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2nd IEEE Global Conference on Communications and Information Technologies, GCCIT 2024

作者： Prakash, Mangali Bhanu Kumar, E. Ravi Anitha, Banavath Bansilal, Boda Mukkamall, Babu Reddy Sanjana, Gudipati Pranaya Vardhaman College Of Engineering Dept. of Information Technology Hyderabad India Krishna University Machilipatnam Dept. of Computer Application Machilipatnam India

ISBN: (纸本)9798350388916

Picture steganography plays a crucial role in secure communication by discreetly altering images for various purposes such as data authentication, privacy protection, and watermarking. However, traditional methods often lack resistance to manipulation. To address this, we propose a solution that merges automated password generation with the Least Significant Bit (LSB) approach. This method involves embedding text within images and automatically generating an encryption password to safeguard data security. By employing Simple Mail Transfer Protocol (SMTP) credentials, encrypted photos can be directly sent to recipients, significantly expediting the process. This automated approach eliminates the necessity for separate transfers of the image and decryption password, thereby enhancing simplicity and security. This new technology seamlessly integrates encryption, ensuring a trustworthy and secure communication channel. With this innovative solution, users can transmit sensitive information confidently, knowing that it is shielded from unauthorized access or manipulation. By combining the strengths of automated password generation, LSB steganography, and SMTP transmission, our approach provides a robust framework for safeguarding digital communication in various context. © 2024 IEEE.

关键词： Authentication Protocol

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Multi-agent QoS-aware autonomic resource provisioning framework for elastic BPM in containerized multi-cloud environment

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Journal of Ambient Intelligence and Humanized Computing 2023年第9期14卷 12895-12920页

作者： Saif, Mufeed Ahmed Naji Niranjan, S.K. Murshed, Belal Abdullah Hezam Al-ariki, Hasib Daowd Esmail Abdulwahab, Hudhaifa Mohammed Department of Computer Applications Sri Jayachamarajendra College of Engineering VTU Mysore India Department of Studies in Computer Science University of Mysore Karnataka Mysore India Department of Computer Science College of Eng. &IT University of Amran Amran Yemen Department of Information Technology Faculty of Engineering and Information Technology Al-ata’a University for Science and Technology Taiz Yemen Department of Computer Networks Engineering and Technologies Sana’a Community College Sana’a Yemen Department of Computer Application Ramaiah Institute of Technology VTU Bangalore India

Cloud computing enables businesses to improve their market competitiveness, enabling instant and easy access to a pool of virtualized and distributed resources such as virtual machines (VM) and containers for executing their business operations efficiently. Though the cloud enables the deployment and management of business processes (BPs), it is challenging to deal with the enormous fluctuating resource demands and ensure smooth execution of business operations in containerized multi-cloud. Therefore, there is a need to ensure elastic provisioning of resources to tackle the over and under-provisioning problems and satisfy the objectives of cloud providers and end-users considering the quality of service (QoS) and service level agreement (SLA) constraints. In this article, an efficient multi-agent autonomic resource provisioning framework is proposed to ensure the effective execution of BPs in a containerized multi-cloud environment with guaranteed QoS. To improve the performance and ensure elastic resource provisioning, autonomic computing is utilized to monitor the resource usage and predict the future resource demands, then resources are scaled based on demand. Initially, the required resources for executing the incoming workloads are identified by clustering the workloads into CPU and I/O intensive, and the local agent achieves this with the help of an initialization algorithm and K-means clustering. Then, the analysis phase predicts the workload demand using the proposed enhanced deep stacked auto-encoder (EDSAE), further, the containers are scaled based on the prediction outcomes, finally, the multi-objective termite colony optimization (MOTCO) algorithm is used by the global agent to find suitable containers for executing the clustered workloads. The proposed framework has been implemented in the Container Cloudsim platform and evaluated using the business workload traces. The overall simulation results proved the effectiveness of the proposed approach compare

关键词： Quality of service

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Enhancing Automated Industrial Guiding Through computer Vision-Based Detection of Centerlines and Patterns

Enhancing Automated Industrial Guiding Through Computer Visi...

