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Information and Communication Technology for Development for Africa (ICT4DA), International Conference on

作者： Hambisa Mitiku Gebre Getachew Mamo Wegari Department of Information Science Faculty of Computing and Informatics Jimma University Jimma Ethiopia Department of Information Technology Faculty of Computing and Informatics Jimma University Jimma Ethiopia

ISBN: (数字)9798331527792

ISBN: (纸本)9798331527808

Background:- Breast cancer is one of the most common and lethal diseases in the world. Traditional breast cancer diagnostic and prognosis procedures usually involve significant human talent and can be time-consuming and subjective, leading to potential errors and treatment delays. Two recent technical advancements, deep learning, and big data analytics are promising to improve breast cancer diagnosis and therapy. As a result, this systematic review aims to examine specific papers that describe deep learning techniques and big data analytics in the context of breast cancer diagnosis and ***: Using Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA), peer-reviewed articles published in the English language from January 2020 to August 2023 were selected from electronic databases such as PubMed, ACM, Digital Library, and Science Direct, as well as citations and manual searches. This review paper takes into account papers about deep learning algorithms, big data analytics, the efficacy of deep learning and big data analytics, as well as the problems and limitations of merging deep learning methods with big data analytics. Articles that were not original or in English were not ***: - Ten articles were identified for this review. The finding showed that deep-learning techniques play a great role in analyzing vast datasets to identify malignant cells or tumors, aiding radiologists in accurate diagnoses and improving patient outcomes. Big data analytics in breast cancer diagnosis and treatment can improve accuracy, efficiency, and patient-centered care. Deep learning techniques are utilized with big data, enhancing screening test accuracy and guiding diagnostic procedures, especially for image-based scanning that leads to early breast cancer identification, improving patient outcomes, and potentially enhancing diagnostics. Obtaining huge volumes of high-quality data for training deep learning models is a challenge and limita

关键词： Deep learning Training Accuracy Merging Medical treatment Manuals Big Data Breast cancer Prognostics and health management Tumors

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Well-founded Semantics for Recursive SHACL 4

Well-founded Semantics for Recursive SHACL

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4th International Workshop on the Resurgence of Datalog in Academia and Industry, Datalog-2.0 2022

作者： Chmurovic, Adrian Šimkus, Mantas Faculty of Informatics TU Wien Austria Department of Computing Science Umeå University Sweden

W3C has recently introduced SHACL as a new standard for integrity constraints on RDF graphs. Unfortunately, the standard defines the semantics of non-recursive constraints only, which has spurred recent research efforts into finding a suitable, mathematically crisp semantics for constraints with cyclic dependencies. To this end, Corman et al. [1] introduced a semantics related to supported models known in logic programming, while Andresel et al. [2] presented a semantics based on stable models known in Answer Set Programming (ASP). In this paper, we argue that recursive SHACL can be naturally equipped with a semantics inspired in the well-founded semantics for (recursive) DATALOG queries with default negation. This semantics is not only intuitive, but it is also computationally tractable, unlike the previous proposals. To draw a connection with the classic definition of well-founded semantics in logic programming, we provide a simple translation of recursive SHACL under the well-founded semantics into propositional logic programs under the well-founded semantics. This translation is not only of theoretical interest: It can be efficiently implemented using the functionality of standard RDF triple stores (specifically, by issuing a small number of SPARQL queries), followed by an efficient evaluation using an existing engine for computing the well-founded model of a propositional logic program. © 2022 Copyright for this paper by its authors.

关键词： Semantics

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Cybersecurity and Smart Cities: Current Status and Future

Cybersecurity and Smart Cities: Current Status and Future

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2023 IEEE International Conference on Emerging Trends in Engineering, Sciences and Technology, ICES and T 2023

作者： Habib, Muhammad Yasir Qureshi, Haseeb Ahmad Khan, Shujahat Ali Mansoor, Zara Chishti, Abdul Rehman The Islamia University of Bahawalpur Faculty of Engineering Dept. of Electronic Engineering Pakistan Bournemouth University Faculty of Computing Dept. of Computing and Informatics Bournemouth United Kingdom Charles Darwin University College of Engineering IT and Environment Darwin Australia

