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International Conference on computer Communication and Informatics (ICCCI)

作者： Harishma Ashok Swathi Ganesan Nalinda Somasiri Maters in Data Analytics PSG Institute of Advanced Studies Coimbatore India Department of Computer Science York St John University London UK

Internet of things (IoT) is one of the leading technologies of transforming the internet into the next level. Security of IoT is becoming a major challenge and its measures of stopping these insecurities have been developing. Improving IoT security is important since IoT provides a great environment for systems in the industrial world and other several applications. The challenges need to be addressed so that consumer’s data can be safe. Measures available are to improve the protection of access by unauthorized persons, providing a safe way to transfer data, and ensuring synchronization of the system. Blockchain has also provided a safe way for IoT devices, each device is given the public key, IoT devices scramble and send the message dependent on the public key of the objective device so just the objective device can unscramble the message.

关键词： Privacy Strips Public key Time measurement Blockchains Safety Internet of Things

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Performance Optimization of Semantic Communications for Users with Heterogeneous Knowledge

Performance Optimization of Semantic Communications for User...

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IEEE International Conference on Communications (ICC)

作者： Jiantong Zhang Mingzhe Chen Yujiao Zhu H. Shihao Tao Luo Zhilong Zhang Beijing Laboratory of Advanced Information Network Beijing University of Posts and Telecommunications Beijing China Department of Electrical and Computer Engineering and Institute for Data Science and Computing University of Miami Coral Gables FL USA

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

In this paper, a semantic communication framework for a scenario where the transmitter and the receiver have different knowledge is proposed. In the proposed framework, the transmitter extracts semantic information from the data according to its knowledge and sends it to the receiver. The receiver requires to process the received semantic information based on its knowledge. Here, the knowledge implies a method which the transmitter or the receiver can use to process the semantic information. Since the transmitter or the receiver have different knowledge, they may have different understandings for the same information. To ensure the receiver can understand the semantic information, the transmitter requires to estimate the receiver's knowledge by asking a series of questions about the transmitted data. By evaluating the difference between the answers of the receiver and the answers of the transmitter, the transmitter can adjust the method of semantic information extraction. Since the size of the extracted semantic information and the number of the questions that the transmitter can ask are limited, the transmitter must adjust the method of semantic information extraction and select appropriate questions to transmit. This problem is formulated as an optimization problem whose goal is to maximize the similarity of answers of the transmitter and the receiver by determining semantic information while minimizing the semantic similarity of answers by determining the questions to be transmitted. To solve this problem, an adversarial reinforcement learning (ARL) algorithm is proposed. The proposed algorithm, which consists of a semantic information RL and a question RL, can find the optimal semantic information generation scheme and question selection scheme by a competitive game between two agents. Simulation results demonstrate that the proposed framework can improve the semantic similarity of answers by up to 3.7% gain and can achieve up to 15.2 % gain in terms of the aver

关键词： Transmitters Simulation Semantics Receivers Games Transforms Reinforcement learning

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A Novel Deep Learning Approach for Capturing Time Series Dependencies and Improving Short-term Weather Forecasting 7

A Novel Deep Learning Approach for Capturing Time Series Dep...

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7th International Conference on Image Information Processing, ICIIP 2023

作者： Johri, Shiva Divyajyothi, M.G. Anitha, S. Rani, M. Sandya Murari, Thejovathi Shirisha, N. Oriental College of Management Oriental Group of Institutes Department of Management Madhya Pradesh Bhopal462022 India University of Technology And Applied Sciences - Al Mussanah Department of Information Technology Al Muladha Muscat Oman Vels Institute of Science Technology And Advanced Studies Department of Computer Science Engineering Pallavaram Krishnapuram Tamil Nadu Chennai India St. Martin's Engineering College Secunderabad Telangana Dhulapally500100 India Acharya Nagarjuna University Department of Computer Science And Engineering Andhra Pradesh Guntur India Mlr Institute of Technology Department of Cse Hyderabad Dundigal India

