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Intelligent Data Communication Technologies and Internet of Things (IDCIoT), International Conference on

作者： Sanjay Reddy Komatireddy Y. Krishna Bhargavi Dept. of Computer Science and Engineering Gokaraju Rangaraju Institute of Engineering and Technology Hyderabad India

Human-computer Interaction (HCI) is a dynamic field pi votal in shaping human-technology relationships. HCI is a multidisciplinary field, essential in understanding and enhancing the interaction between humans and technology. Challenges within HCI encompass design, usability, accessibility, and emotional resonance. The aim of this research study is to highlight the multifaceted nature of HCI, offering insights into its transformative and complementing potential and its continuous influence on the digital landscape. By delving into the challenges faced and the current technologies (Multimodal Affect Recognition, Artificial Intelligence, etc.), this review serves as a foundation for further research and development in this vital domain, offering valuable insights into the dynamic HCI landscape.

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Real-Time Face Mask Detector 3

Real-Time Face Mask Detector

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3rd IEEE International Conference on Technology, engineering, Management for Societal Impact using Marketing, Entrepreneurship and Talent, TEMSMET 2023

作者： Patel, Vishwajeet Guru Prasad, M.S. Aditya Pai, H. Kumar, A Suresh Praveen Gujjar, J. Naveen Kumar, H.N. Dept. of Computer Science and Engg. Dehradun India JAIN [Deemed-to-be University Faculty of Management Studies Bengaluru India Vidyavardhaka College of Engineering Dept. of Electronics and Communication Engg. Karnataka Mysuru India

ISBN: (纸本)9798350397819

When the COVID-19 pandemic was present we all have faced various challenges in our everyday lives. Pandemic created worldwide emergency which led to the lockdown in most of the countries resulting into disruption in world trade and movement. To reduce the covid cases WHO recommended to wear mask and maintain social distancing and then these steps became mandatory for some places, such as restaurants, hospitals, grocery stores etc., The purpose of limiting interaction with individuals as much as possible in such situations is simply defeated by having a staff personally check each person to make sure their mask is on. To avoid this dilemma, it became necessary to build a project named 'Real-time face mask detector', This reveals whether a mask-wearing individual is there. This project needed the use of some python libraries like TensorFlow, Keras, OpenCV. Using this project, we will be able to Detect mask-on faces in live video clip with accuracy of 97-98 %. © 2023 IEEE.

关键词： COVID-19

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Modulo-(22n + 1) Arithmetic via Two Parallel n-bit Residue Channels

arXiv

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arXiv 2024年

作者： Jaberipur, Ghassem Nadimi, Bardia Lee, Jeong-A Dept. of Computer Engineering Chosun University Gwangju Korea Republic of Dept. of Computer Science and Engineering University of South Florida TampaFL United States

Augmenting the balanced residue number system moduli-set {m1 = 2n, m2 = 2n − 1, m3 = 2n + 1}, with the co-prime modulo m4 = 22n + 1, increases the dynamic range (DR) by around 70%. The Mersenne form of product m2m3m4 = 24n − 1, in the moduli-set {m1, m2, m3, m4}, leads to a very efficient reverse converter, based on the New Chinese remainder theorem. However, the double bit-width of the m4 residue channel is counter-productive and jeopardizes the speed balance in {m1, m2, m3}. Therefore, we decompose m4 to two complex-number n−bit moduli 2n ± √−1, which preserves the DR and the co-primality across the augmented moduli set. The required forward modulo-(22n + 1) to moduli-(2n ± √−1) conversion, and the reverse are immediate and cost-free. The proposed unified moduli-(2n ± √−1) adder and multiplier, are tested and synthesized using Spartan 7S100 FPGA. The 6−bit look-up tables (LUT), therein, promote the LUT realizations of adders and multipliers, for n = 5, where the DR equals 225 −25. However, the undertaken experiments show that to cover all the 32-bit numbers, the power-of-two channel m1 can be as wide as 12 bits with no harm to the speed balance across_ the five moduli. The results also show that the moduli-(25 ± √−1) add and multiply operations are advantageous vs. moduli-(25 ± 1) in speed, cost, and energy measures and collectively better than those of modulo-(210 + 1). Copyright © 2024, The Authors. All rights reserved.

