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arXiv 2023年

作者： Ren, Ziyao Kang, Yan Fan, Lixin Yang, Linghua Tong, Yongxin Yang, Qiang State Key Laboratory of Software Development Environment Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing School of Computer Science Beihang University China Webank China Hong Kong University of Science and Technology Hong Kong

SecureBoost is a tree-boosting algorithm leveraging homomorphic encryption to protect data privacy in vertical federated learning setting. It is widely used in fields such as finance and healthcare due to its interpretability, effectiveness, and privacy-preserving capability. However, SecureBoost suffers from high computational complexity and risk of label leakage. To harness the full potential of SecureBoost, hyperparameters of SecureBoost should be carefully chosen to strike an optimal balance between utility, efficiency, and privacy. Existing methods either set hyperparameters empirically or heuristically, which are far from optimal. To fill this gap, we propose a Constrained Multi-Objective SecureBoost (CMOSB) algorithm to find Pareto optimal solutions that each solution is a set of hyperparameters achieving optimal tradeoff between utility loss, training cost, and privacy leakage. We design measurements of the three objectives. In particular, the privacy leakage is measured using our proposed instance clustering attack. Experimental results demonstrate that the CMOSB yields not only hyperparameters superior to the baseline but also optimal sets of hyperparameters that can support the flexible requirements of FL participants. Copyright © 2023, The Authors. All rights reserved.

关键词： Trees (mathematics)

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Signal approximation with Pascal’s triangle and sampling

Signal approximation with Pascal’s triangle and sampling

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Chinese Control and Decision Conference, CCDC

作者： Lei Chen Xinghuo Yu Jinhu Lü School of Automation Science and Electrical Engineering State Key Laboratory of Software Development Environment Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing China School of Engineering RMIT University Melbourne VIC Australia

ISBN: (数字)9781728158556

ISBN: (纸本)9781728158563

This brief explores the approximation properties of a unique basis expansion based on Pascal's triangle, which realizes a sampled-data driven approach between a continuous-time signal and its discrete-time representation. The roles of certain parameters, such as sampling time interval or model order, and signal characteristics, i.e., its curvature, on the approximation are investigated. Approximate errors in one and multiple-step predictions are analyzed. Furthermore, time-variant approximations under the thresholds of signal curvature are employed to narrow errors and provide flexibilities.

关键词： Shape Electronic mail Analytical models Mathematical analysis Data models Upper bound

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Generating disentangled arguments with prompts: A simple event extraction framework that works

arXiv

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arXiv 2021年

作者： Si, Jinghui Peng, Xutan Li, Chen Xu, Haotian Li, Jianxin Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University China State Key Laboratory of Software Development Environment Beihang University China Alibaba Group China Department of Computer Science The University of Sheffield United Kingdom

Event Extraction bridges the gap between text and event signals. Based on the assumption of trigger-argument dependency, existing approaches have achieved state-of-the-art performance with expert-designed templates or complicated decoding constraints. In this paper, for the first time we introduce the prompt-based learning strategy to the domain of Event Extraction, which empowers the automatic exploitation of label semantics on both input and output sides. To validate the effectiveness of the proposed generative method, we conduct extensive experiments with 11 diverse baselines. Empirical results show that, in terms of F1 score on Argument Extraction, our simple architecture is stronger than any other generative counterpart and even competitive with algorithms that require template engineering. Regarding the measure of recall, it sets new overall records for both Argument and Trigger Extractions. We hereby recommend this framework to the community, with the code publicly available at https://***/GDAP. Copyright © 2021, The Authors. All rights reserved.

关键词： Extraction

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A parallel algorithm for logic simulation on transputer networks

A parallel algorithm for logic simulation on transputer netw...

