Exploring the ethical considerations of using Chat GPT in university education

Periodicals of Engineering and Natural Sciences (PEN), Год журнала: 2023, Номер 11(4), С. 105 - 105

Опубликована: Авг. 30, 2023

This study investigates the moral dilemmas that arise with incorporating Chat GPT into higher education, a focus on situation in Latinoamerican institutions of learning. The surveyed 220 people via online questionnaire to learn more about their experiences and motivations for using AI-powered conversational agents. An overview demographics participants was provided through descriptive statistics. investigation subject at hand lays groundwork further research. It also reveals hidden meanings observed phenomena, it suggests possible solutions problems have been uncovered. research looks how AI systems chatbots can supplement human knowledge judgment, as well potential drawbacks. results showed thought integration moderately accessible had positive social attitudes. They understood value responsibility creating individualized educational opportunities. Participants stressed necessity explicit institutional standards regarding privacy data security. Gender, age, sense accessibility, attitude, opinions, personal experience, security, guidelines, learning were found affect participants' reliance regression analysis. findings shed light education is complicated by factors such individual beliefs, cultural norms, ethical problems. busy schedules students may be accommodated resources they need succeed made available thanks this adaptability. In addition, natural language processing models offer instantaneous help text chat, voice, or video. To fully grasp consequences lead creation responsible implementation techniques, proposes additional qualitative investigations, longitudinal studies, comparative across diverse contexts required. Closing these gaps will move field forward ways are beneficial classroom.

Язык: Английский

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Enhancing Surveillance with Machine and Deep Learning-Based Facial Recognition Model: A Proposed Approach for Identification

Journal of Engineering and Sustainable Development, Год журнала: 2025, Номер 29(1), С. 127 - 135

Опубликована: Янв. 1, 2025

There is limited understanding and utilization of facial recognition models in surveillance. This work addresses the underutilization Models surveillance contexts. A Model that leverages its proposed technology to monitor locate individuals real-time video streams dataset images. The model begins with an initial containing images specific individuals, such as university professors, missing persons, or criminals. These extract essential attributes for training capable identifying live recordings. Upon a successful match, identifies tracks their movements using cameras. primary objective this integrate seamlessly current infrastructure, minimizing operational costs disruptions. employs two main artificial intelligence approaches: Support Vector Machine achieved accuracy 85.33%, demonstrating effective compared Multilayer Perceptron 89.0% accuracy. Additionally, Linear Discriminant Analysis highest classification at 87.66%. Furthermore, our custom deep learning demonstrated exceptional accuracy, ranging between 99.5% 99.8%, showcasing significant advancements over existing methodologies.

Язык: Английский

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Enhancing gender detection in computer vision: Leveraging transfer learning and data augmentation

AIP conference proceedings, Год журнала: 2025, Номер 3282, С. 030021 - 030021

Опубликована: Янв. 1, 2025

Язык: Английский

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Innovative drought monitoring: development and application of the multi-regional aggregated standardized drought index (MRASDI)

Earth Science Informatics, Год журнала: 2025, Номер 18(2)

Опубликована: Апрель 8, 2025

Язык: Английский

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White shark optimizer via support vector machine for video-based gender classification system

Multimedia Tools and Applications, Год журнала: 2025, Номер unknown

Опубликована: Янв. 23, 2025

Abstract Gender identification from videos is a challenging task with significant real-world applications, such as video content analysis and social behavior research. In this study, we propose novel approach, the White Shark Optimizer-Support Vector Machine (WSO-SVM), tailored specifically for gender data. The WSO-SVM integrates Optimizer, bio-inspired optimization algorithm mimicking hunting of white sharks, Support Machine, powerful machine learning technique classification. By combining these two methods, aim to exploit advantages both algorithms enhance accuracy. To evaluate performance in identification, work conducted extensive experiments using diverse dataset clips containing individuals various genders backgrounds. compared results conventional SVM-based state-of-the-art methods. findings demonstrate that achieves superior accuracy traditional approaches. WSO-SVM's ability efficiently explore solution space select optimal SVM parameters contributes its improved performance. Moreover, exhibits robustness handling variations lighting conditions, poses, facial expressions, making it well-suited video-based tasks . outcomes derived approach produced an average FPR 7.14%, Sensitivity 93.06%, Specificity 92.86%, Precision 91.0%, overall 93.00% 45.83 s recognition time s.

