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IEEE Conference Photovoltaic Specialists (PVSC)

作者： Spyros Theocharides Anastasios Koumis George Makrides George E. Georghiou Department of Electrical and Computer Engineering PV Technology Laboratory FOSS Research Centre for Sustainable Energy University of Cyprus Nicosia Cyprus

Accurate photovoltaic (PV) generation forecasting is an important feature that can assist utilities and plant operators in the direction of energy management and dispatchability planning. However, the accuracy of the PV forecasting is directly related to the quality of the weather forecasts. In this work, an evaluation of the various weather forecasting models is performed. Additionally, an investigation of the effect of the quality of the weather forecasts on PV generation forecasting will be examined. Finally, this study focused to propose an approach to improve the quality of the weather forecasts and eventually the PV production forecasting accuracy by employing machine learning and linear regression models that could record the behaviour of the local weather.

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Sarcasm detection in product reviews using textual entailment approach 23

Sarcasm detection in product reviews using textual entailmen...

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Proceedings of the 2023 7th International Conference on Natural Language Processing and Information Retrieval

作者： Shubham Sinha Tarun Vijeta Pratik Kishor Kubde Ayush Pradeep Gajbhiye Mansi Anup Radke Christopher Jones Department of Computer Science and Engineering Visvesvaraya National Institute of Technology India School of Computer Science and Informatics Cardiff University UK

ISBN: (纸本)9798400709227

Sarcasm is a form of sentiment characterized by the use of words that express the opposite of what is meant. Sarcasm detection has applications in multiple domains ranging from sentiment analysis in product reviews to user feedback, and online forums. Sarcasm detection is important to understand user opinions and intentions in areas such as sentiment-based classification and opinion mining. This can result in better product development and customer service. Sarcasm detection can be a challenging task because sarcastic sentences may use positive expressions to convey negative meanings or may use negative sentences to convey positive meanings. Also, sarcastic sentences form a very small component of the entire communication. The increasing use of sarcasm in various social media such as Twitter, Reddit, Amazon product reviews, etc. has highlighted the importance of detecting and understanding sarcasm in various contexts. Sarcasm detection is a challenging problem for NLP systems that often rely on statistical models for performing sentiment analysis. In this research, the focus is on the use of a textual entailment approach for detecting sarcasm. Textual entailment is a natural language inference task that involves determining whether one text (hypothesis) can be derived from another text (premise). The underlying assumption behind this approach is that - if there is a contradiction between the premise and hypothesis, we can say that the hypothesis is sarcastic. To test our approach, an annotated corpus of 3000 product reviews was developed methodically from the Amazon Reviews dataset and tested using the textual entailment approach. The proposed approach achieved an F1 score of 0.76 on this dataset. The result is better than the baseline considered which is the BERT binary classifier which gives an F1 score of 0.48 on the same dataset.

关键词： Hypothesis Natural Language Inference Premise Sarcasm Detection Textual Entailment

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A Comprehensive View on the Progress of Organoid Research with an Emphasis on its Relevance to Disease Characterization

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Biomedical and Environmental Sciences 2023年第10期36卷 959-971页

作者： Chandra KISHORE Vaishali Ji Saurav Mallik Ayan MUKHERJI Namrata TOMAR Soumen Kumar Pati LI Ai Min Sinthia Roy BANERJEE Soumadip GHOSH Raza Ali NAQVI University of California Irvine Medical CenterOrangeCA 92868USA Department of Botany J.D.Women’s CollegeBailey RoadPatna-800023India Harvard T.H.Chan School of Public Health BostonMA 02115USA Department of Information Technology Haldia Institute of TechnologyHaldiaWest BengalIndia Medical College of Wisconsin MilwaukeeWI 53226USA Department of Bioinformatics Maulana Abul Kalam Azad University of TechnologyNadiaWest BengalIndia Center for Precision Health School of Biomedical InformaticsThe University of Texas Health Science Center at HoustonHoustonTX 77030USA School of Computer Science and Engineering Xi’an University of TechnologyXi'an 710048ShaanxiChina Department of Information Technology Guru Nanak Institute of TechnologyKolkataWest BengalIndia Department of Computer Science and Engineering Sister Nivedita UniversityKolkataWest BengalIndia Center for Precision Health School of Biomedical InformaticsUniversity of IllinoisChicago60612USA

INTRODUCTION Organoids are primary tissue or stem cells derived cell aggregates that have the capacity for self-organization,self-renewal,and the capacity to mimic cellular and tissue level *** can overcome the shortc... 详细信息

