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Unleashing the Power of Generative Artificial Intelligence: Exploring its Boundless Potential and Overcoming Challenges in Academic Environments 6

Unleashing the Power of Generative Artificial Intelligence: ...

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6th International Conference on Contemporary Computing and Informatics, IC3I 2023

作者： Fegade, Atul Raut, Rajesh Deshpande, Amruta Mittal, Amit Kaul, Natashaa Khanna, Vandana Sri Balaji University BIMM Pune India Indira School of Business Studies PGDM Pune India Chitkara Business School Chitkara University Punjab India Symbiosis Center for Management and Human Resource Development Symbiosis International University Pune India Sri Sukhmani Institute of Engineering & Technology MBA Department Mohali India

ISBN: (纸本)9798350304480

Integrating generative artificial intelligence tools can allow one to manage and develop novel business methods efficiently. With the introduction of self-learning generative artificial intelligence (GAI) tools, the corporate world is trying to figure out the applications and their business implications. Major technology companies like Microsoft, Google, Facebook, etc., have shown enormous interest in investing in ventures developing generative AI tools/models. These tools/models can be experimented with, and their business use is being explored. The study aims to explore the potential uses of generative AI (GAI) in academics through its current capabilities and applications. The study also highlights the potential challenges and concerns arising from using generative AI in academics. The study has used descriptive and quantitative methods to answer the research questions. The study has used a questionnaire based on the Likert scale to measure the significance of indirect variables, viz. perceived ease of use (PEOU) and perceived trust (PT) on direct variable adoption of generative artificial intelligence (AGAI) in academics. The sample size consists of 100 students and 100 university professors. The study Mentions that perceived ease of use (PEOU) positively influences GAI (AGAI) adoption. Also, perceived trust (PT) has a predictive ability of AGIA when controlling for PEOU. The use of generative AI in a few years will become imperative in most human lives, which makes it mandatory to explore the possible ways of its adoption in the mainstream rather than avoiding or restricting its usage in academics. © 2023 IEEE.

关键词： Academic Integrity BARD ChatGPT Education Generative Adversarial Networks Generative Artificial Intelligence Plagiarism

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Earlier peak photosynthesis timing potentially escalates global wildfires

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National Science Review 2024年第09期11卷 171-180页

作者： Gengke Lai Jialing Li Jun Wang Chaoyang Wu Yongguang Zhang Constantin M.Zohner Josep Pe?uelas Quansheng Ge International Institute for Earth System Sciences Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing University Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural ResourcesSchool of Geography and Ocean Science Nanjing University The Key Laboratory of Land Surface Pattern and Simulation Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Huangshan National Park Ecosystem Field Scientific Observation and Research Station of the Ministry of Education Jiangsu International Joint Carbon Neutrality Laboratory Nanjing University Department of Environmental Systems Science Institute of Integrative BiologyETH Zurich CSIC Global Ecology Unit CREAF-CSIC-UAB CREAF Cerdanyola del Vallès

More intense fire weather due to climate change is implicated as a key driver of recent extreme wildfire events. As fuel stock, the role of vegetation and its phenology changes in wildfire dynamics, however is not fully appreciated. Using long-term satellite-based burned areas and photosynthesis observations, we reveal that an earlier peak photosynthesis timing(PPT) potentially acts to escalate subsequent wildfires, with an increase in the global average burned fraction of 0.021%(～2.20 Mha) for every additional day of PPT advancement. Satellite observations and Earth System modeling consistently show that this fire escalation is likely due to intensified drought conditions and increased fuel availability associated with the climate feedback arising from earlier PPT. Current fire-enabled dynamic global vegetation models can reproduce the observed negative correlation between PPT and burned area but underestimate the strength of the relationship notably. Given the continued PPT advancement owing to climate change, the bioclimatic effects of vegetation phenology change suggest a potentially pervasive upward pressure on future wildfires.