关键词： Table lookup

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Identification of Fraudulent Transactions for Enhanced Credit Card Fraud Detection 4

Identification of Fraudulent Transactions for Enhanced Credi...

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4th International Conference on Technological Advancements in Computational sciences, ICTACS 2024

作者： Gupta, Monica Gayathri, V. Narula, Rachna Kumar, Vijay Kaur, Surinder Singh, Neetu Bharati Vidyapeeth's College of Engineering Dept. of Electronics and Communication Engineering New Delhi India Bharati Vidyapeeth's College of Engineering Department of Computer Science and Engineering New Delhi India Bharati Vidyapeeth's College of Engineering Department of Information and Technology New Delhi India

ISBN: (纸本)9798350387490

With the flourishment of the digital era and the evolution of new techniques and technology, this paper highlights the ever-growing risk of credit card fraud. The advancing technology has provided fraudsters with new and untraceable techniques for scamming genuine users. With the increasing impact of fraud, financial institutions must use machine learning tools for scam detection to provide safety and security to their users' accounts. This paper consists of an interdisciplinary comparative analysis of ML algorithms: Random Forest Classifier, XGBoost, ADABoost, Logistic Regression, Decision Trees, and Artificial Neural Networks. The diverse selection of algorithms aims to determine the most effective algorithm with the highest accuracy score for predicting legitimate and fraudulent transactions. The methodology involves fetching data from an Excel file, training the models, testing them on 20% of the dataset, and finally obtaining results in a Word document, having a confusion matrix and accuracy of each algorithm. By comparing the results of the confusion matrix and accuracy score, the Random Forest Classifier and XGBoost demonstrate the highest accuracy scores, while Logistic Regression yields a lower accuracy score. © 2024 IEEE.

关键词： Logistic regression

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Advancements in User Security: Enhancing Usability with Graphical Password Authentication

Advancements in User Security: Enhancing Usability with Grap...

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Intelligent Data Communication Technologies and Internet of Things (IDCIoT), International Conference on

作者： Harisha Sandhya Ramesh Naik Shettigar Sarvani Vasudeva K Shrilakshmi Vaishnavi Kothwal Dept. of Computer Science & Engineering Sahyadri College of Engineering & Management Mangalore Karnataka India

Text-based password authentication is a common method used to verify the identity of users who are trying to access a secure system or service. In order to use this authentication method, the user must input a password or other secret phrase that is then compared to a server-side copy of the same password. Access is given if the password typed matches the one saved. Graphical password authentication is a type of user authentication that involves using images or visual elements instead of alphanumeric characters to verify the identity of the user. Unlike traditional text-based passwords, graphical passwords offer an intuitive and user-friendly way of authentication, as they rely on the user's ability to remember pictures, shapes, and patterns. This technology has been developed to address the limitations of traditional text-based passwords, such as the difficulty of creating and remembering complex passwords, and the vulnerability to brute-force attacks. Compared to conventional text-based passwords, graphical password authentication has a number of benefits, including better usability and higher security.

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Non-Invasive Oral Cancer Detection Using Hyperspectral Imaging and Advanced Spectral Unmixing Models

Non-Invasive Oral Cancer Detection Using Hyperspectral Imagi...

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Intelligent Computing and Emerging Communication Technologies (ICEC), International Conference on

作者： Valluri Ayyapa Kesava Sriram Kothamasu Priyusha Killaru Saadhivik Muddana Suresh Aala Vamsi Gutha Mukkara Prasana Kumar Sunil Chinnadurai Dept.of Electronics and Communication Engineering SRM University AP India Dept. of Computer Science and Engineering SRM University AP India Dept. of Computer Science SRM University AP India

