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Shadow learner system: implementation of CNN with explainable AI model for bone radiology image classification

Soft Computing 2025年第7期29卷 3571-3588页

作者： Wu, Yaoyang Fong, Simon Liu, Liansheng Department of Computer and Information Science University of Macau Taipa China Medical Imaging Department The Sixth Affiliated Hospital of Jinan University Guangdong China Faculty of Digital Science and Technology Macau Millennium College China

Advancements in deep learning models for medical image classification have greatly improved accuracy, yet the challenge of explainability persists, making it difficult for clinicians to trust and effectively utilize these models in decision-making. This paper presents the Shadow Learner system, a novel approach that combines Convolutional Neural Networks with Explainable AI (XAI) techniques, focusing on the value of misclassified data—both false positives and negatives—by analyzing them to uncover important insights that traditional methods might overlook. We call our framework the Duplex computer-Aided Diagnosis system. Using the Musculoskeletal Radiographs dataset from Stanford University, which includes images of bone abnormalities that may require surgical intervention, we demonstrate how our system enhances explainability. Our findings show that about 85% of the Regions of Interest identified from misclassified images provided useful insights that clinicians found valuable in their work. Moreover, we observed that the shadow set—comprising important misclassified instances—constituted approximately 4–6% of the original dataset. This research highlights how misclassified data can reveal hidden patterns that improve the overall understanding and trust in AI models used in healthcare. The Shadow Learner system not only serves as a reference for treatment decisions but also has potential applications for other medical conditions that require surgical evaluation, such as osteonecrosis and various tumors. By shifting the focus of XAI from mere model validation to enhancing clinical interpretability, this work contributes to the more effective integration of AI in medical practice. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Convolutional neural networks

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Internal Hidden Processing Model-Based for SELECT Command in Structured Query Language 24

Internal Hidden Processing Model-Based for SELECT Command in...

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24th International Arab Conference on information technology, ACIT 2023

作者： Idhaim, Hasan Aljaidi, Mohammad Samara, Ghassan Qasem, Mais Haj Alsarhan, Ayoub Khalid, Muhammad The Hashemite University Faculty of Prince Al-Hussein Bin Abdallah Ii for Information Technology Department of Computer Information Systems Zarqa13116 Jordan Zarqa University Faculty of Information Technology Department of Computer Science Zarqa13110 Jordan The Hashemite University Faculty of Prince AI-Hussein Bin Abdallah Ii for Information Technology Department of Information Technology Zarqa13116 Jordan University of Hull Department of Computer Sciences and Technology Kingston upon Hull United Kingdom

ISBN: (纸本)9798350384307

The most used command in Structured Query Language (SQL) for retrieving data is select. In order to secure the retrieved data, this paper uses the hidden processing scheme (HPS).HPS breaks down the execution of user query into five phases to protect data. This data is identical to the select statement's physical execution. The model is based on the axiom that better results can be obtained by having a better understanding of how things work. The proposed scheme divides the query into five steps and improves the accuracy of retrieved data significantly, this will aid in the enhancing security, comprehension, and outcome anticipation needed to improve the SQL development research field. This work presents a theoretical SQL's statements modeling to predict the query output result that is not revealed in detail in the physical execution. The work is a uniquely researched paper in the field of database. © 2023 IEEE.

关键词： Group function (GF) Hidden Processing Scheme (HPS) Metadata Query Relational Database (RD)

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Enhancing Dog Tracking Through Dynamic Geofencing and Environmental Awareness 5

Enhancing Dog Tracking Through Dynamic Geofencing and Enviro...

