Simple Projection Research Articles

Structure-Based Training: A Training Method Aimed at Pixel Errors for a Correlation-Coefficient-Based Neural Network.

In research on building a one-shot learning neural network without pre-training using mass data, the limitation on the information obtained from a single training sample downgrades the performance of the network. In order to improve performance and take full advantage of the support set, in this study, we design three kinds of shadow nodes and propose a structure-based training method for a correlation-coefficient-based neural network. This training strategy focuses on branches that are not activated or inactivated as expected. In contrast to existing networks that optimize the parameters using back-propagation, the training method proposed in this paper optimizes the structure of the correlation-coefficient-based network by correcting its pixel errors. For the shadow nodes and training process based on this strategy, the intersection over union (IOU) of a detected target increases by 4.83% in the experiments when using the Fashion-Mnist dataset, increases by 4.02% when using the Omniglot dataset, and increases by 3.89% when using the Cifar-10 dataset. The samples in category "7" wrongly classified as "1" decreased by 27.32% when using the Mnist dataset after training. This training strategy, along with shadow nodes, makes the correlation-coefficient-based network a more practical model and enables the network to develop during the accumulation of reliable samples, thus making it more suitable for simple target detection projects that collect samples over time. Moreover, the shadow nodes and training method proposed in this paper supplement the non-gradient-based parameter-gaining strategy. Additionally, it is a new attempt to explore the imitation of a human's ability to learn a new pattern from a low number of references.

Multi-stage and multi-colour liquid crystal reflections using a chiral triptycene photoswitchable dopant.

The photomodulation of the helical pitch of cholesteric liquid crystals results in dynamic and coloured canvases that can potentially be used in applications ranging from energy-efficient displays to colour filters, anti-counterfeiting tags and liquid crystal (LC) lasers. Here we report on the analysis of a series of photoswitchable chiral dopants that combine the large geometrical change and bistability of hydrazone switches with the efficient helical pitch induction of the chiral motif, triptycene. We elucidate the effects that conformational flexibility, dispersion forces and π-π interactions have on the chirality transfer ability of the dopant. We then use the irradiation time with visible light (442 nm) combined with a simple digital light processing microscope projection set-up to draw numerous stable multi-coloured images on an LC canvas, showcasing the fine control this dopant yields over the LC assembly.

Reducing healthcare waste by eliminating exam table paper in a primary care practice: a sustainable quality improvement initiative.

Climate change is now the greatest threat to human survival. The healthcare system contributes significantly to global pollution and greenhouse gas emissions. Individual practitioners play an important role in helping to reduce these impacts in day-to-day practice. Deimplementation of unnecessary processes and products, such as exam table paper, in medical offices is one simple approach to incorporating principles of planetary health into practice. All quality improvement (QI) projects must start to consider environmental impacts to fully evaluate change ideas. We designed a single Plan-Do-Study-Act cycle using the Institute for Health Improvement Model for Improvement. We removed the exam table paper from our primary care office and measured changes in staff time, laundry, financial costs, paper use and carbon dioxide (CO2) emissions. Eliminating exam table paper in our clinic resulted in modest annual cost savings of $C718 and improved staff efficiency and motivation to introduce other green office practices. In our clinic alone, this change will save 8.2 km of exam table paper, 10 trees and 148 kg of CO2e (equivalent to driving 1233 km) every year. There were no negative consequences or feedback. This simple QI project demonstrates the feasibility of implementing a small change in a primary care clinic that can improve environmental sustainability with multiple co-benefits. If all family physicians in Canada eliminated exam table paper in their offices, it would result in savings of approximately 95 940 km of paper, 121 680 trees, $C8 400 600 and 3054 T CO2 emissions, equivalent to driving around the world 360 times.

The Evolution of the Hunga Hydration in a Moistening Stratosphere

AbstractThe 2022 Hunga eruption caused unprecedented stratospheric hydration. Aura Microwave Limb Sounder (MLS) measurements show that the stratospheric water vapor mass remains essentially unchanged as of early 2024 and that the Hunga hydration occurred atop a robust (possibly accelerating) moistening trend in the stratosphere. Enhanced by the excess Hunga water vapor, dehydration via polar stratospheric cloud sedimentation in the 2023 Antarctic vortex exceeded climatological values by 50%. Simple projections based on modeled exponential decay illustrate that the timing of the return to humidity levels that would have been expected absent the Hunga hydration depends on the ongoing stratospheric water vapor trend. With the Hunga hydration compounding an underlying moistening trend, the stratosphere could remain anomalously humid for an extended period.

