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Evaluating the Impact of Different Features on the Efficiency of Emotion Recognition Algorithms in Text

Evaluating the Impact of Different Features on the Efficienc...

Artificial Intelligence and Machine Learning applications Theme: Healthcare and Internet of Things (AIMLA), International Conference on

作者： Sunil Sharma G. Ezhilarasan Rajkumari Ghosh Department of Computer Science & Application Vivekananda Global University Jaipur India Department of Electrical and Electronics Engineering School of Engineering and Technology AIN (Deemed to be University) Bangalore Karnataka India Department of English ARKA JAIN University Jamshedpur Jharkhand India

ISBN: (数字)9798350349221

ISBN: (纸本)9798350349238

The effectiveness today's emotion recognition algorithms in texts has become increasingly more critical in current years today's its programs in supporting users gauge actual-time reactions from text-based totally conversations. On this paper, we advise a fixed state-of-the-art experiments to assess the effect that different functions, along with syntactic and semantic functions, have at the efficiency contemporary emotion reputation algorithms in textual content. We use a manually annotated dataset from the automatic have an effect on recognition in text (AART) task to create characteristic units consultant of various ranges latest functions. Those feature units are then used to assess the overall performance latest emotion recognition algorithms – Recursive Neural Networks and Convolutional Neural Networks. The results display that incorporating syntactic and semantic functions can improve the accuracy present day emotion popularity algorithms at a charge ultra-modern 6-10% while as compared with the baseline overall performance. From the findings modern this test, we conclude that incorporating syntactic and semantic features can drastically enhance the overall performance trendy emotion popularity algorithms in text-based totally conversations.

关键词： Emotion recognition Text recognition Semantics Neural networks Medical services Machine learning Syntactics

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Dynamics of COVID-19 Misinformation: An Analysis of Conspiracy Theories, Fake Remedies, and False Reports

Dynamics of COVID-19 Misinformation: An Analysis of Conspira...

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17th International Conference on Social Computing and Social Media, SCSM 2025, held as part of the 27th HCI International Conference, HCII 2025

作者： Thakur, Nirmalya Shao, Mingchen Knieling, Victoria Su, Vanessa Bian, Andrew Jeong, Hongseok Department of Electrical Engineering and Computer Science South Dakota School of Mines and Technology Rapid CitySD57701 United States Department of Computer Science Emory University AtlantaGA30322 United States Program in Linguistics Emory University AtlantaGA30322 United States Goizueta Business School Emory University AtlantaGA30322 United States

ISBN: (纸本)9783031935350

This paper makes four scientific contributions to the area of misinformation detection and analysis on digital platforms, with a specific focus on investigating how conspiracy theories, fake remedies, and false reports emerge, propagate, and shape public perceptions in the context of COVID-19. A dataset of 5,614 posts on the internet that contained misinformation about COVID-19 was used for this study. These posts were published in 2020 on 427 online sources (such as social media platforms, news channels, and online blogs) from 193 countries and in 49 languages. First, this paper presents a structured, three-tier analytical framework that investigates how multiple motives - including fear, politics, and profit - can lead to a misleading claim. Second, it emphasizes the importance of narrative structures, systematically identifying and quantifying the thematic elements that drive conspiracy theories, fake remedies, and false reports. Third, it presents a comprehensive analysis of different sources of misinformation, highlighting the varied roles played by individuals, state-based organizations, media outlets, and other sources. Finally, it discusses multiple potential implications of these findings for public policy and health communication, illustrating how insights gained from motive, narrative, and source analyses can guide more targeted interventions in the context of misinformation detection on digital platforms. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Data mining

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AI applications and Simulation-Based Learning Integrating Future of Nursing Education

AI Applications and Simulation-Based Learning Integrating Fu...

