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International Conference on Advancement in Electrical and Electronic engineering (ICAEEE)

作者： Eshat Ahmad Shuvo Wahidur Rahman Md Shakhawat Hossain Md. Tarequl Islam Md. Sadiq Iqbal Dept. of Computer Science and Engineering Bangladesh University Adabor Bangladesh Dept. of Computer Science and Engineering Uttara University Uttara Dhaka Bangladesh Dept. of Computer Science & Engineering & RIoT Center Independent University Bangladesh Dept. of Computer Science & Engineering Khwaja Yunus Ali University Sirajganj Bangladesh

ISBN: (数字)9798350388282

ISBN: (纸本)9798350388299

Diabetic retinopathy (DR) is a common yet fatal complication of diabetic patients in which high levels of blood sugar damage the blood vessels in the retina, the light-sensitive eye tissue crucial for human vision. Early detection and timely intervention are essential to managing DR and preventing severe vision loss. Traditionally, the examination is performed by ophthalmologists manually examining the retinal fundus images to check for signs of DR. This approach is helpful but subjective, time-consuming and tedious. Artificial intelligence (AI)-guided computer vision has recently become very compelling and practical for image analysis and diagnosis. Existing AI-based methods achieved sufficient accuracy at the cost of high computing resources and large datasets. This paper proposes a cascaded network incorporating deep learning and the traditional machine learning approaches with a bio-inspired heuristic optimization algorithm for DR detection from fundus images. The proposed method achieved sufficient accuracy (97.1%) when trained using limited data and low computing machines. The AI models for the cascaded networks were selected through an exhaustive search in which five popular CNN models were used for extracting features; the Bacterial foraging optimization (BFO) was used to determine optimal features, and seven traditional machine models were used to detect the DR. The ResNet50-BFO-SVC cascaded network was found to be most suitable in this study. The proposed cascaded network brings efficiency, accuracy, scalability, and robustness to DR screening.

关键词： Diabetic retinopathy Accuracy Microorganisms Computational modeling Biological system modeling Scalability Feature extraction

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Clinical Score Estimation for Determining Oro-Facial Dysfunction Severity 23

Clinical Score Estimation for Determining Oro-Facial Dysfunc...

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2023 International Conference on Robotics, Control and Vision engineering, RCVE 2023

作者： Ipapo, Trassandra Jewelle Del Rosario, Charlize Abu, Patricia Angela Alampay, Raphael Ateneo Laboratory for Intelligent Visual Environment Dept. of Information Systems and Computer Science Ateneo de Manila University Quezon City Philippines

ISBN: (纸本)9798400707742

Stroke and amyotrophic lateral sclerosis manifest symptoms that affect facial motion in patients. Tracking these movements and assessing the severity of the impairment can be achieved with facial alignment technology and classification algorithms. Using the Toronto NeuroFace Dataset consisting of patients and healthy individuals performing clinical examination tasks, this study focuses on score estimation of clinical examinations to determine oro-facial dysfunction severity. Facial landmarks extracted using the 2D FAN were used to determine features under range of motion, speed of motion, and symmetry. Speech language pathologist scores from the dataset were transformed using ordinal encoding, then oversampled using random oversampling. The features and transformed scores were fed into random forest classifier models to predict a score using a scale of 1 to 4 for each feature category. The results show that the proposed method is able to estimate oro-facial dysfunction severity and classify between healthy individuals and patients. The average performance of the model setups are comparable to that of the baseline in terms of accuracy ( © 2023 ACM.

关键词： Score Estimation Face Alignment Oro-facial Dysfunction Ordinal Classification

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Control Techniques Review for the Ball-on-Sphere (BOS) System 2

Control Techniques Review for the Ball-on-Sphere (BOS) Syste...