关键词： functions. overcome shortcomings

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Optimization of 3D Holographic Projection for a Medical Image System using Taguchi Method and Fuzzy Inference System

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Journal of Imaging Science and technology 2023年第4期67卷 1-7页

作者： Chou, Ming-Chung Huang, Tian-Hsiang Tsai, Jinn-Tsong Chen, Yen-Ming J. Hwang, Kao-Shing Huang, Wei-Tai Ho, Wen-Hsien Department of Medical Imaging and Radiological Sciences Kaohsiung Medical University Kaohsiung Taiwan Center for Big Data Research Kaohsiung Medical University Kaohsiung Taiwan Department of Medical Research Kaohsiung Medical University Hospital Kaohsiung Taiwan Department of Computer Science and Information Engineering National Penghu University of Science and Technology Penghu Taiwan Department of Computer Science and Artificial Intelligence National Pingtung University Pingtung Taiwan Department of Healthcare Administration and Medical Informatics Kaohsiung Medical University Kaohsiung Taiwan Department of Information Management National Kaohsiung University of Science and Technology Kaohsiung Taiwan Department of Electrical Engineering National Sun Yat-Sen University Kaohsiung Taiwan Department of Mechanical Engineering National Pingtung University of Science and Technology Pingtung Taiwan College of Professional Studies National Pingtung University of Science and Technology Pingtung Taiwan

Two dimensional projections of three dimensional (3D) objects are used to teach anatomy. These projections are relatively unrealistic, and medical students cannot easily and accurately grasp the position and shape of each anatomical structure. As a remedy, 3D holographic projections allow for 3D anatomical structures to be projected in space without the use of worn contraptions. This study designed a method for optimizing 3D holographic projections with respect to the quality characteristics of 3D imaging definition and stereoscopic quality. The Taguchi method was used to determine the factors that most greatly influenced these quality characteristics, and the Delphi method and fuzzy theory were used to quantify image quality. Among three main factors of material of the projection panel, thickness of the projection panel, and angle made by the projection panel with the horizontal plane, thickness was the most influential. The optimal combination of factors was acrylic material, a thickness of 1 mm, and an angle of 45°. This paper's method aids medical pedagogy and can be used by the holographic projection manufacturing industry to optimize 3D imaging definition and stereoscopic quality. © 2023 Society for Imaging Science and technology.

关键词： Taguchi methods

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Blockchain-Based Secure and Efficient Secret Image Sharing With Outsourcing Computation in Wireless Networks

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IEEE Transactions on Wireless Communications 2024年第1期23卷 423-435页

作者： Zhou, Zhili Wan, Yao Cui, Qi Yu, Keping Mumtaz, Shahid Yang, Ching-Nung Guizani, Mohsen Institute of Artificial Intelligence and Blockchain Guangzhou University Guangzhou510006 China Engineering Research Center of Digital Forensics Ministry of Education Nanjing University of Information Science and Technology Nanjing210044 China Graduate School of Science and Engineering Hosei University Tokyo184-8584 Japan RIKEN Center for Advanced Intelligence Project RIKEN Tokyo103-0027 Japan Department of Applied Informatics Silesian University of Technology Gliwice44-100 Poland Department of Engineering Nottingham Trent University NottinghamNG1 4FQ United Kingdom Department of Computer Science and Information Engineering National Dong Hwa University Hualien97401 Taiwan Abu Dhabi United Arab Emirates

Secret Image Sharing (SIS) is the technology that shares any given secret image by generating and distributing n shadow images in the way that any subset of k shadow images can restore the secret image. However, in the existing SIS schemes, the shadow images will be easily tampered and corrupted during the communication, which will pose serious security issues. Recently, blockchain has emerged as a promising paradigm in the field of data communication and information security. To securely communicate and effectively protect the secret image data in wireless networks, we propose a Blockchain-based Secure and Efficient Secret Image Sharing (BC-SESIS) scheme with outsourcing computation in wireless networks. In the proposed BC-SESIS scheme, the shadow images are encrypted and stored in the blockchain to prevent them from being tampered and corrupted. The identity authentication-enabled smart contract is deployed to achieve the (k,n) threshold for secret image restoring. Furthermore, to reduce the computational burden of smart contract and users, an efficient outsourcing computation method is designed to outsource the restoring task, which is securely implemented by agent miners in the encryption domain. Theoretical analysis and extensive experiments demonstrate that the BC-SESIS scheme can achieve desirable communication security and high computational efficiency in the wireless networks. © 2023 IEEE.

