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Simplifying Structure and Pattern in Complex Social Networks Using Graph Isomorphism 14

Simplifying Structure and Pattern in Complex Social Networks...

引用

14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Arunakumari, B.N. Kshama, S.B. Swasti, S. Sameeksha, B.H. Puri, Sonia Rubini, P.A. Bms Institute of Technology and Management Dept. of Computer Science and Engineering Bengaluru India Bms Institute of Technology and Management Dept. of Information Science and Engineering Bengaluru India

ISBN: (纸本)9798350335095

In recent years, networks have grown in size and complexity, traditional network testing methods have become time-consuming and inefficient. As a result, there is a need for more efficient and reliable network testing methods. One important topic in the field of network testing is graph pattern matching. Network analysis relies on graph pattern matching. The paper discusses the use of graph isomorphism for network testing. This paper also gives an overview of recent advances in isomorphism testing, which determines if two networks are structurally identical despite potential labeling discrepancies between them. The combination of isomorphism and pattern matching in network analysis is used to identify equivalent structures in different networks. This approach is used to identify and compare common patterns in complex network structures, such as those found in social networks. © 2023 IEEE.

关键词： Pattern matching

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Multi-layer network modelling of genomic and transcriptomic data to investigate the response to checkpoint inhibitors in NSCLC

Multi-layer network modelling of genomic and transcriptomic ...

引用

2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Mascolo, Davide Farina, Lorenzo Petti, Manuela Sapienza University of Rome Program in Data Science Rome Italy Sapienza University of Rome Dept. of Computer Control and Management Engineering Rome Italy

ISBN: (纸本)9798350337488

Recent innovations and developments in molecular biology and biotechnology have made it possible to acquire and store large omics datasets. In particular genomics, transcriptomics and the study of their relationship represent the key elements to understand how genotype influences phenotype. In this work we investigate the potential of multi-layer network modeling in integrating genomic and transcriptomic data of 152 advanced non-small cell lung cancer (NSCLC) patients treated with anti-PD-(L)1 therapy. For the transcriptomic layer, we performed differential expression and differential co-expression analyses in order to identify a subset of key genes in differentiating responder patients from non-responders. Adding to the genomic-transcriptomic model other three layers related to immune, myeloid and curated immunotherapy-based literature signatures we obtained a 5-layer Patient Similarity Network. The application of Similarity Network Fusion algorithm revealed a statistically significant stratification of patients (p-value ≤ 0.05) which allows the identification of two clusters characterized by patients responding and not responding to immunotherapy. © 2023 IEEE.

关键词： immunotherapy multi-layer network Network-based omics integration non-small cell lung cancer patient Stratification

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An Analysis of Various Classification Algorithms for Fake News Detection 2

An Analysis of Various Classification Algorithms for Fake Ne...

引用

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

作者： Khare, Sakshi Singh, Pushpa Kumar, Pankaj Dept. of Computer Science and Engineering G. L. Bajaj Institute of Technology & Management Greater Noida India

ISBN: (纸本)9798331530389

With the expansion of social media and advanced stages, the spread of fake news has ended up a noteworthy societal issue. This paper presents a comprehensive outline of machine learning strategies utilized for the detection of fake news. We talk about different approaches such as Natural Language Processing (NLP), unsupervised learning calculations, and machine learning models utilized within the recognizable proof of fake news. We dive into highlight designing, opinion investigation, and organize examination as key components of fake news detection frameworks. Moreover, we look at datasets, assessment measurements, and challenges related with detection of fake news. Through this analysis, we point to supply bits of knowledge into the current state-of-the-art techniques and headings for future investigate in combating fake news dispersal. This paper mainly used K-Nearest Neighbor, Jaccard similarity, LSTM, Decision Tree, and Logistic regression Classifiers for the classification. Main objective of this paper to verify the accuracy of models by performing the pre-processing the data and handle the unbalanced data more appropriately. The results of this papers show comparison of all classifiers with accuracy. Our results shows that KNN achieves 83%, 84% for Logistic Regression, 84% for Decision Tree, 85% for Jaccard Similarity & Random Forest is 85% and 98% for LSTM in our experiment. © 2025 IEEE.

关键词： Adversarial machine learning

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Design and Fabrication of an IoT based Air Purifier using HEPA Filter 11

Design and Fabrication of an IoT based Air Purifier using HE...