ISBN: (纸本)9798350371406

Weather forecasting is a critical and challenging task that requires accurate predictions based on historical data and intricate dependencies between time series. Traditional neural networks, such as Back Propagation through Time (BPTT) trained RNNs, struggle to effectively capture these dependencies, leading to suboptimal performance in weather forecasting. In this study, we suggest a novel Integrated-Stack based Bi-LSTM Model, which associations the strengths of LSTM and Bi-LSTM networks, to address these limitations and enhance the accuracy of short-term weather predictions. The primary objective of this research is to develop a versatile deep learning model capable of maintaining long-term dependances and reading any length of sequence, while simultaneously providing real-time short-term weather forecasts. To achieve this, the Integrated-Stack based Bi-LSTM Model is designed to exploit the versatility and non-linear adaptive processing ability of neural networks. The proposed model's architecture involves the integration of LSTM and Bi-LSTM layers. By incorporating both forward and reverse direction processing, the model gains a comprehensive understanding of complex patterns present in time-series data. This bidirectional approach enables the model to capture dependencies effectively, which is essential for accurate weather predictions. To estimate the presentation of the Integrated-Stack based Bi-LSTM Model, we conducted experiments using real-world weather data. We compared the model's predictive capabilities against traditional LSTM models and other state-of-the-art weather forecasting methods. The assessment metrics included accuracy, root mean square error (RMSE), and mean absolute error (MAE). © 2023 IEEE.

关键词： Weather forecasting

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QSCL-EWIL: Quantum Stochastic Contrast Learning for Enhanced WiFi-Based Indoor Localization

arXiv

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arXiv 2025年

作者： Dastagir, Muhammad Bilal Akram Han, Dongsoo Al-Kuwari, Saif Farouk, Ahmed The School of Computing Korea Advanced Institute of Science and Technology Daejeon Korea Republic of The Qatar Center for Quantum Computing College of Science and Engineering Hamad Bin Khalifa University Doha Qatar Qatar Center for Quantum Computing College of Science and Engineering Hamad Bin Khalifa University Doha Qatar The Department of Computer Science Faculty of Computers and Artificial Intelligence South Valley University Hurghada Egypt

WiFi-based indoor localization is essential for asset tracking, healthcare monitoring, and smart buildings. However, existing systems face challenges such as data variability, environmental noise, and difficulty detecting floor and building levels, compounded by limited labeled data and high received signal strength (RSS) collection costs. This paper introduces quantum stochastic contrast learning (QSCL), a novel framework grounded in rigorous theoretical foundations. We present four theorems and one lemma that establish the probabilistic augmentation, diversity enhancement, relationship preservation, and resilience of QSCL under quantum noise, supported by formal proofs. Leveraging these foundations, QSCL utilizes quantum computing (QC) to generate strong data augmentations with stochastic perturbations, enhancing data diversity, while classical weak augmentations provide subtle variations for robust feature learning. We propose a spatial temporal adaptive attention (STAA) encoder that integrates convolutional layers with adaptive attention mechanisms to capture spatial and temporal dependencies in sequential data. Furthermore, a bidirectional contrastive loss function is introduced to capture forward and reverse relationships between augmented views, ensuring robust representations. Comprehensive evaluations on the UJIIndoorLoc and UTSIndoorLoc datasets validate QSCL, demonstrating superior performance with reduced labeled data and resilience to quantum noise such as bit-flip, dephasing, and measurement noise. The proposed framework significantly improves localization accuracy, floor and building detection, and generalizability in challenging indoor environments. © 2025, CC BY.

关键词： Quantum noise

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Leveraging Digital Twins and AI for Enhanced Clinical Decision Support in Endometrial Cancer Treatment

Leveraging Digital Twins and AI for Enhanced Clinical Decisi...

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IoT Based Control Networks and Intelligent Systems (ICICNIS), International Conference on

作者： Suresh Palarimath Pyingkodi Maran Wilfred Blessing N. R Cibi. A S. J. Kavitha Steffi S College of Computing and Information Sciences University of Technology and Applied Sciences Salalah Sultanate of Oman Department of Computer Application Kongu Engineering College Erode India College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Sultanate of Oman Data & Analytics Visualizaation – Delivery Virtusa Consulting Service Private Limited Chennai India Department of Computer Science and Engineering Vels Institute of Science Technology and Advanced Studies Chennai India Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India

ISBN: (数字)9798331518097

ISBN: (纸本)9798331518103

Digital twins are a relatively new concept that have lately garnered interest in the industrial sector. Digital twins are virtual models that mirror actual products. In this research, we suggest using the technology of digital twins to the field of healthcare in order to enhance clinical decision support and to provide more individualized treatment for patients. When artificial intelligence (AI) is combined with digital twins, healthcare professionals are able to more effectively analyze large volumes of varied data and increase their ability to make diagnostic and therapeutic decisions. In this research, we provide a conceptual framework for leveraging digital twins and AI to solve existing limits in cancer care, notably endometrial cancer therapy. This research study mainly focuses on cancer care, and more specifically on endometrial cancer treatment. In addition, we analyze the possible challenges and opportunities that may arise throughout the process of integrating this technology in healthcare settings. Our overarching objective is to improve the standard of treatment as well as the clinical results for people who have cancer.

