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检索条件"丛书名=Lecture Notes in Networks and Systems"

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Predictive Analysis Model to Improve the Control of Eating Disorders in Adolescents in Metropolitan Lima Based on Machine Learning 9th

Predictive Analysis Model to Improve the Control of Eating D...

引用

9th International Congress on Information and Communication Technology (ICICT)

作者： Molina Solano, Jeffery Bryce Castillo Revelo, Valeria Angelica Parasi Falcon, Victor Manuel Univ Peruana Ciencias Aplicadas UPC Prolongac Primavera 2390 Monterrico Santiago De Sur Peru

ISBN: (纸本)9789819732883;9789819732890

Objective Eating disorders in adolescents have been a recurring issue within our society, significantly impacting their mental and physical well-being. This study aims to implement a predictive analysis model based on machine learning and the EDI-3 evaluation method to forecast eating disorders (ED) in adolescents. Method Using the machine learning tool with the Random Forest algorithm and the Eating Disorder Inventory-3 (EDI-3) assessment method, a dataset of information was gathered from a sample of 500 adolescent students. This dataset will contribute to the training of the predictive model, enabling it to identify patterns of eating behaviors in end-users. Results Through data cleaning of the final dataset, 70% of the information was utilized for training the predictive model, and 30% was allocated for subsequent validation. This approach yielded an effectiveness rate of 92.27% upon completion of the training. Furthermore, in order to validate these results, Cronbach's alpha coefficient was employed, resulting in a score of 0.70, indicative of a satisfactory level of reliability. Discussion The results obtained strongly support one of the main objectives of the study conducted, as it significantly surpasses the 85% accuracy threshold. Our results suggest that eating behavior patterns can be crucial factors in making predictions that enable the early identification of positive cases.

关键词： Eating disorders Machine learning Random Forest Inventory of eating disorders

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Exchangeable Integral and Partitioned Parameterization in 3D Shape Modeling

Exchangeable Integral and Partitioned Parameterization in 3D...

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Intelligent systems Conference (IntelliSys)

作者： Vucina, Damir Curkovic, Milan Kragic, Ivo Marinic Univ Split FESB Split Croatia

ISBN: (纸本)9783031477232;9783031477249

Early-stage design and modeling of shape require sufficient generality and global and local shape control which the corresponding numerical tools, typically based on parametric surfaces, must offer. However, these requirements typically materialize into a large number of shape parameters. If numerical shape optimization is to be applied, this maps to excessively high-dimensional search spaces, sometimes prohibitively complex in terms of numerical effort. This paper presents an approach which involves reparameterization into a different set of shape variables based on partitioning of the overall geometry and applying simpler geometric primitives at partitions where it is adequate. Depending on the case, this may lead to short-cutting many iterations of evolutionary shape optimization involving also re-structuring of the genotypes. The transition from partitioned to integral representation is implemented by B-spline surface fitting and the inverse process from integral surfaces to partitioned models is based on feature detection, data-set decomposition and elementary surface fitting. Basic primitives are applied here with more complex ones to be demonstrated in future work.

关键词： 3D Shape Modeling Parametric Surfaces Integral Models Partitioned Models

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A Review of Brain Tumor MRI Classification and Feature Extraction Using Varying Methods 5th

A Review of Brain Tumor MRI Classification and Feature Extra...

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5th International Conference on Communication and Intelligent systems (ICCIS)

作者： Agarwal, Sunil Kumar Gupta, Yogesh Kumar Banasthali Vidyapith Tonk Rajasthan India

ISBN: (纸本)9789819720811;9789819720828

Early detection of brain tumors is critical for saving human lives. MRI is generally used in medical imaging for diagnosing and classifying brain tumors. However, the classification of brain tumors using MRI images is getting more challenging due to the large amount of data and the presence of noise and other objects. Feature extraction is an extremely important step in the brain tumor classification process as it determines the quality of features used for diagnosis. In this work, we examine various feature extraction and classification techniques utilized in MRI image-based brain tumor classification. We have discussed various methods for classification and feature extraction, highlighting the advantages and disadvantages of each. Furthermore, as a result, we analyzed various studies and compared their findings graphically based on performance parameters like accuracy, specificity, and sensitivity. This study's result will be useful for future researchers, providing them with a positive direction towards emerging techniques.

关键词： Brain tumor classification Confusion matrix Feature extraction MRI images

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Enhancing and Personalising Endometriosis Care with Causal Machine Learning

Enhancing and Personalising Endometriosis Care with Causal M...

