In this paper, the superiority of Ge/Ge0.98Sn0.02asymmetrical supper lattice structure based vertically doped nano-scale pin photo-sensor under operating wavelength of 1200 nm to 2200 nm is reported. The aut...
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Hypernym detection and discovery are fundamental tasks in natural language *** former task aims to identify all possible hypernyms of a given hyponym term,whereas the latter attempts to determine whether the given two...
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Hypernym detection and discovery are fundamental tasks in natural language *** former task aims to identify all possible hypernyms of a given hyponym term,whereas the latter attempts to determine whether the given two terms hold a hypernymy relation or *** research on hypernym detection and discovery tasks projects a term into various semantic spaces with single mapping *** their success,these methods may not be adequate in capturing complex semantic relevance between hyponym/hypernymy pairs in two ***,they may fall short in modeling the hierarchical structure in the hypernymy relations,which may help them learn better term ***,the polysemy phenomenon that hypernyms may express distinct senses is *** this paper,we propose a Multi-Projection Recurrent model(MPR)to simultaneously capture the hierarchical relationships between terms and deal with diverse senses caused by the polysemy ***,we build a multi-projection mapping block to deal with the polysemy phenomenon,which learns various word senses by multiple ***,we adopt a hierarchy-aware recurrent block with the recurrent operation followed by a multi-hop aggregation module to capture the hierarchical structure of hypernym *** on 11 benchmark datasets in various task settings illustrate that our multi-projection recurrent model outperforms the *** experimental analysis and case study demonstrate that our multi-projection module and the recurrent structure are effective for hypernym detection and discovery tasks.
Internet of Thing based healthcare ecosystems are extremely popular as they are built on a network of devices that are connected directly to one another in order to collect, share, and use important contextual informa...
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Context:Decentralized autonomous organizations are a new form of smart contract-based *** autonomous organization platforms,which support the creation of such organizations,are becoming increasingly popular,such as Ar...
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Context:Decentralized autonomous organizations are a new form of smart contract-based *** autonomous organization platforms,which support the creation of such organizations,are becoming increasingly popular,such as Aragon and *** the best fitting platform is challenging for organizations,as a significant number of decision criteria,such as popularity,developer availability,governance issues and consistent documentation of such platforms,should be ***,decision-makers at the organizations are not experts in every domain,so they must continuously acquire volatile knowledge regarding such ***:Supporting decision-makers in selecting the right decentralized autonomous organization platforms by designing an effective decision model is the main objective of this *** aim to provide more insight into their selection process and reduce time and effort significantly by designing a decision ***:This study presents a decision model for the decentralized autonomous organization platform selection *** decision model captures knowledge regarding such platforms and concepts *** model is based on an existing theoretical framework that assists software engineers with a set of multi-criteria decision-making problems in software ***:We conducted three industry case studies in the context of three decentralized autonomous organizations to evaluate the effectiveness and efficiency of the decision model in assisting *** case study participants declared that the decision model provides significantly more insight into their selection process and reduces time and ***:We observe in the empirical evidence from the case studies that decision-makers can make more rational,efficient,and effective decisions with the decision ***,the reusable form of the captured knowledge regarding decentralized autonomous organization platforms can be
In recent years, with the aging population and the increasing incidence of natural cavity diseases and cancer tumors, the demand for minimally invasive surgery has risen. This, in turn, requires robotic arms with grea...
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In an era dominated by information dissemination through various channels like newspapers,social media,radio,and television,the surge in content production,especially on social platforms,has amplified the challenge of...
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In an era dominated by information dissemination through various channels like newspapers,social media,radio,and television,the surge in content production,especially on social platforms,has amplified the challenge of distinguishing between truthful and deceptive *** news,a prevalent issue,particularly on social media,complicates the assessment of news *** pervasive spread of fake news not only misleads the public but also erodes trust in legitimate news sources,creating confusion and polarizing *** the volume of information grows,individuals increasingly struggle to discern credible content from false narratives,leading to widespread misinformation and potentially harmful *** numerous methodologies proposed for fake news detection,including knowledge-based,language-based,and machine-learning approaches,their efficacy often diminishes when confronted with high-dimensional datasets and data riddled with noise or *** study addresses this challenge by evaluating the synergistic benefits of combining feature extraction and feature selection techniques in fake news *** employ multiple feature extraction methods,including Count Vectorizer,Bag of Words,Global Vectors for Word Representation(GloVe),Word to Vector(Word2Vec),and Term Frequency-Inverse Document Frequency(TF-IDF),alongside feature selection techniques such as Information Gain,Chi-Square,Principal Component Analysis(PCA),and Document *** comprehensive approach enhances the model’s ability to identify and analyze relevant features,leading to more accurate and effective fake news *** findings highlight the importance of a multi-faceted approach,offering a significant improvement in model accuracy and ***,the study emphasizes the adaptability of the proposed ensemble model across diverse datasets,reinforcing its potential for broader application in real-world *** introduce a pioneering ensemble
Concrete is a vital component in modern construction, prized for its strength, durability, and versatility. Accurately determining the quantities of concrete components is crucial in civil engineering applications to ...