A dual opposition learning-based multi-objective Aquila Optimizer for trading-off time-cost-quality-CO2 emissions of generalized construction projects

PurposeMost of the existing time-cost-quality-environmental impact trade-off (TCQET) analysis models have focused on solving a simple project representation without taking typical activity and project characteristics into account. This study aims to present a novel approach called the “hybrid opposition learning-based Aquila Optimizer” (HOLAO) for optimizing TCQET decisions in generalized construction projects.Design/methodology/approachIn this paper, a HOLAO algorithm is designed, incorporating the quasi-opposition-based learning (QOBL) and quasi-reflection-based learning (QRBL) strategies in the initial population and generation jumping phases, respectively. The crowded distance rank (CDR) mechanism is utilized to rank the optimal Pareto-front solutions to assist decision-makers (DMs) in achieving a single compromise solution.FindingsThe efficacy of the proposed methodology is evaluated by examining TCQET problems, involving 69 and 290 activities, respectively. Results indicate that the HOLAO provides competitive solutions for TCQET problems in construction projects. It is observed that the algorithm surpasses multiple objective social group optimization (MOSGO), plain Aquila Optimization (AO), QRBL and QOBL algorithms in terms of both number of function evaluations (NFE) and hypervolume (HV) indicator.Originality/valueThis paper introduces a novel concept called hybrid opposition-based learning (HOL), which incorporates two opposition strategies: QOBL as an explorative opposition and QRBL as an exploitative opposition. Achieving an effective balance between exploration and exploitation is crucial for the success of any algorithm. To this end, QOBL and QRBL are developed to ensure a proper equilibrium between the exploration and exploitation phases of the basic AO algorithm. The third contribution is to provide TCQET resource utilizations (construction plans) to evaluate the impact of these resources on the construction project performance.

The Theory of Projection

Abstract Whitehead’s process philosophy offers a wide range of speculatively generalized concepts that allow for an application in transdisciplinary research. The notion of projection is an often-overlooked detail of his philosophy that not only appears in his far-reaching theory of perception, but also constitutes an integral part of his theory of extension as the formal foundation of his metaphysical project. His perceptive theory relies on the idea of projection as the fundamental ontological relationship that lifts the past into the present. Projections of sensa describe one side of the ‘double-barreled’ theory of perception and the spatial relations of the contemporary world. The microscopic projection is just as fundamental for perception and for the integrity of a relational theory of becoming, as the perceptual projection is necessary ingredient for symbolic modes of experience. The simple projection in the mode of presentational immediacy is the basis of temporary stability of events and of any perceptual situation in the biological realm. Whitehead was aware of the possible misconceptions that this term might lead to. Discussing his remarks on the hierarchical variety of different modes of projection can resolve those misconceptions and throw a new light on the importance of projection for interdisciplinary inquiries.

Investigating rhoticity in Scottish Standard English with sociolinguistic interviews and corpus data

AbstractThis paper approaches variable rhoticity in Scottish Standard English (SSE) from a methodological, data‐oriented perspective. The main focus is on how to integrate within a single sociolinguistic framework data that have been elicited under different conditions (sociolinguistic interviews vs. corpus data) and may therefore be incompatible when we take a relatively simplistic approach to stylistic variation. The article first models variation in such an unbalanced ‘patchwork’ dataset in a holistic, unified analysis and then proceeds to deconstruct the results by taking a closer look at the behaviour of the two main components of the data. While previously reported trends in the development of coda‐/r/ in SSE accents are confirmed, it is also shown that, depending on the precise nature of registers (or genres), productions may be considerably more diverse and may go beyond a simple projection of middle‐class identities. The integration of different styles in a single interpretive framework is challenging and far from straightforward.

A simple projection method to correlate the principal mechanical direction with the principal microstructural direction of human osteoporotic femoral heads.

The mechanics of the trabecular bone is related to its structure; this work aimed to propose a simple projection method to clarify the correlation between the principal mechanical direction (PMD) and the principal microstructural direction (PMSD) of trabecular bones fromosteoporotic femoral heads. A total of 529 trabecular cubes were cropped from five osteoporotic femoral heads. The micro computed tomography (μCT) sequential images of each cube were first projected onto the three Cartesiancoordinate planes to have three overlapped images, and the trabecular orientation distribution in the three images was analyzed. The PMSD corresponding to the greatest distribution frequency of the trabecular orientation in the three images was defined. Then, the voxel finite element (FE) models of the cubes were reconstructed and simulated to obtain their compliance matrices, and the matrices were subjected to transversal rotation to find their maximum elastic constants. The PMD corresponding to the maximum elastic constant was defined. Subsequently, the correlation of the defined PMSD and PMD was analyzed. The results showed that PMSD and PMD of the trabecular cubes did not show a significant difference at the xy- and yz-planes except that at the zx-plane. Despite this, the mean PMSD-PMD deviations at the three coordinate planes were close to 0°, and the PMSD-PMD fitting to the line PMSD = PMD demonstrated their high correlation. This study might be helpful to identify the loading direction of anisotropic trabecular bones in experiments by examining the PMSD and also to guide bone scaffold design for bone tissue repair.

