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19th International Conference on Machine Learning and Cybernetics, ICMLC 2020

作者： Mashiat, Afsara Akhlaque, Reza Rifat Fariha, Fahmeda Hasan Reza, Tanzim Rahman, Md Anisur Parvez, Mohammad Zavid Brac University Software Engineering and HCI Research Group Department of Computer Science and Engineering Bangladesh Charles Sturt University School of Computing and Mathematics Australia

ISBN: (纸本)9780738124261

As brain is the most vital organ of the human body, the affects of brain related diseases can be severe. One of the most harmful diseases is brain tumor, which results in a very short life expectancy of the affected patient. Detection of brain tumor is a challenging task in the early stages. Still, with the help of modern technology and machine learning algorithms, it has become a matter of great interest for research. While detecting the brain tumor of an affected person, we are considering the fMRI data of the patient. Our aim is to identify whether the tumor is present in the patient's brain or not. We use a Convolutional Neural Network(CNN) that is good enough to generate high accuracy. We have used some deeper architecture design VGG16, VGG19, and Inception v3 for better accuracy. Three classification techniques are used namely binary classification, lobe based classification, and position based classification. The main contribution of our proposed work is that we have identified the specific region of the brain where the tumor is located. The region-based classification distinguishes our work from others that are applied on the same dataset. For binary classification, we found approximately 95% accuracy from all the three architectures. Furthermore, we found approximately 78% accuracy for lobe based classification and approximately 97% accuracy for position based classification. The experimental results indicate the superiority of our proposed method in terms of identifying the brain tumor. © 2020 IEEE.

关键词： Brain

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software Development Practice: How Organisation Dynamics Inhibit the Utilization of Process Tools in Small software Companies 21

Software Development Practice: How Organisation Dynamics Inh...

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Proceedings of the 10th International Conference on software and Information engineering

作者： Micheal Tuape Victoria Hasheela-Mufeti Petrus Iiyambo Anna Kayanda Jussi Kasirinen Department of Software Engineering Lappeenranta_Lahti University of Technology Finland Department of Computing Mathematical and Statistical Sciences University of Namibia Namibia Information Systems Department. College of Business Education Dar-es Salaam Tanzania

ISBN: (纸本)9781450384315

Low-quality software products are synonymous with small software companies, yet thousands of process tools and methods are available, although unfortunately, they remain unutilized. The utilization of these process tools are said to be very challenging to small software companies with the difficulty of adaptability tagged to the context in which the companies operate since the process tools are not designed to take care of the operational context of the small software companies. This survey study was undertaken to empirically investigate the implication of the organizational dynamics on using process tools in SSCs. A total of 115 respondents from Tanzania, Namibia, and Ghana were reached through a structured questionnaire. Our findings reveal that the ad-hoc behaviors and attitude breed a culture that inhibits procedural and process-intensive practices synonymous with most software engineering process tools. This finding is interesting because this area has been underestimated while looking at software practice, yet it is significant in understanding practice in relation to software process tools, significantly how small software companies can be helped to adopt the different tools and also provide a mechanism to help the designers of process tools make tools that are usable in the context of the practice of SSCs.

关键词： Utilization of process tools Organisation dynamics software development practice Small software companies

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Asynchronous Federated Clustering with Unknown Number of Clusters 39

Asynchronous Federated Clustering with Unknown Number of Clu...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Zhang, Yunfan Zhang, Yiqun Lu, Yang Li, Mengke Chen, Xi Cheung, Yiu-Ming School of Computer Science and Technology Guangdong University of Technology Guangzhou China Fujian Key Laboratory of Sensing and Computing for Smart City School of Informatics Xiamen University Xiamen China College of Computer Science and Software Engineering Shenzhen University Shenzhen China Department of Computer Science Hong Kong Baptist University Hong Kong