ISBN: (数字)9798331508432

ISBN: (纸本)9798331508449

Oral cancer is a significant global health concern, often leading to high mortality rates due to late-stage diagnosis and the lack of effective early detection methods. Despite advances in medical science, the absence of reliable early diagnostic tools remains a critical challenge. Hyperspectral imaging (HSI) has emerged as a powerful noninvasive technology, capturing detailed spectral information across a wide range of wavelengths. This allows for accurate differentiation between cancerous and healthy tissues, improving early detection and enhancing treatment outcomes. In this study, we propose the use of HSI for early oral cancer diagnosis. To address the scarcity of labeled data, we developed a synthetic hyperspectral dataset that includes spectral signatures of both normal and cancerous tissues. The dataset was generated using a bilinear mixing model, with key spectral features extracted through Vertex Component Analysis (VCA) and abundances computed using Non-Negative Least Squares (NNLS). The model's performance was evaluated using Spectral angle distance (SAD) and Root mean square error (RMSE) metrics. Our findings demonstrate that HSI significantly improves the accuracy of early oral cancer detection, outperforming traditional methods. This work highlights the potential of advanced imaging technologies in revolutionizing cancer diagnosis, offering a robust framework for non-invasive detection and showcasing the effectiveness of synthetic datasets in medical imaging research.

关键词： Measurement Accuracy Computational modeling Mortality Feature extraction Reliability Root mean square Cancer Hyperspectral imaging Synthetic data

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IoT-Enhanced Smart Bulletin Board: A Multi-Functional Connectivity Hub

IoT-Enhanced Smart Bulletin Board: A Multi-Functional Connec...

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Intelligent Data Communication Technologies and Internet of Things (IDCIoT), International Conference on

作者： Mallikarjuna Rao Gundavarapu VeerlapalIi Swapna Enugu Sriamsh Reddy Pindi Praveen Kumar Abhinay Prathapani Kothapally Shivaji Dept. of Computer Science and Engineering Gokaraju Rangaraju Institute of Engineering and Technology Hyderabad India

The problem with traditional notice boards is their static nature, leading to outdated information and manual effort to update. An IoT-based smart notice board solves this by providing real-time updates but requires addressing challenges such as connectivity, power management, compatibility, user interface, security, and maintenance. Addressing these challenges ensures an effective and user-friendly smart notice board. The proposed model involves using an LED dot matrix, ESP32, Kodular app, Firebase Cloud and DS3231 module. The app sends messages to the Firebase then it passes the message to ESP32, which displays message on the LED dot matrix, We use Firebase cloud which provides infinite range. Firebase provides a NoSQL database that allows developers to store and synchronize data in real-time. It is suitable for applications that require real-time updates, such as chat apps, collaborative tools, and live dashboards. The DS3231 module shows real-time information. This study implements a feature that allows the user to retrieve the current time and temperature by pressing a button in the Kodular app. When the button is pressed, a command is sent to the ESP32, which retrieves the relevant data from the DS3231 module and sends it to display. This study creates a buffer to store messages, accessible by indexes, allowing easy retrieval. The proposed system provides a comprehensive solution for displaying messages, real-time data, and efficient message storage. QR codes are also provided to scan.

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Design of Automatic Radiation Detection System as a Part of Radiation Protection in Linear Accelerator Facilities 12

Design of Automatic Radiation Detection System as a Part of ...

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12th International Scientific Conference on Communication and Information Technologies, KIT 2023

作者： Dugas, Martin Ferencik, Norbert Hudak, Radovan Nadova, Zuzana Kolembusova, Petra Steingartner, William Technical University of Košice Dept. of Biomedical Engineering Košice Slovakia Pavol Jozef Šafárik University in Košice Faculty of Science Slovakia Technical University of Košice Dept. of Computers and Informatics Košice Slovakia

ISBN: (纸本)9798350338393

The main objective of this study is the development of an automatic radiation detection system that can be installed at linear accelerator facilities. This system aims to inform the linear accelerator operating staff about the ambient radiation dose rate inside the treatment room. This information might further improve radiation safety. The system is meant to capture residual radiation in the treatment room induced by photonuclear radioactive activation of materials inside the linear accelerator. This study contains current knowledge about ionizing radiation, its dosimetry and detection. It also contains the newest radiation protection laws and radiation protection standards of linear accelerator facilities. The main part of the study is concerned with the design of the detection system - hardware, software, connection and testing of functionality and reliability of the system. The testing was performed by measurement of residual radiation 20 cm away from the source of the linear accelerator. It was performed immediately after applying determined monitor units of photons with energies of 10 MeV and 15 MeV. Measurements were carried out simultaneously using our system and a certified dosimeter RAYSAFE 452. The measured values were compared afterward. Measurement error of 6,08 % and 6,25 %, respectively, was observed. Therefore, the system is arguably reliable and adequate for its purposed use. © 2023 IEEE.