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2024 International Conference on Computing, Communication, Cybersecurity and AI

作者： Hine, Ariane Webber, Thais Bowles, Juliana Univ St Andrews Sch Comp Sci St Andrews KY16 9SX Fife Scotland Aston Univ Sch Comp Sci & Digital Technol Birmingham B4 7ET W Midlands England Software Competence Ctr Hagenberg Softwarepk A-4232 Hagenberg Austria

ISBN: (纸本)9783031744426;9783031744433

Endometriosis poses significant challenges in diagnosis and management due to the wide range of varied symptoms and systemic implications. Integrating machine learning into healthcare screening processes can significantly enhance and optimise resource allocation and diagnostic efficiency, and facilitate more tailored and personalised treatment plans. This paper discusses the potential of leveraging patient-reported symptom data through causal machine learning to advance endometriosis care and reduce the lengthy diagnostic delays associated with this condition. The goal is to propose a novel personalised non-invasive diagnostic approach that understands the underlying causes of patient symptoms and combines health records and other factors to enhance prediction accuracy, providing an approach that can be utilised globally.

关键词： Female reproductive health Endometriosis Artificial Intelligence Prediction models Diagnosis Menstrual health

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War Strategy Optimization for Optimal Integration of Public Fast Charging Stations in Radial Feeders 4th

War Strategy Optimization for Optimal Integration of Public ...

引用

4th Congress on Intelligent systems (CIS)

作者： Kurian, Jacob Janamala, Varaprasad CHRIST Sch Engn & Technol Dept Elect & Elect Engn Bangalore 560074 Karnataka India

ISBN: (纸本)9789819990429;9789819990436

In light of rising pollution and global warming, there is need for raising the acceptance rate of electric vehicles (EVs) across the globe for sustainable and clean transportation. However, low-voltage electrical distribution networks (EDN) are necessary to provide the electrical power needed to charge the EV batteries. Due to their radial construction and high r/x ration branches;these networks typically suffer from significant energy losses, inadequate voltage profiles, and low stability margins. Therefore, the performance of EDNs shouldn't be further compromised by the incorporation of EV charging stations. In light of this, this work presents a unique heuristic war strategy optimization (WSO) for integrating fast charging stations (FCS) as efficiently as possible utilizing the voltage stability index (VSI). The effect of equivalent EV load penetration in EDS is initially evaluated in terms of loss, voltage profile, and voltage stability for a certain number of EVs. Simulations are executed for IEEE 15-bus system for three different scenarios. The technological advantages seen in the simulations illustrate the efficiency of the suggested technique for real-time adaptation.

关键词： Public fast charging stations War strategy optimization Voltage stability index Electrical distribution networks Loss Voltage profile Voltage stability margin

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Knowledge Representation Technologies for Narratives, Digital Humanities and Cultural Heritage 1

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11st World Conference on Information systems and Technologies (WorldCIST)

作者： Zarri, Gian Piero Sorbonne Univ STIH Lab F-75005 Paris France

ISBN: (数字)9783031456510

ISBN: (纸本)9783031456503;9783031456510

This paper describes the conceptual tools that, in an NKRL context (NKRL = Narrative Knowledge Representation Language), allow us to obtain a (computer-usable) description of full narratives as logically-structured associations of the constituting (and duly formalized) elementary events. These conceptual tools must then be able to formalize those connectivity phenomena - denoted, at surface linguistic level, by logico-semantic coherence links like causality, goal, co-ordination, subordination, indirect speech etc. - which assure the conceptual unity of the whole narrative. The unification-based solutions adopted in this context like, e.g., completive construction and binding occurrences, allow us to take into account the connectivity phenomena by reifying the formal representations used to model the constitutive elementary events.

关键词： Elementary events connectivity phenomena reification completive construction binding occurrences inference rules

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Security and Communication Models of Failures and Attacks on E-services 20th

Security and Communication Models of Failures and Attacks on...

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20th International Workshop on Combinatorial Image Analysis (IWCIA)

作者： Pira, Anna Protasiewicz, Jaroslaw Natl Informat Proc Inst Warsaw Poland

ISBN: (纸本)9783031665936;9783031665943

This article proposes an autonomous and adaptive communication model that is applied during failures and attacks on e-services. We explore what kind of model is relevant in the rapidly changing environments that are typical for agile projects and teams. Then, through an extensive literature review and a practical case study, we critically examine existing communication and security models, which rely primarily on static, well established procedures. We conclude that security protocols must undergo continuous and frequent updates to keep pace with the swiftly evolving design landscape, in which systems and teams progress rapidly. The process of updating communication pathways can prove both costly and error prone. These findings justify the need for a novel approach: a model that recommends appropriate actions in a dynamically changing organisation.

