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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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A Survey of Dynamic Exploration Symmetric Encryption with Backward & Forward Secrecy 3

A Survey of Dynamic Exploration Symmetric Encryption with Ba...

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3rd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2023

作者： Singh, Satendra Bhagat, Samriti Vivekananda Global University Department of Computer Science Engineering Jaipur India Chandigarh School of Business Department of Master of Computer Application India

ISBN: (纸本)9798350399264

A sophisticated type of symmetric encryption is called Multiuser Dynamic Searchable Symmetric Encryption. It expands the capabilities of conventional symmetric encryption to enable actions such as adding and removing encrypted data as well as the ability for a verified set of information users to access their preferred encrypted data within the dynamic database. The latter can use using erased data and search results to comprehend the content, while the former allows attackers to discover by performing file injection attacks, keywords from the injected data were exposed. can do. To our knowledge, the available literature has not completely addressed these privacy problems for M-DSSE. In light of this, our attention is directed toward multiuser dynamic searchable symmetric encryption that satisfies the requirements for forwarding and backward security. It uses Inverted indexes are created and updated using random number generator Functions (RNG) and Authenticator primitives search tokens to suggest specific solutions. In the accidental model, the suggested approach is shown to be secure. Additionally, the performance study demonstrates that the suggested approach provides increased security assurances at a fair cost to efficiency. © 2023 IEEE.

关键词： Cryptography

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A Method to Evaluate User-Centered Self-Adaptive Systems for Smart Environments 10

A Method to Evaluate User-Centered Self-Adaptive Systems for...

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10th International Conference on eDemocracy and eGovernment, ICEDEG 2024

作者： Avila, Marcelo Quito, Christian Valdez, Wilson Cardenas-Delgado, Paul Cedillo, Priscila Universidad de Cuenca Computer Science Department Cuenca Ecuador University of Szeged Software Engineering Department Szeged Hungary

ISBN: (纸本)9798350365535

With the advent of Industry 4.0, Ambient Intelligence, and other related technologies, self-Adaptation has been seen in modern systems. In this sense, Human-computer Interaction (HCI) requires an approach focused on the user and the environment, which facilitates and enhances the use of the systems. In this context, the quality of Self-Adaptive Systems (SAS) is essential for their adoption, dissemination, and service. Thus, this study introduces a detailed evaluation method to analyze the quality of HCI in SAS, providing a solution applicable to various contexts aligned with the standard ISO/IEC 25040. This study also presents a quality model aligned with the ISO/IEC 25010 standard. The quality evaluation method allows the objective definition for the measurement application through specific metrics that determine the degree of functional adequacy and interaction capability. Finally, this study demonstrates how to perform a detailed evaluation of the quality of HCI in SAS, using as an example the evaluation of the Spotify system as a case study, applying metrics to evaluate functional adequacy and interaction capacity aligned with ISO/IEC 25040 and 25010 standards. © 2024 IEEE.

关键词： ISO Standards

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Internet of Things (IoT) applications security trends and challenges

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Discover Internet of Things 2024年第1期4卷 1-22页

作者： Laghari, Asif Ali Li, Hang Khan, Abdullah Ayub Shoulin, Yin Karim, Shahid Khani, Muhammad Adnan Kaim Software College Shenyang Normal University Shenyang China Department of Computer Science Bahria University Karachi Campus Karachi75000 Pakistan School of Information Engineering Xi’an Eurasia University Shaanxi Xian710065 China Department of Computer Science Ilma University Karachi Pakistan

The idea behind layered design is the foundation of the Internet of Things. Each tier uses a variety of technologies for capacity, preparation, and information transmission. With regard to the risks and vulnerabilities related to IoT-enabled devices, as well as potential assurance mechanisms in light of equipment constraints and novel information transfer techniques, this study attempts to analyze the current architecture of the Internet of Things. After that, we talk about IoT architecture and applications. The following is a list of effective real-time IoT applications that are now in use: Self-driving cars, traffic management systems, smart grids, logistic management hierarchies, environment monitoring, building safety applications, and many more are examples of emerging technologies. Specifically, we highlight the latest improvements and challenges associated with IoT security. Finally, we discuss the state-of-the-art research and its conclusions, as well as the outstanding problems for future IoT security research. © The Author(s) 2024.