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Great Lakes Symposium on VLSI

作者： S. Srinivas A. Basu A. Paulraj L.M. Patnaik Department of Electrical and Computer Engineering Concordia University Montreal QUE Canada Centre for Development of Advanced Computing Bangalore India Microprocessor Applications Laboratory Supercomputing Education and Research Center Department of Computer Science and Automation Indian Institute of Science Bangalore India

The authors present a parallel algorithm for logic simulation of VLSI circuits. It is implemented on a network of transputers connected in a ring topology. The approach is based on partitioning a functionality matrix representation of the circuit among the transputers and adopting a data flow technique for the solution. A significant aspect of the algorithm is that it overlaps computation with communication, thereby reducing the communication overhead. It also attempts even distribution of load in order to reduce processor idle time. The algorithm possesses the advantages of ease of implementation and ease of extension to incorporate additional parameters for simulation. Performance results of the algorithm are given.< >

关键词： Parallel algorithms Circuit simulation Computational modeling Concurrent computing Application software Logic circuits Very large scale integration Algorithm design and analysis Logic design Design automation

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IoT-Enabled Automated Smart Irrigation System Incorporating Sensor Parameters 5th

IoT-Enabled Automated Smart Irrigation System Incorporating ...

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5th Doctoral Symposium on Computational Intelligence, DoSCI 2024

作者： Singh, Jagendra Neeraj Srinivas Reddy, P. Hasan, Dler Salih Alsahlanee, Abbas Thajeel Rhaif Shaik, Nazeer Alliance School of Advanced Computing Alliance University Bangalore India School of Computer Science Engineering and Technology Bennett University Greater Noida India Department of Mechanical Engineering CVR College of Engineering Hyderabad India Department of Computer Science and Information Technology University of Salahaddin-Erbil Erbil Iraq Development and Continuous Education Center University of Thi-Qar Thi-Qar Iraq Department of Computer Science and Engineering Srinivasa Ramanujan Institute of Technology—Autonomous Anantapur India

ISBN: (纸本)9789819763177

This article presents the experimental findings of a smart irrigation system evaluated in two separate agricultural settings—small-scale farming and large-scale agriculture. The system combines sensors, microcontrollers, and actuators to precisely monitor and regulate the irrigation process in order to optimum water use and crop output. Water savings range from 20 to 45% when using smart irrigation technology in small-scale agriculture. By only turning on the irrigation pump when necessary, the technology optimizes water use and fosters sustainable farming methods. Furthermore, by sustaining perfect growing conditions, the approach boosts crop output, with yield benefits ranging from 10 to 22%. These improvements assist small-scale farmers in becoming more profitable and raising their level of living. In large-scale agriculture, smart irrigation systems allow excellent water management and resource optimization across huge agricultural fields. The technology consistently saves a large quantity of water, often between 25 and 50%, addressing water scarcity issues. Additionally, this method has led to a 12–25% increase in aggregate crop yields, thereby raising farm income and increasing agricultural firm profitability. Experiments shows that this smart irrigation system could bring cost-effective, sustainable techniques to extensive and intensive agriculture alike. Intelligence-guided decision-making technology is applied here, and cutting-edge technologies are brought to bear on the water use problem. The system conserves precious resources and increases agricultural output at the same time. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Smart agriculture

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On the Outage Performance of Drones-Aided Cooperative D2D communications systems

On the Outage Performance of Drones-Aided Cooperative D2D co...

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Computer Communications and Intelligent Systems (I3CIS), International Conference on

作者： Widad Belaoura Khalida Ghanem Mohummed Zeeshan Shakir Department Engineering of Electrical Systems Université M'Hamed Bougara Boumerdes Boumerdes Algeria System Architecture Laboratory Center of development of advanced techniques (CDTA) Algiers Algeria School of Computing Engineering and Physical Sciences University of the West of Scotland Paisley UK

The advanced Device-to-Device (D2D) system is recognized as one of the key emerging technologies to support the increasing wireless data traffic of fifth generation (5G) systems and beyond. In this paper, we aim to study a novel cooperative D2D communications concept to improve the communication between the D2D users. In this model, multiple drones are included in the network and operate as half duplex amplify-and-forward (AF) relays scheme and the Maximal Ratio Combining (MRC) method is employed at the receiver side to combine the relayed signals. The effect of various parameters on the outage probability is investigated, including drone altitude placement, number of drones, and transmission power. Simulation results indicate that the outage probability of the cooperative D2D solution is greatly improved whenever an additional drone is added to the cooperative system.

