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7th IEEE International Conference on Smart Cloud, SmartCloud 2022

作者： Chen, Lin Yu, Qingchun Liang, Wei Cai, Jiahong Zhu, Hangyu Xie, Songyou Hunan University of Science and Technology Hunan Key Laboratory for Service computing and Novel Software Technology School of Computer Science and Engineering Xiangtan China Shenzhen Research Institute Sun Yat-sen University and Novel Software Technology ShenZhen China Hunan University College of Computer Science and Electronic Engineering Changsha China

ISBN: (数字)9781665451796

ISBN: (纸本)9781665451796

With the increasing growth of electronic medical data, the difficulties of data sharing among medical institutions and the leakage of data privacy have become the focus of the public and medical workers. The blockchain has the characteristics of decentralization, traceability, and immutability, which can provide new ideas for fine-grained secure access to medical research. This article first introduces blockchain and blockchain-based privacy protection technology;then analyzes the advantages and disadvantages of electronic medical records, and introduces the current development status of electronic medical records based on blockchain technology;then from data encryption, access the three aspects of control and transaction anonymity introduce the medical data privacy protection method based on blockchain technology;finally, the full text is summarized and prospected. © 2022 IEEE.

关键词： Blockchain

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Quantum and classical query complexities for determining connectedness of matroids

arXiv

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arXiv 2023年

作者： Huang, Xiaowei Feng, Shiguang Li, Lvzhou Institute of Quantum Computing and and Software School of Computer Science and Engineering Sun Yat-sen University Guangzhou510006 China

Connectivity is a fundamental structural property of matroids, and has been studied algorithmically over 50 years. In 1974, Cunningham proposed a deterministic algorithm consuming O(n2) queries to the independence oracle to determine whether a matroid is connected. Since then, no algorithm, not even a random one, has worked better. To the best of our knowledge, the classical query complexity lower bound and the quantum complexity for this problem have not been considered. Thus, in this paper we are devoted to addressing these issues, and our contributions are threefold as follows: (i) First, we prove that the randomized query complexity of determining whether a matroid is connected is Ω(n2) and thus the algorithm proposed by Cunningham is optimal in classical computing. (ii) Second, we present a quantum algorithm with O(n3/2) queries, which exhibits provable quantum speedups over classical ones. (iii) Third, we prove that any quantum algorithm requires Ω(n) queries, which indicates that quantum algorithms can achieve at most a quadratic speedup over classical ones. Therefore, we have a relatively comprehensive understanding of the potential of quantum computing in determining the connectedness of matroids. © 2023, CC BY.

关键词： Quantum theory

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Energy and Exergy-Aware Workload Assignment for Air-Cooled Data Centers 21

Energy and Exergy-Aware Workload Assignment for Air-Cooled D...

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12th ACM International Conference on Future Energy Systems, e-Energy 2021

作者： Gupta, Rohit Down, Douglas G. Puri, Ishwar K. Department of Mechanical Engineering McMaster University HamiltonON Canada Department of Computing and Software McMaster University HamiltonON Canada

ISBN: (纸本)9781450383332

The energy required to cool a data center (DC) depends on both thermal and workload management. Although existing energy-and temperature-aware workload assignment approaches reduce operational expenditure by minimizing cooling energy consumption, they do not address the loss of available cooling capacity (i.e., loss of thermodynamic exergy) due to unavoidable system inefficiencies. By quantifying the exergy efficiency, the actual cooling COP and maximum achievable COP during operation can be embedded in the DC control system. A multi-objective optimization problem is formulated that quantifies the tradeoff between energy and exergy efficiencies. By reducing the exergy loss, the available cooling capacity, and therefore the capital expenditure can be effectively utilized, potentially reducing the total cost of ownership. We identify scenarios when significant improvements in the utilization of cooling capacity are possible with only small increases in energy consumption. © 2021 ACM.

