Concept Of Map Research Articles

Bayesian approach for meta-analyses in biomedical research: a scoping review protocol.

The overarching aim of this scoping review is to describe and analyze the scope of use and reporting of Bayesian methods in meta-analyses in biomedical research. The Bayesian approach provides a powerful and flexible framework for meta-analysis, particularly suited for dealing with complex, sparse, or heterogeneous data. Due to these advantages and its appeal, Bayesian methods have been increasingly used in many areas of biomedical research; however, their use in meta-analysis remains scarce. This review will include studies that used Bayesian methods for meta-analysis of primary studies in biomedical research. The proposed review will be conducted in accordance with the JBI methodology for scoping reviews. PubMed, Embase, CINAHL, and the Cochrane Database of Systematic Reviews will be searched to identify relevant full-text papers published since 2016 in English. No geographical restriction will be applied. Two reviewers will screen the articles and extract the data using a tool that will be pilot-tested and revised, as necessary. Analysis will involve frequency counts, narrative synthesis, and mapping concepts to propose an appropriate workflow. The details of the scoping review will be reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guideline. Open Science Framework https://osf.io/jenp4/.

Research on the SLAM technology moving away from high-precision maps in the context of autonomous driving

SLAM(Simulation Localization and Mapping) technology is widely used in the fields of unmanned driving, autonomous robots and augmented reality. Real-time localization and mapping capabilities provide important support for autonomous driving. In this paper, we present a review of the implications of SLAM technology away from high-precision maps in autonomous driving scenarios, and the concept and production process of high-precision maps, as well as their role and advantages in autonomous driving, are discussed. Then, the application, significance, and advantages of SLAM technology in autonomous driving scenarios are discussed in detail, and the advantages of SLAM technology in environmental adaptability, real-time performance, cost and scalability, and safety in emergency situations are emphasized. Finally, the challenges faced by the current SLAM technology in autonomous driving are analyzed, and the development prospects of SLAM technology in the field of autonomous driving in the future are discussed.

Locating Loneliness Through Social Intelligence Analysis.

Loneliness is a global public health issue, but the dynamics of loneliness are not understood. Through a global loneliness map, we plan to understand the dynamics of loneliness better by analyzing social media data on loneliness through social intelligence analysis. In this paper, we present the first proof of concept of the global loneliness map. Data on loneliness using keywords associated with loneliness was collected from the USA and analyzed to find meaningful associations of themes with loneliness. The NLP tool used for sentiment analysis of the tweets is a valence aware dictionary for sentiment reasoning (VADER). The tweets with negative sentiment were further analyzed for psychosocial linguistic features to find meaningful correlation between loneliness and socioeconomic and emotional themes and factors. Loneliness is subjective, hence social intelligence analysis through social media and machine learning tools can help us better understand loneliness.

Maledia Broadcasting: Getting Ready to Go on Air

This case focuses on the positioning strategy development for a new regional television channel of Maledia Broadcasting Network (MBN), a venture of the Kerala-based media group from India, Model Publication Trust. It also introduces the concept of perceptual maps for brand positioning and addresses brand extension. In 2011, MBN prepared to launch a Malayalam news channel. Samjad, Deputy CEO of the new company, faced the challenge of determining the channel’s positioning strategy. This task involved not only differentiation but also redefining competition in India’s dynamic and competitive broadcasting industry. The decision would impact marketing aspects such as the brand name and channel identity. This case offers opportunities to explore qualitative aspects of audience behaviour beyond competitive data, helping marketing students gain insights and analyse the competitive landscape in the industry to make strategic marketing decisions.

Concept of Bilinear Transformation, Jacobian, and Conformal Mapping with Applications

This article explores the concepts of bilinear transformation, Jacobian transformation, and conformal mapping, focusing on their essential properties and presenting key results. The discussion revolves around isogonal transformation, conformal transformation, Jacobian transformation, and bilinear transformation, as well as critical points and fixed points.

PROFESSIONAL BOOK REVIEWS

Richard Willis, visiting professor at the University of South Wales, reviews a book which argues for the increased incorporation of slow pedagogies and slow knowledge in early childhood education and care (ECEC). The title won the Professional Book of the Year at the Nursery World Awards 2023. Meg Barclay, educational consultant and early years reviewer for the School Library Association reviews picture books which help support young readers' understanding of different emotions, the natural world and the concept of maps.

Machine learning for hypothesis generation in biology and medicine: exploring the latent space of neuroscience and developmental bioelectricity

FieldSHIFT uses in-context learning to translate neuroscience abstracts into developmental biology abstracts based on example concept mappings, creating new research hypotheses at scale.

