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Security to text (S2T): multi-layered based security approaches for secret text content

Multimedia Tools and Applications 2025年第15期84卷 15151-15171页

作者： Kashid, Shamal Awasthi, Lalit K. Berwal, Krishan Department of Computer Science and Engineering National Institute of Technology Uttarakhand IN Srinagar India Faculty of Communication Engineering Military College of Telecommunication Engineering IN Mhow India

In the digital world, text data is produced in an unstructured manner across various communication channels. Extracting valuable information from such data with security is crucial and requires the development of techniques in text mining, information retrieval, and natural language processing (NLP). To solve this issue, we introduce two novel approaches: keyword extraction (KE) and a multi-layered secret sharing scheme (MLSS) to provide security to extracted keywords rather than overall text documents. The KE approach encompasses a sequence of text pre-processing procedures, including tokenization, stopword removal, stemming, and bag of words representation, followed by indexing. This methodology aims to efficiently extract keywords from text datasets. For this research work, we have proposed three datasets, including text messages, whatsapp messages, and electronic mail. MLSS enhances the security of extracted textual data by leveraging text pre-processing steps. This scheme ensures better confidentiality and the non-revealment of sensitive information. Additionally, we evaluate our KE model on our dataset as well as on standard datasets. Experimental results demonstrate the effectiveness of our proposed security to text (S2T) model, which outperform existing state-of-the-art approaches. The model obtains a 100% correlation between the reconstructed text and the original text. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Extraction

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Proposed Edge Computing Neural Accelerator 4

Proposed Edge Computing Neural Accelerator

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4th IEEE International Conference on ICT in Business Industry and Government, ICTBIG 2024

作者： Singh, Vikram Aditya Verma, Rajesh Saini, Dori Singh Berwal, Krishan Vishwakarna, Sanotsh Kr Military College of Telecommunication Engineering Faculty of Telecommunication Engineering Indore India Computer Discount Warehouse Indore India Indian Institute of Technology Indore India

ISBN: (纸本)9798331518981

Edge computing is revolutionizing data processing, especially for applications like surveillance and traffic control systems. The data being processed closer to the source (e.g., cameras or sensors), with this edge computing reduces communication latency, bandwidth consumption, and power usage, addressing limitations of centralized cloud systems. The integration of machine learning (ML) in edge environments enhances surveillance systems, enabling real-time analytics, such as object detection and activity recognition. Convolutional Neural Networks (CNNs), widely used in video analytics, facilitate instant object recognition at the edge. However, the computational demands of deep neural networks (DNNs) require hardware accelerators like DNN accelerators for efficient deployment. These accelerators, implemented using technologies like Field-Programmable Gate Arrays (FPGAs) and Application-Specific Integrated Circuits (ASICs), improve latency and energy efficiency. Key benefits include parallelism, optimized memory management, and energy-efficient processing, essential for resource-constrained environments like surveillance drones. This paper explores the architecture of deep learning accelerators, such as the Edge Computing Neural Accelerator (ECNA), focusing on their role in real-time surveillance systems. By leveraging binary-weight convolutional layers and systolic array designs, ECNA significantly enhances processing speed and energy efficiency, enabling real-time video analytics while consuming minimal power. © 2024 IEEE.

关键词： Systolic arrays

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Advising and Scheduling Tool Based on Electrical Power engineering Concepts

Advising and Scheduling Tool Based on Electrical Power Engin...

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2025 International Conference on Control, Automation, and Instrumentation, IC2AI 2025

作者： Nehme, Bechara Al Ahmar, Elie Zalaket, Joseph Electrical Telecommunication and Computer Engineering Department Jounieh Lebanon University Furn El Chebbak Faculty of Engineering Sagesse Baabda Lebanon

ISBN: (纸本)9798331529604

University administrations are always in need for tools to optimize their operation decreasing operational costs and ensuring a good learning experience for students. Advising and course offering are two main tasks that require knowledge in the field and expertise. The tasks need also data and its related analytics. This paper presents an innovative advising tool based on data mining leveraging from electrical power concepts. The tool uses Python and Excel to automate advising sheets and electrical power engineering by applying simultaneity and the factor of utilization to students records and courses to predict future course enrollment with a RMSE=0.75. The research proposed is unique since it helps administration and advisors. With the reduction of resources and disruption of the classical educational system new tools should be elaborated to reduce costs and secure on time graduation of students. © 2025 IEEE.

