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10th International Conference on Web Research, ICWR 2024

作者： Baradaran, Amir Hossein Bohlouli, Masoumeh Motlagh, Mohammad Reza Jahed Iran University of Science and Technology School of Electrical Engineering Tehran Iran Alzahra University Department of Computer Engineering Tehran Iran Iran University of Science and Technology School of Computer Engineering Tehran Iran

ISBN: (纸本)9798350394986

With the rising prominence of gold as a lucrative investment avenue in Iran, this research delves into predicting the future price of 18-carat gold. In pursuit of this objective, a comprehensive comparison is conducted between two neural network architectures: the Gated Recurrent Unit (GRU) as a single structure and a hybrid model combining Convolutional Neural Network (CNN) and Long Short-Term Memory Neural Network (LSTM). The evaluation criteria employed focus on error metrics to gauge the accuracy of price predictions. Results reveal that the CNN-LSTM hybrid neural network exhibits superior performance, showcasing lower error values in predicting the price of 18-carat gold in Iran. Consequently, the chosen model, CNN-LSTM, is employed to forecast the following day's gold prices, providing valuable insights for investors navigating the Iranian market. This research contributes to the ongoing discourse on gold investment strategies by highlighting the effectiveness of advanced neural network models in enhancing predictive accuracy. © 2024 IEEE.

关键词： Long short-term memory

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Accurate threat hunting in industrial internet of things edge devices

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Digital Communications and Networks 2023年第5期9卷 1123-1130页

作者： Abbas Yazdinejad Behrouz Zolfaghari Ali Dehghantanha Hadis Karimipour Gautam Srivastava Reza M.Parizi Cyber Science Lab School of Computer ScienceUniversity of GuelphOntarioCanada Department of Electrical and Software Engineering University of CalgaryAlbertaCanada Department of Mathematics and Computer Science Brandon UniversityBrandonCanada College of Computing and Software Engineering Kennesaw State UniversityGAUSA Research Center for Interneural Computing China Medical UniversityTaichungTaiwanChina Department of Computer Science and Mathematics Lebanese American UniversityBeirut1102Lebanon

Industrial Internet of Things(IIoT)systems depend on a growing number of edge devices such as sensors,controllers,and robots for data collection,transmission,storage,and *** kind of malicious or abnormal function by each of these devices can jeopardize the security of the entire ***,they can allow malicious software installed on end nodes to penetrate the *** paper presents a parallel ensemble model for threat hunting based on anomalies in the behavior of IIoT edge *** proposed model is flexible enough to use several state-of-the-art classifiers as the basic learner and efficiently classifies multi-class anomalies using the Multi-class AdaBoost and majority *** evaluations using a dataset consisting of multi-source normal records and multi-class anomalies demonstrate that our model outperforms existing approaches in terms of accuracy,F1 score,recall,and precision.

关键词： IIoT Threat hunting Edge devices Multi-class anomalies Ensemble methods

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Application of Recursive Query on Structured Query Language Server

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Journal of Donghua University(English Edition) 2023年第1期40卷 68-73页

作者：荀雪莲 ABHIJIT Sen 姚志强 Library North China Institute of Aerospace EngineeringLangfang 065000China Department of Computer Science&Information System Kwantlen Polytechnic UniversitySurreyCanada School of Computer Science and Engineering North China Institute of Aerospace EngineeringLangfang 065000China

The advantage of recursive programming is that it is very easy to write and it only requires very few lines of code if done *** query language(SQL)is a database language and is used to manipulate *** Microsoft SQL Server 2000,recursive queries are implemented to retrieve data which is presented in a hierarchical format,but this way has its *** table expression(CTE)construction introduced in Microsoft SQL Server 2005 provides the significant advantage of being able to reference itself to create a recursive *** data structures,organizational charts and other parent-child table relationship reports can easily benefit from the use of recursive *** recursive query is illustrated and implemented on some simple hierarchical *** addition,one business case study is brought forward and the solution using recursive query based on CTE is *** the same time,stored procedures are programmed to do the recursion in *** results show that recursive queries based on CTEs bring us the chance to create much more complex queries while retaining a much simpler syntax.

