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7th International Conference on Electronics, Materials engineering and Nano-Technology, IEMENTech 2023

作者： Bose, Shreea Seth, Prakriti St Xavier's College Department of Post Graduate and Research Computer Science Kolkata India National Institute of Technology Department of Biotechnology and Medical Engineering Rourkela India

ISBN: (纸本)9798350305517

Autism Spectrum Disorder (ASD) is a specific category of neurodevelopmental disorder that can be associated with several behavioral conditions and has no known cure to date. ASD can be detected from a very early stage in childhood and upon successful detection can be ameliorated. There have been several clinical diagnosis procedures and they can be error-prone and time-consuming. Thus, machine learning-based prediction models for early-stage ASD as well as in adolescents and adults are being developed over the years. In our study, several parameters of ASD detection were implemented with open-source ASD datasets and analysed using several machine learning models like Logistic regression, XGboost, SVC and Naive Bayes. Among these XGboost showed the best performance. The outcomes of such analytical approaches demonstrate that, when suitably optimized, machine-learning techniques can offer robust predictions of Autism Spectrum Disorder (ASD) status. These findings imply that it may be feasible to employ these models for the early ASD detection, thereby enhancing the prospects of timely and effective intervention. XGBoost has given best results throughout all datasets, including cross validation. An accuracy of 100% has been achieved, making the model best for prediction. © 2023 IEEE.

关键词： Diagnosis

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Fusion of Frequency Domain Features of Face and Iris Traits for Person Identification

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Journal of The Institution of Engineers (India): Series B 2021年第5期102卷 987-996页

作者： Kagawade, Vishwanath C. Angadi, Shanmukhappa A. Department of Computer Applications Basaveshwar Engineering College Bagalkot India Department of Computer Science and Engineering Centre for Post Graduate Studies VTU Belagavi India

In this study, we present a new approach for person recognition through feature level fusion of face and iris traits. The strength of the multimodal biometric system relies much more on the consistency to determine relevant features from the individual biometric traits and fusion technique employed for integration. Hence, this paper presents a new feature extraction approach for a face–iris multimodal biometric system. The face and iris feature extraction is performed by employing Polar Fast Fourier Transform to obtain textural information in diverse scales and orientations of the face and eye images. The Canonical Correlation Analysis method is employed to integrate face and iris traits features, which reduces the new feature vector length than the input feature vectors. The proposed approach is capable to obtain and improve the discriminative power for person recognition from multi-feature data of face and iris traits. The effectiveness of the proposed model is illustrated through the use of both artificial and genuine face and iris multimodal databases, along with comparisons involving existing state-of-the-art techniques. © 2021, The Institution of Engineers (India).

关键词： Feature extraction

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Multi-agent Architecture for Passive Rootkit Detection with Data Enrichment

Multi-agent Architecture for Passive Rootkit Detection with...

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International Conference on computer science, Electronics, and Industrial engineering, CSEI 2022

作者： Trinks, Maickel Gondim, João Albuquerque, Robson Professional Post-Graduate Program in Electrical Engineering - PPEE - Department of Electrical Engineering University of Brasília DF Brasília Brazil Department of Computer Science Universidade de Brasília DF Brasília Brazil

ISBN: (纸本)9783031305917

The added value of the information transmitted in a cybernetic environment has resulted in a sophisticated malicious actions scenario aimed at data exfiltration. In situations with advanced actors, like APTs, such actions use obfuscation techniques of harmful activities as persistence assurance on strategic targets. The MADEX and NERD architectures proposed flow analysis solutions to detect rootkits that hide network traffic;however, it presents some operational cost, either in traffic volume or due to lack of aggregated information. In that regard, this work changes and improves user flow analysis techniques to eliminate impacts on network traffic, with data enrichment on local and remote bases, detection of domains consulted by rootkits and aggregation of information to generate threat intelligence, while maintaining high performance. The results show the possibility of aggregating information to data flows used by rootkits in order to have effective cyber defense actions against cybernetic threats without major impacts on the existing network infrastructure. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Multi agent systems

