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共 13045 条记录，以下是281-290 订阅

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Enhanced Adaptive Video Streaming for Resource-Constrained UAVs through Dynamic Region-of-Interest Tile Swapping 10

Enhanced Adaptive Video Streaming for Resource-Constrained U...

引用

10th International Conference on Applied System Innovation, ICASI 2024

作者： Hsu, Tz-Heng Ju, Rui-Han Horng, Gwo-Jiun Southern Taiwan University of Science and Technology Dept. of Computer Science and Information Engineering Tainan Taiwan

ISBN: (纸本)9798350394924

Real-time video transmission via unmanned aerial vehicles (UAVs) is significantly impacted by latency issues. Using Region of Interest (ROI) tile segmentation methods, video streaming techniques can dynamically adjust the encoding bitrate, assign various priorities to distinct video tiles, and specify different quality quantization factors. High-efficiency video tile encoding techniques, combined with ROI-based streaming methods, can meet various Quality of Service (QoS) criteria. However, dynamically assigning quantization factors for different tiles has the disadvantage of increasing the encoding system's complexity. This study presents a method to dynamically swap ROI tiles to lower the complexity of the encoding system, making it suitable for UAVs with limited computational capacities. By adopting the proposed adaptive video streaming transmission method with tile-swapping strategy, it is feasible to enhance the visual quality in critical areas for resource-constrained UAV devices. © 2024 IEEE.

关键词： Video streaming

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Reconsider Time Series Analysis for Insider Threat Detection

Reconsider Time Series Analysis for Insider Threat Detection

引用

2024 IEEE International Conference on Big Data, BigData 2024

作者： Chen, Chia-Cheng Pao, Hsing-Kuo National Taiwan University of Science and Technology Dept. of Computer Science and Information Engineering Taipei Taiwan

ISBN: (纸本)9798350362480

Insider threat detection (ITD) presents a significant challenge in cybersecurity, particularly within large and complex organizations. Traditionally, ITD has been overshadowed by the focus of external threats, resulting in less attention and development in this critical area. Conventional ITD approaches often rely heavily on event-driven approaches. On top of that, researchers developed various rule-based methods to conquer the tasks. Based on that, we often ignore the intrinsic temporal relationships that are naturally built in between events that occur in different moments. For instance, we may easily understand events with causality such as one anomalous event followed by another specific event to complete a malicious action;however, may not be aware of events that occur around 9 am every morning during working hours. In our opinion, we attempt to re-consider the temporal behavior to extract the information hidden in cyberspace activities. Specifically, some effective sentence embeddings can assist us in providing informative internal representations to summarize temporal behaviors in the temporal activity sequences to make the right judgment on insider threat detection. In this paper, we propose a novel methodology for insider threat detection that emphasizes temporal relationship modeling on top of already-matured event sequence analysis to effectively catch insider threats. The proposed approach leverages contrastive sentence embeddings to learn users' intentions in sequences, followed by the deployment of a user-level and event-level Contrastive Learning (euCL) model to incorporate temporal behaviors with user behavior embeddings. To validate the proposed methodology, we conduct extensive analyses and experiments using the publicly available CERT dataset. The results demonstrate the effectiveness and robustness of the proposed method in detecting insider threats and identifying malicious scenarios, highlighting its potential for enhancing cybersecurity measur

关键词： Contrastive Learning

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Method for Improving the Performance of Operational Amplifier with HA2700 Microchip Architecture

Method for Improving the Performance of Operational Amplifie...

