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5th International Conference on Recent Innovations in Computing , ICRIC 2022

作者： Umapathi, N. Harshitha, Poladi Bhavani, Ireddy Department of Electronic and Communication Engineering Jyothishmathi Institute of Technology & Science Telangana Karimnagar India

ISBN: (纸本)9789819906000

In underground mining industries, there are many factors that may risk the lives of workers. We have seen many people who lost their livelihood due to emergency situations in the mines. These emergency situations occur due to the leakage of harmful gases or sudden explosions, and also workers may undergo some kind of ventilation problems. As we know, coal contributes more in the production of energy, so mining of a coal plays a major role. By considering all these factors, we have introduced a smart helmet system which helps the workers to get warned under any emergency circumstances. The only objective of this prototype is to ensure the safety of the workers. And, the technique we use to do this is to provide a proper communication between the worker and the monitoring system. The communication can be provided using various methods such as Bluetooth, ZigBee, Wi-Fi modules. Here, we have chosen Wi-Fi module, i.e., ESP32 as it provides higher transmission rate along with covering longest distance. The data can be received by a monitoring system through the Blynk app which is an open-source IoT platform. The gases exist in the environment are detected by our smart helmet using the related sensors and are sent to the monitoring system. By implementing this model, we have created a communication so that the worker can feel safe to enter the mines and can concentrate on his/her work. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Occupational risks

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Machine Learning for Signal Processing in communication Systems

Machine Learning for Signal Processing in Communication Syst...

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2024 International Conference on Innovative Computing, Intelligent communication and Smart Electrical Systems, ICSES 2024

作者： Reddy, PoliLokeshwara Shreyas, Chanda Bhargavi, Pamulapati. Raja, G.V. Rani, D. Leela Maheswari, S. Anurag University Department of Electronics and Communication Engineering Telangana Hyderabad500088 India Kkr & Ksr Institute of Technology and Sciences Department of Computer Science Engineering Andhra Pradesh Guntur522017 India Sri Sairam College of Engineering Department of Electronics and Communication Engineering Karnataka Bengaluru562106 India Mohan Babu University Department of Electronics and Communication Engineering Andhra Pradesh Tirupati517102 India Kongu Engineering College Department of Electrical and Electronic Engineering Tamil Nadu Perundurai638060 India

ISBN: (纸本)9798331543617

The traditional styles of signal processing are passing constraints in their capability to handle the different and dynamic character of ultramodern data transfers. This is because communication systems are getting increasingly complicated. The operation of machine literacy presents a potentially useful answer since it enables data-driven, adaptive approaches that have the eventuality to ameliorate signal processing performance. This composition provides a comprehensive examination of a variety of machine literacy ways and their operations in important disciplines such as modulation recognition, noise reduction, channel estimation, and signal discovery. The study demonstrates how machine literacy ways may vastly increase the effectiveness, delicacy, and robustness of signal-processing tasks in communication systems. This is fulfilled through detailed analysis and comparison. With the help of machine literacy, unborn communication systems will be suitable to attain advanced situations of robotization and intelligence, which will pave the way for further developments in areas similar to wireless dispatches, the Internet of Effects(IoT), and other areas. In light of these findings, it's clear that machine literacy can fully transfigure assiduity by furnishing new shoes and approaches to the optimization of signal processing in the unborn generation of communication networks. © 2024 IEEE.

关键词： Noise abatement

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Clustering-based adaptive low-power subframe configuration with load-aware offsetting in dense heterogeneous networks

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Digital communications and Networks 2022年第5期8卷 843-852页

作者： Dinkisa A.Bulti Jyri Hämäläinen Beneyam B.Haile Yihenew Wondie School of Electrical and Computer Engineering Addis Ababa Institute of Technology(AAiT)Ethiopia Department of Communication and Networking Aalto UniversityFinland

