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Phytochemical screening, antioxidant properties, and photocytotoxicity of Clinacanthus nutans leaf extracts

Vegetos 2024年第4期37卷 1652-1661页

作者： Chen, Chee-Shien Loke, Chui-Fung Poh, Tze-Ven Tan, Siow-Ping Department of Physical Science Faculty of Applied Sciences Tunku Abdul Rahman University of Management and Technology Kuala Lumpur 53300 Malaysia Research & Development and Commercialization Tunku Abdul Rahman University Management and Technology Kuala Lumpur 53300 Malaysia Department of Computer Science and Embedded Systems Faculty of Computing and Information Technology Tunku Abdul Rahman University Management and Technology Kuala Lumpur 53300 Malaysia

Clinacanthus nutans (Burm. f.) Lindau (C. nutans) is renowned in many tropical countries for its wide range of traditional uses and medicinal properties. This study qualitatively screened ethanol, hexane, and ethyl acetate (EA) leaf extracts of C. nutans for phytochemicals and evaluated their antioxidant activities using 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging and ferric reducing antioxidant power (FRAP) assays. Furthermore, the photocytotoxicity of the extracts against the A431 human skin squamous carcinoma cells was assessed using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. Qualitative phytochemicals screening revealed the presence of terpenes, alkaloids, phenols, quinones, and chlorophyll, whereas flavonoids and anthraquinones were absent in all crude extracts. In the DPPH assay, the EA crude extract exhibited the lowest EC₅₀ value of 31 ± 2 μg/mL, whereas the same extract demonstrated the highest FRAP value of 7.42 ± 1.87 mmol Fe2+/g DW. After photodynamic therapy (PDT) activation, EA crude extract demonstrated the strongest photocytotoxic activity against A431 cells with an IC₅₀ value of 8 ± 1 μg/mL, followed by the hexane crude extract (IC₅₀ = 16 ± 2 μg/mL) and the ethanol crude extract (IC₅₀ = 20 ± 1 μg/mL). However, all three crude extracts showed negligible activity against the A431 cells in the absence of PDT treatment, even at concentrations as high as 200 μg/mL after 24 h of dark incubation. These findings suggest that C. nutans could serve as a potential source of natural antioxidants and photosensitizers for photodynamic therapy in cancer treatment. © 2023, The Author(s) under exclusive licence to Society for Plant Research.

关键词： Antioxidant activity Clinacanthus nutans PDT treatment Photocytotoxicity Phytochemical screening

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Sustainable-Security Assessment Through a Multi Perspective Benchmarking Framework

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computers, Materials & Continua 2022年第6期71卷 6011-6037页

作者： Ahmed Saeed Alfakeeh Abdulmohsen Almalawi Fawaz Jaber Alsolami Yoosef B.Abushark Asif Irshad Khan Adel Aboud SBahaddad Md Mottahir Alam Alka Agrawal Rajeev Kumar Raees Ahmad Khan Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Electrical and Computer Engineering Faculty of EngineeringKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Information Technology Babasaheb Bhimrao Ambedkar UniversityLucknow-226025Uttar PradeshIndia Department of Computer Science and Engineering Babu Banarasi Das UniversityLucknow-226028Uttar PradeshIndia

The current cyber-attack environment has put even the most protected systems at risk as the hackers are nowmodifying technologies to exploit even the tiniest of weaknesses and infiltrate *** this situation,it’s critical to design and construct software that is both secure and *** security is the most well-defined aspect of health information software systems,it is equally significant to prioritise sustainability because any health information software system will be more effective if it provides both security and sustainability to the customers at the same *** this league,it is crucial to determine those characteristics in the systems that can help in the accurate assessment of the sustainable-security of the health information software during the development *** research work employed the Fuzzy Analytic Network Process(Fuzzy ANP)to estimate the impact of the overall sustainable-security of health information software systems and their characteristics in order to achieve a high level of ***,the study validates the efficacy of the Fuzzy ANP procedure by testing it on five different versions of a health information software system through Fuzzy Technique for Order of Preference by Similarity to Ideal Solutions(Fuzzy TOPSIS).Despite the sensitivity of the health information software systems,this study employedmultiple versions of health information software *** compared with the existing procedures for testing the sustainable-security of health information software systems,the outcomes were conclusive and significantly more *** saving time and resources,the mechanism suggested in this research work aims to establish an outline that software practitioners can follow to enhance the sustainablesecurity of health information software systems.