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2nd International Conference on Multidisciplinary engineering and Applied Science, ICMEAS 2023

作者： Mohammed, Usman Karataev, Tologon Oghenewvoaaaa, Oghorada Oshiga, Omotayo O. Kasimu, Abdullahi Abba Thomas, Sadiq Nile University of Nigeria Dept. of Elect/Elect Engineering Abuja Nigeria Head Office Leading Diagonal Engineering Ltd Abuja Nigeria Nile University of Nigeria Dept. of Computer Engineering Abuja Nigeria

ISBN: (纸本)9798350358834

There are many important balancing systems in control theory. The Ball-on-Sphere (BOS) system is one of these systems. It finds applications in aerospace, transportation, robotics, etc. The system is a nonlinear multiple-input multiple-output (MIMO) system where the ball is controlled on the sphere. It is a testing ground, due to its naturally nonlinear, under-actuation, and unstable nature, in nonlinear systems control. Consequently, different techniques have been used to control the system. A review of these techniques of comprehensive nature is presented in this paper. Different reputable publishers were considered using different search engines utilizing different search terms. The techniques include Linear Quadratic Gaussian (LQG), Sliding Mode Control (SMC), Fuzzy Logic Control (FLC), Artificial Neural Network (ANN), Feedback Linearization (FL), Linear Quadratic Regulator (LQR) and their hybrids. It was established that the system is not covered much in the literature. The LQR, LQG, and SMC were found to be the most used controllers to control the system. Also, 93% of the techniques used no optimization. Additionally, it was established that more techniques need to be explored for the system control. Control techniques hybridization and exploration and optimization usage were found to be the major future directions. © 2023 IEEE.

关键词： Sliding mode control

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Kinship Recognition through Stacked Self-Calibrated Attention Network 33

Kinship Recognition through Stacked Self-Calibrated Attentio...

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33rd International Conference on computer Theory and Applications, ICCTA 2023

作者： Dabas, Ahmed A. Ghanem, Nagia M. Ismail, Mohamed A. Alexandria University Faculty of Engineering Dept. of Computer and Systems Engineering Alexandria Egypt

ISBN: (纸本)9798350309577

Kinship recognition is becoming an important path in the evolution of biometric recognition research. Over the past decade, notable progress has been achieved in this emerging field attracting more researchers to exploit new methods for its branches. The most common use case is facial kinship recognition with its two variants: verification and identification. In this paper, we propose a novel kinship verification network based on a self-calibrated attention model and residual blocks to expand the fields-of-view through the attention stack for producing more discriminative features. In addition, we extend our work to build a kinship identification network based on joint learning of self-calibrated verification ensembles. Experimental results on benchmark datasets are demonstrated to show the effectiveness of our proposed scheme when compared to state-of-the-art solutions on the kinship identification track. © 2023 IEEE.

关键词： Biometrics

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QCRMut: Quantum Circuit Random Mutant generator tool

arXiv

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arXiv 2024年

作者： Gil, Sinhué García Díaz, Luis Llana Jarabo, José Ignacio Requeno Dept. of Information Systems and Computing Faculty of Computer Engineering Complutense University of Madrid Madrid Spain

Quantum computing has been on the rise in recent years, evidenced by a surge in publications on quantum software engineering and testing. Progress in quantum hardware has also been notable, with the introduction of impressive systems like Condor boasting 1121 qubits, and IBM Quantum System Two, which employs three 133-qubit Heron processors. As this technology edges closer to practical application, ensuring the efficacy of our software becomes imperative. Mutation testing, a well-established technique in classical computing, emerges as a valuable approach in this context. In our paper, we aim to introduce QCRMut, a mutation tool tailored for quantum programs, leveraging the inherent Quantum Circuit structure. We propose a randomised approach compared to previous works with exhaustive creation processes and the capability for marking immutable positions within the circuit. These features facilitate the preservation of program structure, which is crucial for future applications such as metamorphic testing. © 2024, CC BY-NC-SA.

