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25th International Electronics Symposium, IES 2023

作者： Widarto, Mochamad Farhan Eka Marta, Bayu Sandi Dewantara, Bima Sena Bayu Setiawardhana Politeknik Elektronika Negeri Surabaya Dept. of Informatics and Computer Engineering Surabaya Indonesia

ISBN: (纸本)9798350314731

Navigation systems are very important for social robots, especially autonomous robots, because they are required to be adaptive to their surrounding environment. This paper proposes a new navigation system for the Autonomous Trash Can Robot (ATRACBOT) using the Fuzzy-based Social Force Model (F-SFM). The navigation system employed in earlier stages of development depended on the Braitenberg approach, leading to the robot's motion appearing rigid. On the other hand, the Social Force Model (SFM) employs the forces surrounding objects to engage with and evade other entities, presenting a different approach. The magnitude of the force to avoid objects is determined by the SFM parameters and the stimulus received by the robot. The Fuzzy Inference System (FIS) is used to obtain the optimal value of the gain factor, k, which is one of the SFM parameters, based on the relative distance, d, and relative angle, \gamma, between the obstacle and robot. The FIS will process both inputs and produce a suitable gain factor, k, so that the stimulus received can match the robot's reactivity and responsiveness. Based on the results from a realistic 3D simulator V-Rep, the implementation of the F-SFM method can deliver the robot to the goal point without hitting obstacles and make the robot's movements more natural compared to the Braitenberg method. © 2023 IEEE.

关键词： Navigation systems

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A Novel Deep Ensemble Learning Approach to Predict Eye Diseases from OCT Images 5

A Novel Deep Ensemble Learning Approach to Predict Eye Disea...

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5th International Conference on Sustainable Technologies for Industry 5.0, STI 2023

作者： Uddin, Nazim Mia, Md Sajib Uddin, Mohammed Nasir Mahmud, Prince Chandpur Science and Technology University Dept. of Information and Communication Technology Bangladesh Sylhet Engineering College Dept. of Computer Science and Engineering Bangladesh Jagannath University Dept. of Computer Science and Engineering Bangladesh Chandpur Science and Technology University Dept. of Computer Science and Engineering Bangladesh

ISBN: (纸本)9798350394290

As the world advances in technology, the classification of eye diseases is thought to have clinical applications since it evaluates and analyzes the results. Optometrists research and diagnose age-related eye problems such as Choroidal Neovascularization (CNV), Diabetic Macular Edema (DME), and Drusen using optical coherence tomography (OCT) of the human eye. Because their symptoms are similar, identifying these diseases is challenging and requires hours of expert analysis. The requirements for eye illness classification should be straightforward in nature, structure, and evaluation. Deep Learning Convolutional Neural Network Classification can create a hierarchical representation of images to differentiate between normal and diseased eye patterns for diagnostic purposes. Therefore, this paper aims to implement and define deep learning to classify and identify eye diseases. Using a four-class classification problem, this work investigates the automatic detection of Choroidal Neovascularization (CNV), Diabetic Macular Edema (DME), Drusen, and Normal in Optical Coherence Tomography (OCT) pictures. Multi-transfer learning architecture was used in the suggested deep learning Ensemble classification model. The most incredible accuracy of our proposed Ensemble model for multi- class classification was 83%. © 2023 IEEE.

关键词： Optical tomography

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Simplifying Digital Streaming: An Innovative Cross-Platform Streaming Solution 15

Simplifying Digital Streaming: An Innovative Cross-Platform ...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Muduli, Debendra Sahoo, Saroj Kumar Mishra, Jayanta Kumar Pradhan, Debasish Sharma, Santosh Kumar C.V Raman Global University Dept. of Computer Science Engineering Odisha Bhubaneswar India Centurion University of Technology and Management Dept. of Computer Science Engineering India GITA Autonomous College Dept. of Computer Science Engineering Odisha Bhubaneswar India

ISBN: (纸本)9798350370249

Our research aims to investigate how reinforcement learning methods can be applied to develop a movie recommendation system. We frame the issue of interactive recommendation as a contextual multi-armed bandit, where the system learns user preferences by suggesting new movies and receiving feedback. Through reinforcement learning, we address challenges such as balancing exploitation and exploration and tackling the coldstart problem. Additionally, we incorporate the novelty factor of movies into our model. We evaluate both content-based and collaborative filtering approaches which achieved accuracy 72.33(%), both of which demonstrate effective recommendation outcomes. © 2024 IEEE.

关键词： Contrastive Learning

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Detection and Classification of Cardiac Arrhythmia from Photoplethysmography Signal

Detection and Classification of Cardiac Arrhythmia from Phot...

