We propose a new automatic procedure to generate hybrid meshes to simulate turbulent flows for wind farm design and management. In particular, numerical modeling of wind farms involves a RANS simulation of the Atmosph...
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We propose a new automatic procedure to generate hybrid meshes to simulate turbulent flows for wind farm design and management. In particular, numerical modeling of wind farms involves a RANS simulation of the Atmospheric Boundary Layer (ABL) flow and modeling the turbines using the actuator disc theory. Therefore, the generated meshes have to fulfill several geometrical requirements to answer to the different modeling features. They must: capture the topography features that can influence the wind flow; have a boundary layer close to the terrain to resolve the ABL; be conformally adapted to the disc (turbine) to simulate the turbine effects on the wind flow; be adapted around the disc to capture the wake effect; and present a smooth mesh size transition around the disc to conform the mesh size of the ABL mesh, in which the turbines are immersed. We highlight that the mesh generation procedure is fully automatic once given the mesh size, a topography description, the wind inflow direction, a list of turbine insertion points, and the turbine models. To illustrate the applicability of the proposed procedure, we present two wind farm cases: an offshore wind farm mesh where we illustrate the computed wind deficit, and an onshore farm assimilating real topography data.
While extensively explored in text-based tasks, Named Entity Recognition (NER) remains largely neglected in spoken language understanding. Existing resources are limited to a single, English-only dataset. This paper a...
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The previous approaches have failed to effectually score the language proficiency of a non-native speakers especially in case of non-English languages which are complex and a slight change of pronunciation can alter t...
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The Bit coin currency is steadily growing in popularity as an alternative to physical currencies. This paper presents an approach for utilizing the Bit coin system for creating permanent messages that are located on c...
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The Bit coin currency is steadily growing in popularity as an alternative to physical currencies. This paper presents an approach for utilizing the Bit coin system for creating permanent messages that are located on computers worldwide. By manipulating the amount field of Bit coin transactions, messages can be embedded into the Bit coin block chain. This approach was implemented by extending the Bit coin-Qt v0.7.2 application and the source code is freely available.
In this paper we utilize Bayesian modeling and inference to learn a softmax classification model which performs Supervised Classification and Active Learning. For p p-priors are used to impose sparsity on the adaptive...
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With the advent and rapid spread of microblogging services, web information management finds a new research topic. Although classical information retrieval methods and techniques help search engines and services to pr...
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Recently, the Internet of Things (IoT) has gained widespread popularity, yet its security remains a critical challenge due to the massive amount of information generated by connected devices. While encryption algorith...
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ISBN:
(数字)9798350350265
ISBN:
(纸本)9798350350272
Recently, the Internet of Things (IoT) has gained widespread popularity, yet its security remains a critical challenge due to the massive amount of information generated by connected devices. While encryption algorithms are commonly employed to protect this information, they are susceptible to various attacks. This paper introduces a novel encryption method to enhance data security in the Consumer IoT domain. The proposed approach combines DNA-inspired encryption with blockchain technology. The DNA encryption algorithm is utilized for the primary encryption phase, followed by the secure handling of encrypted data using blockchain. To evaluate the proposed scheme, a comparison is made with traditional techniques such as RSA, DNA, and a hybrid of both, considering encryption and decryption times. Simulations are conducted using MATLAB software, and an analytical study is performed to assess the performance of the suggested scheme.
Cache management is an important component in any network and it has even more importance in the Future Internet Architectures (FIAs) including Named Data Networking (NDN), because the caches play the key role in redu...
Cache management is an important component in any network and it has even more importance in the Future Internet Architectures (FIAs) including Named Data Networking (NDN), because the caches play the key role in reducing the overall network latency and scalability. In this paper, we discuss the functionality of cache management in NDN, its types as well as its importance for the NDN architecture. In addition, we propose a machine learning-empowered cache management and interests predication for NDN to only preserve the cache only to the secure and really needed data. Our proposal uses Apriori algorithm which is supervised learning algorithm to find the association rules and then to recommend the next requested data. Implementation and experiments on real data traffic depicted that the network’ performance and its influence on the cache increased by 3.2% for two content store sizes of 20 and 40 MB. In addition, a larger cache size of 80 MB shows an increase of the cache hit ratio reaching 90% and hence, clearly reducing the network latency.
We study mathematical models and discuss optimization algorithms for the dimensioning of 3G multimedia networks. We propose two models which aims at dimensioning networks with both a radio and a core component. The fi...
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We study mathematical models and discuss optimization algorithms for the dimensioning of 3G multimedia networks. We propose two models which aims at dimensioning networks with both a radio and a core component. The first one is an anticipative one in which we assume that we know a priori the traffic over the planning period and the dimensioning is defined with a best possible call admission control procedure. The second one is a causal one in which we define an explicit call admission control procedure which makes the accept/reject decisions without any knowledge on the forthcoming traffic. We then compare, on an experimental basis, the dimensioning obtained by both models on some multi-service networks.
Present approaches of automated language scoring lack the ability to investigate the multiple-level and several contexts of sequential features which are helpful to examine the language proficiency for the responses (...
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