ISBN: (纸本)9781665455602

A Smart city implements the latest IoT and information and communication technologies (ICT) to improve the quality of urban city administrations, decrease expenditures, asset management and interconnect citizens of a Smart city. Smart cities offer numerous advantages like improved energy productivity, management, healthcare facilities, efficient transport systems, proper waste and water management, and individual security. Nonetheless, this reliance on ICT and IoT technologies makes a Smart city prone to digital cyber assaults. These technologies are vulnerable to many security issues like Information theft, Eaves-dropping attack, Denial of service, Communication delays, Data manipulation, IoT security attacks, Communication interception, Jamming, Sensor failure, insecure API, and Remote exploitation. This research study intends to address opinions on cybersecurity technologies, vulnerabilities, and cybercrime awareness based on the systematic literature review 'PRISMA Model' as our research method and help researchers and practitioners to look for innovative Smart City solutions. Our research endeavors to momentarily depict the central ideas of digital security and protection issues related to Smart city areas and uncover digital cyber-Attacks that focus on Smart city communities in the literature. In brief, the focus of this research is to explore and review the aspects of Smart city cybersecurity issues, Smart city vulnerabilities related to information security, and provide a comprehensive research framework that will help the researchers and practitioners explore this area of research. © 2023 IEEE.

关键词： Cybersecurity

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PSO Based Multi-Objective Approach for Controlling PID Controller

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Computers, Materials & Continua 2022年第6期71卷 4409-4423页

作者： Harsh Goud Prakash Chandra Sharma Kashif Nisar Ag.Asri Ag.Ibrahim Muhammad Reazul Haque Narendra Singh Yadav Pankaj Swarnkar Manoj Gupta Laxmi Chand Indian Institute of Information Technology NagpurIndia School of Computing&Information Technology Manipal UniversityJaipur(Rajasthan)India Faculty of Computing and Informatics University Malaysia SabahJalan UMS88400Kota Kinabalu SabahMalaysia Faculty of Computing&Informatics Multimedia UniversityPersiaran Multimedia63100CyberjayaSelangorMalaysia Maulana Azad National Institute of Technology BhopalIndia Department of Electronics and Communication Engineering JECRC UniversityJaipur(Rajasthan)India

CSTR(Continuous stirred tank reactor)is employed in process control and chemical industries to improve response characteristics and system *** has a highly nonlinear characteristic that includes complexities in its control and *** performance is compassionate to change in system parameterswhich need more effort for planning a significant controller for *** reactor temperature changes in either direction from the defined reference *** is important to note that the intensity of chemical actions inside the CSTR is dependent on the various levels of temperature,and deviation from reference values may cause degradation of biomass *** and implementation of an appropriate adaptive controller for such a nonlinear system are *** this paper,a conventional Proportional Integral Derivative(PID)controller is *** conventional techniques to deal with constraints suffer severe limitations like it has fixed controller ***,A novel method is applied for computing the PID controller parameters using a swarm algorithm that overcomes the conventional controller’s *** the proposed technique,PID parameters are tuned by Particle Swarm Optimization(PSO).It is not easy to choose the suitable objective function to design a PID controller using PSO to get an optimal *** this article,a multi-objective function is proposed for PSO based controller design of CSTR.

关键词： Particle swarm optimization multi-objective PSO continuous stirred tank reactor proportional integral derivative controller

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Vision-Based Dynamic Hand Gesture Recognition Techniques and Applications: A Review 1

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8th International Conference on Computational Science and Technology, ICCST 2021

作者： Franslin, Nurfazlin Muhamad Feizal Ng, Giap Weng Faculty of Computing and Informatics Universiti Malaysia Sabah Sabah Kota Kinabalu88400 Malaysia

