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Three-Stage Transfer Learning with AlexNet50 for MRI Image Multi-Class Classification with Optimal Learning Rate

Computer Modeling in Engineering & Sciences 2025年第1期142卷 155-183页

作者： Suganya Athisayamani A.Robert Singh Gyanendra Prasad Joshi Woong Cho School of Computing Sastra Deemed to be UniversityThanjavur613401India Department of Computational Intelligence SRM Institute of Science and TechnologyKattankulathur603203India Department of ai and Software Engineering Kangwon National UniversitySamcheok25913Republic of Korea Department of Electronics Information and Communication EngineeringKangwon National UniversitySamcheok25913Republic of Korea

In radiology,magnetic resonance imaging(MRI)is an essential diagnostic tool that provides detailed images of a patient’s anatomical and physiological *** is particularly effective for detecting soft tissue ***,radiologists manually interpret these images,which can be labor-intensive and time-consuming due to the vast amount of *** address this challenge,machine learning,and deep learning approaches can be utilized to improve the accuracy and efficiency of anomaly detection in MRI *** manuscript presents the use of the Deep AlexNet50 model for MRI classification with discriminative learning *** are three stages for learning;in the first stage,the whole dataset is used to learn the *** the second stage,some layers of AlexNet50 are frozen with an augmented dataset,and in the third stage,AlexNet50 with an augmented dataset with the augmented *** method used three publicly available MRI classification datasets:Harvard whole brain atlas(HWBA-dataset),the School of Biomedical Engineering of Southern Medical University(SMU-dataset),and The National Institute of Neuroscience and Hospitals brain MRI dataset(NINS-dataset)for *** hyperparameter optimizers like Adam,stochastic gradient descent(SGD),Root mean square propagation(RMS prop),Adamax,and AdamW have been used to compare the performance of the learning ***-dataset registers maximum classification *** evaluated the performance of the proposed classification model using several quantitative metrics,achieving an average accuracy of 98%.

关键词： MRI tumors classification AlexNet50 transfer learning hyperparameter tuning optimizer

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Recent Progresses in Deep Learning Based Acoustic Models

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IEEE/CAA Journal of Automatica Sinica 2017年第3期4卷 396-409页

作者： Dong Yu Jinyu Li Tencent ai Lab Tencent Microsoft ai and Research Microsoft

In this paper,we summarize recent progresses made in deep learning based acoustic models and the motivation and insights behind the surveyed *** first discuss models such as recurrent neural networks(RNNs) and convolutional neural networks(CNNs) that can effectively exploit variablelength contextual information,and their various combination with other *** then describe models that are optimized end-to-end and emphasize on feature representations learned jointly with the rest of the system,the connectionist temporal classification(CTC) criterion,and the attention-based sequenceto-sequence translation *** further illustrate robustness issues in speech recognition systems,and discuss acoustic model adaptation,speech enhancement and separation,and robust training *** also cover modeling techniques that lead to more efficient decoding and discuss possible future directions in acoustic model research.

关键词： Attention model convolutional neural network(CNN) connectionist temporal classification(CTC) deep learning(DL) long short-term memory(LSTM) permutation invariant training speech adaptation speech processing speech recognition speech separation

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Enhancing Solar Energy Production Forecasting Using Advanced Machine Learning and Deep Learning Techniques: A Comprehensive Study on the Impact of Meteorological Data

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Computers, Materials & Continua 2024年第11期81卷 3147-3163页

作者： Nataliya Shakhovska Mykola Medykovskyi Oleksandr Gurbych Mykhailo Mamchur Mykhailo Melnyk Instutute of Computer Science and Information Technologies Lviv Polytechnic National UniversityLviv79013Ukraine Department of Applied Mathematics University of Agriculture in KrakowKrakow31-120Poland blackthorn ai Ltd.LondonEC1V 2NXUK