关键词： Multiobjective optimization

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Unveiling Public Perception of ChatGPT Through Twitter Data and Machine Learning 4

Unveiling Public Perception of ChatGPT Through Twitter Data ...

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4th International Conference on Data Analytics for Business and Industry, ICDABI 2023

作者： Abishethvarman, Vadivel Banujan, Kuhaneswaran Wijeratne, Ashansa Nirubikaa, Ravikumar Kumara, Samantha Prasanth, Senthan Sabaragamuwa University of Sri Lanka Department of Computing and Information Systems Belihuloya Sri Lanka Sabaragamuwa University of Sri Lanka Department of Software Engineering Belihuloya Sri Lanka Sabaragamuwa University of Sri Lanka Department of Physical Sciences and Technology Belihuloya Sri Lanka

ISBN: (纸本)9798350369786

The study comprehensively analysed public sentiment towards ChatGPT, a language processing AI tool, using approximately 135,000 tweets from an initial dataset of 236,275 entries. After cleaning and pre-processing the data using basic NLP techniques, Machine Learning (ML) models - Long Short-Term Memory (LSTM), Decision Tree (DT), and Support Vector Machine (SVM) - were applied to classify the tweets into positive, negative, and neutral categories. The LSTM model demonstrated superior performance across all evaluation metrics - accuracy, precision, recall, and F1 score - for all tweet categories. Word clouds generated for each category revealed that the most frequent words in positive tweets included 'student,' 'education,' 'research,' and 'teacher,' indicating a strong association of ChatGPT with educational and research contexts. Similarly, 'AI,' 'student,' 'research,' 'course,' and 'education' dominated neutral and negative tweets, highlighting prevalent discussion topics. However, the study had limitations, including dependency on a single dataset, potential loss of contextual information during pre-processing, and a focus on English tweets only. Despite these limitations, the study provides valuable insights into the public's perception of ChatGPT, underscoring its significant association with education and research and the effectiveness of the LSTM model in classifying tweets. The findings suggest that future research should incorporate diverse data sources and languages better to understand global sentiment towards ChatGPT and similar AI tools. © 2023 IEEE.

关键词： Tweets

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Process Mining representation using Communication Structured Acyclic Nets (CSA-nets)

Process Mining representation using Communication Structured...

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2024 International Workshop on Petri Nets and software engineering, PNSE 2024

作者： Almutairi, Nadiyah Alshammari, Tuwailaa Alahmadi, Mohammed School of Computing Newcastle University Science Square Newcastle upon TyneNE4 5TG United Kingdom Department of Science and Technology University of Hafr Albatin Hafr Al-Batin39524 Saudi Arabia Department of Software Engineering University of Jeddah Jeddah21493 Saudi Arabia

Communication Structured Acyclic Nets (CSA-nets) are derived from Structured Occurrence Nets SON which are a Petri net-based formalism used to represent the behaviour of Complex Evolving Systems (CESs). It consists of sets of Acyclic Nets ANs that communicate with each other through a set of buffer places. It supports the analysis and visualisation of activities of CESs. In this work, we use SONs formalism to represent processes that have been decomposed using approaches in [1], we used SONs to compose the subnets and use its robust representation to analyse and visualise the same model, however, without any existing cycles. Our approach provides a mechanism for composing a SON model by using the decomposed subnets. We argue that the resulting model exhibits similar behaviour to the original model. © 2024 Copyright for this paper by its authors.

关键词： Petri nets

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Faceswap Finder: A Fusion-Based Deepfake Detection Technique

Faceswap Finder: A Fusion-Based Deepfake Detection Technique

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International Conference on Advancements in Computational Sciences (ICACS)

作者： Nimra Basit Fatima Khalid Qurat Ul Ain Maria Andleeb Department of Software Engineering University of Engineering and Technology Taxila Pakistan Faculty of Computer Sciences and Engineeing GIKI Topi Pakistan Department of Computing Shifa Tameer-e-Millat University PRC Islamabad Pakistan

