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IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Shang Wu Yijie Wang Science and Technology on Parallel and Distributed Processing Laboratory College of Computer National University of Defense Technology

Attack payloads are often short segments hidden in HTTP requests; thus they can be found by HTTP payload anomaly detection. Deep learning models learn data features during training without manual feature extraction, and better performance has received more attention. Recurrent Neural Network models process sequences directly, which are widely used in payload anomaly detection. However, due to the gradient vanishing problem, RNN has limits on processing the long sequences. Meanwhile, RNN uses its final hidden state for detection and pays more attention to the content of the end of the payload. Besides, deep learning generally lacks interpretability. The paper proposes an unsupervised deep learning model for HTTP payload Anomaly Detection, namely Attention-based Encoder-Decoder Recurrent Neural Networks Anomaly Detection model (AEDRAD). AEDRAD utilizes the encoder-decoder RNN and attention mechanism to detect anomalies by reconstructing the original sequences. AEDRAD filters the fields of HTTP protocol that cannot exist anomalies, focusing on the suspicious segments. Through the encoder-decoder network, the normal payload can be well-reconstructed while the anomaly payload fails. With the attention mechanism, AEDRAD generates practical features for further anomaly detection from a global perspective. Meanwhile, it marks abnormal fragments visually, which is conducive to a subsequent analysis by experts. The experimental results show that AEDRAD significantly outperforms three state-of-the-art unsupervised algorithms on two real datasets.

关键词： Deep learning Training Recurrent neural networks Protocols Focusing Manuals Feature extraction

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parallelization of Fast Monte Carlo Dose Calculation for Radiotherapy Treatment Planning on the ARMv8 Architecture

Parallelization of Fast Monte Carlo Dose Calculation for Rad...

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International Conference on Information science and technology (ICIST)

作者： Chi Jin Qinglin Wang Yang Zhao Yong Dou Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha China

Monte Carlo (MC) simulation plays a key role in radiotherapy. Since the simulation time of the MC program cannot fully meet the clinical requirements, we use the ARM-based FT-2000+ multi-core processor for parallelization, which provides an effective solution for accelerating MC dose calculation. In this paper, we implement and verify FT-DPM, which is an OpenMP-based MC Dose Planning Method on FT-2000+. FT-DPM utilizes the parallelism of MC simulation and the advantage of ARM architecture to achieve the parallelization on ARM architecture. Meanwhile, we optimize the original DPM program in terms of memory allocation, data structure and data type. The experiments show that, compared with the original DPM code, FT-DPM obtains very accurate results and reaches the maximum speedups of 155.94 times for the electron case. The parallel program based on FT-2000+ only takes 44.1 seconds to simulate the particle transport of 100 million times, showing good clinical application potential. In addition, the speedup and efficiency of FT-DPM running on different core counts are also discussed.

关键词： Monte Carlo methods Multicore processing Simulation Scalability parallel processing Data structures Load management

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City models: past, present and future prospects

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Frontiers of Urban and Rural Planning 2025年第1期3卷 1-24页

作者： Ritter, Helge Herzog, Otthein Rothermel, Kurt Cohn, Anthony G. Wu, Zhiqiang Faculty of Technology Bielefeld University Bielefeld Germany College of Architecture and Urban Planning Tongji University Shanghai People’s Republic of China FB 03 University of Bremen Bremen Germany Institute of Parallel and Distributed Systems University of Stuttgart Stuttgart Germany School of Computer Science University of Leeds Leeds UK The Alan Turing Institute London UK