关键词： vegetation photosynthesis phenology wildfire climate feedback Earth System model

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Exploring the Mediator in Science Service Learning: Analysis of University Students’ Behavioural Intention to Use Digital Platforms

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The Asia-Pacific Education Researcher 2022年第6期32卷 841-854页

作者： Mou, Tsai-Yun Kao, Chia-Pin Lin, Kuen-Yi Osborne, Michael Department of Visual Arts National Pingtung University Pingtung Taiwan Department of Child Care and Education Southern Taiwan University of Science and Technology Tainan Taiwan Department of Technology Application & Human Resource Development National Taiwan Normal University Taipei Taiwan Adult and Lifelong Learning School of Education University of Glasgow Glasgow UK

This study examined two mediators of university students’ behavioural intention to use digital platforms in the context of science service learning in Taiwanese universities. Based on the technology acceptance model (TAM), we proposed two cognitive variables as antecedents, self-efficacy and science trust, to verify their influences on students’ behavioural intention. We further investigated two mediators, perceived usefulness and perceived ease of use, to examine to what extent they had effects on students’ intention. Questionnaire data were collected from 282 university students who participated in a science service project. A structural equation model (SEM) procedure was used to test the direct and indirect relationships between the variables. The results showed that both self-efficacy and science trust had direct influences on perceived usefulness and perceived ease of use. The two mediators also had direct effects on students’ behavioural intention. Nevertheless, as a mediating variable, only perceived ease of use effectively mediated the relationships between both self-efficacy and science trust and students’ behavioural intention. Findings of this research could provide some suggestions to enhance students’ behavioural intention for institutions where science service learning is a required project/programme.

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Global Terrestrial Ecosystem Carbon Flux Inferred from TanSat XCO_(2)Retrievals

Journal of Remote Sensing

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Journal of Remote Sensing 2022年第1期2022卷 299-310页

作者： Hengmao Wang Fei Jiang Yi Liu Dongxu Yang Mousong Wu Wei He Jun Wang Jing Wang Weimin Ju Jing MChen Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology International Institute for Earth System ScienceNanjing UniversityNanjing 210023China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing 210023China Institute of Atmospheric Physics Chinese Academy of SciencesBeijing 100029China Department of Geography University of TorontoTorontoOntarioCanada M5S3G3

TanSat is China’s first greenhouse gases observing *** recent years,substantial progresses have been achieved on retrieving column-averaged CO_(2)dry air mole fraction(XCO_(2)).However,relatively few attempts have been made to estimate terrestrial net ecosystem exchange(NEE)using TanSat XCO_(2)*** this study,based on the GEOS-Chem 4D-Var data assimilation system,we infer the global NEE from April 2017 to March 2018 using TanSat XCO_(2).The inversion estimates global NEE at−3.46 PgC yr^(-1),evidently higher than prior estimate and giving rise to an improved estimate of global atmospheric CO_(2)growth ***,our inversion greatly increases the carbon uptakes in northern mid-to-high latitudes and significantly enhances the carbon releases in tropical and southern lands,especially in Africa and India *** increase of posterior sinks in northern lands is mainly attributed to the decreased carbon release during the nongrowing season,and the decrease of carbon uptakes in tropical and southern lands basically occurs throughout the *** against independent CO_(2)observations and comparison with previous estimates indicate that although the land sinks in the northern middle latitudes and southern temperate regions are improved to a certain extent,they are obviously overestimated in northern high latitudes and underestimated in tropical lands(mainly northern Africa),*** results suggest that TanSat XCO_(2)retrievals may have systematic negative biases in northern high latitudes and large positive biases over northern Africa,and further efforts are required to remove bias in these regions for better estimates of global and regional NEE.

关键词： estimates remove attributed

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Determinants of Cybercrime Victimization: Experiences and Multi-stage Recommendations from a Survey in Cameroon 14th

Determinants of Cybercrime Victimization: Experiences and Mu...