引用

2024 International Conference on Electrical engineering and Photonics, EExPolytech 2024

作者： Kuznetsov, Dmitry V. Titov, Alexey E. Sergeenko, Marsel A. Prokopenko, Nikolay N. Don State Technical University Dept. of Scientific Research Dept. of Information Systems and Radio Engineering Rostov-on-Don Russia Southern Federal University Dept. of Automatic Control Systems Rostov-on-Don Russia Don State Technical University Dept. of Information Systems and Radio Engineering Rostov-on-Don Russia

ISBN: (纸本)9798350388879

A circuit technique for increasing the maximum output voltage slew rate (SR) of an integrated operational amplifier (OpAmp) with the HA2700 microchip architecture based on the modernization of the input differential stage (DS) is considered. An OpAmp architecture is proposed in which the influence of parasitic capacitances of DS reference current sources and capacitances on the transistor substrate on the SR is minimized. This allows the use of micron technological processes in the fabrication of CBJT OpAmps, which are widely used to improve the radiation resistance of microchips. Computer simulation of the proposed OpAmp is performed, which shows that the SR of the new circuit differs from the SR of the well-known serial OpAmp by more than 40 times and reaches values of about 800 V/μs at the emitter current of the input transistors of the DC in the range of up to 80-100 μA. The developed OpAmp is recommended for practical use in discrete-to-analog filters on switched capacitors. © 2024 IEEE.

关键词： Operational amplifiers

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Silicon nitride photonic beam splitters for O-band power and polarization management 23

Silicon nitride photonic beam splitters for O-band power and...

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23rd Slovak-Czech-Polish Optical Conference on Wave and Quantum Aspects of Contemporary Optics

作者： Litvik, Ján Korček, Radovan Benedikovič, Daniel Dept. of Multimedia and Information-Communication Technologies Faculty of Electrical Engineering and Information Technology University of Zilina Univerzitna 1 Zilina01026 Slovakia

ISBN: (数字)9781510688094

ISBN: (纸本)9781510688087

Silicon nitride waveguides play a leading role in photonic system integration. Silicon nitride leverages unique low-loss passive functions, mature deposition techniques of low-pressure chemical vapor deposition and plasma-enhanced chemical vapor deposition, and compatibility with complementary metal-oxide-semiconductor fabrication. So far, a wide variety of photonic devices have been demonstrated in Silicon nitride platforms, including ultra-low-loss waveguides, filters, multiplexers, and grating or edge couplers, to name a few. Among these elements, beam splitters based on multimode interference couplers are key building blocks for complex chip-scale photonic systems, including coherent communications or advanced optical networks. This work is focused on O-band (spectral range between 1260 nm and 1360 nm) multimode interference beam splitters on silicon nitride platform for power and polarization on-chip management. It is used three-dimensional eigenmode expansion and finite difference time domain solvers, respectively. We proposed a 1x2 power and polarization splitters with a compact footprint of 2.6 μm and 5.55 μm and insertion loss as low as 0.3 dB across 400 nm wavelength range. Also, we designed multimode interference power splitters 1:4 and 1:8 with insertion loss as low as 0.5 dB with bandwidth 240 nm and 60 nm, respectively. These results are promising for the development of scalable and high-performance chip-integrated components in power-hungry and polarization-sensitive applications. For effective designing of polarization splitter based on multimode interference it is necessary using apodization techniques to avoid large footprint and very low bandwidth. © 2025 SPIE.

关键词： Silicon nitride

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High Gain, E-Shaped Microstrip Antenna with Two Identical Slits for 5G Applications in the 60 GHz Band 3

High Gain, E-Shaped Microstrip Antenna with Two Identical Sl...

引用

3rd International Conference on Emerging Smart Technologies and Applications, eSmarTA 2023

作者： Ali, Ala'a N. S. Gaid, AbdulGuddoos S. A. Saeed, Mamoon M. Saeed, Rashid A. Hawash, Burkan Taiz University Faculty of Engineering & Information Technology Dept. of Communications & Computer Taiz Yemen Faculty of Engineering Dept. Communications & Electronics Engineering Sana'a Yemen College of Computers & Information Technology Taif University Dept. of Computer Engineering Taif21944 Saudi Arabia Faculty of Information Science & Technology Selangor Malaysia