Simple Project Based Learning To Improve Pronunciation Element In Teaching Speaking

The purpose of this research is to improve students' speaking skills through a project based learning, making them more immersive and active. This study used experimental techniques and analysis of students' cognitive abilities with quantitative research techniques through oral tests. The research questions considered in this study are: was there a significant effectiveness of simple project-based learning syntaxes in teaching speaking (pronunciation element) and to what extent was the effectiveness of simple project-based learning syntaxes in teaching speaking (pronunciation element)?. The purpose of this study is to know whether the Simple project-based learning syntaxes to teach speaking (pronunciation element) contributes significantly to the senior high school students’ speaking ability of eleventh grade student of MA NW Juet academic year 2024. And the perpose of this research is to find out the extent of Simple project-based learning syntaxes in teaching speaking (pronunciation element). The analytical methods used for data processing are included in the Social Science Statistics 22.0 for Windows. The results before applying the project based learning technique, only 50% of students are able to spek in English and after applying the project based learning, it improved student's ability to speak in English by 80%. Applying project based learning , especially speaking, This is the right strategy to improve students' speaking skills (pronunciation).

Quantitative Approaches for Analyzing the Potential Effectiveness of Vietnam’s Emissions Trading System: A Systematic Review

Carbon pricing initiatives have been developed globally in recent decades. Among carbon pricing initiatives, direct carbon pricing, particularly the emissions trading system (ETS), has attracted the interest of stakeholders and nations. With its ambitious potential for climate change mitigation, Vietnam has considered establishing a domestic ETS. However, studies on the effectiveness and impact of Vietnam’s ETS are scarce. This study reviews the quantitative approaches to assessing Vietnam’s ETS and evaluates the methodologies, limitations, and challenges of current quantitative assessments such as the simple reduced-form emission projection method, computable general equilibrium (CGE), input–output analysis (IOA), and multi-criteria analysis. CGE and IOA are highly recommended to obtain comprehensive results. However, IOA is more capable of avoiding numerous assumptions, complicating the use of CGE. This study recommends directions for possible innovative improvements for utilizing IOA in future research on Vietnam’s ETS; thus, suggesting a competent approach for effectively analyzing ETS.

Pengembangan Materi Pembelajaran IPS untuk Kelas Awal dan Kelas Lanjut dalam Kurikulum Sekolah Dasar

This research aims to develop Social Sciences (IPS) learning materials that suit the needs of students in early grades (1, 2, and 3) and advanced grades (4, 5, and 6) in the Elementary School Curriculum. This learning material development approach uses a competency-based approach and refers to the principles of fun and student-centered learning. The methods used are literature study, observation, and consultation with education experts. Early grades require a more visual and playful approach to social studies learning. Therefore, learning materials for early grades are designed taking these needs into account. For example, material about the surrounding environment is presented through pictures, role plays and short stories that are relevant to children's daily lives. Meanwhile, advanced classes require a more analytical and contextual approach in learning social studies. Learning materials for advanced classes are prepared taking into account students' cognitive and social development. For example, material on history is presented through case studies, group discussions, and simple research projects that allow students to develop analysis and synthesis skills. It is hoped that the results of the development of social studies learning materials will increase students' interest and understanding of social studies materials and help teachers present learning materials that are interesting and relevant to students' needs.

Development of Science Literacy Through Group Choice STEM-PjBL Projects Integrated with Matter State Changes

This research focuses on the development of students' science literacy in the topic of matter state changes at the primary school level. It utilizes Science, Technology, Engineering, and Mathematics - Project-Based Learning (STEM-PjBL) as a holistic integrative learning approach, supporting 21st-century skills. The meaningful learning design is crafted to help students understand the material while applying their understanding to a simple project appropriate for primary school students' cognitive levels. The study was conducted in a fifth-grade class at an educational unit in Tangerang City, Banten Province, Indonesia. Using a qualitative research method, data was collected through interviews, observations, reflective journals, and researchers' notes. The STEM-PjBL learning stages included reflection, research, discovery, application, and communication. The Shwartz assessment was developed as an instrument to evaluate students' science literacy abilities. The results show that implementing the STEM-PjBL approach promotes student-centered learning, builds group cooperation, is enjoyable, and develops students' science literacy. Students worked in groups on their chosen projects related to the topic of matter state changes. The average project score for each group received an A rating in completing the STEM-PjBL project. Interdisciplinary learning can encourage students to understand the characteristics and concepts of a theory and relate them to everyday life, thereby impacting their understanding and project development.