The increasing adoption of solar photovoltaic systems necessitates accurate forecasting of solar energy production to enhance grid stability,reliability,and economic *** study explores advanced machine learning(ML)and deep learning(DL)techniques for predicting solar energy generation,emphasizing the significant impact of meteorological data.A comprehensive dataset,encompassing detailed weather conditions and solar energy metrics,was collected and preprocessed to improve model *** models were developed and trained with different preprocessing ***,three datasets were prepared.A novel hour-based prediction wrapper was introduced,utilizing external sunrise and sunset data to restrict predictions to daylight hours,thereby enhancing model performance.A cascaded stacking model incorporating association rules,weak predictors,and a modified stacking aggregation procedure was proposed,demonstrating enhanced generalization and reduced prediction *** indicated that models trained on raw data generally performed better than those on stripped *** Long Short-Term Memory(LSTM)with Inception layers’model was the most effective,achieving significant performance improvements through feature selection,data preprocessing,and innovative modeling *** study underscores the potential to combine detailed meteorological data with advanced ML and DL methods to improve the accuracy of solar energy forecasting,thereby optimizing energy management and planning.

关键词： Solar energy prediction machine learning deep learning

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UNIFORM DECAY IN WEAKLY DISSIPATIVE TIMOSHENKO SYSTEM WITH INTERNAL DISTRIBUTED DELAY FEEDBACKS

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Acta Mathematica Scientia 2016年第3期36卷 815-830页

作者： Tijani A. APALARA Department of Mathematics University of Hafr AI-Batin (UoHB) Hafr AI-Batin 31991 Saudi Arabia

In this paper we consider one-dimensional Timoshenko system with linear fric- tional damping and a distributed delay acting on the displacement equation. Under suitable assumptions on the weight of the delay and the wave speeds, we establish the well-posedness of the system and show that the dissipation through the frictional damping is strong enough to uniformly stabilize the system even in the presence of delay.

关键词： Timoshenko system well-posedness uniform stability distributed delay

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Intent-Slot Correlation Modeling for Joint Intent Prediction and Slot Filling

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Journal of Computer Science & Technology 2022年第2期37卷 309-319页

作者： Jun-Feng Fan Mei-Ling Wang Chang-Liang Li Zi-Qiang Zhu Lu Mao ai Laboratory KingSoft CorporationBeijing 100190China

Slot filling and intent prediction are basic tasks in capturing semantic frame of human *** and intent have strong correlation for semantic frame *** each utterance,a specific intent type is generally determined with the indication information of words having slot tags(called as slot words),and in reverse the intent type decides that words of certain categories should be used to fill as ***,the Intent-Slot correlation is rarely modeled explicitly in existing studies,and hence may be not fully *** this paper,we model Intent-Slot correlation explicitly and propose a new framework for joint intent prediction and slot ***,we explore the effects of slot words on intent by differentiating them from the other words,and we recognize slot words by solving a sequence labeling task with the bi-directional long short-term memory(BiLSTM)***,slot recognition information is introduced into attention-based intent prediction and slot filling to improve semantic *** addition,we integrate the Slot-Gated mechanism into slot filling to model dependency of slots on ***,we obtain slot recognition,intent prediction and slot filling by training with joint *** results on the benchmark air-line Travel Information System(ATIS)and Snips datasets show that our Intent-Slot correlation model achieves state-of-the-art semantic frame performance with a lightweight structure.

关键词： spoken language understanding slot filling intent prediction Intent-Slot correlation slot recognition

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Classification of Human Protein in Multiple Cells Microscopy Images Using CNN

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Computers, Materials & Continua 2023年第8期76卷 1763-1780页

作者： Lina Al-joudi Muhammad Arif Department of Computer Science ai(CS-ai) Umm Al Qura University(UQU)Makkah24231Saudi Arabia

The subcellular localization of human proteins is vital for understanding the structure of human *** play a significant role within human cells,as many different groups of proteins are located in a specific location to perform a particular *** these functions will help in discoveringmany diseases and developing their *** importance of imaging analysis techniques,specifically in proteomics research,is becoming more *** recent advances in deep learning techniques for analyzing microscopy images,classification models have faced critical challenges in achieving high *** protein subcellular images have a significant class *** use oversampling and under sampling techniques in this research to overcome this *** have used a Convolutional Neural Network(CNN)model called GapNet-PL for the multi-label classification task on the Human Protein Atlas Classification(HPA)*** have found that the ParametricRectified LinearUnit(PreLU)activation function is better than the Scaled Exponential LinearUnit(SeLU)activation function in the GapNet-PL model in most classification *** results showed that the GapNet-PL model with the PReLU activation function achieved an area under the ROC curve(AUC)equal to 0.896,an F1 score of 0.541,and a recall of 0.473.