关键词： Application programs

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Harmonizing open banking in the European Union: an analysis of PSD2 compliance and interrelation with cybersecurity frameworks and standards

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International Cybersecurity Law Review 2024年第1期5卷 79-120页

作者： Gounari, Marianna Stergiopoulos, George Pipyros, Kosmas Gritzalis, Dimitris Dept. of Information & Communication Systems Engineering University of the Aegean Samos Greece Dept. of Computer Science Philips University Nicosia Cyprus Dept. of Informatics Athens University of Economics & Business Athens Greece

This paper focuses on the security protocols enacted in banking transactions across the European Economic Area (EEA), as stipulated by the Second or Revised Payment Service Directive (commonly referred to as ‘PSD2’ or simply ‘the Directive’). The study aims to comprehensively analyse the implementation and efficacy of these security measures within the specified jurisdiction. The Directive incorporates fundamental rights and obligations that all stakeholders are compelled to adhere to and delineates specific security measures and standards that both traditional banking institutions and third-party providers (TPP) are mandated to implement. In particular, one of the cardinal mandates for banking and financial institutions under PSD2 is the obligation to facilitate third-party access to customer data via open application programming interfaces (API). While this open banking paradigm and the consequent proliferation of data sharing unquestionably bring about various advantages, such as enhanced consumer choice and market competition, they concurrently expose the financial ecosystem to a slew of potential security vulnerabilities and privacy risks. Upon conducting a comprehensive review of the security requirements and measures stipulated under PSD2 and a comparative analysis with essential cybersecurity frameworks and standards (NIS2, Cybersecurity Act, GDPR, ISO 27001:22 and PCI DSS), we have ascertained a discernible lack of harmonisation and clarity concerning the technical security specifications for its effective implementation. This lacuna substantiates the challenges banks face in fully grasping the extensive spectrum of compliance obligations mandated by PSD2. The aim of this research is to offer a valuable contribution to both the comprehension and the pragmatic deployment of security standards in the context of banking transactions, as regulated by the PSD2. The paper serves as a valuable resource for traditional banking institut

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ML based Pre-Diagnosis Framework for early detection of Neurodevelopmental Disorders 4

ML based Pre-Diagnosis Framework for early detection of Neur...

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4th International Conference on Advancement in Electronics and Communication engineering, AECE 2024

作者： Pandey, Sumit Sharma, Srishti Agarwal, Anant The Northcap University School of Engineering and Technology Dept. of Computer Science Haryana Gurugram122017 India Aligarh Muslim University Zakir Husain College of Engg. and Tech Dept. of Electronics Engineering Uttar Pradesh Aligarh202001 India

ISBN: (纸本)9798350364729

Neurodevelopmental disorders cover a wide range of behavioral and cognitive symptoms mapped to various conditions. Early diagnosis and planned interventions are crucial for improving outcomes and the quality of life for people suffering from such disorders. This research work talks about a detailed framework with the objective of assisting in the early pre-diagnostic phase of neurodevelopmental disorders. The motivation for the development of a ML-based framework in pre-diagnosis of neurodevelopmental disorders is the effective and zero-cost getting diagnosed. This framework will integrate knowledge from diverse domains to systematize and make recognition of early signs and symptoms associated with neurodevelopmental disorders much more efficient. Additionally, the framework emphasizes two very critical parameters: accessibility and cost-effectiveness. The developed pre-diagnostic mechanism can be implemented in a diversified variety of scenarios, especially with limited resources, towards zero cost. The implementation of advanced machine learning techniques can assist in the analysis of the response to a customized questionnaire in identifying patterns that may suggest a risk of neurodevelopmental disorders. This proactive approach not only supports and facilitates early detection and intervention but also seeks to add towards the overall well-being of patients with these disorders. © 2024 IEEE.

关键词： Adversarial machine learning

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Boosted Hybrid Privacy Preserving Data Mining (BHPPDM) Technique to Increase Privacy and Accuracy 3

Boosted Hybrid Privacy Preserving Data Mining (BHPPDM) Techn...

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

作者： Prasanthi, Kundeti Naga Chandra Sekhara Rao, M.V.P. Pallapothu, Seshu Babu Lakireddy Balireddy College of Engineering Department of Computer Science and Engineering Mylavaram India Rvr and Jc College of Engineering Dept. of Cse Chowdavaram India Kakaraprthi Bhavanarayana College Dept. of Mathematics Vijayawada India

ISBN: (纸本)9781665462167

In the current scenario, large volumes of data are generated by different organizations. Data Mining (DM) applications provide suitable patterns that lead to business growth, improved health care and improved services to users etc. The Humongous data volumes may also contain some confidential information about individuals. So, this data may be exploited for identity theft, identity disclosure etc. In this situation, data mining methodologies that provide confidentiality are useful. Though Privacy-Preserving Data Mining (PPDM) methodologies like randomization, perturbation, anonymization etc., provide privacy, but when applied individually, they are ineffective. Henceforth, this article proposes a combination of these techniques called Boosted Hybrid Privacy Preserving Data Mining (BHPPDM). The proposed technique provides more privacy of data than the current methodologies whilst providing better classification accuracy as demonstrated by investigational results. © 2023 IEEE.

