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International Conference on Ubiquitous and Future Networks, ICUFN

作者： Youbang Sun Jianlin Guo Kieran Parsons Yukimasa Nagai Mitsubishi Electric Research Laboratories (MERL) Cambridge MA USA Department of Mechanical and Industrial Engineering Northeastern University Boston MA USA Information Technology R&D Center Mitsubishi Electric Corporation Kamakura Kanagawa Japan

ISBN: (数字)9798350385298

ISBN: (纸本)9798350385304

The crowdsourced information is useful to calibrate Advanced driver Assistance Systems/Autonomous driving (AdAS/Ad) parameters for automated and autonomous vehicles. However, learning such information in vehicular networks is challenging. On the one hand, data collected by individual vehicle may be not sufficient to train a large scale machine learning model. On the other hand, uploading raw data to cloud server is likewise impractical due to enormous communication bandwidth requirement and data privacy threat. This paper seeks a solution by applying federated learning (FL). We aim to improve FL algorithm stability to increase prediction accuracy. Accordingly, we propose a variance-based and structure-aware FL (VSFL), in which a variance-based model aggregation method is introduced for FL server to make optimal model aggregation and a structure-aware model training scheme is provided for vehicle clients to tackle statistical heterogeneity without compromising performance. We first provide theoretical analysis for the proposed VSFL. We then validate the effectiveness of VSFL algorithms on vehicle trajectory prediction using both synthetic data and real data.

关键词： Training data privacy Accuracy Federated learning Bandwidth Prediction algorithms Stability analysis

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Exploring Vehicular Interaction from Trajectories Based on Granger Causality

Exploring Vehicular Interaction from Trajectories Based on G...

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IEEE Symposium on Intelligent Vehicle

作者： Xishun Liao Guoyuan Wu Matthew J. Barth rohit Gupta Kyungtae Han Department of Electrical and Computer Engineering and the Center for Environmental Research and Technology University of California Riverside CA InfoTech Labs Toyota Motor North America R&D Mountain View CA

Understanding the behavior of human drivers and how they interact with other drivers is crucial to develop and improve the decision-making capabilities of connected and automated vehicles (CAVs). This allows CAVs to anticipate and proactively respond to the actions of other road users in a safe and efficient manner, especially in mixed-traffic environments. Most existing studies rely on neural networks to model such interaction implicitly, and very few studies attempt to interpret the interaction. Considering its interpretability and flexibility, the Granger causality (GC) framework is widely used to understand the relationships between different agents, as well as how these relationships change over time. In this paper, we integrate the knowledge of traffic and vehicle dynamics into the neural network to learn the Granger causality and explore vehicular interaction from multi-vehicle trajectories. The proposed algorithm has been validated using both the INTErACTION dataset and field data collected in riverside, California. The results show that our algorithm is able to address three key questions regarding vehicular interaction: 1) whether the interactions exist between/among the vehicles; 2) when the interactions occur and terminate; and 3) how strong the interactions between/among vehicles are.

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Above-room-temperature intrinsic ferromagnetism in ultrathin van der Waals crystal Fe3+xGaTe2

arXiv

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arXiv 2024年

作者： Zhang, Gaojie Yu, Jie Wu, Hao Yang, Li Jin, Wen Xiao, Bichen Zhang, Wenfeng Chang, Haixin State Key Laboratory of Material Processing and Die & Mold Technology School of Materials Science and Engineering Huazhong University of Science and Technology Wuhan430074 China Wuhan National High Magnetic Field Center Institute for Quantum Science and Engineering Huazhong University of Science and Technology Wuhan430074 China Shenzhen R&D Center of Huazhong University of Science and Technology Shenzhen518000 China

Two-dimensional (2d) van der Waals (vdW) magnets are crucial for ultra-compact spintronics. However, so far, no vdW crystal has exhibited tunable above-room-temperature intrinsic ferromagnetism in the 2d ultrathin regime. Here, we report the tunable above-room-temperature intrinsic ferromagnetism in ultrathin vdW crystal Fe3+xGaTe2 (x = 0 and 0.3). By increasing the Fe content, the Curie temperature (TC) and room-temperature saturation magnetization of bulk Fe3+xGaTe2 crystals are enhanced from 354 to 376 K and 43.9 to 50.4 emu·g-1, respectively. remarkably, the robust anomalous Hall effect in 3-nm Fe3.3GaTe2 indicate a record-high TC of 340 K and a large room-temperature perpendicular magnetic anisotropy energy of 6.6 × 105 J·m-3, superior to other ultrathin vdW ferromagnets. First-principles calculations reveal the asymmetric density of states and an additional large spin exchange interaction in ultrathin Fe3+xGaTe2 responsible for robust intrinsic ferromagnetism and higher TC © 2024, CC BY-NC-SA.