关键词： structured query language(SQL)server common table expression(CTE) recursive query stored procedure hierarchical data

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UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical engineering and computer science 2024年第1期86卷 91-104页

作者： Xu, Yong Peng, Yunke Wang, Hengna Wang, Xue’Er Department of Computer Science & Technology Anhui University of Finance & Economics Bengbu233000 China School of Management Science & Engineering Anhui University of Finance & Economics Bengbu233000 China

In addressing the limitations of traditional short text similarity calculation methods, this paper presents SMSABLC, a deep learning-based approach that takes into account polysemy, character order, and contextual semantics. Utilizing word embedding, SMSABLC converts short text into vectors, initiating the integration of a multi-head self-attention mechanism. This mechanism adeptly captures the relationship between words and the overall context within the short texts, spanning across multiple subspaces. Additionally, two opposing LSTM models are employed to acquire bidirectional sequential information from the character context in the short texts. Employing a combination of a convolutional layer and a pooling layer, CNN effectively facilitates the extraction of local character features inherent in the short text. Moving forward, the subsequent step entails the computation of the discernible difference existing between the two distinct short text vectors. This difference value is then inputted into a fully connected layer, whereupon the ensuing utilization of the Sigmoid function aids in the determination of the extent of similarity between the two textual entities. This article conducted experiments on two datasets, CCKS2018 and LCQMC, and compared with traditional methods and some deep learning based methods, SMSABLC achieved better experimental results. Through the analysis of experimental results, it can be concluded that SMSABLC achieves significant improvements in the calculation of short text similarity by effectively incorporating a wide range of deep semantic information. © 2024, Politechnica University of Bucharest. All rights reserved.

关键词： Convolutional neural networks

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Game-Theoretic Approach for Integrated Sensing and Computation Offloading in Vehicular Edge Networks: A Utility Maximization Design

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IEEE Internet of Things Journal 2025年第13期12卷 23694-23708页

作者： Wang, Lina Wu, Weihong Dai, Minghui Zh, Haijun University of Science and Technology Beijing department of Communication Engineering China Donghua University School of Computer Science and Technology Shanghai China Beijing Engineering and Technology Research Center for Convergence Networks and Ubiquitous Services University of Science and Technology Beijing Beijing China

In recent years, with the rapid development of the Internet of Vehicles (IoVs) and the widespread application of integrated sensing and communication (ISAC) in the IoVs, the integrated sensing and computation offloading in vehicular edge networks has attracted widespread attention from academia and industry. Due to the generation of a large number of latencysensitive tasks from vehicles’ real-time sensing of road conditions, coupled with the rise of other computing-intensive vehicle applications, the current computing capabilities of the onboard devices cannot meet the diverse demands of vehicular users. Therefore, it is necessary to combine the computing resources around the vehicle to complete computing tasks. With the goal of maximizing the difference between gain and consumption, this paper studies the integrated sensing and computation offloading involving roadside units (RSUs) and vehicle platoon in vehicular edge networks. Specifically, we first consider that mobile vehicles can simultaneously offload computing tasks to RSU and vehicle platoon via non-orthogonal multiple access (NOMA) technology, and construct a multi-objective optimization problem with the goal of maximizing the utility of the three parties. Then, we construct a game model among ISAC vehicle, RSU, and vehicle platoon based on the Stackelberg game. By seeking the equilibrium of the game, the optimal offloading and pricing strategy are derived, while the utility of the three parties is maximized. Finally, the simulation results show that the proposed scheme is superior to other traditional schemes, and each party in the game obtains its optimal strategy. © 2014 IEEE.