This paper attempts to take a comprehensive look at the challenges of representing the spatio-temporal structures and dynamic processes that define a city’s overall characteristics. For the task of urban planning and urban operation, we take the stance that even if the necessary representations of these structures and processes can be achieved, the most important representation of the relevant mindsets of the citizens are, unfortunately, mostly neglected. After a review of major “traditional” urban models of structures behind urban scale, form, and dynamics, we turn to major recent modeling approaches triggered by recent advances in AI that enable multimodal generative models. Some of these models can create representations of geometries, networks and images, and reason flexibly at a human-compatible semantic level. They provide huge amounts of knowledge extracted from huge collections of text and image documents and cover the required rich representation spectrum including geographic knowledge by different knowledge sources, degrees of granularity and scales. We then discuss what these new opportunities mean for coping with the modeling challenges posed by cities, in particular with regard to the role and impact of citizens and their interactions within the city infrastructure. We propose to integrate these possibilities with existing approaches, such as agent-based models, which opens up new modeling spaces including rich citizen models which are able to also represent social interactions. Finally, we put forward some thoughts about a vision of a “social AI in a city ecosystem” that adds relevant citizen models to state-of-the-art structural and process models. This extended city representation will enable urban planners to establish citizen-oriented planning of city infrastructures, to make them into inviting environments that reconcile and foster human culture, city resilience and sustainability.

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Design and experimental study of the remote control for a novel patient transfer apparatus 5

Design and experimental study of the remote control for a no...

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2020 5th International Seminar on Computer technology, Mechanical and Electrical Engineering, ISCME 2020

作者： Tian, Yu Wang, Hongbo Zhang, Yongshun Tian, Junjie Du, Jiazheng Parallel Robot and Mechatronic System Laboratory of Hebei Province Yanshan University Qinhuangdao Hebei China Key Laboratory of Advanced Forging and Stamping Technology and Science of Ministry of Education Yanshan University Qinhuangdao Hebei China

This paper introduces the design of the remote control for a novel patient transfer apparatus. First, the overall design of the control system is put forward based on the working principle, and design requirements of the apparatus. Second, voltage regulator circuit of the remote control based on the MC34063 is designed to fit for the OLED displayer, parameters such as the filter capacitor have been determined. Next, wireless communication unit adopted CC1110 and the communication instruction code is introduced. Then, the interaction interface of the remote control is finished to facilitate the implementation of the adjustment functions. finally, a simulation and a real experiment has been completed, it indicates the correctness of the voltage regulator circuit and the effectiveness of the remote control respectively. © Published under licence by IOP Publishing Ltd.

关键词： Remote control

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Statistical Analysis of the MK-3 Customizable Authenticated Encryption

Statistical Analysis of the MK-3 Customizable Authenticated ...

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MILCOM, Military Communications Conference

作者： Peter Bajorski Alan Kaminsky Michael Kurdziel Marcin Łukowiak Stanisław Radziszowski School of Mathematical Sciences Rochester Institute of Technology Parallel Crypto LLC L3Harris Technologies Department of Computer Engineering Rochester Institute of Technology Department of Computer Science Rochester Institute of Technology

To provide security autonomy capability, such that different users can have independent variants of the encryption algorithm, MK-3 is designed to be customizable. Two levels of customization are supported, Factory Customization and Field Customization. Customization is done by modifying functions and function parameters in the algorithm to yield differing cipher functions while preserving the algorithm's security. The main goal of this work is to present the results from the statistical analysis of the customizable MK-3 encryption scheme, focusing on field customized mixers. We recall the main components of the MK-3 algorithm and overview a subset of available factory and field customizations for MK-3. We test the main instances of the field customized versions and give a general argument for their desired statistical properties expected from an encryption scheme.

关键词： Military communication Ciphers Statistical analysis Force Focusing Production facilities Encryption

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The Design of An Intelligent Self-Reconfigurable Single-Module Robot

The Design of An Intelligent Self-Reconfigurable Single-Modu...

