Factors Affecting Student Academic Performance: A Combined Factor Analysis of Mixed Data and Multiple Linear Regression Analysis by Mohamed El Jihaoui, Oum El Kheir Abra, Khalifa Mansouri

“…This approach aims to enhance learning outcomes, improve educational practices, and promote sustainable education.…”
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Tampered text detection via RGB and frequency relationship modeling by Yuxin WANG, Boqiang ZHANG, Hongtao XIE, Yongdong ZHANG

“…In recent years, the widespread dissemination of tampered text images on the Internet constitutes an important threat to the security of text images.However, the corresponding tampered text detection (TTD) methods have not been sufficiently explored.The TTD task aims to locate all text regions in an image while judging whether the text regions have been tampered with according to the authenticity of the texture.Thus, different from the general text detection task, TTD task further needs to perceive the fine-grained information for real-world and tampered text classification.TTD task has two main challenges.One the one hand, due to the high similarity in texture between real-world texts and tampered texts, TTD methods that only learn from RGB domain features have limited capability to distinguish these two-category texts well.On the other hand, as the different detecting difficulty exists in real-world texts and tampered texts, the network cannot well balance the learning process of the two-category texts, resulting in the imbalance detection performance between real-world and tampered texts.Compared with RGB domain features, the discontinuity of text texture in frequency domain can help the network to identify the authenticity of text instances.Accordingly, a new TTD method based on RGB and frequency information relationship modeling was proposed.The features in the RGB and frequency domains were extracted by independent feature extractors respectively.Thus, the identification ability of tampered texture can be enhanced by introducing frequency information during the texture perception.Then, a global RGB-frequency relationship module (GRM) was introduced to model the texture authenticity relationship between different text instances.GRM referred to the RGB-frequency features of other text instances in the same image to assist in judging the authenticity of the current text instance, which solved the problem of imbalanced detection performance.Furthermore, a new TTD dataset (Tampered-SROIE) was proposed to evaluate the effectiveness of proposed method, which contains 986 images (626 training images and 360 test images).By evaluating on the Tampered-SROIE, the proposed method obtains 95.97% and 96.80% in F-measure for real-world and tampered texts respectively and reduces the imbalanced detection accuracy by 1.13%.The proposed method will give new insights to the TTD community from the perspective of network structure and detection strategy.Tampered-SROIE also provides an evaluation benchmark for future TTD methods.…”
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Police Culture and Change: The Case Of Compstat In Police Organizations by Yusuf Yuksel

“…The findings suggest designing differently the structure and setting of the Compstat meetings in a way to spur brain storming and promote a learning environment. This paper extends existing works on cultural change by presenting a dynamic and contextual understanding of the change process; presenting the perspectives of not only police managers but also officers from different ranks and positions; and using alternative data sources.…”
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Plant Species Composition and Community Perception Towards Landscaping Work Executed at Hawassa University-Main Campus, Ethiopia by Birhanu Kagnew, Firew Kebede

“…In general educational institutions landscaping need to be encouraged to enhance the teaching-learning process, and to make the working environment attractive. …”
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APAH: An autonomous IoT driven real-time monitoring system for Industrial wastewater by Nishant Chavhan, Resham Bhattad, Suyash Khot, Shubham Patil, Aditya Pawar, Tejasvi Pawar, Palomi Gawli

“…APAH utilizes advanced technologies including, the Internet of Things (IoT) and Machine learning (ML) to provide real-time monitoring and control of wastewater treatment processes. …”
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Evaluation of Hand-Scaling Skills of Dental Hygienist Students: Identification of Contact Between Hand-Scaler Blade Tip and Tooth Surface by Tomoko Yui, Sung-Gwi Cho, Yuki Sato, Yasuaki Orita, Ming Ding, Jun Takamatsu, Takahiro Wada, Tsukasa Ogasawara

“…Dental hygienist students require a self-learning simulator to learn the correctness of hand-scaling techniques. …”
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Design and Experimental Evaluation of a Smart Intra-Row Weed Control System for Open-Field Cabbage by Shenyu Zheng, Xueguan Zhao, Hao Fu, Haoran Tan, Changyuan Zhai, Liping Chen

“…The system integrates deep learning technology for accurate identification and localization of cabbage, enabling precise control and dynamic obstacle avoidance for the weeding knives. …”
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The Neural Development of Chinese Lexical Tone Perception: A Mismatch Negativity Study Across Childhood, Adolescence, and Adulthood by Han Wu, Yixiao Zhang, Yiru Liu, Shijun Zhang, Linjun Zhang, Hua Shu, Yang Zhang

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Ethics and AI-Plagiarism in an Academic Environment: Students’ Understanding of Compliance with Author’s Ethics and the Problem of Plagiarism in the Process of Interaction with Gen... by P. V. Sysoyev