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Intelligent & Innovative Practices in Engineering & Management (IIPEM), International Conference on

作者： Deepak Suwalka Deepak Pandita Snehal Godse Rani Ramrao Patil Abdul Salam Khan Alok Kumar Department of Mental Health Nursing Rama University Kanpur Uttar Pradesh Department of Computer Application (MCA) School of Engineering and Technology Pimpri Chinchwad University Sate Maval Pune Maharashtra India Department of MCA JSPM’s Rajarshi Shahu College of Engineering Tathawade Department of Computer Application Dr.D.Y. Patil School of Science and Technology Pune Maharashtra India Amity School of Fine Arts Amity University Noida UP India

ISBN: (数字)9798350390049

ISBN: (纸本)9798350390056

Nurse educators are modifying their practices with the help of artificial intelligence. artificial intelligence helps nursing students gain their Goal facility arsenic good arsenic their important Althought skills. The purpose of this research is to investigate the advantages disadvantages and results of using artificial intelligence to power Imitation-based learning for nursing school instructors and students. amp mixed-methods access was old inch rate to analyse the memory attending employment and science control of ii c nursing students. The Information utilized included both quantitative and qualitative information. observations such as arsenic the score percentage gain inch attending rates and the forty-five head v head v percentage gain inch important Althought lots point that thither was amp important advance inch pupil interest atonement and Goal competency. Even if significant advancements have been made there is still a need for expensive equipment and insufficient Teaching for faculty members. it is light from these results that Imitations powerful away ersatz word bear the prospective to translate nursing pedagogy and break school prospective nurses for amp active healthcare surround.

关键词： Technological innovation Arsenic Education Employment Medical services Learning (artificial intelligence) Organizations Educational technology Electronic healthcare Pupils

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Enhancement of Antenna Gain With M&W Slot Model on EBG Reflector Structure Utilizing Reflection Phase Diagram Analysis

Enhancement of Antenna Gain With M&W Slot Model on EBG Refle...

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13th International Electrical Engineering Congress, iEECON 2025

作者： Chakunna, Payu Phusam, Nopphadon Mahatthanajatuphat, Pisit Lee, Wilaiporn Suangun, Thanakarn University of Phayao School of Engineering Phayao Thailand Yothinburana School Regular Program in Mathematics-Science Bangkok Thailand King Mongkut's University of Technology North Bangkok Department of Electrical and Computer Engineering Bangkok Thailand

ISBN: (纸本)9798331543952

This research demonstrates the improvement in antenna gain by utilizing an EBG reflector. The EBG reflector includes a unit cell with grooves shaped like the letters M and W to mitigate surface waves at a frequency of 2.45 GHz. The suggested EBG reflector is constructed on an FR-4 substrate exhibiting a uniform dielectric constant of 4.3, a loss tangent of 0.025, and a thickness of 1.6 mm. Furthermore, the impact of boosting the antenna gain can be analyzed by the reflection phase diagram, which exhibits values ranging from +90° to -90° at the resonant frequency of the reflector. The proposed EBG reflector comprises 5x5 unit cells. The testing results of the reflector's performance, when integrated with a general dipole antenna, indicate that it can effectively respond to the resonant frequency of 2.45 GHz, with a |S11| level below -10 dB within the frequency range of 2.2 GHz to 2.6 GHz, thereby adequately covering the IEEE 802.11 b/g/n band. The suggested EBG reflector exhibits a gain of around 6.5 dBi at 2.45 GHz, indicating its efficacy in enhancing gain relative to the standard PEC reflector. Moreover, the radiation pattern is also directional. © 2025 IEEE.

关键词： Antenna reflectors

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Dynamics of COVID-19 Misinformation: An Analysis of Conspiracy Theories, Fake Remedies, and False Reports

arXiv

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arXiv 2025年

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Enhancing Rule-Based Methods for Pulmonary Effusion Diagnosis

Enhancing Rule-Based Methods for Pulmonary Effusion Diagnosi...