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Electronic technology and Information science (ICETIS), International Conference on

作者： Zezheng Xing Qiuwei Zheng Lang Xiong Yundou Xu Laboratory of Parallel Robot and Mechatronic System of Hebei Province Yanshan University Qinhuangdao China School of Mechanical Engineering Yanshan University Qinhuangdao China Key Laboratory of Advanced Forging & Stamping Technology Science (Yanshan University) Ministry of Education of China Qinhuangdao China

ISBN: (数字)9798350388343

ISBN: (纸本)9798350388350

Self-reconfigurable robot is a typical modular robot, which is composed of a large number of identical modules based on cell design idea. Perform a job by combining it as a whole while working. At present, the carrying capacity of the self-reconfigurable robot is limited and the degree of intelligence is not high, which leads to the limited working ability of the self-reconfigurable robot. Therefore, an intelligent single-module self-reconfigurable robot is designed in this paper. Firstly, a high stiffness bidirectional butt locking mechanism is designed for the connection between modules. Secondly, aiming at the task of quick survey of fire rescue environment, the identification and distance detection of ignition point and rescue personnel are designed in the fire environment. The BI _ A * algorithm is used to complete the single-module path planning of the self-reconfigurable robot, and the Multi_ Bi _ A * algorithm is proposed for the optimal path planning of the collection of multi-module self-reconfigurable robots. Finally, the functional verification of the prototype is completed by using a single three-room model experiment platform.

关键词： Surveys Target recognition Prototypes Programming Multitasking Stability analysis Path planning

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LRCB: A Comprehensive Benchmark Evaluation of Reference-free Lossless Compression Tools for Genomics Sequencing Long Reads Data

LRCB: A Comprehensive Benchmark Evaluation of Reference-free...

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Data Compression Conference (DCC)

作者： Hui Sun Huidong Ma Yingfeng Zheng Haonan Xie Meng Yan Cheng Zhong Xiaoguang Liu Gang Wang Nankai-Baidu Joint Lab Parallel and Distributed Software Technology Lab College of Computer Science Nankai University Tianjin China School of Electrical Engineering Guangxi University Nanning China School of Computer Electronics and Information Guangxi University Nanning China

ISBN: (数字)9798350385878

ISBN: (纸本)9798350385885

The advancement of long reads sequencing technologies has led to a significant increase in biological sequencing big data. Although several reference-free compressors are available for saving long reads data storage space, choosing the suitable one is challenging due to the shortage of thorough and systematic evaluations of their lossless compression effectiveness, both dedicated and general-purpose. In this study, we performed benchmark examinations on 30 compressors, including 11 specialized for long reads and 19 general-purpose ones, using 31 real-world datasets with differing sequencing platforms, species, and lengths. Each lossless compressor was evaluated on 13 performance measures, including compression strength, compression robustness, as well as time and peak memory required for compression and decompression. Additionally, for future long reads data compressors, we outlined investigation directions with consideration for privacy-sensitive sequences data security, hardware parallel acceleration, parameter tuning framework, and system hardware-algorithm integration design. We summarized the results as the Long Reads Compression Benchmark, available at https://***/fahaihi/LRCB.

关键词： Sequential analysis Systematics Memory management Benchmark testing Compressors Loss measurement Time measurement

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NKMH: A Neural Efficient Recommendation Based on Neighborhood Key Information Aggregation of Modified Hawkes

NKMH: A Neural Efficient Recommendation Based on Neighborhoo...

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IEEE Annual International Computer Software and Applications Conference (COMPSAC)

作者： Xin Xu Nan Wang Hu Jin Yang Liu Kun Li Key Laboratory of Database and Parallel Computing of Heilongjiang Province School of Computer Science and Technology Heilongjiang University Harbin China Postdoctoral Program of Heilongjiang Hengxun Technology Co. Ltd School of Computer Science and Technology Heilongjiang University Harbin China

ISBN: (数字)9781665488105

ISBN: (纸本)9781665488112

The rapid development of neural networks has con-tributed to the increasing maturity of recommendation systems. However, deep neural networks have poor interpretability for models and do not show strong advantages for sparse data and noisy data. Recently, Hawkes process has become more and more focused for its good interpretability with probabilistic models. Based on this, we proposes A Neural Efficient Recommendation Model Based on Neighborhood Key Information Aggregation of Modified Hawkes(NKMH). The model utilizes a neural network and designs three modules to jointly fit the modified Hawkes process. It not only inherits the high interpretability of Hawkes, but also effectively solves the problem of poor prediction ability of the Hawkes process. Besides, we present a novel key information search strategy(KISS), which can effectively remove the noise in a session and alleviate the sparsity of the data to some extent. Extensive experiments on two datasets show that the NKMH model outperforms many current popular models.