关键词： CNN protein PReLU SeLU microscopy images subcellular localization multi-cells

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Tuning of Multi-stability Profile and Transition Sequence of Stacked Miura-Origami Metamaterials

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Acta Mechanica Solida Sinica 2023年第4期36卷 554-568页

作者： Haiping Wu Hongbin Fang Institute of ai and Robotics Fudan UniversityShanghai 200433China MOE Engineering Research Center of ai and Robotics Fudan UniversityShanghai 200433China Shanghai Engineering Research Center of ai and Robotics Fudan UniversityShanghai 200433China

Multi-stable origami structures and metamaterials possess unique advantages and could exhibit multiple stable three-dimensional configurations,which have attracted widespread research interest and held promise for applications in many *** a great deal of attention has been paid to the design and application of multi-stable origami structures,less knowledge is available about the transition sequence among different stable configurations,especially in terms of the fundamental mechanism and the tuning *** fill this gap,with the multi-stable dual-cell stacked Miura-ori chain as a platform,this paper explores the rules that govern the configuration transition and proposes effective methods for tuning the transition ***,by correlating the energy evolution,the transition paths,and the associated force-displace-ment profiles,we find that the critical extension/compression forces of the component cells play a critical role in governing the transition ***,we summarize the rules for predicting the transition sequence:the component cell that first reaches the critical force during quasi-static extension or compression will be the first to undergo a configuration *** on these findings,two methods,i.e.,a design method based on crease-stiffness assignment and an online method based on internal pressure regulation,are proposed to tune the stability profile and the transition sequence of the multi-stable origami *** crease-stiffness design approach,although effective,cannot be employed for online tuning once the prototype has been *** pressure-based approach,on the other hand,has been shown experimentally to be effective in adjusting the constitutive force-displacement profiles of the component cells and,in turn,tuning the transition sequence according to the summarized *** results of this study will advance the state of the art of origami mechanics and promote the engineering applications of mu

关键词： Origami metamaterial Bi-stability Origami mechanics Pneumatic origami Snap-through transition

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Decreased levels of phosphorylated synuclein in plasma are correlated with poststroke cognitive impairment

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Neural Regeneration Research 2025年第9期20卷 2598-2610页

作者： Yi Wang Yuning Li Yakun Gu Wei Ma Yuying Guan Mengyuan Guo Qianqian Shao Xunming Ji Jia Liu Department of Clinical Laboratory Beijing Bo’ai HospitalChina Rehabilitation Research CenterCapital Medical UniversityBeijingChina Beijing Institute of Brain Disorders Laboratory of Brain DisordersMinistry of Science and TechnologyCollaborative Innovation Center for Brain DisordersBeijing Advanced Innovation Center for Big Data-based Precision MedicineCapital Medical UniversityBeijingChina Department of Neurosurgery Xuanwu HospitalCapital Medical UniversityBeijingChina

Poststro ke cognitive impairment is a major secondary effect of ischemic stroke in many patients;however,few options are available for the early diagnosis and treatment of this *** aims of this study were to(1)determine the specific relationship between hypoxic andα-synuclein during the occur of poststroke cognitive impairment and(2)assess whether the serum phosphorylatedα-synuclein level can be used as a biomarker for poststro ke cognitive *** found that the phosphorylatedα-synuclein level was significantly increased and showed pathological aggregation around the cerebral infa rct area in a mouse model of ischemic *** addition,neuronalα-synuclein phosphorylation and aggregation were observed in the brain tissue of mice subjected to chronic hypoxia,suggesting that hypoxia is the underlying cause ofα-synuclein-mediated pathology in the brains of mice with ischemic *** phosphorylatedα-synuclein levels in patients with ischemic stroke were significantly lower than those in healt hy subjects,and were positively correlated with cognition levels in patients with ischemic ***,a decrease in serum high-density lipoprotein levels in stroke patie nts was significantly correlated with a decrease in phosphorylatedα-synuclein *** ischemic stroke mice did not show significant cognitive impairment or disrupted lipid metabolism 14 days after injury,some of them exhibited decreased cognitive function and reduced phosphorylatedα-synuclein *** together,our results suggest that serum phosphorylatedα-synuclein is a potential biomarker for poststroke cognitive impairment.

