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3D food printing for soft foods such as nursing food: Effects of protein and gelling agent added to burdock puree on retaining the shape of the discharged line and the printed object

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Japan Journal of Food engineering 2021年第1期22卷 27-38页

作者： Horiuchi, Mami Akachi, Toshiyuki Fujii, Ryoji Kawakami, Masaru Furukawa, Hidemitsu Department of Mechanical Systems Engineering Graduate School of Science and Engineering Yamagata University 4-3-16 Jonan Yonezawa Yamagata992-8510 Japan General Laboratories Daiwa Can Company 5-5-1 Nishi-hashimoto Midori-ku Sagamihara Kanagawa252-5183 Japan

3D printers have become popular in the world, and are expected to be used not only in industrial sectors but also in food sectors these days. Especially, making soft meals such as nursing foods with a 3D printer is useful to improve the satisfaction of eating and to reduce the burden of the caregiver. Therefore, we tried 3D printing of soft foods by using a combination of protein and gelling agent. And the effects of proteins and gelling agents were investigated. The results showed that 3D printing of soft foods can be performed by using a combination of protein and gelling agent and then extruding in a temperature range where the gelling agent does not completely gel and has fluidity after thermal denaturation of protein. Protein contributed to maintaining fluidity and retaining the shape of the discharged line, and gelling agent contributed to retaining the shape of the discharged line and adhering the layers. Furthermore, instead of protein, thermosetting gelling agent and thermoplastic gelling agent having a high gelation temperature also can be used. © 2021 Japan Society for Food engineering.

关键词： Proteins

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Identification of Polypyrrole-Encapsulated BiSCl as a Novel and Viable Conversion/Alloying Anode Material for High-Performance Lithium Storage

SSRN

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SSRN 2024年

作者： Li, Sen Huang, Zhiyuan Hua, Yingkai Liu, Xingchen Chen, Xi Feng, Qi Feng, Jun Department of Materials Science and Engineering Southern University of Science and Technology Guangdong Shenzhen518055 China Department of Industrial Systems Engineering The Hong Kong Polytechnic University 100872 Hong Kong Department of Pharmacology Graduate School of Medicine Kagawa University 1750-1 Takamatsu761-0793 Japan Department of Advanced Materials Science Faculty of Engineering and Design Kagawa University 2217-20 Takamatsu761-0396 Japan Guangdong Provincial Key Laboratory of Functional Oxide Materials and Devices Southern University of Science and Technology Guangdong Shenzhen518055 China Institute for Quantum Science and Engineering Southern University of Science and Technology Guangdong Shenzhen518055 China

Anode materials combining conversion and alloying mechanisms are increasingly valued in advanced rechargeable batteries for their exceptional theoretical capacities and advantageous working voltages. This study showcases BiSCl as a novel conversion/alloying anode material, demonstrating a high specific capacity and enhanced durability through polypyrrole encapsulation. Employing in-situ X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), ex-situ transmission electron microscopy (TEM), and field emission scanning electron microscopy (FESEM), we offer a detailed analysis of the lithiation mechanism in BiSCl. The anode exhibits a low average working potential of approximately 0.6 V, supporting a theoretical specific capacity of 784 mAh g−1 and a volumetric capacity of 4664 mAh cm−3. The innovative BiSCl-PPy core-shell composite effectively addresses the challenges of volumetric expansion and polysulfide dissolution. This composite delivers a remarkable reversible capacity of 753 mAh g–1 at a current rate of 100 mA g−1, maintaining 96% of its specific capacity over 400 cycles, and sustains 419 mAh g–1 at 500 mA g−1 after 800 cycles, demonstrating more superior performance than that of BiSCl. These findings establish BiSCl as a highly promising conversion/alloying anode material for lithium storage, significantly enhanced in durability by the BiSCl-PPy core-shell composite. © 2024, The Authors. All rights reserved.

关键词： Anodes

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Predictive Cruise control with Velocity Profile Online Optimization for Energy Efficiency

Predictive Cruise Control with Velocity Profile Online Optim...