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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Kumari, Neeraj Ojha, Ananta Goyal, Manish Kumar Teetthanker Mahaveer University Department of Computing Sciences and Information Technology Uttar Pradesh Moradabad India Department of Computer Science and Information Technology Bangalore India Vivekananda Global University Department of Computer Science & Application Jaipur India

ISBN: (纸本)9798350383348

This paper gives a method for enhancing automatic industrial guiding via pc vision-based detection of centerlines and patterns. The principal intention of this painting is to utilize vision algorithms to offer a reliable steering system for commercial robots. The technique combines numerous vision-primarily based detection techniques that allow you to come across the favored center lines and patterns. The consequent steerage device is then examined with actual robot experiments for validation. Moreover, a novel metric for measuring the accuracy of the detection device is also proposed. The effects show that the proposed technique gives a dependable answer for automatic commercial guiding. This paper discusses an automated business steerage technique, which leverages laptop imagination and is prescient to become aware of centerlines and patterns in business additives. This method uses a Convolutional Neural community (CNN) to discover those strains and patterns. To carry out detection, a CNN is educated on a fixed of photographs containing centerlines or styles and corresponding ground reality that is manually annotated. The effects of the CNN are used to guide robots to their favored function and become aware of element edges. © 2024 IEEE.

关键词： algorithms commercial experiments misalignments robots

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Automatic Controlled Robotic Car Based on Node MCU for Real-Time Obstacle and Explosive Detection 4

Automatic Controlled Robotic Car Based on Node MCU for Real-...

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

作者： Dutt, Krishan Misra, Alok Tiwari, Raj Gaurang Singh, Ravinder Mishra, Mohit Kaur, Amninder School of Computer Application Lovely Professional University Punjab Phagwara India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798350387490

Automatic vehicles have significant challenges when it comes to detecting and avoiding obstacles in real-time. By considering hardware, software, and communication settings, this study shows the design and implementation of a robotic automobile that can recognize and avoid obstacles in real-time. Robotic vehicles that are programmed to drive themselves utilizing platform-based sensors are detailed in this research. Working together, an Android-based smartphone and this automated gadget are developed. The Arduino Uno has functioned as the robot's central processing unit. The robot is comprised of a multitude of hardware components, such as buzzers, infrared sensors, ultrasonic sensors, and Bluetooth modules. It also contains the software component that is used by mobile applications. Through a smartphone app, the driver of the autonomous vehicle may choose the desired route or driving mode and then order the vehicle to follow it. The robot may be set to work in conjunction with your smart device, or it can be just left in autonomous mode so it will go where it wants to go. Consequently, the robot can detect life and get away from the obstacle. The purpose of this paper is to alert both military and civilian personnel to the possibility of terrorist attacks, with a focus on those branches of the military that have live, detectable sensors. © 2024 IEEE.

关键词： Ultrasonic sensors

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CLAACS-IOD: Certificate-embedded lightweight authentication and access control scheme for Internet of Drones

CLAACS-IOD: Certificate-embedded lightweight authentication ...

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作者： Sadhukhan, Dipanwita Ray, Sangram Dasgupta, Mou Rodrigues, Joel J. P. C. Department of Computer Science and Engineering National Institute of Technology Sikkim Sikkim Ravangla India Department of Computer Application National Institute of Technology Raipur Raipur India Qingdao China Instituto de Telecomunicações Covilhã Portugal