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Multi-robot Map Exploration Based on Multiple Rapidly-Exploring Randomized Trees

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SN computer science 2024年第1期5卷 31页

作者： Mukhopadhyay, Shayok Umari, Hassan Koirala, Koshish Electrical & Computer Engineering and Computer Science Department University of New Haven 300 Boston Post Rd West Haven 06516 CT United States Department of Electrical Engineering American University of Sharjah Sharjah P.O. Box 26666 United Arab Emirates Mechatronics Engineering graduate program American University of Sharjah Sharjah P.O. Box 26666 United Arab Emirates

A map is necessary for tasks such as path planning or localization, which are common to mobile robot navigation. However, a map may be unavailable if the environment in which a robot navigates is unknown. Creating a map requires an exploration algorithm. Such algorithms guide robots to boundaries that separate known portions of a map from the unknown portions. Such boundaries are known as frontiers. There are image processing-based algorithms that detect frontiers. The authors’ previous work uses two, i.e., local and global, rapidly exploring random trees (RRTs) for two-dimensional exploration using a single robot. The present work applies the above to a multiagent system with three robots. A market-based strategy is used to allocate exploration tasks to the robots. Results show that the developed exploration strategy successfully explores a map in a reasonable amount of time compared to image processing-based approaches, and also reduces the map exploration cost. This strategy is readily usable for three-dimensional exploration with drones. It is also shown that the usage of a local frontier detector along with a global frontier detector helps reduce exploration time compared to simply using a global frontier detector alone. As an outline to future work, the paper also shows an extension of the proposed approach towards three-dimensional mapping using a single robot. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Exploration Mapping Multi-agent Navigation ROS RRT

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MonuAR:M.A.R Application for Visualising 3D Monuments

MonuAR:M.A.R Application for Visualising 3D Monuments

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Networking and Communications (ICNWC), International Conference on

作者： Shanthi D Sorna B Bhuvaneswaran Adhithya R Manoj S Pooja Department of Computer Science of Engineering Rajalakshmi Engineering College Chennai Department of Computer Science of Engineering Under Graduate Student Rajalakshmi Engineering College Chennai

The Art and Heritage has been an integral part of our Indian Culture. These art forms and heritage are left unnoticed just because they are very much away. Therefore these sites can be brought back to life in any environment. The heritage properties of art and craft of India can be brought to life from anywhere by using an AR application on the phone. There are times when people visit the monuments and they are in need of a third party to show them the main attractions of the monument. Instead of relying on a third party, this can be done using this app where an AR marker appears on important tourist spots. The software that are used are Unity, Blender, Python and Visual Studio for C#. The software development kit used are Vuforia AR SDK and Mapbox *** software that are used are Unity, Blender, Python and Visual Studio for C#. The software development kit used are Vuforia AR SDK and Mapbox SDK

关键词： Visualization Solid modeling Art Three-dimensional displays Machine learning algorithms Chatbots Software

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Automated Sulcus Depth Measurement on Axial Knee MR Images 7th

Automated Sulcus Depth Measurement on Axial Knee MR Images

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7th International Conference on computer Vision and Image Processing, CVIP 2022

作者： Ridhma Kaur, Manvjeet Sofat, Sanjeev Chouhan, Devendra K. Prakash, Mahesh Department of Computer Science and Engineering Punjab Engineering College Sector-12 Chandigarh India Cyber Security Research Center Punjab Engineering College Sector-12 Chandigarh India Department of Orthopaedics Post Graduate Institute of Medical Education and Research Sector-12 Chandigarh India Department of Radio Diagnosis and Imaging Post Graduate Institute of Medical Education and Research Sector-12 Chandigarh India

