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Impacts of Swachh Bharat Mission on Health and Communicable Disease control: A Systematic Review Protocol

HEALTH SCIENCE REPORTS 2025年第2期8卷 e70425页

作者： Varshney, Karan Khatri, Chirag Lamichhane, Prabhat Deakin Univ Sch Med Geelong Australia Monash Univ Sch Publ Hlth & Prevent Med Melbourne Australia La Trobe Univ Dept Publ Hlth Melbourne Australia

Background and AimsSwachh Bharat Mission (SBM) is a major initiative led by the Government of Bharat (India) in 2014 to improve sanitation across the country. While the government has received international praise for SBM's achievements, the health impacts of this initiative are not well understood, and to date, no systematic review has been conducted on the topic. In this protocol, we aim to describe our methodology for systematically reviewing the literature to determine the impacts of SBM on communicable disease control and population health outcomes across *** protocol describes the process that will be taken for our systematic review. The review will follow the Preferred Reporting Items for Systematic review and Meta-analysis guidelines. Searches will be conducted in Scopus, Embase, Medline, Web of Science, Cumulated Index to Nursing and Allied Health Literature, PubMed, and Global Health. Original, full-text research articles conducted after October 2014 (the enactment of SBM) will be eligible for inclusion, as will be gray literature. modeling studies will be excluded from this review. Studies which analyze impacts/trends relating to health or communicable disease control in any region of Bharat will be eligible for inclusion Included studies will assess at least one of the following: impact on infectious disease incidence/prevalence and morbidity/mortality, infant and under-five mortality, nutritional impacts (including stunting, underweight and wasting) or non-communicable disease rates. Study quality will be assessed using the Kmet checklist. Where possible, data will be pooled and synthesized to determine overall findings and *** review will highlight the extent to which SBM has, or has not, had lasting impacts on health and communicable disease control. The findings of this review can have important implications in shaping and guiding the ongoing implementation of SBM across Bharat.

关键词： communicable disease infection sanitation Swachh Bharat

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Selective Miniature Circuit Breaker Operation Mechanism Motion process Mechanical Properties Optimization analysis

Selective Miniature Circuit Breaker Operation Mechanism Moti...

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International conference of Electrical, Electronic and Networked Energy Systems, EENES 2024

作者： Peng, Jin Wang, Xianbing Huang, Kecheng Peng, Jiyu School of Mechanical and Electrical Engineering Chuzhou Univesity Chuzhou239000 China School of Electrical and Information Engineering Anhui University of Science and Technology Huainan232001 China

ISBN: (纸本)9789819620418

A force characteristics mathematical modeling of motion process and optimization method was proposed to handle the selective miniature circuit breaker (SMCB) performance issue. The proposed solution resolved the collaboration of force characteristics among the operation mechanism components, and improved the miniature circuit breaker control characteristics. Based on the operation mechanism principle, it established the mechanical model of closing, breaking and tripping process. The Adams simulation platform was set up to analyze the operating mechanism motion process force energy distribution. Besides, it built the mathematical model for the operation mechanism structural parameters, and analyzed the topology optimization design via the quantum particle swarm algorithm. The optimized handle operating force was 7.4 N, and the operation mechanism achieved the optimal operation performance on the basis of reliable closing of miniature circuit breaker. The optimized tripping force was 0.48 N, which minimized the friction between the extension plate upper end and the lock catch upper end and achieved the miniature circuit breaker quick release. Finally, it designed the 100 A SMCB experiment prototype. The experimental results showed that the proposed prototype achieved good control performance, and the operation mechanism force characteristics collaborated well with the electromagnetic mechanism motion threshold characteristics under short-circuit. Thus, it met the selective protection goal. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Particle swarm optimization (PSO)

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analysis of Graphical Responses in Energy Efficiency Simulators

Analysis of Graphical Responses in Energy Efficiency Simulat...

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International Joint conference on Mechanics, Design Engineering and Advanced Manufacturing, JCM 2024

作者： García, Ruth Fernández Fernández, Marta Menéndez Diez, Rafael Rodríguez-Galindo Gero, María Belén Prendes Miguel, Diego José Guerrero Cerra, Pablo Pando Mining Tecnology Topography and Structures Department University of León León24071 Spain Construction and Manufacturing Engineering Department University of Oviedo Gijón33203 Spain

