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Attaining synergetic equilibrium of electrical conductivity and tensile strength in GQDs@GN/Cu composites through multi-scale intragranular and intergranular reinforcements

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Rare Metals 2024年第1期43卷 366-379页

作者： Shuang-Yin Zhang Liang Liu Rui Bao Jian-Hong Yi Sheng-Da Guo Faculty of Materials Science and Engineering Kunming University of Science and TechnologyKunming 650093China Key Laboratory of Advanced Materials of Yunnan Province Kunming University of Science and TechnologyKunming 650093China Faculty of Materials Metallurgy and Chemistry Jiangxi University of Science and TechnologyGanzhou 341000China

The configuration and quality of reinforcements, as well as the robustness of interfacial bonding,holding a critical significance in determining the concurrence between electrical conductivity and mechanical strength in metal matrix composites. In this study, citric acid was employed as the precursor for synthesizing multiscale carbon nanomaterials(graphene quantum dots and graphene, abbreviated as GQDs and GN). The GQDs@GN/Cu composites were fabricated through a segmented ball milling process in conjunction with subsequent spark plasma sintering(SPS). The intragranular GQDs and intergranular GQDs@GN had synergistically reinforced Cu composites through Orowan strengthening, load transfer strengthening and refinement strengthening. Furthermore,the robust interface bonding between GQDs@GN and Cu effectively mitigated interfacial impedance stemming from electron-boundary scattering. The yield strength and ultimate tensile strength of the GQDs@GN/Cu composites were recorded as 270 and 314 MPa, respectively, representing an improvement of 92 and 28% over pure Cu, while maintaining electrical conductivity at a level comparable to that of pure Cu. This study advances the understanding of the possibility of realizing a synergistic compatibility between electrical conductivity and mechanical strength in Cu composites.

关键词： Cu matrix composites Interface bonding Mechanical property Graphene quantum dots(GQDs) Electrical conductivity

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Evaluation of the Relative Tectonic Activity from the Faults in the Gengma-Lancang-Menghai Seismic Belt(Southwestern China)

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Journal of Earth science 2024年第1期35卷 131-143页

作者： Dan Wang Youpu Dong Zhipeng Xi Dongyue Zhang Jiaxin Duan Huayu Yu Liang Yu Faculty of Land Resource Engineering Kunming University of Science and TechnologyKunming 650093China

The Gengma-Lancang-Menghai seismic belt,the southernmost part of the North-South seismic belt,is controlled by four active faults:the Nantinghe fault(NTHF),the Sanjianshan fault(SJSF),the Hanmuba-Lancang fault(HMB-LCF),and the Heihe fault(HHF),from northwest to ***,the tectonic activity of the faults in the Gengma-Lancang-Menghai seismic belt has not been fully studied *** the present work,we conducted tectonic geomorphic indices to analyze the relative tectonic activity along the faults in the seismic belt based on the digital elevation *** interpreted asymmetric factor,index of drainage basin shape,hypsometric integral,normalized streamlength gradient,valley floor-to-width to height ratio,and longitudinal profiles to show that the relative tectonic activity is higher in the north and lower in the south,and is strong in the region from Shanjia to Huimin in the center of the seismic belt.

关键词： Gengma-Lancang-Menghai seismic belt southeastern Tibetan Plateau geomorphic indices longitudinal profile

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LMR-IPGN: An Effective Model for automatic summarization of Chinese long text

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Multimedia Systems 2025年第3期31卷 1-20页

作者： Shao, Dangguo Huang, Gaoan Ma, Lei Wu, Yuxin Tang, Kaiqiang Yi, Sanli Li, Jingtao Duan, Nuoyun Pu, Chunyun Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming China