Язык: Английский

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A New Hybrid Model to Predict Human Age Estimation from Face Images Based on Supervised Machine Learning Algorithms

Cybernetics and Information Technologies, Год журнала: 2023, Номер 23(2), С. 20 - 33

Опубликована: Июнь 1, 2023

Abstract Age estimation from face images is one of the significant topics in field machine vision, which great interest to controlling age access and targeted marketing. In this article, there are two main stages for human estimation; first stage consists extracting features areas by using Pseudo Zernike Moments (PZM), Active Appearance Model (AAM), Bio-Inspired Features (BIF). second step, Support Vector Machine (SVM) Regression (SVR) algorithms used predict range images. The proposed method has been assessed utilizing renowned databases IMDB-WIKI WIT-DB. general, all results obtained experiments, we have concluded that can be chosen as best

Язык: Английский

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Stacked ensemble learning for facial gender classification using deep learning based features extraction

Cluster Computing, Год журнала: 2024, Номер 27(8), С. 11491 - 11513

Опубликована: Май 27, 2024

Язык: Английский

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Content-based filtering algorithm in social media

Wasit Journal of Computer and Mathematics Science, Год журнала: 2023, Номер 2(1), С. 14 - 17

Опубликована: Март 30, 2023

Content-based filtering is a recommendation algorithm that analyzes user activity and profile data to provide personalized recommendations for content matches user's interests preferences. This widely used by social media platforms, such as Facebook Twitter, increase engagement satisfaction. The methodology of content-based involves creating based on recommending the interests. continually updates personalizes feedback, incorporates strategies promote diversity serendipity in recommendations. While has some limitations, it remains powerful tool arsenal offering efficient discovery experiences at scale.

Язык: Английский

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Using Speech Signal for Emotion Recognition Using Hybrid Features with SVM Classifier

Wasit Journal of Computer and Mathematics Science, Год журнала: 2023, Номер 2(1), С. 18 - 24

Опубликована: Март 30, 2023

Emotion recognition is a hot topic that has received lot of attention and study,owing to its significance in variety fields, including applications needing human-computer interaction (HCI). Extracting features related the emotional state speech remains one important research challenges.This study investigated approach core idea behind feature extraction residual signal prediction procedure difference between original .hence visibility using sets extracting from single when statistical local were used achieve high detection accuracy for seven emotions. The proposed based on fact can provide efficient representations suitable pattern recognition. Publicly available datasets like Berlin dataset are tested support vector machine (SVM) classifier. hybrid trained separately. results indicated some terrible. Some very encouraging, reaching 99.4%. In this article, SVM classifier test with same published previous article will be presented, also comparison works technique emotion techniques.

Язык: Английский

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A combined method based on CNN architecture for variation-resistant facial recognition

International journal of electrical and computer engineering systems, Год журнала: 2023, Номер 14(9), С. 993 - 1001

Опубликована: Ноя. 14, 2023

Identifying individuals from a facial image is technique that forms part of computer vision and used in various fields such as security, digital biometrics, smartphones, banking. However, it can prove difficult due to the complexity structure presence variations affect results. To overcome this difficulty, paper, we propose combined approach aims improve accuracy robustness recognition variations. end, two datasets (ORL UMIST) are train our model. We then began with pre-processing phase, which consists applying histogram equalization operation adjust gray levels over entire surface quality enhance detection features each image. Next, least important eliminated images using Principal Component Analysis (PCA) method. Finally, pre-processed subjected neural network architecture (CNN) consisting multiple convolution layers fully connected layers. Our simulation results show high performance approach, rates up 99.50% for ORL dataset 100% UMIST dataset.

Язык: Английский

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