“…Everyday, artificial intelligence (AI) is being increasingly integrated into the teaching and learning process at Russian universities. The high level of quality of feedback from AI tools leads to the spread of AI plagiarism – unauthorized borrowing of generative AI materials – among students. …”
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Advantages and challenges of using arterial spin labelling MRI to monitor cerebral blood flow in multi-centre clinical trials of neurodegenerative disease: Experience from the RADA... by Lina Jarutyte, Jan Petr, Nicholas Turner, Patrick G. Kehoe, Henk-Jan Mutsaerts, David L. Thomas

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The spatial and temporal pattern of COVID-19 and its effect on humans’ development in China by X. Xie, E. Naminse, S. Liu, Q. Yi

“…It has been estimated that about 80% of students’ online learning at all schools were not effective due to lack of access to reliable and uninterrupted internet services especially in the rural areas of China.…”
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The mental health impact of COVID-19: the need for community interventions and collaboration for recovery by Nadarajah Rajeshkannan, Daya Somasundaram, Balachandran Kumarendran, Thirunavukarasu Kumanan, Ivan Dinesh Aloysius, Nalayini Sugirthan, Sivanantham Sasikumar, Nalayini Jegathesan

“…There were also positive effects such as better understanding of bio-knowledge, interventions and discoveries, online learning, gratitude toward health-care workers, increased community and family cohesion, reduction in road traffic accidents, and drop in other respiratory infections with their resultant morbidity and mortality. …”
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Acute management of massive pulmonary embolism in pregnancy by Shahin Qadri, Shahin Qadri, Ashwini Bilagi, Ashwini Bilagi, Abha Sinha, Derek Connolly, Derek Connolly, Derek Connolly, Richard Murrin, Shagaf Bakour, Shagaf Bakour, Shagaf Bakour

“…During the post-partum period, thrombectomy is the treatment of choice.Learning objectives•To understand the pathophysiology of massive PE.…”
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Forecasting cardiovascular disease mortality using artificial neural networks in Sindh, Pakistan by Moiz Qureshi, Khushboo Ishaq, Muhammad Daniyal, Hasnain Iftikhar, Mohd Ziaur Rehman, S. A. Atif Salar

“…This study analyzes and forecasts the CVD deaths in the Sindh province of Pakistan using classical time series models, including Naïve, Holt-Winters, and Simple Exponential Smoothing (SES), which have been adopted and compared with a machine learning approach called the Artificial Neural Network Auto-Regressive (ANNAR) model. …”
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Gross and applied anatomy pedagogical approaches in occupational therapy education: protocol for a scoping review by Emily S Ho, Anne Agur, Andrea Duncan, Erica Dove, Kelly Hennessy, Athena Kirou-Mauro, Lorna Aitkens

“…The types of different anatomy pedagogical approaches used and their impact on learning outcomes in occupational therapy education are unclear. …”
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MaDis-Stereo: Enhanced Stereo Matching via Distilled Masked Image Modeling by Jihye Ahn, Hyesong Choi, Soomin Kim, Dongbo Min

“…In stereo matching, Convolutional Neural Networks (CNNs), a class of deep learning models designed to process grid-like data such as images, have traditionally served as the predominant architectures. …”
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Temporal Convolutional Network Approach to Secure Open Charge Point Protocol (OCPP) in Electric Vehicle Charging by Ikram Benfarhat, Vik Tor Goh, Chun Lim Siow, Muhammad Sheraz, Teong Chee Chuah

“…The primary challenge within EVCS architecture lies in defending against various cyberattacks. Several machine learning models, including convolutional neural networks, recurrent neural networks, and long short-term memory, have been employed to enhance EVCS security. …”
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Risk prediction model of cognitive performance in older people with cardiovascular diseases: a study of the National Health and Nutrition Examination Survey database by Hui Wang, Sensen Wu, Dikang Pan, Yachan Ning, Cong Wang, Jianming Guo, Yongquan Gu

“…After which, based on the selected relevant variables, we developed a machine learning model that was predictive of cognitive impairment such as Alzheimer’s diseases in the older people. …”
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Design Considerations of Online Infertility Prevention Training (OIPT): Development and Evaluation by Bahar Baran, Sirin Nur Yaci, Murat Ocal, Digdem Muge Siyez

“…Furthermore, the results of this study show that feedback design is crucial in the navigation of online learning environments. Overall, this study strengthens the idea that while designing online education environments, it is important to determine users’ needs and expectations at first, afterwards conducting usability tests to specify the design challenges. …”
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An optimized deep-forest algorithm using a modified differential evolution optimization algorithm: A case of host-pathogen protein-protein interaction prediction by Jerry Emmanuel, Itunuoluwa Isewon, Jelili Oyelade

“…Deep Forest employs forest structures and leverages deep architecture to learn feature vector information adaptively. However, deep forest-based models have limitations such as manual hyperparameter optimization and time and memory usage inefficiencies. …”
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