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检索条件"任意字段=1st Conference on Information Technology and Data Science, CITDS 2020"

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citds 2020 - Proceedings of the 1st conference on information technology and data science

CITDS 2020 - Proceedings of the 1st Conference on Informatio...

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1st conference on information technology and data science, citds 2020

The proceedings contain 27 papers. The topics discussed include: deep learning-based method for detecting Cassini-Huygens spacecraft trajectory modifications;multi-resident location detecting in smart home;smartwatch activity recognition using *** framework;possible neural models to support the design of prime Convo assistant;inversion of artificial neural networks for WiFi RSSI propagation modeling;on the time series of antivirus testing procedures;theoretical and simulation results for a 2-type network evolution model;the impact of servers reliability on the characteristics of cognitive radio systems;and recent results on finite-source retrial queues with collisions and impatient customers in the orbit.

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Attention Span and it's Correlation with Mental Health 1

Attention Span and it's Correlation with Mental Health

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1st International conference on AIML-Applications for Engineering and technology, ICAET 2025

作者： Shah, Richa Bewoor, Laxmi Rak, Sarthak Patne, Ayush Vishwakarma Institute of Information Technology Artificial Intelligence and Data Science Pune India Vishwakarma Institute of Information Technology Computer Engineering Pune India

ISBN: (纸本)9798350355611

This paper delves into the correlation between attention span and mental health. Attention span is the ability to focus on a task before being distracted by certain factors. It ranges from 2 seconds to more than 20 minutes. Meanwhile, mental health constitutes a person's psychological, sociological, and emotional well-being. Using a clustering algorithm, this research seeks to provide a concrete relation between the two across an age group of 18-25. © 2025 IEEE.

关键词： Electronic health record

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1st International conference on Computer Applied science and information technology, ICCASIT 2020

1st International Conference on Computer Applied Science and...

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1st International conference on Computer Applied science and information technology, ICCASIT 2020

The proceedings contain 179 papers. The topics discussed include: the influence of computer network on the ideological and political work of college students;application of computer application technology in employment guidance education in higher vocational colleges;inheritance of intangible cultural heritage of Oroqen ethnic group based on computer network culture;the application of computer image recognition technology in textile and clothing;the key problems of intelligent quality control of green building are analyzed based on computer information data;coupled discrete-finite element method for settlement analysis of transition zone between ballasted and ballastless track with polyurethane reinforcement based on computer aided technology;research on the detection algorithm of data integrity verification results in big data storage;translation and development planning of literary tourism based on computer semiotic analysis;and research on the influence of the integration of public art and computer on urban culture from the perspective of media ecology.

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Optimization of Intelligent Substation Location Scheme Based on data Fusion technology and Artificial Intelligence 24

Optimization of Intelligent Substation Location Scheme Based...

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1st International conference on Image Processing Machine Learning and Pattern Recognition

作者： Wang, Zhipeng Xie, Dan Feng, Cai He, Chunhui Lan, Feng State Grid Shandong Elect Power Co Econ &Technol Res Inst Beijing Peoples R China

ISBN: (纸本)9798400707032

At present, the world is experiencing the second information wave with data as the core and the Internet as the means, and the society is shifting from IT (information) era to DT (data) era. The planning of substation location is mainly based on the existing satellite vector data through the software simulation platform, and the optimal scheme and path planning are often based on the experience of designers in actual design and erection. However, with the continuous expansion of the project scale and increasing complexity, it has brought great challenges to the design work. Therefore, substation location needs to be combined with current data fusion technology and artificial intelligence technology to effectively improve the intelligent level of substation location.

关键词： Substation location data fusion technology Artificial intelligence technology Weighted Voronoi diagram

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SupplyRx: Intelligent Pharmaceutical Inventory and Supply Monitoring System 1

SupplyRx: Intelligent Pharmaceutical Inventory and Supply Mo...