关键词： Wireless communication Simulation System performance Cooperative systems Receivers Probability Device-to-device communication

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Fast Tunable Coupling Scheme of Kerr Parametric Oscillators Based on Shortcuts to Adiabaticity

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Physical Review Applied 2022年第3期18卷 034076-034076页

作者： S. Masuda T. Kanao H. Goto Y. Matsuzaki T. Ishikawa S. Kawabata Research Center for Emerging Computing Technologies (RCECT) National Institute of Advanced Industrial Science and Technology (AIST) 1-1-1 Umezono Tsukuba Ibaraki 305-8568 Japan NEC-AIST Quantum Technology Cooperative Research Laboratory National Institute of Advanced Industrial Science and Technology (AIST) Tsukuba Ibaraki 305-8568 Japan Frontier Research Laboratory Corporate Research & Development Center Toshiba Corporation 1 Komukai-Toshiba-cho Saiwai-ku Kawasaki 212-8582 Japan

Kerr parametric oscillators (KPOs), which can be implemented with superconducting parametrons possessing large Kerr nonlinearity, have been attracting much attention in terms of their applications to quantum annealing, universal quantum computation, and studies of quantum many-body systems. It is of practical importance for these studies to realize fast and accurate tunable coupling between KPOs in a simple manner. We develop a simple scheme of fast tunable coupling of KPOs with high tunability in speed and amplitude using the fast transitionless rotation of a KPO in the phase space based on the shortcuts to adiabaticity. Our scheme enables rapid switching of the effective coupling between KPOs, and can be implemented with always-on linear coupling between KPOs, by controlling the phase of the pump field and the resonance frequency of the KPO without controlling the amplitude of the pump field nor using additional drive fields and couplers. We apply the coupling scheme to a two-qubit gate, and show that our scheme realizes high gate fidelity compared with a purely adiabatic one, by mitigating undesired nonadiabatic transitions.

关键词： Circuit quantum electrodynamics Optoelectronics Quantum control Quantum gates Quantum information with solid state qubits Optical parametric oscillators & amplifiers Superconducting qubits Kerr effect

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Graph convolutional neural networks via motif-based attention

arXiv

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arXiv 2018年

作者： Peng, Hao Li, Jianxin Gong, Qiran Wang, Senzhang Ning, Yuanxing Yu, Philip S. Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University State Key Laboratory of Software Development Environment Beihang University Collage of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Department of Computer Science University of Illinois at Chicago

Many real-world problems can be represented as graph-based learning problems. In this paper, we propose a novel framework for learning spatial and attentional convolution neural networks on arbitrary graphs. Different from previous convolutional neural networks on graphs, we first design a motif-matching guided subgraph normalization method to capture neighborhood information. Then we implement subgraph-level self-attentional layers to learn different importances from different subgraphs to solve graph classification problems. Analogous to image-based attentional convolution networks that operate on locally connected and weighted regions of the input, we also extend graph normalization from one-dimensional node sequence to two-dimensional node grid by leveraging motif-matching, and design self-attentional layers without requiring any kinds of cost depending on prior knowledge of the graph structure. Our results on both bioinformatics and social network datasets show that we can significantly improve graph classification benchmarks over traditional graph kernel and existing deep models. Copyright © 2018, The Authors. All rights reserved.

关键词： Graphic methods

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Detecting forensically relevant information from PE executables

Detecting forensically relevant information from PE executab...

