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Turbulence modeling Through Deep Learning: An In-Depth Study of Wasserstein GANs

Turbulence Modeling Through Deep Learning: An In-Depth Study...

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Smart Electronics and Communication (ICOSEC), international conference on

作者： Wajdi Alghamdi S. Mayakannan G A Sivasankar Jagendra Singh B. Ravi Naik Ch. Venkata Krishna Reddy Department of Information Technology Faculty of Computing and Information Technology King Abdulaziz University Jeddah Saudi Arabia Mechanical Engineering Vidyaa Vikas College of Engineering and Technology Tiruchengode Namakkal Tamilnadu Department of Aeronautical Engineering KIT - Kalaignar Karunanidhi Institute of Technology Coimbatore School of Computer Science Engineering and Technology Bennett University Great Noida Uttar Pradesh Department of Mechanical Engineering St. Martin's Engineering College Secunderabad Telangana India Department of Electrical and Electronics Engineering Chaitanya Bharathi Institute of Technology Hyderabad

This research study compares the accuracy of different techniques based on deep learning (DL) for predicting turbulent flows. Different types of Generative Adversarial Networks (GANs) are examined in terms of their applicability to the study and simulation of turbulence. Next, we select Wasserstein Gans (WGANs) to produce localized disturbances. Network features including the learning rate and loss function are examined as they pertain to the performance of the WGANs during training on turbulent data gleaned from high-resolution Direct Numerical simulations (DNS). DNS input data and the generated turbulent structures are proven to agree qualitatively well. The projected turbulent fields are evaluated quantitatively and statistically.

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Prediction of Blockchain Transaction Fraud Using a Lightweight Generative Adversarial Network

Prediction of Blockchain Transaction Fraud Using a Lightweig...

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Blockchain Computing and Applications (BCCA), international conference on

作者： Charles Rawlins S. Jagannathan Donald Wunsch Electrical and Computer Engineering Missouri University of Science and Technology Rolla MO USA

Classic blockchain protocol design is centered around a computationally-intense cryptographic scheme, such as Bitcoin's Proof-of-Work (PoW). Network scalability and efficiency are stifled with the computational resources necessary to approve new transactions, thus rendering PoW unsuitable with limited devices like Internet of Things (IoT). As a first step towards alleviating this, a novel lightweight Generative Adversarial Network (GAN) called Vector GAN (VecGAN) is introduced wherein its weights are tuned through a direct error-driven learning approach with a Bayesian estimator for the selection of random noise matrices, called Bayesian Feedback Alignment (BFA), to augment data for improved fraud prediction. The augmented data is subsequently processed by a classifier for prediction. This combination of VecGAN with a classifier is treated as a novel method of blockchain ledger decision-making to approve ground-truth data. By using the two-step process, prediction accuracy using a classifier was improved up to 8% for real-world datasets. Resource consumption comparison to existing IoT blockchain protocols in a realistic simulation environment is also provided, where lightweight approaches for VecGAN in training and noise modeling reduce computation compared to other techniques.

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Performance Analysis of Covert Communication Based on Integrated Satellite Multiple Terrestrial Relay Networks

Performance Analysis of Covert Communication Based on Integr...

引用

international conference on computer and Communications (ICCC)

作者： Zeke Wu Haifeng Shuai Rui Liu Kefeng Guo Shibing Zhu School of Space Information Space Engineering University Beijing China

With the arrival of the sixth generation (6G) mo-bile communication technology, one of its signature features is satellite-terrestrial fusion communication. Hence, integrated satellite multiple terrestrial relay network (ISMTRN) has become an emerging network architecture that has recently attracted much attention from scholars. Nevertheless, because of the open nature of the wireless channel, it inevitably leads to security issues. Moreover, covert communication technology has been considered one of the most promising and effective methods for secure communication. This paper explores the ISMTRN's covert performance with partial relay selection scheme. Particularly, one scenario that when a satellite communicates with one user via relaying, the specific relay may transmit covert information to the user is considered. Furthermore, we derive the closed-form expression of probability of detection error (PDE) to evaluate covert performance. Lastly, by virtue of numerical simulation, the influence of related system parameters on covert performance is investigated.

