scholarly journals Exploring Research Trends and Building a Multidisciplinary Framework Related to Brownfield: A Visual Analysis Using CiteSpace

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Xinjia Zhang ◽  
Yang Song ◽  
Shijun Wang ◽  
Sitong Qian
Keyword(s):  
Visual Analysis ◽  
Temporal Distribution ◽  
Research Direction ◽  
Evolutionary Trends ◽  
Research Directions ◽  
Main Research ◽  
Theoretical Support ◽  
Modern Cities ◽  
Critical Issues ◽  
And Cluster Analysis

Brownfield has become one of the critical issues in modern cities. Over the past few decades, a considerable number of papers on brownfield research have been published. This study reviewed 773 documents themed with “brownfield” in the Web of Science core database between 1980 and 2020 and used the CiteSpace software to sort out the spatial and temporal distribution, knowledge groups, subject structures and hotspot fields, and evolutionary trends of global brownfield research. The analysis focuses on distribution of lead authors and their institutions, high-frequency categories and keywords, high influential journals, author contribution, and evolutionary trends based on coword analysis, coauthor analysis, cocitation analysis, and cluster analysis of documents. On the basis of the aforementioned keywords, clusters, and citation bursts analysis, this paper establishes a multidisciplinary framework for brownfield research, suggesting the main research directions for the future development, which provides theoretical support and practical guidance for the research direction of future brownfield research.

scholarly journals The Main Research Directions in CA Assembly Analysis and Assembly Workstation Design

2018 ◽  
Vol 26 (42) ◽  
pp. 69-75
Author(s):  
Štefan Václav ◽  
Katarína Senderská ◽  
Albert Mareš
Keyword(s):  
Process Analysis ◽  
Research Direction ◽  
Assembly Process ◽  
Research Directions ◽  
Digital Factory ◽  
Main Research ◽  
Workstation Design ◽  
Computer Aided ◽  
Analysis Computer ◽  
Assembly Analysis

Abstract The article deals with main research direction in the field of assembly process analysis and assembly workstation design. The basic applied methods and tool in the mentioned research direction are a part of digital factory concept. The paper presents the application of knowledge system for DFA analysis, computer aided assembly, workstation design and application of virtual reality.

scholarly journals Visual Analysis on Information Theory and Science of Complexity Approaches in Healthcare Research

Entropy ◽  
2020 ◽  
Vol 22 (1) ◽  
pp. 109 ◽  
Author(s):  
Xiaoyu Wang ◽  
Wang Zhao ◽  
Yongzhong Wang ◽  
Qin Zhao ◽  
Xuejie Yang ◽  
...  
Keyword(s):  
Information Theory ◽  
Visual Analysis ◽  
Temporal Distribution ◽  
Research Direction ◽  
Healthcare Research ◽  
Research Field ◽  
Future Research ◽  
Knowledge Support ◽  
Analytical Tools ◽  
Research Hotspots

In order to explore the knowledge base, research hotspot, development status, and future research direction of healthcare research based on information theory and complex science, a total of 3031 literature data samples from the core collection of Web of Science from 2003 to 2019 were selected for bibliometric analysis. HistCite, CiteSpace, Excel, and other analytical tools were used to deeply analyze and visualize the temporal distribution, spatial distribution, knowledge evolution, literature co-citation, and research hotspots of this field. This paper reveals the current development of healthcare research field based on information theory and science of complexity, analyzes and discusses the research hotspots and future development that trends in this field, and provides important knowledge support for researchers in this field for further relevant research.

scholarly journals IoT-based smart cities: a bibliometric analysis and literature review

2021 ◽  
Vol 13 (2) ◽  
pp. 115-136
Author(s):  
Katarzyna Szum
Keyword(s):  
Internet Of Things ◽  
Bibliometric Analysis ◽  
Smart Cities ◽  
Research Process ◽  
Security And Privacy ◽  
Research Directions ◽  
Main Research ◽  
Modern Cities ◽  
Research Themes ◽  
Record Selection

Abstract Modern cities face many challenges related to globalisation, metropolisation and digitalisation. The smart city concept, which has been gaining popularity in recent years, is considered an answer to their needs. One of the paradigms of modern smart cities is the Internet of Things. This article aims to identify the main research directions and trends in the scientific literature in the field of Internet-of-Things-based smart cities. The author of the paper conducted a bibliometric analysis of publications from 2012–2021, collected from the Web of Science, Scopus and IEEE Xplore databases. The methodology includes: (i) the selection of databases and key words, (ii) defining search criteria, (iii) data export, creation of an aggregate database and record selection, and (iv) the analysis of the results and identification of the major research trends. The study involved 1019 publications. The last stage of the research process identified the leading countries, institutions, journals, and authors in terms of publication activity, as well as the most frequently occurring terms. The key word analysis allowed identifying five main research directions: IoT application domains in smart cities, IoT architecture for smart cities, energy, security and privacy and data. Within each area, the main research themes have been identified, and selected publications have been reviewed.

