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2024 IEEE International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale, 3M-NANO 2024

作者： Bian, Wenzhi Li, Song Zhang, Tingting Zhang, Shuhua Chen, Yujuan Li, Zhiping Changchun University of Science and Technology School of Life Science and Technology Changchun China Research and Development Center for Process and Analysis Methods Changchun GeneScience Pharmaceutical Co. Ltd. Changchun China Changchun GeneScience Pharmaceutical Co. Ltd. R&d Department Changchun China Academy of Military Medical Sciences Institute of Military Veterinary Medicine Changchun China

ISBN: (纸本)9798350362107

At present, with the improvement of people's living standards, food borne pathogens, as one of the biggest threats to food safety, are widely valued by people. Therefore, it is urgent to create a fast and efficient method for detecting foodborne pathogens. This article discusses the establishment of a fast and non-destructive detection method for foodborne pathogenic bacteria using terahertz time-domain spectroscopy. In this study, the bacterial dry powder of Cronobacter sakazakii was mixed with polyethylene with different mass ratios (0 %, 1 %, 5 %, 10 %, 20 %, 30 %, 40 %, 50 %, 100 % w/w) to make tablet, the thickness of the tablet is 1~1.4 mm, and the diameter is 1.4 cm, and the mass is 0.18 g. Transmission spectrum was used for detection. By observed and analyzed the absorption spectra, the waveforms of three groups of repeated data showed consistency, and there were obvious characteristic absorption peaks at 1.28 and 1.78 THz. The accuracy of clustering software analysis results is 100 %, which shows that the method has good stability and specificity. The detection limit of Cronobacter sakazakii is 1%. We have successfully established a terahertz time-domain spectral detection method for foodborne pathogens. This method is rapid, stable and sensitive, and has a broad application prospect. © 2024 IEEE.

关键词： Terahertz spectroscopy

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On the tensor product of completely distributive quantale-enriched categories

arXiv

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arXiv 2025年

作者： Balan, Adriana Department of Mathematical Methods and Models Fundamental Sciences Applied in Engineering Research Center National University of Science and Technology POLITEHNICA of Bucharest BucharestRO-060042 Romania

Tensor products are ubiquitous in algebra, topology, logic and category theory. The present paper explores the monoidal structure of the category V-Sup of separated cocomplete enriched categories over a commutative quantale V, the many-valued analogue of complete sup-lattices. We recover the known result that V-Sup is ∗-autonomous and we show that the nuclear/dualizable objects in V-Sup are precisely the completely distributive cocomplete *** Codes 18D20, 18B35, 18A40, 06D10, 06F07, 18M05, 18C20 © 2025, CC BY.

关键词： Tensors

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Evolution of superconductivity and corresponding electronic structure in pressurized Nb_(3)Sn

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Superconductivity 2025年第1期13卷 17-22页

作者： Wenxuan Chen Xintian Chen Yangfan Gao Yazhou Zhou Shu Cai Jinyu Zhao Ke Yang Aiguo Li Sheng Jiang Qi Wu Defang Duan Jing Guo Liling Sun Institute of Physics Chinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China Center for High Pressure Science&Technology Advanced Research Beijing 100094China Shanghai Synchrotron Radiation Facilities Shanghai Advanced Research InstituteChinese Academy of SciencesNo.239 Zhangheng RoadShanghai 201204China Key Laboratory of Material Simulation Methods&Software of Ministry of Education and State Key Laboratory of Superhard Materials College of physicsJilin University130012ChangchunChina

The studies on superconductors under extreme conditions offer valuable insights for assessing their potential in new ***_(3)Sn,an intermetallic alloy with an A15 structure,is a key commercial superconductor known for its high critical current and magnetic field ***,we systematically investigated the physical properties of Nb_(3)Sn under high *** findings reveal that superconductivity in Nb_(3)Sn remains robust up to∼142 GPa,demonstrating remarkable stability despite a gradual suppression of��c with increasing ***-principles calculations indicate that the pressure-dependent superconducting behavior is primarily driven by variations in the density of states of Nb’s d-electrons,particularly contributions from the d_(x^(2)-y^(2)) and d_(z^(2)) ***,we predict the potential for synthesizing Nb_(3)Sn films and demonstrate that biaxial strain induced by suitable substrates can preserve their superconducting *** comprehensive study not only enhances our understanding of Nb_(3)Sn’s superconducting mechanism under high pressure but also opens new avenues for its application in advanced superconducting technologies.

