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2025 International Conference on Intelligent Control, Computing and Communications, IC3 2025

作者： Himanshu Singh, Pushpendra Singh, Vinai Kumar Srm Institute of Science and Technology Department of Computer Science and Engineering Delhi-NCR Campus Ghaziabad201204 India Gl Bajaj Group of Institutions Department of Applied Science and Humanities Mathura India

ISBN: (纸本)9798331527495

Today's rapidly changing world has led travelers to seek customized experiences that align with their individual preferences and interests. With the continuous evolution of the digital realm, the expectations of users interacting with online platforms for travel planning and reservations are also evolving. To cater to the demand for personalized recommendations and enhance the user experience, we propose the incorporation of a Content-Based Filtering algorithm into our tour website. This algorithm, in conjunction with a recommender system for Travel and tourism management, enables users to book tours nationwide through a single dynamic website that provides comprehensive information on various destinations and tour specifics. Developed with PHP as the front end and Microsoft SQL Server 2008 as the back end, the website is compatible with all browsers. Programming languages such as HTML, CSS, Bootstrap, and PHP were utilized in its creation. Administrators have the capability to add tour packages from selected travel agents and hotels by establishing a tour page. Subsequently, users can register and reserve each package, with confirmation managed by the admin in the booking management section. Users can easily view their confirmations in the 'My Booking' page, making this platform user-friendly for all travelers seeking seamless bookings and detailed information. Furthermore, alongside implementing a Content-Based Filtering algorithm for personalized tour recommendations, we aim to promote the availability of accommo-dations in local rural areas. This endeavor not only presents travelers with cost-effective lodging choices but also contributes to the economic growth of the communities they visit. © 2025 IEEE.

关键词： Recommender systems

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Joint Radar-Communication Systems by Optimizing Radar Performance and Quality of Service for Communication Users

IEEE Transactions on Radar Systems

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IEEE Transactions on Radar Systems 2024年 2卷 778-790页

作者： Tsinos, Christos G. Arora, Aakash Tsiftsis, Theodoros A. National and Kapodistrian University of Athens Department of Digital Industry Technologies Evripus Campus Euboea 34400 Greece University of Twente Radio Systems Group Faculty of Electrical Engineering Mathematics and Computer Science AE Enschede7500 Netherlands Indian Institute of Technology Delhi Centre for Applied Research in Electronics New Delhi110016 India University of Thessaly Department of Informatics and Telecommunications Lamia35100 Greece Jinan University Zhuhai Campus School of Intelligent Systems Science and Engineering Zhuhai519070 China

In this article, the problem of linear precoding and radar receive beamforming design for joint radar-communication (JRC) systems is studied. A multiple antenna base station (BS) that serves multiple single-antenna user terminals on the downlink is assumed. Furthermore, the BS employs a simultaneous radar function in the form of point-like target detection from the reflected return signals in a signal-dependent interference environment. In this work, we jointly design the JRC linear precoder and the radar receive beamformer, thus aiming to optimize the performance of the radar part while maintaining a desired quality of service (QoS) for the communication one subject to a total transmit power constraint. To that end, we formulate a challenging fractional nonconvex optimization problem via which the optimal precoder and radar receive beamformer are derived. Then, we develop algorithmic solutions based on the majorization-minimization (MM) principle and the semidefinite relaxation (SDR) methodology for the formulated optimization problem. The performance of both the proposed solutions is examined and compared to the one of a system that supports only the radar functionality via numerical results. © 2023 IEEE.

关键词： Signal to noise ratio

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InDaMul: Incentivized Data Mules for Opportunistic Networking Through Smart Contracts and Decentralized Systems

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Distributed Ledger Technologies: Research and Practice 2023年第2期2卷 1-28页

作者： Mirko Zichichi Luca Serena Stefano Ferretti Gabriele D’angelo Ontology Engineering Group Universidad Politécnica de Madrid Department of Computer Science and Engineering University of Bologna Department of Pure and Applied Sciences University of Urbino “Carlo Bo”

The rise of Internet-of-Things enables the development of smart applications devoted to improving the quality of life in urban and rural areas, thus fostering the creation of smart territories. However, some dislocated areas are underprivileged in providing such services due to the lack, inefficiency, or excessive cost of Internet access. Opportunistic networking techniques might aid in surmounting these problems. In this article, we propose a framework that relies on an untrusted Data Mule to carry data from an offline source to an online destination. In particular, we present a framework that enables the communication between different actors and a reward mechanism using Distributed Ledger Technologies, Smart Contracts, and Decentralized File Storage. The protocol involved in bringing a Client’s message online and getting back a response is thoroughly explained in all its steps and then discussed on the most important trust and security issues. Finally, we evaluate such a protocol and the whole framework through a series of communication latency tests, an analysis of the Smart Contract usage, and simulations in which buses act as Data Mules. Our results suggest the feasibility of our proposal in a smart territory scenario.