Heterogeneous Networks(HetNets)and cell densification represent promising solutions for the surging data traffic demand in wireless *** dense HetNets,user traffic is steered toward the Low-Power Node(LPN)when possible to enhance the user throughput and system capacity by increasing the area spectral ***,because of the transmit power differences in different tiers of HetNets and irregular service demand,a load imbalance typically exists among different serving *** offload more traffic to LPNs and coordinate the Inter-Cell Interference(ICI),Third-Generation Partnership Project(3GPP)has facilitated the development of the Cell Range Expansion(CRE),enhanced Inter-Cell Interference Coordination(eICIC)and Further enhanced ICIC(FeICIC).In this paper,we develop a cell clustering-based load-aware offsetting and an adaptive Low-Power Subframe(LPS)*** solution allows the separation of User Association(UA)functions at the User Equipment(UE)and network server such that users can make a simple cell-selection decision similar to that in the maximum Received Signal Strength(max-RSS)based UA scheme,where the network server computes the load-aware offsetting and required LPS periods based on the load conditions of the *** proposed solution is evaluated using system-level simulations wherein the results correspond to performance changes in different service *** show that our method effectively solves the offloading and interference coordination problems in dense HetNets.

关键词： Heterogeneous networks(HetNets) 5G LTE-AUser association Interference coordination Load balancing Cell range expansion Almost blank subframe Further enhanced ICIC Low-power subframe

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Unveiling the Safety Aspects of DevSecOps: Evolution, Gaps and Trends

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Recent Advances in computer Science and communications 2023年第3期16卷 61-69页

作者： Ramaj, Xhesika Sánchez-Gordón, Mary Chockalingam, Sabarathinam Colomo-Palacios, Ricardo Department of Computer Science and Communication Faculty of Computer Sciences Engineering and Economics Østfold University College Halden Norway Department of Risk Safety and Security Institute for Energy Technology Halden Norway

Background: The popularity of DevSecOps is on the rise because it promises to integrate a greater degree of security into software delivery pipelines. However, there is also an unacceptable risk related to safety that cannot be overlooked, given the importance of this aspect in many industries. Objective: The objective of this study is to provide an overview of the safety aspects reported in the literature on DevSecOps. This study also characterizes such aspects and identifies the gaps that may lead to future research work. Methods: A systematic literature review was conducted using five well-known academic databases. The search was executed in September 2021 and March 2022 to identify relevant studies. Results: The search returned 114 academic studies. After the screening process, five primary studies published between 2019 and 2021 were selected. These studies were analyzed thoroughly to identify the safety aspects. Then, we categorized them into three main groups: (i) risk-related safety aspects, (ii) human-related aspects, and (iii) management aspects. Conclusion: Safety is an important characteristic that is becoming more critical as the number of critical systems grows. This review reveals that only a scarce number of studies are focusing on safety in DevSecOps. However, those studies gave us some insights into this topic. Therefore, our main observation is that this topic has not yet been completely explored in the academic literature. This review can encourage reflection and discussion between the safety and security communities. © 2023 Bentham Science Publishers.

关键词： Accident prevention

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Hybrid CNN-LSTM Model for Enhanced Weather Forecasting: Leveraging Spatial and Temporal Dependencies 4

Hybrid CNN-LSTM Model for Enhanced Weather Forecasting: Leve...

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4th International Conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Vallileka, N. Rajkumar, G.Vinoth Krishnan, R. Santhana Shankar, S. Vijay Francis Raj, J. Relin Karthikeyan, M. Saravana Psna College of Engineering and Technology Department of Computer Applications Dindigul India J. P. College of Engineering Department of Electronics and Communication Engineering Tenkasi India Scad College of Engineering and Technology Department of Electronics and Communication Engineering Cheranmahadevi India Sona College of Technology Department of Electrical and Electronics Engineering Salem India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Electronics and Communication Engineering Chennai India Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Avadi Chennai India