ISBN: (纸本)9798350305333

This article presents a simple, high-gain, E-shaped antenna suitable for 5G applications in the unlicensed 60 GHz band, characterized by high absorption and path losses. In order to optimize the reflection coefficient performance, enhance the gain, and adjust the resonance frequency of the proposed antenna, two identical slits are incorporated into the front edge of the radiating patch. The proposed structure is built on a Rogers RT/Duroid 5880 dielectric substrate, characterized by a thickness of 0.118 mm, a dielectric constant of 2.2, and a tangent loss of 0.0009. The optimized design with a compact size of 3.8 x 6 x 0.118 mm3 achieves an impedance bandwidth ( © 2023 IEEE.

关键词： Radiation efficiency

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Quasi Neural Network assisted Channel Estimation for MIMO-OFDM 24

Quasi Neural Network assisted Channel Estimation for MIMO-OF...

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24th IEEE International Conference on Communication technology, ICCT 2024

作者： Hu, Wanchen Liang, Xin Yang, Jie Ran, Rong Jiang, Yi Fudan University School of Information Science and Technology Dept. of Communication Science and Engineering Shanghai China

ISBN: (纸本)9798350363760

This paper presents a quasi-neural network (QuasiNN) based parametric channel estimation for multiple inputs and multiple outputs with orthogonal frequency division multiplexing (MIMO-OFDM) systems. This approach jointly considers time delay, multipath gain, direction-of-arrival (DOA), direction-of-departure (DOD), and the number of multipaths. We construct a Quasi-NN that accurately models the signal transmission process via a parametrized channel. By leveraging the layered structure of Quasi-NN, similar to that of artificial neural networks (ANNs), we can directly apply the backpropagation (BP) algorithm. To address parameter initialization in scenarios with clustered multipath distributions, we propose a low-complexity fast Fourier transform (FFT)-based initialization method. Furthermore, we propose a hypothesis testing based method for estimating number of multipaths during the optimization of the Quasi-NN. Simulation results verify that the proposed Quasi-NN assisted parametric channel estimation closely approaches the Cramér Rao Bound (CRB). © 2024 IEEE.

关键词： Orthogonal frequency division multiplexing

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A Survey on Improved Feature engineering Assisted Multi-Constraints Outlier Analysis Model for Heuristic Driven K-Means Clustering

A Survey on Improved Feature Engineering Assisted Multi-Cons...

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2024 International Conference on Knowledge engineering and Communication Systems, ICKECS 2024

作者： Palaparthi, Durga Prasad Sampath, S. Dept. of Information Science & Engineering Adichunchanagiri Institute of Technology Chikkamagaluru India Vtu Belagavi India

ISBN: (纸本)9798350359688

Outliers are the data points that vary significantly from the primary distribution of data. In data mining, determining outliers is an essential task for establishing the data quality, decision-making, and models' performance. Outliers generally cause errors during data collection, sensor malfunction, or data entry. By addressing and detecting outliers, the overall reliability and quality of the data can be increased. The clustering approach is utilized in data mining, image identification, and pattern recognition. In this study, the hard and soft efficient outlier detection clustering models that are implemented for data mining are considered. These are namely K-Means, K++, modified K-Means, K-Medoids, Fuzzy C-means (FCM), Adaptive Switching Randomly Perturbed Particle Swarm Optimization (ASRPPSO) based FCM, and Teaching and Learning-based optimization (TLBO). Accuracy, False Positive Rate (FPR), precision, f-measure, f-score, True Positive Rate (TPR), Completeness Score (CS), Purity measure, Silhouette (SC), Entropy measure, Partition entropy, Partition coefficient Rand Index (RI), Adjusted Rand Index (ARI), Weighted Kappa (WK) coefficient, and convergence time are utilized as the parameters in this study respectively. © 2024 IEEE.