关键词： Wireless communication Satellites Closed-form solutions Computational modeling simulation Relay networks (telecommunication) Numerical simulation

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Toward Efficient Physical and Algorithmic Design of Automated Garages

Toward Efficient Physical and Algorithmic Design of Automate...

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IEEE international conference on Robotics and Automation (ICRA)

作者： Teng Guo Jingjin Yu Department of Computer Science Rutgers the State University of New Jersey Piscataway NJ USA

Parking in large metropolitan areas is often a time-consuming task with further implications for traffic patterns that affect urban landscaping. Reducing the premium space needed for parking has led to the development of automated mechanical parking systems. Compared to regular garages having one or two rows of vehicles on each island, automated garages can have multiple rows of vehicles stacked together to support higher parking demands. Although this multi-row layout reduces parking space, it makes parking and retrieval more complicated. In this work, we propose an automated garage design that supports nearly 100% parking density. modeling the problem of parking and retrieving multiple vehicles as a special class of multi-robot path planning problem, we propose associated algorithms for handling all common operations of the automated garage, including (1) optimal algorithm and near-optimal methods that find feasible and efficient solutions for simultaneous parking/retrieval and (2) a novel shuffling mechanism to rearrange vehicles to facilitate scheduled retrieval at rush hours. We conduct thorough simulation studies showing the proposed methods are promising for large and high-density real-world parking applications.

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computer System Breakdown Intelligent Analysis simulation Model Based on Deep Learning

Computer System Breakdown Intelligent Analysis Simulation Mo...

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Mechatronics, IoT and Industrial Informatics (ICMIII), international conference on

作者： Bihua Zhuo Officers College of PAP Department of Information and Communication Chengdu Sichuan China

Massive process measurement message brings great computational complexity and modeling complexity to the traditional breakdown diagnosis algorithm, and the traditional diagnosis algorithm has the disadvantage that it is difficult to make online estimation by using high-order quantities. Modern industrial systems have been developing towards largescale and complexity, which makes the breakdown diagnosis means for industrial systems encounter a series of technical questions. In view of the powerful data representation learning and analysis ability of deep learning technique, breakdown diagnosis based on deep learning has attracted wide attention from industrial and academic circles, and has made intelligent process control more automatic and resultful. The means adopted in this paper is deep learning, which is carried out alternately by convolution and sub-sampling. At last, the algorithm close to the output layer adopts the common multilayer neural network. As a breakthrough in the domain of latter-day artificial intelligence, deep learning can voluntarily learn valuable traits from the original trait set or even the original data. The research in this paper shows that the algorithm in this paper is resultful in breakdown prediction, and it is suitable to be widely applied in practical applications.

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Formal Model for Control of Autonomous Navigation

Formal Model for Control of Autonomous Navigation

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international conference on Sciences and Techniques of Automatic Control and computer Engineering (STA)

作者： Hela Kadri Riheb Cherif Abdel Aitouche Rochdi Merzouki CRISTAL Lille University France ESME ESME Research Lab Lille France Junia Lille CRISTAL France

ISBN: (纸本)9781665482622

Formal modeling techniques can be exploited for autonomous vehicle modeling, enabling resilient navigation inside container terminals (CTs). Road vehicles will be characterized by a new intelligent vehicle technology such as Intelligent Autonomous vehicle (IAV) compared to the trucks, which are able to bring containers within the Terminal Container (TC) based on GPS. In the TC, electric unmanned aerial vehicles (UAVs) present in the TC are able to emulate redundant positioning data from the IAV, where its signals are disturbed within the corridor of containers. Petri nets are formal models suitable for modeling and controlling classes of systems such as transportation systems. They allow to control the movement of the IAV while reconstructing the positioning data of the IAV. This is ensured by GPS or by communication between the IAV that loses its position and the IAV s close to it, the other drones, and the crane. Thus, this paper proposes a reconfiguration strategy for the IAV to manage its navigation under resilient conditions, even if it loses its own GPS signal. simulation results and perspectives are presented in this paper.

