scholarly journals Visualizing the Knowledge Structure and Research Evolution of Infrared Detection Technology Studies

Information ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 227 ◽  
Author(s):  
Rui Hong ◽  
Chenglang Xiang ◽  
Hui Liu ◽  
Adam Glowacz ◽  
Wei Pan
Keyword(s):  
Thermal Imaging ◽  
Citation Index ◽  
Infrared Detection ◽  
Current Status ◽  
Future Research ◽  
Technology Research ◽  
Main Research ◽  
Detection Techniques ◽  
Technology Studies ◽  
Detection Technology

This paper aims to explore the current status, research trends and hotspots related to the field of infrared detection technology through bibliometric analysis and visualization techniques based on the Science Citation Index Expanded (SCIE) and Social Sciences Citation Index (SSCI) articles published between 1990 and 2018 using the VOSviewer and Citespace software tools. Based on our analysis, we first present the spatiotemporal distribution of the literature related to infrared detection technology, including annual publications, origin country/region, main research organization, and source publications. Then, we report the main subject categories involved in infrared detection technology. Furthermore, we adopt literature cocitation, author cocitation, keyword co-occurrence and timeline visualization analyses to visually explore the research fronts and trends, and present the evolution of infrared detection technology research. The results show that China, the USA and Italy are the three most active countries in infrared detection technology research and that the Centre National de la Recherche Scientifique has the largest number of publications among related organizations. The most prominent research hotspots in the past five years are vibration thermal imaging, pulse thermal imaging, photonic crystals, skin temperature, remote sensing technology, and detection of delamination defects in concrete. The trend of future research on infrared detection technology is from qualitative to quantitative research development, engineering application research and infrared detection technology combined with other detection techniques. The proposed approach based on the scientific knowledge graph analysis can be used to establish reference information and a research basis for application and development of methods in the domain of infrared detection technology studies.

scholarly journals Comprehensive Analysis on the Performance and Material of Automobile Brake Discs

Metals ◽  
2020 ◽  
Vol 10 (3) ◽  
pp. 377 ◽  
Author(s):  
Wanyang Li ◽  
Xuefeng Yang ◽  
Shouren Wang ◽  
Jupeng Xiao ◽  
Qimin Hou
Keyword(s):  
Current Status ◽  
Future Research ◽  
Brake Disc ◽  
Main Research ◽  
Brake Discs ◽  
The Matrix ◽  
Fiber Materials ◽  
Brake Noise ◽  
Composite Heat ◽  
Automotive Brake

This article reviews the current status of automotive brake disc research and the prospects for future research. At present, the research of brake disc performance mainly includes thermal conductivity, thermal fatigue resistance, wear resistance, and brake noise. It is found that a new alloy composite, heat treatment process, ceramic composite, new structure, and new materials are emerging. At the same time, it was found that ceramic and resin were used as the matrix, fiber materials were used as reinforcements to prepare brake discs, the addition of new fillers and the study of special reinforcement materials have become new hotspots in the study of brake discs. In the future development, carbon-fiber ceramic brake discs may become the main research focus of brake discs.

scholarly journals Human Face Detection Techniques: A Comprehensive Review and Future Research Directions

Electronics ◽  
2021 ◽  
Vol 10 (19) ◽  
pp. 2354
Author(s):  
Md Khaled Hasan ◽  
Md. Shamim Ahsan ◽  
Abdullah-Al-Mamun ◽  
S. H. Shah Newaz ◽  
Gyu Myoung Lee
Keyword(s):  
Face Detection ◽  
Future Research ◽  
Research Directions ◽  
Detection Techniques ◽  
Detection Algorithms ◽  
Detection Technology ◽  
The Neural Network ◽  
Comprehensive Survey ◽  
Computational Resources ◽  
Working Procedure

Face detection, which is an effortless task for humans, is complex to perform on machines. The recent veer proliferation of computational resources is paving the way for frantic advancement of face detection technology. Many astutely developed algorithms have been proposed to detect faces. However, there is little attention paid in making a comprehensive survey of the available algorithms. This paper aims at providing fourfold discussions on face detection algorithms. First, we explore a wide variety of the available face detection algorithms in five steps, including history, working procedure, advantages, limitations, and use in other fields alongside face detection. Secondly, we include a comparative evaluation among different algorithms in each single method. Thirdly, we provide detailed comparisons among the algorithms epitomized to have an all-inclusive outlook. Lastly, we conclude this study with several promising research directions to pursue. Earlier survey papers on face detection algorithms are limited to just technical details and popularly used algorithms. In our study, however, we cover detailed technical explanations of face detection algorithms and various recent sub-branches of the neural network. We present detailed comparisons among the algorithms in all-inclusive and under sub-branches. We provide the strengths and limitations of these algorithms and a novel literature survey that includes their use besides face detection.