关键词： Sustainable-security sustainable health information software systems analytic network process fuzzy logic

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A Birds Species Detection Utilizing an Effective Hybrid Model 21

A Birds Species Detection Utilizing an Effective Hybrid Mode...

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21st International Multi-Conference on systems, Signals and Devices, SSD 2024

作者： Rafa, Sara Abbas Al-Qfail, Zohaa Mubarak Adil Nafea, Ahmed Abd-Hood, Samia F. Al-Ani, Mohammed M Alameri, Saeed Amer College of Law and Political Science University of Anbar Dept. Law Ramadi Iraq College of Computer Science and Information Technology University of Anbar Dept. Artificail Inteligence Ramadi Iraq Selangor Bangi Malaysia Seiyun University Dept. Computer Science Faculty of Applied Sciences Hadhramout Yemen Hadhramout University Faculty of Computers and Information Almukalla Hadhramout Yemen Seiyun University Dept. Department of Information Technology Hadhramout Yemen

ISBN: (纸本)9798350374131

The aim of this study is to improve the performance of detection Birds Species by proposed a hybrid model using a combination of MobileNetV2 for feature extraction, an Autoencoder for dimensionality reduction, and Support Vector Machines (SVM) for classification. The methodology includes preprocessing, augmentation, feature extraction, and classification phases. The proposed model is evaluated using the Bird Species dataset, consisting of 525 bird species the dataset is carefully curated to ensure cleanliness and absence of leakage between sets. The evaluation metrics include precision, recall, accuracy, and F-measure. The results have shown the efficiency of the proposed model in bird species classification. © 2024 IEEE.

关键词： Support vector machines

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A Method and Software to Create SCORM Units for computer science Courses

A Method and Software to Create SCORM Units for Computer Sci...

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Conference on Software Engineering Education & Training (CSEE&T)

作者： Peter Braun Faculty of Computer Science and Business Information Systems Technical University of Applied Sciences Würzburg-Schweinfurt Würzburg Germany

ISBN: (数字)9798350378979

ISBN: (纸本)9798350378986

Producing learning videos for flipped classrooms is a time-consuming and manual task. This paper presents a method and software to create SCORM units for computer science courses. The method consists of a common structure for learning videos, a Python script to create SCORM units, and ChatGPT for quiz creation. The software is based on the open-source software FFmpeg for video production. The results after 40 learning units show that producing a learning video can be automated to a great extent.

关键词： computer science Electronic learning Education Production Manuals Recording Online services

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Multimodal Fusion for Enhanced Parkinson's Disease Screening: Integrating Brain MRI, Hand Drawing, Facial Expressions, and Voice Analysis 5

Multimodal Fusion for Enhanced Parkinson's Disease Screening...

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5th International Conference on Advancements in Computing, ICAC 2023

作者： Warnakulasuriya, Naveen De Silva, Shalinika Madushika, Janani Gamage, Sadali Jayawardena, Sanath Karunasena, Anuradha Sri Lanka Institute of Information Technology Faculty of Computing Department of Information Technology Malabe Sri Lanka Sri Lanka Institute of Information Technology Faculty of Computing Department of Computer Science and Software Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Faculty of Computing Department of Computer Systems Engineering Malabe Sri Lanka

ISBN: (纸本)9798350358131

Parkinson's disease (PD) profoundly impacts millions in Sri Lanka, emphasizing the importance of early detection for better patient outcomes. We introduce 'NeuraTrace PD,' an innovative application for early PD screening, combining brain MRI, hand-drawn image analysis, facial expression assessment, and voice analysis. For brain MRI analysis, we employed a Graph Convolutional Network (GCN), achieving an impressive accuracy of 91% and identifying distinct graph connectivity patterns using graph theory. We also use a deep Convolutional Neural Network (CNN) to reach 90% accuracy in analyzing hand-drawn images, while optimizing image resolution for efficiency and information retention. Facial expression analysis is a vital component, leveraging CNN and Constrained Local Models (CLM) to accurately extract Facial Action Units (FAUs), which contribute to a remarkable 95% accuracy using the XGBoost machine learning model. We introduce a Machine Learning (ML) algorithm and advanced signal processing to enhance voice feature analysis, offering a thorough understanding and classification of PD patients. It reaches 99% accuracy. In summary, our approach holds significant promise for advancing early PD diagnosis, ultimately improving the quality of life for those affected by this challenging condition. © 2023 IEEE.