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5th International Conference on IoT Based Control Networks and Intelligent systems, ICICNIS 2024

作者： Saikrupa, P.A. Dhaarini, G. Sanjai, R. Sri Sairam Institute of Technology Department of Information Technology Chennai India School of Computer Science and Engineering Vellore Institute of Technology Chennai India

ISBN: (数字)9798331518097

ISBN: (纸本)9798331518097

With the development of smart technologies, tracking businesses have evolved as tracking collars are now becoming the most crucial piece of safety equipment as well as monitoring tools for dogs. Various solutions like Fi Smart Collar and SpotOn have promising features such as geofencing and activity tracking but integrate with their smart product with less features lacking dynamic geofencing environmental awareness, as well as intelligent system connectivity. The paper proposed a new dog tracking collar system that integrates the use of GPS, Bluetooth, Wi-Fi, and environmental sensors all together onto a unified platform. The system employs an adaptive geofencing module which is dynamic and responds to changes in the environment, including weather and time, as well as different behaviors of pets, keeping it safe within the intended zones. The other advantage with this collar is the maximization of battery life, as it has used low power GPS tracking and intelligent algorithms to adjust the frequency of tracking in line with the assessment of the movement and risk of the pet. The system further integrates into smart home technology and will notify and automatically respond in real-time to changes that might be detected within the pet's environment. The comparative analysis of the current technologies for pet tracking shows significant improvement in accuracy, battery efficiency, and responsiveness to dynamic conditions. The proposed collar was tested and validated by controlled trials and real-time performance assessments, for which considerable results evidenced the reliability and effectiveness for real-time applications. This proposed framework thus would eventually be able to act as a potential future solution that integrates advanced technologies for enhanced pet welfare and with real-time dynamic geofencing and AI in order to create a whole system of pet monitoring. © 2024 IEEE.

关键词： Environmental monitoring

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A Semi-automatic Quality Assessment system for Capturing High-quality Fundus Image 23

A Semi-automatic Quality Assessment System for Capturing Hig...

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23rd International Conference on Cyberworlds, CW 2024

作者： Arfi, Asif Mohammed Toyoura, Masahiro Kashiwagi, Kenji Nishiguchi, Satoshi Go, Kentaro Zhu, Zhenyang Mao, Xiaoyang University of Yamanashi Department of Computer Science and Engineering Yamanashi Kofu Japan University of Yamanashi Faculty of Medicine Department of Ophthalmology Yamanashi Chuo Japan Osaka Institute of Technology Faculty of Information Science and Technology Osaka Hirakata Japan

ISBN: (纸本)9798331527174

The precision of medical diagnoses based on images is inextricably linked to the quality and clarity of the images. Poor image quality can impede accurate diagnosis and pose challenges for both physicians and machine learning algorithms in interpreting images. By automating the process of fundus image quality assessment during capture, we can ensure that only high-quality images are used, improving diagnostic accuracy. Accordingly, we propose a novel approach for automatically assessing the quality of fundus images using deep learning techniques. Our method incorporates retinal vessel segmentation into RGB images to create four-channel images and then trains a deep learning model on these images to identify the image focus and quality of the images. It can evaluate the quality of fundus images and request image recapture with the adjustment of specific parameters that are classified as poor quality. Our proposed method has the potential to improve the diagnostic accuracy and efficiency of retinal disease diagnosis, particularly in telemedicine settings. By automating the process of fundus image quality assessment, we can ensure that only high-quality images are used for diagnosis, thus improving diagnostic precision. It can serve as an efficient screening tool in the initial stage of acquiring high-quality fundus images. © 2024 IEEE.

关键词： Image quality

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User Acceptance Testing (UAT) of Self-Service Checkout Kiosks: A Case Study in E-Mart Tabuan Jaya, Kuching, Malaysia 7

User Acceptance Testing (UAT) of Self-Service Checkout Kiosk...

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7th International Conference on information technology, information systems and Electrical Engineering, ICITISEE 2023

作者： Chai, Cheen Shun Hipiny, Irwandi Ujir, Hamimah Universiti Malaysia Sarawak Faculty of Computer Science and Information Technology Kota Samarahan Malaysia

ISBN: (纸本)9798350382266

This work uses quantitative methods to assess the user acceptance level of self-service checkout kiosks in E-mart Tabuan Jaya, Sarawak, Malaysia. Using the technology Acceptance Model (TAM) as the theoretical foundation, we investigated how the users perceive the technology using survey data collected from customers who had or had not utilised the kiosks before the survey. According to our findings, user acceptability of the self-service checkout counter is significantly impacted by constructs such as the system's Perceived Usefulness and Perceived Ease of Use. The study also reveals various factors influencing user acceptance, such as experience with self-service technology and demographic factors, e.g., age and gender. From our findings, we observed that for our respondents, Perceived Ease of Use (0.734) has a larger impact towards Attitude Towards Usage of the self-service kiosks when compared to Perceived Usefulness (0.198). © 2023 IEEE.