ISBN: (数字)9789811685156

ISBN: (纸本)9789811685149

Hand gesture recognition is an area in computer science that focuses on utilizing mathematical algorithms to analyze human gestures. The aim of this study is to perform a review evaluating related input devices, techniques, limitations and problems of dynamic hand gesture recognition using vision-based methods. More precisely, the hand gesture recognition process is divided into four stages: (a) input image, (b) segmentation, (c) feature extraction and (d) classification/recognition. Gesture control is the ability to acknowledge and interpret human body movements using a variety of gestures or motions made in the air by interacting and controlling devices without having the need to physically touch them. The Single Camera, Leap Motion Controller (LMC) and Microsoft Kinect are the three vision-based hand gestures devices that are compared in this review paper. We found out that the Single Camera is able to perform and achieve an accuracy rate of more than 95%. Besides, this paper not only is able to differentiate and compare the accuracy rate between the input devices, but also between the techniques applied which consists of (a) Hidden Markov Model, (b) Dynamic Time warping and (c) Neural Network including their advantages as well as the disadvantages. The applications that are used in vision-based dynamic hand gesture recognition are presented. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Computer vision

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Improved QoS in Internet of Things (IoTs) through Short Messages Encryption Scheme for Wireless Sensor Communication

Improved QoS in Internet of Things (IoTs) through Short Mess...

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2022 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2022

作者： Kazmi, Syed Hussain Ali Qamar, Faizan Hassan, Rosilah Nisar, Kashif Selangor43600 Malaysia University Malaysia Sabah Faculty of Computing and Informatics Sabah Malaysia

ISBN: (纸本)9798350332421

Global interest in Internet of Things (IoTs) can be accorded to the provisioning of Wireless Sensors Communication (WSC). Sensor data cannot be standardized due to diverse nature of measurements. However, the sensor's data needs to be converted into standard size for compatibility with encryption schemes. Therefore, IoTs face various processing and communication overhead issues for acceptable Quality of Service (QoS) in WSC. We proposed a communication model of the Short Messages Encryption Scheme (SMES) Model with the least additional padding in plain text. We performed a comparative analysis of various existing encryption modes and highlighted the limitations concerning compatibility with SMES. Our communication model utilizes Time of Day (TOD) based loose synchronization intervals in combination with Cipher Feed-Back (CFB) mode of AES encryption. Our evaluation of the proposed scheme shows least processing requirements and overheads in comparison with various other encryption modes. We concluded this paper by deliberating possible future research directions in SMES for IoTs. © 2022 IEEE.

关键词： Cryptography

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Refactoring = Substitution + Rewriting Towards Generic, Language-Independent Refactorings

Refactoring = Substitution + Rewriting Towards Generic, Lang...

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2023 Eelco Visser Commemorative Symposium, EVCS 2023

作者： Thompson, Simon Horpácsi, Dániel School of Computing University of Kent Canterbury United Kingdom Faculty of Informatics Eötvös Loránd University Budapest Hungary

ISBN: (纸本)9783959772679

Eelco Visser’s work has always encouraged stepping back from the particular to look at the underlying, conceptual problems. In that spirit we present an approach to describing refactorings that abstracts away from particular refactorings to classes of similar transformations, and presents an implementation of these that works by substitution and subsequent rewriting. Substitution is language-independent under this approach, while the rewrites embody language-specific aspects. Intriguingly, it also goes back to work on API migration by Huiqing Li and the first author, and sets refactoring in that general context. © Simon Thompson and Dániel Horpácsi;licensed under Creative Commons License CC-BY 4.0.

关键词： API upgrade generic language independent refactoring rewriting substitution

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Color-based shadow detection method in aerial images 3

Color-based shadow detection method in aerial images

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3rd International Conference on Emerging Electrical Energy, Electronics and computing Technologies 2021, ICE4CT 2021

作者： M-Desa, S. Zali, S.A. Mohd-Isa, W.N. Che-Embi, Z. Faculty of Computing and Informatics Multimedia University Persiaran Multimedia Selangor Cyberjaya63100 Malaysia

This study evaluates the performance of shadow detection using different image color models. The pixel-level supervised classification procedure employed in this study includes filtering images, creating a trained shadow model, obtaining shadow masks and post-processing of the output masks. Considering the advent of drones usage, we discuss the results of shadow detection on aerial images. Based on the results, the method using YCbCr color features yielded 92.71% average accuracy. The low performance of shadow detection on images with small shadowed regions and images under various weather conditions indicated that additional investigation is necessary to create detection schemes for challenging input images with high spatial resolution. © Published under licence by IOP Publishing Ltd.

