检索结果-内蒙古大学图书馆

Enhancing Renewable Energy Integration:A Gaussian-Bare-Bones Levy Cheetah Optimization Approach to Optimal Power Flow in Electrical Networks

引用

computer Modeling in engineering & sciences 2024年第8期140卷 1339-1370页

作者： Ali S.Alghamdi Mohamed A.Zohdy Saad Aldoihi Department of Electrical Engineering College of EngineeringMajmaah UniversityAl-Majmaah11952Saudi Arabia Electrical and Computer Engineering Department Oakland UniversityRochesterMI48309USA Institute of Earth and Space Science King Abdulaziz City for Science and Technology(KACST)Riyadh11442Saudi Arabia Computer Science and Systems Engineering Institute Polytechnique de ParisPalaiseau CedexFrance

In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(RESs).Efficient integration of stochastic RESs and optimal power flow(OPF)management are critical for network *** study introduces an innovative solution,the Gaussian Bare-Bones Levy Cheetah Optimizer(GBBLCO),addressing OPF challenges in power generation systems with stochastic *** primary objective is to minimize the total operating costs of RESs,considering four functions:overall operating costs,voltage deviation management,emissions reduction,voltage stability index(VSI)and power loss ***,a carbon tax is included in the objective function to reduce carbon *** scrutiny,using modified IEEE 30-bus and IEEE 118-bus systems,validates GBBLCO’s superior performance in achieving optimal *** results demonstrate GBBLCO’s efficacy in six optimization scenarios:total cost with valve point effects,total cost with emission and carbon tax,total cost with prohibited operating zones,active power loss optimization,voltage deviation optimization and enhancing voltage stability index(VSI).GBBLCO outperforms conventional techniques in each scenario,showcasing rapid convergence and superior solution ***,GBBLCO navigates complexities introduced by valve point effects,adapts to environmental constraints,optimizes costs while considering prohibited operating zones,minimizes active power losses,and optimizes voltage deviation by enhancing the voltage stability index(VSI)*** research significantly contributes to advancing OPF,emphasizing GBBLCO’s improved global search capabilities and ability to address challenges related to local *** emerges as a versatile and robust optimization tool for diverse challenges in power systems,offering a promising solution for the evolving needs of renewable energy-integrated power grids.

关键词： Renewable energy integration optimal power flow stochastic renewable energy sources gaussian-bare-bones levy cheetah optimizer electrical network optimization carbon tax optimization

来源：评论

学校读者我要写书评

暂无评论

MediGuide AI using Machine Learning 2

MediGuide AI using Machine Learning

引用

2nd International Conference on Machine Learning and Autonomous systems, ICMLAS 2025

作者： Pooja, R. Elugubanti, Nikitha Mary Shiba, C. Kalai priya, V. Sasirekha, K. Sabapathy, S Rathana R.M.K Engineering College Computer Science and Business Systems Tiruvallur District Kavaraipettai India R.M.K Engineering College Department Of Computer Science and Business Systems Kavaraipettai India R.M.K College of Engineering and Technology Department Of Computer Science and Engineering Tiruvallur District Puduvoyal India R.M.D Engineering College Department Of Computer Science and Business Systems Kavaraipettai India Dhaanish Ahmed College of Engineering Department Of Computer Science and Engineering Vanchuvanchery Chennai India

ISBN: (纸本)9798331505745

Providing diverse patient groups with their specific medication requirements, using a wide range of drugs, poses meaningful challenges for prescribing. Standardized approaches often lead to large waste, many side effects and suboptimal outcomes. Therefore, we need improved, more personalized healthcare. MediGuide AI's drug recommendation system is powered by machine learning and it offers a thorough solution. Optimized data pre-processing and analysis, leading to the desired outcome, is achieved using advanced machine learning algorithms like Naive Bayes, TF-IDF and the Natural Language Toolkit. Highly personalized prescriptions are generated using thorough patient data, including demographics and meaningful clinical factors to achieve substantially better accuracy. Important enhancements include dual recommendation outputs, which provide many drug recommendations alongside a large number of alternative Ayurvedic treatments presented side by side for effortless comparison. An advanced personalized dosage calculation module precisely determines drug dosages using advanced regression models based on age, weight and metabolism. This system helps patients track and record their medications and it also suggests several nearby Ayurvedic shops based on their location. MediGuide AI employs exceptionally powerful algorithms and its advanced tools deliver remarkably precise and exceptionally user-friendly healthcare solutions. Current systems make use of rule-based methods that cannot learn from new data, whereas MediGuide AI leverages a hybrid Naïve Bayes and PassiveAggressiveClassifier model for higher accuracy and real-time adaptability. It also includes Ayurvedic options to ensure personalized healthcare experience. © 2025 IEEE.