关键词： Acceptance tests

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Detection and Security in Falls with IoT Server 3

Detection and Security in Falls with IoT Server

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3rd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2023

作者： Kavitha, C. Sridevi, N. Dhivagar, D. Department of Information Technology Villupuram India Sathyabama Institution of Science and Technology Department of Computer Science and Engineering Chennai India Department of It Department of Information Technology Villupuram India

ISBN: (纸本)9781665462167

Heart rate (HR) and Heart rate variability (HRV) have received a great deal of attention that promises to change the dimension of awareness of health and fitness while swimming. HRV is very useful to understand physiological and psychological status of an individual. The variation in HR, provides a reliable information about the role of Autonomic Nervous system (ANS). HRV is very convenient to understand the overall physiological status of an individual. Due to individuality of the HRV, regular monitoring HRV is useful to understand training adaptation, load, recovery, overtraining. The study provides a brief concept on HR and HRV in swimming individual. Although RR intervals are highly individual centric but due to same practice pattern or same type of physical activity, the swimmer group has very small quartile range. A significance difference in RR intervals between control group and swimmer group may come from two different effects of the nervous system. Either it indicates a significant increase in parasympathetic tone due to normal training adaptation or a sign of overtraining that has caused increase in parasympathetic tone. High HRV denotes good indication of positive adaptation, good cardiovascular efficiency. Low HRV score indicates deterioration in VO2max. © 2023 IEEE.

关键词： Internet of things

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Automating News Tweet Writing Based on Indonesia Language Using NLG Approach 1

Automating News Tweet Writing Based on Indonesia Language Us...

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1st IEEE International Conference on Cryptography, Informatics, and Cybersecurity, ICoCICs 2023

作者： Christina Aulia, Indra Purnamawati, Sarah University of North Sumatra Faculty of Computer Science and Information Technology Department of Information Technology Medan Indonesia Telkom University School of Computing Jakarta Indonesia

ISBN: (纸本)9798350339437

Over time, after the advent of the internet, the dissemination of news media has undergone developments ranging from websites to social media. However, news posted on social media is still written by reporters and undergoes editorial checks, resulting in a relatively long news processing time for posting. Therefore, to overcome these limitations, this research proposes an NLG (Natural Language Generation) approach using LSTM algorithms to assist in processing news data obtained from reporters into news tweets in the Indonesian language with the system called Automated Sports News Tweet Generator (ASNTG). The study's findings highlight the effectiveness of this method in generating news tweets sourced directly from on-location reporters through a Telegram chatbot. By doing so, it enables the production of real-time news updates, allowing readers to stay promptly informed about the latest events. Furthermore, the generated news tweets exhibit excellent naturalness aspects, as assessed by social media users and language experts who participated as respondents. © 2023 IEEE.

关键词： Data handling

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OFDM-structure based waveform designs for integrated sensing and communication

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science China(information sciences) 2025年第5期68卷 267-284页

作者： Jiaqi LIU Ping YANG Ke JIANG Jiarong ZHAO Wei XIANG Jianping WEI Ruixiang DUAN Saviour ZAMMIT Tony Q.S.QUEK National Key Laboratory of Wireless Communications University of Electronic Science and Technology of China School of Computing Engineering and Mathematical Sciences La Trobe University Meituan Academy of Robotics Department of Communications and Computer Engineering University of Malta Information Systems Technology and Design Pillar Singapore University of Technology and Design