关键词： Smart contract

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Descriptive Exam Evaluation through Semantic Mining and Analysis

Descriptive Exam Evaluation through Semantic Mining and Anal...

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2023 Human-Centered Cognitive Systems, HCCS 2023

作者： Akhtar, Raybal Safyan, Muhammad Iqbal, Muddesar Sarwar, Sohail University of Management and Technology Department of Informatics and Systems Lahore Pakistan Government College University Lahore Department of Computer Science Lahore Pakistan Prince Sultan University Department of Communication & Network Engineering Riyadh Saudi Arabia Bahria University Islamabad Department of Computer Science Islamabad Pakistan

ISBN: (纸本)9798350359183

Online examination evaluation methods are used as an alternative to the traditional examination's way of evaluation methods. They offer a number of advantages while addressing issues associated with outdated conventional approaches. Online evaluation methods are mainly used for objective and short answers based exams but may not suitable for assessing the depth knowledge in candidates. So, candidate's descriptive examinations are conducted to assess their depth of knowledge. Descriptive evaluation methods have been put into practice for quite some time but they greatly rely on keyword-matching techniques between the questions and answers. Due to this limitation, the semantic meanings of these answers are ignored. In current research, the deficiencies in prevalent systems have been addressed by calculating the semantic and syntactic similarity between answers. Moreover, the repetitive words and similarity between counteractive answers has also been considered. We have used SQuAD1 dataset in current research. Our model has achieved a value of 0.88 in terms of accuracy for while computing similarity among listed items. © 2023 IEEE.

关键词： Semantics

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AlexNet Architecture Based Convolution Neural Network for Realtime Audio to Text Translator of Bisindo Hand Sign

AlexNet Architecture Based Convolution Neural Network for Re...

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2023 International Seminar on Application for technology of Information and Communication, iSemantic 2023

作者： Sujatmiko, Dhiki Sari, Christy Atika Rachmawanto, Eko Hari Krismawan, Andi Danang Altamer, Bilal R. Alkhafaji, Mohamed Ayad University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia University of Dian Nuswantoro Study Program in Animation Semarang Indonesia Mosul University Presidency University of Mosul Department of Computer Science Mosul Iraq National University of Science and Technology Department of Computer Science DhiQar Iraq

ISBN: (纸本)9798350339215

Deafness is a condition that results in the loss of hearing function, hindering the reception of information such as oral communication that relies on auditory senses. Consequently, individuals with hearing impairment experience communication barriers and may have limited or no ability to respond. One solution is the use of sign language. In Indonesia, there are two known sign languages: Sibi and Bisindo. Both serve the same function but differ in their style of movement and expression. Bisindo is considered more flexible as it conveys meaning based on the Indonesian language. However, the universal understanding of this language solution is still limited among many people. Therefore, a program is needed to facilitate translation between deaf individuals who use sign language and their counterparts who do not communicate through sign language. CNN (Convolutional Neural Network) is a deep learning algorithm used for training visual input data recognition by computer systems. There are various CNN-based architectures, and one of them is AlexNet. Based on the author's testing, the AlexNet architecture proves to be suitable for real-time sign language translation. The evaluation of the system involved 7,800 datasets and 520 testing instances, with an average accuracy of 468 correct translations. When averaged, the system achieved a 90% accuracy rate, representing a 100% increase in accuracy compared to previous approaches. © 2023 IEEE.

关键词： Audition

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Net Load Prediction Using Machine Learning Methods: A Case Study of Residential Households

Net Load Prediction Using Machine Learning Methods: A Case S...

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International Conference on Energy Transition in the Mediterranean Area (SyNERGY MED)

作者： Panagiotis Herodotou Georgios Tziolis George Makrides George E. Georghiou Department of Electrical and Computer Engineering PV Technology Laboratory University of Cyprus (UCY) PHAETHON Centre of Excellence (CoE) for Intelligent Efficient and Sustainable Energy Solutions Nicosia Cyprus

ISBN: (数字)9798350375923

ISBN: (纸本)9798350375930

As residential solar photovoltaic (PV) systems are increasingly integrated into distribution networks globally, there is a growing necessity to shift from traditional load forecasting to net load forecasting (i.e., predicting the combination of PV and load collectively). Understanding and predicting the daily net energy of a typical household is crucial for designing and sizing appropriate renewable energy systems and storage solutions. This paper compares the performance of different machine learning methods in predicting the net load patterns of a typical household. The database contained PV production and energy load records from 68 actual households in cyprus, over a period of one year. The results showed that the eXtreme Gradient Boosting (XGBoost) model outperformed all other models yielding a normalized root mean square error of 5.52%. Despite the inherent unpredictability of net load patterns, the findings indicate that the proposed XGBoost model can achieve high prediction accuracies for household electricity net load profiles.

