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arXiv 2023年

作者： Qiu, Jianing Li, Lin Sun, Jiankai Peng, Jiachuan Shi, Peilun Zhang, Ruiyang Dong, Yinzhao Lam, Kyle Lo, Frank P.-W. Xiao, Bo Yuan, Wu Wang, Ningli Xu, Dong Lo, Benny The Department of Computing Imperial College London United Kingdom The Department of Biomedical Engineering The Chinese University of Hong Kong Hong Kong Ltd. Hong Kong The Department of Informatics King’s College London United Kingdom The School of Engineering Stanford University United States The Department of Engineering Science University of Oxford United Kingdom The Faculty of Engineering The University of Hong Kong Hong Kong The Department of Surgery and Cancer Imperial College London United Kingdom The Hamlyn Centre for Robotic Surgery Imperial College London United Kingdom Beijing Tongren Eye Center Beijing Tongren Hospital Capital Medical University China Beijing Ophthalmology & Visual Sciences Key Laboratory Beijing China The Department of Electrical Engineering and Computer Science United States The Christopher S. Bond Life Sciences Center University of Missouri United States The Facualty of Medicine Imperial College London United Kingdom

Large AI models, or foundation models, are models recently emerging with massive scales both parameter-wise and data-wise, the magnitudes of which can reach beyond billions. Once pretrained, large AI models demonstrate impressive performance in various downstream tasks. A prime example is ChatGPT, whose capability has compelled people’s imagination about the far-reaching influence that large AI models can have and their potential to transform different domains of our lives. In health informatics, the advent of large AI models has brought new paradigms for the design of methodologies. The scale of multi-modal data in the biomedical and health domain has been ever-expanding especially since the community embraced the era of deep learning, which provides the ground to develop, validate, and advance large AI models for breakthroughs in health-related areas. This article presents a comprehensive review of large AI models, from background to their applications. We identify seven key sectors in which large AI models are applicable and might have substantial influence, including 1) bioinformatics;2) medical diagnosis;3) medical imaging;4) medical © 2023, CC BY-NC-ND.

关键词： Medical imaging

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Enhancing the OPEN Process Framework with Service-Oriented Method Fragments

arXiv

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arXiv 2020年

作者： Fahmideh, Mahdi Sharifi, Mohsen Jamshidi, Pooyan Azad University of Science and Research Branch Tehran Iran School of Computer Engineering Iran University of Science and Technology Tehran Iran Lero - The Irish Software Engineering Research Centre School of Computing Dublin City University Dublin Ireland

Service-orientation is a promising paradigm that enables the engineering of large-scale distributed software systems using rigorous software development processes. The existing problem is that every service-oriented software development project often requires a customized development process that provides specific service-oriented software engineering tasks in support of requirements unique to that project. To resolve this problem and allow situational method engineering, we have defined a set of method fragments in support of the engineering of the project-specific service-oriented software development processes. We have derived the proposed method fragments from the recurring features of eleven prominent service-oriented software development methodologies using a systematic mining approach. We have added these new fragments to the repository of OPEN Process Framework to make them available to software engineers as reusable fragments using this well-known method repository. Copyright © 2020, The Authors. All rights reserved.

关键词： Software design

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A Contrastive Learning-based PPC-UNet for Colorectal Histopathology Whole Slide Image Segmentation

A Contrastive Learning-based PPC-UNet for Colorectal Histopa...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Yuxuan Wang Xuechen Li Jingxin Liu Linlin Shen Kunming Sun Suying Wang School of Computer Science and Software Engineering AI Research Centre for Medical Image Analysis and Diagnosis and Marshall Laboratory of Biomedical Engineering Shenzhen University Shenzhen China Histo Pathology Diagnostic Center Shanghai and School of AI and Advanced Computing Xi’an Jiaotong-Liverpool University Suzhou China Histo Pathology Diagnostic Center Shanghai China Ningbo Diagnostic Pathology Center Ningbo China

ISBN: (纸本)9781665429825

Colorectal cancer (CRC) is the third most common cancer and is usually diagnosed using colonoscopy and biopsy. Diagnosis of pathological biopsy requires professional knowledge and technology. computer-aided gland and lesion segmentation systems have been proposed to help pathologists in diagnosis of CRC. However, to the best of our knowledge, there has not been a literature work trying to segment different levels of intraepithelial neoplasia in CRC pathological image. To reduce such a research gap, in this paper, we firstly collect a colorectal cancer biopsy histopathology whole slide image (WSI) dataset, named Histo-CRC Biopsy dataset, for algorithm evaluation. We further propose a PPC-UNet network to segment high level, low level intraepithelial neoplasia and normal tissues. The proposed PPC-UNet consists of two modules i.e., a UNet-based network for segmentation, and a pixel-to-propagation consistency (PPC) contrastive learning-based network for UNet encoder pre-training. As the important feature can be learned from the unannotated data during pre-training, our approach can consistently improve the Dice of UNet by around 2% when different ratios of the training data are labeled.