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International Conference on Computing and Networking technology (ICCNT)

作者： Vikas Kumar Kharbas N Raghu Priyabati Choudhury Department of Computer Science & Application Vivekananda Global University Jaipur India Department of Electrical and Electronics Engineering School of Engineering and Technology JAIN (Deemed to be University) Bangalore Karnataka India Department of Pharmacy ARKA JAIN University Jamshedpur Jharkhand India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

The diagnosis of pulmonary effusion is a difficult assignment for scientific practitioners because of the excessive variance in the presentation and manifestation of the circumstance. Maximum current diagnosis structures rely upon the use of either sensory/visible remark of chest radiographs (CRs) by radiologists or handcrafting statistical features through area experts with the use of computer-aided analysis (CAD) tools. However, those methods regularly need better generalization and are constrained via their reliance on conventional heuristic algorithms, as well as the mistake-inclined technique of guide identification of features. This paper explores the capacity of the usage of rule-based total methods as better diagnostic structures for pulmonary effusion. Particularly, a rule-based total device primarily based on supervised mastering-based total fashions is proposed as an alternative to traditional feature identification and model development strategies. The proposed device includes an output layer and an enter layer, which includes photograph features and radiological descriptors. Experiments have been conducted on the LIDC-IDRI dataset, and the proposed system outperformed traditional feature-based approaches in terms of both accuracy and specificity. Furthermore, the use of rule-based methods for diagnosis of pulmonary effusion provides a more reliable diagnosis process, which may reduce the radiological review times and improve the accuracy of non-radiological diagnosis.

关键词： Solid modeling Accuracy Design automation Reviews Heuristic algorithms Lung Sensitivity and specificity Reliability Object recognition Diagnostic radiography

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Cryptocurrency and Data Privacy in Human Resource Management 3

Cryptocurrency and Data Privacy in Human Resource Management

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3rd International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2023

作者： Chandrasekeran, Indhumathi Dharmaraj, A. Juyal, Ashima Shravan, M. Deb Barman, Rajesh Lourens, Melanie Department of Commerce with Computer Application PSG College of Arts & Science CoimbatoreTamil Nadu India Department of Management Karpagam Academy of Higher Education CoimbatoreTamil Nadu India Uttaranchal Institute of Technology Uttaranchal University India School of Business SR University WarangalTelangana India Department of Commerce Bodoland University Kokrajhar BTR Assam783370 India Faculty of Management Sciences Durban University of Technology South Africa

ISBN: (纸本)9798350399264

Cryptocurrency and data privacy are two important considerations in human resource management. Cryptocurrency, such as Bitcoin, can be used to pay employees, provide incentives, and manage payroll, but it also poses risks such as price volatility and regulatory issues. Data privacy, on the other hand, is the protection of personal information from unauthorized access and use. The use of blockchain technology, which is the underlying technology behind many cryptocurrencies, can enhance data privacy in human resource management by providing a secure and tamper-proof record of all transactions. However, it's important to comply with all applicable laws and regulations related to the use of cryptocurrency and data privacy in human resource management. © 2023 IEEE.

关键词： Human resource management

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The Design of Smart Cashless Transaction 2020

The Design of Smart Cashless Transaction

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5th International Conference on Intelligent Information technology, ICIIT 2020

作者： Fernando, Anthony Bryan Shreevasta Desprianto, Ferry Gaol, Ford Lumban Oktavia, Tanty Mobile Application and Technology-School of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Program-Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Information Systems Department-School of Information Systems Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781450376594

Cashless Transaction describes as a state where financial transactions are not bound by physical form such as banknotes or coins, but rather trough transfer of digital information (electronic representation of money). Cashless Transaction exists because of fast majorities of human transaction evolved towards digital environment, this creates an opportunity where legal money exists, recorded, and exchanged in digital form. Thus cashless transaction will make less effort in currency operation cost, keep on track with expenses, connected anytime everywhere as long as connected with internet, and eliminates the needs of banknotes or receipt. Cashless Transaction have done over the past few years making life easier by reducing a number of objects to merge into 1 functional object that could make payments faster and simpler starting with check the first mark of cashless transaction that's still being used nowadays, but cashless transaction doesn't stop evolving in this modern era where money is demonetized, cashless transaction is moving into the digital grid resulting a breakthrough mobile wallets and online transfer that offers people flexibility because its technology advancement makes it possible to make payments anytime and anywhere since it's only depend on a secure network(internet) and a platform, therefore cashless transaction could be done as fast as possible saving precious time. Cashless transaction has some of key components such as security, UX, Functionality, Performance and Data Integrity. Five key components could make cashless transaction become reality but also poses a different threat to cashless transaction. Hacking is one of them. Hacking could be done by anyone that have the ability to compromise the transmission, the transmission needs to have more data protection thus the cashless transaction could be done safely and free of risk. © 2020 ACM.