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International Conference on Recent Trends in Information Technology (ICRTIT)

作者： Shany Jophin Meera Vijayan S Dija Dept. Of Computer Science Adi Shankara Institute of Engineering and Technology Kalady Dept. Of Computer Science Adi Shankara Institute of Engineering and Technology Kalady India Resource Center for Cyber Forensics Centre for Development of Advanced Computing (CDAC) Trivandrum India

Cyber forensics analysis is the procedure to find crucial evidence with respect to a crime from a digital media. Malware forensics and Network security plays a crucial role in the current scenario where malware attacks are a common problem. A malicious software which can be commonly termed as a malware would cause interruption to a computer operation and may collect necessary information or illegally access private systems. A malware may either take the form of a script, code, spyware and many other kinds of malicious programs. Reverse engineering principles are applied in this domain to analyze malware. It is the comprehensive process of breaking software to figure out how it works. This paper proposes an advanced and resource friendly malware forensics analysis procedure which uses the principles of static analysis to figure out the exact purpose of an executable file. Portable executable format can be explored with higher accuracy using the proposed method.

关键词： Malware Feature extraction Databases Accuracy Software Market research Information technology

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An efficient sequential method for enhanced landfill leachate treatment and detoxification: Electrocoagulation/permanganate, peroxymonosulfate-based process, and electro-peroxone

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Journal of Environmental Management 2025年 388卷 125785页

作者： Hosseinikhah, Maryam Ghalebizade, Mohamad Hassani, Aydin Behzadian, Kourosh Waclawek, Stanislaw Lin, Kun-Yi Andrew Ghanbari, Farshid Civil and Environmental Engineering Faculty Tarbiat Modares University Tehran Iran Department of Materials Science and Nanotechnology Engineering Faculty of Engineering Near East University 99138 Nicosia TRNC Mersin 10 Turkey Near East University 99138 Nicosia TRNC Mersin 10 Turkey School of Computing and Engineering University of West London London United Kingdom Department of Civil Environmental and Geomatic Engineering UCL London United Kingdom Institute for Nanomaterials Advanced Technologies and Innovation Technical University of Liberec Studentská 1402/2 Liberec461 17 Czech Republic Institute of Analytical and Environmental Sciences National Tsing Hua University Hsinchu Taiwan Department of Environmental Engineering & Innovation and Development Center of Sustainable Agriculture National Chung Hsing University Taichung Taiwan Abadan University of Medical Sciences Abadan Iran

This study investigates the electrocoagulation/permanganate (EC/PM) process as a pre-treatment, followed by UV-activated peroxymonosulfate (PMS) and electro-peroxone (EP) treatments. This sequence is designed to effectively mineralize organic matter. Notably, PM was integrated into the EC process for the first time to enhance removal efficiency. The iron sludge generated from the EC/PM process (sludge-derived electrocoagulation;SDEC) was repurposed as a cost-effective source of iron oxide in the PMS/SDEC/UV treatment. Treatment optimization was achieved by adjusting the main operating parameters. A comprehensive analysis was conducted to assess the biodegradability and toxicity of the leachate post-treatment, including measurements of COD, BOD, TOC, ammonia levels, average oxidation state, biodegradability, organic carbon content, and spectroscopic methods. The results demonstrated substantial removal efficiencies across the treatment stages, with 98.9 % for COD, 94.9 % for BOD, 96.4 % for TOC, and 97.7 % for ammonia. Spectroscopic changes indicated that the leachate was broken down into smaller, more oxidized, and highly acidic molecules with an increased aliphatic structure while effectively eliminating aromatic compounds. The BOD5/COD ratio improved to 0.55, indicating that the treated leachate is suitable for biological treatment processes with significantly reduced toxicity. Overall, the sequence of treatment processes yielded promising results. © 2025 Elsevier Ltd

关键词： Electro-peroxone Electrocoagulation Landfill leachate Permanganate Peroxymonosulfate Sequential treatment

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