关键词： Cloud security

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Empowering Learning Analytics with Business Intelligence 2

Empowering Learning Analytics with Business Intelligence

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2nd International Conference on Cyber Resilience, ICCR 2024

作者： El-Khalili, Nuha Abu Arqoub, Muhammad Hasan, Mohammad Al-Shaikh Banna, Abed Alkarim Arafah, Mohammad University Of Petra Software Engineering Department Amman Jordan University Of Petra Computer Science Department Amman Jordan Brunel University London Computer Science Department London United Kingdom

ISBN: (纸本)9798350394962

Business Intelligence (BI) tools can provide benefits to various stakeholders in Higher Education Institutions (HEI) and support the academic process. We use BI tools to visualize data produced from learning analytics systems at the University of Petra (UOP). The utilized data come from two different sources: a learning outcomes calculation system and a student registration system. In this work, we visualize the data as dashboards using power BI to help students and advisors to monitor the progress of student attainment of program outcomes over the courses and years of study, thus facilitating the prediction of student performance. We also visualize the attainment of program outcomes in relation to student attributes, which facilitate data- driven decision making. The future work of this work is to collect data for a full cohort, to be used for prediction of student performance. © 2024 IEEE.

关键词： Students

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Dynamic Multimedia Encryption Using a Parallel File System Based on Multi-Core Processors 4

Dynamic Multimedia Encryption Using a Parallel File System B...

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4th IEEE International Conference on Data engineering and Communication Systems, ICDECS 2024

作者： Simi Margarat, G. Malathi, S. Pasumpon Pandian, A. Anakath, A.S. Kannadasan, R. New Prince Shri Bhavani College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Grt Institute of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Tiruttani India Care College of Engineering Department of Computer Science and Engineering Trichy India Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India School of Computer Science and Engineering Department of Software Systems Tamil Nadu Vellore India

ISBN: (纸本)9798350393354

A new parallel file system and multi-core processor-based dynamic multimedia encryption method is presented in this study. Multimedia encryption efficiency and security were the main goals, addressing massive data sets and high-speed processing. We created a dynamic encryption algorithm for multimedia content, supported by a strong parallel file system and tuned for multi-core processing. Multiple tests showed significant improvements in encryption and decryption times, retaining short durations for real-time applications. After encryption, the system maintained multimedia content quality and accuracy with data integrity rates nearing 100%. Balanced CPU utilization showed efficient resource use and processor load management. The system's excellent throughput efficiency showed its capacity to process enormous amounts of data. These results indicate that parallel file systems and multi-core CPUs may solve multimedia encryption problems. Adaptable and scalable, the system supports many multimedia formats and sizes. This paper proposes a multimedia encryption system that improves performance data security and integrity, paving the way for safe multimedia processing advances. © 2024 IEEE.

关键词： Cryptography

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Deep Learning Based Automated Lip Reading for Deaf 3

Deep Learning Based Automated Lip Reading for Deaf

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3rd International Conference for Advancement in Technology, ICONAT 2024

作者： Prathyakshini Prathwini Pratheeksha Hegde, N. Vaishali Rashmi, N. Kumar, Archana Praveen NMAM Institute of Technology Department of Information Science and Engineering Karkala Nitte India NMAM Institute of Technology Department of Master of Computer Applications Karkala Nitte India NMAM Institute of Technology Department of Computer Science and Engineering Karkala Nitte India Manipal Academy of Education Manipal Institute of Technology Department of Computer Science and Engineering India

ISBN: (纸本)9798350354171

Speech recognition systems play an integral role in numerous applications, from virtual assistants to accessibility tools. This paper offers a new viewpoint to speech recognition utilizing computer vision and deep learning techniques. The proposed system is trained on a sizable dataset comprising 700 video clips of individuals uttering predefined words, add up to approximately 3 GB of data. Leveraging TensorFlow and Keras, model architecture is designed incorporating convolutional and dense layers. The training process yielded promising results, with a training accuracy of 95.7% and a validation accuracy of 98.5%, indicative of robust classification performance. The integration of computer vision enriches the system's ability to extract meaningful features from audio-visual inputs, enhancing its overall recognition accuracy. Proposed method demonstrates significant potential for real-time speech recognition applications in different areas, like human-computer interaction and assistive technologies. © 2024 IEEE.