关键词： Superconductivity High pressure Nb_(3)Sn

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Determining the contribution of Mo single atoms components in MoO_(2)nanocatalyst in transfer hydrogenation

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Nano research 2023年第2期16卷 2302-2310页

作者： Ze-Nan Hu Yongjian Ai Yan Zhao Yiming Wang Kelong Ding Wenhui Zhang Rongxiu Guo Xinyue Zhang Xiangbin Cai Ning Wang Jianshe Hu Qionglin Liang Hongyang Liu Fei Huang Limin Wu Jiangwei Zhang Hong-bin Sun School of Environmental Engineering and Chemistry Luoyang Institute of Science and TechnologyLuoyang 471023China Department of Chemistry Northeastern UniversityShenyang 110819China MOE Key Laboratory of Bioorganic Phosphorus Chemistry&Chemical Biology Beijing Key Lab of Microanalytical Methods&InstrumentationDepartment of ChemistryCenter for Synthetic and Systems BiologyTsinghua UniversityBeijing 100084China College of Energy Material and Chemistry Inner Mongolia UniversityHohhot 010021China Department of Physics and Center for Quantum Materials Hong Kong University of Science and TechnologyClear Water BayKowloonHong Kong SARChina Shenyang National Laboratory for Materials Science Institute of Metal ResearchChinese Academy of SciencesShenyang 110016China

Nanocatalysts are likely to contain undetected single-atom components,which may have been ignored but have significant effect in catalytic ***,we report a catalyst composed of Mo single atoms(SAs)and MoO_(2)nanoparticles(NPs)(MoSAs-MoO_(2)@NC),which is an exact model to understand how the SAs contribute to the *** experimental results and the density functional theory calculations reveal that Mo SAs on nitrogen-doped carbon provides the reaction zone for nitro reduction,while MoO_(2)is the active site for decomposing hydrazine hydrate to produce H*.Thanks to the synergy between Mo SAs and MoO_(2)NPs,this catalyst exhibits noble metal-like catalytic activity(100%conversion at 4 min)for the dechlorination-proof transfer ***,the hydrogen migration on the catalyst is verified by the electrochemical tests in the absence of a hydrogen *** work provides a model for further study on the coexistence of single atoms in nanoparticle catalysts.

关键词： synergistic effect Mo single atoms MoO_(2)nanocatalyst transfer hydrogenation nitroarenes

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Hyper Elliptic Curve Based Certificateless Signcryption Scheme for Secure IIoT Communications

引用

Computers, Materials & Continua 2022年第5期71卷 2515-2532页

作者： Usman Ali Mohd Yamani Idna Idris Jaroslav Frnda Mohamad Nizam Bin Ayub Roobaea Alroobaea Fahad Almansour Nura Modi Shagari Insaf Ullah Ihsan Ali Department of Computer System and Technology Faculty of Computer Science and Information TechnologyUniversity of MalayaKuala Lumpur50603Malaysia Department of Computer Science University of SwatSaidu Sharif19130Pakistan Center for Research in Mobile Cloud Computing University of MalayaKuala Lumpur50603Malaysia Department of Quantitative Methods and Economic Informatics Faculty of Operation and Economics of Transport and CommunicationsUniversity of Zilina01026 ZilinaSlovakia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Science College of Sciences and Arts in RassQassim UniversityBuraydah51452Saudi Arabia Department of Computer Science Hamdard Institute of Engineering and TechnologyIslamabad44000Pakistan

Industrial internet of things (IIoT) is the usage of internet of things(IoT) devices and applications for the purpose of sensing, processing andcommunicating real-time events in the industrial system to reduce the unnecessary operational cost and enhance manufacturing and other industrial-relatedprocesses to attain more profits. However, such IoT based smart industriesneed internet connectivity and interoperability which makes them susceptibleto numerous cyber-attacks due to the scarcity of computational resourcesof IoT devices and communication over insecure wireless channels. Therefore, this necessitates the design of an efficient security mechanism for IIoTenvironment. In this paper, we propose a hyperelliptic curve cryptography(HECC) based IIoT Certificateless Signcryption (IIoT-CS) scheme, with theaim of improving security while lowering computational and communicationoverhead in IIoT environment. HECC with 80-bit smaller key and parameterssizes offers similar security as elliptic curve cryptography (ECC) with 160-bitlong key and parameters sizes. We assessed the IIoT-CS scheme security byapplying formal and informal security evaluation techniques. We used Realor Random (RoR) model and the widely used automated validation of internet security protocols and applications (AVISPA) simulation tool for formalsecurity analysis and proved that the IIoT-CS scheme provides resistance tovarious attacks. Our proposed IIoT-CS scheme is relatively less expensivecompared to the current state-of-the-art in terms of computational cost andcommunication overhead. Furthermore, the IIoT-CS scheme is 31.25% and 51.31% more efficient in computational cost and communication overhead,respectively, compared to the most recent protocol.