A Review on the Structure of Fuzzy Regular Proper Mappings in Fuzzy Topological Spaces and Their Properties

The purpose of this paper is construct the concept of fuzzy regular proper mapping in fuzzy topological spaces. We give some characterization of fuzzy regular compact mapping and fuzzy regular coercive mapping. We study the relation among the concepts of fuzzy regular proper mapping, fuzzy regular compact mapping and fuzzy regular coercive mapping and we obtained several properties.

A new class of hybrid contractions with higher-order iterative Kirk's method for reckoning fixed points

<p>The concept of contraction mappings plays a significant role in mathematics, particularly in the study of fixed points and the existence of solutions for various equations. In this study, we described two types of enriched contractions: enriched $ F $-contraction and enriched $ F^{\prime } $-contraction associated with $ u $-fold averaged mapping, which are involved with Kirk's iterative technique with order $ u $. The contractions extracted from this paper generalized and unified many previously common super contractions. Furthermore, $ u $-fold averaged mappings can be seen as a more general form of both averaged mappings and double averaged mappings. Moreover, we demonstrated that the $ u $-fold averaged mapping with enriched contractions has a unique fixed point. Our work examined the necessary conditions for the $ u $-fold averaged mapping and weak enriched contractions to have equal sets of fixed points. Additionally, we illustrated that an appropriate Kirk's iterative algorithm can effectively approximate a fixed point of a $ u $-fold averaged mapping as well as the two enriched contractions. Also, we delved into the well-posedness, limit shadowing property, and Ulam-Hyers stability of the $ u $-fold averaged mapping. Furthermore, we established necessary conditions that guaranteed the periodic point property for each of the illustrated strengthened contractions. To underscore the generality of our findings, we presented several examples that aligned with comparable results found in the existing literature.</p>

Exploring new geometric contraction mappings and their applications in fractional metric spaces

<abstract><p>This article delves deeply into some mathematical basic theorems and their diverse applications in a variety of domains. The major issue of interest is the Banach Fixed Point Theorem (BFPT), which states the existence of a unique fixed point in fractional metric spaces. The significance of this theorem stems from its utility in a variety of mathematical situations for approximating solutions and resolving iterative problems. On this foundational basis, the study expands by introducing the concept of fractional geometric contraction mappings, which provide a new perspective on how convergence develops in fractional metric spaces.</p></abstract>

Existence, uniqueness, and blow-up analysis of a quasi-linear bi-hyperbolic equation with dynamic boundary conditions

<abstract><p>For this study, we investigate the existence and uniqueness of local solutions and derive a blow-up solution for a quasi-linear bi-hyperbolic equation under dynamic boundary conditions. We utilize the contraction mapping concept to demonstrate the solution's local well-posedness and employ a concavity approach to establish the blow-up result.</p></abstract>

Developing Topographic Map Study Skills in Advanced-Level Geography Students: A Teacher’s Experiences

Map work is a core component of the geography curriculum, but it presents unique challenges for both students and teachers. Students must have a high level of cognitive and conceptual development to read and interpret a map. Teachers, too, often find it difficult to instill the necessary skills for graphic literacy. The unique challenges associated with topographic map study skills are highly relevant to the choice of this subject. The primary goal of this study was to help advanced-level geography students improve their topographic map study skills. For this study, the action research method was used as a research method. Following the pre-test, four students with lower grades were chosen as a sample. Thematic analysis is performed on the data. This research found that most of the students in year 12 felt that they had some issues with incorrect topography identification based on map observation, incorrect recognition of standard symbols from map observation, incorrectly calculating the area of a map, difficulties comprehending the relationship between physical and cultural landscapes, and difficulties with reading and analysing a map. The research then revealed that students require fundamental knowledge of drawing, reading, and interpreting maps. It is also critical to teach map work in as practical a manner as possible. Teachers can use models as teaching aids and the group discussion method as a teaching method to help students develop these skills. Teachers’ peer intervention, individual attention, and discussion with friends all help to increase knowledge of basic topographic map concepts. It contends that the sophistication and complexity of the skills required to interpret topographical maps should not be underestimated. Teachers must be made aware of how students acquire map reading skills and the difficulties they face during this process so that teaching programmes that correspond to students’ levels of cognitive development can be developed. The study’s findings and recommendations have implications for geography teachers, textbook authors, and educational authorities, particularly those involved in curriculum and syllabus development.

When Protein Structure Embedding Meets Large Language Models.

