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An Exploration Study on Developing Blockchain Systems - the Practitioners' Perspective

information and software Technology 2025年

作者： Bakheet Aljedaani Aakash Ahmad Mahdi Fehmideh Arif Ali Khan Jun Shen Computer Science Department Aljumum University College Umm Alqura University Makkah Saudi Arabia School of Computing and Communications Lancaster University Leipzig Germany School of Business at University of Southern Queensland Queensland Australia M3S Empirical Software Engineering Research Unit University of Oulu Oulu Finland School of Computing and Information Technology University of Wollongong Wollongong Australia

Context Blockchain-based software (BBS) builds upon the foundational technologies of cryptocurrencies like Bitcoin, utilising decentralised, immutable ledgers, to support the development and operation of security-critical and transaction-intensive systems and services. In recent years, a number of research studies have investigated the strategic benefits and technical limitations of BBS that is central to the operations of a wide variety of systems ranging from cyber security, healthcare, education, and financial technologies. Despite an increasing interest both from academia and industry in BBS, there is a dearth of empirical evidence resulting in a lack of understanding about processes, methods, and techniques to enable a systematic development of this class of software systems. Objectives Existing research lacks a consolidated view, particularly empirically-driven guidelines based on published evidence and development practices. Therefore, our objective is to derive new or leverage existing development processes, patterns, and models to design, implement, and validate BBS systems. Method Tied to this knowledge gap, we conducted a two-phase research that unifies the findings of (i) a systematic literature review and (ii) practitioners’ survey to derive and validate the development process for BBS systems. First, we conducted a systematic literature review of 58 studies to derive a process comprising of 26 activities, to develop BBS systems. We than engaged 102 blockchain practitioners from, 35 countries across 6 continents to validate the BBS system development processes. Results Our results revealed a statistically significant difference (p-value <.001) in the importance ratings of 24 out of 26 BBS activities by our participants. The only two activities that were not statistically significant were incentive protocol design and granularity design. Our study also presented some of the activities that have been emphasised by our participants within the different dev

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Biometric authentication integrated with wireless communication malicious activity detection in a cyber physical system-based Fintech banking

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Optik 2023年 272卷

作者： Almuhannad Sulaiman Alorfi Saud Yonbawi Sultan Alahmari Abdullaev Abror Bozorboevich Mahendran Arumugam Pham Quang Huy Department of Information System Faculty of Computing and Information Technology King Abdulaziz University City Rabigh Saudi Arabia Department of Software Engineering College Of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia King Abdul Aziz City for Science and Technology Riyadh Saudi Arabia The Department of Acconting Economic Analysis and Audit Tashkent Institute of Finance Tashkent Uzbekistan Center for Transdisciplinary Research Saveetha Dental College Saveetha institute of Medical and Technical Science Chennai India University of Economics Ho Chi Minh City (UEH) Vietnam

Recently, biometric technology has been extensively embedded in mobile devices to enhance security of mobile devices. With rise of financial technology (FinTech) that employs mobile applications as well as devices as promotional platforms, biometrics has a significant role in strengthening the detection of this privacy application. This manuscript offers the design of salp swarm optimization with auto-encoder based biometric authentication (SSOAE-BMA) model for the recognition of abnormal activities in the Fintech banking applications based on wireless communication. The major aim of the SSOAE-BMA model lies in the proper authentication of persons via biometric matching process. Initially, the presented SSOAE-BMA model makes use of stacked ResNet-50 model for deriving feature vectors. Next, the SSOAE-BMA model utilizes AE for biometric verification and the performance of the AE model is adjusted using the Social Spider Optimization (SSO) Algorithm which in turn enhances the recognition outcomes. To demonstrate the improved performance of SSOAE-BMA model, a series of simulations were carried out. The experimental outcomes signified the enhancements of the SSOAE-BMA model over existing models.

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A novel lift adjustment methodology for improving association rule interpretation

Decision Analytics Journal

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Decision Analytics Journal 2025年 15卷

作者： Sowan, Bilal Zhang, Li Matar, Nasim Zraqou, J. Omar, Firas Alnatsheh, Athari Department of Business Intelligence and Data Analytics University of Petra Amman Jordan Department of Computer Science Royal Holloway University of London Surrey TW20 0EX United Kingdom Department of Software Engineering Al-Zaytoonah University of Jordan Amman Jordan Department of Computer Science/Virtual and Augmented Reality University of Petra Amman Jordan Department of Business Intelligence Al-Zaytoonah University of Jordan Amman Jordan Department of Information Security and Cybersecurity Philadelphia University Amman Jordan