Designing an Information Technology Platform for Imparting Entrepreneurship Values in Social-Emotional Learning for Kindergarten Children Using EFA and CFA

Kindergarten is crucial for today's education. Kindergarten helps kids develop in all areas. Students work in groups on a simple project task in this study. The work includes topic-related activities. Kids should learn early on that being an entrepreneur will shape their identity & future. This condition makes someone realize that their long-term desire to be an entrepreneur comes from their academic success. This study investigated how the 35 questions are assembled & what improves them. 195 kindergarten teachers participated in the study. The sample was analyzed using EFA & CFA. Exploratory factor analysis revealed twelve unknown variables. The above variables explained 80% of the variation. Various factors explained the remaining 20%. All Cronbach's alpha values exceed requirements. CR >.7 & AVE >.5, indicating credible & tested constructs. The EFA showed that 195 research samples were sufficient because the KMO was above 0.50. This allowed more research. Six-factor solutions explained over 80.71% of the variation, so the EFA liked them. These factors kept the results consistent with those of previous studies. These traits facilitate legislator-educator dialogue rather than kindergarten teacher business observation. Researchers can use these properties for cluster analysis or multivariate linear regression. This subject requires more research because students develop a structured approach. Furthermore, experts should examine the research on what is making kindergarten entrepreneurship instruction popular.

Поиск оптимальной модели (прототипа), предназначенной для управления проектами в медицинских организациях региона.

Building a system for measuring the value of a model of a medical organization implementing a project involves choosing a mutually appropriate model of the optimal prototype, by assessing and preparing tools based on it for effective project management. The purpose of the study is to formalize the requirements for searching and visualizing the optimal project prototype using the principles (adequacy, value, abstraction and simplicity) applied to determining the model of a medical organization implementing a regional project. Materials and methods. Using the analytical research method, an attempt was made to determine the correspondence between the required accuracy and the initial data of the object (MO implementing the project) by formalizing the requirements of the stages of constructing a mathematical model to find the optimal prototype. Results. Determining the adequacy of the goals when the properties of the model coincide with similar indicators of the modeled object is a necessary condition for assessing the value of the model, giving an understanding of the degree of reliability and approximation of the calculation results to experimental (pragmatic) data. The totality of data from the model of a medical organization implementing a project in conjunction with its elements that interact with the environment as a single whole is the principle of adequacy (value) of the project model for finding the initial parameters of the prototype. The principle of abstraction from minor details of the model, or simplification, while maintaining the essential properties of the system, is an important condition for its optimization. Structuring the interconnections of relationships, functions of objects and subjects of relationships during the empirical deployment of the initial model to a prototype (working model of the project) for a subset of possible stakeholders (customer, developer, performer, patient) provides feedback and transformation of the model at an early stage. The principles of abstraction from minor details of the model (simplification) and simplicity are important conditions for the formation of assumptions for the search for a prototype. Conclusions. Thus, finding a compromise between the desire to create a complete description and obtaining the required results when constructing a simple project model is possible by taking into account the essential parameters specified in the framework of assessing their impact on the efficiency of the system.

Simple projection method: a novel algorithm for estimation of characteristic element length in finite element simulations of composites

Simple projection method: a novel algorithm for estimation of characteristic element length in finite element simulations of composites

When can networks be inferred from observed groups?

AbstractCollecting network data directly from network members can be challenging. One alternative involves inferring a network from observed groups, for example, inferring a network of scientific collaboration from researchers’ observed paper authorships. In this paper, I explore when an unobserved undirected network of interest can accurately be inferred from observed groups. The analysis uses simulations to experimentally manipulate the structure of the unobserved network to be inferred, the number of groups observed, the extent to which the observed groups correspond to cliques in the unobserved network, and the method used to draw inferences. I find that when a small number of groups are observed, an unobserved network can be accurately inferred using a simple unweighted two-mode projection, provided that each group’s membership closely corresponds to a clique in the unobserved network. In contrast, when a large number of groups are observed, an unobserved network can be accurately inferred using a statistical backbone extraction model, even if the groups’ memberships are mostly random. These findings offer guidance for researchers seeking to indirectly measure a network of interest using observations of groups.

