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Catalytic wet torrefaction of lignocellulosic biomass: An overview with emphasis on fuel application

South African Journal of Chemical Engineering 2023年 43卷 162-189页

作者： Phang, Frederick Jit Fook Soh, Megan Khaerudini, Deni Shidqi Timuda, Gerald Ensang Chew, Jiuan Jing How, Bing Shen Loh, Soh Kheang Yusup, Suzana Sunarso, Jaka Research Centre for Sustainable Technologies Faculty of Engineering Computing and Science Swinburne University of Technology Jalan Simpang Tiga Sarawak Kuching 93350 Malaysia Research Center for Advanced Materials National Research and Innovation Agency (BRIN) Bld. 440 Kawasan Puspiptek Serpong Banten South Tangerang 15314 Indonesia Energy and Environmental Unit Engineering and Processing Division Malaysian Palm Oil Board 6 Persiaran Institusi Bandar Baru Bangi Selangor Kajang 43000 Malaysia Generation Unit (Fuel and Combustion Section) TNB Research Sdn. Bhd. No. 1 Kawasan Institusi Penyelidikan Jalan Ayer Hitam Selangor Kajang 43000 Malaysia

Wet torrefaction (WT), also named hydrothermal carbonisation (HTC), has been regarded as one of the highly studied thermochemical process pathways for biomass-to-solid fuel conversion in the last decade (2012–2021). Catalysts have been added in the WT or HTC of lignocellulosic biomass for various applications (i.e. solid fuel synthesis, carbon material synthesis, pre-treatment, sugar production, ash content removal, and the study of reaction kinetics). Regardless, there is no review on the addition of catalysts in WT to produce hydrochar as fuel, specifically on the role of catalysts in the formation of ‘secondary deposits’, which refers to deposits that have been observed on the hydrochar. This review discusses the fundamentals of WT and how the lignocellulosic biomass components in various biomass, operating process parameters, and catalysts affect the fuel properties of the hydrochar product. For catalytic WT and HTC, relevant studies in different yet interrelated applications are overviewed, where insights are given based on the effect of catalyst addition on the properties of hydrochar and the promotion of ‘secondary deposits’. The ‘secondary deposits’ established in carbon material synthesis studies can reveal the relationship between catalyst addition and formation. On top of that, it also serves as a complimentary knowledge to enhance the understanding of how these deposits can be used to increase the higher heating value of the hydrochar, which is lacking in the existing hydrochar synthesis studies. Therefore, the aim of this review is to provide insights into the addition of catalysts for the synthesis of hydrochar for fuel application. © 2022 The Author(s)

关键词： Catalyst Hydrochar Hydrothermal carbonisation Mechanism Secondary deposit

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Optical Anisotropy in van der Waals materials: Impact on Direct Excitation of Plasmons and Photons by Quantum Tunneling

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Light(Science & Applications) 2021年第12期10卷 2387-2398页

作者： Zhe Wang Vijith Kalathingal Thanh Xuan Hoang Hong-Son Chu Christian A.Nijhuis Department of Chemistry National University of Singapore3 Science Drive 3Singapore 117543Singapore Centre for Advanced 2D Materials National University of Singapore6 Science Drive 2Singapore 117564Singapore Department of Electrical and Computer Engineering National University of Singapore4 Engineering Drive 3Singapore 117583Singapore Department of Electronics and Photonics Institute of High Performance ComputingA*STAR(Agency for ScienceTechnology and Research)1 Fusionopolis WaySingapore 138632Singapore Hybrid Materials for Opto-Electronics Group Department of Molecules and MaterialsMESA+Institute for Nanotechnology and Center for Brain-Inspired Nano SystemsFaculty of Science and TechnologyUniversity of Twente7500 AE EnschedeThe Netherlands

Inelastic quantum mechanical tunneling of electrons across plasmonic tunnel junctions can lead to surface plasmon polariton(SPP)and photon *** far,the optical properties of such junctions have been controlled by changing the shape,or the type of the material,of the electrodes,primarily with the aim to improve SPP or photon emission *** we show that by tuning the tunneling barrier itself,the efficiency of the inelastic tunneling rates can be improved by a factor of *** exploit the anisotropic nature of hexagonal boron nitride(hBN)as the tunneling barrier material in Au//hBN//graphene tunnel junctions where the Au electrode also serves as a plasmonic strip *** this junction constitutes an optically transparent hBN–graphene heterostructure on a glass substrate,it forms an open plasmonic system where the SPPs are directly coupled to the dedicated strip waveguide and photons outcouple to the far *** experimentally and analytically show that the photon emission rate per tunneling electron is significantly improved(~×3)in Au//hBN//graphene tunnel junction due to the enhancement in the local density of optical states(LDOS)arising from the hBN *** the dedicated strip waveguide,SPP outcoupling efficiency is quantified and is found to be∼80%stronger than the radiative outcoupling in Au//hBN//graphene due to the high LDOS of the SPP decay channel associated with the inelastic *** new insights elucidated here deepen our understanding of plasmonic tunnel junctions beyond the isotropic models with enhanced LDOS.