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The seamless integration of intelligent Internet of Things devices with conventional wireless sensor networks has revolutionized data communication for different applications,such as remote health monitoring,industria...
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The seamless integration of intelligent Internet of Things devices with conventional wireless sensor networks has revolutionized data communication for different applications,such as remote health monitoring,industrial monitoring,transportation,and smart *** and reliable data routing is one of the major challenges in the Internet of Things network due to the heterogeneity of *** paper presents a traffic-aware,cluster-based,and energy-efficient routing protocol that employs traffic-aware and cluster-based techniques to improve the data delivery in such *** proposed protocol divides the network into clusters where optimal cluster heads are selected among super and normal nodes based on their residual *** protocol considers multi-criteria attributes,i.e.,energy,traffic load,and distance parameters to select the next hop for data delivery towards the base *** performance of the proposed protocol is evaluated through the network simulator *** different traffic rates,number of nodes,and different packet sizes,the proposed protocol outperformed LoRaWAN in terms of end-to-end packet delivery ratio,energy consumption,end-to-end delay,and network *** 100 nodes,the proposed protocol achieved a 13%improvement in packet delivery ratio,10 ms improvement in delay,and 10 mJ improvement in average energy consumption over LoRaWAN.
The ability to accurately predict urban traffic flows is crucial for optimising city ***,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to understand complex mo...
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The ability to accurately predict urban traffic flows is crucial for optimising city ***,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to understand complex mobility *** learning techniques,such as graph neural networks(GNNs),are popular for their ability to capture spatio-temporal ***,these models often become overly complex due to the large number of hyper-parameters *** this study,we introduce Dynamic Multi-Graph Spatial-Temporal Graph Neural Ordinary Differential Equation Networks(DMST-GNODE),a framework based on ordinary differential equations(ODEs)that autonomously discovers effective spatial-temporal graph neural network(STGNN)architectures for traffic prediction *** comparative analysis of DMST-GNODE and baseline models indicates that DMST-GNODE model demonstrates superior performance across multiple datasets,consistently achieving the lowest Root Mean Square Error(RMSE)and Mean Absolute Error(MAE)values,alongside the highest *** the BKK(Bangkok)dataset,it outperformed other models with an RMSE of 3.3165 and an accuracy of 0.9367 for a 20-min interval,maintaining this trend across 40 and 60 ***,on the PeMS08 dataset,DMST-GNODE achieved the best performance with an RMSE of 19.4863 and an accuracy of 0.9377 at 20 min,demonstrating its effectiveness over longer *** Los_Loop dataset results further emphasise this model’s advantage,with an RMSE of 3.3422 and an accuracy of 0.7643 at 20 min,consistently maintaining superiority across all time *** numerical highlights indicate that DMST-GNODE not only outperforms baseline models but also achieves higher accuracy and lower errors across different time intervals and datasets.
With the popularity of the Internet of Vehicles(IoV),a large amount of data is being generated every *** to securely share data between the IoV operator and various value-added service providers becomes one of the cri...
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With the popularity of the Internet of Vehicles(IoV),a large amount of data is being generated every *** to securely share data between the IoV operator and various value-added service providers becomes one of the critical *** to its flexible and efficient fine-grained access control feature,Ciphertext-Policy Attribute-Based Encryption(CP-ABE)is suitable for data sharing in ***,there are many flaws in most existing CP-ABE schemes,such as attribute privacy leakage and key *** paper proposes a Traceable and Revocable CP-ABE-based Data Sharing with Partially hidden policy for IoV(TRE-DSP).A partially hidden access structure is adopted to hide sensitive user attribute values,and attribute categories are sent along with the ciphertext to effectively avoid privacy *** addition,key tracking and malicious user revocation are introduced with broadcast encryption to prevent key *** the main computation task is outsourced to the cloud,the burden of the user side is relatively *** of security and performance demonstrates that TRE-DSP is more secure and practical for data sharing in IoV.
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