关键词： Image segmentation Histopathology Conferences Biopsy Training data Glands Colonoscopy

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Enhancing the Harrow-Hassidim-Lloyd (HHL) algorithm in systems with large condition numbers

arXiv

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arXiv 2024年

作者： Tsemo, Peniel Bertrand Jayashankar, Akshaya Sugisaki, K. Baskaran, Nishanth Chakraborty, Sayan Prasannaa, V.S. Centre for Quantum Engineering Research and Education TCG CREST Sector V Salt Lake Kolkata700091 India Graduate School of Science and Technology Keio University 7-1 Shinkawasaki Saiwai-ku Kanagawa Kawasaki212-0032 Japan Quantum Computing Center Keio University 3-14-1 Hiyoshi Kohoku-ku Kanagawa Yokohama223-8522 Japan Keio University 2-15-45 Mita Minato-ku Tokyo108-8345 Japan Department of Electrical and Computer Engineering The University of British Columbia VancouverBCV6T 1Z4 Canada Institute for Advancing Intelligence TCG CREST Sector V Salt Lake Kolkata700091 India Ghaziabad201002 India

Although the Harrow-Hassidim-Lloyd (HHL) algorithm offers an exponential speedup in system size for treating linear equations of the form A→x =⃗b on quantum computers when compared to their traditional counterparts, it faces a challenge related to the condition number (κ) scaling of the A matrix. In this work, we address the issue by introducing the post-selection-improved HHL (Psi-HHL) approach that involves a simple yet effective modification of the HHL algorithm to extract a feature of |x〉, and which leads to achieving optimal behaviour in κ (linear scaling) for large condition number situations. This has the important practical implication of having to use substantially fewer shots relative to the traditional HHL algorithm. Additionally, we discuss the capability of Psi-HHL to address the cases where A is singular. We carry out two sets of simulations, where we go up to 26-qubit calculations, to demonstrate the ability of Psi-HHL to handle situations involving large κ matrices via: (a) a set of toy matrices, for which we go up to size 64 × 64 and κ values of up to ≈ 1 million, and (b) application to quantum chemistry, where we consider matrices up to size 256 × 256 that reach κ of about 393. The molecular systems that we consider are Li2, KH, RbH, and CsH. Although the feature of |x〉 considered in our examples is an overlap between the input and output states of the HHL algorithm, our approach is general and can be applied in principle to any transition matrix element involving |x〉. © 2024, CC BY.

关键词： Quantum computers

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Construction of Two Dimensional Cubic-Tent-Sine Map for Secure Image Transmission 1

引用

10th International Conference on Applications and Techniques in Information Security, ATIS 2019

作者： Rajendran, Sujarani Doraipandian, Manivannan Department of Computer Science and Engineering Srinivasa Ramanujan Centre SASTRA Deemed University Kumbakonam612001 India School of Computing SASTRA Deemed University Thanjavur613401 India

ISBN: (数字)9789811508714

ISBN: (纸本)9789811508707

A fusion two dimensional Cubic Tent Sine (CTS) map is formulated and its dynamic range is analysed. To explore its application in secure electronic data transmission, an image cipher is developed under the architecture of confusion and diffusion. A new dual form of chaos series based confusion with fast and efficient method is employed in this cipher. Chaotic key image with excellent random behaviour is utilized for diffusion phase. The proposed cryptosystem entails higher key space and single round structural design to achieve fast and efficient cipher. The random evaluation of CTS proves that the generated key series has more complicate chaotic conduct. Simulation outcomes demonstrates that the proposed cipher possesses better performance than other image ciphers. Security assessment proves the cipher strength that can resist against various attacks. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Cryptography

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Air Pollution and Cardiorespiratory Hospitalization, Modeling and Analysis Using Artificial Intelligence Techniques