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1st International conference on Advances in Computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Singh, Dhruvveer Singh, Harkamal Kumar, Shubham Garg, Vanshit Kumar, Vijay Chahar, Narendra Kumar Dr B R Ambedkar National institute of Technology Department of Information Technology Jalandhar India

ISBN: (纸本)9798331518578

To guarantee the availability of necessary medications and reduce waste in healthcare systems, effective management of drug inventory and supply chains is vital. The goal of the Drug Inventory and Supply Chain Tracking System is to make the distribution, storage, monitoring, and acquisition of pharmaceuticals more efficient Utilizing cutting-edge technologies, this system offers automated inventory updates, real-time tracking, and demand forecasting predictive analytics. By keeping precise records of medication movements and expirations, it improves regulatory compliance, guarantees supply chain transparency, and lowers the possibility of stockouts or overstocking. The architecture of the system incorporates modules for point-of-sale tracking, transportation logistics, warehouse operations, and supplier management. To further protect sensitive data, it integrates access control and user authentication and access control systems to protect private information. This technology helps healthcare organizations save money, enhance patient outcomes, and run more efficiently by promoting data-driven decision-making and resource optimization. © 2025 IEEE.

关键词： Access control

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Analysis of data Extraction Techniques on Medical Health Records 1

Analysis of Data Extraction Techniques on Medical Health Rec...

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1st IEEE International conference on Electronics, Computing, Communication and Control technology, ICECCC 2024

作者： Ruwali, Abhishek Bisht, Lavanya Narang, Harshit Das, Purushottam Dhanalakshmi, R. Yadav, Satya Prakash Graphic Era Hill University Computer Science and Engineering Dehradun India Indian Institute of Information Technology Department of Computer Science and Engineering Tamil Nadu Tiruchirappalli India Department of Computer Science and Engineering Greater Noida201306 India

ISBN: (纸本)9798350371802

Extracting cancer-related information from unstructured text presents challenges that require accurate identification and extraction techniques. This study compares three methods: keyword-based matching, regular expression pattern matching, and deep learning-based approaches. The study proposes evaluation metrics including file comparison, cosine similarity, and k-means clustering with Jaccard similarities. The findings demonstrate that the deep learning- based approach achieves the highest accuracy of 99.06%, outperforming the keyword-based (34.27%) and regular expression methods (93.58%). © 2024 IEEE.

关键词： Pattern matching

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Kissan Konnect: AI-Powered Plant Disease Control System Fusing Temporal data Modeling with Deep Learning 1

Kissan Konnect: AI-Powered Plant Disease Control System Fusi...

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1st International conference on Software, Systems and information technology, SSITCON 2024

作者： Verma, Manav Singh, Ajay Pal Singh, Japneet Kumari, Sakshi Chandigarh University Department of Computer Science and Engineering Mohali India

ISBN: (纸本)9798350352931

This research introduces a sophisticated framework tailored for the proactive identification and management of viral afflictions in plants, concentrating on five primary culprits: Yellow Curl Virus, Mosaic Virus, Late Blight Virus, Chlorosis, and Bacterial Spot Virus. By seamlessly fusing remote sensing technology, machine learning algorithms, and comprehensive data analytics, the system enables real-time surveillance and precise forecasting of potential disease outbreaks. This innovative tool equips agriculturists, researchers, and policymakers with actionable insights, fostering the early prediction of viral incursions. Consequently, it supports the strategic deployment of targeted interventions, which not only boost crop vitality and yield but also safeguard long-term food security. © 2024 IEEE.

关键词： Plant diseases

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A Binary and Multi Classification Model on Tax Evasion:A Comparative study 1

A Binary and Multi Classification Model on Tax Evasion:A Com...

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1st International conference on Emerging Technologies for Dependable Internet of Things, ICETI 2024

作者： Shujaaddeen, Abeer Abdullah Ba-Alwi, Fadl Mutaher Zahary, Ammar T. Alhegami, Ahmed Sultan Alsabry, Ayman Al-Badani, Abdulkader M. Faculty of Computer and Information Technology Sana’a University Sana’a Yemen International University of Technology Twintech Malaysia Department of Computer Science Faculty of Computing and Information Technology University of Science and Technology Sana’a University Sana’a Yemen Department of Computer Science International University of Technology Twintech Sana’a Yemen Faculty of Science and Engineering Department of Computers Aljazeera University Ibb Yemen