关键词： K-means clustering

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Malware Detection across Clusters

Malware Detection across Clusters

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2023 IEEE International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, ICIITCEE 2023

作者： Manjushree, C.V. Nandakumar, A.N. Vemana Institute of Technology Dept. of Information Science & Engineering India City Engineering College Dept. of Computer Science & Engineering India

ISBN: (纸本)9781665462631

Due to diverse software vulnerabilities and hardware attacks, user credentials are vulnerable or could land in demilitarized zones. An attempt is made to explore and finally proposed a trust based malware detection based on optimal data classification. An improved glowworm swarm optimization (IGWSO) algorithm is proposed for clustering in the input dataset into different groups. After clustering, recurrent deep neural network based computation is used for deriving different trust levels for cloud information that classify the suspected intrusion. The proposed TMD system implemented in java with cloudsim tool evidently discovers the effectiveness of the algorithm over existing state of art systems on the parameters of high detection, precision, recall and F-measures. © 2023 IEEE.

关键词： Deep neural networks

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A Comparative Analysis of ML Algorithms to Improve Crop Productivity Prediction

A Comparative Analysis of ML Algorithms to Improve Crop Prod...

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2023 International Conference on Disruptive Technologies, ICDT 2023

作者： Nigam, Anushree Jain, Divyanshu Talan, Manish Singh Singh, S.K. Umrao, Sandhya Galgotias College of Engineering and Technology Dept. of Information Technology Greater Noida India Noida Institute of Engineering and Technology Dept. of Computer Science Engineering Greater Noida India

ISBN: (纸本)9798350323887

According to numerous calculations, the global food output must significantly increase by 2050. Additionally, water levels have been declining, and there is a shortage of usable agricultural land. The first step to introducing smart agriculture in India is good analysis and implementation of machine learning. This research strives to present the best-fit machine learning algorithm to predict crop production in a specific area, state or season. The aim of this research is to make data-driven farming possible. By comparing various regression models namely decision tree, linear regression, XGB regression, and random forest, authors found the most accurate and fast algorithm to process the large volume of agricultural data. The data was visualized to find the top 5 crops produced in India and then the top 3 of them were visualized area-wise, state-wise, and season-wise to give a detailed analysis of crop distribution and production in India. © 2023 IEEE.

关键词： Crops

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Quantum Resistance Blockchain Algorithm using QHF and Novel Consensus Mechanism

Quantum Resistance Blockchain Algorithm using QHF and Novel ...

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2025 IEEE International Students' Conference on Electrical, Electronics and Computer Science, SCEECS 2025

作者： Paul, Soumyadip Mazumdar, Mausumi Maitra Chakraborty, Sarit Government College of Engineering & Ceramic Technology Dept. of Information Technology Kolkata700010 India Government College of Engineering and Leather Technology Department of Computer Science and Engineering Kolkata700106 India

ISBN: (纸本)9798331529833

The emergence of quantum computing poses a significant threat to the security of traditional blockchain systems, which rely heavily on classical cryptographic algorithms. To safeguard the integrity and reliability of blockchain technology in the upcoming era, this work proposes a novel quantum-resistant blockchain architecture. This approach integrates a robust consensus mechanism, with advanced quantum cryptographic primitives, including quantum digital signatures based on a Quantum Hash Function (QHF). Incorporating a quantum hash function enhances the blockchain resistance, providing an additional layer of security against quantum attacks. By combining these elements, our method creates a blockchain system fortified against the potential vulnerabilities introduced by quantum computers. The proposed solution leverages the power of QHFs to safeguard transaction integrity, while the consensus mechanism ensures the reliability and decentralization of the network. This paper also delves into the theoretical underpinnings of quantum blockchains, exploring their design, feasibility, and potential applications, emphasizing their promising future, particularly in areas such as decentralized identity authentication. Finally, it contributes to the development of a secure and resilient blockchain ecosystem capable of thriving in the coming era. © 2025 IEEE.

关键词： Quantum computers

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