ISBN: (纸本)9783031728280

Year by year, compliance with energy efficiency standards in buildings becomes more and more demanding in order to carry out the different energy transitions established by international institutions to implement the increasingly demanding energy plans for this sector. These objectives affect all the areas involved, not only the building sector, but also the energy sector, administrations and even the end user. For this reason, the control of all the principles of sustainable building is complex due to the amount of data generated in the process, making necessary a series of tools capable of managing all this information, looking for the maximum optimization in the results, which is consumption. One of these data and the basis of the whole process is the geometry of the building, a priority requirement in the process. The work of more than 20 years with the calculation and energy management software supported by the Spanish administration shows a commitment to calculation and estimation programs, to the clear detriment of geometric definitions, which leads to an energy over-dimensioning contrary to the final and real objective sought. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Green buildings

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A Taxonomy for Enhancing Metacognitive Adaptivity and Personalization in Serious Games Using Multimodal Trace data 10th

A Taxonomy for Enhancing Metacognitive Adaptivity and Person...

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10th Joint International conference on Serious Games

作者： Azevedo, Roger Dever, Daryn Wiedbusch, Megan Brosnihan, Annamarie Delgado, Tara Marano, Cameron Patel, Milouni Smith, Kevin Univ Cent Florida Sch Modeling Simulat & Training Orlando FL 32826 USA Univ Florida Inst Adv Learning Technol Sch Teaching & Learning Coll Educ Gainesville FL 32611 USA

ISBN: (纸本)9783031741371;9783031741388

This paper presents a theoretically-driven and empirically-based preliminary taxonomy for optimizing metacognitive adaptivity and personalization in serious games by leveraging multimodal trace data. By integrating diverse sources of multimodal trace data, such as eye tracking, log files, concurrent verbalizations, facial expressions of emotions, physiological sensors, and screen recordings, the taxonomy aims to capture nuanced insights into learners' metacognitive processes during gameplay. Our taxonomy focuses on six specific metacognitive processes, including judgments of learning (JOLs), feelings of knowing (FOKs), content evaluations (CEs), monitoring progress towards goals (MPTG), and monitoring use of strategies (MUS), and self-questioning (SQ). These metacognitive processes are critical in learning, reasoning, and problem solving across several learning technologies, including serious games. We provide operational definitions and examples of how each process can be captured by each multimodal data channel during gameplay. More specifically, the taxonomy facilitates the development of serious games that dynamically adjust difficulty levels, provide personalized feedback, and offer tailored scaffolding to enhance metacognitive development using advanced machine learning techniques, including generative AI, for real-time multimodal analysis. Through this taxonomy, researchers and developers can design and evaluate adaptive serious games that optimize metacognitive awareness, monitoring, regulation, and reflection, contributing to advancing the science of learning with serious games. Lastly, future research needs to empirically test these recommendations, andwe expect further refinements based on such testing with different serious games across various learners, tasks, domains, and educational contexts.

关键词： Serious games Metacognition Adaptivity Personalization Multimodal data Taxonomy

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Life Cycle Assessment and Sustainability analysis of Anaerobic Digestion

Life Cycle Assessment and Sustainability Analysis of Anaerob...

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Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), IEEE conference on

作者： Rahul Kumar Rajak Prashant Baredar Gaurav Dwivedi Raj Suman Energy Centre MANIT Bhopal Bhopal India

ISBN: (数字)9798331521691

ISBN: (纸本)9798331521707

In order to comprehend, maximize, and expand this complex biological process, mathematical modeling in anaerobic digestion is crucial. As a result of anaerobic digestion, dig estate and biogas are produced when microorganisms break down organic matter in the absence of oxygen. In order to depict and evaluate the dynamics of anaerobic digestion systems, mathematical models are essential. Dynamic models that monitor changes in substrates and products over time, as well as mass balance and kinetic models that characterize reaction rates, are among them Prominent models comprise Anaerobic Digestions Model No. 1, which incorporates different phases of the digestion process, and Biochemical Methane Potential models, which determine the potential for producing methane from substrates. These model plays a crucial role in process parameter optimization, scaling from laboratory to industrial scale, and improving real-time monitoring and control. They also aid in waste management plans and assess environmental effects by forecasting performance, efficiency, and sustainability.

关键词： Biological system modeling Computational modeling Predictive models Mathematical models data models Biogas Kinetic theory Sustainable development Substrates Optimization

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Optimizing Battery Performance in Electric Vehicles Through Predictive modeling

Optimizing Battery Performance in Electric Vehicles Through ...