In recent era, the unmanned aerial vehicles (UAVs) commonly known as drones has emerged as a one of the most significant and promising tools which has demonstrated its wide range of implementations variating from commercial domain to the field of defense due to its distinct capabilities such as inspection, surveillance, precision and so forth. Internet connected drones provides a propitious trend that boosts the flying safety, and service qualities of the UAVs where numerous low-altitude drones winged in different flying regions for executing a precise task such as gathering the real-time information from the unuttered environment to be interpretated by users. Nevertheless, the open-access insecure communications in hostile environment, the issues like safety and confidentiality threats, various security concerns such as the leakage of flying courses, identities, position, and gathered data by the drones are upstretched. To address these security concerns, access control mechanism provides a potential service in terms of authentication and key agreement for securing the communication between the individual drones within their respective flying regions. This article introduces a robust, efficient, lightweight, and privacy preserving ECC integrated access control approach by employing digital certificate with considering the high dynamicity and mobility of the drones. The designing of this proposed approach, that is, CLAASC-IoD is influenced by the aim of inter-drone and drone-to-ground station communication in the IoD paradigm. The detailed analysis of security using probabilistic random oracle model as well as simulation using well-accepted security verification tool AVISPA and comparative performance evaluation supports the claim of robustness, effectiveness, and proficiency. © 2023 John Wiley & Sons Ltd.

关键词： Internet of things

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Accurate Diagnosis by Magnetic Resonance Imaging Using Deep Learning

Accurate Diagnosis by Magnetic Resonance Imaging Using Deep ...

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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Rengarajan, A. Ahmed, Zahid Pandey, Rajendra P. Department of Computer Science and Information Technology Bangalore India Vivekananda Global University Department of Computer Science & Application Jaipur India Teetthanker Mahaveer University Department of Computing Sciences and Information Technology Uttar Pradesh Moradabad India

ISBN: (纸本)9798350383348

deep mastering has revolutionized the field of scientific imaging, providing practical affected person prognosis competencies. A current example is deep studying for Magnetic Resonance Imaging (MRI) acquisition, reconstruction, segmentation, and interpretation. Deep mastering-primarily based strategies leverage convolutional neural networks (CNNs) to automatically classify and section not unusual disease areas in MRI scans, allowing particular and correct prognosis. Those computerized strategies can potentially conquer the bottleneck of the complex work-intensive guide segmentation and visualization procedure. Moreover, they can provide an extra complete assessment of complex sicknesses. Through incorporating both the semantic and spatial information of image information, the overall performance of deep-gaining knowledge of-based totally structures for MRI evaluation has dramatically progressed. Moreover, CNN-based total MRI segmentation has proven promise in targeted and effective remedies for numerous diseases, including mind tumors, stroke, and dementia. The demonstration of superior effects in segmentation and classification tasks, in terms of accuracy and efficiency, shows the potential of deep learning-based techniques as an effective device within the automation of MRI analysis. © 2024 IEEE.

关键词： classification demonstration performance prognosis visualization

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Designing Blockchain Based Consensus Mechanism for Smart Healthcare IoT

Designing Blockchain Based Consensus Mechanism for Smart Hea...

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2023 IEEE International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, ICIITCEE 2023

作者： Kumari, Trishla Kumar, Rakesh Dwivedi, Rajendra Kumar Madan Mohan Malviya University of Technology Dept. of Computer Science and Engineering Gorakhpur India Madan Mohan Malviya University of Technology Dept. of Information Technology and Computer Application Gorakhpur India

ISBN: (纸本)9781665462631

In today's world, healthcare system is improving day by day by using smart IoT based system. Blockchain based system is totally a decentralized system due to which attackers are unable to access the confidential records easily. Blockchain play an important role in controlling and management of sensitive information in healthcare system and insurance sector. Consensus mechanisms used in blockchain technology to validate whichever block is going to be added next in the blockchain network. In this paper we proposed a hybrid based system which solves trust issues arises in the blockchain. Hybrid consensus mechanism provides reputation according to the activities of blocks in a blockchain network. Four layer architecture is designed in Hybrid model. Five algorithms are used to create, validate, fork handling, reward and punishment scheme and Markle tree is constructed respectively. This model is implemented on Ethereum based platform which shows that HCM model is better than a PoXR model as it consume less memory (50 percent) and consume less CPU(below 2 percent). © 2023 IEEE.

关键词： Blockchain

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Unsupervised Anomaly Detection Based on CNN-VAE with Spectral Residual for KPIs 24

Unsupervised Anomaly Detection Based on CNN-VAE with Spectra...