ISBN: (数字)9798331533038

ISBN: (纸本)9798331533045

The significant improvement in deepfake generation algorithms has made possible the manipulation of visual data. The advancement of GAN technology and tools has made it relatively simple to use source and target photos and build realistic deepfakes. The challenges associated with deepfakes include political defamation, impersonation, misinformation, and cyberstalking. The generation of deepfakes through faceswap approach hinders the detection oftentimes as it spans numerous artifacts – illumination, facial skin tones, and other conditions. Existing techniques do not employ robust mechanisms to detect such deepfakes either due to computational inefficiency or focusing on a few parameters for decision-making. To counteract these dangers, a robust deepfake detection model must be developed and implemented. This paper proposes Efficient-Fused Net (EF-Net) - a transfer learning approach to two EfficientNet-B5 models with partial freezing between its layers that can differentiate between real and fake images generated from faceswap implementation. We evaluated our model’s performance using the challenging deepfake subset of the extensive and varied FaceForensics++ and DFDC-Preview datasets. The proposed method outperforms state of the art methods in the detection of faceswap deepfakes, surpassing the performance by $89.19 \%$ accuracy on DFDC-Preview and $\mathbf{9 7 . 7 0 \%}$ of Deepfakes subset of FaceForensics++.

关键词： Deepfakes Visualization Computational modeling Transfer learning Decision making Lighting Focusing Skin Robustness Resilience

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Comparative Analysis of Differential Privacy Implementations on Synthetic Data

Comparative Analysis of Differential Privacy Implementations...

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IEEE Annual computing and Communication Workshop and Conference (CCWC)

作者： Huwida E. Said Qusay H. Mahmoud Mandeep Goyal Faiza Hashim Department of Computing and Applied Technolgy College of Technological Innovation Zayed University Dubai UAE Department of Electrical Computer and Software Engineering Ontario Tech University Oshawa ON Canada Department of Computer Science and Software Engineering College of Information Technology UAE University AI-Ain UAE

ISBN: (数字)9798331507695

ISBN: (纸本)9798331507701

Differential privacy offers a promising solution to balance data utility and user privacy. This paper compares two prominent differential privacy tools-PyDP and IBM's diffprivlib-that are applied to a synthetic dataset with medical attributes. We evaluate these tools based on their effectiveness in maintaining data privacy while preserving the statistical integrity of the data. Our results reveal that PyDP provides synthetic data that closely matches real-world data, making it appropriate for tasks requiring accuracy while striking a better balance between data utility and privacy. However, IBM's diffprivlib is more suitable for privacy-critical applications due to its stronger privacy guarantees, but at the cost of increased noise and decreased data utility. This paper contributes to the practical understanding of implementing differential privacy in machine learning and software applications and enhances the tools available for developers in sensitive data environments.

关键词： Differential privacy Costs Accuracy Conferences Noise Machine learning software Synthetic data

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Finite-Time Probabilistic Impulsive Synchronization for Fuzzy Multiplicative Stochastic Coupled Memristive Neural Networks

SSRN

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SSRN 2024年

作者： Yang, Nijing Peng, Hong Lu, Xiang Wang, Xiangxiang Deng, Ping School of Computer and Software Engineering Xihua University Chengdu610039 China Ascend Computing Product Department Huawei Technologies Co Ltd Chengdu610041 China School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu610054 China

In this paper, the finite-time synchronization (FTS) of T-S fuzzy multiplicative stochastic coupled memristive neural networks (CMNNs) with probabilistic delayed impulsive effects is investigated. First, a novel CMNNs model is designed, in which mismatched parameters and adjustable coupling strength are considered to ensure accuracy of the CMNNs. Meanwhile, because the multiplicative noise, which is different from external input noise, is inevitable in information transmission. The multiplicative noise is considered in the CMNNs. Then, the impulsive controller with fuzzy impulsive strength is introduced to enhance the robustness of the system. To be more practical, the probabilistic time delays are analyzed in the controller. Moreover, finite-time stability theory and impulsive control theory are utilized to establish some sufficient conditions for FTS with synchronizing impulses and desynchronizing impulses on CMNNs. Further more, the upper bounds for settling time of synchronization are effectively estimated. Finally, a numerical example is provided to illustrate the effectiveness of the main results. © 2024, The Authors. All rights reserved.