ISBN: (纸本)157735897X

Federated Clustering (FC) is crucial to mining knowledge from unlabeled non-Independent Identically Distributed (non-IID) data provided by multiple clients while preserving their privacy. Most existing attempts learn cluster distributions at local clients, then securely pass the desensitized information to the server for aggregation. However, some tricky but common FC problems are still relatively unexplored, including the heterogeneity in terms of clients’ communication capacity and the unknown number of proper clusters. To further bridge the gap between FC and real application scenarios, this paper first shows that the clients’ communication asynchrony and unknown proper cluster numbers are complex coupling problems, and then proposes an Asynchronous Federated Cluster Learning (AFCL) method accordingly. It spreads the excessive number of seed points to clients as a learning medium and coordinates them across clients to form a consensus. To alleviate the distribution imbalance cumulated due to the unforeseen asynchronous uploading from the heterogeneous clients, we also design a balancing mechanism for seeds updating. As a result, the seeds gradually adapt to each other to reveal a proper number of clusters. Extensive experiments demonstrate the efficacy of AFCL. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Federated learning

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Impact of Data Leakage in Vibration Signals Used for Bearing Fault Diagnosis

SSRN

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SSRN 2024年

作者： Wheat, Lesley von Mohrenschildt, Martin Habibi, Saeid Al-Ani, Dhafar Department of Computing and Software McMaster University 1280 Main St W HamiltonONL8S4L7 Canada Department of Mechanical Engineering McMaster University 1280 Main St W HamiltonONL8S4L7 Canada Department of Electrical and Computer Engineering McMaster University 1280 Main St W HamiltonONL8S4L7 Canada

Bearing fault diagnosis is a well-developed field and an active area of research in which the combination of model-free machine learning techniques with vibration data has become a popular approach. However, vibration data from rotating machines has the potential to contain domain shifts beyond the accepted causes in this research area (different part models, operating conditions and sensor locations) which can enable data leakage between training and test datasets. To examine the impact of data leakage, six straightforward bearing diagnosis methods are applied to two datasets using three data splitting methods to compare classification performance. Diagnosis is preformed using Principal Component Analysis (PCA), Supervised Principal Component Analysis (SPCA) and Linear Discriminant Analysis (LDA) in combination with frequency analysis and envelope analysis feature extraction methods. Datasets from McMaster University and Paderborn University are used as experimental data sources, and produce vastly differing results depending on the selected dataset splitting method. Despite great results for diagnosis methods using frequency response analysis on the data from McMaster, these results are not expected to generalize due to possible data leakage within the vibration data itself and the limited number of parts within the dataset. © 2024, The Authors. All rights reserved.

关键词： Failure analysis

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Improved Fireworks Optimization Algorithm for Multi-product Human-robot Collaborative Hybrid Disassembly Line Balancing

Improved Fireworks Optimization Algorithm for Multi-product ...

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IEEE International Conference on Human-Machine Systems

作者： Feng Guo Xiwang Guo Jiacun Wang Weitian Wang Jinrui Cao Imane Bigaume Information and Control Engineering Liaoning Petrochemical University Fushun China Computer Science and Software Eng. Monmouth University Wes Long Branch New Jersey USA School of Computing Montclair State University Montclair USA Computer Science Department New Jersey City University Jersey City USA

ISBN: (数字)9798350315790

ISBN: (纸本)9798350315806

In the remanufacturing process, the efficient disassembly of end-of-life (EOL) products assumes paramount significance for recycling endeavors. This work introduces a novel disassembly model aiming at enhancing disassembly efficiency within a hybrid disassembly line through the strengths of humanrobot collaboration. In order to optimize the generation of disassembly sequences, this work proposes an improved fireworks optimization algorithm (IFW) that combines uniform mutation and two-point crossover methods. Afterwards, the model’s validity and algorithmic accuracy are substantiated using the CPLEX solver (a commercial solver). Furthermore, a comparative analysis and evaluation against alternative algorithms, such as salp swarm algorithm (SSA) and whale optimization algorithm (WOA), demonstrate a better stability of the proposed algorithm in the human-robot collaborative hybrid disassembly line balancing problem.