关键词： Drug dosage

来源：评论

学校读者我要写书评

暂无评论

Defense for Advanced Persistent Threat with Inadvertent and Malicious Insider Threats

引用

无人系统（英文） 2024年第2期12卷 341-358页

作者： Ziqin Chen Guanpu Chen Yiguang Hong Department of Control Science and Engineering and Shanghai Research Institute for Intelligent Autonomous Systems Tongji UniversityShanghaiP.R.China School of Electrical Engineering and Computer Science KTH Royal Institute of TechnologyStockholmSweden

In this paper,we propose a game theory framework to solve advanced persistent threat problems,especially considering two types of insider threats:malicious and *** this framework,we establish a unified three-player game model and derive Nash equilibria in response to different types of insider *** analyzing these Nash equilibria,we provide quantitative solutions to advanced persistent threat problems pertaining to insider ***,we have conducted a comparative assessment of the optimal defense strategy and corresponding defender's costs between two types of insider ***,our findings advocate a more proactive defense strategy against inadvertent insider threats in contrast to malicious ones,despite the latter imposing a higher burden on the *** theoretical results are substantiated by numerical results,which additionally include a detailed exploration of the conditions under which different insiders adopt risky *** conditions can serve as guiding indicators for the defender when calibrating their monitoring intensities and devising defensive strategies.

关键词： Security game advanced persistent threat insider threats Nash equilibrium

来源：评论

学校读者我要写书评

暂无评论

Heart Diseases Prediction with Sound Wave using Support Vector Machine 2

Heart Diseases Prediction with Sound Wave using Support Vect...

引用

2nd International Conference on Artificial Intelligence and Machine Learning Applications, AIMLA 2024

作者： Hariharasudhan, S. Komarasamy, Dinesh Aravindh, S. Darshan, S. Saranya, S. Mohana Iyapparaja, M. Kongu Engineering College Department of Computer Science & Engineering Perundurai India VIT School of Computer Science Engineering and Information Systems Tamil Nadu Vellore India

ISBN: (纸本)9798350349221

Heart illnesses are now an increasing occurrence, and regular human heart testing gets more and more significant. The Phonocardiogram (PCG), a useful diagnostic technique for examining heart sounds, offers insightful data regarding the clinical state of the heart. This research provides an algorithmic method employing PCG sound data to distinguish between abnormal and normal cardiac sounds. Both signal types undergo Cepstrum analysis, and the heart sounds' features are retrieved. Following that, a support vector machine classifier is trained and evaluated using these extracted features, with an accuracy of 95 percentage, generating a method for characterizing heart sound normal or abnormal for PCG signals. © 2024 IEEE.

关键词： Heart

来源：评论

学校读者我要写书评

暂无评论

Mixed-decomposed convolutional network:A lightweight yet efficient convolutional neural network for ocular disease recognition

引用

CAAI Transactions on Intelligence Technology 2024年第2期9卷 319-332页

作者： Xiaoqing Zhang Xiao Wu Zunjie Xiao Lingxi Hu Zhongxi Qiu Qingyang Sun Risa Higashita Jiang Liu Research Institute of Trustworthy Autonomous Systems and Department of Computer Science and Engineering Southern University of Science and TechnologyShenzhenChina Tomey Corporation NagoyaJapan Guangdong Provincial Key Laboratory of Brain‐inspired Intelligent Computation Department of Computer Science and EngineeringSouthern University of Science and TechnologyShenzhenChina Singapore Eye Research Institute SingaporeSingapore

Eye health has become a global health concern and attracted broad *** the years,researchers have proposed many state-of-the-art convolutional neural networks(CNNs)to assist ophthalmologists in diagnosing ocular diseases efficiently and ***,most existing methods were dedicated to constructing sophisticated CNNs,inevitably ignoring the trade-off between performance and model *** alleviate this paradox,this paper proposes a lightweight yet efficient network architecture,mixeddecomposed convolutional network(MDNet),to recognise ocular *** MDNet,we introduce a novel mixed-decomposed depthwise convolution method,which takes advantage of depthwise convolution and depthwise dilated convolution operations to capture low-resolution and high-resolution patterns by using fewer computations and fewer *** conduct extensive experiments on the clinical anterior segment optical coherence tomography(AS-OCT),LAG,University of California San Diego,and CIFAR-100 *** results show our MDNet achieves a better trade-off between the performance and model complexity than efficient CNNs including MobileNets and ***,our MDNet outperforms MobileNets by 2.5%of accuracy by using 22%fewer parameters and 30%fewer computations on the AS-OCT dataset.