ISBN: (纸本)9783031314063

Patellofemoral instability is a knee disorder in which the patella, slips out of its usual placement leading to knee pain. The patella may displace from its position due to abnormality in the shape of patellar surface on femur bone. The orthopaedic experts manually measure certain parameters from the available axial knee scans for the patellar instability diagnosis, which is labor-intensive and susceptible to inter-and intra-observer variations. The automated segmentation of femur region in knee magnetic resonance (MR) image can help in easily identifying the abnormality in the patellar surface. Therefore, in this paper, the femur bone in the axial knee MR scans has been segmented using two variants of U-Net: basic U-Net and U-Net++ and the results have been compared and visualized. The validation dice similarity coefficient (DSC) and accuracy of 89.62% and 94.05% were obtained, respectively, for U-Net. For U-Net++, the validation DSC of 95.04% and validation accuracy of 94.91% were obtained. Further, in this paper, the sulcus depth measurement has been automated using basic image processing techniques. A mean error of 0.565 mm was obtained when tested on 20 axial knee MR images. The T2-weighted knee MRI dataset of 55 patients has been acquired from post graduate Institute of Medical Education and Research (PGIMER), Chandigarh for training and testing of the proposed approach. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Magnetic resonance imaging

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Driving Design and Performance of Dental Restorations through Next-Generation Additive Manufacturing Resins 3

Driving Design and Performance of Dental Restorations throug...

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3rd International Conference on Computational Modelling, Simulation and Optimization, ICCMSO 2024

作者： Dhingra, Ashwani Kumar Chhabra, Deepak Gahletia, Sumit Dhingra, Sunita Sahdev, Ravinder Kumar Dhingra, Sunil Kaushik, Ashish Rathee, Mannu Maharshi Dayanand University UIET Department of Mechanical Engineering Rohtak India Deenbandhu Chhotu Ram University of Science and Technology Department of Mechanical Engineering Sonipat India Maharshi Dayanand University UIET Department of Computer Science and Engineering Rohtak India University Institute of Engineering and Technology Kurukshetra University Department of Mechanical Engineering Haryana Kurukshetra India Pt. Bhagwad Dayal Sharma University of Health Sciences Post Graduate Institute of Dental Sciences Department of Prosthodontics Rohtak India

ISBN: (纸本)9798350361391

The advancement of novel and enhanced resin materials is crucial in improving dental product development and enabling the efficient customization of products using emerging technologies like 3D printing. The research explores the impact of AM resins on design improvements, facilitating the production of customized restorations for patients that offer enhanced fit and usefulness. This study intends to demonstrate how developments in AM resins are revolutionizing the design and performance of dental restorations, providing substantial advantages for patients and dental practitioners. This sets the stage for a future in dentistry marked by resin materials and digital manufacturing technologies that must be integrated to establish a materials innovation ecosystem in dental restorations and improve product functionality. © 2024 IEEE.

关键词： Dental materials

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High-Speed Optical Convolutional Neural Network Accelerator with 100 Gbaud EO-polymer/Si Hybrid Optical Modulator

High-Speed Optical Convolutional Neural Network Accelerator ...

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2023 Opto-Electronics and Communications Conference, OECC 2023

作者： Shinya, Akito Kida, Koji Sato, Hiromu Lu, Guo-Wei Yokoyama, Shiyoshi Fujikata, Junichi Tokushima University Graduate School of Science and Technology for Innovation Tokushima Japan Kagawa University Fuculty of Engineering and Design Takamatsu Japan Institute for Materials Chemistry and Engineering Kyushu University Kasuga Japan The University of Aizu Division of Computer Engineering Aizu Japan Institute of Post-LED Photonics Tokushima University Tokushima Japan

ISBN: (纸本)9781665462136

Convolutional neural networks are a powerful category of artificial neural networks that can extract hierarchical features of biological data to significantly reduce parametric complexity and increase prediction accuracy. In this paper, we propose high-speed optical convolutional neural network accelerator with 100Gbaud EO-polymer/Si hybrid optical modulator and demonstrated proof of concept both in simulation and experiment. © 2023 IEEE.

