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Dm-Health App:Diabetes Diagnosis Using Machine Learning with Smartphone

computers, Materials & Continua 2022年第7期72卷 1713-1746页

作者： Elias Hossain Mohammed Alshehri Sultan Almakdi Hanan Halawani Md.Mizanur Rahman Wahidur Rahman Sabila Al Jannat Nadim Kaysar Shishir Mia Department of Software Engineering Daffodil International UniversityDhaka1207Bangladesh Department of Computer Science Najran UniversityNajran55461Saudi Arabia Department of Computer Science and Engineering Rajshahi University of Engineering and TechnologyRajshahi6204Bangladesh Department of Computer Science and Engineering Mawlana Bhashani Science and Technology UniversitySantoshTangail1902Bangladesh Department of Computer Science and Engineering BRAC UniversityDhaka1212Bangladesh Department of Computer Science and Engineering World University BangladeshDhaka1230Bangladesh

Diabetes Mellitus is one of the most severe diseases,and many studies have been conducted to anticipate *** research aimed to develop an intelligent mobile application based on machine learning to determine the diabetic,pre-diabetic,or non-diabetic without the assistance of any physician or medical *** study’s methodology was classified into two the Diabetes Prediction Approach and the Proposed System Architecture *** Diabetes Prediction Approach uses a novel approach,Light Gradient Boosting Machine(LightGBM),to ensure a faster *** Proposed System ArchitectureDesign has been combined into sevenmodules;the Answering Question Module is a natural language processing Chabot that can answer all kinds of questions related to *** Doctor Consultation Module ensures free treatment related to *** this research,90%accuracy was obtained by performing K-fold cross-validation on top of the K nearest neighbor’s algorithm(KNN)&*** evaluate the model’s performance,Receiver Operating Characteristics(ROC)Curve and Area under the ROC Curve(AUC)were applied with a value of 0.948 and 0.936,*** manuscript presents some exploratory data analysis,including a correlation matrix and survey ***,the proposed solution can be adjustable in the daily activities of a diabetic patient.

关键词： Machine learning diabetes-prediction support vector machine(SVM) LightGBM eHealth ROC-AUC

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Adaptive and Learnable Label for Face Anti-Spoofing 3

Adaptive and Learnable Label for Face Anti-Spoofing

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3rd International Conference on computer Vision and Pattern Analysis, ICCPA 2023

作者： Chen, Shijie Wang, Yifeng Han, Yuehu Department of Computer Science and Technology Chongqing University of Posts and Telecommunications ChongQing China Department of Software Engineering Chongqing University of Posts and Telecommunications ChongQing China

ISBN: (纸本)9781510667563

Face anti-spoofing(FAS) is an important task to secure face recognition systems from presentation attacks (PAs). Most of the FAS methods use scalar(0, 1) or handcrafted pixel-wise labels(binary mask) as the ground truth labels. However, these labels may are not the most adequate way to supervise PA detectors learning intrinsic and discriminative spoofing cues. In this work, we present an adaptive and learnable label for more efficient supervision of PA detectors. Then we propose a dual-branch network for FAS that utilizes the proposed supervision to detect PAs more reasonably. We evaluate our method by conducting experiments on public datasets, the proposed supervision method can not only improve the detection performance of the PA detectors, but also enhance the model’s interpretability (i.e., locating the pixel-level positions of PAs more reasonably). © 2023 SPIE.

关键词： Pixels

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Enhanced Mask R-CNN blur instance segmentation based on generated adversarial network 2

Enhanced Mask R-CNN blur instance segmentation based on gene...

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2nd International Conference on Electronic Information technology, EIT 2023

作者： Han, Yuehu Chen, Shijie Zhang, Xiaoyan Department of Software Engineering Chongqing University of Posts and Telecommunications Chongqing China Department of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing China

ISBN: (数字)9781510666627

ISBN: (纸本)9781510666610

Aiming at the detection of blur SEM nanoparticle images, a blur instance segmentation network (BL-Mask R-CNN) based on generative adversarial network deblurring convolution block (Deblur) and Mask R-CNN instance segmentation algorithm is proposed. The network uses the enhanced method of the blind deblurring algorithm (DeblurGAN-v2) of the generative confrontation network to preprocess the image, restore the grainy texture details in the image and generate a clear image that is conducive to instance segmentation and detection. The experimental results show that this method effectively improves the detection accuracy of blurred SEM nanoparticle images. Tested on the blur images of the NFFA-EUROPE dataset, the improved BL-Mask R-CNN has compared the detection accuracy of the original Mask R-CNN. The accuracy rate AP has increased from 0.8339 to 0.9613, and achieved good results in the test. © 2023 SPIE.

关键词： Nanoparticles

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Using IoT for Patient Health Monitoring System(PHMS) to Measure Temperature, Blood Pressure and ECG Based on Arduino IDE 2.x

Using IoT for Patient Health Monitoring System(PHMS) to Meas...

