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

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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A Comprehensive Evaluation Process by Analytical Hierarchical Process for Identification of Potential Groundwater Zones 2

A Comprehensive Evaluation Process by Analytical Hierarchica...

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2nd DMIHER International Conference on Artificial Intelligence in Healthcare, Education and Industry, IDICAIEI 2024

作者： Gudadhe, Amit Anil Reddy, K.T.V. Faculty of Engineering and Technology Computer Science and Design Department Wardha India Faculty of Engineering and Technology Wardha India

ISBN: (纸本)9798331528713

For social and economic development of any region, groundwater plays a very vital role. Surface water infiltration depends on various parameters of the earth. The parameters includes Slope, Geology, Soil Type, Land Use/Land Cover, Rainfall, Drainage Density based on the study area under consideration. There exists various techniques for recognizing of groundwater probable regions. This paper focuses specifically on the recognizing of the subsurface water probable regions by Analytical Hierarchy Process. The steps involved in the process are discussed in detailed and shows how the potential zone identification is based on value of weights evaluated. © 2024 IEEE.

关键词： Land use

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Application of VGIS Digital Twin Platform for Enhanced Oilfield Disaster Management and Environmental Protection

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Informatica (Slovenia) 2024年第14期48卷 27-42页

作者： Alabbasi, Awab Aljabery, Maalim A. Bölük, Pınar Sarısaray Faculty of Engineering and Natural Sciences Electrical and Computer Engineering Dept. Bahcesehir University Istanbul34353 Turkey Faculty of Computer Science and Information Technology Computer Science Dept. University of Basrah Basrah61004 Iraq Faculty of Engineering and Natural Sciences Software Engineering Dept. Bahçeşehir University Istanbul34353 Turkey

VGIS (Virtual Geographic Information System) Platform is a unified oilfield operations management platform based on MaaS (Management as a Service) that integrates advanced technologies such as AIoT (Artificial Intelligence & Internet of Things), GIS (Geographic Information System), Digital Twin, and AR (Augmented Reality)/ VR (Virtual Reality). The VGIS platform connects, collects, integrates, analyses, and acts on disparate data sources to provide the oilfield with a centralized view to help make informed decisions fast, bring operational visibility across all assets to improve safety and operational efficiency, reduce costs and improve margins, provide comprehensive analytics and decision support, increase business agility, and reduce management complexity. This is a case study of the application of the VGIS platform Majnoon oilfield, Basrah, Iraq. VGIS digital transformation, production process, and KPIs (Key performance indicators) are highly managed taking oilfield management to a higher level globally, in this study, the objective is to address and resolve the issue of high costs associated with using cloud services by utilising a local Data Center (a large group of networked computer servers typically used by organizations for the remote storage, processing, or distribution of large amounts of data). This approach involves directly uploading 3D maps to ensure faster service on the intranet, eliminating the need to pay for cloud *** aims providing a platform for researching and implementing monitoring and controlling processes in a more convenient and remote manner. The vGIS platform has emerged as a crucial instrument in the realm of disaster response and crisis management. This technology enables responders to rapidly evaluate, analyse, and respond to crucial information in real-time. This research examined the application of vGIS technology in disaster response and analyse the potential advantages and obstacles associated with its utilisation. © 2

关键词： Information management

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Quantum Coordination Rates in Multi-User Networks

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IEEE Transactions on Information Theory 2025年第6期71卷 4428-4453页

作者： Natur, Husein Pereg, Uzi Technion-Israel Institute of Technology Faculty of Electrical and Computer Engineering Helen Diller Quantum Center Haifa3200003 Israel

Quantum coordination is considered in networks with classical and quantum links. We begin with networks with classical links, and characterize the generation of separable and classical-quantum correlations in three primary models: 1) a two-node network with limited common randomness (CR), 2) a no-communication network, and 3) a broadcast network, which consists of a single sender and two receivers. We establish the optimal tradeoff between the classical communication and CR rates in each setting, thus characterizing the minimal resources for simulating classical-quantum correlations. Next, we consider coordination in networks with quantum links. We study the following models: 1) a cascade network with limited entanglement, 2) a broadcast network, and 3) a multiple-access network with two senders and a single receiver. We establish the optimal tradeoff between quantum communication and entanglement rates in each setting, characterizing the minimal resources for entanglement coordination. The examples demonstrate that coordination of entanglement and coordination of separable correlations behave differently. At last, we show the implications of our results on nonlocal games with quantum strategies. © 1963-2012 IEEE.

关键词： Quantum communication

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Revolutionizing Diagnostic Precision: The Role of Neural Networks in Advancing Medical Imaging 1

Revolutionizing Diagnostic Precision: The Role of Neural Net...