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14th EAI International Conference on Towards new e-Infrastructure and e-Services for Developing Countries, AFRICOMM 2022

作者： Ntsama, Jean Emmanuel Tchakounte, Franklin Tchakounte Tchuimi, Dimitri Faissal, Ahmadou Fotso Kuate, Franck Arnaud Effa, Joseph Yves Udagepola, Kalum Priyanath Atemkeng, Marcellin Department of Mathematics and Computer Science Faculty of Science University of Ngaoundéré Ngaoundéré Cameroon Yaoundé Cameroon Department of Human Resource Economics Faculty of Economics and Management University of Yaoundé II SOA Yaoundé Cameroon Department of Physics Faculty of Science University of Ngaoundéré Ngaoundéré Cameroon Department of Information and Computing Sciences Scientific Research Development Institute of Technology Loganlea Australia Department of Mathematics Rhodes University Makhanda South Africa

ISBN: (纸本)9783031348952

Cybercrimes are multiplying and spreading at an elusive speed commensurate with the emerging technologies of the fourth revolution. Their sophistication and user’s vulnerability to attacks catalyze their success. Several surveys have been conducted to determine the factors favoring victimization. However, they can only be applied within a contextual framework since each ecosystem has particularities. Attempts in this direction are unavailable in Cameroon where cybercrimes cost 12.2 billion CFA in 2021. This work consists of a semi-direct survey conducted in Cameroon in 2021 to provide the determinants explaining the most frequent cybercriminal techniques, the vulnerabilities left by the users, the most targeted population segments, and the socio-demographic and economic factors justifying this security fragility. The results relate to 370 questionnaires collected throughout the territory. According to descriptive statistics and the chi-square test, the explanatory variables of cybercrime victimization are gender, age, intellectual level, level of digital knowledge, level of Information and Communication technology (ICT) proficiency, type of equipment used, the mobile and desktop operating system used, the possession of an anti-virus/anti-spam and the marital status. Within this work, we have identified threats and their drivers and a theoretical framework has been provided with several stages that could be followed to contain cybercrime. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Statistical tests

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Effectiveness of a short-Term soy nutrition education intervention on nutrition knowledge and self-efficacy scores of rural elderly Zambian women

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Nutrition and Healthy Aging 2023年第1期8卷 97-108页

作者： Mukherjee, Upasana Dawson, John A. Chalwe, Joseph Musonda Oldewage-Theron, Wilna Youth and Families Program Unit College of Agriculture Human and Natural Resource Sciences Washington State University Extension Pullman WA United States Department of Nutritional Sciences College of Human Sciences Texas Tech University Lubbock TX United States Department of Economics Applied Statistics and International Business New Mexico State University Las Cruces NM United States Department of Health Sciences Faculty of Applied and Computer Sciences Vaal University of Technology Vanderbijlpark South Africa Department of Sustainable Food Systems and Development Faculty of Natural and Agricultural Sciences University of the Free State Bloemfontein South Africa

BACKGROUND: Women are at most risk for chronic diseases which can be prevented by healthy dietary choices. Evidence exists that nutrition education interventions (NEIs) are effective in educating community-dwelling women to modify their behavior for better health outcomes. OBJECTIVES: The objectives of this study were to implement a need-based, tailored NEI and evaluate its effectiveness in improving nutrition and soy knowledge and self-efficacy of participants in the intervention group compared to a control group. METHODS: A quasi-experimental pre-post-study design was used in a convenience sample of 149 women from the copper belt region of Zambia. The health belief model (HBM) informed the NEI, which consisted of six lessons, three cooking demonstrations, and an illustrative recipe book. Nutrition and soy knowledge scores and self-efficacy scores were evaluated using validated and reliable questionnaires. Data were analyzed using IBM SPSS software, version 26, and mean change scores in knowledge and self-efficacy were compared between the intervention and control groups. RESULTS: The average improvement in the scores for total nutrition knowledge and all six sub-sections of knowledge was significantly higher in the intervention group compared to the control group. The mean total self-efficacy score for the intervention group improved significantly (p=5.7767e-20) from a pre-intervention score of 29.9±7.4 to 57.3±7.0 after the implementation of the NEI. No significant improvement (p=0.904) in the control group was observed. CONCLUSIONS: A short-Term, multi-component NEI was effective in improving the nutrition and soy knowledge and soy cooking self-efficacy of the participants in the intervention group. © 2023-The authors. Published by IOS Press.