关键词： Accuracy Human-machine systems Collaboration Programming Stability analysis Whale optimization algorithms Recycling

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Explicit synchronous partitioned scheme for coupled reduced order models based on composite reduced bases

arXiv

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arXiv 2023年

作者： de Castro, Amy Bochev, Pavel Kuberry, Paul Tezaur, Irina Department of Mathematics Clemson University United States Center for Computing Research Sandia National Laboratories AlbuquerqueNM87185 United States Quantitative Modeling & Software Engineering Department Sandia National Laboratories P.O. Box 969 LivermoreCA94551-0969 United States

This paper formulates, analyzes and demonstrates numerically a method for the explicit partitioned solution of coupled interface problems involving combinations of projection-based reduced order models (ROM) and/or full order models (FOMs). The method builds on the partitioned scheme developed in [1], which starts from a well-posed formulation of the coupled interface problem and uses its dual Schur complement to obtain an approximation of the interface flux. Explicit time integration of this problem decouples its subdomain equations and enables their independent solution on each subdomain. Extension of this partitioned scheme to coupled ROM-ROM or ROM-FOM problems requires formulations with non-singular Schur complements. To obtain these problems, we project a well-posed coupled FOM-FOM problem onto a composite reduced basis comprising separate sets of basis vectors for the interface and interior variables, and use the interface reduced basis as a Lagrange multiplier. Our analysis confirms that the resulting coupled ROM-ROM and ROM-FOM problems have provably non-singular Schur complements, independent of the mesh size and the reduced basis size. In the ROM-FOM case, analysis shows that one can also use the interface FOM space as a Lagrange multiplier. We illustrate the theoretical and computational properties of the partitioned scheme through reproductive and predictive tests for a model advection-diffusion transmission problem. © 2023, CC BY.

关键词： Galerkin methods

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Detection of stress for visually impaired people using EEG signals based on time-frequency domain analysis 19

Detection of stress for visually impaired people using EEG s...

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19th International Conference on Machine Learning and Cybernetics, ICMLC 2020

作者： Sultana, Samia Rahman, Md Anisur Zavid Parvez, Mohammad BRAC University Software Engineering and HCI Research Group Department of Computer Science and Engineering Bangladesh Charles Sturt University School of Computing and Mathematics Australia

ISBN: (纸本)9780738124261

Stress refers to body's physical, emotional and psychological reaction to any environmental change needing adjustment with major impact on human psychology. Stress is specially difficult to manage for visually impaired people (VIP) as they can become easily stressed in unknown situations. Electroencephalogram (EEG) signals can be used to detect stress as it basically represents the ongoing electrical signal changes in human brain. Literature shows that the stress detection techniques are mostly based on either time or frequency domain analysis. However, using either time or frequency domain analysis may not be sufficient to provide appropriate outcome for stress detection. Hence, in this paper a method is proposed using empirical mode decomposition (EMD) and short-term Fourier transform (STFT) are used to extract features considering spatio-temporal information from EEG signals. In the EMD, the signal is first decomposed into intrinsic mode functions (IMFs) representing a finite number of signals while maintaining the time domain and STFT is used to convert time domain to time-frequency domain. Support vector machine (SVM) is applied to classify the stress of VIP in unfamiliar indoor environments. The performance of the proposed method is compared with a state-of-the-art technique for stress detection. The experimental results demonstrate the superiority of the proposed technique over the existing technique. © 2020 IEEE.

关键词： Empirical mode decomposition

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Improved lattice-based CCA2-secure PKE in the standard model

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Science China(Information Sciences) 2020年第8期63卷 147-168页

作者： Jiang ZHANG Yu YU Shuqin FAN Zhenfeng ZHANG State Key Laboratory of Cryptology Guangdong Provincial Key Laboratory of Data Security and Privacy Protection Jinan University Department of Computer Science and Engineering Shanghai Jiao Tong University Trusted Computing and Information Assurance Laboratory Institute of SoftwareChinese Academy of Sciences