Association rules can offer a human-interpretable insight extracted from data. The lift measures used for evaluating association rules in classical Association Rule Mining (ARM) contexts are mainly based on traditional and well-known ones but suffer from interpretation inadequacy when dealing with skewed distributions or low support. This study introduces a new lift adjustment approach with four methods to overcome traditional lift measures and identify the best rules in association rule mining. More concretely, our main objective is to improve the interpretability of association rules to make them more practically relevant for decision-making. We propose an approach incorporating four novel lift adjustment methods (smoothed, weighted, log, and threshold-adjusted lift) to achieve this. We introduce a flexible, dynamic approach combined with four new lift adjustment methods: smoothed, weighted, logarithm, and threshold-adjusted lift. Each technique addresses specific limitations of the traditional lift measure and better captures the reliable representation of item associations by exaggerating stronger relationships or smoothing weaker ones. The proposed methods applied context-aware rule evaluation and adjustment based on measures of relative significance (e.g., Jaccard similarity). The experimental results involving real-world data and synthetic datasets reveal new methods’ effectiveness and robustness in understanding the strengths of association rules and provide a comprehensive view that considers item importance. We evaluate the performance stability of our proposed methods using statistical analysis, including ANOVA, chi-squared, t-tests, and effect size metrics. © 2025 The Author(s)

关键词： Association rule mining Context-aware analysis Data interpretability Lift adjustment Rule evaluation Statistical analysis

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Retraction notice to “Biometric authentication integrated with wireless communication malicious activity detection in a cyber physical system-based Fintech banking” [Optik 272 (2023) 170294]

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Optik 2023年 288卷

作者： Almuhannad Sulaiman Alorfi Saud Yonbawi Sultan Alahmari Abdullaev Abror Bozorboevich Mahendran Arumugam Pham Quang Huy Department of Information System Faculty of Computing and Information Technology King Abdulaziz University City Rabigh Saudi Arabia Department of Software Engineering College of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia King Abdul Aziz City for Science and Technology Riyadh Saudi Arabia The Department of Acconting Economic Analysis and Audit Tashkent Institute of Finance Tashkent Uzbekistan Center for Transdisciplinary Research Saveetha Dental College Saveetha institute of Medical and Technical Science Chennai India University of Economics Ho Chi Minh City (UEH) Viet Nam

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Generalized Closed-form Formulae for Feature-based Subpixel Alignment in Patch-based Matching

arXiv

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arXiv 2021年

作者： Jospin, Laurent Valentin Laga, Hamid Boussaid, Farid Bennamoun, Mohammed Faculté ENAC École Polytechnique Fédérale de Lausanne Station 15 VD LausanneCH-1015 Switzerland School of Computer Science and Software Engineering University of Western Australia 35 Stirling Highway PerthWA6009 Australia School of Information Technology Murdoch University 90 South Street MurdochWA6150 Australia School of Electrical Engineering University of Western Australia 35 Stirling Highway PerthWA6009 Australia

Patch-based matching is a technique meant to measure the disparity between pixels in a source and target image and is at the core of various methods in computer vision. When the subpixel disparity between the source and target images is required, the cost function or the target image has to be interpolated. While cost-based interpolation is easier to implement, multiple works have shown that image-based interpolation can increase the accuracy of the disparity estimate. In this paper we review closed-form formulae for subpixel disparity computation for one dimensional matching, e.g., rectified stereo matching, for the standard cost functions used in patch-based matching. We then propose new formulae to generalize to high-dimensional search spaces, which is necessary for unrectified stereo matching and optical flow. We also compare the image-based interpolation formulae with traditional cost-based formulae, and show that image-based interpolation brings a significant improvement over the cost-based interpolation methods for two dimensional search spaces, and small improvement in the case of one dimensional search spaces. The zero-mean normalized cross correlation cost function is found to be preferable for subpixel alignment. A new error model, based on very broad assumptions is outlined in the Supplementary Material to demonstrate why these image-based interpolation formulae outperform their cost-based counterparts and why the zero-mean normalized cross correlation function is preferable for subpixel alignement. Copyright © 2021, The Authors. All rights reserved.

关键词： Cost functions

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Fog-cloud task scheduling of energy consumption optimisation with deadline consideration

Fog-cloud task scheduling of energy consumption optimisation...