关键词： Multiobjective optimization

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Enhancing Driver Safety Using Deep Learning Models 5

Enhancing Driver Safety Using Deep Learning Models

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5th IEEE Global Conference for Advancement in Technology, GCAT 2024

作者： Shokeen, Ishaan Uday, Krishnendu M Venugopalan, Manju Amrita Vishwa Vidyapeetham Amrita School of Engineering Department of Electronics and Computer Engineering Bengaluru India Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350376685

This proposed work emphasizes the critical role of eye movement detection, particularly open and closed eye states, in identifying drowsiness, providing a clear focus on the project's main technological approach and its importance for road safety. The proposed model ensures constant checks on the driver's safety and provides necessary observations on their behavioral activities. To ensure effective drowsiness detection, different methodologies such as Convolutional Neural Networks (CNN), customized Neural Networks and Recurrent Neural Networks (RNN) were employed for image processing. The CNN model achieved the best results. Two different data sources from Kaggle provided various training images for the model to operate in different scenarios. The proposed model aims to achieve accurate predictions across various case scenarios and to develop the most efficient model for real-time detection and alert systems, ensuring driver safety. Among the models our system gives the best result using CNN reporting an accuracy of 98.53%, and precision, recall and F-score of 98.71%, 98.04% and 98.37% respectively. © 2024 IEEE.

关键词： Convolutional neural networks

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Neural network-supported study on erosive wear performance analysis of Y2O3/WC-10Co4Cr HVOF coating

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Journal of King Saud University - engineering sciences 2024年第8期36卷 662-676页

作者： Singh, Jashanpreet Singh, Simranjit Department of Engineering Punjab State Aeronautical Engineering College Punjab Patiala147001 India School of Computer Science Engineering and Technology Bennett University Uttar Pradesh Greater Noida201310 India

In this work, a study was carried out by modifying the conventional Tungsten Carbide Cobalt Chrome (WC–10Co4Cr) powder with a small addition of yttrium-oxide (Y2O3). Reinforcement was done by adding yttria (Y2O3) ceramics in WC–10Co4Cr powder by using a jar ball mill process. The surface microstructure, chemical composition, and phase compositions of coating powder and coatings were examined by using scanning electron microscopy, energy dispersive spectroscopy, and X-ray diffractometry. Silt erosion was evaluated through a pot tester by preparing equi- and multi-sized slurries at different velocities, impact angles, concentrations, and rates. Results show that the WC–10Co4Cr powder coating reinforced by Y2O3 ceramics possesses low porosity, providing higher erosive performance as compared to conventional WC–10Co4Cr coating. The present study reveals that the deposition of conventional WC–10Co4Cr coating helps improve the wear resistance of AISI 316L stainless steel (UNS S31600) by 9.98% for the variation in rotational speed. However, the erosive wear performance of conventional WC–10Co4Cr coating was improved by 45.9% by blending it with the Y2O3 ceramics. © 2021 The Authors

关键词： Wear of materials

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Identification of DNA N4-methylcytosine Sites via Multiview Kernel Sparse Representation Model

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第5期4卷 1236-1245页

作者： Ai, Chengwei Tiwari, Prayag Yang, Hongpeng Ding, Yijie Tang, Jijun Guo, Fei Tianjin University School of Computer Science and Technology College of Intelligence and Computing Tianjin300072 China Aalto University Department of Computer Science Espoo02150 Finland Quzhou610056 China University of South Carolina Department of Computational Science and Engineering CO29208 United States Central South University School of Computer Science and Engineering Changsha410017 China

Identifying DNA N4-methylcytosine (4mC) sites is of great significance in biological research, such as chromatin structure, DNA stability, DNA-protein interaction, and controlling gene expression. However, the traditional sequencing technology to identify 4mC sites is very time-consuming. In order to detect 4mC sites, we develop a multiview learning method for achieving more effectively via merging multiple feature spaces. Furthermore, we think about whether the multiview learning method can improve the across species classification ability by fusing data of multiple species. In our study, we propose a multiview Laplacian kernel sparse representation-based classifier, called MvLapKSRC-HSIC. First, we make use of three feature extraction methods [position-specific trinucleotide propensity, nucleotide chemical property, and DNA physicochemical properties) to extract the DNA sequence features. MvLapKSRC-HSIC uses a kernel sparse representation-based classifier with graph regularization. In order to maintain the independence between various views, we add a multiview regularization term constructed by Hilbert-Schmidt independence criterion (HSIC). In the experiments, MvLapKSRC-HSIC is applied on six datasets, so as to compare with other popular methods in single-species and cross-species experiments. All experimental results show that MvLapKSRC-HSIC is superior to other outstanding methods on both single species and cross species. Importantly, MvLapKSRC-HSIC can identify a series of potential DNA 4mC sites, which have not yet been experimentally evaluate on multiple species and merit further research. © 2020 IEEE.