关键词： Accuracy Cancer treatment Medical services Machine learning Digital twins Mirrors Artificial intelligence Wearable sensors Standards Cancer

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Modelling of Firefly Algorithm with Densely Connected Networks for Near-Duplicate Image Detection System

Modelling of Firefly Algorithm with Densely Connected Networ...

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Sustainable Communication Networks and Application (ICSCNA), International Conference on

作者： Srinidhi Sundaram Kamalakkannan Somasundaram S. Jothilakshmi Sasikala Jayaraman P. Dhanalakshmi Department of Information Technology Annamalai University Annamalai Nagar Department of Information Technology School of Computing Sciences VISTAS (Vels Institute of Sciences Technology & Advanced Studies) Pallavaram Chennai Dept of Computer Science & Engineering Annamalai University Annamalai Nagar

Near-duplicate image detection is the way of detecting and flagging images that are highly similar to each other but not identical. It is a crucial task in different fields, including search engines, content management, and copyright enforcement, as it helps in content and organization de duplication. To achieve this, techniques and algorithms are employed that calculate similarity metrics, compare features, or analyze image content to define the degree of resemblance between images. Near-duplicate image detection can include approaches such as feature extraction, machine learning, and perceptual hashing to effectively manage and identify similar images in large datasets, which offer benefits in content retrieval and storage optimization. Therefore, this study presents a new firefly algorithm with deep learning-based near-duplicate image detection (FFADL-NDID) technique. Initially, median filtering (MF) approach is used to preprocess the input images. The proposed FFADL-NDID technique exploits the robust feature extraction abilities of DenseNet, a pre-trained DL model for capturing complex visual patterns from database and query images. In addition, the FFA is applied to carry out the hyperparameter tuning, optimizing the system for superior performance. This synergistic fusion enhances the overall efficiency of near-duplicate image detection by successfully searching the hyperparameter space for optimal configurations. Finally, the FFADL-NDID framework applies Euclidean distance-based similarity matching processes, which detects the near-duplicate images significantly. The simulation analysis of the FFADL-NDID method is tested on multiple datasets and the outcomes show its promising performance over other DL models in terms of different measures.

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Research Challenges in Future Internet of Things (IoT) Applications and Technologies 5

Research Challenges in Future Internet of Things (IoT) Appli...

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5th International Conference on Trends in Electronics and Informatics, ICOEI 2021

作者： Anandkumar, V. Diwakaran, M. Sivabalan, K.N. Balakrishna, R. Sri Krishna College of Engineering and Technology Department of Information Technology Coimbatore India Vels Institute of Science Technology and Advanced Studies Department of Computer Science and Engineering India

ISBN: (纸本)9781665415712

The internet has become an integral part of our daily lives, and it is the medium that connects everyone on the planet, allowing individuals to exchange their opinions, knowledge, and experience. Because this entire network of individuals is connected via the internet, they might be referred to as the 'internet of people'. What if the diurnal devices use by humans can also share their experiences with other things, communicate with us and work according to our commands using the internet as the medium. This whole idea is being realized under Internet of Things (IOT) technology. So, all the IOT devices or networks are developed to attain the above functionality and they are also equipped with three different layers of technologies namely Sensor, Communication and computational or processing technologies. This integrated network of various technologies is being developed to sort out the key human adversities such as water wastage, pollution, depletion of energy resources, health issues etc., and this paves way to establish a balance between the growing population and resources. © 2021 IEEE.

关键词： Internet of things

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Executing the Apriori Hybrid Algorithm in Semi-structured Mining Datasets and Comparison with HD Algorithm 1st

Executing the Apriori Hybrid Algorithm in Semi-structured Mi...