关键词： biomarker high-density lipoprotein ischemic stroke phosphorylatedα-synuclein poststroke cognitive impairment

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Environmental contact modeling for the earthworm-like robot via the novel elementary mechanical network

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Science China(Technological Sciences) 2022年第6期65卷 1366-1382页

作者： HE KunPeng ZHANG XiaoXu Institute of ai and Robotics Fudan UniversityShanghai 200433China Shanghai Engineering Research Center of ai&Robotics Fudan UniversityShanghai 200433China MOE Engineering Research Center of ai&Robotics Fudan UniversityShanghai 200433China

The earthworm-like robot is designed for prospective applications such as disaster rescue and pipeline detection in natural ***,current studies on the interaction modeling between the earthworm-like robot and the environment only consider rigid *** simplification limits the reliability of dynamic analysis and locomotion optimization on soft surfaces,such as ***,developing a method for refined contact modeling for the earthworm-like robot and describing the contact effect induced by the soft environmental medium is *** this end,this paper proposes a new modeling architecture called the elementary mechanical network(EMN).EMN is constructed as fractal structures for the convenience of network ***,elementary mechanical elements,such as the damper,spring,and slider,are parallelly connected to constitute a basic ***,the modules are serially linked to create a ***,the groups are parallelly assembled to form the *** is also proven to be equivalent to recurrent neural networks in specific ***,EMN inherits the advantages of physical interpretability from mechanical elements and universal approximability from conventional *** addition,particle swarm optimization and Boolean operation are employed for network weight training and topological *** examples show that using EMNs with identical initial structures can accurately describe diverse empirical models in the minimum *** is applied for contact modeling for the earthworm-like locomotion robot in the dry sand based on such *** experiment measures the normal and tangential ground reaction forces with different sinkage depths and locomotion *** results reveal a common law that the contact effect in the dry sand is similar to Coulomb *** proposed EMN does not require prior system knowledge and promises a minimal physical representation,thus encouraging a succes

关键词： bioinspired locomotion robot data-driven modeling reconfigurable network soft terrain system identification

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An Intelligent Admission Control Scheme for Dynamic Slice Handover Policy in 5G Network Slicing

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Computers, Materials & Continua 2023年第5期75卷 4611-4631页

作者： Ratih Hikmah Puspita Jehad Ali Byeong-hee Roh Department of ai Convergence Network Ajou UniversitySuwon16499Korea Department of Computer Engineering and Department of AI Convergence NetworkAjou UniversitySuwon16499Korea

5G use cases,for example enhanced mobile broadband(eMBB),massive machine-type communications(mMTC),and an ultra-reliable low latency communication(URLLC),need a network architecture capable of sustaining stringent latency and bandwidth requirements;thus,it should be extremely flexible and *** enables service providers to develop various network slice *** users travel from one coverage region to another area,the callmust be routed to a slice thatmeets the same or different *** research aims to develop and evaluate an algorithm to make handover decisions appearing in 5G sliced *** of thumb which indicates the accuracy regarding the training data classification schemes within machine learning should be considered for validation and selection of the appropriate machine learning ***,this study discusses the network model’s design and implementation of self-optimization Fuzzy Qlearning of the decision-making algorithm for slice *** algorithm’s performance is assessed by means of connection-level metrics considering the Quality of Service(QoS),specifically the probability of the new call to be blocked and the probability of a handoff call being ***,within the network model,the call admission control(AC)method is modeled by leveraging supervised learning algorithm as prior knowledge of additional ***,to mitigate high complexity,the integration of fuzzy logic as well as Fuzzy Q-Learning is used to discretize state and the corresponding action *** results generated from our proposal surpass the traditional methods without the use of supervised learning and fuzzy-Q learning.

关键词： 5g network slice fuzzy q-Learning slice handover

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