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1st International Conference on Healthcare Innovations, Software and engineering Technologies, HISET 2024

作者： Raymond, David Goureshettiwar, Palash Kumar, Praveen Faculty of Engineering and Technology Depertment of Computer Science and Medical Engineering Nagpur India Faculty of Engineering and Technology Department of Computer Science and Medical Engineering Name of Organization Nagpur India

ISBN: (纸本)9798350360707

The incorporation of neural networks into medical imaging has recently resulted in significant modifications to diagnosis. This article looks at the job of brain networks in clinical picture handling, featuring their enhancements in exactness, speed and consistency across different clinical spaces. The utilization of profound learning models, for example, CNN and RNN has become significant in picture examination, illness recognizable proof, and treatment arranging. The exhaustive review investigates the elements of brain network processes and their applications in different imaging modalities like radiology, pathology and neuroimaging. Also, it tends to the difficulties, development possibilities, and moral contemplations related with conveying brain networks in true medical services conditions. As brain networks keep on changing clinical pictures, this examination fills in as a complete aide, showing their significant effect on further developing diagnostics and reconsidering clinical imaging © 2024 IEEE.

关键词： Convolutional neural networks

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A review on spreading and Forensics Analysis of Windows-Based ransomware

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Annals of Data Science 2024年第5期11卷 1503-1524页

作者： Chayal, Narendrakumar Mangilal Saxena, Ankur Khan, Rijwan Department of Computer Science and Technology Faculty of Engineering and Technology Department of Computer Engineering Sankalchand Patel University Visnagar India Department of Computer Science Indus Institute of Information and Communication Technology Dean-ICT & ampDirector-IIICT Indus University Gujarat Ahmedabad India Department of Computer Science and Engineering ABES Institute of Technology Ghaziabad Affiliated to AKTU Lucknow India

Ransomware is one of the most advanced malware which uses high computer resources and services to encrypt system data once it infects a system and causes large financial data losses to the organization and individuals. There are certain automatic ransomware detection and analysis strategies available nowadays. File system analysis reveals some essential patterns and artifacts that can be very useful to understand its behavior spreading mechanism, taxonomy for malware forensics experts. Current trend explores Ransomware as a service (RaaS) and Malware as a service (MaaS) on Darknet. This paper reveals a theory of digital forensic methodology to identify the spreading/infection mechanism and attack path, the cryptographic methodology, windows services, process, APIs, persistence mechanism, and system lockdown strategies and malware analysis methodology. This review could be helpful to learn and understand malware forensic analysis for threat researchers, students, cyber experts, etc. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022.

关键词： Malware

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Deep Learning for Sentiment Analysis 4

Deep Learning for Sentiment Analysis

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

作者： Rokade, Gayatri Ughade, Radhe Gaurshettiwar, Palash Faculty of Engineering and Technology Computer Science and Medical Engineering Maharashtra Wardha India

ISBN: (纸本)9798331523923

This paper represents that one of the critical subfields of NLP, SA applies DL techniques to analyze the feelings expressed in text, image, and voice context. As new technology of Web 2.0 emerges, there are many opportunities and challenges because of the large amount of content generated from blogs, forums, social networking sites, etc. This work explores the development of DL-based SA and notes that enhancements have been made primarily on the document, sentence, phrase, as well as aspect levels. Ambiguity, sarcasm, and negation are also discussed, as well as specific domain and multimodal aspects. The work shows that it might be possible to transition to semi-supervised, and unsupervised learning to overcome real-world data limitations and offers emergent prospects in the real-time analysis, domain fine-tuning, and data enhancement. The inspiration for future research is offered by the multimodal sentiment analysis and the enhancement of the DL architectures. © 2025 IEEE.

关键词： Contrastive Learning

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Advising career choice through tweeter data

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Multimedia Tools and Applications 2024年 1-17页

作者： Erbay, Hasan Yurttakal, Ahmet Haşim Dağıstanlı, Ömer Kör, Hakan Computer Engineering Department Engineering Faculty Ostim Technical University Ankara06374 Turkey Computer Engineering Department Engineering Faculty Afyon Kocatepe University Afyon03204 Turkey Department of Computer Technology Bogazliyan Vocational School Yozgat Bozok University Yozgat610101 Turkey Department of Computer Engineering Engineering Faculty Hitit University Çorum610101 Turkey