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1st International Conference on Mathematical Modeling and Computational science, ICMMCS 2020

作者： Akila, D. Jeyalaksshmi, S. Suseendran, G. D.Balaganesh Department of Information Technology Vels Institute of Science and Technology and Advanced Studies Chennai India Department of Computer Science and Multimedia Lincoln University College Kota Bharu Malaysia

ISBN: (纸本)9789813343887

The recent development in data mining in various fields and firms, for example, hospital, medicinal research, banking, government firm attracted many users. Data examination can be done in numerous possible ways quickly. But for the data examination in semi-structured datasets like XML format, json is little tricky than standard datasets. The easy examination of data in semi-structured datasets is possible by using Apriori hybrid algorithm. Hash tree algorithm is combined with weighed Apriori to get the Apriori hybrid algorithm and when compared with hybrid distribution algorithm (HD algorithm). The pseudo-code is then created and implemented for the proposed algorithm. The systematic graph illustrates to differentiate the Apriori hybrid algorithm and other algorithms like weighted, hash tree, and hybrid distribution algorithm. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Data mining

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Anomalous Fraunhofer-like patterns in quantum anomalous Hall Josephson junctions

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Physical Review Research 2024年第2期6卷 023293-023293页

作者： Junjie Qi Haiwen Liu Jie Liu Hua Jiang Dong E. Liu Chui-Zhen Chen Ke He X. C. Xie Beijing 100193 China Center for Advanced Quantum Studies Department of Physics School of Physics Institute for Nanoelectronic Devices and Quantum Computing State Key Laboratory of Low Dimensional Quantum Physics Department of Physics Frontier Science Center for Quantum Information Beijing 100084 China Hefei 230088 China School of Physical Science and Technology Institute for Advanced Study International Center for Quantum Materials School of Physics

The intriguing interplay between topology and superconductivity has attracted significant attention, given its potential for realizing topological superconductivity. In the quantum anomalous Hall insulators (QAHIs)-based junction, the supercurrents are carried by the chiral edge states, characterized by a 2Φ0 magnetic flux periodicity (Φ0=h/2e is the flux quantum, h the Planck constant, and e the electron charge). However, experimental observations indicate the presence of bulk carriers in QAHI samples due to magnetic dopants. In this study, we reveal a systematic transition from edge-state to bulk-state dominant supercurrents as the chemical potential varies from the bulk gap to the conduction band. This results in an evolution from a 2Φ0-periodic oscillation pattern to an asymmetric Fraunhofer pattern. Furthermore, a Fraunhoher-like pattern emerges due to the coexistence of chiral edge states and bulk states caused by magnetic domains, even when the chemical potential resides within the gap. These findings not only advance the theoretical understanding but also pave the way for the experimental discovery of the chiral Josephson effect based on QAHI doped with magnetic impurities.

关键词： Andreev reflection Critical current Josephson effect Quantum interference effects Superconductivity

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Understanding Older Adults' (Dis)Engagement with Design Materials 25

Understanding Older Adults' (Dis)Engagement with Design Mate...

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2025 CHI Conference on Human Factors in computing Systems, CHI 2025

作者： Pradhan, Alisha Jelen, Ben Thangaraj, Ramprabu Siek, Katie A. Jette, Shannon Lazar, Amanda Department of Informatics Ying Wu College of Computing New Jersey Institute of Technology NewarkNJ United States Computer Science and Software Engineering Rose-Hulman Institute of Technology Terre HauteIN United States Ying Wu College of Computing New Jersey Institute of Technology NewarkNJ United States Luddy School of Informatics Computing and Engineering Indiana University BloomingtonIN United States University of Maryland College ParkMD United States College of Information Studies University of Maryland College ParkMD United States

ISBN: (纸本)9798400713941

Design workshops are a popular approach to include older adults in the technology design process. However, formative design sessions with older adults have had unexpected outcomes such as the non-use of traditional design materials like craft-based prototyping supplies or disengagement from design activities. Analyzing the engagement of 32 older adults across two design workshops, this paper sheds insights on some of these outcomes. Contributing to a growing body of HCI research on understanding older adults' participation in design, we provide an understanding of how design materials can shape older adults' engagement in formative design activities. Our discussion furthers research on understanding who older adults design for and why, argues for a different understanding of creative expression, and offers considerations for choosing design materials. © 2025 Copyright held by the owner/author(s).

关键词： Design for manufacturability

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