关键词： Stochastic systems

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Exploiting the sequential nature of genomic data for improved analysis and identification

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Computers in Biology and Medicine 2024年 183卷 109307-109307页

作者： Nawaz, M. Saqib Nawaz, M. Zohaib Junyi, Zhang Fournier-Viger, Philippe Qu, Jun-Feng College of Computer Science and Software Engineering Shenzhen University China Faculty of Computing and Information Technology Department of Computer Science University of Sargodha Pakistan School of Computer Engineering Hubei University of Arts and Science Hubei Xiangyang China

Genomic data is growing exponentially, posing new challenges for sequence analysis and classification, particularly for managing and understanding harmful new viruses that may later cause pandemics. Recent genome sequence classification models yield promising performance. However, the majority of them do not consider the sequential arrangement of nucleotides and amino acids, a critical aspect for uncovering their inherent structure and function. To overcome this, we introduce GenoAnaCla, a novel approach for analyzing and classifying genome sequences, based on sequential pattern mining (SPM). The proposed approach first constructs and preprocesses datasets comprising RNA virus genome sequences in three formats: nucleotide, coding region, and protein. Then, to capture sequential features for the analysis and classification of viruses, GenoAnaCla extracts frequent sequential patterns and rules in three forms and in codons. Eight classifiers are utilized, and their effectiveness is assessed by employing a variety of evaluation metrics. A performance comparison demonstrates that the suggested approach surpasses the current state-of-the-art genome sequence classification and detection techniques with a 3.18% performance increase in accuracy on average. © 2024 Elsevier Ltd

关键词： Genome

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Formal Timing Analysis and Verification of the Interrupt-driven Programs for ISO26262

Formal Timing Analysis and Verification of the Interrupt-dri...

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2025 2nd International Conference on Algorithms, software engineering and Network Security (ASENS)

作者： Qing She He Huang Shenglin Bao Xin Guo National Trusted Embedded Software Engineering Technology Research Center East China Normal University / Shanghai Huayuan Chuangxin Software Co. Ltd China High end Equipment Systems Department Shanghai Huayuan Chuangxin Software Co. Ltd China Basic Software Department East China Institute of Computing Technology China National Trusted Embedded Software Engineering Technology Research Center East China Normal University China

ISBN: (数字)9798331520298

ISBN: (纸本)9798331520304

Safety-critical systems refer to software systems whose operation can affect the safety of people and facilities used in the automotive industry, aerospace, and hospital health care systems. The high level of safety of software in the aforementioned fields has often drawn attention. ISO26262 has been issued for the automotive industry, which defines standards and procedures, including software level, software development standards, and software validation standards to ensure the high level of safety of software. In high-safety automotive software, a real-time safeguard requires the analysis of interrupt-driven programming. Such analysis presents a challenging and complex task because of the uncertainty of interrupts. In ISO26262, the formalized method is suggested to verify the process of software development. To achieve the verification goals defined in ISO26262, we use a formal method instead of traditional verification methods to analyze worst-case execution time. We analyze interrupt-driven programs from the perspective of timeliness and present the Interrupt Control Flow Graph (ICFG), which is used to describe the control flow of interrupt-driven programs. The execution of interrupts may largely increase the number of program states, potentially leading to state explosion, resulting in a sizable ICFG. To solve this problem, we propose an algorithm for reducing the size of ICFG. On the basis of the reduced ICFG, the worst-case execution path can be determined and thus be used to verify whether the program execution time exceeds the expected time and identify the execution path that may cause a timeout problem.

关键词： Industries Uncertainty software algorithms software systems Timing Flow graphs Standards Automotive engineering software development management software engineering

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