关键词： tunneling strip coupling

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A Study of the Efficacy of Generative Flow Networks for Robotics and Machine Fault-Adaptation

arXiv

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arXiv 2025年

作者： Sufiyan, Zahin Golestan, Shadan Miwa, Shotaro Mitsuka, Yoshihiro Zaiane, Osmar Department of Computing Science University of Alberta 8900 114 St NW EdmontonABT6G 2S4 Canada Advanced Technology R&D Center Mitsubishi Electric Corporation 8-1-1 Tsukaguchi-honmachi Amagasaki-shi Hyogo661-8661 Japan Information Technology R&D Center Mitsubishi Electric Corporation 5-1-1 Ofuna Kamakura-shi Kanagawa247-8501 Japan Alberta Machine Intelligence Institute 10065 Jasper Ave #1101 EdmontonABT5J 3B1 Canada

Advancements in robotics have opened possibilities to automate tasks in various fields such as manufacturing, emergency response and healthcare. However, a significant challenge that prevents robots from operating in real-world environments effectively is out-of-distribution (OOD) situations, wherein robots encounter unforseen situations. One major OOD situations is when robots encounter faults, making fault adaptation essential for real-world operation for robots. Current state-of-the-art reinforcement learning algorithms show promising results but suffer from sample inefficiency, leading to low adaptation speed due to their limited ability to generalize to OOD situations. Our research is a step towards adding hardware fault tolerance and fast fault adaptability to machines. In this research, our primary focus is to investigate the efficacy of generative flow networks in robotic environments, particularly in the domain of machine fault adaptation. We simulated a robotic environment called Reacher in our experiments. We modify this environment to introduce four distinct fault environments that replicate real-world machines/robot malfunctions. The empirical evaluation of this research indicates that continuous generative flow networks (CFlowNets) indeed have the capability to add adaptive behaviors in machines under adversarial conditions. Furthermore, the comparative analysis of CFlowNets with reinforcement learning algorithms also provides some key insights into the performance in terms of adaptation speed and sample efficiency. Additionally, a separate study investigates the implications of transferring knowledge from pre-fault task to post-fault environments. Our experiments confirm that CFlowNets has the potential to be deployed in a real-world machine and it can demonstrate adaptability in case of malfunctions to maintain functionality. © 2025, CC BY.

关键词： Generative adversarial networks

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Enhancing Hardware Fault Tolerance in Machines with Reinforcement Learning Policy Gradient Algorithms

arXiv

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arXiv 2024年

作者： Schoepp, Sheila Taghian, Mehran Miwa, Shotaro Mitsuka, Yoshihiro Golestan, Shadan Zaïane, Osmar R. Department of Computing Science University of Alberta 8900 114 St NW EdmontonABT6G 2S4 Canada Alberta Machine Intelligence Institute 10065 Jasper Ave #1101 EdmontonABT5J 3B1 Canada Advanced Technology R&D Center Mitsubishi Electric Corporation 8-1-1Tsukaguchi-honmachi Hyogo Amagasaki-shi661-8661 Japan Information Technology R&D Center Mitsubishi Electric Corporation 5-1-1 Ofuna Kanagawa Kamakura-shi247-8501 Japan

Industry is rapidly moving towards fully autonomous and interconnected systems that can detect and adapt to changing conditions, including machine hardware faults. Traditional methods for adding hardware fault tolerance to machines involve duplicating components and algorithmically reconfiguring a machine’s processes when a fault occurs. However, the growing interest in reinforcement learning-based robotic control offers a new perspective on achieving hardware fault tolerance. However, limited research has explored the potential of these approaches for hardware fault tolerance in machines. This paper investigates the potential of two state-of-the-art reinforcement learning algorithms, Proximal Policy Optimization (PPO) and Soft Actor-Critic (SAC), to enhance hardware fault tolerance into machines. We assess the performance of these algorithms in two OpenAI Gym simulated environments, Ant-v2 and FetchReach-v1. Robot models in these environments are subjected to six simulated hardware faults. Additionally, we conduct an ablation study to determine the optimal method for transferring an agent’s knowledge, acquired through learning in a normal (pre-fault) environment, to a (post-)fault environment in a continual learning setting. Our results demonstrate that reinforcement learning-based approaches can enhance hardware fault tolerance in simulated machines, with adaptation occurring within minutes. Specifically, PPO exhibits the fastest adaptation when retaining the knowledge within its models, while SAC performs best when discarding all acquired knowledge. Overall, this study highlights the potential of reinforcement learning-based approaches, such as PPO and SAC, for hardware fault tolerance in machines. These findings pave the way for the development of robust and adaptive machines capable of effectively operating in real-world scenarios. © 2024, CC BY.