关键词： Distributed ledger technology mobile networking smart contracts state channels

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System Approximation Using Pole Spectrum Analysis (PSA) and Modified Cauer Continued Fraction Method

System Approximation Using Pole Spectrum Analysis (PSA) and ...

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2025 International Conference on Intelligent Control, Computing and Communications, IC3 2025

作者： Sengar, R.S. Awasthy, Neeta Singh, Bholey Singh, Ashish Pratap Kumar, Satender Kumar, Aadesh Gl Bajaj Group of Institutions Department of Electrical & Electronics Engineering Mathura India Gl Bajaj Group of Institutions Department of Computer Science and Engineering Mathura India Gl Bajaj Group of Institutions Department of Applied Science and Humanities Mathura India Gl Bajaj Group of Institutions Department of Electronics and Communications Engineering Mathura India Gl Bajaj Group of Institutions Department of Mechanical Engineering Mathura India

ISBN: (纸本)9798331527495

The manuscript presents an advanced approach for reducing large-scale Linear Time-Invariant (LTI) dynamic systems, utilizing a combined framework that integrates Dominant Pole Retention (DPR), Pole Spectrum Analysis (PSA), and Modified Cauer Continued Fraction (MCCF) method. The denominator dynamics of the reduced-order model are extracted via the PSA integrated with a pole dominance technique, while the numerator dynamics are obtained through MCCF method. Notably, for higher-order stable systems, the approach significantly guarantees the stability of the simplified system. To substantiate the efficacy and fidelity of the proposed technique, a set of numerical exemplars sourced from literature has been rigorously analyzed. Comparative evaluations have been conducted, leveraging performance indices and response congruence metrics to benchmark the alignment between the original and simplified system responses, thereby affirming the robustness and precision of the proposed reduction method. © 2025 IEEE.

关键词： Lyapunov methods

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An Abstractive Summarization Technique with Variable Length Keywords as per Document Diversity

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computers, Materials & Continua 2021年第3期66卷 2409-2423页

作者： Muhammad Yahya Saeed Muhammad Awais Muhammad Younas Muhammad Arif Shah Atif Khan M.Irfan Uddin Marwan Mahmoud Department of Software Engineering Government College UniversityFaisalabadFaisalabad38000Pakistan Department of IT and Computer Science Pak-Austria Fachhochschule Institute of Applied Sciences and TechnologyHaripurPakistan Department of Computer Science Islamia College PeshawarPeshawarPakistan Institute of Computing Kohat University of Science and TechnologyKohatPakistan Faculty of Applied Studies King Abdulaziz UniversityJeddahSaudi Arabia

Text Summarization is an essential area in text mining,which has procedures for text *** natural language processing,text summarization maps the documents to a representative set of descriptive ***,the objective of text extraction is to attain reduced expressive contents from the text *** summarization has two main areas such as abstractive,and extractive *** text summarization has further two approaches,in which the first approach applies the sentence score algorithm,and the second approach follows the word embedding *** such text extractions have limitations in providing the basic theme of the underlying *** this paper,we have employed text summarization by TF-IDF with PageRank keywords,sentence score algorithm,and Word2Vec word *** study compared these forms of the text summarizations with the actual text,by calculating cosine ***,TF-IDF based PageRank keywords are extracted from the other two extractive *** intersection over these three types of TD-IDF keywords to generate the more representative set of keywords for each text document is *** technique generates variable-length keywords as per document diversity instead of selecting fixedlength keywords for each *** form of abstractive summarization improves metadata similarity to the original text compared to all other forms of summarized *** also solves the issue of deciding the number of representative keywords for a specific text *** evaluate the technique,the study used a sample of more than eighteen hundred text *** abstractive summarization follows the principles of deep learning to create uniform similarity of extracted words with actual text and all other forms of text *** proposed technique provides a stable measure of similarity as compared to existing forms of text summarization.