关键词： Image resolution

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Fake Twitter Followers Detection using Machine Learning Approach 2

Fake Twitter Followers Detection using Machine Learning Appr...

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2nd International Conference on Business Analytics for Technology and Security, ICBATS 2023

作者： Zeshan Shabbir, Muhammad Naseer, Iftikhar Akhter, Shamim Abubakar, Muhammad Issa, Ghassan F. Hassaan Mehmood, Muhammad Comsats University Faculty of Information and Technology Islamabad Pakistan The Superior University Faculty of Computer Science & Information Technology Lahore Pakistan Minhaj University School of Library & Information Sciences Lahore Pakistan Fast School of Computing National University of Computer and Emerging Sciences Lahore Pakistan Skyline University College School of Information Technology University City Sharjah Sharjah1797 United Arab Emirates NCBA&E School of Computer Science Lahore Pakistan Applied Science Private Universit Applied Science Research Center Amman11937 Jordan

ISBN: (纸本)9798350335644

Fake user accounts on social media are a serious threat. Artificial intelligence can play an important role in getting rid of fake user accounts. Twitter has a problem with fake accounts that are run by automated bots. These bots are used for bad things like spamming, sabotaging trends, and getting more followers. In this research, publicly available information about Twitter users, such as their activity patterns, profile information, and tweets, to figure out how real each one is. Twitter's API and other ways of getting information will be used to get user data. The proposed model consists of a machine learning technique, and it detects whether the user accounts are real or fake. Various algorithms such as logistic regression, long short-term memory, K-mean, and random forest are applied to evaluate the proposed model. The experimental results show that the random forest algorithm has obtained the highest accuracy 0.7557, a precision of 0.7277, and F1 of 0.7943 among all other algorithms. © 2023 IEEE.

关键词： Logistic regression

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Natural Language Processing with Optimal Deep Learning-Enabled Intelligent Image Captioning System

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computers, Materials & Continua 2023年第2期74卷 4435-4451页

作者： Radwa Marzouk Eatedal Alabdulkreem Mohamed KNour Mesfer Al Duhayyim Mahmoud Othman Abu Sarwar Zamani Ishfaq Yaseen Abdelwahed Motwakel Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

The recent developments in Multimedia Internet of Things(MIoT)devices,empowered with Natural Language Processing(NLP)model,seem to be a promising future of smart *** plays an important role in industrial models such as speech understanding,emotion detection,home automation,and so *** an image needs to be captioned,then the objects in that image,its actions and connections,and any silent feature that remains under-projected or missing from the images should be *** aim of the image captioning process is to generate a caption for *** next step,the image should be provided with one of the most significant and detailed descriptions that is syntactically as well as semantically *** this scenario,computer vision model is used to identify the objects and NLP approaches are followed to describe the *** current study develops aNatural Language Processing with Optimal Deep Learning Enabled Intelligent Image Captioning System(NLPODL-IICS).The aim of the presented NLPODL-IICS model is to produce a proper description for input *** attain this,the proposed NLPODL-IICS follows two stages such as encoding and decoding ***,at the encoding side,the proposed NLPODL-IICS model makes use of Hunger Games Search(HGS)with Neural Search Architecture Network(NASNet)*** model represents the input data appropriately by inserting it into a predefined length ***,during decoding phase,Chimp Optimization Algorithm(COA)with deeper Long Short Term Memory(LSTM)approach is followed to concatenate the description sentences 4436 CMC,2023,vol.74,no.2 produced by the *** application of HGS and COA algorithms helps in accomplishing proper parameter tuning for NASNet and LSTM models *** proposed NLPODL-IICS model was experimentally validated with the help of two benchmark *** comparative analysis confirmed the superior performance of NLPODL-IICS model over other models.

关键词： Natural language processing information retrieval image captioning deep learning metaheuristics

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Geometric Modelling of Fractal Structured Objects based on Integration of R-Function And L-System Methods

Geometric Modelling of Fractal Structured Objects based on I...