关键词： IoT security authentication protocols hyperelliptic curve cryptography certificateless public key cryptography

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Machine Learning for Energy Load Prediction and its Interpretation 11

Machine Learning for Energy Load Prediction and its Interpre...

引用

11th IEEE International Conference on Intelligent Systems, IS 2022

作者： Charytanowicz, Malgorzata Olwert, Anna Radziszewska, Weronika Jarnicka, Jolanta Gajowniczek, Krzysztof Zabkowski, Tomasz Brozyna, Jacek Mentel, Grzegorz Matejko, Grzegorz Research Institute Pas Center for Methods of Data Analysis Systems Warsaw Poland Research Institute Pas Department of Computer Science Systems Warsaw Poland Research Institute Pas Center for Computer Modelling Systems Warsaw Poland Warsaw University of Life Sciences Institute of Information Technology Warsaw Poland Rzeszow University of Technology Department of Quantitative Methods Rzeszów Poland Polskie Towarzystwo Cyfrowe Lublin Poland

ISBN: (纸本)9781665456562

This paper refers to real-life data on energy consumption from three companies, connected to a medium voltage grid. The companies use single-, two-, or three-zone tariffs and the general characteristic of their activity is comparable. The input dataset contains hourly electricity consumption recorded from January 2020 to December 2020. The independent variables used for the study include weather, time-dependent factors, and aggregated energy factors. We perform the prediction of consumption using three methods: naive, multiple regression, and extreme gradient boosting regression. The performance of the methods is compared based on the MSE, RMSE, MAE, and MAPE metrics. The study shows that the scores achieved for the extreme gradient boosting method are higher than for the multiple regression. To gain the interpretability of the energy load forecasting and feature analysis the Shapley additive explanations method is used for the best model. As a result, a ranking of the most important factors is created. It shows the importance of aggregated energy factors and weather conditions while placing daylight and season at the bottom of the ranking. © 2022 IEEE.

关键词： Energy utilization

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Leveraging Artificial Intelligence in Online Educational Platforms to Enhance Continuous Professional Development in the Teaching Profession 2

Leveraging Artificial Intelligence in Online Educational Pla...

引用

2nd International Conference Computational and Characterization Techniques in Engineering and sciences, IC3TES 2024

作者： Amankulovich, Khujakulov Sherzod Tokhirovich, Mannabov Javlon Bakhridinovich, Kadirov Tulkin Kuvandikovich, Taylakov Umid Ananth, Christo Kumar, T. Ananth Samarkand Regional National Center for Training Teachers in New Methods Uzbekistan Uzbekistan Samarkand Agroinnovations and Research University Uzbekistan Samarkand State University Uzbekistan&Adjunct Faculty Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Avadi Chennai India Ifet College of Engineering Computer Science and Engineering Tamilnadu India

ISBN: (纸本)9798350364699

To keep up with the dynamic nature of the modern classroom, teachers must have access to online learning platforms for professional development purposes. This investigation looks at how these platforms can be used to improve teachers' skills, make information sharing easier, and open doors to CPD opportunities. This study examines the relationship between online resources and methods to demonstrate how digital tools have an impact on teacher training and professional development by leveraging AI. It also draws attention to the fact that these platforms are helping with information-methodological support for teachers as well as the ongoing reforms in our nation. Incorporating empirical observations and case studies, the analysis demonstrates how effective online platforms are in fostering a collaborative and innovative environment for professional learning. Digital transformation has the potential to radically alter how teachers obtain professional development, and this study emphasizes that fact. This will enable teachers to effectively address the demands of modern classrooms. © 2024 IEEE.