关键词： Metadata page rank sentence score word2vec cosine similarity This

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MKGL: mastery of a three-word language 24

MKGL: mastery of a three-word language

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Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Lingbing Guo Zhongpu Bo Zhuo Chen Yichi Zhang Jiaoyan Chen Yarong Lan Mengshu Sun Zhiqiang Zhang Yangyifei Luo Qian Li Qiang Zhang Wen Zhang Huajun Chen College of Computer Science and Technology Zhejiang University and ZJU-Ant Group Joint Lab of Knowledge Graph Ant Group Department of Computer Science The University of Manchester School of Computer Science and Engineering Beihang University School of Computer Science Beijing University of Posts and Telecommunications School of Software Technology Zhejiang University and ZJU-Ant Group Joint Lab of Knowledge Graph

ISBN: (纸本)9798331314385

Large language models (LLMs) have significantly advanced performance across a spectrum of natural language processing (NLP) tasks. Yet, their application to knowledge graphs (KGs), which describe facts in the form of triplets and allow minimal hallucinations, remains an underexplored frontier. In this paper, we investigate the integration of LLMs with KGs by introducing a specialized KG Language (KGL), where a sentence precisely consists of an entity noun, a relation verb, and ends with another entity noun. Despite KGL's unfamiliar vocabulary to the LLM, we facilitate its learning through a tailored dictionary and illustrative sentences, and enhance context understanding via real-time KG context retrieval and KGL token embedding augmentation. Our results reveal that LLMs can achieve fluency in KGL, drastically reducing errors compared to conventional KG embedding methods on KG completion. Furthermore, our enhanced LLM shows exceptional competence in generating accurate three-word sentences from an initial entity and interpreting new unseen terms out of KGs.

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Encryption Algorithm for Securing Non-Disclosure Agreements in Outsourcing Offshore software Maintenance

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computers, Materials & Continua 2022年第11期73卷 3827-3845页

作者： Atif Ikram Masita Abdul Jalil Amir Bin Ngah Nadeem Iqbal Nazri Kama Azri Azmi Ahmad Salman Khan Yasir Mahmood Assad Alzayed Faculty of Ocean Engineering Technology and Informatics University Malaysia TerengganuKuala TerengganuMalaysia Department of Computer Science&Information Technology Faculty of Information TechnologyThe University of LahoreLahore54000Pakistan Department of Software Engineering Faculty of Information TechnologyThe University of LahoreLahore54000Pakistan Advanced Informatics Department Razak Faculty of Technology and InformaticsUniversiti Teknologi Malaysia54100Kuala LumpurMalaysia Computer Science and Information Systems Department College of Business Studies Public Authority for Applied Education and Training(PAAET)AdailiyaKuwait

Properly created and securely communicated,non-disclosure agreement(NDA)can resolve most of the common disputes related to outsourcing of offshore software maintenance(OSMO).Occasionally,these NDAs are in the form of *** the work is done offshore,these agreements or images must be shared through the Internet or stored over the *** breach of privacy,on the other hand,is a potential threat for the image owners as both the Internet and cloud servers are not void of *** article proposes a novel algorithm for securing the NDAs in the form of *** an agreement is signed between the two parties,it will be encrypted before sending to the cloud server or travelling through the public network,the *** the image is input to the algorithm,its pixels would be scrambled through the set of randomly generated rectangles for an arbitrary amount of *** confusion effects have been realized through an XOR operation between the confused image,and chaotic ***,5D multi-wing hyperchaotic system has been employed to spawn the chaotic vectors due to good properties of chaoticity it *** machine experimentation and the security analysis through a comprehensive set of validation metric vividly demonstrate the robustness,defiance to the multifarious threats and the prospects for some real-world application of the proposed encryption algorithm for the NDA images.

关键词： Non-disclosure agreement encryption decryption secret key chaoticmap confusion diffusion

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Federated transfer learning for distributed drought stage prediction

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Discover Artificial Intelligence 2025年第1期5卷 1-13页

作者： Raza, Muhammad Owais Umar, Aqsa Rasheed, Jawad Asuroglu, Tunc Alsubai, Shtwai Department of Computer Engineering Istanbul Sabahattin Zaim University Istanbul34303 Turkey Department of Computer Science Sindh Madressatul Islam University Karachi74000 Pakistan Department of Software Engineering Istanbul Nisantasi University Istanbul34398 Turkey Applied Science Research Center Applied Science Private University Amman Jordan Faculty of Medicine and Health Technology Tampere University Tampere33720 Finland VTT Technical Research Centre of Finland Tampere33720 Finland Department of Computer Science College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz University Al-Kharj11942 Saudi Arabia

Due to the uncertain nature of drought, it is one of the most menacing natural disasters. Drought modeling (Prediction, Detection, Forecasting, and Stage Prediction) is very essential for efficient policy making. But one of the key problems with drought modeling is the limited availability of centralized datasets. To address this problem, we are a novel proposing federated learning based transfer learning models for the prediction of drought stages. In this study, satellite image dataset was collected from the Tharparkar district (prone to drought) of Pakistan. We trained the dataset using traditional and federated learning approaches, comparing centralized ML models, pre-trained models, and their respective federated learning models (FL-ResNet, FL-DenseNet, FL-MobileNet). The development of these models is the novel aspect of the study specifically for the use case of drought stage prediction. Based on the final evaluation, FL-MobileNet achieved 82% precision while baseline MobileNet scored 68%. The results show the effectiveness of novelty (federated learning), that our proposed framework improves the performance of the drought stage classification task. © The Author(s) 2025.