ISBN: (纸本)9798331523923

Accurate weather forecasting is critical for decision-making in agriculture, disaster management, urban planning, and numerous other domains. Traditional forecasting methods often struggle to capture the intricate spatial and temporal dependencies in weather data. This work proposes a hybrid deep learning model that integrates Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks to address these challenges. The CNN component efficiently extracts spatial features from satellite images, such as cloud formations and precipitation zones, while the LSTM network models the temporal dependencies inherent in meteorological data, such as temperature, humidity, and wind speed. The model is trained on a dataset comprising historical weather records and satellite imagery, spanning several years. PyTorch, a dynamic deep learning framework, is used to implement and train the hybrid architecture. Data preprocessing involves normalization, image augmentation, and sequence structuring to prepare inputs for the model. The CNN layers, built with convolutional and pooling operations, extract spatial features, which are combined with temporal weather data and passed to the LSTM network. The LSTM layers capture long-term dependencies and trends in weather patterns. Fully connected layers map the learned features to final predictions, including temperature, rainfall, and other key weather parameters. The hybrid model is evaluated using metrics such as Root Mean Square Error (RMSE) for numerical predictions and accuracy for classification tasks. Results indicate that the proposed hybrid CNN-LSTM model outperforms standalone models and traditional statistical approaches, demonstrating its ability to leverage spatial and temporal dependencies for accurate weather forecasting. This work highlights the potential of hybrid deep learning models in advancing weather forecasting capabilities, offering a scalable and reliable solution for real-world applications such as e

关键词： Convolutional neural networks

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Fundamental Limits of Multiple-Access Integrated Sensing and communication Systems

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IEEE Transactions on Information Theory 2025年第6期71卷 4317-4341页

作者： Liu, Yao Li, Min Liu, An Ong, Lawrence Yener, Aylin Zhejiang University College of Information Science and Electronic Engineering Zhejiang Provincial Key Laboratory of Multi-Modal Communication Networks and Intelligent Information Processing Hangzhou310027 China University of Newcastle School of Engineering CallaghanNSW2308 Australia The Ohio State University Department of Electrical and Computer Engineering ColumbusOH43210 United States

A state-dependent discrete memoryless multiple access channel is considered to model an integrated sensing and communication system, where two transmitters wish to convey messages to a receiver while simultaneously estimating the state parameter sequences through echo signals. In particular, the sensing state parameters are assumed to be correlated with the channel state. In this setup, improved inner and outer bounds for capacity-distortion region are derived. The inner bound is based on an achievable scheme that combines message cooperation and joint compression of past transmitted codewords and echo signals at each transmitter, resulting in unified cooperative communication and sensing. The outer bound is based on the ideas of dependence balance for communication rate, genie-aided state estimator and rate-limited constraints on sensing distortion. The proposed inner and outer bounds are proved to improve the state-of-the-art bounds. Finally, numerical examples are provided to demonstrate that our new inner and outer bounds strictly improve the existing results. © 1963-2012 IEEE.

关键词： Signal distortion

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Performance of MISO Systems with Alamaouti Transmit Diversity and Antenna Selection in TDD and FDD 4th

Performance of MISO Systems with Alamaouti Transmit Divers...

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4th International Conference on Emerging Technology Trends in electronics, communication and Networking, ET2ECN 2021

作者： Trivedi, Dehit H. Joshi, Neel N. Trivedi, Y.N. Department of Electronic and Communication Engineering Institute of Technology Nirma University Ahmedabad382481 India

ISBN: (纸本)9789811967368

In this paper, the focus is to obtain performance of a multiple input and single output (MISO) wireless communication system in a real-time scenarios of time division duplex (TDD) and frequency division duplex (FDD). We consider a MISO system equipped with 2N transmit antennas. In the total N pairs of antenna, there is a spatial correlation in each pair (two antennas) only. We assume quasi-static Rayleigh fading channels. We select one pair of antennas with the highest channel power gain. In case of FDD, we assume antenna selection and detection, both based on imperfect channel state information (CSI), whereas in case of TDD, detection is based on imperfect CSI, but antenna selection is to be done using perfect CSI. Finally, we use Alamouti transmit diversity. For this system, we present the performance in terms of bit error rate (BER) versus avg. signal-to-noise ratio (SNR) and outage probability versus avg. SNR using Monte Carlo simulations. We have seen the adverse effect of spatial correlation and imperfect CSI on the performance. We conclude that TDD outperforms the FDD due to higher antenna selection gain. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Antennas

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Analysis of Cs2TiBr6 Single-Halide Perovskite Solar Cell by Introducing IDL 24

Analysis of Cs2TiBr6 Single-Halide Perovskite Solar Cell by ...