关键词： artificial intelligence deep learning deep neural networks image analysis image classification medical applications medical image processing

来源：评论

学校读者我要写书评

暂无评论

Performance *** Comparative Analysis of Multimodal Bilinear Pooling Fusion Approaches for Deep Learning-Based Visual Arabic-Question Answering systems

引用

computer Modeling in engineering & sciences 2025年第4期143卷 373-411页

作者： Sarah M.Kamel Mai A.Fadel Lamiaa Elrefaei Shimaa I.Hassan Electrical Engineering Department Faculty of Engineering at ShoubraBenha UniversityCairo11629Egypt Computer Science Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer and Systems Engineering Faculty of Engineering and TechnologyBadr University in Cairo(BUC)Cairo11829Egypt Communication Systems Engineering Department Faculty of EngineeringBenha National UniversityObour11846QalyubiaEgypt

Visual question answering(VQA)is a multimodal task,involving a deep understanding of the image scene and the question’s meaning and capturing the relevant correlations between both modalities to infer the appropriate *** this paper,we propose a VQA system intended to answer yes/no questions about real-world images,in *** support a robust VQA system,we work in two directions:(1)Using deep neural networks to semantically represent the given image and question in a fine-grainedmanner,namely ResNet-152 and Gated Recurrent Units(GRU).(2)Studying the role of the utilizedmultimodal bilinear pooling fusion technique in the *** the model complexity and the overall model *** fusion techniques could significantly increase the model complexity,which seriously limits their applicability for VQA *** far,there is no evidence of how efficient these multimodal bilinear pooling fusion techniques are for VQA systems dedicated to yes/no ***,a comparative analysis is conducted between eight bilinear pooling fusion techniques,in terms of their ability to reduce themodel complexity and improve themodel performance in this case of VQA *** indicate that these multimodal bilinear pooling fusion techniques have improved the VQA model’s performance,until reaching the best performance of 89.25%.Further,experiments have proven that the number of answers in the developed VQA system is a critical factor that *** the effectiveness of these multimodal bilinear pooling techniques in achieving their main objective of reducing the model *** Multimodal Local Perception Bilinear Pooling(MLPB)technique has shown the best balance between the model complexity and its performance,for VQA systems designed to answer yes/no questions.

关键词： Arabic-VQA deep learning-based VQA deep multimodal information fusion multimodal representation learning VQA of yes/no questions VQA model complexity VQA model performance performance-complexity trade-off

来源：评论

学校读者我要写书评

暂无评论

A Solution Supporting Secure Transmission of Big Data

引用

Tsinghua science and Technology 2023年第5期28卷 838-848页

作者： Haonan Ling Yan Gao Huibin Wang Ming Chen Institute of Computer Science and Technology Nanjing University of Aeronautics and AstronauticsNanjing 211106China China Electronic Systems Engineering Corporation Beijing 100840China College of Computer and Information Engineering Chuzhou UniversityChuzhou 239000

Traditional Internet protocol networks cannot provide the service of selecting a secure path to transmit various types of data with specific security ***,to solve the“secure path transmission”problem,this paper first proposes a search-transmit model for secure network path transmission,i.e.,to find a multi-attribute optimized path that meets the specific security requirements in the search phase,and then transmit the packets along the optimized path in the transmission ***,we propose a solution to the search-transmit *** idea of the solution is to use the particle swarm optimization algorithm to search for a secure path that meets the multi-attribute requirements and then set the source route on the router to control the packet ***,a prototype system based on network function virtualization is developed to evaluate the feasibility and performance of the proposed *** results show that the proposed solution outperforms existing algorithms in terms of performance.

关键词： network secure path search-transmit model multi-attribute path optimization segment routing network function virtualization

来源：评论

学校读者我要写书评

暂无评论

Efficient Cache Performance Equivalent 2D-Texel to Memory Mapping Identification for Embedded GPUs

引用

IEEE Access 2025年 13卷 95094-95121页

作者： El-Mahdy, Ahmed Elteir, Marwa K. Shata, Kholoud Giza Egypt Egypt–Japan University of Science and Technology Department of Computer Science and Engineering New Borg El-Arab City21934 Egypt Alexandria University Department of Computer and Systems Engineering Alexandria21544 Egypt New Borg El-Arab City Egypt