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International Journal of Internet Manufacturing and Services

作者： Xu, Jiuyun Sun, Xiaoting Zhang, Ruru Liang, Hongliang Duan, Qiang School of Computer and Communication Engineering China University of Petroleum Qingdao China Software Technology Company No. 58 Kunshan Road Science and Technology City Suzhou High-Tech Zone Jiangsu Province China Department of Informatics Beijing University of Posts and Telecommunications Beijing China Information Sciences and Technology Department Pennsylvania State University PennsylvaniaPA United States

The emerging IoT introduces many new challenges that cannot be adequately addressed by the current 'cloud-only' architectures. The cooperation of the fog and cloud is considered to be a promising architecture, which efficiently handles IoT's data processing and communications requirements. However, how to schedule tasks to better adapt to IoT real-time needs and reduce the energy in the fog-cloud system is not well addressed. In this paper, we first model the energy consumption of the fog and cloud, respectively, and formulate a task scheduling problem into a constrained optimisation problem in fog-cloud computing system. Then, an efficient deadline-energy scheduling algorithm based on ant colony optimisation (DEACO) is put forward to tackle this problem, which achieves to reduce energy consumption on the condition of satisfying the task deadline. Finally, algorithms have been simulated on the extended CloudSim simulator. The experimental results have shown that our scheduling approach reduces energy more effective. © 2020 Inderscience Enterprises Ltd.

关键词： Green computing Ant colony optimization computer architecture Constrained optimization Data handling Energy utilization Fog Internet of things Multitasking Cloud systems Cloudsim Constrained optimisation problems Optimisations Real time Reduce energy consumption Task scheduling problem Task scheduling

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Inequivalent multipartite coherence classes and two operational coherence monotones

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Physical Review A 2019年第4期99卷 042306-042306页

作者： Yu Luo Yongming Li Min-Hsiu Hsieh College of Computer Science Shaanxi Normal University Xi'an 710062 China Centre for Quantum Software and Information Faculty of Engineering and Information Technology University of Technology Sydney Australia

Quantum coherence has received significant attention in recent years, but the structure of multipartite coherent states is unclear. In this paper, we generalize important results in multipartite entanglement theory to their counterparts in quantum coherence theory. First, we give a necessary and sufficient condition for when two pure multipartite states are equivalent under local incoherent operations assisted by classical communications (LICC), i.e., two states can be deterministically transformed to each other under LICC operations. Next, we investigate and give the conditions in which such a transformation succeeds only stochastically. Different from the entanglement case for two-qubit states, we find that the stochastic LICC (sLICC) equivalence classes are infinite. Moreover, it is possible that there are some classes of states in multipartite entanglement that can convert into each other, whereas they cannot convert into each other in multipartite coherence. In order to show the difference among sLICC classes, we introduce two coherence monotones: accessible coherence and source coherence, following the logistics given in [Phys. Rev. Lett. 115, 150502 (2015)]. These coherence monotones have a straightforward operational interpretation, namely, the accessible coherence characterizes the proficiency of a state to generate other states via quantum incoherent operations, whereas the source coherence characterizes the set of states that can be reached via quantum incoherent operations acting on the given state of interest.

关键词： Quantum coherence & coherence measures Quantum entanglement Quantum protocols Resource theories

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Iterative pseudo-labeling based adaptive copy-paste supervision for semi-supervised tumor segmentation

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Knowledge-Based Systems 2025年 324卷

作者： Qiangguo Jin Hui Cui Junbo Wang Changming Sun Yimiao He Ping Xuan Linlin Wang Cong Cong Leyi Wei Ran Su School of Software Northwestern Polytechnical University Shaanxi China Yangtze River Delta Research Institute of Northwestern Polytechnical University Taicang China Department of Computer Science and Information Technology La Trobe University Melbourne Australia CSIRO Data61 Sydney Australia Department of Computer Science School of Engineering Shantou University Guangdong China Shandong Cancer Hospital and Institute Shandong First Medical University and Shandong Academy of Medical Sciences Shandong China Australian Institute of Health Innovation (AIHI) Macquarie University Australia School of Software Shandong University Shandong China Centre for Artificial Intelligence driven Drug Discovery Faculty of Applied Science Macao Polytechnic University Macao Special Administrative Region of China School of Computer Software College of Intelligence and Computing Tianjin University Tianjin China