关键词： Contrastive Learning

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A coarse-grained bonded particle model for large-scale rock simulation

Rock Mechanics Bulletin

引用

Rock Mechanics Bulletin 2024年第4期3卷 58-69页

作者： Chengshun Shang Liping Li Kaiwei Chu Zongqing Zhou Guillermo Casas Wenfeng Tu Yuxue Chen Shangqu Sun School of Qilu Transportation Shandong University250061JinanChina International Center for Numerical Methods in Engineering(CIMNE) 08034BarcelonaSpain Universitat Politecnica de Catalunya(UPC) 08034BarcelonaSpain Geotechnical and Structural Engineering Research Center Shandong University250061JinanChina College of Civil Engineering and Architecture Shandong University of Science And Technology266590QingdaoChina

For solving the computationally intensive problem encountered by the discrete element method(DEM)in simulating large-scale engineering problems,it is essential to establish a numerical model that can effectively simulate large-scale *** this study,the coarse-graining effect of a linear-Mindlin with bonding model was studied in the unconfined compression strength(UCS)and Brazilian tensile strength(BTS)*** found that the main reason for the coarse-graining effect of the BTS tests is that the type I fracture toughness is positively correlated with the size of the *** on the results analysis and fracture mechanics,the coarse-grained(CG)modeling theory was combined with a bonded particle model(BPM)for the first time and a coarse-grained bonded particle model(CG-BPM)was developed,which can be effectively used to model the tensile strength of large-scale rocks with different particle *** excavation damage zone(EDZ)in an underground research laboratory(URL)was selected as an application case,which shows that the coarse-grained bonding model presented in this paper is more accurate and reliable than the traditional one in large-scale rock simulation,at least in the scenario where tensile failure is dominant.

关键词： Numerical simulation Discrete element method(DEM) Coarse-grained bonded particle model(CGBPM) Large-scale rock

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Distributed averaging for accuracy prediction in networked systems

arXiv

引用

arXiv 2023年

作者： Sirocchi, Christel Bogliolo, Alessandro Research Methods in Science and Technology The Department of Pure and Applied Sciences University of Urbino Italy Computer Science The Department of Pure and Applied Sciences University of Urbino Italy

Distributed averaging is among the most relevant cooperative control problems, with applications in sensor and robotic networks, distributed signal processing, data fusion, and load balancing. Consensus and gossip algorithms have been investigated and successfully deployed in multi-agent systems to perform distributed averaging in synchronous and asynchronous settings. This study proposes a heuristic approach to estimate the convergence rate of averaging algorithms in a distributed manner, relying on the computation and propagation of local graph metrics while entailing simple data elaboration and small message passing. The protocol enables nodes to predict the time (or the number of interactions) needed to estimate the global average with the desired accuracy. Consequently, nodes can make informed decisions on their use of measured and estimated data while gaining awareness of the global structure of the network, as well as their role in it. The study presents relevant applications to outliers identification and performance evaluation in switching topologies. © 2023, CC BY.

关键词： Message passing

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Exploring the Impact of Random Distribution Choices on Particle Swarm Optimization: An Initial Analysis 27

Exploring the Impact of Random Distribution Choices on Parti...

引用

27th International Conference on Knowledge Based and Intelligent Information and Engineering Sytems, KES 2023

作者： Kolodziejczyk, Joanna Tarasenko, Yuliia Sulikowski, Piotr Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence Methods and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology in Szczecin ul. Zolnierska 49 Szczecin71-210 Poland National Institute of Telecommunications ul. Szachowa 1 Warsaw04-894 Poland Department of Information Systems Engineering Faculty of Computer Science and Information Technology West Pomeranian University of Technology in Szczecin ul. Zolnierska 49 Szczecin71-210 Poland

Particle Swarm Optimization (PSO) is a robust stochastic optimization algorithm for solving complex and constrained optimization problems. This paper aims to systematically investigate the influence of diverse random number distributions on the learning parameters of PSO and evaluate the algorithm's sensitivity based on these parameters. To this end, several exhaustive numerical experiments were conducted on several test functions, including asymmetric Sphere, Easom, and Csendes. Initially, appropriate random distributions were identified for the learning parameters and proceeded to compare these distributions using all potential combinations. The sensitivity of PSO to these parameters was evaluated using the mean best score, the relative proximity of the best particle to the theoretical optimum, and the average objective function evaluations. The most significant contribution of this research lies in the insights derived from the experimental data. The discovery was that highly skewed and long-tailed distributions such as Chi, Chi-square, Lomax, and Exponential often underperform. On the other hand, distributions that are bounded proportionally to the problem domain consistently surpass the performance of the standard uniform distribution. These findings significantly enhance the understanding of PSO algorithms and provide valuable guidelines for their practical deployment. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0)

关键词： Particle Swarm Optimization random number distribution stochastic optimization

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