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Emerging Smart Technologies and Applications (eSmarTA), International Conference on

作者： Esraa Abrahim Elkhidr Abdelsalam Saleh Elrashdi Salem El Khiralla Nada Ali Altawerghi Fatma Mohammed Hasan Department of Computer Networks College of Computer Technology Benghazi Libya Department of Software Engineering College of Computer Technology Benghazi Libya

ISBN: (数字)9798350354133

ISBN: (纸本)9798350354140

By 2030, there will be 500 billion devices with sensors and an Internet connection. The Internet of Things is the name of the network that links these gadgets together for data transport (IoT). In order to rapidly exchange medical information to connect people, resources, and organizations we have proposed paper using an IoT for Patient Health Monitoring (PHMS). For almost medical equipment having an internet connection and the capacity to track at least one patient's health parameter, including blood pressure, body temperature, heart rate, ECG, steps taken, etc. We made a prototype that carries out different procedures for example, if the patient's temperature rises above 38 degrees Celsius, it will send messages to the doctor that there is a patient who needs special care. The Arduino IDE 2.x processes the data produced by the sensors. The feedback was extremely favorable and supportive of the efficacy of monitoring patient health by the use of Arduino IDE 2.x.

关键词： Temperature measurement Temperature sensors Medical services Blood pressure Pressure measurement Internet of Things Biomedical monitoring

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Lightweight Cryptography Concepts and Algorithms: A Survey 2

Lightweight Cryptography Concepts and Algorithms: A Survey

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2nd International Conference on Advanced computer Applications, ACA 2023

作者： Mohammed, Zahraa A. Hussein, Khalid Ali University of Babylon Information Technology College Department of Software Baghdad Iraq Al Mustansiriyah University College of Education Computer Science Department Baghdad Iraq

ISBN: (纸本)9798350341829

Evolutionary technologies have been raised under the umbrella of the Internet, such as Cloud computing, The Internet of Things (IoT), and The Internet of Everything (IoE). All these technologies are extensively data exchange channels, while they are not saving channels. Security plays a vital role;thus, the data must not be easily reached by any type or method of attack. The new trends in data protection are looking for easy-to-use, low-consumption, and high-performance methods. Therefore, Lightweight cryptography algorithms appeared strongly in the protection field;since this type of cipher has the flexibility to be used in all the sharing and using of data channels that have different characteristics and resources. This paper applies a light spot-on various encryption lightweight study. Where the paper presents analyzing the study of common symmetric lightweight algorithms implemented in many recent fields and shows the strength point of each of these algorithms. © 2023 IEEE.

关键词： Internet of Everything

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Multivariate time series forecasting model based on sliding window machine learning 3

Multivariate time series forecasting model based on sliding ...

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3rd International Conference on Electronics technology and Artificial Intelligence, ETAI 2024

作者： Bai, Hexiang Yu, Peiwen Yang, Zhenshan Xing, Ruijia Rui, Zhang College of Computer Science and Technology Jilin University Changchun China College of Software Jilin University Changchun China Financial Technology Department BANK OF JILIN CO. Ltd. Changchun China

ISBN: (纸本)9781510683143

This paper introduces a multivariate time series forecasting model that combines a sliding window technique with machine learning, incorporating a convolutional neural network to extract spatio-temporal features. This integration boosts predictive accuracy and robustness. Applied to the Jilin credit card installment dataset, our SHRF method improves AUC PRECISION and F1 scores. Validations on the BeijingAirQuality dataset using the SHL model show our model reduces RMSE per time step to 15.18, demonstrating excellent performance in multivariable time series forecasting. © 2024 SPIE.

关键词： Adversarial machine learning

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User Recognition based on Gait Pattern via Smartwatch Accelerometer in Unrestricted Environment 3

User Recognition based on Gait Pattern via Smartwatch Accele...

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3rd International Conference on Communication, Computing and Digital Systems, C-CODE 2023

作者： Khan, Sheharyar Shah, Syed M Adnan Arsalan, Aamir Ahmed, Wakeel University of Engineering and Technology Taxila Department of Computer Science Taxila Pakistan Fatima Jinnah Women University Rawalpindi Department of Software Engineering Rawalpindi Pakistan

ISBN: (纸本)9798350332391

Wearable gadgets are becoming a major constituent of our society due to a wide range of applications like financial transactions, unlocking automobiles, tracking health and fitness, and many more. Personal data is usually required to manage these services, however, most commercially available wearables devices either lack a user authentication mechanism or employ knowledge-based authentication like passwords, PINs, or pattern locks. In this growing digital age, it is really difficult for an individual to memorize such a huge number of passwords. In this research, we put forward a technique for recognizing users from their walking patterns recorded in real-life settings using a smartwatch accelerometer sensor. Ensemble classification techniques (bagging and boosting) are used for the purpose of user identification using the selected time domain features. Our proposed method attained the highest classification accuracy of 88.35% which transcends the existing user recognition schemes available in the literature. © 2023 IEEE.