Semi-supervised learning (SSL) has attracted considerable attention in medical image processing. The latest SSL methods use a combination of consistency regularization and pseudo-labeling to achieve remarkable success. However, most existing SSL studies focus on segmenting large organs, neglecting the challenging scenarios where there are numerous tumors or tumors of small volume. Furthermore, the extensive capabilities of data augmentation strategies, particularly in the context of both labeled and unlabeled data, have yet to be thoroughly investigated. To tackle these challenges, we introduce a straightforward yet effective approach, termed iterative pseudo-labeling based adaptive copy-paste supervision (IPA-CP), for tumor segmentation in CT scans. IPA-CP incorporates a two-way uncertainty based adaptive augmentation mechanism, aiming to inject tumor uncertainties present in the mean teacher architecture into adaptive augmentation. Additionally, IPA-CP employs an iterative pseudo-label transition strategy to generate more robust and informative pseudo labels for the unlabeled samples. Extensive experiments on both in-house and public datasets show that our framework outperforms state-of-the-art SSL methods in medical image segmentation. Ablation study results demonstrate the effectiveness of our technical contributions.

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Multiphase MRI radiomics model for predicting microvascular invasion in HCC: Development and clinical validation

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iLIVER 2025年第2期4卷

作者： Peng, Yue Wu, Songxiong Xiong, Bing Chen, Fuqiang Zaki, Nazar Wu, Ruodai Qin, Wenjian Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China University of Chinese Academy of Sciences Beijing 100049 China Department of Radiology Shenzhen University General Hospital Shenzhen University Shenzhen 518000 China Department of Computer Science and Software Engineering College of Information Technology United Arab Emirates University (UAEU) Al Ain 15551 United Arab Emirates

Background and aims: Accurate preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) is crucial for treatment planning. This study aimed to develop and validate a multi-phase magnetic resonance imaging (MRI)-based radiomics model for predicting MVI in HCC patients. Methods: This retrospective study included 110 HCC patients (training: n = 77;validation: n = 33) who underwent preoperative multi-phase MRI. Radiomics features were extracted from four MRI phases (non-contrast, arterial, portal, and hepatobiliary). Feature selection was performed using least absolute shrinkage and selection operator regression, and five machine learning classifiers were evaluated. Model performance was assessed using standard metrics including area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy. Results: The four-phase radiomics model with logistic regression classifier showed optimal performance in both the training (AUC = 0.896;95% confidence interval, 0.792–0.963) and validation cohorts (AUC = 0.889, 95% confidence interval, 0.781–0.982), outperforming the single-phase (AUC = 0.789), two-phase (AUC = 0.815), and three-phase models (AUC = 0.848) in the validation cohort. In the validation cohort, the model achieved balanced performance with sensitivity, specificity, accuracy, and precision all reaching 0.857. Conclusions: The multi-phase MRI-based radiomics model significantly improves MVI prediction accuracy in HCC patients. This non-invasive approach could enhance preoperative assessment and treatment planning. © 2025 The Authors

关键词： Hepatocellular carcinoma Microvascular invasion Multi-phase MRI

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Investigating Bi-level optimization for learning and vision from a unified perspective: A survey and beyond

arXiv

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arXiv 2021年

作者： Liu, Risheng Gao, Jiaxin Zhang, Jin Meng, Deyu Lin, Zhouchen DUT-RU International School of Information Science & Engineering Dalian University of Technology Key Laboratory for Ubiquitous Network Service Software of Liaoning Province Dalian116024 China Department of Mathematics Southern University of Science and Technology National Center for Applied Mathematics Shenzhen China School of Mathematics and Statistics Ministry of Education Key Lab of Intelligent Networks and Network Security Xi’an Jiaotong University Xi’an Shaanxi China School of Electronics Engineering and Computer Science Peking University Beijing100871 China Cooperative Medianet Innovation Center Shanghai Jiao Tong University Shanghai200240 China

Bi-Level Optimization (BLO) is originated from the area of economic game theory and then introduced into the optimization community. BLO is able to handle problems with a hierarchical structure, involving two levels of optimization tasks, where one task is nested inside the other. In machine learning and computer vision fields, despite the different motivations and mechanisms, a lot of complex problems, such as hyper-parameter optimization, multi-task and meta learning, neural architecture search, adversarial learning and deep reinforcement learning, actually all contain a series of closely related subproblms. In this paper, we first uniformly express these complex learning and vision problems from the perspective of BLO. Then we construct a best-response-based single-level reformulation and establish a unified algorithmic framework to understand and formulate mainstream gradient-based BLO methodologies, covering aspects ranging from fundamental automatic differentiation schemes to various accelerations, simplifications, extensions and their convergence and complexity properties. Last but not least, we discuss the potentials of our unified BLO framework for designing new algorithms and point out some promising directions for future research. © 2021, CC BY.

关键词： Deep learning

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