Multimodal Sentiment Analysis(SA)is gaining popularity due to its broad application *** existing studies have focused on the SA of single modalities,such as texts or photos,posing challenges in effectively handling so...
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Multimodal Sentiment Analysis(SA)is gaining popularity due to its broad application *** existing studies have focused on the SA of single modalities,such as texts or photos,posing challenges in effectively handling social media data with multiple ***,most multimodal research has concentrated on merely combining the two modalities rather than exploring their complex correlations,leading to unsatisfactory sentiment classification *** by this,we propose a new visualtextual sentiment classification model named Multi-Model Fusion(MMF),which uses a mixed fusion framework for SA to effectively capture the essential information and the intrinsic relationship between the visual and textual *** proposed model comprises three deep neural *** different neural networks are proposed to extract the most emotionally relevant aspects of image and text ***,more discriminative features are gathered for accurate sentiment ***,a multichannel joint fusion modelwith a self-attention technique is proposed to exploit the intrinsic correlation between visual and textual characteristics and obtain emotionally rich information for joint sentiment ***,the results of the three classifiers are integrated using a decision fusion scheme to improve the robustness and generalizability of the proposed *** interpretable visual-textual sentiment classification model is further developed using the Local Interpretable Model-agnostic Explanation model(LIME)to ensure the model’s explainability and *** proposed MMF model has been tested on four real-world sentiment datasets,achieving(99.78%)accuracy on Binary_Getty(BG),(99.12%)on Binary_iStock(BIS),(95.70%)on Twitter,and(79.06%)on the Multi-View Sentiment Analysis(MVSA)*** results demonstrate the superior performance of our MMF model compared to single-model approaches and current state-of-the-art techniques based on model evaluation cr
Deep learning methods, which form the backbone of neural network architectures, have not only demonstrated exceptional capabilities in classifying data but also in reducing false predictions when handling vast dataset...
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Deep learning technology has extensive application in the classification and recognition of medical images. However, several challenges persist in such application, such as the need for acquiring large-scale labeled d...
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This paper investigates how distributed energy resources investment capacities impact the carbon footprint of a renewable energy community. The investigation is conducted through the formulation of an optimisation pro...
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This paper presents a dual-band implantable antenna with coaxial probe feeding for wireless biotelemetry applications. The antenna features spiral patches, resulting in a compact size of 27 × 14 × 1.6 mm3. I...
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Hydrocephalus is characterized by the accumulation of excess cerebrospinal fluid(CSF)in the cranium due to an imbalance between production and absorption of *** standard treatment involves the implantation of a shunt ...
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Hydrocephalus is characterized by the accumulation of excess cerebrospinal fluid(CSF)in the cranium due to an imbalance between production and absorption of *** standard treatment involves the implantation of a shunt to divert excess CSF into the peritoneal cavity,but these shunts exhibit high failure rates over *** pursuit of improved reliability and performance,this study proposes a miniaturized valve designed to mimic the natural one-way valve function of the arachnoid granulations and thereby replace the shunts.A benchtop testing setup was employed to characterize the behavior of the fabricated ***,an animal study was conducted to assess the valve’s in vivo *** involved the injection of saline into the lateral ventricle to elevate intracranial pressure(ICP),followed by the drainage of the saline through the valve inserted into the cisterna magna(CM)to reduce *** prototype features a silicone duckbill valve design combined with a silicone tube as an *** benchtop testing,the valve exhibited unidirectional flow with negligible reverse leakage,revealing that critical parameters such as the width of the fluid channel(W)and bill length(L)could be controlled to optimize valve ***,the valve configuration with W=0.8mm and L<0.5mm achieved the lowest cracking pressure(2.22±0.07 mmHg)and outflow resistance(22.00±0.70 mmHg/mL/min)within the low cracking pressure range of conventional *** observations of the in vivo test demonstrated that when untreated states,pressure differences from baseline to peak exceeded 20 mmHg due to the absence of drainage,resulting in sustained pressure ***,upon treating states by removing the clamp,pressure differences from baseline to peak remained below 5 mmHg,indicating effective drainage of injected saline through the *** promising results highlight the potential of the miniaturized duckbill valve as an alternative for ICP management in hydr
This paper proposes an empirical wavelet transform(EWT)based method for identification and analysis of sub-synchronous oscillation(SSO)modes in the power system using phasor measurement unit(PMU)*** phasors from PMUs ...
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This paper proposes an empirical wavelet transform(EWT)based method for identification and analysis of sub-synchronous oscillation(SSO)modes in the power system using phasor measurement unit(PMU)*** phasors from PMUs are preprocessed to check for the presence of *** the presence is established,the signal is decomposed using EWT and the parameters of the mono-components are estimated through Yoshida *** superiority of the proposed method is tested using test signals with known parameters and simulated using actual SSO signals from the Hami Power Grid in Northwest *** show the effectiveness of the proposed EWT-Yoshida method in detecting the SSO and estimating its parameters.
Wind power plants(WPPs)are increasingly mandated to provide temporary frequency support to power systems during contingencies involving significant power ***,the frequency support capabilities of WPPs under derated op...
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Wind power plants(WPPs)are increasingly mandated to provide temporary frequency support to power systems during contingencies involving significant power ***,the frequency support capabilities of WPPs under derated operations remain insufficiently investigated,highlighting the potential for further improvement of the frequency *** paper proposes a bi-level optimized temporary frequency support(OTFS)strategy for a *** implementation of the OTFS strategy is collaboratively accomplished by individual wind turbine(WT)controllers and the central WPP ***,to exploit the frequency support capability of WTs,the stable operational region of WTs is expanded by developing a novel dynamic power control approach in WT *** approach synergizes the WTs'temporary frequency support with the secondary frequency control of synchronous generators,enabling WTs to release more kinetic energy without causing a secondary frequency ***,a model predictive control strategy is developed for the WPP *** strategy ensures that multiple WTs operating within the expanded stable region are coordinated to minimize the magnitude of the frequency drop through efficient kinetic energy ***,comprehensive case studies are conducted on a real-time simulation platform to validate the effectiveness of the proposed strategy.
Load balancing and scheduling are essential components of cloud computing that aim to optimize resource allocation and utilization. In a cloud environment, multiple virtual machines and applications compete for shared...
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Healthcare is a fundamental part of every individual’s *** healthcare industry is developing very rapidly with the help of advanced *** researchers are trying to build cloud-based healthcare applications that can be ...
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Healthcare is a fundamental part of every individual’s *** healthcare industry is developing very rapidly with the help of advanced *** researchers are trying to build cloud-based healthcare applications that can be accessed by healthcare professionals from their premises,as well as by patients from their mobile devices through communication *** systems promote reliable and remote interactions between patients and healthcare ***,there are several limitations to these innovative cloud computing-based systems,namely network availability,latency,battery life and resource *** propose a hybrid mobile cloud computing(HMCC)architecture to address these ***,we also evaluate the performance of heuristic and dynamic machine learning based task scheduling and load balancing algorithms on our proposed *** compare them,to identify the strengths and weaknesses of each algorithm;and provide their comparative results,to show latency and energy consumption *** issues for cloudbased healthcare systems are discussed in detail.
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