检索结果-内蒙古大学图书馆

Delhi Section Conference (DELCON), IEEE

作者： Jeba Singh O D. Godwin Immanuel Sheila Mahapatra Rajesh Sharma R Akey Sungheetha G. S. Pradeep Ghantasala Centre for Academic Research Alliance University Bengaluru India School of Electrical and Electronics Sathyabama Institute of Science of Technology Chennai India Department of Electrical and Electronics Engineering Alliance University Bengaluru India Department of Computer Sciences and Engineering Alliance University Bengaluru India

ISBN: (数字)9798331518592

ISBN: (纸本)9798331518608

Nowadays, Power Quality (PQ) problems should be more concentrated in distribution systems of power sector. To maintain the power quality in the distribution system the occurrence of PQ disturbances must be identified and compensated. Disturbances like voltage sag and swell are the major issues that cause failure in electrical devices. In this paper, a Superconducting Magnetic Energy Storage (SMES) integrated Dynamic Voltage Restorer (DVR)is implemented to protect the grid voltage from sag, swell and transients. A better solution to PQ disturbances and mitigation related issues are provided through DVR topology. Voltage sag is one of the dominant problems which cause the PQ issues. In this proposed work, sag, swell and outages are mitigated thus the real power is recovered so that the power wastage is prevented. Moreover, this SMES technology-based DVR method compensates the grid from balanced and unbalanced sag, mitigation of outages, interruption, single phase and two-phase swell conditions. The principle, design and working of the SMES based DVR is implemented using MATLAB / SIMULINK. The testing of the established model and performance results are presented.

关键词： Voltage fluctuations Software packages Prevention and mitigation Power quality Reliability engineering Topology Power system reliability Superconducting magnetic energy storage Transient analysis Testing

来源：评论

学校读者我要写书评

暂无评论

A Q-learning-based Multipath Scheduler for Data Transmission Optimization in Heterogeneous Wireless Networks

A Q-learning-based Multipath Scheduler for Data Transmission...

引用

Consumer Communications and Networking Conference, CCNC IEEE

作者： Thanh Trung Nguyen Minh Hai Vu Phi Le Nguyen Phan Thuan Do Kien Nguyen School of Information and Communication Technology Hanoi University of Science and Technology Hanoi Vietnam Faculty of Computer Science Phenikaa University Hanoi Vietnam Institute for Advanced Academic Research Chiba University Japan Graduate School of Engineering Chiba University Japan

In the era of 5G and beyond, mobile devices usually can access several heterogeneous wireless networks (e.g., Wi-Fi and 5G). To simultaneously and efficiently utilize the accessible network resources, muli path transport protocols, such as MPTCP and MPQUIC, have shown much potential. In these protocols, scheduling is one of the critical processes to ensure the performance of the multipath transmission. Although there have been many proposed multipath schedulers in the literature, they have not performed well in heterogeneous networks, especially when the network conditions vary (i.e., dynamicity). In this paper, we propose a novel Q-learning-based Multipath scheduler for data transmission optimization (Q-SAT), aiming to bypass the existing limitation. By leveraging the self-learning ability of reinforcement learning, Q-SAT can instantly observe environmental changes and deploy appropriate path selection to optimize data transmission time. As a result, Q-SAT efficiently schedules multipath communication in heterogeneous wireless networks with different dynamicity levels. We have implemented Q-SAT with MPQUIC and extensively evaluated Q-SAT in an emulated environment and a real network. The evaluation results show that Q-SAT improves the data transmission time by at least 10% in the emulation and 26% in the actual deployment compared to the state-of-the-art schedulers.

关键词： Transport protocols Schedules 5G mobile communication Wireless networks TCPIP Mobile handsets Heterogeneous networks

来源：评论

学校读者我要写书评

暂无评论

Predicting the effectiveness of chemotherapy treatment in lung cancer utilizing artificial intelligence-supported serum N-glycome analysis

引用

computers in Biology and Medicine 2025年 186卷 109681-109681页

作者： Torok, Rebeka Meszaros, Brigitta Gombas, Veronika Vathy-Fogarassy, Agnes Szabo, Miklos Csanky, Eszter Jarvas, Gabor Guttman, Andras Research Institute of Biomolecular and Chemical Engineering University of Pannonia Veszprem Hungary Horváth Csaba Memorial Laboratory of Bioseparation Sciences Research Center for Molecular Medicine Doctoral School of Molecular Medicine Faculty of Medicine University of Debrecen Debrecen Hungary Department of Computer Science and Systems Technology University of Pannonia Veszprem Hungary Department of Pulmonology Borsod Academic County Hospital Miskolc Hungary