scholarly journals Development of Sustainable Thinking by Information Literacy

2021 ◽  
Vol 13 (3) ◽  
pp. 1287
Author(s):  
Angela Repanovici ◽  
Cristina Salcă Rotaru ◽  
Cristinel Murzea
Keyword(s):  
Information Literacy ◽  
Web Of Science ◽  
Scientific Information ◽  
Close Correlation ◽  
Research Direction ◽  
Research Directions ◽  
Main Research ◽  
Qualitative Research Study ◽  
New Research ◽  
Scientometric Study

Developing the sustainable thinking of students is an important preoccupation of specialists, teachers, and civil society. Information literacy represents the development of students’ skills to search, identify, evaluate, and ethically use scientific information. Is there a connection between sustainable thinking (ST) and information literacy (IL)? Through a scientometric study in the Web of Science (WOS) database, the authors identify clusters of keywords, analyze the articles identified in WOS, and identify the main research directions and the existing concepts. At the same time, a qualitative research study is performed regarding the opinions of students who participated in the IL class. By corroborating and interpreting the results obtained by the two previously mentioned research, the authors demonstrate a close correlation between the two, thus creating an extended map of these concepts, a limited map of the concepts used, and a theoretical map of the concepts. The connection between information literacy and the development of ST is demonstrated, thus creating the premise for a new research direction.

scholarly journals Modules and Techniques for Motion Planning: An Industrial Perspective

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 420
Author(s):  
Stefano Quer ◽  
Luz Garcia
Keyword(s):  
Data Fusion ◽  
Autonomous Driving ◽  
Random Trees ◽  
Approximation Techniques ◽  
Main Research ◽  
Autonomous Cars ◽  
Critical Issues ◽  
Relative Errors ◽  
Path Planner ◽  
Many Core

Research on autonomous cars has become one of the main research paths in the automotive industry, with many critical issues that remain to be explored while considering the overall methodology and its practical applicability. In this paper, we present an industrial experience in which we build a complete autonomous driving system, from the sensor units to the car control equipment, and we describe its adoption and testing phase on the field. We report how we organize data fusion and map manipulation to represent the required reality. We focus on the communication and synchronization issues between the data-fusion device and the path-planner, between the CPU and the GPU units, and among different CUDA kernels implementing the core local planner module. In these frameworks, we propose simple representation strategies and approximation techniques which guarantee almost no penalty in terms of accuracy and large savings in terms of memory occupation and memory transfer times. We show how we adopt a recent implementation on parallel many-core devices, such as CUDA-based GPGPU, to reduce the computational burden of rapidly exploring random trees to explore the state space along with a given reference path. We report on our use of the controller and the vehicle simulator. We run experiments on several real scenarios, and we report the paths generated with the different settings, with their relative errors and computation times. We prove that our approach can generate reasonable paths on a multitude of standard maneuvers in real time.

scholarly journals Tomato Leaf Disease Diagnosis Based on Improved Convolution Neural Network by Attention Module

Agriculture ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 651
Author(s):  
Shengyi Zhao ◽  
Yun Peng ◽  
Jizhan Liu ◽  
Shuo Wu
Keyword(s):  
Neural Network ◽  
High Performance ◽  
Model Comparison ◽  
Research Direction ◽  
Disease Diagnosis ◽  
Tomato Leaf ◽  
Identification Accuracy ◽  
Main Research ◽  
Proposed Model ◽  
Complex Features

Crop disease diagnosis is of great significance to crop yield and agricultural production. Deep learning methods have become the main research direction to solve the diagnosis of crop diseases. This paper proposed a deep convolutional neural network that integrates an attention mechanism, which can better adapt to the diagnosis of a variety of tomato leaf diseases. The network structure mainly includes residual blocks and attention extraction modules. The model can accurately extract complex features of various diseases. Extensive comparative experiment results show that the proposed model achieves the average identification accuracy of 96.81% on the tomato leaf diseases dataset. It proves that the model has significant advantages in terms of network complexity and real-time performance compared with other models. Moreover, through the model comparison experiment on the grape leaf diseases public dataset, the proposed model also achieves better results, and the average identification accuracy of 99.24%. It is certified that add the attention module can more accurately extract the complex features of a variety of diseases and has fewer parameters. The proposed model provides a high-performance solution for crop diagnosis under the real agricultural environment.