关键词： Students

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Design and Analysis of a UWB Slotted Vivaldi Antenna for Microwave Imaging Applications

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IEIE Transactions on Smart Processing and Computing 2023年第4期12卷 350-357页

作者： Paul, Liton Chandra Majumder, Akash Rani, Tithi Hossain, Md. Najmul Rahim, Md. Abdur Shin, Jungpil Yun, Keun Soo Department of Electrical Electronic and Communication Engineering Faculty of Engineering and Technology Pabna University of Science and Technology Pabna6600 Bangladesh Department of Electronics & Telecommunication Engineering Faculty of Electrical & Computer Engineering Rajshahi University of Engineering & Technology Rajshahi6204 Bangladesh Department of Computer Science and Engineering Faculty of Engineering and Technology Pabna University of Science and Technology Pabna6600 Bangladesh School of Computer Science and Engineering The University of Aizu / Fukushima Aizuwakamatsu965-8580 Japan School of Computer and Information Technology Ulsan College / Dong-gu Ulsan44610 Korea Republic of

An ultra-wideband (UWB) slotted compact Vivaldi antenna with a microstrip line feed was evaluated for microwave imaging (MI) applications. The recommended FR4 substrate-based Vivaldi antenna is 50×50×1.5 mm3 in size. The proposed compact Vivaldi antenna showed good radiation characteristics and spanned an ultra-wide bandwidth of 10 GHz, ranging from 3.6 to 13.6 GHz, using a microstrip line feed with a radial stub, tapered slots, and resonant cavities. After analyzing the simulation findings, the proposed compact slotted UWB Vivaldi antenna was compared with the basic Vivaldi antenna. The maximum gain and efficiency were 7.35 dB and 82%, respectively. The antenna was simulated in the time domain using the computer simulation technology (CST) microwave studio. The frequency domain solver was also used for cross-validation, and the results were equally good. In conclusion, the proposed compact Vivaldi antenna is a good option for microwave imaging applications. © 2023 The Institute of Electronics and Information Engineers.

关键词： Cavity resonators

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Cultural Heritage Monitoring and Predictive Maintenance using Internet of Things: Assessment and Future Aspects

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Journal of Mobile Multimedia 2024年第6期20卷 1211-1250页

作者： Um-E-habiba Shaikh, Faisal Karim Chowdhry, Bhawani Shankar Department of Computer Science Shaheed Zulfikar Ali Bhutto Institute of Science and Technology Hyderabad Pakistan Telecommunication Engineering Department Mehran University of Engineering and Technology Jamshoro Pakistan Faculty of Electrical Electronics and Computer Engineering Mehran University of Engineering and Technology Jamshoro Pakistan

This study presents a detailed survey on the use of the Internet of Things (IoT) for predictive maintenance and monitoring of cultural heritage, focusing on museums and exhibitions. The integration of IoT in these fields offers significant potential for optimizing maintenance and supervision of heritage resources while also enhancing maintenance strategies. This review examines the application of IoT devices, data analysis, and predictive algorithms in monitoring the state of heritage resources to improve tourist experiences and conserve cultural resources. Key enabling technologies can enable adaptive interactions and engagement with enhanced navigation. Visualization technologies are also common, offering hands-on displays. The study also emphasizes the value of accessibility and interactivity, providing personalization and content sharing features. Several initiatives prioritize the delivery of digital content through mobile applications, internet browsers, and downloadable *** study examines how IoT-enabled predictive maintenance systems can recognize potential hazards, like resource decay or environmental dangers, enabling immediate action. This survey also highlights trends, challenges, and future research in IoT and cultural heritage monitoring. © 2025 River Publishers.

关键词： heritage monitoring IoTs predictive maintenance trends

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Vehicle-Named Data Network Case Study in Traffic Management System 6

Vehicle-Named Data Network Case Study in Traffic Management ...

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6th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2023

作者： Gusrian, Ghivari Faiz Negara, Ridha Muldina Ahdan, Syaiful Telecommunication Engineering School of Electrical Engineering Telkom University Indonesia Universitas Teknokrat Indonesia Faculty of Engineering and Computer Science Lampung Indonesia

ISBN: (纸本)9798350358346

Rapid technological advancements, especially in telecommunications, have increased network demands. According to Cisco's annual report, the global internet user population is expected to grow by 66% by 2023, reflecting the surge of technology in-vehicle networks. In this context, Named Data Networking (NDN) is emerging as a potential solution to enhance the efficiency of data movement in vehicle environments through the Vehicular-NDN (V-NDN) concept. NDN is a content-focused network architecture and is considered the architecture of the future owing to its routing scalability, forwarding speed, network security, and content protection and privacy. Within this paradigm, data requests are content based, supporting data acquisition efficiency in vehicle environments. The V-NDN network is anticipated to realize the future transportation system, enabling vehicles to communicate with each other (V2V) and with infrastructure (V2I). NDNs can potentially reduce delays in data retrieval by allowing consumers to access or share data through communication processes. In this paper, a simulation of data movement was conducted using moving nodes and three forwarding strategies. The simulation involved two schemes: changes in test time and variations in the amount of interest. Overall, multicast VANET exhibited the best performance compared to the other two forwarding strategies. 'Best Route' demonstrated superior performance, outperforming 'Localhop'. © 2023 IEEE.

关键词： Network architecture

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Performance Evaluation of YOLO Models for Automatic Crop and Weed Detection 33

Performance Evaluation of YOLO Models for Automatic Crop and...