关键词： Ferromagnetism

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Solution of Power Equipment Condition Monitoring System Based on Things Oriented Architecture

Solution of Power Equipment Condition Monitoring System Base...

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International Conference on Power System technology (POWErCON)

作者： Shimin Gong Jin Zhu Nanzi Power Grid R&D Center Guodian Nanjing Automation Co. LtD Nanjing China School of Information and Communication Engineering Nanjing Institute of Technology Nanjing China

From the perspective of power equipment operation and maintenance management, this paper summarizes the limitations of traditional Pd monitoring, maintenance and operation, breaks through the traditional implementation methods, applies the advanced technology of ubiquitous Internet of things, and comprehensively considers the design from the aspects of acquisition mode, transmission means, diagnosis method and active decision feedback, puts forward a new monitoring system solution, and introduces the components of the monitoring system Some key technologies and implementation principles are introduced, and the typical engineering application implementation scheme is given. The results show that the operation and maintenance efficiency and management level of electrical equipment can be greatly improved through the application of new technology, and lay a data foundation for the next step of artificial intelligence and big data application mining.

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A novel chemical-free porous carbon micro-rods derived from used wooden chopsticks (CS) for solid-state symmetric supercapacitor device

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diamond and related Materials 2024年 141卷

作者： Senthilkumar, Arun Kumar Kumar, Mohanraj Chen, Ching-Lung Murugan, Sandhiya Ho, Mon-Shu Chang, Jih-Hsing Department of Environmental Engineering and Management Chaoyang University of Technology Taichung413310 Taiwan Department of Applied Chemistry Chaoyang University of Technology Taichung413310 Taiwan Department of Safety Health and Environmental Engineering Ming Chi University of Technology New Taipei City24301 Taiwan Center for Environmental Sustainability and Human Health Ming Chi University of Technology New Taipei City24301 Taiwan Biochemical Technology R&D Center Ming Chi University of Technology New Taipei City24301 Taiwan Department of Physics National Chung Hsing University Taichung City40227 Taiwan

Energy storage application technology is still in its infancy, and carbon-based materials have gained attention in recent years. The finding of low-cost carbon material with controllable characteristics for energy application is quite a complex thing. The major objective of this work is to carbonize used wooden chopsticks at various temperatures in order to create porous carbon materials. Electrochemical studies were tested in 1 M KOH electrolyte assessed by a three-electrode system for supercapacitor application. Among the prepared carbon materials, CS-7 material prepared at 700 °C with a carbon ratio of 88.2 %, demonstrated a high specific capacitance of 184.66 F/g at 0.3 A/g, and the material exhibited an excellent capacitance endurance of 96 % after 10,000 cycles. An asymmetric solid-state supercapacitor was developed for real-time application to study the electrochemical characteristics of the porous carbon material. This study clarifies the creation of complex porous carbon using waste biomass as an energy storage medium. © 2023 Elsevier B.V.

关键词： Supercapacitor

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Agar-Gelatin Maillard Conjugates Used for Pickering Emulsion Stabilization

SSRN

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SSrN 2024年

作者： du, Lipeng ru, Yi Weng, Huifen Zhang, Yonghui Chen, Jun Xiao, Anfeng Xiao, Qiong College of Ocean Food and Biological Engineering Jimei University Xiamen361021 China National R&D Center for Red Alga Processing Technology Xiamen361021 China Fujian Provincial Engineering Technology Research Center of Marine Functional Food Xiamen361021 China Xiamen Key Laboratory of Marine Functional Food Xiamen361021 China