An efficient novel approach is introduced to predict the effectiveness of chemotherapy treatment in lung cancer by monitoring the serum N-glycome of patients combined with artificial intelligence-based data analysis. The study involved thirty-three lung cancer patients undergoing chemotherapy treatments. Serum samples were taken before and after the treatment. The N-linked oligosaccharides were enzymatically released, fluorophore-labeled, and analyzed by capillary electrophoresis with laser-induced fluorescence detection. The resulting electropherograms were thoroughly processed and evaluated by artificial intelligence-based classifiers, i.e., utilizing a machine learning algorithm to categorize the data into two (binary) classes. The classifier analysis method revealed a strong association between the structural changes in the N-glycans and the outcomes of the chemotherapy treatments (ROC >0.9). This novel combination of bioanalytical and AI methods provided a precise and rapid tool for predicting the effectiveness of chemotherapy. © 2025 The Authors

关键词： Lung cancer

来源：评论

学校读者我要写书评

暂无评论

Fq-Sat: A Fuzzy Q-Learning-Based Mpquic Scheduler for Data Transmission Optimization

SSRN

引用

SSRN 2023年

作者： Nguyen, Thanh Trung Vu, Minh Hai Dinh, Thi Ha Ly Nguyen, Thanh Hung Le Nguyen, Phi Nguyen, Kien School of Information and Communication Technology Hanoi University of Science and Technology Hanoi Viet Nam Faculty of Computer Science Phenikaa University Hanoi Viet Nam Institute for Advanced Academic Research Chiba University Japan Graduate School of Engineering Chiba University Japan

In the 5G and beyond era, multipath transport protocols, including MPQUIC, are necessary in various use cases. In MPQUIC, one of the most critical issues is efficiently scheduling the upcoming transmission packets on several paths considering path dynamicity. To this end, this paper introduces FQ-SAT - a novel Fuzzy Q-learning-based MPQUIC scheduler for data transmission optimization, including download time, in heterogeneous wireless networks. Different from previous works, FQ-SAT combines Q-learning and Fuzzy logic in an MPQUIC scheduler to determine optimal transmission on heterogeneous paths. FQ-SAT leverages the self-learning ability of reinforcement learning (i.e., in a Q-learning model) to deal with heterogeneity. Moreover, FQ-SAT facilitates Fuzzy logic to dynamically adjust the proposed Q-Learning model's hyper-parameters along with the networks' rapid changes. We evaluate FQ-SAT extensively in various scenarios in both simulated and actual networks. The results show that FQ-SAT reduces the download time by 2.1%-13.5% in simulation and by 2.2%-5.1% in actual network, compared to state-of-the-art MPQUIC schedulers. © 2023, The Authors. All rights reserved.

关键词： Fuzzy logic

来源：评论

学校读者我要写书评

暂无评论

Augmented Selection of Cluster Heads and Enlightening Network Lifetime in Underwater Wireless Sensor Networks Using Grey Wolf Optimization (GWO) 6

Augmented Selection of Cluster Heads and Enlightening Networ...

引用

6th International Conference on Contemporary Computing and Informatics, IC3I 2023

作者： Hole, Snehal Zaboun, Abdul Razzaq T. Al-Ghanimi, Hayder Hussen, Omad Aldeen Alchilibi, Haider Abdul Kadeem, Sahar R. S.N.G Institute of Management and Research Pune India Al-Esraa University College Forensic Sciences Department Baghdad Iraq Techniques Engineering Hilla University College Department of Medical Instrumentation Babylon Iraq Al-Kunooze University College Computer Engineer Department Basra Iraq Al-Farahidi University Medical Laboratory Techniques Department Baghdad10022 Iraq National University of Science and Technology Dhi Qar Iraq

ISBN: (纸本)9798350304480

The Underwater Wireless Sensor Network (UWSN) is a collection of sensor nodes deployed beneath the seabed to monitor and record challenging applications in offshore exploration and oceanic environments. In order to ensure proper energy consumption in a dynamic environment, the effective forwarding of data packets through efficient paths is crucial. Routing, therefore, plays a significant role in reducing power consumption by making informed decisions on packet destinations. In this study, we propose and analyze an efficient routing technique for underwater wireless sensor networks based on Grey-Wolf Optimization. The proposed technique is evaluated under various conditions, and the experimental results demonstrate a reduced number of iterations for selecting a cluster head, leading to a longer network lifetime compared to existing protocols such as Energy Efficient Routing Protocol (EERP) and Directional Flooding based Routing (DFR). © 2023 IEEE.