关键词： Ionizing radiation

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A Semi-Supervised Approach For Detecting Agricultural Land Reduction In Bangladesh Using Satellite Images

A Semi-Supervised Approach For Detecting Agricultural Land R...

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Computing, Applications and Systems (COMPAS), IEEE International Conference on

作者： Wahid Mahmood Shafin Sk. Md. Masudul Ahsan Dept. of Computer Science and Engineering Khulna University of Engineering & Technology (KUET) Khulna Bangladesh

ISBN: (数字)9798331529765

ISBN: (纸本)9798331529772

Recently, remote sensing change detection has significantly improved because of greater access to global satellite images and developments in satellite technology. Several CNN-based techniques have demonstrated exceptional precision. Detecting the amount of agricultural area that has been reduced is a type of change detection problem that can easily be solved using deep learning methods on satellite data. But the majority of deep learning methods have been specifically created for high-resolution images. This data lacks global coverage, consists of at most 3 to 4 bands, and is costly. The Sentinel-2 satellite, which was launched in 2015, offers medium-resolution multi-spectral image data consisting of 14 bands and provides free global coverage. Having more bands enhances the capabilities for model analysis. But there is a lack of labeled satellite data. This research proposes a semi-supervised method for generating ground truth by employing a multi-step procedure. This technique began with semi-supervised classification to label the images, followed by a sequence of refinement processes to enhance the accuracy of the ground truth mask. The mask was created using the XGBoost machine learning technique. The dataset was assessed using the output images generated by the trained model. Detecting changes in low-resolution image may be difficult, but proposed method will greatly streamline the procedure. Applying this approach revealed an approximately 8.35% decrease in agricultural land area inside the test image area between 2018 and 2022. In the test area of 237.77 square kilometers, the reduced area measures approximately 19.861 square kilometers.

关键词： Deep learning Deforestation Satellites Accuracy Computational modeling Urban areas Area measurement Streaming media Satellite images Remote sensing

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Optimizing 3D Flight Paths for Multiple UAVs with Connectivity Management in Urban Delivery Systems

Optimizing 3D Flight Paths for Multiple UAVs with Connectivi...

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International Conference on Ubiquitous Information Management and Communication (IMCOM)

作者： Yeongmin Lee Raihan Muhammad Syahran Mael Spangenberger Huigyu Yang Jiyong Oh Hyunseung Choo Dept. of Artificial Intelligence Dept. of Electrical and Computer Engineering Dept. of Informatics Télécom SudParis Évry France Convergence Research Institute Dept. of AI Systems Engineering Sungkyunkwan University Suwon S. Korea

ISBN: (数字)9798331507817

ISBN: (纸本)9798331507824

The dynamic deployment of aerial vehicles in urban delivery scenarios demands precise route planning, reliable data links, and efficient use of network infrastructure. Although prior efforts have explored various aspects of unmanned navigation or communication optimization, existing approaches often overlook the combined impact of three-dimensional path selection and robust connectivity maintenance. To address this gap, this paper proposes a deep reinforcement learning framework employing Independent Proximal Policy Optimization (IPPO) to steer the flight paths of unmanned vehicles while curtailing needless interactions with base stations (BSs). By incorporating communication-specific metrics, Reference Signal Received Power (RSRP), the proposed system adapts to urban conditions and upholds resilient network links. Comprehensive performance evaluations reveal the potential of the framework to reduce excessive BS connections by up to 82.24%, preserve RSRP levels above -80 dBm, and balance handover frequencies across flight trajectories. These findings affirm the scalability and effectiveness of the method for achieving efficient aerial navigation and consistent communication in urban delivery services.

关键词： Three-dimensional displays Navigation Scalability Surveillance Handover Autonomous aerial vehicles Trajectory Resource management Vehicle dynamics Optimization

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