引用

11th International Conference on Internet of Everything, Microwave engineering, Communication and Networks, IEMECON 2023

作者： Choudhary, Arpita Saini, Lakhan Ahmad, Afaq Banerjee, Hriday Gazi, Firoj University of Engineering and Management Jaipur Dept. of Computer Science Jaipur India UEM Jaipur Dept. of Computer Science Jaipur India University of Alberta Dept. of Computer Science Edmonton Canada

ISBN: (纸本)9781665475129

Air pollution has become one of the major problems for human health across the globe. Indoor air pollution poses more risk than outdoor air pollution, since the human body is more exposed to the inside. It refers to the contamination of indoor air that causes harmful health problems. To purify the polluted air, the air purifier is a main necessity. In this Internet of Things (IoT) project, we have created an air purifier that purifies the indoor air by passing it through the High Efficiency Particulate Air (HEPA) filter and Ultraviolet light. The microcontroller used is the NodeMCU based on the ESP8266 WiFi enabled chip. Two MQ135 air quality sensors used to monitor the change and calculate the efficiency of the purified air. IoT customization eases the manual work of changing the purifier manually every time by providing a platform that operates on the mobile phone via Wi-Fi where the user can operate it accordingly. It provides an equivalent grade of services at a very moderate cost that is affordable even for the average person and can provide real time analytics. The proposed system is capable for providing hands-on practical operations, which enables more exciting possibilities in IoT based automation systems. © 2023 IEEE.

关键词： Internet of things

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Quantum Inspired Zeroshot Classification For Adverse Drug Reactions Detection From Social Media Reviews

Quantum Inspired Zeroshot Classification For Adverse Drug Re...

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2024 International Conference on Artificial Intelligence and Emerging Technology, Global AI Summit 2024

作者： Dey, Arijit Shrivastava, Jitendra Nath B. P. Poddar Institute of Management and Technology Dept. of Computer Applications WB Kolkata India Invertis University Dept. of Computer Science and Engineering UP Bareilly India

ISBN: (纸本)9798350379716

A deep learning model enhanced with quantum transformer has been introduced in detection of adverse reactions of drugs within the reviews collected from social media written in English language. This proposed model enhanced the human language understanding for detecting adverse reactions of drug. Quantum transformers are used for position embedding and attention purpose. Variational quantum circuit encoded the human language and identify the relevant components of the input reviews as class feature vectors to develop a relationship network for each drug correspond to the condition and review comments on which probability distribution functions applied to detect ADRs found in a medicinal product or not. The correctness of advanced model architecture built on quantum transformer is quite encouraging, and it performs better than other cutting-edge learning models. Achieved an accuracy of 93% with a loss of 0.0393 with this proposed model. Though it is too early to declare that quantum computing has completely replaced. This proposed quantum enhanced transformer helps to show the direction towards quantum enhanced hybrid model design in research. © 2024 IEEE.

关键词： Distribution functions

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Machine Learning Approaches for Predictive Channel State Information in MIMO Systems Using LSTM 2

Machine Learning Approaches for Predictive Channel State Inf...

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2nd International Conference on Advanced Computing and Communication Technologies, ICACCTech 2024

作者： Upadhyay, Deepak Sharma, Amulya Gupta, Mridul Devgan, Divyansh Garg, Shobhit Upadhyay, Abhay Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Electronics and Communication Engineering Dehradun India Graphic Era Deemed to be University Dept. of Management Studies Dehradun India

ISBN: (纸本)9798331519056

In this paper, we analyse machine learning models, including Long Short-Term Memory networks, to predict the CSI and evaluate their impact on adaptive transmission in MIMO systems. To achieve this objective, we use simulation to generate CSI data in a MIMO environment and compare the performance of ML models to traditional methods. Our simulation reveals using our dataset that LSTM models improve the SNR values significantly, which means that their predictions are more accurate. At the same time, these models require greater computational and other resources. In contrast, despite its relative inefficiency in comparison with LSTM, Decision Trees improve the SNR moderately while consuming fewer resources but needing a substantial amount of time. Analysis of the source tries to examine the balance between performance and resource usage may validate the use of ML-based methods, and especially LSTM, to predict the CSI advancedly, but the actual application must take constraints into account. © 2024 IEEE.

关键词： Contrastive Learning

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Experimental Validation of Blockchain Based Triple Branch MRC for Secured Communication in Adverse Fading Conditions

Experimental Validation of Blockchain Based Triple Branch MR...

引用

2024 IEEE Region 10 Symposium, TENSYMP 2024

作者： Upadhyay, Deepak Upadhyay, Abhay Gupta, Mridul Sharma, Kunj Bihari Maindola, Meenakshi Garg, Shobhit Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era Deemed to be University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Electronics and Communication Engineering Dehradun India Graphic Era Deemed to be University Dept. of Management Studies Dehradun India

ISBN: (纸本)9798350364866

The investigation in this study entails integrating blockchain technology with maximal ratio combining in a triple branch configuration for secure communications under multipath fading conditions. The proposed combines blockchain's decentralized and immutable characteristics with MRC's communication outcomes and flaws, which are worsened by the multipath fading channels. To evaluate this, the team carried out various empirical tests with the key findings being the Signal-to-Noise Ratio performance. Since the blockchain integrated system is anticipated to exhibit a higher SNR, our results showed a substantial increase in SNR. This confirms the robust and secure communication capabilities of the integrated solution under study. Therefore, the researchers demonstrate how blockchain can greatly enhance security as well as the quality of the communication, presenting a better solution in challenging data transmission conditions. This study establishes the foundation for further research on blockchain technology applications in the communication field. © 2024 IEEE.