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2025 International conference on Intelligent control, Computing and Communications, IC3 2025

作者： Kumar, C. Siva Sagar, P. Lakshmi Venkata Bhanu Pratap, B. Geethamadhuri, Gurramkonda Kumar, Banda Sai Ram Dinesh, Bommineni Mukesh, Pallaputhimmannagari Sree Vidyanikethan Engineering College Dept of Csse Andhra Pradesh Tirupati India Dept of Data Science Karakambadi A.P Tirupati India BORiTS Private Limited Telangana Hyderabad India Ug School Dept of Csbs Sree Vidyanikethan Engineering College Andhra Pradesh Tirupati India

ISBN: (纸本)9798331527495

The fast-paced electrification of the automobile sector has intensified an immediate need for reliable battery management systems capable of sustaining long-term performance. One of the most important indicators when it comes to battery health is State of Health (SOH), which indicates how much capacity is left and how long a certain battery will endure. Reliable estimation of SOH is critical to enable the optimal performance of vehicles, reduce service costs, avoid unanticipated failures. In this project, we propose a machine learning approach to predict the SOH of EV batteries based on the two widely used algorithms, XGBoost and LGBM. In order to cover and analyze as many process variables available as possible to build a database for the training and evaluation of the models, we measured multiple battery parameters, such as voltage, current, temperature and historical charge/discharge cycles. The train test split this dataset in such a way that the greater part of the dataset is used for the machine learning operations. Individual models, such as XGBoost and LGBM, are used to be train due to its strength in handling large data and complex data with a high precision. This study attempts to find out the better of the two algorithms for real-time SOH prediction in practice by analyzing the accuracy and performance metrics of both algorithms. Results of this analysis can help manufacturers and operators make data-informed decisions regarding battery usage, maintenance schedules and replacement, which will contribute to improved vehicle reliability and extended battery life. © 2025 IEEE.

关键词： Decision making

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Intelligent City Construction Resource Optimization and Scheduling Algorithm Based on T-S Fuzzy Neural Network and Deep data Mining 24

Intelligent City Construction Resource Optimization and Sche...

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4th International Joint conference on Robotics and Artificial Intelligence, JCRAI 2024

作者： Yu, Jiming Feng, Qiang Zhang, Liyuan Columbia University New York United States Changchun University of Technology Changchun China Changchun Institute of Technology Changchun China

ISBN: (纸本)9798400710100

The challenges of cost control in construction and installation projects have perennially been a significant concern for entities in the construction sector. The intricate interplay of various equipment, personnel, and tasks during the installation process often leads to an extension in the construction timeline, thereby escalating the overall cost of construction. To address this issue, this study introduces a heuristic two-phase optimization deployment approach. Furthermore, to facilitate efficient and intelligent resource management for urban construction projects, a resource optimization algorithm predicated on the T-S Fuzzy Neural Network (T-S FNN) and deep data mining is proposed. This algorithm employs the T-S FNN to conduct an in-depth analysis and selection of resource data, followed by the application of the Particle Swarm Optimization algorithm to enhance the network. Experimental outcomes demonstrate that the proposed algorithm significantly curtails the overall construction duration and labor cost when juxtaposed with multiple standard allocation strategies. This underscores its efficacy and efficiency in reducing the time and cost associated with project construction. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Particle swarm optimization (PSO)

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20th EAI International conference on Computer Science and Education in Computer Science, CSECS 2024

20th EAI International Conference on Computer Science and Ed...

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20th EAI International conference on Computer Science and Education in Computer Science, CSECS 2024

ISBN: (纸本)9783031843112

The proceedings contain 23 papers. The special focus in this conference is on Computer Science and Education in Computer Science. The topics include: Enabling Autonomy Through Voice control: AI-Assisted Mobile Platform;maRz: A Fast, Transparent Fuzzy Machine Learning Technique;segmentation and data Extraction from Carte du Ciel Astrographic Maps;Quadratic Sets and (3mod5)-Arcs in PG(r,5);the Periodic Table: Chemical Properties and Mendeleev Meets Physical Properties and Machine Learning;large Language Models for Identification of Medical data in Unstructured Records;impact of the Iteration Length on the Software Quality;double-Stranded Differential Evolution and Particle Swarm Optimization with LibreOffice Nonlinear Programming Solver;analyzing the Geometric Ratios of Greek Vases;assessment of Segmentation Models on Panoramic Radiographic Dental Images;3D Cycle-Consistent Adversarial Network for Designing Dental Implant Crown;Eliminating Risk Involved in Using ChatGPT for Clinical Decision Support System;innovative Approaches for the Mental Development and Education of Children with Autism Through Mixed Reality;applications of Simulation modeling and Computer Visualizations for Studying Structured Crystals for Implementation in Technical Devices;harnessing Programmable Logic for Quaternion Multiplication;digital Transformation in Primary and Secondary Education in Bulgaria;building a Chatbot to Adopt an Effective Learning Strategy for Graduate Courses in Computer Science;Impact of the Self-training Over Formative Assessment in SQL Part of University database Course;teaching and Learning Python by Comparative Visualization;an Interdisciplinary Approach in Education of Master Students in Intelligent Sustainable Habitats;Cross-Continental Insights: Comparative analysis of Using AI for Information System Stakeholder analysis in Undergraduate Courses in the EU and USA.