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2023 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2023

作者： Dewantara, Bima Sena Bayu Sari, Dewi Mutiara Fahmi, Ahmad Nur Politeknik Elektronika Negeri Surabaya Dept. of Informatics and Computer Engineering Surabaya Indonesia

ISBN: (纸本)9798350319040

This paper presents the development of an application for classifying cardiac arrhythmia by utilizing photoplethys-mography sensor signals. The Photoplethysmography (PPG) sensor is used as a reader for the cardiovascular system by measuring changes in blood volume in the skin tissue. The PPG sensor captures electrical signals originating from the reflected light source due to changes in blood flow during heart activity. After going through the preprocessing stage, the signals are then extracted into several features that will be classified using the Random Forest algorithm. The results from the Random Forest algorithm will provide a diagnosis based on the detection of arrhythmia. Based on the experimental results, the accuracy achieved using the method and dataset is 72%. The accuracy of the system testing using the smartwatch under normal heart conditions is 88.88%. © 2023 IEEE.

关键词： Photoplethysmography

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Securing of Cloud Storage Data Using Hybrid AES-ECC Cryptographic Approach

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Journal of Mobile Multimedia 2023年第2期19卷 363-388页

作者： Kumar, Sunil Kumar, Dilip Dept. of Computer Science and Engineering National Institute of Technology Jamshedpur India

Internet has revolutionized the world in a way no one could have ever imagined. It paved the way for various different technologies, that have transformed the world exceptionally. Internet enabled cloud technology which provides cost-effective, scalable, on-demand computing resources with little to no downtime. Cloud storage allows its users to store and access private data from anywhere in the world without needing any high-end computing system. Cloud storage isn’t always secure, but that doesn’t imply it isn’t. The security of a data depends on the security policies followed by the provider along with the security of the communication channel via which the data is being sent. Encryption is used to obfuscate the data so that it can only be viewed when correct credentials, known as encryption keys, are provided. Following study proposes an encryption technique using ECC (Elliptic Curve Cryptography) along with AES (Advance Encryption Standard) to provide data confidentiality in an efficient way for securing data on cloud and hence, protect the personal information of user from any adversary. This new method is more effective, and the results are superior as a consequence. © 2022 River Publishers.

关键词： AES asymmetric encryption authentication blowfish cloud storage security ECC Symmetric encryption

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Cat-CNN: Human Eye Cataract Detection from Color Fundus Photograph with Deep CNN with Optimized Cascaded Network

Cat-CNN: Human Eye Cataract Detection from Color Fundus Phot...

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2024 IEEE International Conference on Signal Processing, Information, Communication and Systems, SPICSCON 2024

作者： Islam, Md Sariful Bappy, Md Tusher Ahmad Shawon, Jubayer Ahmed Hasan, Mehedi Rahman, Wahidur Akter, Lija Azad, Mir Mohammad Dept. of Computer Science and Engineering Uttara University Uttara Dhaka Bangladesh Dept. of ICE Bangladesh Army University of Engineering and Technology Natore Bangladesh Dept. of Computer Science and Engineering Inpendent Researcher Dhaka Bangladesh

ISBN: (纸本)9798331510213

Cataracts are clouding of the lens in the eye, leading to loss of vision that can progress to blindness if not treated. This paper proposed a new method for automatic cataract detection using color fundus images and deep learning methods. A dataset of 1,105 color fundus images labeled by expert ophthalmologists was used in this process. We used seven pre-trained CNNs (DenseNet121, EfficientNetB0, MobileNetV2, InceptionV3, Xception, ResNet50, VGG16, and VGG19) for feature extraction before reducing the extracted features using PCA. We used the following combination of machine learning classifiers: SVC, RF, Decision Tree, Gaussian Naive Bayes, XGBoost, K-Nearest Neighbors, and Logistic Regression. For evaluating the models’ performance, we used accuracy, precision, recall, F1-score, and computational efficiency. For all metrics, MobileNetV2 with Random Forest achieved perfect scores: 100% accuracy, precision, recall, and F1-score, with an average processing time of 669 ms ± 28.8 ms. Thus, it can be applied in real-time applications. EfficientNetB0 with SVC gave an average accuracy of 87.33%, with the rest of the precision and recall metrics above 86%. Then, ResNet50, VGG16, and VGG19 followed with high accuracies between the range of 89.64% to 90.50%. It systemizes the proper choice of architectures of CNNs and classifiers, making the system both accurate and computationally efficient. Future work will include augmentation of the dataset, real-time support in the clinical setting, and advanced techniques for image preprocessing, generative adversarial networks. In addition, the development of an automated annotation tool, improvement of explainable AI, will further improve the deployment of robust AI systems in early diagnosis of cataracts, enhancing the outcome for patients. © 2024 IEEE.

关键词： Cataract detection CNN color fundus photography deep learning feature extraction image classification machine learning ophthalmology PCA

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A Game Theoretic Approach to Enhance DCF Performance in Full Duplex Ad-hoc WLANs 12

A Game Theoretic Approach to Enhance DCF Performance in Full...