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Chinese Automation Congress (CAC)

作者： Kai Sun Mengge Sun Fanyuan Chu Lulu Guo Jinlong Hong Bingzhao Gao School of Automotive Studies Tongji University Shanghai China Department of Control Science and Engineering Tongji University Shanghai China Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Factors such as road gradient, driving style, and traffic conditions all significantly impact the energy consumption performance of heavy trucks. Predictive Cruise control (PCC) algorithm, which based on Model Predictive control (MPC), can utilize the upcoming road gradient to achieve energy-efficient driving by controlling the truck's longitudinal speed. However, as a type of cruise control, PCC regulates longitudinal speed within a certain range, which limits its ability to fully exploit the energy-saving potential brought by speed variations. Dynamic Programming (DP) can compute the globally optimal vehicle speed for energy-efficient driving using pre-obtained map information. However, it requires significant computational resources and cannot be used in real-time online scenarios. This paper utilizes the powerful fitting capability of neural networks to enable online use of the DP algorithm. It utilizes the suggested vehicle speed output by the network to guide the PCC algorithm in speed tracking, thereby significantly enhancing energy efficiency. The proposed method has been compared with the Adaptive Cruise control (ACC) algorithm and the original PCC algorithm. Simulation results show that this method achieves superior energy efficiency: compared to the ACC algorithm, it improves energy savings by 14% to 18%, and compared to the original PCC, it improves energy savings by 6 % to 8 %.

关键词： Roads Heuristic algorithms Simulation Energy conservation Prediction algorithms Energy efficiency Real-time systems Dynamic programming Cruise control Predictive control

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EBSD evaluation of creep damage process for fine grained heat affected zone of serviced Mod.9Cr-1Mo steel

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Zairyo/Journal of the Society of Materials science, Japan 2021年第2期70卷 169-176页

作者： Nakamura, Takuya Kataoka, Oga Yoshimura, Hidenori Hirata, Hideyuki Fujiyama, Kazunari Energy Engineering Department Shikoku Research Institute Inc. Yashimanishi-machi Takamatsu761-0192 Japan Graduate School of Engineering Kagawa University Hayashi-cho Takamatsu761-0396 Japan Area of Mechanical Systems Engineering Faculty of Engineering and Design Kagawa University Hayashi-cho Takamatsu761-0396 Japan Department of Mechanical Engineering Faculty of Science and Technology Meijo University Tempaku-ku Nagoya468-8502 Japan

Type IV creep damage in fine grained heat affected zone of Mod.9Cr-1Mo steel has been concerned and extensively studied for steam piping of thermal power plants. However, the evaluation of Type IV damage by EBSD measurement is not enough. Serviced materials that have been used for a long time in an actual equipment are considered to effective materials for investigating microstructural changes in a long-term region. In this study, SEM observation and EBSD measurement were performed on the material of the Mod. 9Cr-1Mo steel FGHAZ used on the actual equipment and interrupted test specimen. As a result, as the creep progressed, strain concentration due to dislocation accumulation was observed in the portion near the voids, and recovery due to dislocation reduction was confirmed in the non-void portion, and the mechanism of Type IV damage caused by local strain concentration was confirmed. ΔKAM, which is obtained by subtracting KAMlocal, which is the KAM value near the void portion, and KAM0, which is the KAM value of the nonvoid portion, showed a monotonic increase with respect to the creep damage rate t/tr. The possibility that creep damage can be evaluated by this index was shown. In addition to examining the estimation formula expressing the change of the KAM value, it was found that the macroscopic and local void numbers could be evaluated from the KAM value. © 2021 Society of Materials science Japan. All rights reserved.

关键词： Creep

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Velocity Estimation of an Underwater Vehicle Using Doppler Shift of Positioning Signals

Velocity Estimation of an Underwater Vehicle Using Doppler S...

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International Symposium on Underwater Technology

作者： Atsushi Tsuchiya Tadashi Ebihara Naoto Wakatsuki Tohru Yoshihara Graduate School of Science and Technology University of Tsukuba Tsukuba Japan Institute of Systems and Information Engineering University of Tsukuba Tsukuba Japan Technology Development Department Aomi Construction Co. Ltd. Tokyo Japan

ISBN: (数字)9798331534189

ISBN: (纸本)9798331534196

This paper proposes a method for estimating the moving velocity of underwater vehicles by utilizing the Doppler shift in positioning signals employed for time-of-arrival (ToA) acoustic positioning. The Doppler shift generated in the received signal was measured by resampling, and the moving velocity in global coordinates was estimated by finding the least-squares solution using the Doppler shift generated in the direct wave and the position measured by ToA positioning. Field experiments conducted in a real marine environment demonstrated the feasibility and effectiveness of the proposed velocity estimation method.