关键词： Analytical models Cranes Navigation Computational modeling simulation Petri nets Transportation

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Chinese Implicit Sentiment Analysis based on Hybrid Neural Networks 7

Chinese Implicit Sentiment Analysis based on Hybrid Neural N...

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2020 7th international conference on computer-Aided Design, Manufacturing, modeling and simulation, CDMMS 2020

作者： Qi, Yanfang Wang, Chao Zhu, Guoan School of Computer and Artificial Intelligence Lanzhou Institute of Technology Lanzhou Gansu730030 China School of Computer Science and Engineering Wuhan Institute of Technology Wuhan Hubei430000 China Department of Computer Science and Technology College of Engineering Yanbian University Yanji133002 China

Implicit sentiment analysis is an important part of sentiment computing, especially sentiment analysis based on deep learning has become a research hotspot in recent years. In this paper, convolutional neural networks are used to extract text features, combined with long-term and short-term memory network (LSTM) structure to extract context information, and add attention mechanism to the network to construct a new hybrid neural network model to achieve implicit emotion for text analysis. The hybrid neural network model extracts more meaningful sentence semantic and structural hidden features from the word-level and sentence-level hierarchies, respectively, and pays attention to the features with a large emotional contribution rate through the attention mechanism. The classification accuracy rate of the model on the public implicit sentiment dataset has reached 77%. The research of implicit sentiment analysis can improve the effect of text sentiment analysis more comprehensively, and further promote the application of text sentiment analysis in the fields of knowledge embedding, text representation learning, user modeling and natural language. © Published under licence by IOP Publishing Ltd.

关键词： Sentiment analysis

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Holistic Security Approach in Cybersecurity Services for Datacenters and Telecommunication Operators

Holistic Security Approach in Cybersecurity Services for Dat...

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IEEE international conference on Performance, Computing and Communications (IPCCC)

作者： Kasım Öztoprak Yusuf Kursat Tuncel Department of Computer Engineering Konya Food and Agriculture University Konya Turkey

This study examines and presents a resolution for Protocol Independent Switch Architecture (PISA) to handle data at the application layer, facilitating the precise inspection of security traffic, particularly in relation to DDOS attacks. The primary objective of this approach is to empower telecommunication operators to develop their own networking code within a hardware environment, granting them the ability to write code for hardware-level operations. This strategy also simplifies the process of modeling equipment in a simulation environment, as all components of a hardware switch run compatible code in a software-modeled switch. The innovative techniques proposed in this paper leverage the key functionalities of a programmable switch and combine them with the streaming data processor to achieve the desired outcomes from the perspective of a telecommunication operator, reducing costs and enabling comprehensive network management. The findings demonstrate that the suggested employment of PISA switches remarkably enhances the detection of DDOS attacks. This capability assists operators in bridging a significant gap between flexibility and scalability by efficiently utilizing limited compute resources for DDOS attack detection and response. The study helps to build a building block for a holistic security system combined by deep packet inspection systems and DDOS prevention systems.

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Prediction of the Welding Process Parameters and the Weld Bead Geometry for Robotic Welding Applications with Adaptive Neuro-Fuzzy Models

Prediction of the Welding Process Parameters and the Weld Be...

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Proceedings of the international conference on Intelligent Systems and Network, ICISN 2023

作者： Vu, Minh Duc My, Chu Anh Nguyen, The Nguyen Duong, Xuan Bien Le, Chi Hieu Gao, James Zlatov, Nikolay Hristov, Georgi Nguyen, Van Anh Mahmud, Jamaluddin Packianather, Michael S. Department of Aerospace Engineering Le Quy Don Technical University Hanoi Viet Nam Institute of Simulation Technology Le Quy Don Technical University Hanoi Viet Nam Center of Advanced Technology Le Quy Don Technical University Hanoi Viet Nam Faculty of Science and Engineering University of Greenwich Kent GillinghamME4 4TB United Kingdom Institute of Mechanics Bulgarian Academy of Sciences Sofia1113 Bulgaria University of Ruse "Angel Kanchev" 8 Studentska Street Ruse7004 Bulgaria Welding Engineering Laser Processing Centre Cranfield University Cranfield United Kingdom College of Engineering Universiti Teknologi MARA Selangor Shah Alam Malaysia School of Engineering Cardiff University CardiffCF24 3AA United Kingdom