Research Square

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Research Square 2021年

作者： Usmani, Raja Sher Afgun Pillai, Thulasyammal Ramiah Hashem, Ibrahim Abaker Targio Marjani, Mohsen Shaharudin, Rafiza Binti Latif, Mohd Talib School of Computer Science and Engineering Taylor’s University Selangor Malaysia College of Computing and Informatics Department of Computer Science University of Sharjah Sharjah27272 United Arab Emirates Institute for Medical Research Environmental Health Research Centre Occupational Health Unit Jalan Pahang Kuala Lumpur50588 Malaysia Department of Earth Sciences and Environment Faculty of Science and Technology Universiti Kebangsaan Malaysia Selangor Bangi43600 Malaysia

Air pollution has a serious and adverse effect on human health, and it has become a risk to human welfare and health throughout the globe. In this paper, we present the modeling and analysis of air pollution and cardiorespiratory hospitalization. This study aims to investigate the association between cardiorespiratory hospitalization and air pollution, and predict cardiorespiratory hospitalization based on air pollution using the Artificial Intelligence (AI) techniques. We propose the Enhanced Long Short-Term Memory (ELSTM) model and provide a comparison with other AI techniques, i.e., Long Short-Term Memory (LSTM), Deep Learning (DL), and Vector Autoregressive (VAR). This study was conducted at seven study locations in Klang Valley, Malaysia. The prediction results show that the ELSTM model performed significantly better than other models in all study locations, with the best RMSE scores in Klang study location (ELSTM: 0.002, LSTM: 0.013, DL: 0.006, VAR: 0.066). The results also indicated that the proposed ELSTM model was able to detect and predict the trends of monthly hospitalization significantly better than the LSTM and other models in the study. Hence, we can conclude that we can utilize AI techniques to accurately predict cardiorespiratory hospitalization based on air pollution in Klang Valley, Malaysia. © 2021, CC BY.

关键词： Long short-term memory

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Quantifying dynamical coherence with coherence measures

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Physical Review A 2021年第1期104卷 012404-012404页

作者： Sunho Kim Chunhe Xiong Asutosh Kumar Guijun Zhang Junde Wu School of Mathematical Sciences Harbin Engineering University Harbin 150001 China School of Computer and Computing Science Zhejiang University City College Hangzhou 310015 China P.G. Department of Physics Gaya College Magadh University Rampur Gaya 823001 India Harish-Chandra Research Institute HBNI Chhatnag Road Jhunsi Allahabad 211019 India Vaidic and Modern Physics Research Centre Bhagal Bhim Bhinmal Jalore 343029 India School of Mathematical Sciences Zhejiang University Hangzhou 310027 China

Quantum coherence, like entanglement, is a fundamental resource in quantum information. In recent years, remarkable progress has been made in formulating resource theory of coherence from a broader perspective. The notions of block-coherence and POVM-based coherence have been established. Certain challenges, however, remain to be addressed. It is difficult to define incoherent operations directly, without requiring incoherent states, which proves a major obstacle in establishing the resource theory of dynamical coherence. In this paper, we overcome this limitation by introducing an alternate definition of incoherent operations induced via coherence measures and quantify dynamical coherence based on this definition. Finally, we apply our proposed definition to quantify POVM-based dynamical coherence.

关键词： Resource theories

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Earthworm optimization algorithm based cascade LSTM-GRU model for android malware detection

Cyber Security and Applications

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Cyber Security and Applications 2025年 3卷

作者： Gupta, Brij B. Gaurav, Akshat Arya, Varsha Bansal, Shavi Attar, Razaz Waheeb Alhomoud, Ahmed Psannis, Konstantinos Department of Computer Science and Information Engineering Asia University Taiwan Taichung 413 China School of Cybersecurity Korea University Seoul South Korea Symbiosis Centre for Information Technology (SCIT) Symbiosis International University Pune India University of Economics and Human Science Warsaw Poland Ronin Institute Montclair NJ United States Hong Kong Metropolitan University (HKMU) Hong Kong Center for Interdisciplinary Research University of Petroleum and Energy Studies (UPES) Dehradun India Insights2Techinfo India UCRD Chandigarh University Chandigarh India Management Department College of Business Administration Princess Nourah bint Abdulrahman University P.O. Box 84428 Riyadh 11671 Saudi Arabia Department of Computer Sciences Faculty of Computing and Information Technology Northern Border University Rafha 91911 Saudi Arabia University of Macedonia Greece