Chinese Text Summarization has been a hot topic in last few years. But it faces two inherent constraints compared to other languages: (1) The lack of explicit morphological changes in Chinese combined with long-distance dependency issues leads to semantic understanding deviations;(2) Flexible character combinations create ambiguous structures that interfere with capturing global semantic features, resulting in generated summary with semantic confusion and fabricated content. Additionally, cross-entropy based learning methods do not always yield optimal evaluation results. To address these challenges, we propose a hybrid model(LMR-IPGN) that integrates multiple types of attention based on encoder-decoder model and policy learning. First, during the preprocessing stage, Chinese lexical resources and word segmentation tools are employed to process source documents, reducing redundancy through synonym substitution while resolving Chinese word segmentation ambiguities. Specifically, the hierarchical level intra multi-head attention mechanism enhances key information extraction by allocating more attention to low-frequency yet critical words, thereby mitigating excessive focus on high-frequency but less significant terms or phrases. Secondly, the model integrates temporal attention with the pointer mechanism to record attention distributions of historically generated words, penalizing repetitively attended regions to avoid information redundancy. Finally, a hybrid reward signal combining cross-entropy and ROUGE-N is introduced during the decoding stage, optimizing generation quality through a mixed learning strategy. Experimental results on the NLPCC2017 dataset and CSL dataset show that our proposed model significantly outperforms other baselines in terms of Rouge-N scores. We also perform human evaluation to demonstrate the effectiveness of our model by evaluating the generated summary using several subjective metrics. © The Author(s), under exclusive licence to Springe

关键词： Redundancy

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CIRCULAR ECONOMY INDICATORS APPLIED TO WASTEWATER TREATMENT PROCESS

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical engineering and Computer science 2025年第1期87卷 401-414页

作者： Ion, Nicolae Safta, Carmen-Anca Faculty of Energy Engineering National University of Science and Technology POLITEHNICA Bucharest Romania

The present paper presents the results obtained for the evaluation of the circularity index using a methodology existing in the literature. The evaluation methodology of the technological process in the conceptual circular economy is based on the 3R principle (Reuse, Reduce, and Recycle) and it uses the life cycle analysis-LCA, and material flow analysis-MFA. The circularity indices are calculated for a wastewater treatment plant WWTP (Constanta Nord WWTP). Four possible scenarios were considered in which the economic circularity concept was hypothetical applied, for different materials and energy in the technological circuit of the sewage treatment plant. The four scenarios considered are in accordance with hypothetical situations of the technological development of the wastewater treatment plant. Thus, "Scenario 4" in which: the technology used would allow the drying of the sewage sludge and it’s recycling, the fermentation of the sludge and the obtaining of biogas, the use of energy from renewable energy sources and the reuse of purified water in human activities, the circularity index is 88%. Compared to "Scenario 1" with circularity indicators quite close to those of "Scenario 4", but without a tertiary water treatment technology at the exit from the treatment plant for drinking water, the circularity index is increased in "Scenario 4" with 25%. © 2025, Politechnica University of Bucharest. All rights reserved.

关键词： Circular economy

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Single- and Dual-Beam Pattern Reconfigurable Patch Antenna With Dual Switchable CP for Internet of Vehicles

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IEEE Internet of Things Journal 2025年第12期12卷 21904-21914页

作者： Wang, Shi-Tong Zhu, Lei University of Macau Department of Electrical and Computer Engineering Faculty of Science and Technology China

In this article, a novel method is proposed to facilitate the design of compact, low-profile, pattern reconfigurable antennas with fixed or switchable circular polarization (CP) for Internet of Vehicles (IoV) applications. The proposed method eliminates the need for a complex beamforming or phase-tuning network by innovatively exploiting four resonant modes of a square patch antenna. Specifically, the TM01 and TM10 modes are utilized to accomplish the single-beam CP pattern, while the dual-beam CP pattern is achieved by combining the TM11 and TM02 modes. An electric current model is developed to investigate the far-field radiation, revealing that the radiation pattern of TM11 mode can be effectively reshaped from quad-beam to dual-beam by manipulating the surface current distribution. The complete design method is verified by an antenna prototype working at 3.5 GHz, which consists of a radiative patch, a pair of open-ended stubs, a pair of slots, and four equivalent switchable pins. Different from the conventional pin-loading method, the proposed equivalent switchable pins attain excellent CP performance during switching by compensating for the detrimental electric coupling. The prototype is fabricated and measured. Its radiation can be switched between single-beam (7.8 dBic) and dual-beam CP pattern (3.5 dBic), exhibiting an overlapped CP coverage from −123° to 73°. Furthermore, another prototype with the extended switchable CP capability is realized. Without increasing the number of p-i-n diodes, this prototype achieves four operating states with independent pattern (single- and dual-beam) and polarization (right- and left-handed CP) reconfiguration. The merits of compact size, low profile, and flexible reconfigurability make the proposed method and design cases excellent candidates for IoV applications and intelligent transportation systems (ITSs). © 2014 IEEE.