关键词： DFR EERP Energy routing Grey wolf lifetime

来源：评论

学校读者我要写书评

暂无评论

Personalizing text summarization based on sentence weighting

Personalizing text summarization based on sentence weighting

引用

2007 IADIS European Conference on Data Mining, DM 2007, part of the 1st IADIS Multi Conference on computer Science and Information Systems, MCCSIS 2007

作者： Bouras, Christos Poulopoulos, Vassilis Tsogkas, Vassilis Research Academic Computer Technology Institute Computer Engineering and Informatics Department University of Patras N. Kazantzaki Str. Rion26500 Greece

ISBN: (纸本)9789728924409

The amount of data that exists on the Internet is enormous enough to distract users when trying to find useful information. In addition, the expansive use of small screen devices for browsing the World Wide Web generates huge problems when trying to find and read information. A solution to these problems is to personalize the web and try to reduce algorithmically the amount of text. Many text summarizers have been presented in order to reduce the valueless information that is presented to the users and many web sites, especially news portals, introduce personalization features for the users, though, still these techniques are not often used in combination in order to create more effective results. In this paper a mechanism for creating personalized summaries for the members of a news portal that reproduces articles collected from major portals is presented, together with evaluation both of the summarizer and the personalized summaries. The evaluators of the personalized summaries are members of the news portal. The personalized summary mechanism can also be utilized by users of small screen devices, for easier reading of less but inclusive information. © 2007 IADIS

关键词： Text processing

来源：评论

学校读者我要写书评

暂无评论

An innovation analysis of LZ77 and LZ78 Compression Algorithms for Data Compression & Source Coding

An innovation analysis of LZ77 and LZ78 Compression Algorith...

引用

International Conference on Computing and Networking technology (ICCNT)

作者： Rakesh Kumar Giri Abhinav Mishra Aruna Sri Rongali Laxmi A. Bewoor R Raghavendra M. S. Kavitha Department of Computer Science & Engineering Sunrise University Alwar India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of Information Technology Emphasis/Technology Software Engineer Ph.D University of The Cumberlands US Department of Computer Engineering Vishwakarma Institute of Technology Pune INDIA College of Computing Sciences And Information Technology Jain (deemed to be) University Bangalore Karnataka India Department of ECER. M. K. Engineering College RSM Nagar Kavaraipettai

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

This paper evaluates innovation on two of the most widely used compression algorithms — the LZ77 and the LZ78 algorithms — for information compression and supply coding programs. A detailed assessment of these algorithms presents insights approximately their design philosophy, technical traits, and performance metrics. Additionally, the studies offer a complete overview of their packages and implementations. The paper investigates the prominent considerations for implementing compression algorithms and analyzes their relative blessings and downsides. An exploration of the constraints of every algorithm is likewise undertaken. Furthermore, the research explores distinctive design elements of the algorithms, such as data structure, compression engine, and set of rules optimization. Eventually, the paper assesses the algorithms by reading the exchange-offs between their performance and complexity. This study facilitates practitioners and developers to apprehend the results of using those algorithms for diverse compression and supply coding applications. It can assist practitioners in identifying the first-class compression set of rules for their unique application needs. This paper gives an innovative evaluation of the LZ77 and LZ78 Compression Algorithms. These algorithms are algorithms designed for statistics compression and source coding. They’re used to take a given series of characters (or bits) and encode them right into an area-green representation. The innovation evaluation presents a valuable perception of how the algorithms improve compression ratios and shop area. It also discusses the effect of positive parameters such as window length, repeat cycle, and buffer size on compression efficiency. ultimately, the paper will speak to future studies’ challenges in this region and the capability packages of those algorithms.

关键词： Measurement Technological innovation Image coding Codes Philosophical considerations Source coding Green products Approximation algorithms Compression algorithms Optimization

来源：评论

学校读者我要写书评

暂无评论

Forest Region Extraction and Evaluation from Satellite Images using CNN Segmentation

Forest Region Extraction and Evaluation from Satellite Image...