关键词： Data mining

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Facial Emotion Analysis using Deep Learning for Seamless Human-computer Interaction 2

Facial Emotion Analysis using Deep Learning for Seamless Hum...

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2nd IEEE International Conference on Networks, Multimedia and Information Technology, NMITCON 2024

作者： Sangeetha, S. Saini, Poonam Banupriya, R. Srimathi, S. Kiruthiga, S. Aarthi, R. Srm Arts and Science College Department of computer Applications and Technology Kattankulathur Changelpattu603203 India Sir Padampat Singhania University Dept. of Computer Science & Engineering Vil. Bhatewar Teh. Vallabhnagar Rajasthan Udaipur India Pgp College Of Engineering and Technology Dept. of Electrical and Electronics Engineering India Saveetha School of Engineering Simats Department of Bio Technology Tamilnadu Chennai India Vel Tech Rangarajan Dr Sagunthala R & D Institute of Science & Technology School of Computing Department of Computer Science & Engineering Chennai India R.M.D Engineering College Department of Ece India

ISBN: (纸本)9798350372892

HCII, or human-computer intelligent interaction, is a new academic subject that tries to make computer use more intuitive. Some say machines need human-level social abilities before interacting with people. These skills include reading emotions. Due to its exponential expansion, facial emotion recognition is becoming essential to face recognition. According on photographs, machine learning can recognise expressions. This paper discusses expression recognition model training datasets. Deep learning for Facial Emotion Recognition (FER) is used in this research to teach robots to recognise and adapt to human emotions. An extensive review of deep learning models, including CNNs and CNNR, emphasises their ability to extract spatial and temporal data needed for emotion classification. FER pipeline components like data collection, preprocessing, and model architecture are examined in the paper. Transfer learning, pre-trained models, and data augmentation are studied to address low-labeled dataset concerns. Detailed model training, validation, and evaluation metrics emphasise performance assessment. This study uses the enlarged CohnKanade (CK+) dataset from a face emotion recognition experiment. The system averaged 92.81% accuracy. Eight emotions were successfully detected by the algorithm. The proposed method for emotion recognition has proven useful. © 2024 IEEE.

关键词： Contrastive Learning

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Dantalion: Digital Twinning the Computing Continuum

Dantalion: Digital Twinning the Computing Continuum

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2023 IEEE Globecom Workshops, GC Wkshps 2023

作者： Laso, Sergio Martín, Luis Herrera, Juan Luis Galán-Jiménez, Jaime Berrocal, Javier Murillo, Juan M. Cáceres Spain University of Extremadura Dept. of Computer Systems and Telematics Engineering Spain University of Bologna Dipartamento di Informatica Scienza e Ingegneria Italy Cáceres Spain

ISBN: (纸本)9798350370218

Thanks to the Internet of Things (IoT) paradigm, it is now possible to develop computer applications that automate real, intensive processes, by processing sensor information using techniques such as artificial intelligence or computer vision. Nonetheless, due to the criticality of the processes they automate, intensive IoT applications have very strict Quality of Service (QoS) requirements to function properly, motivating their deployment throughout the Computing Continuum to optimize the obtained QoS. Evaluating and guaranteeing the QoS of this application can be a challenging endeavor, as current QoS evaluation tools are unable to predict future changes to the real world, evaluate multiple adaption alternatives, or act accordingly. To fulfill these needs, in this paper, we present the evolution of a Computing Continuum emulator towards Dantalion, a complete Digital Twin for the Computing Continuum. © 2023 IEEE.

关键词： Computing Continuum Digital Twin In-ternet of Things Quality of Service

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