The future sixth-generation(6G) paradigm aims to seamlessly integrate communication and environmental sensing capabilities into a single radio signal, promising improved efficiency and cost-effectiveness through simultaneous data communications and environmental perception. At the core of this evolution, orthogonal frequency division multiplexing(OFDM) and its advanced waveforms emerge as pivotal for integrated sensing and communications(ISAC). This study introduces a concise and unified ISAC waveform design framework based on orthogonal multicarriers. This framework supports versatile applications of OFDM and its derivative waveforms within a generalized ISAC system, marking a significant leap in integrating communication and sensing capabilities. A distinguishing feature of this framework is its adaptability,allowing users to intelligently select modulation strategies based on their specific environmental needs. This adaptability optimizes performance across diverse scenarios. Central to our innovations is the proposal of discrete Fourier transformspread OFDM with index modulation(DFT-S-OFDM-IM). This framework is paired with newly proposed signal processing methods for single-input single-output and multiple-input multiple-output(MIMO) systems. Extensive evaluations highlight DFT-S-OFDM-IM's superiority, including dramatically reduced peak-to-average power ratios(PAPRs), competitive communication performance, and exceptional sensing capabilities, striking an elegant balance between communication capacity and environmental sensing precision.

关键词： DFT-S-OFDM-IM index modulation integrated sensing and communication OFDM

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Generating A New Shilling Attack for Recommendation systems

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computers, Materials & Continua 2022年第5期71卷 2827-2846页

作者： Pradeep Kumar Singh Pijush Kanti Dutta Pramanik Madhumita Sardar Anand Nayyar Mehedi Masud Prasenjit Choudhury Department of Computer Science&Engineering National Institute of TechnologyDurgapurIndia Graduate School Duy Tan UniversityDa NangVietnam Faculty of Information Technology Duy Tan UniversityDa NangVietnam Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

A collaborative filtering-based recommendation system has been an integral part of e-commerce and *** keep the recommendation systems reliable,authentic,and superior,the security of these systems is very *** the existing shilling attack detection methods in collaborative filtering are able to detect the standard attacks,in this paper,we prove that they fail to detect a new or unknown *** develop a new attack model,named Obscure attack,with unknown features and observed that it has been successful in biasing the overall top-N list of the target users as *** Obscure attack is able to push target items to the top-N list as well as remove the actual rated items from the *** proposed attack is more effective at a smaller number of k in top-k similar user as compared to other existing *** effectivity of the proposed attack model is tested on the MovieLens dataset,where various classifiers like SVM,J48,random forest,and naïve Bayes are utilized.

关键词： Shilling attack recommendation system collaborative filtering top-N recommendation biasing shuffling hit ratio

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An Efficient ResNetSE Architecture for Smoking Activity Recognition from Smartwatch

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Intelligent Automation & Soft Computing 2023年第1期35卷 1245-1259页

作者： Narit Hnoohom Sakorn Mekruksavanich Anuchit Jitpattanakul Department of Computer Engineering Image Information and Intelligence LaboratoryFaculty of EngineeringMahidol UniversityNakhon Pathom73170Thailand Department of Computer Engineering School of Information and Communication Technology University of PhayaoPhayao56000Thailand Department of Mathematics Faculty of Applied ScienceKing Mongkut’s University of Technology North BangkokBangkok10800Thailand Intelligent and Nonlinear Dynamic Innovations Research Center Science and Technology Research InstituteKing Mongkut’s University of Technology North BangkokBangkok 10800Thailand

Smoking is a major cause of cancer,heart disease and other afflictions that lead to early *** effective smoking classification mechanism that provides insights into individual smoking habits would assist in implementing addiction treatment *** activities often accompany other activities such as drinking or ***,smoking activity recognition can be a challenging topic in human activity recognition(HAR).A deep learning framework for smoking activity recognition(SAR)employing smartwatch sensors was proposed together with a deep residual network combined with squeeze-and-excitation modules(ResNetSE)to increase the effectiveness of the SAR *** proposed model was tested against basic convolutional neural networks(CNNs)and recurrent neural networks(LSTM,BiLSTM,GRU and BiGRU)to recognize smoking and other similar activities such as drinking,eating and walking using the UT-Smoke *** different scenarios were investigated for their recognition performances using standard HAR metrics(accuracy,F1-score and the area under the ROC curve).Our proposed ResNetSE outperformed the other basic deep learning networks,with maximum accuracy of 98.63%.

关键词： Smoking activity recognition deep residual network smartwatch sensors deep learning

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