With the increasing trend of utilizing smart devices, exploiting embedded GPUs becomes plausible to provide for intense computations that approach workstation performance, opening the way for complex, server-grade applications on such devices. Although general-purpose development frameworks exist, they generally abstract implementation details making it difficult for further performance exploitation. One such critical aspect is the texture memory hierarchy design parameters, which are primarily trade secrets. Unfortunately, standard cache hierarchy identification methods are not applicable, due to utilizing logical 2D-texel-to-memory mapping to exploit the 2D locality of access prior to physical cache access. This paper presents, for the first time, a parameterized model capable of describing the underlying multi-dimensional tiling layouts governing this mapping. Although it can be shown that reverse-engineering the model to obtain the exact parameters is an undecidable problem, we strive to obtain a corresponding set of parameters that results in the same cache behavior. In particular, such parameters define the texture order resulting in a linear order that traverses the caches in memory contiguous blocks. This study proposes a reverse-engineering observation method that exploits the contiguity of tiled cached regions and cache set conflicts to efficiently reveal such parameters. The complexity of the method is O(n2), where n is the number of bits in one of the texture buffer dimensions, ensuring practical applicability. Furthermore, optimization of a benchmark workload—via input data and memory access pattern alignment with the inferred multidimensional tiling layout—yields up to a 2.22× speedup. © 2013 IEEE.

关键词： Reverse engineering

来源：评论

学校读者我要写书评

暂无评论

Transfer Learning based Framework of VGG16 to Detect Breast Cancer using Histopathological Images 6

Transfer Learning based Framework of VGG16 to Detect Breast ...

引用

6th Doctoral Symposium on Intelligence Enabled Research, DoSIER 2024

作者： Divya, Zion G. Tripathy, B.K. School of Computer Science and Engineering VIT TN Vellore632014 India School of Computer Science Engineering and Information Systems VIT TN Vellore632014 India

Breast Cancer Detection introduces a prominent confrontation for researchers and clinical experts as it is one of the major public health issues and is weighed as a leading root for cancer correlated deaths among women worldwide. Early diagnosis helps the chances of survival rate which is a crucial part, but standard breast cancer classical techniques rely on operative techniques, open procedures and time-consuming analyses. So, the standard classical techniques pave a way in demanding accurate solutions that are provided with efficient algorithms. This paper addresses these challenges by utilizing automated cancer detection that presents an ensemble deep learning approach by implementing transfer learning for breast cancer detection using histopathological images for classifying Benign and Malignant tissues. Transfer learning uses VGG16 to train the model on large dataset, by reusing the knowledge that has obtained from previous task which is considered as an input to another task thereby improving the performance. In this paper VGG16 architecture is considered as a pretrained model to train on ImageNet. Ensemble strategy is applied as a next step by taking the average of predicted probabilities, out of which the VGG16 model offers overall best accuracy of 98.83%. © 2025 Copyright for this paper by its authors.

关键词： CNN Deep Learning Transfer Learning VGG16

来源：评论

学校读者我要写书评

暂无评论

Distilled Gradual Pruning With Pruned Fine-Tuning

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2024年第8期5卷 4269-4279页

作者： Fontana, Federico Lanzino, Romeo Raoul Marini, Marco Avola, Danilo Cinque, Luigi Scarcello, Francesco Foresti, Gian Luca The Department of Computer Science Sapienza University of Rome Rome00198 Italy The Department of Computer Engineering Modeling Electronics and Systems University of Calabria Rende87030 Italy The Department of Mathematics Computer Science and Physics University of Udine Udine33100 Italy

—Neural networks (NNs) have been driving machine learning progress in recent years, but their larger models present challenges in resource-limited environments. Weight pruning reduces the computational demand, often with performance degradation and long training procedures. This work introduces distilled gradual pruning with pruned fine-tuning (DG2PF), a comprehensive algorithm that iteratively prunes pretrained NNs using knowledge distillation. We employ a magnitude-based unstructured pruning function that selectively removes a specified proportion of unimportant weights from the network. This function also leads to an efficient compression of the model size while minimizing classification accuracy loss. Additionally, we introduce a simulated pruning strategy with the same effects of weight recovery but while maintaining stable convergence. Furthermore, we propose a multistep self-knowledge distillation strategy to effectively transfer the knowledge of the full, unpruned network to the pruned counterpart. We validate the performance of our algorithm through extensive experimentation on diverse benchmark datasets, including CIFAR-10 and ImageNet, as well as a set of model architectures. The results highlight how our algorithm prunes and optimizes pretrained NNs without substantially degrading their classification accuracy while delivering significantly faster and more compact models. Impact Statement—In recent times, NNs have demonstrated remarkable outcomes in various tasks. Some of the most advanced possess billions of trainable parameters, making their training and inference both energy intensive and costly. As a result, the focus on pruning is growing in response to the escalating demand for NNs. However, most current pruning techniques involve training a model from scratch or with a lengthy training process leading to a significant increase in carbon footprint, and some experience a notable drop in performance. In this article, we introduce DG2PF. This unstruct

关键词： computer architecture

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：