关键词： Circular polarization

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Impact of machine learning-based imputation techniques on medical datasets- a comparative analysis

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Multimedia Tools and Applications 2025年第9期84卷 5905-5925页

作者： Tiwaskar, Shweta Rashid, Mamoon Gokhale, Prasad Department of Computer Engineering Faculty of Science and Technology Vishwakarma University Pune India

In the realm of medical datasets, particularly when considering diabetes, the occurrence of data incompleteness is a prevalent issue. Unveiling valuable patterns through medical data analysis is crucial for early and precise medical predictions. However, the quality of data and the proper handling of missing data hold significant significance. To address this challenge, imputation stands as a robust approach. The main goal of this paper aims to provide a comprehensive investigation into the effects brought about by Machine Learning (ML) based imputation techniques, specifically K Nearest Neighbor Imputation (KNNI), Multiple Imputation by Chained Equations (MICE), and MissForest. Results of all three techniques are compared with the complete dataset for five missing rates (10% to 50%), and evaluated using four categories of evaluation criteria i.e. (1) model performance, (2) imputation error rate (Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Coefficient of Determination (R^2) values), (3) Pearson correlation analysis and, (4) model selection basis (Bayesian information criterion (BIC), Akaike information criterion (AIC), values). Model performance includes accuracy, precision, recall, F1 score, and Matthews Correlation Coefficient (Mcoff) score of four ML classifiers viz. (a) Random Forest (RF), (b) Support vector machine (SVM), (c) AdaBoost, (d) XGBoost (XGB). For all missing rate cases, the MissForest technique is better than the KNNI and MICE in accuracy and Mcoff in 80% of cases, precision in 40% of cases, recall in 60% of cases, F1 score, MAE, RMSE, R^2 in 100% of cases, AIC in 80% of cases, and BIC values in 100% of cases. Also, the correlation analysis confirms that the MissForest imputation preserves association between the variables, like the complete dataset. Overall, our findings suggest that MissForest is a better machine learning-based imputation technique for handling missing data in diabetes research. © The Author(s), under exclusive lice

关键词： Adaptive boosting

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Food ingredient recognition model via image and textual feature extraction and hybrid classification strategy

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International Journal of Reasoning-based Intelligent Systems 2024年第1期16卷 74-90页

作者： Madival, Sharanabasappa A. Jawaligi, Shivkumar S. Department of Computer Science and Engineering Faculty of Engineering and Technology Sharnbasva University India Department of Electronic and Communication Engineering Faculty of Engineering and Technology Sharnbasva University Karanataka Kalburgi India

This research work focuses on food recognition, especially, the identification of the ingredients from food images. Here, the developed model includes two stages namely: 1) feature extraction;2) classification. Initially, the image features and textual features will be extracted, where image features like SIFT and improved CNN-based deep features, textural features are extracted. Then, the hybrid classifier is used for the identification of food ingredients that combines the models like neural network (NN) as well as long short-term memory (LSTM). In order to make the accurate results, the weights of NN and LSTM are fine-tuned via the Chebyshev map evaluated teamwork optimisation (CME-TWO) algorithm. At the final stage, the primacy of the offered scheme is proven concerning varied metrics. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： Feature extraction

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An Encode-and CRT-Based Scalability Scheme for Optimizing Transmission in Blockchain

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Computer Modeling in engineering & sciences 2024年第5期139卷 1733-1754页

作者： Qianqi Sun Fenhua Bai Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming650500China

Blockchain technology has witnessed a burgeoning integration into diverse realms of economic and societal ***,scalability challenges,characterized by diminished broadcast efficiency,heightened communication overhead,and escalated storage costs,have significantly constrained the broad-scale application of *** paper introduces a novel Encode-and CRT-based Scalability Scheme(ECSS),meticulously refined to enhance both block broadcasting and ***,ECSS categorizes nodes into distinct domains,thereby reducing the network diameter and augmenting transmission ***,ECSS streamlines block transmission through a compact block protocol and robust RS coding,which not only reduces the size of broadcasted blocks but also ensures transmission ***,ECSS utilizes the Chinese remainder theorem,designating the block body as the compression target and mapping it to multiple modules to achieve efficient storage,thereby alleviating the storage burdens on *** evaluate ECSS’s performance,we established an experimental platformand conducted comprehensive *** results demonstrate that ECSS attains superior network scalability and stability,reducing communication overhead by an impressive 72% and total storage costs by a substantial 63.6%.