Exploring the knowledge domain of earthquake prediction based on bibliometric analysis and text mining

2021 ◽  
pp. 1-17
Author(s):  
Xiaorong He
Keyword(s):  
Text Mining ◽  
Bibliometric Analysis ◽  
Earthquake Prediction ◽  
Citation Index ◽  
Knowledge Domain ◽  
Scientific Publications ◽  
Main Research ◽  
Detection Techniques ◽  
Subject Categories ◽  
Earthquake Research

Earthquake prediction is one of the important themes of earthquake research, and it is also a very difficult scientific problem in the world. In this study, a bibliometric analysis is conducted on the scientific publications about earthquake prediction indexed in SCIE (Science Citation Index Expanded) and SSCI (Social Sciences Citation Index) databases during the past two decades (1998–2017). The subject categories, annual and journal distributions, leading countries/regions and institutions are investigated in this field. The main research topics are identified through text mining method. The research trends are explored by keyword co-occurrence analysis and bursting keywords detection techniques. The results of this study are helpful for scholars in this field to find the knowledge structure and important participants. It is also helpful for scholars to seize the current research hotspots and future development trends in this field.

Advances in Information Foraging Research

2014 ◽  
Vol 701-702 ◽  
pp. 1376-1379
Author(s):  
Bing Wu ◽  
Chen Yan Zhang
Keyword(s):  
Information Search ◽  
Citation Index ◽  
Web Design ◽  
Research Area ◽  
Future Research ◽  
Research Information ◽  
Information Foraging ◽  
Engineering Research ◽  
Main Research ◽  
Research Software

Information Foraging Theory (IFT) explains and predicts how people navigate in response to the information in their environment. It has proven particularly helpful in both behavior prediction and practical utility for Web design. We gleaned from science citation index expanded (SCI-EXPANED) and Social Sciences Citation Index (SSCI) database on web of science, concerning advances in information foraging research. The result indicates that the main research territory is USA accounting for 64.706%, then followed by IRELAND of 11.765%. Accordingly, the organizations are Indiana Univ Natl Univ Ireland Univ Coll Cork, Oregon State Univ Parc and Univ Memphis. The number of publication literature on this topic mainly distributes in recently 7 years, reaching climax of 6 in 2013. And from the analysis of research area, research on computer science accounts for 70.588%. Accordingly the percentage of source title as decision support systems is 11.765%. Overall, the related research topics can be classified in four areas: long tail research, software engineering research, information search behaviour and emergency response. New opportunities for future research are discussed in the end.

Development of Precision Medical Technology and its Current Clinical Applications

2021 ◽  
Vol 15 ◽  
Author(s):  
Ziwen Wang ◽  
Yuanying Chi ◽  
Kaiye Gao ◽  
Rui Peng
Keyword(s):  
Big Data ◽  
Precision Medicine ◽  
Gene Editing ◽  
Gene Sequencing ◽  
Clinical Applications ◽  
Current Status ◽  
Cellular Immunotherapy ◽  
Future Research ◽  
Main Research ◽  
Key Technologies

Background: Precision medicine has emerged with the development of science and technology and the rise of big data. This study first defines and presents the advantages of precision medicine and then introduces the development of three technologies: gene sequencing, cellular immunotherapy, and gene editing. The clinical applications of precision medicine in lung cancer, cervical cancer, breast cancer, and prostate cancer are thus analyzed. Lastly, the existing problems and future development directions of precision medicine are identified. The introduction of gene sequencing, bioanalytical techniques, and big data analysis tools has propelled medicine into the era of precision medicine. Key technologies in precision medicine form the foundation of its development. Therefore, this study elaborates on the development of key technologies in precision medicine, the current status of its clinical application, and the main problems that currently exist. This study also suggests solutions to the problems. Objective: To systematically explain the development and principle of three core technologies in precision medicine and to predict the main research trends of precision medicine. Results: Research in gene sequencing, cell immunotherapy, and gene editing technology has shown significant progress, and accurate medical treatment has achieved remarkable results, effectively prolonging the survival time and improving the quality of life of patients. Conclusion: Precision medicine has made significant achievements, but problems remain. Ensuring safety and efficiency in precision medicine should be the focus of future research.

Advances in Online Authority Research

2014 ◽  
Vol 596 ◽  
pp. 994-997
Author(s):  
Bing Wu ◽  
Chen Yan Zhang
Keyword(s):  
Social Sciences ◽  
Public Relations ◽  
Online Community ◽  
Web Of Science ◽  
Citation Index ◽  
Research Area ◽  
Future Research ◽  
Main Research ◽  
Social Sciences Citation Index ◽  
Science Citation Index Expanded

As previous research has established that communication and public relations play a crucial role, to understand the resources needed for effective online intervention has been proven particularly helpful to locate in time the central issue. Science citation index expanded (SCI-EXPANED) and Social Sciences Citation Index (SSCI) database on web of science are gleaned, concerning advances in online authority research. The result indicates that the main research territory is England, accounting for 30%, then followed by USA and Spain of 20% respectively. The number of publication literature on this topic mainly distributes in recent 5 years, reaching climax of 4 in 2011. And from the analysis of research area, research on communication accounts for 40%, then followed by computer science of 30%. Overall, the related research topics can be classified in four areas: evaluation of the online authority, cognitive search models, authority in online community and online authority communication. Finally, new opportunities for future research are discussed.