The rise in mobile malware risks brought on by the explosion of Android smartphones required more efficient detection techniques. Inspired by a cascade of Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) networks, optimized using the Earthworm Optimization Algorithm (EOA), this study presents an android malware detection model. The paper used random forest model for feature selection. With a 99% accuracy and the lowest loss values, the proposed model performs better than conventional models including GRU, LSTM, RNN, Logistic Regression, and SVM. The findings highlight the possibility of proposed method in improving Android malware detection, thereby providing a strong answer in the changing scene of cybersecurity. © 2024

关键词： Android Earthworm optimization algorithm GRU LSTM Malware detection

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Circularity-based embodied carbon performance in building design: Index development and circular initiatives

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Journal of Cleaner Production 2025年 518卷

作者： Mohsen Ahmadi Asal Pournaghshband Farzad Piadeh M. Reza Hosseini School of Architecture and Built Environment Deakin University Geelong VIC 3220 Australia Centre for Engineering Research School of Physics Engineering and Computer Science University of Hertfordshire Hatfield AL10 9AB UK Smart Infrastructure and Green Technologies Research Group School of Computing and Engineering University of West London London W5 5RF UK Faculty of Architecture Building and Planning The University of Melbourne Parkville VIC 3010 Australia

This study introduces the Circularity-based Embodied Carbon (CiBEC) index, a comparative metric designed to assess the effects of circular actions on the embodied carbon (EC) of building projects. Built upon the conventional EC measurement, this index enhances traditional approaches by incorporating inclusive material inflow and outflow allocations, acknowledging variations in usage intensity, and factoring in potential changes to building lifespan strategies. Unlike conventional methods, it also recognises the collective efforts of all stakeholders - including third-party contributors - by fairly redistributing carbon savings across product (A) and beyond the building (D) phases of the life cycle assessment, offering a more holistic and equitable perspective. While demonstrated on a global scale, the index is applied to a real office building project to validate its practicality and demonstrate real-world applicability. Both individual and combined circular scenarios are assessed, revealing how key benefits from circular initiatives - often unaccounted for in conventional methods - are effectively captured through the CiBEC framework. The results indicate that among the eight developed circular scenarios, two - specifically, renovation and the multi-use of building spaces - are identified as EC-intensive. In contrast, the remaining scenarios achieve reductions of up to only 10 % when the conventional approach is used. However, when assessed using the CiBEC method, the “renovation” scenario notably demonstrates a 36 % reduction. Furthermore, the study shows that integrating various circular strategies through the development of seven combined scenarios can lead to substantial EC reductions, decreasing the initial EC from 629 to 191 kgCO 2 eq./m 2 . This significant reduction is not achieved through a simple statistical aggregation but through the complex interactions among the different strategies. Therefore, it seems that while the CiBEC index is most effective dur

关键词： Building industry Building lifespan Circularity Greenhouse gas Usage intensity

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Converting coherence based on positive-operator-valued measures into entanglement

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Physical Review A 2021年第5期103卷 052418-052418页

作者： Sunho Kim Chunhe Xiong Asutosh Kumar Junde Wu School of Mathematical Sciences Harbin Engineering University Harbin 150001 China School of Computer and Computing Science Zhejiang University City College Hangzhou 310015 China P.G. Department of Physics Gaya College Magadh University Rampur Gaya 823001 India Harish-Chandra Research Institute HBNI Chhatnag Road Jhunsi Allahabad 211019 India Vaidic and Modern Physics Research Centre Bhagal Bhim Bhinmal Jalore 343029 India School of Mathematical Sciences Zhejiang University Hangzhou 310027 China

Quantum resource theories provide a diverse and powerful framework for extensively studying the phenomena in quantum physics. Quantum coherence, a quantum resource, is the basic ingredient in many quantum information tasks. It is a subject of broad and current interest in quantum information, and many new concepts have been introduced and generalized since its establishment. Here we show that the block coherence can be transformed into entanglement via a block-incoherent operation. Moreover, we find that the coherence based on positive-operator-valued measures (POVMs) associated with block coherence through the Naimark extension acts as a potential resource from the perspective of generating entanglement. Finally, we discuss avenues of creating entanglement from POVM-based coherence, present strategies that require embedding channels and auxiliary systems, give some examples, and generalize them.

关键词： Resource theories

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