关键词： Doppler shift Accuracy Coordinate measuring machines Estimation Position measurement Acoustic measurements Velocity measurement Underwater technology Underwater acoustics Underwater vehicles

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Blockchain-based Edge Computing Service with Dynamic Entry and Exit Mechanism

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IEEE Transactions on Mobile Computing 2025年

作者： He, Qiang Feng, Zheng Fang, Hui Wang, Xingwei Zhao, Liang Yu, Keping Choo, Kim-Kwang Raymond Northeastern University College of Medicine and Biological Information Engineering China Shanghai University of Finance and Economics Research Institute for Interdisciplinary Science School of Information Management and Engineering China Northeastern University College of Computer Science and Engineering Shenyang110169 China Shenyang Aerospace University College of Computer Science and Engineering Shenyang110136 China Hosei University Graduate School of Science and Engineering Tokyo184-8584 Japan University of Texas at San Antonio Department of Information Systems and Cyber Security San AntonioTX78249 United States

With the widespread application of 5G and artificial intelligence (AI) technology, the Internet of Things (IoT) has been expanding and integrated into various aspects of our daily lives. However, this also poses challenges such as the ubiquitous demand for communication and computing resources, and data privacy issues. Considering its flexible deployment, high security, and ease of scalability, blockchain-enabled edge computing IoT network (BECIN) has become a promising solution to provide secure and fast communication and computing services. However, existing research on computation offloading in edge computing largely overlooks the stochastic arrival of computational tasks and the potential variability in the number, locations, and resource provisions of edge computing service providers. Therefore, we propose a dynamic, self-adjusting BECIN framework aimed at providing long-term stable, efficient, and secure edge computing data offloading services for ground users in a specific region. This framework supports the dynamic entry and exit of edge computing service providers. Additionally, we introduce a novel dynamic Dueling DDQN approach to update the offloading and resource management policies based on changes in resource provisioning. Experimental results demonstrate the feasibility and superior performance of our framework on system cost and system latency. © 2002-2012 IEEE.

关键词： Reinforcement learning

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Design of a Dual-Polarized Dual-Band and Wideband Multi-Ring Microstrip Antenna Fed by Two L-Probes with a Cavity Structure for Stable Gain Characteristics

Design of a Dual-Polarized Dual-Band and Wideband Multi-Ring...

引用

2021 IEEE International Symposium on Antennas and Propagation and North American Radio science Meeting, APS/URSI 2021

作者： Kimura, Yuki Saito, Sakuyoshi Kimura, Yuichi Graduate School of Science and Engineering Saitama University Department of Electrical and Electronic Systems 255 Shimo-ohkubo Sakura-ku Saitama338-8570 Japan

ISBN: (纸本)9781728146706

This paper presents a dual-polarized dual-band and wideband multi-ring microstrip antenna (MR-MSA) fed by two L-probes with a cavity structure. The proposed antenna consists of two circular ring patches arranged at the top and middle layers of a triple-layered dielectric substrate and two L-probe placed orthogonally in the bottom layer with a large thickness for dual-polarized dual-band and wideband operation. In order to obtain stable gain characteristics against finite sizes of the dielectric substrate and the ground plane, a cavity structure which is composed of a square ring patch on the top layer and several vias connecting to the ground plane is introduced surrounding the radiating patches. The cavity structure is designed in a small size without affecting the dual-band and wideband performance of the MR-MSA by using the numerical simulation with ANSYS HFSS. The design frequencies of the MR-MSA are around 3.5 GHz and 4.75 GHz. The simulated results reveal that dual-band and wideband performance of 26% and 23% fractional bandwidths less than -10 dB reflection is observed. It is also confirmed by the simulation that stable gain characteristics against sizes of the substrate and the ground plane of the designed MR-MSA with the cavity structure are obtained in comparison with the same MR-MSA without the cavity structure. © 2021 IEEE.