关键词： attitudes knowledge Nutrition education self-efficacy women Zambia

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Ambient formaldehyde concentrations in summer in 30 Chinese cities and impacts on air cleaning of built environment

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Energy and Built Environment 2024年第4期5卷 493-499页

作者： Shuolin Qiu Zirui He Guangdong Liu Zhen Ding Zhongming Bu Jianping Cao Wenjing Ji Wei Liu Chunxiao Su Xinke Wang Fan Liu Ting Li Hua Qian Cong Liu School of Energy and Environment Southeast UniversityNanjingJiangsu210096China China Green Development Investment Group Co.LTD Beijing100000China Department of Environmental Health Jiangsu Provincial Center for Disease Control and PreventionNanjingJiangsu210009China Department of Energy and Environmental System Engineering Zhejiang University of Science and TechnologyHangzhouZhejiang310023China School of Environmental Science and Engineering Sun Yat-sen UniversityGuangzhouGuangdong510006China School of Civil and Resource Engineering University of Science and Technology BeijingBeijing100083China Institute for Health and Environment Chongqing University of Science and TechnologyChongqing401331China School of Environment and Architecture University of Shanghai for Science and TechnologyShanghai200093China School of Human Settlements and Civil Engineering Xi’an Jiaotong UniversityXi’an710049ShaanxiChina Tsinghua University Beijing100084China

Formaldehyde is an important carcinogen commonly found *** indoor sources have been intensively *** study on outdoor formaldehyde concentration,which is potentially an important source to indoors,remains *** study attempts to characterize temporal and spatial distribution of the atmospheric formalde-hyde concentration in Chinese *** variation of ambient formaldehyde was examined in 6 cities and peak hours were identified between 12:00 pm and 3:00 ***,outdoor formaldehyde concentrations were measured in the peak hours in 30 cities during the summer months of Jul.-Aug.,*** formaldehyde concentrations in the peak hours fell into a range of 0.005-0.087 mg/m^(3)(median value is 0.027 mg/m^(3)),87.7%of which have exceeded the chronic reference exposure criteria of 0.009 mg/m^(3) set by Office of Environmental Health Hazard *** risk analysis suggests that exposure to ambient formaldehyde could cause a median carcinogenic risk of 1.9×10^(−5)(3.17×10^(−6)-6.13×10^(−5)),higher than threshold limit of 10−*** correlation analysis of the 30 cities shows that ambient summertime atmospheric formaldehyde concentrations of the city are positively correlated with its Gross Domestic Product(r=0.48).We also found that the outdoor formaldehyde concentrations in urban areas(median:0.017 mg/m^(3))is slightly higher than those in suburban areas(median:0.013 mg/m^(3)).Results here prove that outdoor formaldehyde is ubiquitous in Chinese cities and reduces effectiveness of ventilation in dilution indoor *** it would underestimate air cleaner capacity needed by a factor of about *** should be accounted for in health analysis and air quality engineering control design of built environment in the future.

关键词： Atmospheric formaldehyde Temporal distribution Health risk Ventilation efficiency

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Behavioral-pattern exploration and development of an instructional tool for young children to learn AI

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Computers and Education: Artificial Intelligence 2021年 2卷

作者： Hsu, Ting-Chia Abelson, Hal Lao, Natalie Tseng, Yu-Han Lin, Yi-Ting Department of Technology Application and Human Resource Development National Taiwan Normal University Taiwan Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology United States

This study aimed at developing an instructional tool for the artificial intelligence education of young students, and used learning analytics to identify the sequential learning behavioral patterns of students during the process of learning with the instructional tool. The instructional experiment took 9 weeks. The first stage of the course was 5 weeks spent on individual learning of MIT App Inventor and Personal Image Classifier. The second stage was 4 weeks spent on cooperative learning to make a robot car and play a computational thinking board game. In the second stage, the students worked in pairs to make the robot car. Finally, they played the computational thinking board game with the personal image classification application they developed in the first stage and the robot car they made in the second stage. The innovative studies found meaningful behavioral patterns when the young students learned the application of artificial intelligence with the instructional tool developed and proposed in the study. © 2021 The Author(s)

关键词： Students

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Multimodal Brain Tumor Segmentation Using a Dual-Branch Vision Transformer Integrated with Region-Attention Fusion Network

Multimodal Brain Tumor Segmentation Using a Dual-Branch Visi...