引用

Advances in Computing, Communication and Applied Informatics (ACCAI), International Conference on

作者： Swaetha Ramadasan K. Vijayakumar S. Prabha E. Karthickeien Senior Business Intelligence Engineer Perma Technologies Atlanta GA USA Department of Information Technology St. Joseph’s Institute of Technology OMR Chennai TN India Department of CSE Center for Research and Innovation Saveetha School of Engineering SIMATS Chennai TN India Computer and Communication Engineering Amrita Vishwa Vidyapeetham Chennai TN India

ISBN: (数字)9798350389449

ISBN: (纸本)9798350389456

The segmentation and analysis of forests from satellite images play a vital role in the comprehensive monitoring and effective management of ecosystems. This process facilitates precise evaluations of various critical aspects such as forest cover, biodiversity, and overall health. By connecting this information, resource planning becomes more informed and strategic, contributing to sustainable forest management practices. Moreover, the data derived from satellite imagery aids in identifying areas susceptible to deforestation, allowing for timely intervention to mitigate its adverse environmental impacts. The integration of advanced satellite technologies in forest analysis enhances the ability to address contemporary environmental challenges, providing a foundation for policies and practices that promote ecological resilience and the long-term well-being of our planet. In this work, VGG-UNet is implemented to segment the forest and it achieved an accuracy of >94%, which is better compared to other existing methods in the literature.

关键词： Measurement Image segmentation Forests Satellites Information resources Planets Satellite images

来源：评论

学校读者我要写书评

暂无评论

MSEMG: Surface Electromyography Denoising with a Mamba-based Efficient Network

MSEMG: Surface Electromyography Denoising with a Mamba-based...

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Yu-Tung Liu Kuan-Chen Wang Rong Chao Sabato Marco Siniscalchi Ping-Cheng Yeh Yu Tsao Department of Electronics and Electrical Engineering National Yang Ming Chiao Tung University Taiwan Research Center for Information Technology Innovation Academic Sinica Taiwan Graduate Institute of Communication Engineering National Taiwan University Taiwan Department of Computer Science and Information Engineering National Taiwan University Taiwan University of Palermo Italy

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Surface electromyography (sEMG) recordings can be contaminated by electrocardiogram (ECG) signals when the monitored muscle is closed to the heart. Traditional signal processing-based approaches, such as high-pass filtering and template subtraction, have been used to remove ECG interference but are often limited in their effectiveness. Recently, neural network-based methods have shown greater promise for sEMG denoising, but they still struggle to balance both efficiency and effectiveness. In this study, we introduce MSEMG, a novel system that integrates the Mamba state space model with a convolutional neural network to serve as a lightweight sEMG denoising model. We evaluated MSEMG using sEMG data from the Non-Invasive Adaptive Prosthetics database and ECG signals from the MIT-BIH Normal Sinus Rhythm Database. The results show that MSEMG outperforms existing methods, generating higher-quality sEMG signals using fewer parameters.

关键词： Adaptation models Databases Computational modeling Surface contamination Noise reduction Interference Electrocardiography Electromyography Speech processing Surface treatment

来源：评论

学校读者我要写书评

暂无评论

Nuclear correlation functions using first-principle calculations of lattice quantum chromodynamics

arXiv

引用

arXiv 2024年

作者： Chakraborty, Debsubhra Srivastava, Piyush Kumar, Arpith Mathur, Nilmani Department of Theoretical Physics Tata Institute of Fundamental Research Homi Bhabha Road Mumbai400005 India School of Technology and Computer Science Tata Institute of Fundamental Research Homi Bhabha Road Mumbai400005 India Department of Physical Sciences IISER Mohali Academic Block 1 AB1-1F9 Sector 81 Mohali India

Exploring nuclear physics through the fundamental constituents of the strong force - quarks and gluons - is a formidable challenge. While numerical calculations using lattice quantum chromodynamics offer the most promising approach for this pursuit, practical implementation is arduous, especially due to the uncontrollable growth of quark-combinatorics, the so-called Wick-contraction problem of nuclei. We present here two novel methods providing a state-of-the art solution to this problem. In the first, we exploit randomized algorithms inspired from computational number theory to detect and eliminate redundancies that arise in Wick contraction computations. Our second method explores facilities for automation of tensor computations-in terms of efficient utilization of specialized hardware, algorithmic optimizations, as well as ease of programming and the potential for automatic code generation-that are offered by new programming models inspired by applications in machine learning (e.g., TensorFlow). We demonstrate the efficacy of our methods by computing two-point correlation functions for Deuteron, Helium-3, Helium-4 and Lithium-7, achieving at least an order of magnitude improvement over existing algorithms with efficient implementation on GPU-accelerators. Additionally, we discover an intriguing characteristic shared by all the nuclei we study: specific spin-color combinations dominate the correlation functions, hinting at a potential connection to an as-yetunidentified symmetry in nuclei. Moreover finding them beforehand can reduce the computing time further and substantially. Our results, with the efficiency that we achieved, suggest the possibility of extending the applicability of our methods for calculating properties of light nuclei, potentially up to A ∼12 and beyond. Copyright © 2024, The Authors. All rights reserved.

关键词： Tensors

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：