关键词： Analytical models Accuracy Load forecasting Production Predictive models Data models Real-time systems Smart grids Random forests Load modeling

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Characterizing Abhorrent, Misinformative, and Mistargeted Content on YouTube

arXiv

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arXiv 2021年

作者： Papadamou, Kostantinos Department of Electrical Engineering Computer Engineering and Informatics Cyprus University of Technology Cyprus

YouTube has revolutionized the way people discover and consume video content. Although YouTube facilitates easy access to hundreds of well-produced educational, entertaining, and trustworthy news videos, abhorrent, misinformative and mistargeted content is also common. The platform is plagued by various types of inappropriate content including: 1) disturbing videos targeting young children;2) hateful and misogynistic content;and 3) pseudoscientific and conspiratorial content. While YouTube’s recommendation algorithm plays a vital role in increasing user engagement and YouTube’s monetization, its role in unwittingly promoting problematic content is not entirely understood. In this thesis, we shed some light on the degree of abhorrent, misinformative, and mistargeted content on YouTube and the role of the recommendation algorithm in the discovery and dissemination of such content. Following a data-driven quantitative approach, we analyze thousands of videos posted on YouTube. Specifically, we devise various methodologies to detect problematic content, and we use them to simulate the behavior of users casually browsing YouTube to shed light on: 1) the risks of YouTube media consumption by young children;2) the role of YouTube’s recommendation algorithm in the dissemination of hateful and misogynistic content, by focusing on the Involuntary Celibates (Incels) community;and 3) user exposure to pseudoscientific misinformation on various parts of the platform and how this exposure changes based on the user’s watch history. In a nutshell, our analysis reveals that young children are likely to encounter disturbing content when they randomly browse the platform starting from benign videos relevant to their interests and that YouTube’s currently deployed counter-measures are ineffective in terms of detecting them in a timely manner. By analyzing the Incel community on YouTube, we find that not only Incel activity is increasing over time, but platforms may also play an active r

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SEMU5G: an Emulator for Improving Model Accuracy and Performance Evaluation of 5G Network Core Architectures based on SDN 10

SEMU5G: an Emulator for Improving Model Accuracy and Perform...

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10th International Conference on Wireless and Telematics, ICWT 2024

作者： Zaki Hamidi, Eki Ahmad Lazuardi, Arga Valen Rahmansyah, Muhammad Litfan Novel Bajri, Salman Alfarizi Tulloh, Rohmat Negara, Ridha Muldina Ahdan, Syaiful Jupriyadi UIN Sunan Gunung Djati Bandung Electrical Engineering Department Bandung Indonesia Telkom University Telecommunication Technology School of Applied Science Bandung Indonesia The University Center of Excellence Intelligent Sensing-IoT Telkom University Indonesia Telkom University School of Electrical Engineering Bandung Indonesia Universitas Teknokrat Indonesia Faculty of Engineering & Computer Science Indonesia Institut Teknologi Bandung School of Electrical Engineering and Informatics Bandung Indonesia Universitas Teknokrat Indonesia Faculty of Engineering and Computer Science Bandarlampung Indonesia

ISBN: (纸本)9798350377057

The rapid advancement of 5G Radio Access Network (RAN) architecture is facilitating the construction of 5G networks, marking a significant milestone in telecommunications evolution. Given the complexity of the 5G core architecture, traditional simulation methods are insufficient, necessitating novel approaches. Emulator systems are crucial for creating dynamic, controlled environments that enable exploration of real-world scenarios without physical constraints. SEMU5G, a 5G core emulator, SDN controller, and RAN simulator, utilizes Open5GS implemented in Docker Container for test system flexibility and isolation. Additionally, an SDN controller is integrated to monitor data flows in the User Plane Function (UPF) and gNB simulated by UERANSIM in Mininet-WiFi. This comprehensive integration facilitates effective and flexible real-world exploration, providing a dynamic and controlled test environment for 5G core research. Scenario testing comprises two stages: firstly, a fixed network topology is employed to compare resource usage and confirm successful SEMU5G integration. Secondly, a mobile network topology is utilized to implement a mobile device scenario and compare the Quality of Service (QoS) of SEMU5G with other available emulators. These stages ensure thorough evaluation of SEMU5G's performance and its comparative advantage over existing solutions. © 2024 IEEE.

关键词： Wi-Fi

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