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NLP-Based AI-Driven Resume Screening Solution for Efficient Candidate Selection 9th

NLP-Based AI-Driven Resume Screening Solution for Efficient ...

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9th International Congress on Information and Communication Technology (ICICT)

作者： Sarveshwaran, R. Karthikeyan, S. Cruz, Meenalosini, V Shreyanth, S. Niveditha, S. Rajesh, P. K. Birla Inst Technol & Sci Data Sci & Engn Pilani Rajasthan India MINE AI & Software Dev Bangalore Karnataka India Georgia Southern Univ Dept Informat Technol Statesboro GA USA Rajalakshmi Engn Coll Dept Biotechnol Chennai Tamil Nadu India

ISBN: (纸本)9789819735556;9789819735563

Finding the appropriate candidate for a position can be a difficult and time-consuming effort. The sheer volume of resumes and an expanding applicant pool makes it difficult for hiring managers to find the best-suited applicants quickly and accurately. Effective candidate selection is critical in today's highly competitive employment market. Traditional resume screening processes are time-consuming and prone to bias, resulting in poor recruiting judgments. This study presents an AI-driven resume screening system based on Natural Language Processing (NLP) to address these difficulties. A proprietary spaCy Named Entity Recognition (NER) library is used to extract key data from resumes, including names, organizations, job titles, skills, experiences, and education. The system employs data preprocessing techniques such as data cleansing, structuring, augmentation, text normalization, tokenization, part-of-speech tagging, stop word removal, and lemmatization/stemming to assure correctness and reliability. Following that, the proprietary NER model computes scores for each application based on the retrieved data, resulting in a ranked list of the best applicants. A comparison study was done to compare the suggested approach to traditional resume screening methods. In terms of accuracy, efficiency, and fairness, the results showed that the NLP-driven resume screening solution surpassed traditional approaches. Furthermore, it lowered the time and effort required for resume screening, allowing recruiters to focus on more important activities like candidate assessments and interviews.

关键词： Natural Language Processing (NLP) Resume parser and analyzer Machine learning Vector space model Cosine similarity Term frequency-inverse-document frequency (TF-IDF) Named Entity Recognition (NER)

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Contracts of Transport Services Provision as a Factor of Increasing the Effectiveness of the Urban Public Transport 1

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19th Scientific and Technical Conference of the Transport systems Theory and Practice

作者： Dydkowski, Grzegorz Galecka, Wiktoria Urbanek, Anna Univ Econ Katowice Dept Transport Katowice Poland

ISBN: (数字)9783031531811

ISBN: (纸本)9783031531804;9783031531811

Public financing of urban collective transport enables the provision of urban collective transport services where the revenues from the sale of services do not cover the costs, but it is justified by social reasons and the implementation of a pricing policy that increases the availability and improves the competitiveness of collective transport in relation to travel by passenger cars. It also ensures the stability of service provision and favorable conditions for the purchase of modern low-emission rolling stock and other investments. The paper, based on the experience in the operation of the urban collective transport in the central part of the Silesian Voivodeship, presents the direction of their evolution, so as to reduce the operators burden of the risk of events, which they cannot affect, but at the same time, only to a limited extent, to introduce risks and thereby an element of remuneration due to the services provision, depending on the transport volume. It is expected, that, together with relevant procedures for operators to submit conclusions and suggestions of changes in the transport offer, it will result in the increased productivity and rationality of the services provision by the urban public transport in cities.

关键词： urban transport contracts risk allocation

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Software Patterns for Creating Computer Simulations 13th

Software Patterns for Creating Computer Simulations

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13th Computer Science Online Conference

作者： Sobolev, Yuriy Kreinin, Roman Kudinova, Tatiana Nanay, Farida MIREA Russian Technol Univ Moscow 119454 Russia

ISBN: (纸本)9783031705175;9783031705182

This article provides an overview of Object-oriented, Entity Component System and Functional Reactive Programming software patterns for implementing real-time simulations with numerous interacting components. Three former patterns are used to implement a simple scene in Unity Engine, a comparison of flexibility and applicability is made #CSOC1120.

关键词： Real-Time Simulations Entity Component System Functional Reactive Programming Monadic Stream Functions

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