关键词： Reinforcement learning

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Metaheuristic Based IDS Using Multi-objective Wrapper Feature Selection and Neural Network Classification 2nd

Metaheuristic Based IDS Using Multi-objective Wrapper Featur...

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2nd International Conference on Advances in Cyber Security, ACeS 2020

作者： Ghanem, Waheed Ali H. M. El-Ebiary, Yousef A. Baker Abdulnab, Mohamed Tubishat, Mohammad Alduais, Nayef A. M. Nasser, Abdullah B. Abdullah, Nibras Al-wesabi, Ola A. Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Kuala Terengganu Malaysia Faculty of Engineering and Faculty of Education-Aden and Saber Aden University Aden Yemen Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Kuala Terengganu Malaysia School of Computing and Technology Asia Pacific University of Technology and Innovation Kuala Lumpur Malaysia Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia Parit Raja Malaysia Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Pekan Malaysia National Advanced IPv6 Center Universiti Sains Malaysia Gelugor Malaysia Faculty of Computer Science and Engineering Hodeidah University Al Hudaydah Yemen

ISBN: (纸本)9789813368347

Due to the significant ongoing expansion of computer networks in our lives nowadays, the demand for network security and protection from cyber-attacks has never been more imperative to either clients or businesses alike, which signifies the key role of cyber intrusion detection systems in network security. This article proposes a cyber-intrusion detecting system classification with MLP trained by a hybrid metaheuristic algorithm and feature selection based on multi-objective wrapper method. The classifier, named as HADMLP is trained using a hybridization of the artificial bee colony along with the dragonfly algorithm. A multi-objective artificial bee colony model which is wrapper-based is used for selection of feature. Hence, collective name of the proposed technique referred as MO-HADMLP. For performance evaluation, the proposed method was assessed using ISCX 2012 and KDD CUP 99 datasets. The results of our experiments indicate a significant enhancement to the efficacy of network intrusion detection when compared to other approaches. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Multiobjective optimization

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High-Order Randomized Compiler for Hamiltonian Simulation

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PRX Quantum 2024年第2期5卷 020330-020330页

作者： Kouhei Nakaji Mohsen Bagherimehrab Alán Aspuru-Guzik Chemical Physics Theory Group Department of Chemistry University of Toronto Toronto Ontario Canada M5S 3H6 Research Center for Emerging Computing Technologies National Institute of Advanced Industrial Science and Technology (AIST) 1-1-1 Umezono Tsukuba Ibaraki 305-8568 Japan Quantum Computing Center Keio University 3-14-1 Hiyoshi Kohoku-ku Yokohama Kanagawa 223-8522 Japan Department of Computer Science University of Toronto Toronto Ontario Canada M5S 2E4 Vector Institute for Artificial Intelligence Toronto Ontario Canada M5G 1M1 Department of Chemical Engineering & Applied Chemistry University of Toronto Toronto Ontario Canada M5S 3E5 Department of Materials Science & Engineering University of Toronto Toronto Ontario Canada M5S 3E4 Canadian Institute for Advanced Research (CIFAR) Toronto Ontario Canada M5S 1M1

Hamiltonian simulation is known to be one of the fundamental building blocks of a variety of quantum algorithms such as its most immediate application, that of simulating many-body systems to extract their physical properties. In this work, we present qSWIFT, a high-order randomized algorithm for Hamiltonian simulation. In qSWIFT, the required number of gates for a given precision is independent of the number of terms in the Hamiltonian, while the systematic error is exponentially reduced with regard to the order parameter. In this respect, our qSWIFT is a higher-order counterpart of the previously proposed quantum stochastic drift protocol (qDRIFT), the number of gates in which scales linearly with the inverse of the precision required. We construct the qSWIFT channel and establish a rigorous bound for the systematic error quantified by the diamond norm. qSWIFT provides an algorithm to estimate given physical quantities by using a system with one ancilla qubit, which is as simple as other product-formula-based approaches such as regular Trotter-Suzuki decompositions and qDRIFT. Our numerical experiment reveals that the required number of gates in qSWIFT is significantly reduced compared to qDRIFT. In particular, the advantage is significant for problems where high precision is required; e.g., to achieve a systematic relative propagation error of 10−6, the required number of gates in third-order qSWIFT is 1000 times smaller than that of qDRIFT.