关键词： Assistive technology

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Image Forgery Detection Using Deep Learning 7th

Image Forgery Detection Using Deep Learning

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7th International Conference on Smart Trends in Computing and Communications, SmartCom 2023

作者： Koshy, Litty Chithu, K. Department of Computer Science and Engineering SCMS School of Engineering & Technology Ernakulam India Master of Computer Applications SCMS School of Engineering & Technology Ernakulam India

ISBN: (纸本)9789819908370

Since cameras are so widely available, taking pictures has become more and more common. In order to gain more information, it is frequently necessary to enhance photographs, which are crucial in our daily lives as memories or sources of wealth of information. There are many tools accessible to enhance the quality of photos;however, some of them are also widely used to alter images, leading to the dissemination of false information. This makes picture forgeries more severe and frequent, which is now a major cause of concern. To identify fake images, many conventional methods have been developed over time. Convolutional neural networks (CNNs) have drawn a lot of interest recently, and they have had an impact on the area of picture fraud detection as well. However, the majority of CNN-based picture forgery detection methods currently used in the literature are restricted to identifying a certain kind of fraud (either image splicing or copymove). As a result, a method that can quickly and precisely identify any hidden forgeries in a picture is needed. We present a powerful deep learning-based approach for detecting picture forgeries in this study. The RGB format images converted to error level analysis (ELA) are used to train our model. The suggested model is compact, and its effectiveness shows that it outperforms cutting-edge methods in terms of speed. The experiment's findings are promising, with a 91.37% total validation accuracy. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Convolutional neural networks

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Personalized Confederation Training for Smart Iot Systems: A Cloud - Delivered Structure 3

Personalized Confederation Training for Smart Iot Systems: A...

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3rd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2023

作者： Katariya, Jitendra Kumar Nivesh Vivekananda Global University Department of Computer Science Engineering India Chandigarh School of Business Department of Master of Computer Application Jhanjeri India

ISBN: (纸本)9798350399264

The Internet of Things (IoT) has significantly impacted many facets of contemporary life, and several sophisticated IoT applications and services are already being developed. Recently, the concept of federated learning has been proposed in order to train a globally shared model on IoT devices utilising a large number of user-generated data samples while stopping data leak. Due to the widespread heterogeneities in device, statistics, and model in complex IoT contexts, traditional federated learning is not suitable for instant implementation. In this paper, we present a cloud-edge architecture for intelligent IoT applications that includes a customised federated learning framework. To address the heterogeneity worries in IoT conditions, we examine imaginative altered united learning calculations that could diminish the unfortunate results brought about by heterogeneities in various aspects. The advantages of edge registering empower smart IoT applications to meet the models for high handling pace and low inertness. At long last, we give a contextual investigation of human movement recognition in light of Web of Things to show the advantages of customisable combined learning for intelligent IoT applications. © 2023 IEEE.

关键词： Internet of things

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A survey on security analysis of Amazon echo devices

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High-Confidence Computing 2022年第4期2卷 28-36页

作者： Surendra Pathak Sheikh Ariful Islam Honglu Jiang Lei Xu Emmett Tomai Department of Computer Science The University of Texas Rio Grande ValleyUSA Department of Computer Science and Software Engineering Miami UniversityUSA Department of Computer Science Kent State UniversityUSA

Since its launch in 2014,Amazon Echo family of devices has seen a considerable increase in adaptation in consumer homes and *** a market worth millions of dollars,Echo is used for diverse tasks such as accessing online information,making phone calls,purchasing items,and controlling the smart *** offers user-friendly voice interaction to automate everyday tasks making it a massive *** many people view Amazon Echo as a helpful assistant at home or office,few know its underlying security and privacy *** this paper,we present the findings of our research on Amazon Echo’s security and privacy *** findings are divided into different categories by vulnerability or *** proposed mitigation(s)to the vulnerabilities are also presented in the *** conclude that though numerous privacy concerns and security vulnerabilities associated with the device are mitigated,many vulnerabilities still need to be addressed.

关键词： Amazon echo Privacy Security Intelligent virtual assistants

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