ISBN: (纸本)9798331533557

In this paper, a model was built to compare the performance of the following machine learning (ML) models: DT, RF, SVM, and MLP, using two types of classification: binary classification and multi classification. The researchers concluded that the MLP classifier was the most efficient using multi classifications, as the classifier gave an accuracy of 99.77%, a recall of 93.25%, a precision of 92.02%, and an F-score of 92.63%. Using the dataset provided by the Tax Authority of Yemen, which is related to the commercial and industrial profits tax explained in detail in other papers for the same authors, which consists of 1083 record, after the preprocessing of data. © 2024 IEEE.

关键词： Contrastive Learning

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Investigating Bigdata Analytics Adoption in Higher Education: Pilot study 1

Investigating Bigdata Analytics Adoption in Higher Education...

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1st IEEE Karachi Section Humanitarian technology conference, Khi-HTC 2024

作者： Salleh, Noor Afzan Shah, Asadullah Talpur, Samar Raza Ali, Hazirah Bee Yusof Ali, Najma Imtiaz Mat, Che Rosmawati Che International Islamic University of Malaysia Kuliyyah of Information and Communication Technology Malaysia International Islamic University of Malaysia Kulliyah of Information and Communication Technology Kuala Lumpur Malaysia Sukkur IBA University Kandhkot Campus Pakistan University Malaysia of Computer Science and Engineering Kuala Lumpur Malaysia Institute of Mathematics and Computer Science University of Sindh Jamshoro Pakistan Universiti Kuala Lumpur Kuala Lumpur Malaysia

ISBN: (纸本)9798350373042

In a data-centric era, big data analytics (BDA) in promoting sustainable development and data-driven decision-based culture has gained recent attention in various studies. Although big data analytics does enhance innovation performance, there is little empirical research focused on big data analytics and higher education organizational performance. Therefore, the proposed framework underpins the Resources Based-View and Dynamic Capability View to investigate how big data analytics affect higher education institutions. The proposed framework was validated through a pilot study of 48 respondents from higher education institutions in Malaysia by employing a purposive sampling method using PLS-SEM. The analysis provides interesting implications on multiple perspectives for stakeholders, policymakers and big data service providers in higher education institutions. © 2024 IEEE.

关键词： Big data

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Optimizing Electricity Theft Detection using Neural Turing Machines and Machine Learning 1

Optimizing Electricity Theft Detection using Neural Turing M...

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1st International conference on Software, Systems and information technology, SSITCON 2024

作者： Buyukbicakci, Erdal Bulat, Selcuk Senthilkumar, C. Rajesh, A. Sivasundaram, Malatthi Palla, Rama Raju Svsv University of Applied Sciences Information Technologies Vocational Highschool Department of Computer Technologies Sakarya Turkey Institute of Natural Sciences Sakarya University Turkey Erode Sengunthar Engineering College Department of Artificial Intelligence and Data Science Erode India Erode Sengunthar Engineering College Department of Cse Erode India Ksr College of Engineering Department of Computer Science and Design Tiruchengode India Vignan's Institute of Information Technology Department of Cse Duvvada India Turkish Standards Institution Department of Nanoscience and Nanoengineering Istanbul Turkey

ISBN: (纸本)9798350352931

Electricity theft detection (ETD) is crucial for smart grids to maintain their cost-effectiveness. Current approaches for identifying theft struggle with large datasets of electricity use owing to problems with missing values, data variance, and nonlinear patterns in the data;furthermore, an integrated infrastructure to coordinate the study of electricity load data is not currently in *** suggested method trains models after feature extraction and stage preprocessing. data normalization, missing value imputation, and data cleansing are all components of data preprocessing. Utility data sets often suffer from inconsistent and missing data as a result of manual and unsynchronized meter reading and registering processes;however, this can be mitigated through the feature extraction process. All the way through training, the proposed approach stuck with the NTM paradigm. The average accuracy of this state-of-the-art approach is 94.22%, which is higher than RNN and ELM. © 2024 IEEE.

关键词： Adversarial machine learning

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