关键词： Blockchain network coding block compression transmission optimization

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Bio-Inspired Intelligent Routing in WSN: Integrating Mayfly Optimization and Enhanced Ant Colony Optimization for Energy-Efficient Cluster Formation and Maintenance

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Computer Modeling in engineering & sciences 2024年第10期141卷 127-150页

作者： V.G.Saranya S.Karthik Department of Electronics and Communication Engineering Faculty of Engineering&TechnologySRM Institute of Science and TechnologyVadapalani CampusChennai600026India

Wireless Sensor Networks(WSNs)are a collection of sensor nodes distributed in space and connected through wireless *** sensor nodes gather and store data about the real world around ***,the nodes that are dependent on batteries will ultimately suffer an energy loss with time,which affects the lifetime of the *** research proposes to achieve its primary goal by reducing energy consumption and increasing the network’s lifetime and *** present technique employs the hybrid Mayfly Optimization Algorithm-Enhanced Ant Colony Optimization(MFOA-EACO),where the Mayfly Optimization Algorithm(MFOA)is used to select the best cluster head(CH)from a set of nodes,and the Enhanced Ant Colony Optimization(EACO)technique is used to determine an optimal route between the cluster head and base *** performance evaluation of our suggested hybrid approach is based on many parameters,including the number of active and dead nodes,node degree,distance,and energy *** objective is to integrate MFOA-EACO to enhance energy efficiency and extend the network life of the WSN in the *** proposed method outcomes proved to be better than traditional approaches such as Hybrid Squirrel-Flying Fox Optimization Algorithm(HSFLBOA),Hybrid Social Reindeer Optimization and Differential Evolution-Firefly Algorithm(HSRODE-FFA),Social Spider Distance Sensitive-Iterative Antlion Butterfly Cockroach Algorithm(SADSS-IABCA),and Energy Efficient Clustering Hierarchy Strategy-Improved Social Spider Algorithm Differential Evolution(EECHS-ISSADE).

关键词： Enhanced ant colony optimization mayfly optimization algorithm wireless sensor networks cluster head base station(BS)

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Regulation of crystal and microstructures of RETaO4（RE=Nd,Sm,Gd,Ho,Er） powders synthesized via co-precipitation

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Journal of Rare Earths 2025年第6期43卷 1246-1255页

作者： Jiang Tian Lin Chen Xunlei Chen Keren Luo Baihui Li Di Zhang Meng Wang Bing Xu Zhiyi Ren Shixiao Yan Xiaoliang Sun Chi Liu Jing Feng Faculty of Materials Science and Engineering Kunming University of Science and Technology Southwest United Graduate School Shanghai Electro-Mechanical Engineering Institute Shanghai Spaceflight Precision Machinery Institute

Ferroelastic rare earth tantalates（RETaO4） are widely researched as the next-generation thermal barrier coatings（TBCs）,and RETaO4powders are hugely significant for synthesizing their *** current research used chemical co-precipitation within an automated experimental device to synthesize RETaO4（RE=Nd,Sm,Gd,Ho,Er） *** device automatically monitored and controlled the solutions' pH,improving the chemical co-precipitation *** crystal structure and microstructure of the RETaO4powders can be controlled by changing the annealing temperature,and the materials undergo an m'-m phase *** m'-RETaO4powders exhibit nano-size grains,while m-RETaO4powders evince micron-size grains,altered by the annealing temperatures.A simultaneous thermal analysis estimates the reversive ferroelastic tetragonal-monoclinic phase transition ***,this research focuses on the synthesis,crystal structures,micro structures,and phase transition of the fabricated RETaO4powders.

关键词： Annealing temperatures Chemical co-precipitation method Crystal structures Microstructures Rare earth tantalates Rare earths

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