Implementation of an Online Programming Software to Explore the Computational Thinking Ability of Biological Education Students

This study aimed to explore the Computational Thinking (CT) ability of biology education students in artificial intelligence courses through code.org programming, an online programming software. Students were required to solve problems systematically and design systems with coding for beginners. The research method used a qualitative approach because it was based on observational data from computational media produced in accordance with artificial intelligence learning for education and based on CT indicators. The subjects of this study were 73 students of the Biology Education Study Program in 2021. How students responded to using the code.org platform was captured through a questionnaire distributed via a Google form. The results showed that students could follow each stage of educational game projects through the code.org platform to practice computational thinking skills in accordance with the success of the stages of doing simple projects through good, systematic and problem-solving coding. Student responses to the code.org platform as an online program tool that can hone computational thinking can provide creativity and enthusiasm for student learning. As evidenced by the questionnaire results, 63.3% of students strongly agree that this increases creativity.
 Keywords: online programming, computational thinking, biological education, students

The Influence of 3D Printing Parameters on the Mechanical Behavior of PLA

Additive technologies are continually evolving and are crucial in numerous industries, including medical, aerospace, and automotive, but they can also play an important role in the prototyping phase. Due to additive manufacturing, amateurs and enthusiasts can construct simple projects as well as large projects with specialized usage in specific applications. When it comes to complex pieces, traditional manufacturing technologies such as milling, chipping, drilling, and so on have specific constraints, often need even additional production processes to complete the item. All of these constraints can be solved with additive technologies. This work investigates Fused Deposit Modeling (FDM) printing of many specimens with varying properties in order to analyze PLA (Poly Lactic Acid) material behavior following tensile testing. The collected findings will be analyzed in order to determine the specimens with the most significant behavior according on the modified parameters.

A Study of Learning Environment for Initiating Flutter App Development Using Docker

The Flutter framework with Dart programming allows developers to effortlessly build applications for both web and mobile from a single codebase. It enables efficient conversions to native codes for mobile apps and optimized JavaScript for web browsers. Since utilizing a wide range of widgets in Flutter ensures consistent experiences on various devices for users, it becomes crucial in programming education by providing a unified environment for learning app development while reducing the need for platform-specific knowledge. However, the setup of the Flutter environment is challenging for novice students due to its multiple steps, such as installing dependencies and configuring environments. To support independent learning for these students, it is essential to simplify the setup by providing user-friendly instructions and automated tools. In this paper, we present a Docker-based environment for Flutter app developments across Windows, Linux, and Mac through Visual Studio Code, ensuring a unified learning experience. This paper aims to simplify complex configurations and address the obstacles encountered by students when initiating Flutter projects. For the evaluation, we prepared three simple Flutter projects along with the setup environment in a Docker container. Then, we asked 24 Master’s students at Okayama University, Japan, to install the environment and modify the source codes in the projects independently by following the given instructions. The results show that all the students successfully completed the assignments, which confirms the efficiency and validity of our proposal.

Techno‐Economic Modeling of Diverse Renewable Energy Sources Integration: Achieving Net‐Zero CO2 Emissions

Integrating renewable energy sources (RES) into power systems presents significant challenges due to their diverse nature and operational characteristics. This study addresses these challenges through an innovative strategy that simulates solar and wind farms, storage systems, fuel cell generators of hydrogen energy (via electrolysis), and hydrogen storage, all governed by an intelligent controller. Alongside a mathematical model defining the system's dynamics, a multi‐objective optimization model is employed, exploring the system's operational, financial, and environmental impacts. While the mathematical model has limitations, the advanced model captures the system's dynamic behavior with exceptional precision. This intelligent simulation simplifies the complex interrelationships between various resources in the system, highlighting the viability of RES integration for enhanced benefits. Multi‐objective optimization of a real case study of Iowa 240‐Bus power system in the Midwest United States has resulted in an annual savings of $126 147.8, along with a significant CO2 reduction of 951 035.6 kg compared with the basecase. The total annual energy costs, including capital costs and electricity sales, are reported to be $157 430.4, and the total annual CO2 emissions are −4453.8 kg. Financial indicators highlight an annual cost reduction of 10.3% and an annual emission reduction of 100.5%. The simple and detailed project break‐even years are 18 and 1, respectively, with the project savings to cost minimization scenario ratio at 1.04. The optimization process efficiently handled a complex problem involving 5921 iterations, 299 247 variables, 11 854 discrete variables, and 342 167 equations, completing the entire operation in 12.7 s. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.