Based on the identity-based encryption(IBE) from lattices by Agrawal et al.(Eurocrypt’10),Micciancio and Peikert(Eurocrypt’12) presented a CCA1-secure public-key encryption(PKE), which has the best known efficiency in the standard model and can be used to obtain a CCA2-secure PKE from lattices by using the generic BCHK transform(SIAM J Comput, 2006) with a cost of introducing extra overheads to both computation and storage for the use of other primitives such as signatures and commitments. In this paper, we propose a more efficient standard model CCA2-secure PKE from lattices by carefully combining a different message encoding(which encodes the message into the most significant bits of the LWE’s "secret term") with several nice algebraic properties of the tag-based lattice trapdoor and the LWE problem(such as unique witness and additive homomorphism). Compared to the best known lattice-based CCA1-secure PKE in the standard model due to Micciancio and Peikert(Eurocrypt’12), we not only directly achieve the CCA2-security without using any generic transform(and thus do not use signatures or commitments), but also reduce the noise parameter roughly by a factor of 3. This improvement makes our CCA2-secure PKE more efficient in terms of both computation and storage. In particular, when encrypting a 256-bit(respectively,512-bit) message at 128-bit(respectively, 256-bit) security, the ciphertext size of our CCA2-secure PKE is even 33%–44%(respectively, 36%–46%) smaller than that of their CCA1-secure PKE.

关键词： lattice public-key encryption chosen ciphertext security standard model

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Weighted Poisson-disk Resampling on Large-Scale Point Clouds

arXiv

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arXiv 2024年

作者： Jiao, Xianhe Lv, Chenlei Zhao, Junli Yi, Ran Wen, Yu-Hui Pan, Zhenkuan Wu, Zhongke Liu, Yong-Jin College of Computer Science and Technology Qingdao University China College of Computer Science and Software Engineering Shenzhen University China Department of Computer Science and Engineering Shanghai Jiao Tong University China School of Computer Science & Technology Beijing Jiaotong University China School of Artificial Intelligence Beijing Normal University China Department of Computer Science and Technology MOE-Key Laboratory of Pervasive Computing Tsinghua University China

For large-scale point cloud processing, resampling takes the important role of controlling the point number and density while keeping the geometric consistency. However, current methods cannot balance such different requirements. Particularly with large-scale point clouds, classical methods often struggle with decreased efficiency and accuracy. To address such issues, we propose a weighted Poisson-disk (WPD) resampling method to improve the usability and efficiency for the processing. We first design an initial Poisson resampling with a voxel-based estimation strategy. It is able to estimate a more accurate radius of the Poisson-disk while maintaining high efficiency. Then, we design a weighted tangent smoothing step to further optimize the Voronoi diagram for each point. At the same time, sharp features are detected and kept in the optimized results with isotropic property. Finally, we achieve a resampling copy from the original point cloud with the specified point number, uniform density, and high-quality geometric consistency. Experiments show that our method significantly improves the performance of large-scale point cloud resampling for different applications, and provides a highly practical solution. Copyright © 2024, The Authors. All rights reserved.

关键词： Poisson distribution

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Timely status update: Should ARQ be used in two-hop networks?

arXiv

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arXiv 2022年

作者： Feng, Jian Pan, Haoyuan Chan, Tse-Tin Liang, Jiaxin College of Computer Science and Software Engineering Shenzhen University Shenzhen China Department of Computing The Hang Seng University of Hong Kong Hong Kong Hong Kong Department of Information Engineering The Chinese University of Hong Kong Hong Kong Hong Kong

This paper investigates the information freshness of two-hop networks. Age of information (AoI) is used as the metric to characterize the information freshness, defined as the time elapsed since the latest received status update was generated. In error-prone wireless networks, prior studies indicated that Automatic Repeat-reQuest (ARQ) does not help improve the average AoI performance of single-hop networks, because sending a new packet always carries the most up-to-date information (i.e., discarding the old packet). We believe that this observation does not apply to two-hop networks. For example, when a packet transmission fails in the second hop, although a new packet has more recent information, it may require more time to be delivered (i.e., the communication has to restart from the first hop), thus leading to a high AoI. This paper analyzes the theoretical average AoI of two-hop networks with and without ARQ. Specifically, we model the two schemes using Markov chains, from which we derive the average AoI. Our theoretical and simulation results confirm that, unlike single-hop networks, ARQ should be used in two-hop networks to achieve lower average AoI. In particular, when ARQ is used, the successful decoding probability of the second hop has a greater impact on the average AoI than that of the first hop. Overall, our findings provide insight into the ARQ design for two-hop timely status update systems. Copyright © 2022, The Authors. All rights reserved.

关键词： Error correction

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