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12th International Conference on Modern Circuits and Systems Technologies, MOCAST 2023

作者： Politis, Anastasios C. Anastassiu, Hristos T. Hilas, Constantinos S. International Hellenic University Informatics and Telecommunications Engineering Dept. of Computer Serres Greece

ISBN: (纸本)9798350321074

Physical Full Duplex (FD) operation in WLANs is a promising technology aiming at substituting the traditional Half Duplex (HD) functionality. An increased performance is expected which, theoretically, can be expressed as a double increase in system throughput. However, due to the initial design of the basic access method in WLANs, known as Distributed Coordination Function (DCF), this performance boost is poorly exhibited. Game theory is an invaluable tool to model the performance of Medium Access Control (MAC) protocols used in WLANs. In this paper, we exploit game theory to propose a simple enhancement to the DCF access method, in order to increase the benefit received when the FD capability is enabled in ad-hoc WLANs. © 2023 IEEE.

关键词： Game theory

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A Framework Leveraging Robotics and Machine Learning Technologies for Early Disease and Pest Detection in Greenhouse Tomato Crops 4

A Framework Leveraging Robotics and Machine Learning Technol...

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4th International Conference on Control, Artificial Intelligence, Robotics and Optimization, ICCAIRO 2023

作者： Kounalakis, Nikolaos Kalykakis, Emmanouil Kosmopoulos, Dimitrios Fasoulas, John Sfakiotakis, Michael Heraklion Greece University of Patras Dept. of Computer Engineering and Informatics Patras Greece

ISBN: (纸本)9798350300918

We present an integrated framework for intelligent automated plant monitoring, towards early disease and pest detection in greenhouse tomato crops. The framework combines the use of a robotic mobile platform to autonomously collect multi-spectral images of the plants, with a tool that utilizes Faster R-CNN to detect regions that signify the presence of a disease or pest. The robot is based on a modified mobile vertical mast lift platform, and integrates a 6-dof robotic arm that is used to position the plant imaging multi-spectral camera. The robot can navigate autonomously inside the greenhouse via a magnetic guidance sensor. Results from a series of experiments demonstrate the validity and effectiveness of the implemented framework. © 2023 IEEE.

关键词： Machine learning

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Analysis of Physical Layer Impairments Resources Allocation Aware Algorithm/Framework in Transparent OTNs 4

Analysis of Physical Layer Impairments Resources Allocation ...

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4th IEEE International Conference on Electrical, computer, and Energy Technologies, ICECET 2024

作者： Nleya, Bakhe Molefe, M. Khulekani, Sibiya Durban University of Technology Dept. of Electronic and Computer Engineering Durban South Africa

ISBN: (纸本)9798350395914

Present-day, limitedly fixed wavelength routed based all Transparent Optical Transport Networks (OTNs) are quite energy efficient in comparison to translucent and opaque equivalents. As a result they are also regarded as a practical solution transport network provisioning ultrahigh bandwidth capabilities to support the various applications and services. The resulting heterogeneous nature of present-day global traffic makes such wavelength-routed networks spectrally inefficient. However, advancements in DSP techniques, modulation approaches, and transmission impairment mitigation techniques have vastly improved such net-works' spectral efficiencies and optical reach. The paper thus reviews the efficiency in the operation of an orthogonal frequency division multiplexing (OFDM) based Transparent OTN that is characterized by flexibility in the provisioning of available spectral resources. We address the challenges of optimal routing level allocation of wavelengths subject to maximizing spectral efficiencies. In so doing, we also consider the impact of various physical impairments. We introduce a quality factor-based tool (Q-factor) that aids in choosing op-timal routes. Ultimately, The tool is later incorporated into a proposed resource allocation framework's algorithms, which focus on ensuring spectral efficiency and overall network energy-efficient operation. Overall, we conclude that the pro-posed transport network architecture is relatively efficient regarding energy and spectral efficiencies. © 2024 IEEE.

关键词： Orthogonal frequency division multiplexing

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A Futuristic Optical and Wireless Convergence Network Towards 6G and Beyond 4

A Futuristic Optical and Wireless Convergence Network Toward...

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4th IEEE International Conference on Electrical, computer, and Energy Technologies, ICECET 2024

作者： Molefe, Mlungisi Sibiya, Khulekani Nleya, Bakhe Durban University of Technology Dept. of Electronic and Computer Engineering Durban South Africa

ISBN: (纸本)9798350395914

Emerging use cases and stringent requirements for 6G and beyond networks require new quantum leaps in mobile communication due to the demands of higher throughput, extensive bandwidth requirements, ultra-low latency and massive number of connected devices. The advancement in wireless communications and the advancement in optical networks will be essential in addressing the demands for future mobile networks by providing an innovative infrastructure for 6G and beyond networks. To support stringent requirements for 6G networks and beyond, new innovative technologies and systems are required that will combine optical and wireless networks. An innovative approach of converging optical and wireless networks promises to improve the network into new heights by creating a smart world with beyond-human cognitive communication capacity and speed, improved network scalability and enhanced energy efficiency. Research has shown that a promising architecture to achieve this goal, and cater for extremely high bandwidth and extremely low latency requirements is based on an All-Photonics Network. Therefore, in this paper, we propose an All-Photonics Network for the future to address bandwidth limitations, latency issues and massive connectivity. Furthermore, we propose an evolved infrastructure or architecture converging optical and wireless networks. Potential benefits for the evolved infrastructure are also discussed. © 2024 IEEE.

关键词： Bandwidth

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