关键词： Blockchain

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Implementation of Dynamic Spectrum Access Techniques in Cognitive Radio Networks under Generalized Fading Conditions 2

Implementation of Dynamic Spectrum Access Techniques in Cogn...

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2nd International Conference on Advanced Computing and Communication Technologies, ICACCTech 2024

作者： Upadhyay, Deepak Sharma, Kunj Bihari Gupta, Mridul Garg, Shobhit Sharma, Amulya Devgan, Divyansh Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Electronics and Communication Engineering Dehradun India Graphic Era Deemed to be University Dept. of Management Studies Dehradun India

ISBN: (纸本)9798331519056

This paper is organized as follows: Section II provides a background on our research work based on DSA in CRNs using CR under different fading conditions. c) Performance: We also study how effective adaptive algorithms along with the machine learning can prove in achieving higher spectrum sensing accuracy and decision making on run time. By conducting simulations and extensive performance evaluation, we show that the traditional solutions fall short when compared to our AI-based methodology in terms of accuracy especially under harsh fading conditions. Finally, sensitivity analysis highlights the control parameters that need to be submitted to further optimization for better system performance. With all above analysis, our results indicate that DSA can alleviate spectrum underutilization problem and enhance communication reliability in CRNs. Thus, with proper adaptation strategies and machine learning algorithms, the DSA systems provide an appealing opportunity to meet the continuously increasing requirements of bandwidth-consuming applications in current days wireless networks. The results of this research are helpful in providing effective value input to Advances in the understanding and design of robust, efficient spectrum management approaches for dynamic and diverse wireless settings. © 2024 IEEE.

关键词： Sensitivity analysis

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Real World Deployment of Dual Branch MRC Enhanced by Adaptive Algorithms LMS and RLS in 5G Networks to Improve SNR and QoS 4

Real World Deployment of Dual Branch MRC Enhanced by Adaptiv...

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4th International Conference on Intelligent Technologies, CONIT 2024

作者： Upadhyay, Deepak Upadhyay, Abhay Gupta, Mridul Sharma, Kunj Bihari Maindola, Meenakshi Garg, Shobhit Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era Deemed to Be University Dept. of Electronics and Communication Engineering Dehradun India Graphic Era Deemed to Be University Dept. of Computer Science and Engineering Dehradun India Graphic Era Deemed to Be University Dept. of Management Studies Dehradun India

ISBN: (纸本)9798350349900

This research is aimed at understanding the performance benefits of the use of adaptive algorithms in dual-branch MRC systems as a solution for developing 5G networks. We developed controlled simulations to determine the performance influences of the algorithms in SNR, QoS, BER, and throughput under different network conditions. Our results indicate that the algorithms significantly reduce BER safe power divergence that improves the reliability and performance of the communication platform. The adaptive systems in addition reveal a significantly impressive ability to maintain a higher rate of throughput that is necessary in the current networks due to the increasing volume of data consumed by different users. In conclusion, therefore, this research has showed that adaptive MRC techniques might be a highly-viable option toward enabling the development of 5G technology, provided a suitable method for boosting performance during uncertain communications. © 2024 IEEE.

关键词： 5G mobile communication systems

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Optimizing Urban Mobility: A Comprehensive Framework for Smart Parking Systems Integration Using IoT and Sensor Technologies 7

Optimizing Urban Mobility: A Comprehensive Framework for Sma...

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7th International Conference on Electronics, Materials engineering and Nano-Technology, IEMENTech 2023

作者： Sen, Sayak Mukherjee, Unmesh Banerjee, Subhabrata Biswas, Aparna Ray, Sutapa Chowdhuri, Sayantani Institute of Engineering & Management Dept. of Electronics and Communication Engineering Kolkata India Institute of Engineering & Management Department of Computer Science & Engineering Kolkata India

ISBN: (纸本)9798350305517

Smart Parking Systems have gained prominence as a pivotal component of urban infrastructure, addressing the persistent challenge of limited parking spaces in burgeoning cities. This abstract delves into the evolution and functionality of Smart Parking Systems. Leveraging technology such as microcontroller, sensors, IoT, and data analytics, these systems optimize parking space utilization and enhance the overall parking experience. By providing real-time information to drivers, reducing traffic congestion, and minimizing environmental impact, they contribute to more sustainable urban development. This paper explores the various components and benefits of smart parking systems, showcasing their potential to revolutionize urban mobility and improve quality of life. As cities continue to grow, smart parking systems offer a promising solution to the parking conundrum, fostering a smarter, more efficient, and eco-friendly urban environment. © 2023 IEEE.

关键词： Microcontrollers

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