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Integrated Circuits and Communication Systems (ICICACS), IEEE International Conference on

作者： Sunita Yadwad Rajeswari C D. Nirmal Raj Pravin Dange Department of Computer Science and Engineering Faculty of Engineering and Technology Parul University Gujarat India Department of Computer Science and Engineering Chennai Institute of Technology Kundrathur India Balaji Institute of Management and Human Resource Development (BIMHRD) Pune India Symbiosis Institute of Management Studies Symbiosis International (Deemed University) Pune India

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

Accurate segmentation of brain tumors is a critical task in medical imaging, aiding diagnosis, treatment planning, and prognosis. This paper introduces a novel framework for brain tumor segmentation that leverages a Dual-Branch Vision Transformer (DB-ViT) integrated with a Region-Attention Fusion Network (RAFN) to address the limitations of conventional convolutional neural networks. The DB-ViT processes multimodal MRI sequences, including T1, T1c, T2, and FLAIR, to extract global contextual features while preserving modality-specific information. Simultaneously, the RAFN enhances segmentation precision by refining local features and focusing on critical regions of interest through an attention mechanism. The proposed method effectively combines global and local feature representations, ensuring accurate delineation of tumor boundaries. Extensive experiments were conducted on the BraTS dataset, demonstrating the superiority of our approach over existing methods such as U-Net, Attention U-Net, and TransUNet. Quantitative evaluation metrics, including Dice Score and Intersection over Union (IoU), indicate significant improvements in segmentation accuracy. The framework also achieves computational efficiency and robustness across diverse tumor morphologies. Visual results further validate its ability to enhance boundary delineation, particularly in heterogeneous tumor regions. The proposed methodology represents a significant advancement in automated medical image analysis, offering potential for real-time clinical applications. Future work aims to explore broader clinical validation and real-time deployment of this framework.

关键词： Measurement Image segmentation Computer vision Accuracy Attention mechanisms Refining Brain tumors Transformers Real-time systems Planning

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Enhancing Image Search Engine Accuracy Using Psychological Intention Diagrams

Enhancing Image Search Engine Accuracy Using Psychological I...

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Integrated Circuits and Communication Systems (ICICACS), IEEE International Conference on

作者： Aswathi KP Sunita Yadwad D. Nirmal Raj Shailesh Rastogi Department of Computer Science and Engineering Chennai Institute of Technology Chennai India Department of Computer science and Engineering Faculty of Engineering and Technology Parul University Vadodara India Balaji Institute of Management and Human Resource Development (BIMHRD) Pune India Symbiosis Institute of Business Management Nagpur Symbiosis International (Deemed University) Pune India

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

As the Internet becomes increasingly image-centric, users face substantial challenges in efficiently locating desired images due to the inherent limitations of image search engines in interpreting visual content and keyword ambiguity. This paper introduces an innovative solution employing psychological intention diagrams to enhance search accuracy. These diagrams harness historical data to depict the search intentions associated with specific keywords, reflecting both user and web designer perspectives. By integrating these diagrams, our proposed search engine significantly refines its ability to predict and retrieve the most relevant images. The implementation of this system involves constructing two types of intention diagrams: one based on past user queries and another derived from the intentions of web designers for cases without historical user data. This dual approach not only captures the semantic essence of images more effectively but also addresses the multi-faceted meanings of search keywords. Our experimental results confirm that incorporating psychological dimensions into image search mechanisms substantially improves precision, facilitating more accurate and user-aligned image retrieval. This pioneering approach is the first to apply psychological profiling in enhancing image search engine functionalities, marking a significant advancement in digital image retrieval technologies.

关键词： Visualization Accuracy Digital images Semantics Image retrieval Psychology Machine learning Search engines Internet Standards

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