A few protein- and polysaccharide-based particles have shown promising potential as stabilizers in multi-phase food systems. By incorporating polymer-based particles and modifying the wettability of colloidal systems, it is possible to create particle-stabilized emulsions with excellent stability. Pickering emulsions were developed by optimized agar-gelatin Maillard conjugates (AGMs). Laser confocal microscopy imaging revealed that AGMs particles can be used as solid emulsifiers to produce a typical O/W Pickering emulsion, with AGMs adsorbing onto the droplet surface to form a dense interfacial layer. Cryo-scanning electron microscopy analysis showed that AGMs self-assembled into a three-dimensional network structure, which prevented droplets aggregation through strong spatial site resistance, contributing to emulsion stabilization. These emulsions exhibited stability within a pH range of 1 to 11, NaCl concentrations not exceeding 300 mM, and at temperatures below 80 °C. AGM-stabilized Pickering emulsion was utilized to create a semi-solid mayonnaise as a replacement for hydrogenated oil. rheological analysis demonstrated that low-fat mayonnaise stabilized with AGMs exhibited similar rheological behavior to traditional mayonnaise, offering promise in the development of fat substitutes. This approach has opened up new avenues for the application of AGMs Pickering emulsion in the food industry. © 2024, The Authors. All rights reserved.

关键词： Polysaccharides

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Self-assembled hydrolyzed gelatin nanoparticles from silver carp spine bones for Pickering emulsion stabilization

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Food Bioscience 2022年第4期48卷 87-97页

作者： Wenjuan Wu Jiamin Xu Lili Yang Mengyang Yang Ting Zhang Xichang Wang Jian Zhong National R&D Branch Center for Freshwater Aquatic Products Processing Technology(Shanghai) Integrated Scientific Research Base on Comprehensive Utilization Technology for By-Products of Aquatic Product ProcessingMinistry of Agriculture and Rural Affairs of the People’s Republic of ChinaShanghai Engineering Research Center of Aquatic-Product Processing and PreservationCollege of Food Science&TechnologyShanghai Ocean UniversityShanghai201306China Xinhua Hospital Shanghai Institute of Pediatric ResearchShanghai Key Laboratory of Pediatric Gastroenterology and NutritionSchool of MedicineShanghai Jiao Tong UniversityShanghai200092China

In this work,enzymatic hydrolysis modification was combined with silver carp spine bone gelatin extraction process to obtain pepsin enzyme hydrolyzed gelatins(PEHGs)for emulsion *** pepsins at ratios of 6-24 U/g of silver carp vertebrae,PEHGs were obtained with molecular weights of mainly<5 Kda and the production yields were 12.6%-13.3%.The obtained PEHGs at different pepsin/vertebrae ratios showed similar secondary structure *** could self-assembled into pH-stable *** had higher fat-binding capacity values(16.2-21.5 g of oil/g of PEHG)and higher emulsion stabilization ability(creaming index values<11%after 28-day storage at 4℃)than silver carp scale gelatins,bovine bone gelatin,cold-water CFG and tilapia skin *** the decrease of pepsin/vertebrae ratios in the PEHG preparation process,the nanoparticle numbers and sizes increased,the turbidities of PEHG solutions increased,the gel strengths(164-314 g)of PEHG gels increased,the initial droplet sizes of Pickering emulsions decreased,and creaming stability of Pickering emulsions *** work provided useful information to analyze the effect of enzymatic hydrolysis modification on the structural,functional,and emulsifying properties of a *** also provided an efficient way to prepare protein self-assembly nanoparticles from animal tissues.

关键词： Extraction Enzymatic hydrolysis Fish oil-loaded Pickering emulsion Gelatin nanoparticles Silver carp spine bone

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Effect of Stator and rotor Pole Shapes on Torque of Flux-Modulating Consequent Pole Motors

Effect of Stator and Rotor Pole Shapes on Torque of Flux-Mod...