关键词： Federated learning

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Efficient Privacy-Preserving ML for IoT: Cluster-Based Split Federated Learning Scheme for Non-IID Data 7

Efficient Privacy-Preserving ML for IoT: Cluster-Based Split...

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7th Cyber Security in Networking Conference, CSNet 2023

作者： Arafeh, Mohamad Wazzeh, Mohamad Ould-Slimane, Hakima Talhi, Chamseddine Mourad, Azzam Otrok, Hadi Department of Software and It Engineering Montreal Canada Department of Mathematics and Computer Science Canada New York University Division of Science Abu Dhabi United Arab Emirates Cyber Security Systems and Applied Ai Research Center Lebanese American University Department of Csm Beirut Lebanon Khalifa University Department of Eecs Abu Dhabi United Arab Emirates

ISBN: (纸本)9798350342871

This paper proposes a scheme addressing the challenges of integrating privacy-preserving distributed machine learning in the Internet of Things (IoT) context while improving the efficiency of the learning process and accelerating the convergence of the model. Specifically, it addresses the presence of non-independent and identically distributed (Non-IID) data and device heterogeneity, which occurs during parallel training and are common characteristics of IoT environments. In this context, SplitFed is a privacy-preserving technique that combines Federated Learning (FL) and Split Learning (SL) to enable fast and privacy-preserving model training on IoT devices. Through parallelism, FL allows fast and parallel model training. Furthermore, SL enables weak devices to train models through model splitting. However, SplitFed suffers from the increasing convergence time due to the FL parallelism introducing Non-IID and stragglers issues. In this paper, we aim to address the aforementioned problems by proposing a clustering parallelization scheme. As such, similar clients are combined based on their weight divergence and considered a single FL unit addressing the Non-IID problem. Moreover, to improve time efficiency and overcome the stragglers' presence, we offer a second clustering stage that separates clients by efficiency and uses FedAsync for model aggregation. © 2023 IEEE.

关键词： Internet of things

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A Cascaded Design of Best Features Selection for Fruit Diseases Recognition

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computers, Materials & Continua 2022年第1期70卷 1491-1507页

作者： Faiz Ali Shah Muhammad Attique Khan Muhammad Sharif Usman Tariq Aimal Khan Seifedine Kadry Orawit Thinnukool Department of Computer Science COMSATS University IslamabadWah Campus47080Pakistan Department of Computer Science HITEC University TaxilaTaxila47040Pakistan College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-KhrajSaudi Arabia National University of Science and Technology Islamabad IslamabadPakistan Faculty of Applied Computing and Technology Noroff University CollegeKristiansandNorway Research Group of Embedded Systems and Mobile Application in Health Science College of ArtsMedia and TechnologyChiang Mai UniversityChiang Mai50200Thailand

Fruit diseases seriously affect the production of the agricultural sector,which builds financial pressure on the country’s *** manual inspection of fruit diseases is a chaotic process that is both time and cost-consuming since it involves an accurate manual inspection by an ***,it is essential that an automated computerised approach is developed to recognise fruit diseases based on leaf *** to the literature,many automated methods have been developed for the recognition of fruit diseases at the early ***,these techniques still face some challenges,such as the similar symptoms of different fruit diseases and the selection of irrelevant *** processing and deep learning techniques have been extremely successful in the last decade,but there is still room for improvement due to these ***,we propose a novel computerised approach in this work using deep learning and featuring an ant colony optimisation(ACO)based *** proposed method consists of four fundamental steps:data augmentation to solve the imbalanced dataset,fine-tuned pretrained deep learning models(NasNetMobile andMobileNet-V2),the fusion of extracted deep features using matrix length,and finally,a selection of the best features using a hybrid ACO and a Neighbourhood Component Analysis(NCA).The best-selected features were eventually passed to many classifiers for final *** experimental process involved an augmented dataset and achieved an average accuracy of 99.7%.Comparison with existing techniques showed that the proposed method was effective.

关键词： Fruits diseases data augmentation deep learning features fusion feature selection

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