Protein structure analysis is essential in various bioinformatics domains such as drug discovery, disease diagnosis, and evolutionary studies. Within structural biology, the classification of protein structures is pivotal, employing machine learning algorithms to categorize structures based on data from databases like the Protein Data Bank (PDB). To predict protein functions, embeddings based on protein sequences have been employed. Creating numerical embeddings that preserve vital information while considering protein structure and sequence presents several challenges. The existing literature lacks a comprehensive and effective approach that combines structural and sequence-based features to achieve efficient protein classification. While large language models (LLMs) have exhibited promising outcomes for protein function prediction, their focus primarily lies on protein sequences, disregarding the 3D structures of proteins. The quality of embeddings heavily relies on how well the geometry of the embedding space aligns with the underlying data structure, posing a critical research question. Traditionally, Euclidean space has served as a widely utilized framework for embeddings. In this study, we propose a novel method for designing numerical embeddings in Euclidean space for proteins by leveraging 3D structure information, specifically employing the concept of contact maps. These embeddings are synergistically combined with features extracted from LLMs and traditional feature engineering techniques to enhance the performance of embeddings in supervised protein analysis. Experimental results on benchmark datasets, including PDB Bind and STCRDAB, demonstrate the superior performance of the proposed method for protein function prediction.

Optimal Tilt-Wing eVTOL Takeoff Trajectory Prediction Using Regression Generative Adversarial Networks

Electric vertical takeoff and landing (eVTOL) aircraft have attracted tremendous attention nowadays due to their flexible maneuverability, precise control, cost efficiency, and low noise. The optimal takeoff trajectory design is a key component of cost-effective and passenger-friendly eVTOL systems. However, conventional design optimization is typically computationally prohibitive due to the adoption of high-fidelity simulation models in an iterative manner. Machine learning (ML) allows rapid decision making; however, new ML surrogate modeling architectures and strategies are still desired to address large-scale problems. Therefore, we showcase a novel regression generative adversarial network (regGAN) surrogate for fast interactive optimal takeoff trajectory predictions of eVTOL aircraft. The regGAN leverages generative adversarial network architectures for regression tasks with a combined loss function of a mean squared error (MSE) loss and an adversarial binary cross-entropy (BC) loss. Moreover, we introduce a surrogate-based inverse mapping concept into eVTOL optimal trajectory designs for the first time. In particular, an inverse-mapping surrogate takes design requirements (including design constraints and flight condition parameters) as input and directly predicts optimal trajectory designs, with no need to run design optimizations once trained. We demonstrated the regGAN on optimal takeoff trajectory designs for the Airbus A3 Vahana. The results revealed that regGAN outperformed reference surrogate strategies, including multi-output Gaussian processes and conditional generative adversarial network surrogates, by matching simulation-based ground truth with 99.6% relative testing accuracy using 1000 training samples. A parametric study showed that a regGAN surrogate with an MSE weight of one and a BC weight of 0.01 consistently achieved over 99.5% accuracy (denoting negligible predictive errors) using 400 training samples, while other regGAN models require at least 800 samples.

EVALUATING NAVIGATION PERFORMANCE OF ELASTICALLY CONSTRUCTED HD MAP WITH MULTI-SENSOR FUSION ENGINE SYSTEM

Abstract. In response to the rapid development of autonomous vehicles and the increasing demand for HD maps, the conventional mapping processes following HD maps guidelines require significant manpower and time resources. Therefore, we propose flexible procedures and methods for HD maps creation, aiming to reduce cost expenditure by employing diverse source of ground control point, sensor data collection, and mapping algorithm. This approach accelerates the production speed and capability of HD maps. In this study, we select Taiwan's National Highway No. 8 as the trial field for the elastic HD map construction method, and equipped with autonomous vehicle-grade GNSS, IMU, and LiDAR systems.We align the constructed-map data to the global coordinate system, in order to realize the concept of control point cloud map. To assess the assistance and correction capabilities of HD maps in autonomous vehicle navigation systems, we conduct accuracy evaluation through both direct and indirect methods, and analyse the strengths and weaknesses of each approach. The analysis result demonstrates that the elastic method-built HD maps not only meet the mapping accuracy requirements specified in the HD maps verification and validation guidelines, but also assist autonomous vehicles in realizing positioning, navigation, and timing with “where in lane” level (0.5 meter) accuracy.

Viewing the concept of creation and genetic mapping of the traditional weaving process from the perspective of utensils-- taking the flat barrel cage as an example

China's traditional hand-knitting process resources are quite rich, the hand-knitting process resources are missing with the worrying of current situation because of various reasons. To return the weaving process to the stage of life and improve the lifestyle of modern people, we explore the inheritance and innovative positioning of the traditional weaving process in modern life from the starting point of traditional handicraft weaving. By taking the ‘Flat barrel cage’ as an example to study and analyze its material composition, shape structure, compilation method, etc., as well as the interpretation of the creation concept and the drawing of the genetic map, the concept of creation transmitted through the traditional hand-woven process is obtained for modern design. The deeper artistic aesthetic value, the gene map can well integrate traditional weaving craftsmanship into modern craftsmanship, so that it can better innovate and inherit.