关键词： Probes

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Performance Enhancement of a Spin-Wave-Based Reservoir Computing System Utilizing Different Physical Conditions

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Physical Review Applied 2023年第3期19卷 034047-034047页

作者： Ryosho Nakane Akira Hirose Gouhei Tanaka Department of Electronic Engineering and Information Systems Graduate School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-8656 Japan International Research Center for Neurointelligence (IRCN) The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-0033 Japan Department of Mathematical Informatics Graduate School of Information Technology and Science The University of Tokyo Tokyo 113-8656 Japan

We numerically study how to enhance reservoir computing performance by thoroughly extracting the spin-wave device potential for higher-dimensional information generation. The reservoir device has a 1-input exciter and 120-output detectors on the top of a continuous magnetic garnet film for spin-wave transmission. For various nonlinear and fading-memory dynamic phenomena distributing in the film space, small in-plane magnetic fields are used to prepare stripe domain structures and various damping constants at the film sides and bottom are explored. The ferromagnetic resonant frequency and relaxation time of spin precession clearly characterizes the change in spin dynamics with the magnetic field and damping constant. The common input signal for reservoir computing is a 1-GHz cosine wave with random 6-valued amplitude modulation. A basic 120-dimensional reservoir output vector is obtained from time-series signals at the 120-output detectors under each of three magnetic field conditions. Then, 240- and 360-dimensional reservoir output vectors are also constructed by concatenating two and three basic ones, respectively. In nonlinear autoregressive moving average (NARMA) prediction tasks, the computational performance is enhanced as the dimension of the reservoir output vector becomes higher and a significantly low prediction error is achieved for the tenth-order NARMA task using the 360-dimensional vector and optimum damping constant. The results are clear evidence that the collection of diverse output signals efficiently increases the dimensionality of the integrated reservoir state vector (i.e. reservoir-state richness) and thereby contributes to high computational performance. This paper demonstrates that performance enhancement through various configuration settings is a practical approach for on-chip reservoir computing devices with small numbers of real output nodes.

关键词： Neuromorphic computing Spin dynamics Spin waves Artificial neural networks Devices for digital logic, storage & processing Chaos & nonlinear dynamics Landau-Lifschitz-Gilbert equation Machine learning

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EMHDRL: Adversarial Attacks on Graph Neural Networks via Hierarchical Reinforcement Learning

EMHDRL: Adversarial Attacks on Graph Neural Networks via Hie...

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Chinese control Conference (CCC)

作者： Guowei Sun Jie Ding Xiang Li Department of Electronic Engineering Adaptive Networks and Control Lab School of Information Science and Engineering Fudan University Shanghai China Institute of Complex Networks and Intelligent Systems Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China

Graph neural networks (GNNs), with its powerful ability to explore the topological structure of graph data, have achieved great success in various downstream tasks. However, recent studies have shown that due to the lack of robustness, GNNs are easily fooled by perturbations. For node classification tasks, the current attack methods mainly focus on manipulating edges, modifying features and adding fake nodes. Although these attacks are effective, the changes to the original graph data are easy to be detected. Therefore, to misclassify the target nodes, we propose an Edge Manipulation method via Hierarchical Deep Reinforcement Learning (EMHDRL) by taking accounting to the imperceptibility of perturbation on graph data. Through modeling the topology perturbation as Finite Horizon Markov Decision Process, EMHDRL adopts a hierarchical Q-function network to manipulate edges of graph, while trying to ensure that the degree of the attacked node and the total number of edges of the whole graph remain unchanged. Our experimental results show that the proposed method can effectively reduce the performance of GNNs in classifying the target nodes and has strong transferability.

关键词：

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Federated Cubic Regularized Newton Learning with Sparsification-amplified Differential Privacy

arXiv

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arXiv 2024年

作者： Huo, Wei Liu, Changxin Ding, Kemi Johansson, Karl Henrik Shi, Ling Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Digital Futures StockholmSE-10044 Sweden School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen518055 China

This paper investigates the use of the cubic-regularized Newton method within a federated learning framework while addressing two major concerns that commonly arise in federated learning: privacy leakage and communication bottleneck. We introduce a federated learning algorithm called Differentially Private Federated Cubic Regularized Newton (DP-FCRN). By leveraging second-order techniques, our algorithm achieves lower iteration complexity compared to first-order methods. We also incorporate noise perturbation during local computations to ensure privacy. Furthermore, we employ sparsification in uplink transmission, which not only reduces the communication costs but also amplifies the privacy guarantee. Specifically, this approach reduces the necessary noise intensity without compromising privacy protection. We analyze the convergence properties of our algorithm and establish the privacy guarantee. Finally, we validate the effectiveness of the proposed algorithm through experiments on a benchmark dataset. © 2024, CC BY.

关键词： Federated learning

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