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The effect of mineralogical, mechanical, physical, and dynamic properties on rock brittleness using statistical and soft computing methods

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EARTH SCIENCE INFORMATICS 2025年第1期18卷 1-29页

作者： Xu, Cairui Zhang, Xinyu Yu, Jiuhong Hou, Kang Rastegarnia, Ahmad Gholipour, Sajjad Nanjing Tech Univ Coll Comp & Informat Engn Nanjing 211800 Peoples R China Jinling Univ Sci & Technol Sch Intelligent Sci & Control Engn Nanjing 211169 Peoples R China Ningbo Univ Finance & Econ Res Inst Data Intelligence Ningbo 315175 Peoples R China Chinese Acad Sci Inst Semicond Beijing 100083 Peoples R China Ferdowsi Univ Mashhad Fac Sci Dept Geol Mashhad Iran Urmia Univ Technol Engn Fac Khoy Dept Civil Engn Orumiyeh Iran

Brittleness is one of the most main strength characteristics of rocks that is extensively utilized in drilling operations. This study aimed to estimate the brittleness index (BI) of sandstones using the percentage of quartz, feldspar, fragments, point load value (PLV), water absorption, P-wave velocity (PW), density, and porosity. This study utilized a range of prediction models, namely simple and multivariate linear regression analysis (MVLRA), multilayer backpropagation neural network (MBPN) with diverse learning rates and training algorithms, random forest (RF), Gaussian process regression (GPR), support vector regression (SVR) with various kernel functions, and adaptive neuro-fuzzy inference system (ANFIS). The sandstones under investigation were classified into litharenite and feldspathic litharenite categories. The observation revealed that as the percentage of feldspar and quartz increased, while fragments decreased, there was a corresponding increase in the brittleness index. Quartz and carbonate fragments had the highest and lowest effects on brittleness, respectively. The statistical analysis revealed that PLV and PW have the greatest impact on the BI, while the percentage of minerals had the least influence. Comparing the results of different methods based on error value, performance index, statistical tests, and Taylor diagram, the SVR based on radial basis kernel function demonstrated the highest performance (R2 = 0.99 and RMSE = 0.04) in estimating the brittleness index of the studied sandstones. Tukey's test to check the significance of the mean BI obtained from modeling and measured in the laboratory displayed that there is no significant difference between the BI values obtained from these methods.

关键词： Brittleness index Mineralogy Machine learning Statistical methods Physical properties Mechanical properties P-wave velocity Sandstone

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22nd International conference on Software Engineering and Formal Methods, SEFM 2024

22nd International Conference on Software Engineering and Fo...

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22nd International conference on Software Engineering and Formal Methods, SEFM 2024

ISBN: (纸本)9783031773815

The proceedings contain 25 papers. The special focus in this conference is on Software Engineering and Formal Methods. The topics include: User-Guided Verification of Security Protocols via Sound Animation;a Policy Framework for Regulating External Calls in Smart Contracts;exploiting Assumptions for Effective Monitoring of Real-Time Properties Under Partial Observability;a Formal modeling Language for Smart Contracts;symbolic Execution for Precise Information Flow analysis of Timed Concurrent Systems;Validating Traces of Distributed Programs Against TLA+ Specifications;partially-Observable Security Games for Attack-Defence analysis in Software Systems;secure Smart Contracts with Isabelle/Solidity;Deductive Verification of SYCL in VerCors;minuska: Towards a Formally Verified Programming Language Framework;hierarchical Learning of Generative Automaton Models from Sequential data;composing Run-Time Variability Models;model-Checking the Implementation of Consent;grammarForge: Learning Program Input Grammars for Fuzz Testing;verified Configuration and Deployment of Layered Attestation Managers;right or Wrong – Understanding How Users Write Software Models in Alloy;an Operational Semantics for Yul;execution-Time Opacity control for Timed Automata;unlocking the Power of Environment Assumptions for Unit Proofs;towards Quantum Multiparty Session Types;automated Invariant Generation for Efficient Deductive Reasoning About Embedded Systems;formal analysis of Multi-Factor Authentication Schemes in Digital Identity Cards;leveraging Contracts for Failure Monitoring and Identification in Automated Driving Systems.

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