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2024 Cognitive Models and Artificial Intelligence Conference, AICCONF 2024

作者： Anarova, Shahzoda Azimbayevna, Shakhlo Sadullaeva Berdiev, Golib Ogli, Adhamjon Toxtasinov Ilhomjon Ilxom Kizi, Maftuna Ismoilova Department of Convergence of digital technologies Computer Engineering Faculty Tashkent University of Information Technologies Tashkent Uzbekistan Joint Belarusian-Uzbek Intersectoral Institute of Applied Technical Qualifications Uzbekistan Department of Computer Systems Karshi branch of the Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Uzbekistan

ISBN: (纸本)9798400716928

The article offers suggestions about mathematical modeling of architectural objects based on the functional image using the constructive operations of the theory of R-functions. Given in 2D format 3D surface from the data equations work exit according to approach offer done. Work developed mathematician from the model using construction - architecture L-systems in objects based on three measured geometric to the object processing to give through fractal 3D computer design of an architectural building model work developed. In the article work developed samples of the method opportunities reflection made. Fractal geometry terminology and concepts using natural surfaces, forms enough level right, good quality and quantitative way described. In architecture forms structure spatial organize to be done fractal geometry using natural structures like enough level description possible has been repetitive to himself similar from structures use, fractal construction the rules mathematician models and computer graphics using in architecture application this direction possibilities efficiency increases. © 2024 ACM.

关键词： Fractals

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An Ensembled Real-Time Hand-Gesture Recognition using CNN 15

An Ensembled Real-Time Hand-Gesture Recognition using CNN

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Kavitha, M.N. Saranya, S.S. Prasad, M. Kaviyarasu, S. Ragunath, N. Rahul, P. Kongu Engineering College Department of Computer Science and Design Tamilnadu Erode India PSG Institute of Technology and Applied Research Department of Computer Science and Engineering Tamilnadu Coimbatore India Controller of Examinations Tamilnadu Namakkal India Kongu Engineering College Bachelor of Science - Information Systems Tamilnadu Erode India

ISBN: (纸本)9798350370249

Hand sign recognition is a vital technology in the human-computer interaction, enabling individuals to communicate with machines naturally and effectively. An innovative approach for real-time hand sign identification with the help of CNN and OpenCV is introduced with the fusion of computer vision and deep learning that can accurately interpret and classify an extensive range of hand signs and gestures. This research contributes significantly to the fields of computer vision and human-computer interaction, offering a practical and efficient solution for hand sign recognition. The combination of CNN and OpenCV presents a promising avenue for enhancing accessibility and communication, especially in environments where verbal communication is limited or non-existent. The model is trained with multiple data so that the system can recognize the hand gestures more precisely. Pre-trained architectures like ResNet and MobileNet are combined with the CNN model using ensemble learning and the performance is improved when compared to all the three CNN architectures individually. The ensemble model provides better accuracy of 96 %. The potential applications of this technology are vast, from assisting the hearing-impaired in understanding sign language to more immersive and intuitive interactions. Overall, the approach holds the promise of bridging the gap between human gestures and machine understanding, opening new doors for meaningful interactions between individuals and intelligent systems. © 2024 IEEE.

关键词： Intelligent systems

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Lexicon-based Non-Compositional Multiword Augmentation Enriching Tweet Sentiment Analysis 3

Lexicon-based Non-Compositional Multiword Augmentation Enric...

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3rd International Conference on Artificial Intelligence and Data sciences, AiDAS 2022

作者： Tahayna, Bashar Ayyasamy, Ramesh Kumar Akbar, Rehan Subri, Nor Fatiha Binti Sangodiah, Anbuselvan Universiti Tunku Abdul Rahman Faculty of Information and Communication Technology Department of Information Systems Kampar Malaysia Universiti Teknologi Petronas Faculty of Science and Information Technology Department of Computer & Information Science Malaysia

ISBN: (数字)9781665491648

ISBN: (纸本)9781665491648

One of the benefits of recognizing a slang, an id-iom or an abbreviation in a tweet is the ability to help in finding certain sentiment in a concise and understandable manner. However, a lack of adequate annotated 'idiomatic tweets' makes classification challenging. We propose a pliable augmen-tation technique to improve the classification of idiomatic tweets with tiny training samples. For classification, we evaluate the performance of fine-tuning version of a pre-trained embedding model at different flavors. During the augmentation process, we deduce the intrinsic propositional meaning of the idiomatic ex-pression from IBM's SliDE (Sentiment Lexicon of IDiomatic Expressions) and another lexicon we built. The empirical results show that the proposed method is beneficial in concealing the actual intent of the tweet and advantageous to tackle the prob-lem of overfitting caused by smaller training sets. The experi-ment shows that using data augmentation of the idiomatic ex-pressions has reduced the classification error rate with 16%. © 2022 IEEE.

关键词： Sentiment analysis

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