关键词： Deep learning Conferences Neural networks Predictive models Search problems Probabilistic logic Software

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Fast Maxwell Solvers Based on Exact Discrete Eigen-Decompositions I. Two-Dimensional Case

arXiv

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arXiv 2025年

作者： Wang, Lixiu Jia, Lueling Cao, Zijian Li, Huiyuan Zhang, Zhimin School of Mathematics and Physics University of Science and Technology Beijing Beijing100083 China School of Mathematics and Statistics Shandong Normal University Jinan250358 China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing101408 China State Key Laboratory of Computer Science Laboratory of Parallel Computing Institute of Software Chinese Academy of Sciences Beijing100190 China Department of Mathematics Wayne State University DetroitMI48202 United States

In this paper, we propose fast solvers for Maxwell’s equations in rectangular domains. We first discretize the simplified Maxwell’s eigenvalue problems by employing the lowest-order rectangular Nédélec elements and derive the discrete eigen-solutions explicitly, providing a Hodge-Helmholtz decomposition framework at the discrete level. Based on exact eigen-decompositions, we further design fast solvers for various Maxwell’s source problems, guaranteeing either the divergence-free constraint or the Gauss’s law at the discrete level. With the help of fast sine/cosine transforms, the computational time grows asymptotically as O(n2 log n) with n being the number of grids in each direction. Our fast Maxwell solvers outperform other existing Maxwell solvers in the literature and fully rival fast scalar Poisson/Helmholtz solvers based on trigonometric transforms in either efficiency, robustness, or storage complexity. It is also utilized to perform an efficient pre-conditioning for solving Maxwell’s source problems with variable coefficients. Finally, numerical experiments are carried out to illustrate the effectiveness and efficiency of the proposed fast *** Codes 65N30, 35Q61, 65F05, 68W40 © 2025, CC BY.

关键词： Maxwell equations

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Optimizing All-to-All Collective Communication on Tianhe Supercomputer

Optimizing All-to-All Collective Communication on Tianhe Sup...

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IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Jintao Peng Jie Liu Yi Dai Min Xie Chunye Gong National University of Defense Technology ChangSha China Science and Technology on Parallel and Distributed Processing Laboratory NUDT Changsha China Changsha and Laboratory of Software Engineering for Complex System NUDT Changsha China

All-to-all communication has a wide range of ap-plications in parallel applications like FFT. On most supercom-puters, there are multiple cores in a node. Message aggregation is an efficient method for smaller messages. Using multi-leader to aggregate message show significant improvement in intra-node overhead. However, compared to one-leader aggregation, existing multi-leader design incurs more message count and less aggregated message size. This paper proposes an Overlapped Multi-worker Multi-port all-to-all (OVALL) to scale the message size and parallelism of the aggregation algorithm. The algorithm exploits the all-to-all multi-core parallelism, concurrent commu-nication, and overlapping capabilities. Experiment results show that, compared to systems built-in MPI, OVALL'implementation achieves up to 5.9x or 18x speedup compared to MPI on different HPC systems. For the Fast Fourier Transform (FFT) application, OVALL is up to 2.7x (8192 cores, system A) or 5.6x (4800 cores, system B) faster compared to built-in MPI on peak performance.

关键词： Multicore processing Fast Fourier transforms Scalability Aggregates Supercomputers Libraries Pipeline processing

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