关键词： Machine learning

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Enhancing Real-World Facial Expression Recognition: A Deep Learning Approach based on Attention Mechanisms 3

Enhancing Real-World Facial Expression Recognition: A Deep L...

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3rd International Conference on computer Science, Electronic Information Engineering and Intelligent Control technology, CEI 2023

作者： Wu, Kai Chen, Zhuang Chongqing University of Posts and Telecommunications Department of Software Engineering Chongqing400065 China Chongqing University of Technology Department of Computer Science and Engineering Chongqing China

ISBN: (纸本)9798350372052

Occlusion and pose variation are the biggest interference factors in real-world face expression recognition (FER). Faces are likely to be occluded by items such as sunglasses, ducktails, and scarves, which can significantly change the visual appearance of the face, while varied poses can lead to partial information loss and inaccurate localization. In this paper, we propose a new deep learning network model for facial expression recognition, firstly, an attention mechanism module is added on top of the residual neural network, which includes spatial and channel attention modules for suppressing unimportant feature information and highlight the key information. Second, a regional attention mechanism is added for adaptively extracting feature vectors from localized unobstructed facial regions, which are combined with global feature information to learn more comprehensive and detailed potential key information. The proposed method achieved good results on two facial expression datasets, FER2013 and RAF-DB, obtaining an accuracy of 74.37 and 89.12, respectively. © 2023 IEEE.

关键词： Face recognition

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Modelling and Verification of Context-Aware Intelligent Assistive Formalism

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computers, Materials & Continua 2022年第5期71卷 3355-3373页

作者： Shahid Yousaf Hafiz Mahfooz Ul Haque Abbas Khalid Muhammad Adnan Hashmi Eraj Khan Department of Computer Science&IT The University of LahoreLahore54000Pakistan Department of Software Engineering The University of LahoreLahore54000Pakistan Higher Colleges of Technology Abu Dhabi25026UAE

Recent years have witnessed the expeditious evolution of intelligentsmart devices and autonomous software technologies with the expandeddomains of computing from workplaces to smart computing in everydayroutine life activities. This trend has been rapidly advancing towards the newgeneration of systems where smart devices play vital roles in acting intelligently on behalf of the users. Context-awareness has emerged from the pervasive computing paradigm. Context-aware systems have the ability to acquirecontextual information from the surrounding environment autonomously,perform reasoning on it, and then adapt their behaviors accordingly. With theproliferation of context-aware systems and smart sensors, real-time monitoring of environmental situations (context) has become quite trivial. However,it is often challenging because the imperfect nature of context can cause theinconsistent behavior of the system. In this paper, we propose a contextaware intelligent decision support formalism to assist cognitively impairedpeople in managing their routine life activities. For this, we present a semanticknowledge-based framework to contextualize the information from the environment using the protégé ontology editor and Semantic Web Rule Language(SWRL) rules. The set of contextualized information and the set of rulesacquired from the ontology can be used to model Context-aware Multi-AgentSystems (CMAS) in order to autonomously plan all activities of the users andnotify users to act accordingly. To illustrate the use of the proposed formalism,we model a case study of Mild Cognitive Impaired (MCI) patients usingColored Petri Nets (CPN) to show the reasoning process on how the contextaware agents collaboratively plan activities on the user’s behalf and validatethe correctness properties of the system.

关键词： Context-awareness multi-agents colored petri net ontology

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A Review of Lightweight Security and Privacy for Resource-Constrained IoT Devices

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computers, Materials & Continua 2024年第1期78卷 31-63页

作者： Sunil Kumar Dilip Kumar Ramraj Dangi Gaurav Choudhary Nicola Dragoni Ilsun You Department of Computer Science and Engineering National Institute of Technology JamshedpurJamshedpurIndia School of Computing Science and Engineering VIT University BhopalBhopal466114India Center for Industrial Software The Maersk Mc-Kinney Moller InstituteUniversity of Southern DenmarkSonderborgOdenseDenmark Department of Applied Mathematics and Computer Science Technical University of DenmarkLyngby2800Denmark Department of Information Security Cryptologyand MathematicsKookmin UniversitySeoulSouth Korea

The widespread and growing interest in the Internet of Things(IoT)may be attributed to its usefulness in many different *** settings are probed for data,which is then transferred via linked *** are several hurdles to overcome when putting IoT into practice,from managing server infrastructure to coordinating the use of tiny *** it comes to deploying IoT,everyone agrees that security is the biggest *** is due to the fact that a large number of IoT devices exist in the physicalworld and thatmany of themhave constrained resources such as electricity,memory,processing power,and square *** research intends to analyse resource-constrained IoT devices,including RFID tags,sensors,and smart cards,and the issues involved with protecting them in such restricted *** lightweight cryptography,the information sent between these gadgets may be *** order to provide a holistic picture,this research evaluates and contrasts well-known algorithms based on their implementation cost,hardware/software efficiency,and attack resistance *** also emphasised how essential lightweight encryption is for striking a good cost-to-performance-to-security ratio.

关键词： IoT a sensor device lightweight cryptography block cipher smart card security and privacy

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