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24th IEEE International Conference on Numerical Simulation of Optoelectronic Devices, NUSOD 2024

作者： Kaur, Jaspinder Gupta, Syamantak Basu, Rikmantra Sharma, Ajay Kumar National Institute of Technology Delhi Department of Electronics and Communication Engineering New Delhi India National Institute of Technology Delhi Department of Computer Science and Engineering New Delhi India

ISBN: (纸本)9798350390537

Lead-based perovskite solar cells (PSCs) are popular in the photovoltaic industry for their remarkable properties, but issues like toxicity and instability limit their use. To address these problems, eco-friendly, lead-free, and stable Cesium Titanium Bromide (Cs2TiBr6) absorber material has been introduced. This work simulates an FTO/SnO2/IDL1/Cs2TiBr6/IDL2/MoOX/Au structure using SCAPS-1D incorporating the use of interfacial defect layer (IDL), examining factors such as layer thickness, doping, defect density, and quantum efficiency. The optimized structure achieves a power conversion efficiency (PCE) of 20.11%, having a fill factor of 82.17, VOC of 1.488 V, and JSC of 16.34 mA/cm2. This research supports the development of efficient, low-toxic, and stable PSCs for the solar industry. © 2024 IEEE.

关键词： Perovskite solar cells

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Optimised Data Encryption and Search Efficiency Framework Using Memory Modules for IoT Applications 2

Optimised Data Encryption and Search Efficiency Framework Us...

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2nd International Conference on Computational Intelligence, communication Technology and Networking, CICTN 2025

作者： Gakhar, Suket Kulkarni, Soham Sunil Kumar, Anant Sharma, Vipin Kumar Arora, Sneha Department of Computer Science and Engineering Kurukshetra University Kurukshetra India Department of Computer Science University of California Irvine Irvine United States Department of Computer Science and Engineering Manipal Institute of Technology Manipal India Department of Electronics and Communication Engineering Lovely Professional University Phagwara India

ISBN: (纸本)9798331530389

The proliferation of IoT devices necessitates secure and efficient mechanisms for data encryption and retrieval. This paper presents an optimized framework that leverages AES encryption integrated with memory modules to enhance security and operational efficiency. The proposed system introduces a dynamic key generation mechanism to mitigate key reuse vulnerabilities and incorporates a memory module to achieve reductions in encryption and search execution times by 80% and 79%, respectively, compared to traditional methods. The framework also ensures secure cloud storage of encrypted data and supports privacy-preserving retrieval using trapdoor functions. A Java-based implementation validates the system's scalability, robustness, and platform independence for real-world IoT applications. By addressing key challenges such as data integrity, confidentiality, and low-latency operations, the proposed framework offers a comprehensive solution tailored to the evolving needs of the IoT ecosystem. © 2025 IEEE.

关键词： Data integrity

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Enhancing Sustainable Development Through Electrooculography Based computer Control System for Individuals with Mobility Limitations 1st

Enhancing Sustainable Development Through Electrooculography...

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1st International Conference on Sustainable Development through Machine Learning, Artificial Intelligence, and IoT, ICSD 2023

作者： Bhalla, Pragya Tiwary, Diksha Aggarwal, Manasvi Sharma, Sakshi Kaushik, Monika Agarwal, Megha Department of Electronic and Communication Engineering Bhagwan Parshuram Institute of Technology GGSIPU Delhi India

ISBN: (纸本)9783031470547

Electrooculogram (EOG), the bio-potential produced around eyes due to eyeball motion can be used to track eye movements. This system is especially helpful for individuals with motor disabilities like ALS (Amyotrophic Lateral Sclerosis) and paralysis. The research describes a method of controlling the mouse cursor on a computer screen using a technique called Electrooculography (EOG). EOG could detect the electric potentials generated by eye movements and blink features. The recorded EOG signal is then analyzed to identify and classify the relevant eye movement features. These features are then used to generate control signals that allow for cursor movement. The results show that the cursor control application is highly accurate when tested offline. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Eye movements

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