Android Malware Detection Techniques: A Literature Review

2020 ◽  
Vol 14 ◽  
Author(s):  
Meghna Dhalaria ◽  
Ekta Gandotra
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Malware Detection ◽  
Future Research ◽  
Android Malware ◽  
Detection Techniques ◽  
Android Malware Detection ◽  
Future Research Directions ◽  
To Come ◽  
Tools And Techniques

Purpose: This paper provides the basics of Android malware, its evolution and tools and techniques for malware analysis. Its main aim is to present a review of the literature on Android malware detection using machine learning and deep learning and identify the research gaps. It provides the insights obtained through literature and future research directions which could help researchers to come up with robust and accurate techniques for classification of Android malware. Design/Methodology/Approach: This paper provides a review of the basics of Android malware, its evolution timeline and detection techniques. It includes the tools and techniques for analyzing the Android malware statically and dynamically for extracting features and finally classifying these using machine learning and deep learning algorithms. Findings: The number of Android users is expanding very fast due to the popularity of Android devices. As a result, there are more risks to Android users due to the exponential growth of Android malware. On-going research aims to overcome the constraints of earlier approaches for malware detection. As the evolving malware are complex and sophisticated, earlier approaches like signature based and machine learning based are not able to identify these timely and accurately. The findings from the review shows various limitations of earlier techniques i.e. requires more detection time, high false positive and false negative rate, low accuracy in detecting sophisticated malware and less flexible. Originality/value: This paper provides a systematic and comprehensive review on the tools and techniques being employed for analysis, classification and identification of Android malicious applications. It includes the timeline of Android malware evolution, tools and techniques for analyzing these statically and dynamically for the purpose of extracting features and finally using these features for their detection and classification using machine learning and deep learning algorithms. On the basis of the detailed literature review, various research gaps are listed. The paper also provides future research directions and insights which could help researchers to come up with innovative and robust techniques for detecting and classifying the Android malware.

Novel Coronavirus Disease (COVID-19): A Narrative Review Based on Current Status

2020 ◽  
Vol 18 ◽  
Author(s):  
Rina Das ◽  
Dinesh Kumar Mehta ◽  
Meenakshi Dhanawat
Keyword(s):  
Severe Acute Respiratory Syndrome ◽  
Clinical Symptoms ◽  
Virus Disease ◽  
Relevant Literature ◽  
World Health ◽  
Current Status ◽  
Future Research ◽  
Treatment And Prevention ◽  
First Case ◽  
Novel Coronavirus

Abstract:: A novel virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), appeared and expanded globally by the end of year in 2019 from Wuhan, China, causing severe acute respiratory syndrome. During its initial stage, the disease was called the novel coronavirus (2019-nCoV). It was named COVID-19 by the World Health Organization (WHO) on 11 February 2020. The WHO declared worldwide the SARS-CoV-2 virus a pandemic on March 2020. On 30 January 2020 the first case of Corona Virus Disease 2019 (COVID-19) was reported in India. Now in current situation the virus is floating in almost every part of the province and rest of the globe. -: On the basis of novel published evidences, we efficiently summarized the reported work with reference to COVID-19 epidemiology, pathogen, clinical symptoms, treatment and prevention. Using several worldwide electronic scientific databases such as Pubmed, Medline, Embase, Science direct, Scopus, etc were utilized for extensive investigation of relevant literature. -: This review is written in the hope of encouraging the people successfully with the key learning points from the underway efforts to perceive and manage SARS-CoV-2, suggesting sailent points for expanding future research.

scholarly journals Consumer Neuroscience Techniques in Advertising Research: A Bibliometric Citation Analysis

2021 ◽  
Vol 13 (3) ◽  
pp. 1589
Author(s):  
Juan Sánchez-Fernández ◽  
Luis-Alberto Casado-Aranda ◽  
Ana-Belén Bastidas-Manzano
Keyword(s):  
Self Report ◽  
Future Research ◽  
Complex Nature ◽  
Clear Understanding ◽  
Continuous Growth ◽  
Main Research ◽  
Consumer Neuroscience ◽  
Starting Point ◽  
Wide Range ◽  
Performance Analysis Tools

The limitations of self-report techniques (i.e., questionnaires or surveys) in measuring consumer response to advertising stimuli have necessitated more objective and accurate tools from the fields of neuroscience and psychology for the study of consumer behavior, resulting in the creation of consumer neuroscience. This recent marketing sub-field stems from a wide range of disciplines and applies multiple types of techniques to diverse advertising subdomains (e.g., advertising constructs, media elements, or prediction strategies). Due to its complex nature and continuous growth, this area of research calls for a clear understanding of its evolution, current scope, and potential domains in the field of advertising. Thus, this current research is among the first to apply a bibliometric approach to clarify the main research streams analyzing advertising persuasion using neuroimaging. Particularly, this paper combines a comprehensive review with performance analysis tools of 203 papers published between 1986 and 2019 in outlets indexed by the ISI Web of Science database. Our findings describe the research tools, journals, and themes that are worth considering in future research. The current study also provides an agenda for future research and therefore constitutes a starting point for advertising academics and professionals intending to use neuroimaging techniques.

Sign in / Sign up

Export Citation Format

Share Document