In this context, a novel compound, [Cu4(m-BDC)4(bpa)2DMF]•DMF has been obtained by microwave synthesis, where m-BDC is 1,3-benzenedicarboxylate and bpa 1,2-bis(4-pyridyl)ethane. The crystal structure can be described as a three dimensional framework formed by two equal, interpenetrated networks. Each network consists of two different CuII dimers. Dimer 1 have two coppers with a square pyramidal coordination, and dimer 2 have one with a square pyramidal coordination and other with octahedral one, the last dimer is unique in literature. Therefore, the combination of both type of dimers is unprecedented. Thus, benzenedicarboxylate ligands form sinusoidal chains between the same type of dimers, and also connect both chains forming these layers in the (100) plane. These layers are connected along the [100] direction through the bpa ligand, giving rise to a 3D network with 10 Å2 voids in average. However, the fact that there are two interpenetrated networks results in a significant reduction of the available volume. Structural analysis was carried out by means of single crystal X-ray diffraction and IR spectroscopy. Thermal and magnetic properties have been measured by means of thermogravimetry (TG), X-ray thermodiffractometry (TDX), and electron paramagnetic resonance (EPR). Additionally, CO2 and CH4 high pressure adsorption measurements have been carried out for this compound.Keywords: gas adsorption, interpenetrated networks, magnetic measurements, solid coordination network (SCN), thermal stability
Procedia PDF Downloads 3253360 A Methodology for Sustainable Interoperability within Collaborative Networks
Authors: Aicha Koulou, Norelislam El Hami, Nabil Hmina
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This paper aims at presenting basic concepts and principles in order to develop a methodology to set up sustainable interoperability within collaborative networks. Definitions and clarifications related to the concept of interoperability and sustainability are given. Interoperability levels and cycle that are components supporting the methodology are presented; a structured approach and related phases are proposed.Keywords: Interoperability, sustainability, collaborative networks, sustainable Interoperability
Procedia PDF Downloads 1493359 Foundation Settlement Determination: A Simplified Approach
Authors: Adewoyin O. Olusegun, Emmanuel O. Joshua, Marvel L. Akinyemi
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The heterogeneous nature of the subsurface requires the use of factual information to deal with rather than assumptions or generalized equations. Therefore, there is need to determine the actual rate of settlement possible in the soil before structures are built on it. This information will help in determining the type of foundation design and the kind of reinforcement that will be necessary in constructions. This paper presents a simplified and a faster approach for determining foundation settlement in any type of soil using real field data acquired from seismic refraction techniques and cone penetration tests. This approach was also able to determine the depth of settlement of each strata of soil. The results obtained revealed the different settlement time and depth of settlement possible.Keywords: heterogeneous, settlement, foundation, seismic, technique
Procedia PDF Downloads 4453358 Prediction of Vapor Liquid Equilibrium for Dilute Solutions of Components in Ionic Liquid by Neural Networks
Authors: S. Mousavian, A. Abedianpour, A. Khanmohammadi, S. Hematian, Gh. Eidi Veisi
Abstract:
Ionic liquids are finding a wide range of applications from reaction media to separations and materials processing. In these applications, Vapor–Liquid equilibrium (VLE) is the most important one. VLE for six systems at 353 K and activity coefficients at infinite dilution 〖(γ〗_i^∞) for various solutes (alkanes, alkenes, cycloalkanes, cycloalkenes, aromatics, alcohols, ketones, esters, ethers, and water) in the ionic liquids (1-ethyl-3-methylimidazolium bis (trifluoromethylsulfonyl)imide [EMIM][BTI], 1-hexyl-3-methyl imidazolium bis (trifluoromethylsulfonyl) imide [HMIM][BTI], 1-octyl-3-methylimidazolium bis(trifluoromethylsulfonyl) imide [OMIM][BTI], and 1-butyl-1-methylpyrrolidinium bis (trifluoromethylsulfonyl) imide [BMPYR][BTI]) have been used to train neural networks in the temperature range from (303 to 333) K. Densities of the ionic liquids, Hildebrant constant of substances, and temperature were selected as input of neural networks. The networks with different hidden layers were examined. Networks with seven neurons in one hidden layer have minimum error and good agreement with experimental data.Keywords: ionic liquid, neural networks, VLE, dilute solution
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