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33rd IEEE International Conference on Microelectronics, MIEL 2023

作者： Stankovic, L. Nikolic, T. Talaska, T. Dlugosz, R. University of Nis Faculty of Electronic Engineering Nis Serbia Bydgoszcz University of Science and Technology Faculty of Telecommunication Computer Science and Electrical Engineering Bydgoszcz Poland

ISBN: (纸本)9798350347760

Accurate weed mapping is essential for the implementation of weed management in order to maintain high crop yields and less chemical pollution. This paper focuses on the performance evaluation of YOLO models for automatic crop and weed detection. The research aims to develop weed detection models using one-stage deep learning-based object detectors by transferring pre-trained object detection models to a selected weed dataset. The models are trained on annotated images from a public dataset and evaluated based on detection accuracy. Results demonstrate promising training performance, with approximately 70% mean average precision achieved in 100 training epochs. YOLOv5x exhibits the best performance among the studied models, achieving the highest precision, recall, and mean average precision (0.72, 0.75, and 0.74, respectively). The findings indicate that models with deeper or larger backbone networks tend to provide higher detection accuracy. © 2023 IEEE.

关键词： Crops

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Identification and evaluation of uncertainty contributions to optical current sensor measurement uncertainty 11

Identification and evaluation of uncertainty contributions t...

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11th Brazilian Congress on Metrology, Metrologia 2021

作者： Costa, M.M. Costa, J.C.W.A. Faculty of Electrical and Biomedical Engineering Federal University of Para Belém Brazil Faculty of Electrical and Biomedical Engineering Faculty of Computer and Telecommunication Engineering Federal University of Para Belém Brazil

Optical current sensors can replace traditional current sensor due to their several advantages, as electromagnetic immunity, low dimensions, low cost and others. One of the current main challenges is to develop optical current sensors with good accuracy and stability. This paper presents identification and evaluation of uncertainty contributions to measurement uncertainty evaluation of optical current sensors based on Faraday effect. © Published under licence by IOP Publishing Ltd.

关键词： Uncertainty analysis

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Link Adaptation Performance in the Narrow Band Internet of Things 2nd

Link Adaptation Performance in the Narrow Band Internet of T...

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2nd International Conference on Global Economic Revolutions, ICGER 2023

作者： Daraghma, Raed S. M. Fouchal, Hacene Daraghmi, Yousef-Awwad Ayaida, Marwane Daraghmi, Eman Department of Telecommunication Technology Engineering Faculty of Engineering and Technology Palestine Technical Tulkarm Palestine Department of Mathematics Mechanics and Computer Science University de Reims Reims France

ISBN: (纸本)9783031505171

The aim of the paper was to explore the effectiveness of NB-IOT Narrowband Physical Downlink Shared Channel (NPDSCH), which the 3GPP released in version 13 to serve as a mobile communications feature. When compared to previous cellular technologies, NB-expanded IOT's coverage, data rate, latency, and battery lifetime are its key characteristics. These NB-IOT capabilities make it extremely useful for IOT manufacturing and enable the upcoming technology that may be applied in a variety of situations of deployments, including Agriculture, smart cities, and health, and WSNs. The primary goal of this survey is to evaluate the execution of various NB-IOT grid characteristics with acceptable rates of error in uplink and downlink connections. The effectiveness of the distinct approaches was estimated based on how well they met the requirements of IOT sector. In order to evaluate the various criterion sets and determine which options offer the optimal cost-efficiency trade-offs for building an NB-IOT grid, software simulations were employed. According to the findings, data that is sent in a reduced Transport Block Size (TBS) units experiences less errors than data that is sent in a bigger size units. The outcomes also reveal that, in the propagation channel model, the ER rises as the Doppler frequency rises. The findings also demonstrate that as the subject of modulation and coding scheme (IMCS) increases, the ER rises;finally, the results indicate that an increasing number of antennas is nearly optimal for all parameters. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Internet of things

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IoT Based Water Quality Monitoring System Using Solar Powered and LoRaWAN

IoT Based Water Quality Monitoring System Using Solar Powere...

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2022 International Electrical engineering Congress, iEECON 2022

作者： Savel, Va Rakluea, Paitoon Jangjing, Thinnawat Kumkhet, Boonyarit Mahatthanajatuphat, Chatree Thaiwirot, Wanwisa Electronics and Telecommunication Engineering Faculty of Engineering Pathum Thani Thailand Electrical and Computer Engineering Faculty of Engineering Bangkok Thailand

ISBN: (纸本)9781665402064

This paper proposed IoT based water quality monitoring system using solar power and LoRaWAN. The objective is to study and develop water quality monitoring systems to make it easier for users or those who want to check water quality to see pH, temperature, turbidity, conductivity, and GPS viewpoint in the Cayenne LPP cloud, The water in front of the department of electronics and telecommunication engineering at the Rajamangala University of Technology Thanyaburi will be decided to be a test field. The various water quality data will be wirelessly transferred to the database on the Cayenne LPP cloud. It's also essential to use the greatest wireless connection method. To transport data in the field, the Low-Power Wide-Area Network and the Long-Range WideArea Network will be employed. Moreover, the system can be extended for 36 hours by charging the battery with a solar panel, and the water quality monitoring system error is less than 5%, according to the formula for determining the percentage mistake. © 2022 IEEE.

关键词： Internet of things

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