关键词： Quantum computation Quantum simulation

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Composable free-space continuous-variable quantum key distribution using discrete modulation

arXiv

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arXiv 2024年

作者： Jaksch, Kevin Dirmeier, Thomas Weiser, Yannick Richter, Stefan Bayraktar, Ömer Hacker, Bastian Rößler, Conrad Khan, Imran Petscharning, Stefan Grafenauer, Thomas Hentschel, Michael Ömer, Bernhard Pacher, Christoph Kanitschar, Florian Upadhyaya, Twesh Lin, Jie Lütkenhaus, Norbert Leuchs, Gerd Marquardt, Christoph Max Planck Institute for the Science of Light Staudtstr. 2 Erlangen91058 Germany Department of Physics Friedrich-Alexander-Universität Erlangen-Nürnberg Staudtstr. 7 Erlangen91058 Germany SAOT Graduate School in Advanced Optical Technologies Paul-Gordan-Str. 6 Erlangen91052 Germany AIT Austrian Institute of Technology Center for Digital Safety&Security Giefinggasse 4 Vienna1210 Austria fragmentiX Storage Solutions GmbH xista science park Plöcking 1 Klosterneuburg3400 Austria Atominstitut Technische Universität Wien Stadionallee 2 Vienna1020 Austria Institute for Quantum Computing Department of Physics and Astronomy University of Waterloo WaterlooONN2L 3G Canada

Continuous-variable (CV) quantum key distribution (QKD) allows for quantum secure communication with the benefit of being close to existing classical coherent communication. In recent years, CV QKD protocols using a discrete number of displaced coherent states have been studied intensively, as the modulation can be directly implemented with real devices with a finite digital resolution. However, the experimental demonstrations until now only calculated key rates in the asymptotic regime. To be used in cryptographic applications, a QKD system has to generate keys with composable security in the finite-size regime. In this paper, we present a CV QKD system using discrete modulation that is especially designed for urban atmospheric channels. For this, we use polarization encoding to cope with the turbulent but non-birefringent atmosphere. This will allow to expand CV QKD networks beyond the existing fiber backbone. In a first laboratory demonstration, we implemented a novel type of security proof allowing to calculate composable finite-size key rates against i.i.d. collective attacks without any Gaussian assumptions. We applied the full QKD protocol including a QRNG, error correction and privacy amplification to extract secret keys. In particular, we studied the impact of frame errors on the actual key generation. © 2024, CC BY.

关键词： Quantum cryptography

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Bridging HPC Communities through the Julia Programming Language

arXiv

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arXiv 2022年

作者： Churavy, Valentin Godoy, William F. Bauer, Carsten Ranocha, Hendrik Schlottke-Lakemper, Michael Räss, Ludovic Blaschke, Johannes Giordano, Mosè Schnetter, Erik Omlin, Samuel Vetter, Jeffrey S. Edelman, Alan Massachussetts Institute of Technology United States Oak Ridge National Laboratory United States Paderborn Center for Parallel Computing Paderborn University Germany Department of Mathematics University of Hamburg Germany Applied and Computational Mathematics RWTH Aachen University Germany University of Stuttgart Germany ETH Zurich Switzerland Birmensdorf Switzerland National Energy Research Scientific Computing Center Lawrence Berkeley National Laboratory 1 Cyclotron Road BerkeleyCA94720 United States Centre for Advanced Research Computing University College London Gower Street LondonWC1E 6BT United Kingdom Perimeter Institute 31 Caroline St. N. WaterlooONN2L 2Y5 Canada Department of Physics and Astronomy University of Waterloo 200 University Avenue West WaterlooONN2L 3G1 Canada Center for Computation & Technology Louisiana State University Baton RougeLA70803 United States ETH Zurich Switzerland