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24th IEEE International Conference on High Performance Computing and Communications, 8th IEEE International Conference on Data Science and Systems, 20th IEEE International Conference on Smart City and 8th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and application, HPCC/DSS/SmartCity/DependSys 2022

作者： Li, Gongliang Wen, Zepeng Xie, Xin Institute of Computer Application Technology China Academy of Engineering Physics College of Computer Science Sichuan University Mianyang China Institute of Computer Application Technology China Academy of Engineering Physics Mianyang China

ISBN: (纸本)9798350319934

Current large-scale applications, such as trading systems, blockchain, social software, etc, are increasingly adopting microservice architecture, which bring challenges to manual operation and maintenance, intrusion detection. In both operations and intrusion detection, there are a common characteristic that service metrics and network traffic are normal for most of the time, but anomaly data is more important. In this paper, we propose an unsupervised anomaly detection algorithm based on convolutional neural network with Spectral Residual, which is verified experimentally and has potential application capability with 19.2% f1-score improvement compared to the Variational AutoEncoder. © 2022 IEEE.

关键词： Intrusion detection

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Physics-Informed Neural Networks for One-Dimensional Quantum Well Problems

arXiv

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arXiv 2025年

作者： Sarkar, Soumyadip Department of Computer Application Narula Institute of Technology India

We implement physics-informed neural networks (PINNs) to solve the time-independent Schrödinger equation for three canonical one-dimensional quantum potentials: an infinite square well, a finite square well, and a finite barrier. The PINN models incorporate trial wavefunctions that exactly satisfy boundary conditions (Dirichlet zeros at domain boundaries), and they optimize a loss functional combining the PDE residual with a normalization constraint. For the infinite well, the ground-state energy is known (E = π2 in dimensionless units) and held fixed in training, whereas for the finite well and barrier, the eigenenergy is treated as a trainable parameter. We use fully-connected neural networks with smooth activation functions to represent the wavefunction and demonstrate that PINNs can learn the ground-state eigenfunctions and eigenvalues for these quantum systems. The results show that the PINN-predicted wavefunctions closely match analytical solutions or expected behaviors, and the learned eigenenergies converge to known values. We present training logs and convergence of the energy parameter, as well as figures comparing the PINN solutions to exact results. The discussion addresses the performance of PINNs relative to traditional numerical methods, highlighting challenges such as convergence to the correct eigenvalue, sensitivity to initialization, and the difficulty of modeling discontinuous potentials. We also discuss the importance of the normalization term to resolve the scaling ambiguity of the wavefunction. Finally, we conclude that PINNs are a viable approach for quantum eigenvalue problems, and we outline future directions including extensions to higher-dimensional and time-dependent Schrödinger equations. © 2025, CC BY.

关键词： Schrodinger equation

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Correction to: Evaluation of land use land cover dynamics and urban heat island effects over Mumbai metropolitan Region, India (International Journal of Environmental Science and technology, (2024), 10.1007/s13762-024-06266-4)

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International Journal of Environmental Science and technology 2025年 1-2页

作者： Kavathekar, V. Tripathy, A.K. Chettri, S.K. Bhanage, V. Computer Science and Engineering Computer Application Assam Don Bosco University Assam India Computer Engineering Don Bosco Institute of Technology Mumbai India PHIS Centre The IDEC Institute Hiroshima University IDEC Bldg. 1-5-1 Kagamiyama Higashi-Hiroshima739-8529 Japan

The original version of this Article contained an error in the representation of elevation values depicted in the Fig. 1. Incorrect version of Fig. 1 Geographical location of the Mumbai metropolitan region contributes to achieving the region’s sustainable development goals. (Figure presented.) Readers should consider following Figure as Fig. 1. Correct version of Fig. 1 Geographical location of the Mumbai metropolitan region (Figure presented.) © The Author(s) under exclusive licence to Iranian Society of Environmentalists (IRSEN) and Science and Research Branch, Islamic Azad University 2025.

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