关键词： Feature extraction

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EECLP: AWireless Sensor Networks Energy Efficient Cross-Layer Protocol

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computers, Materials & Continua 2024年第8期80卷 2611-2631页

作者： Mohammed Kaddi Mohammed Omari Moamen Alnatoor LDDI Laboratory University of AdrarAdrar01000Algeria Computer Science and Engineering Department School of EngineeringAmerican University of Ras Al KhaimahRas Al Khaimah72603United Arab Emirates

Recent advancements in wireless communications have allowed the birth of novel wireless sensor networks(WSN).A sensor network comprises several micro-sensors deployed randomly in an area of interest.A micro-sensor is provided with an energy resource to supply electricity to all of its ***,the disposed energy resource is limited and battery replacement is generally *** this restriction,the sensors must conserve energy to prolong their *** energy conservation strategies for WSNs have been presented in the literature,from the application to the physical *** of these solutions focus only on optimizing a single layer in terms of energy *** this research,a novel cross-layer technique for WSNs’effective energy usage is *** most energy consumption factors exist in the Medium Access Control(MAC)layer and network layer,our EECLP protocol(Energy Efficient Cross-Layer Protocol for Wireless Sensor Networks)integrates these two layers to satisfy energy efficiency *** gain access to the transmission channel,we implement a communication regime at the MAC layer based on CSMA/CA(Carrier Sense Multiple Access/Collision Avoidance)***,depending on the activity and a standby period,we employ the RTS/CTS(Request to Send/Clear to Send)method to prevent collisions and resolve hidden node concerns by utilizing the network allocation vector(NAV)to calculate the transmission *** a greedy strategy,we establish chains amongst cluster members to mitigate the issue of high energy consumption in routing *** objective function was utilized to determine the optimal cross-chain path based on the distances to the base station(BS)and residual energy(RE).The simulation,testing,and comparison of the proposed protocol to peer protocols have shown superior outcomes and a prolonged network *** the suggested protocol,the network lifetime increases by 10%compared to FAMACO(Fuzzy and Ant Col

关键词： WSN energy consumption MAC layer network layer EECLP energy-efficient lifespan

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Joint Mode Selection and Beamforming Designs for Hybrid-RIS Assisted ISAC systems

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IEEE Wireless Communications Letters 2025年第6期14卷 1718-1722页

作者： Lin, Yingbin Wang, Feng Zhang, Xiao Han, Guojun Lau, Vincent K. N. Guangdong University of Technology School of Information Engineering Guangzhou510006 China South-Central Minzu University College of Computer Science Wuhan430079 China The Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong Hong Kong

This letter considers a hybrid reconfigurable intelligent surface (RIS) assisted integrated sensing and communication (ISAC) system, where each RIS element can flexibly switch between the active and passive modes. Subject to the signal-to-interference-plus-noise ratio (SINR) constraint for each communication user (CU) and the transmit power constraints for both the base station (BS) and the active RIS elements, with the objective of maximizing the minimum beampattern gain among multiple targets, we jointly optimize the BS transmit beamforming for ISAC and the mode selection of each RIS reflecting element, as well as the RIS reflection coefficient matrix. Such formulated joint hybrid-RIS assisted ISAC design problem is a mixed-integer nonlinear program, which is decomposed into two low-dimensional subproblems being solved in an alternating manner. Specifically, by using the semidefinite relaxation (SDR) technique along with the rank-one beamforming construction process, we efficiently obtain the optimal ISAC transmit beamforming design at the BS. Via the SDR and successive convex approximation (SCA) techniques, we jointly determine the active/passive mode selection and reflection coefficient for each RIS element. Numerical results demonstrate that the proposed design solution is significantly superior to the existing baseline solutions. © 2012 IEEE.

关键词： Beamforming

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