The Julia programming language has evolved into a modern alternative to fill existing gaps in scientific computing and data science applications. Julia leverages a unified and coordinated single-language and ecosystem paradigm and has a proven track record of achieving high performance without sacrificing user productivity. These aspects make Julia a viable alternative to high-performance computing's (HPC's) existing and increasingly costly many-body workflow composition strategy in which traditional HPC languages (e.g., Fortran, C, C++) are used for simulations, and higher-level languages (e.g., Python, R, MATLAB) are used for data analysis and interactive computing. Julia's rapid growth in language capabilities, package ecosystem, and community make it a promising universal language for HPC. This paper presents the views of a multidisciplinary group of researchers from academia, government, and industry that advocate for an HPC software development paradigm that emphasizes developer productivity, workflow portability, and low barriers for entry. We believe that the Julia programming language, its ecosystem, and its community provide modern and powerful capabilities that enable this group's objectives. Crucially, we believe that Julia can provide a feasible and less costly approach to programming scientific applications and workflows that target HPC facilities. In this work, we examine the current practice and role of Julia as a common, end-to-end programming model to address major challenges in scientific reproducibility, data-driven AI/machine learning, co-design and workflows, scalability and performance portability in heterogeneous computing, network communication, data management, and community education. As a result, the diversification of current investments to fulfill the needs of the upcoming decade is crucial as more supercomputing centers prepare for the exascale era. © 2022, CC BY.

关键词： Productivity

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Corrigendum to “Hybridizing flower pollination algorithm with particle swarm optimization for enhancing the performance of IPv6 intrusion detection system” [Alex. Eng. J. 104 (2024) 504–514]

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Alexandria Engineering Journal 2025年 110卷 376-376页

作者： Adnan Hasan Bdair AIghuraibawi Selvakumar Manickam Zaid Abdi Alkareem Alyasseri Rosni Abdullah Ayman Khallel Riyadh Rahef Nuiaa Al Ogaili Fahd N. Al-Wesabi Abdulsamad Ebrahim Yahya National Advanced IPv6 Centre (NAv6) Universiti Sains Malaysia Penang 11800 Malaysia Baghdad College of Economic Sciences University Baghdad Iraq Information Technology Research and Development Center University of Kufa Najaf Iraq College of Engineering University of Warith Al-Anbiyaa Karbala Iraq School of Computer Sciences Universiti Sains Malays Penang 11800 Malaysia Faculty of Computing and Informatics Universiti Malaysia Sabah Sabah Malaysia Department of Cybersecurity Engineering Technology Al Hikma University College Baghdad Iraq Department of Computer Science/ College of Computer Science and Information Technology Wasit University Kut Wasit 52001 Iraq Department of Computer Science College of Science & Art at Mahayil King Khalid University Saudi Arabia Department of Information Technology College of Computing and Information Technology Northern Border University Arar Saudi Arabia

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High fusion computers: The IoTs, edges, data centers, and humans-in-the-loop as a computer

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BenchCouncil Transactions on Benchmarks, Standards and Evaluations 2022年第3期2卷 100075-100075页

作者： Gao, Wanling Wang, Lei Chen, Mingyu Xiong, Jin Luo, Chunjie Zhang, Wenli Huang, Yunyou Li, Weiping Kang, Guoxin Zheng, Chen Xie, Biwei Dai, Shaopeng He, Qian Ye, Hainan Bao, Yungang Zhan, Jianfeng State Key Lab of Processors and Research Center for Advanced Computer Systems Institute of Computing Technology Chinese Academy of Sciences No. 6 Kexueyuan South Road Haidian District Beijing 100190 China Yuquan Road Shijingshan District Beijing 100049 China Guangxi Normal University No. 15 Yucai Road Qixing District Guangxi Guilin541010 China Civil Aviation Flight University of China No. 46 Section 4 Nanchang Road Sichuan Guanghan618307 China Institute of Software Chinese Academy of Sciences No. 4 South 4th Street Beijing Zhongguancun100190 China Beijing Institute of Open Source Chip No. 7 Caoqiao Northwest Corner of Haidian Bridge Haidian District Beijing 100080 China

Emerging and future applications rely heavily upon systems consisting of Internet of Things (IoT), edges, data centers, and humans-in-the-loop. Significantly different from warehouse-scale computers that serve independent concurrent user requests, this new class of computer systems directly interacts with the physical world, considering humans an essential part and performing safety-critical and mission-critical operations;their computations have intertwined dependencies between not only adjacent execution loops but also actions or decisions triggered by IoTs, edge, datacenters, or humans-in-the-loop;the systems must first satisfy the accuracy metric in predicting, interpreting, or taking action before meeting the performance goal under different cases. This article argues we need a paradigm shift to reconstruct the IoTs, edges, data centers, and humans-in-the-loop as a computer rather than a distributed system. We coin a new term, high fusion computers (HFCs), to describe this class of systems. The fusion in the term has two implications: fusing IoTs, edges, data centers, and humans-in-the-loop as a computer, fusing the physical and digital worlds through HFC systems. HFC is a pivotal case of the open-source computer systems initiative. We laid out the challenges, plan, and call for uniting our community's wisdom and actions to address the HFC challenges. Everything, including the source code, will be publicly available from the project homepage: https://***/HFC/. © 2022 The Authors

关键词： Internet of things

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