Review on Relationships of Temperature History, Fatigue Damage and Microstructure Evolution Mechanism of Concrete

2014 ◽  
Vol 584-586 ◽  
pp. 944-950 ◽  
Author(s):  
Dong Fu Zhao ◽  
Mei Liu ◽  
Shi Ji Zhang
Keyword(s):  
High Temperature ◽  
Fatigue Damage ◽  
Microstructure Evolution ◽  
Research Direction ◽  
Concrete Research ◽  
Temperature History ◽  
Evolution Mechanism ◽  
Main Research ◽  
High Temperature Process ◽  
Application Prospects

The domestic and overseas research progresses of microstructure of the concrete and fatigue damage after treated by high temperature are reviewed. The main research direction and current shortage on the high temperature process, fatigue damage and the microstructure evolution mechanism of concrete are discussed. A view of the application prospects of concrete research on the high temperature process, fatigue damage and the microstructure evolution mechanism of concrete is forecast.

Deep learning approach for UHF RFID-based indoor localization

2021 ◽  
pp. 1-13
Author(s):  
Haishu Ma ◽  
Zongzheng Ma ◽  
Lixia Li ◽  
Ya Gao
Keyword(s):  
Radio Frequency Identification ◽  
Indoor Environment ◽  
Indoor Localization ◽  
Estimation Error ◽  
Research Direction ◽  
Linear Interpolation ◽  
Linear Mapping ◽  
Uhf Rfid ◽  
Indoor Location ◽  
Main Research

Due to the proliferation of the IoT devices, indoor location-based service is bringing huge business values and potentials. The positioning accuracy is restricted by the variability and complexity of the indoor environment. Radio Frequency Identification (RFID), as a key technology of the Internet of Things, has became the main research direction in the field of indoor positioning because of its non-contact, non-line-of-sight and strong anti-interference abilities. This paper proposes the deep leaning approach for RFID based indoor localization. Since the measured Received Signal Strength Indicator (RSSI) can be influenced by many indoor environment factors, Kalman filter is applied to erase the fluctuation. Furthermore, linear interpolation is adopted to increase the density of the reference tags. In order to improve the processing ability of the fingerprint database, deep neural network is adopted together with the fingerprinting method to optimize the non-linear mapping between fingerprints and indoor coordinates. The experimental results show that the proposed method achieves high accuracy with a mean estimation error of 0.347 m.

scholarly journals Research status of human resource management in China based on scientific knowledge map

2021 ◽  
Vol 251 ◽  
pp. 03096
Author(s):  
Kun Qian ◽  
Yingxue Li ◽  
Yuenan Lv ◽  
Xiaonan Yang
Keyword(s):  
Cluster Analysis ◽  
Resource Management ◽  
Human Resource Management ◽  
Human Resource ◽  
Scientific Knowledge ◽  
Visual Analysis ◽  
Future Research ◽  
Knowledge Map ◽  
Management Research ◽  
And Cluster Analysis

In order to accurately grasp the current research frontier of human resource management, according to certain retrieval conditions, 2724 literatures published from 2011 to 2021 were retrieved from CNKI database as data samples. CiteSpace software was used for visual analysis, CO citation analysis and cluster analysis were carried out on these literature data, and the corresponding knowledge map was drawn. The objective of this paper is to show the hot topics and cutting-edge trends of human resource management research in China and draw the current situation of human resource management research in China, in order to provide reference for future research.

scholarly journals Neuropolityka – geneza, założenia, perspektywy rozwoju

2021 ◽  
Vol 5 ◽  
pp. 37-54
Author(s):  
Piotr Rutkowski ◽  
Jacek Ziółkowski
Keyword(s):  
Political Science ◽  
Interdisciplinary Research ◽  
Research Area ◽  
Research Directions ◽  
Biological Determinism ◽  
Main Research ◽  
Negative Results ◽  
Nature And Culture ◽  
Development Prospects ◽  
Research Tools

Neuropolityka to interdyscyplinarny obszar badań, znajdujący się na przecięciu nauk, łączący nauki polityczne z neuronaukami. Nie jest to jednak kolejny kierunek, który, zakłada determinizm biologiczny. Opiera się na przekonaniu o przenikaniu się natury i kultury w człowieku, warstwy cielesnej i umysłowej. Celem artykułu jest przybliżenie czytelnikowi historycznych i teoretycznych aspektów tego wciąż rozwijającego się obszaru badawczego. Naszkicowane zostały również narzędzia badawcze oraz główne kierunki badań neuropolitycznych. Autorzy wskazują na pozytywne jak i negatywne, skutki płynące z badań neuropolitycznych, oraz perspektywy stojące przed naukami o polityce i neuronaukami. Neuropolitics – Genesis, Assumptions, Development Prospects Neuropolitcs is an interdisciplinary research area, located at the intersection of various sciences, combining political science with neuroscience. However, it is not another direction that, as it may seem assumes biological determinism. It is based on belief about the interfusion of nature and culture, physical and mental dimensions in man. The aim of article is to familiarize the reader with the historical and theoretical aspects of this still developing research area. Also the research tools and main research directions of neuropolics were outlined. Authors indicate the positive and negative results of neuropolitics research and perspectives for political science and neurosciences.

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