关键词： Light modulators

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IoT-based Efficient Waste Management on University Campus : Enhancing Monitoring and Optimization through Machine Learning

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Procedia computer science 2025年 258卷 4157-4168页

作者： Sumathi M. Hanumanthappa J. K.S. Santhosh Kumar S.P. Shiva Prakash Meghana J. Department of Studies in Computer Science Manasagangothri Campus University of Mysore Mysuru Karnataka 570006 India Department of Artificial Intelligence and Machine Learning Mysore University School of Engineering Manasagangothri Campus University of Mysore Mysuru Karnataka 570006 India Department of Information Science and Engineering & Computer Science and Business Systems JSS Science and Technology University Mysuru Karnataka 570006 India Department of Computer Science Mahajana Post Graduate Center Mysuru Karnataka 570016 India

The introduction of an IoT-based smart waste management system is proposed to optimize various aspects of university campus waste recycle management processes, such as garbage collection scheduling, waste type identification, and collection routes. This system utilizes advanced data analytics algorithms, wireless communication protocols, and sensors to measure and document variations in trash levels, enabling real-time monitoring of waste accumulation. Through this IoT-based infrastructure, university administrators and waste management staff gain fine-grained visibility and control over garbage collection processes. The implications for sustainability advocacy and environmental stewardship in academic environments are significant. By fostering a culture of environmental awareness and accountability, universities can instill ideals of conservation and resourcefulness in their student populations and staff. The proposed IoT-enabled waste bin system exemplifies the synergy between technological innovation and environmental responsibility, serving as a model for institutions worldwide. Collaboration among universities can leverage IoT technology to drive positive change, mitigate environmental degradation, and promote sustainable practices beyond campus boundaries. Efficient waste management is crucial for nurturing sustainability on college and university campuses, as evidenced by the urgent need for the collection and recycling of compost, general waste, and recyclables. Our models consistently achieve high performance, with perfect scores (1.000) across all split ratios, indicating flawless classification of waste types. Although the Artificial Neural Network (ANN) demonstrates slightly lower accuracy, ranging from 0.973 to 0.997 depending on data splits, it still performs well. As a result, Naive Bayes produces less accurate results, typically surpassing 0.93 but falling short of Random Forest, K-Nearest Neighbors (KNN), and Support Vector Machine (SVM)’s flawless

关键词： Artificial Intelligence Smart Parking: Smart city Machine Learning Smart Applications

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Automated Medical Record Summarization for Diagnosis and Training Doctors Using AI 1

Automated Medical Record Summarization for Diagnosis and Tra...

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1st IEEE International Conference on Green Industrial Electronics and Sustainable Technologies, GIEST 2024

作者： Singh, Kulvinder Gupta, Himanshu Singh, Balkar Wadhwa, Shivani Chandigarh University Department of Computer Science & Engineering Punjab Mohali India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Gujranwala Guru Nanak Khalsa College Post Graduate Department of Computer Science Punjab Ludhiana India

ISBN: (纸本)9798331540142

This paper investigates the potential of computers and artificial intelligence (AI) to fundamentally alter the landscape of the healthcare industry. It emphasizes how computers can refine the accuracy of diagnosing diseases by processing medical records and leveraging AI-based tools. The paper also sheds light on the profound impact that analyzing electronic health records (EHRs) can have on enhancing healthcare delivery and empowering patients. It also considers the use of internet search data as an innovative approach for the early detection of diseases, while also addressing the concern that access to health information online could lead to excessive worry among patients. The paper discusses advanced methodologies such as neural networks and deep learning and acknowledges the challenges they present, including the danger of overfitting and the necessity for effective data visualization. It also considers the revolutionary potential of EHRs in redefining healthcare delivery and in giving patients more control over their health. In addition, the paper looks at the significant changes that the adoption of electronic health records (EHRs) can bring to healthcare delivery and patient empowerment. © 2024 IEEE.

关键词： Electronic health record

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