Career is important in everyone’s life. If sleep is factored out, work is almost half of one’s life. So if people’s job is something they hate or are indifferent to, that means that about half of their lives they either hate or are indifferent. Which causes different unhealthy habits such as eating too much, alcohol and drug usage, watching television, having depression, or being quick to anger. However, people having the right career that is compatible with who they are will make them energetic, positive and will also make their lives better outside of work. On the other hand, the job market is undergoing tremendous change as technology rapidly transforms every industry. In a world where everything is constantly evolving, choosing the right career can be a real challenge, and career indecision arises when someone is faced with difficulties in making a career decision, making the challenge more demanding. There is a wealth of career choice software available, each rely on a corresponding career theory such as RAISEC. These software apply the prepared questionnaires to individuals for appropriate careers. Questionnaires measure individuals’ interests, talents and skills, values, personality, and education and training, which are highly influenced by social factors, prior experiences, self-perceptions, intrinsic or personal utility values, or good salaries. Nowadays, information technologies affect almost every aspect of our daily lives, change the perspectives of individuals on many concepts, and make the world a small village that kind of facilitates communication. Online Social Networks(OSNs) bring people in different professions together to exchange thoughts, they use OSNs to express themselves, discuss interests, connect with friends, and advance their careers. Also, OSNs connect individuals with similar interests. Herein, motivated by RAISEC, it was examined whether OSNs could be utilized to help individuals make career choices. Tweets from four individuals with

关键词： Tweets

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Meteorological Prediction Using Cloud's Images 12

Meteorological Prediction Using Cloud's Images

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12th International Electrical engineering Congress, iEECON 2024

作者： Ongkittikul, Surachai Jundang, Nattapong Panyokaew, Thanayut Department Of Computer Engineering Mahanakorn Institute Of Innovation Faculty Of Engineering And Technology Mahanakorn University Of Technology Bangkok Thailand Mahanakorn University Of Technology Engineering Program In Computer Engineering And Artificial Intelligence Faculty Of Engineering And Technology Bangkok Thailand

ISBN: (纸本)9798350383591

This paper uses YOLO deep learning to create a predict system for Meteorological Service for Air Navigation with a total of 5 types of forecast results: BKN, CAVOK, FEW, OVER and SCT. Indicative information for evaluating the image is observing the nature of the clouds arranged together and comparing them to quantities in the sky using the unit of measurement 'okta', which is divided into 8 parts of the image. Therefore, the nature of using deep learning in the article is to teach deep learning to recognize various image characteristics both during the day and at night in order to use the results of the forecast to inform the weather conditions in the sky. The process in this article consists of 3 steps: The first step is to train the data with images with different characteristics from the 5 data types. The next step is to test the accuracy of the weights generated from the training and training steps. The final step is to use water values to create a decision-making system for users. From the experiment, private dataset in this paper, more than 2500 images were used to participate in the experiment. The results of the experiment found that the average results of precision, recall, mAP50, and mAP50-95 could be measured at 84.7%, 92.1%, 95.7%, and 95.3%, respectively. © 2024 IEEE.

关键词： Air navigation

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Robust steganographic approach using generative adversarial network and compressive autoencoder

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Multimedia Tools and Applications 2024年 1-38页

作者： Qasaimeh, Malik Qtaish, Alaa Abu Aljawarneh, Shadi Department of Computer Information Systems Faculty of Computer and Information Technology Jordan University of Science and Technology Irbid Jordan Department of Software Engineering co-joint with the Department of Cyber Security Faculty of Computer and Information Technology Jordan University of Science and Technology Irbid Jordan

Nowadays, social media applications and websites have become a crucial part of people’s lives;for sharing their moments, contacting their families and friends, or even for their jobs. However, the fact that these valuable data are transferred via the Internet and open channels, which are vulnerable to attacks and espionage, requires using defense methods to improve the security of data transmission. Recently, the progress of Deep Learning (DL) inspired researchers to use it with security methods such as steganography, the art of hiding secret data in unrelated content. DL and steganography combined enhanced the hiding properties, especially in the Coverless Image Steganography (CIS) methods. In this paper, we propose a Compressive Coverless Image Steganography (CCIS) model, which is a generated-based CIS, to improve the capacity and robustness of Steganography. This model uses the compressive autoencoder to compress the message, thus increasing the capacity, and uses the Generative Adversarial Network (GAN) to generate a stego image from the compressed vector, thus enhancing concealment ability, besides using a regression model and optimization method to extract the data. Another version was designed to enable sending binary messages by replacing the compressive autoencoder network with a robust mapping rule. Experiments show that the proposed model could improve the characteristics of Steganography. Furthermore, the proposed model could extract binary messages with 256 bits from attacked stego images with 99% recovery accuracy. Thus, capacity and robustness were enhanced using our model with both images and text as secret messages. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Generative adversarial networks

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