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International Conference on Electrical Machines and Systems (ICEMS)

作者： Hiroshi Mitsuda Tadashi Fukami Masato Koyama Kazumasa Ito Graduate School of Engineering Kanazawa Institute of Technology Ishikawa Japan Advanced Technology R&D Center Mitsubishi Electric Corporation Hyogo Japan

ISBN: (数字)9781665493024

ISBN: (纸本)9781665493031

The flux-modulating consequent pole motor (FCM) is a combination of a flux-modulating (FM) motor, which has flux regulation capability, and a permanent magnet (PM) motor. The FCM has a simple consequent pole rotor without brushes and slip rings, and a stator with concentrated armature and field windings. In this paper, the effect of stator and rotor pole shapes on the FCM’s torque is investigated. The torque is calculated from the Maxwell stress tensor method by separating the air gap magnetic flux density into space and time orders.

关键词： Magnetic flux density Torque Frequency modulation Shape AC motors Air gaps Stator windings

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Learning Based routing Link Scheduling in Heterogeneous Wireless loT Networks

Learning Based Routing Link Scheduling in Heterogeneous Wire...

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IEEE International Conference on Communications Workshops, ICC

作者： Zhiyang Wang Jianlin Guo Kieran Parsons Yukimasa Nagai Takenori Sumi Philip Orlik Mitsubishi Electric Research Laboratories (MERL) Cambridge MA USA Department of Electrical and Systems Engineering University of Pennsylvania Philadelphia PA USA Information Technology R&D Center Mitsubishi Electric Corporation Kamakura Kanagawa Japan

ISBN: (数字)9798350304053

ISBN: (纸本)9798350304060

With the advent of 5G and beyond communication technologies, the consumer Internet of Things (loT) devices are evolving from the current-generation to the next-generation. Next-generation loT devices can support multiple communication interfaces and perform more functions. Accordingly, loT network technologies must adapt to the emerging next-generation loT devices. routing is an inevitable technology in multi-hop loT networks. However, as loT devices become more and more diverse, loT networks become more complex. As a result, the routing problem becomes more and more complicated for traditional protocols and mathematical optimization approaches to provide optimal solutions. Machine learning based routing techniques have been recently proposed and can outperform traditional routing methods in complex network environments. To that end, this paper presents a machine learning based routing link scheduling scheme for heterogeneous wireless loT networks. We formulate the routing link scheduling problem as a combinatorial optimization problem, which is then parameterized for application of machine learning algorithm and the parameterized problem is solved using primal-dual approach with zero duality gap. A heterogeneous graph neural network (HetGNN) algorithm is proposed to update the primal-dual problems. We evaluate the proposed HetGNN model under networks with randomly deployed heterogeneous nodes. Compared with a convolutional neural network (CNN) model and a homogeneous GNN (HomGNN) model, the proposed HetGNN model can improve network throughput, reduce link capacity violation and interference link violation.

关键词： Wireless communication Machine learning Interference routing Throughput Graph neural networks Internet of Things

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Construction of Pickering Emulsion Stabilizer by Physical Mosaic Structure of Agar and Amino Acid

SSRN

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SSrN 2024年

作者： du, Lipeng Liu, Meixi ru, Yi Weng, Huifen Chen, Jun Zhang, Yonghui Xiao, Anfeng Xiao, Qiong College of Ocean Food and Biological Engineering Jimei University Xiamen361021 China National R&D Center for Red Alga Processing Technology Xiamen361021 China Fujian Provincial Engineering Technology Research Center of Marine Functional Food Xiamen361021 China Xiamen Key Laboratory of Marine Functional Food Xiamen361021 China

The well-known gelling ability of agar can make aqueous solutions into soft materials, amino acids are expected to embed in the agar gel to form a surfactant-like structure. The resulting agar-amino acid complex gel possesses a crispy texture and can be mechanically processed into microgel particles as the building block for constructing the Pickering emulsion. The functionalization of agar microgels by amino acid imparts a higher hydrophobicity and negative charge to the structure compared to non-functionalized microgels, as proved by contact angle and zeta potential test. Microstructural analysis reveals that the agar-amino acid complex microgels stabilize the Pickering emulsion by forming a self-assembled network structure and adsorbing onto the surface of oil droplets. Agar-amino acid complex microgel particles can stabilize Pickering emulsion at high pH (up to 11) and high temperature (70 ℃), which can provide a new application direction for food grade Pickering emulsion. © 2024, The Authors. All rights reserved.

关键词： Amino acids

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