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...
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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.
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 colla...
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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 ...
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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 di...
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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.
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 microo...
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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.
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 ...
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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, an...
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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 Platfor...
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.
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 ...
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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.
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...
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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