关键词： Personal computing

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Deep Learning with Backtracking Search Optimization Based Skin Lesion Diagnosis Model

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computers, Materials & Continua 2022年第1期70卷 1297-1313页

作者： C.S.S.Anupama L.Natrayan E.Laxmi Lydia Abdul Rahaman Wahab Sait Jose Escorcia-Gutierrez Margarita Gamarra Romany F.Mansour Department of Electronics&Instrumentation Engineering V.R.Siddhartha Engineering CollegeVijayawada520007India Department of Mechanical Engineering Saveetha School of EngineeringSIMATSChennai602105India Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Archives and Communication King Faisal University31982Kingdom of Saudi Arabia Electronic and Telecommunicacions Program Universidad Autonoma del CaribeBarranquilla08001Colombia Department of Computational Science and Electronic Universidad de la CostaCUCBarranquilla08001Colombia Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga72511Egypt

Nowadays,quality improvement and increased accessibility to patient data,at a reasonable cost,are highly challenging tasks in healthcare *** of Things(IoT)and Cloud Computing(CC)architectures are utilized in the development of smart healthcare *** entities can support real-time applications by exploiting massive volumes of data,produced by wearable sensor *** advent of evolutionary computation algorithms andDeep Learning(DL)models has gained significant attention in healthcare diagnosis,especially in decision making *** cancer is the deadliest disease which affects people across the *** skin lesion classification model has a highly important application due to its fine-grained variability in the presence of skin *** current research article presents a new skin lesion diagnosis model i.e.,Deep Learning with Evolutionary Algorithm based Image Segmentation(DL-EAIS)for IoT and cloud-based smart healthcare ***,the dermoscopic images are captured using IoT devices,which are then transmitted to cloud servers for further ***,Backtracking Search optimization Algorithm(BSA)with Entropy-Based Thresholding(EBT)i.e.,BSA-EBT technique is applied in image *** by,Shallow Convolutional Neural Network(SCNN)model is utilized as a feature *** addition,Deep-Kernel Extreme LearningMachine(D-KELM)model is employed as a classification model to determine the class labels of dermoscopic *** extensive set of simulations was conducted to validate the performance of the presented method using benchmark *** experimental outcome infers that the proposed model demonstrated optimal performance over the compared techniques under diverse measures.

关键词： Intelligent models skin lesion dermoscopic images smart healthcare internet of things

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Interference coordination techniques for D2D communications in a spectrum sharing environment

Interference coordination techniques for D2D communications ...

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Artificial Intelligence and Machine Learning applications Theme: Healthcare and Internet of Things (AIMLA), International Conference on

作者： Inzimam Ranganathaswamy M K Ashwini Kumar Department of Computer Science & Application Vivekananda Global University Jaipur India Department of Mechanical Engineering School of Engineering and Technology JAIN (Deemed to be University) Bangalore Karnataka India Department of Mechnical Engineering ARKA JAIN University Jamshedpur Jharkhand India

ISBN: (数字)9798350349221

ISBN: (纸本)9798350349238

device-to-tool (D2D) communications has become an essential a part of allowing understanding transfer, records sharing, and collaboration. As such, green usage of spectrum assets for D2D communications in a spectrum-sharing surroundings is important for making sure equity and advanced consumer revel in. This paper proposes diverse interference coordination techniques for D2D communications in a spectrum sharing environment. These strategies help in enhancing Qu’s by means of mitigating interference inside the goal region, while ensuring minimal disruption to the existing spectrum allocations. The proposed strategies include: Node Clustering and Grid Partitioning; Adaptive carrier Sensing and Dynamic Channel Allocation; Interference Cancellation and signal Combining; and more than one access techniques. The usage of simulation results, the efficacy of the proposed techniques become evaluated under various degrees of interference in the environment. Consequences display that these strategies drastically improve overall performance for a wide variety of applications, together with streaming films, voice communique, and information transfer.

关键词： Time-frequency analysis Simulation Interference Medical services Machine learning Device-to-device communication Sensors

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