Analysis of accessibility map concept for integrated transfer hub

Transportation accessibility for people with disabilities is the challenge of our time. In Poland, there are more than 3 million people with disabilities who have legal proof of disability. In reality, there are many more - from 4 to as many as 7 million. Thus, there is a need to actively include this group of people in social life, including in the area of public transportation. This work aims to present issues related to the accessibility of integrated interchanges for people with special needs. The work also points to a key issue for transport system managers related to and aggregation of knowledge necessary to implement the changes in transport infrastructure. Information about the needs of people with disabilities is, in turn, a prerequisite for proper universal design, which is already becoming noticeable in many areas of social and economic life. As technology evolves, so do the methods of obtaining information about the needs of people with disabilities. The difficulty here, however, is to develop tools that take into account the degree of disability of the specific people from whom we would like to obtain information. The authors in the paper justify, on the one hand, measures that aim to eliminate the difficulties that a person with special needs may encounter when traveling by various means of transportation, and on the other hand, point to certain solutions and tools that are used to acquire knowledge that will consequently allow the precise adaptation of the current infrastructure to the needs precisely defined by these people. The aggregation of knowledge also has additional significance in terms of increasing transportation accessibility for people with disabilities. It enables the informed design of new facilities and supporting infrastructure to take into account the changing needs of people with disabilities.

Application of fixed point theorems in triple bipolar controlled metric space to solve cantilever beam problem

In this article, we introduce the notion of triple bipolar controlled metric space and prove some new fixed point theorems on this space, reformulate the concept of α-admissible mapping with respect to θ in triple bipolar controlled metric space, and introduce the concept of α-admissible crooked mapping with respect to θ in triple bipolar controlled metric space. We supported our results with suitable examples. We also present an application of the derived result to prove the existence and uniqueness solution of the cantilever beam problem, which is in fourth-order differential equation form.

From frequency to intensity – A new index for annual large-scale cropping intensity mapping

Continuous population growth, global warming, extreme weather and local wars pose considerable challenges to agricultural production. Excessive agricultural intensification may lead to serious environmental problems such as water resources depletion and non-point source pollution. Sustainable agricultural intensification is a potential solution, and cropping intensity and its spatio-temporal patterns are of great significance to the planet hearth, human well-being and sustainable development of agriculture. However, traditional methods for cropping intensity mapping lack the deep analysis of crop phenology and failure to consider the spatial detail, spatial coverage and time continuity simultaneously. Existing cropping intensity indicators, such as cropping frequency or multiple crop index, have their limitations in China because of its diverse topographies and fragmented landscapes. In actual fact, few indicators for fine cropping intensity have been developed that address this problem. Time series vegetation index data contain meaningful vegetation phenology information. Information mining on these data can provide new insights for cropping intensity mapping. In this study, the concept of systematic mapping was put forward to measure cropping intensity with a fresh perspective. A new phenology-based cropping intensity index (PCII) was proposed to reach the goal of “from frequency to intensity” in cropping intensity mapping. Through thoroughly exploring the temporal spectral characteristics of croplands and considering the crop pattern as a whole, PCII set up the mapping between cropping intensity and land-cover types. The method can accurately map cropping intensity even though the study spanned a vast area, and can handle the effects of geographical differentiation caused by vegetation phenology differences. It can also precisely measure cropping intensity at the abundance level and reflect the heterogeneity within a pixel. It’s a novel method for annual fine cropping intensity mapping at large-scale and long-term.

OPTIMIZING GEOSPATIAL LITERACY: A QUALITATIVE EXPLORATION OF GOOGLE EARTH AS AN EFFECTIVE LEARNING TOOL IN PRIMARY EDUCATION

The utilization of information technology in the field of education, particularly Google Earth, has become a significant breakthrough. This article examines the potential of Google Earth as a map learning tool at SDN Sidomulyo 02. The research focuses on students and teachers from grades 4-6, employing a qualitative approach with a case study. The research results indicate an improvement in student engagement, a better understanding of map concepts, and increased learning motivation. Google Earth provides a dynamic, visual, and interactive experience, allowing students to explore the world virtually. This advantage is evident in the identification of map symbols, understanding legends, and interpreting geographical information. A comparison with conventional methods emphasizes the superiority of Google Earth in the context of map learning, supporting a contextual learning approach. Despite the positive outcomes, challenges in implementation involve a learning curve for teachers. Therefore, advanced training and technical support are key to the effectiveness of Google Earth usage. This article contributes to a deeper understanding of the positive impact of Google Earth on students' geospatial literacy. Its implications include recommendations for teachers and policymakers to integrate learning technologies, especially Google Earth, into elementary education curricula. As a significant contribution, this research paves the way for the broader use of similar technologies in elementary education and serves as a foundation for further research in the development of learning methods that integrate technology.