ISBN: (纸本)9789819947249

The weld bead geometry is the important information for determining the quality and mechanical properties of the weldment. The welding process parameters or variables that affect the weld bead geometry in the conventional arc welding process include the following: the welding voltage U, the welding current I, the wire feed speed WFS, the contact tip to work distance D, and the welding speed S. modeling and predicting the weld bead geometry play an important role in welding process planning, to determine the optimal welding process parameters for achieving the improved weld quality. There have been lots of efforts and studies to develop modeling solutions and simulations to determine the weld bead geometry (Height H and Width W) from the welding process parameters (U, I, WFS, D, S) as the inputs. The welding process parameters can be determined based on the experiences, and the conventional analysis of variance (ANOVA);however, the high welding quality and accuracy are not always obtained. With the advancement of computer vision technologies, digital images from cameras and videos can be used for training the deep learning models, to accurately identify and classify objects. The digital images for evaluating the welding quality and the characteristics of welding objects can be captured via the use of the high-speed camera, and there are emerging data acquisition systems that can handle a huge dataset. In this paper, an adaptive neuro-fuzzy inference system (ANFIS) model is proposed to determine weld bead geometry from the main welding process parameters U, I and S. The proposed ANFIS model was successfully developed for the first basic investigations, as the foundation for further developments of innovative robotic welding systems which can be used for higher educations or research in Smart Manufacturing, with potentials for industrial applications. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Gas metal arc welding

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AI-Based Geo Intelligent System for Attack Prediction and Virtual simulation

AI-Based Geo Intelligent System for Attack Prediction and Vi...

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Intelligent Control, Computing and Communications (IC3), international conference on

作者： N Kavya Shruthi Ajit Kumar Singh Yadav Department of Computer Science and Engineering North Eastern Regional Institute of Science and Technology Nirjuli Arunachal Pradesh

ISBN: (数字)9798331527495

ISBN: (纸本)9798331527501

One of the blooming technologies of AI is the metaverse, The Metaverse is a virtual environment in which users may interact with virtual things and with one another. The Metaverse can be utilized in Military GeoIntelligent systems to build a virtual training environment, allowing Defence personnel to practice in realistic circumstances without the need for costly physical resources. The military personnel can practice in a virtual training environment using the Metaverse that can be created with realistic scenarios. This can aid in enhancing their abilities, judgment, and quickness of response. For instance, pilots can practice flying in various weather conditions, soldiers can hone their tactical skills, and cyber security officials can practice responding to cyberattacks. In this paper, we have focused on AI-based technologies combined with the geo intelligence and metaverse which can jointly help in defence to model and analyse complex geographic situations, allowing defence specialists to explore numerous situations and evaluate the effectiveness of different strategies before deploying resources, with the goal of improving situational awareness, response times, and decision-making capabilities across all security-related agencies. The satellite images obtained from the geo satellites give a brief description of a variety of different types of maps and visualizations, including topographic maps, vegetation maps, and thermal maps. These types of satellite imagery include infrared images, the locations of water bodies, planes, plateaus and a number of other surface structures of earth. The imagery helps in identifying the loopholes of spotting the enemy hiding locations and the risky regions of exposure of the native soldiers. The AI model can identify such locations and predict the possible threat locations. When this kind of model is deployed in the metaverse, it can help the soldiers in being trained for war zone like situations. The predictive outcome can hand

关键词： Training Solid modeling Metaverse Vegetation mapping Surface structures Satellite images Personnel Time factors Intelligent systems computer crime

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