关键词： Color

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RT-PPS: Real-time privacy-preserving scheme for cloud-hosted IoT data

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Journal of High Speed Networks 2025年第1期31卷 71-89页

作者： Elhoseny, Mohamed Riad, Khaled College of Computing and Informatics University of Sharjah Sharjah27272 United Arab Emirates Faculty of Computers and Information Mansoura University Mansoura35516 Egypt Computer Science Department College of Computer Sciences & Information Technology King Faisal University Al-Ahsa 31982 Saudi Arabia Mathematics Department Faculty of Science Zagazig University Zagazig44519 Egypt

The Internet of Things (IoT) is a rapidly growing network of devices that can communicate with each other and with cloud-based services. These devices generate vast amounts of data that can be used to provide valuable insights into user behavior, environmental conditions, and other important factors. However, as this data is collected and processed by cloud-hosted services, there is a growing concern about privacy and security. Without adequate protection, sensitive information could be exposed to hackers or other malicious actors, putting both individuals and organizations at risk. To address this challenge, real-time privacy-preserving techniques can be used to protect IoT data without compromising its value. This paper introduces an efficient Real-time privacy-preserving scheme (RT-PPS) for cloud-hosted IoT data. RT-PPS employs multi-authority attribute-based encryption on a hybrid cloud environment to keep data secure and private, while still allowing it to be processed and analyzed by cloud-hosted services. RT-PPS has efficient response time and resource consumption, which gives it the ability to handle a huge number of concurrent users at the same time without notable delay. The proposed RT-PPS has been validated through extensive experimental evaluation on a variety of configurations. Moreover, the proposed scheme has been computationally compared with the state-of-the-artwork. RT-PPS has shown excellent performance, effectiveness, and efficiency. The RT-PPS encryption time for a 1 GB dataset while considering 1024 slices is approximately 1000 ms. Also, the RT-PPS decryption time for a 1 GB ciphertext while considering 1024 slices are approximately 235 ms. Finally, RT-PPS is proven secure against any polynomial-time attacks and their variations that have at most a negligible advantage in the introduced security model. Moreover compared to most of the state-of-the-artwork, RT-PPS reduced the ciphertext size and lowered the computations in the encryption, key g

关键词： Ciphertext

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Superficial Wound Classification Using CNN Image Classifier for Initial Wound Care

Superficial Wound Classification Using CNN Image Classifier ...

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IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)

作者： Sitti Wan Fazirah Ambo'Miri Lai Po Hung Florence Sia Fui Sze Tan Soo Fun Faculty of Computing and Informatics Universiti Malaysia Sabah Sabah Malaysia

ISBN: (数字)9798350389692

ISBN: (纸本)9798350389708

Proper diagnosis of the types of wounds is the first step in effective wound management. Healthcare quality can be improved with the use of artificial intelligence technology. In this project, convolutional neural network (CNN) models are employed for superficial wound image classification. The goal of this project is to implement carefully selected CNN models with fine-tuned parameters (batch sizes, augmentation parameters and epoch size) to categorize superficial wounds of abrasion, bruise and superficial skin burns. The library and functions from TensorFlow, Keras, MatplotLib and OpenCv will be used alongside the Python programming language to create this project in a Google Colaboratory notebook, also widely known as Colab. This work evaluates the CNN models of VGG-16, InceptionV3 and ResNet-50 to find out which best classifies the dataset of non-fatal superficial wounds. These models have significant differences especially in their number of layers and concepts of capturing the features of images input. By utilizing these models, the accuracy rate of more than 40% is observed after models being trained and validated on 90% of the dataset (80% for training and 20 for validation), then tested and prediction with the remaining 10% of the dataset for classification report and confusion matrix generation. Out of 3 CNN models used in this study, it is observed that InceptionV3 model's highest accuracy is 44% while both ResNet50 and VGG-16 model achieved 45% accuracy against the superficial wound database (non-fatal wound).

关键词： Training Accuracy Medical services Wounds Predictive models Internet Convolutional neural networks Artificial intelligence Image classification Biomedical imaging

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