scholarly journals Engineering Human–Machine Teams for Trusted Collaboration

2020 ◽  
Vol 4 (4) ◽  
pp. 35
Author(s):  
Basel Alhaji ◽  
Janine Beecken ◽  
Rüdiger Ehlers ◽  
Jan Gertheiss ◽  
Felix Merz ◽  
...  
Keyword(s):  
Systems Engineering ◽  
State Of The Art ◽  
Research Work ◽  
Future Research ◽  
Engineering Systems ◽  
Intensive Research ◽  
Intelligent Machines ◽  
Interdisciplinary Approaches ◽  
Industrial Assembly ◽  
Core Requirements

The way humans and artificially intelligent machines interact is undergoing a dramatic change. This change becomes particularly apparent in domains where humans and machines collaboratively work on joint tasks or objects in teams, such as in industrial assembly or disassembly processes. While there is intensive research work on human–machine collaboration in different research disciplines, systematic and interdisciplinary approaches towards engineering systems that consist of or comprise human–machine teams are still rare. In this paper, we review and analyze the state of the art, and derive and discuss core requirements and concepts by means of an illustrating scenario. In terms of methods, we focus on how reciprocal trust between humans and intelligent machines is defined, built, measured, and maintained from a systems engineering and planning perspective in literature. Based on our analysis, we propose and outline three important areas of future research on engineering and operating human–machine teams for trusted collaboration. For each area, we describe exemplary research opportunities.

Learning Non-Taxonomic Relations of Ontologies

2021 ◽  
Vol 17 (1) ◽  
pp. 97-122
Author(s):  
Mohamed Hassan Mohamed Ali ◽  
Said Fathalla ◽  
Mohamed Kholief ◽  
Yasser Fouad Hassan
Keyword(s):  
Systematic Review ◽  
State Of The Art ◽  
Research Work ◽  
Semantic Knowledge ◽  
Future Research ◽  
Automatic Extraction ◽  
Ontology Learning ◽  
Comprehensive Understanding ◽  
Specific Domain ◽  
Taxonomic Relations

Ontologies, as semantic knowledge representation, have a crucial role in various information systems. The main pitfall of manually building ontologies is effort and time-consuming. Ontology learning is a key solution. Learning Non-Taxonomic Relationships of Ontologies (LNTRO) is the process of automatic/semi-automatic extraction of all possible relationships between concepts in a specific domain, except the hierarchal relations. Most of the research works focused on the extraction of concepts and taxonomic relations in the ontology learning process. This article presents the results of a systematic review of the state-of-the-art approaches for LNTRO. Sixteen approaches have been described and qualitatively analyzed. The solutions they provide are discussed along with their respective positive and negative aspects. The goal is to provide researchers in this area a comprehensive understanding of the drawbacks of the existing work, thereby encouraging further improvement of the research work in this area. Furthermore, this article proposes a set of recommendations for future research.

scholarly journals Deep Learning-Based Monocular Depth Estimation Methods—A State-of-the-Art Review

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2272 ◽  
Author(s):  
Faisal Khan ◽  
Saqib Salahuddin ◽  
Hossein Javidnia
Keyword(s):  
Deep Learning ◽  
State Of The Art ◽  
Research Work ◽  
Depth Estimation ◽  
Autonomous Driving ◽  
Estimation Methods ◽  
Future Research ◽  
Comprehensive Overview ◽  
Ill Posed ◽  
Monocular Depth

Monocular depth estimation from Red-Green-Blue (RGB) images is a well-studied ill-posed problem in computer vision which has been investigated intensively over the past decade using Deep Learning (DL) approaches. The recent approaches for monocular depth estimation mostly rely on Convolutional Neural Networks (CNN). Estimating depth from two-dimensional images plays an important role in various applications including scene reconstruction, 3D object-detection, robotics and autonomous driving. This survey provides a comprehensive overview of this research topic including the problem representation and a short description of traditional methods for depth estimation. Relevant datasets and 13 state-of-the-art deep learning-based approaches for monocular depth estimation are reviewed, evaluated and discussed. We conclude this paper with a perspective towards future research work requiring further investigation in monocular depth estimation challenges.

scholarly journals A bibliometric approach to quantitatively assess current research trends in 5G security

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
M. Najmul Islam Farooqui ◽  
Junaid Arshad ◽  
Muhammad Mubashir Khan
Keyword(s):  
State Of The Art ◽  
Research Work ◽  
Quantitative Description ◽  
Research Trends ◽  
Security And Privacy ◽  
Future Research ◽  
Content Type ◽  
Research Areas ◽  
Art Research ◽  
5G Security

PurposeAlongside the remarkable evolution of cellular communication to 5G networks, significant security and privacy challenges have risen which can affect the widespread adoption of advanced communication technologies. In this context, the purpose of this paper is to examine research within security and privacy for 5G-based systems highlighting contributions made by the research community and identify research trends within different subdomains of 5G security where open issues still exist.Design/methodology/approachThis paper uses a bibliographic approach to review the state-of-the-art in the field of 5G security and is the pioneering effort to investigate 5G security research using this methodology. Specifically, the paper presents a quantitative description of the existing contributions in terms of authors, organizations, and countries. It then presents detailed keyword and co-citation analysis that shows the quantity and pattern of research work in different subfields. Finally, 5G security areas are identified having open challenges for future research work.FindingsThe study shows that China leads the world in terms of published research in the field of 5G security with USA and India ranked second and third respectively. Xidian University, China is ranked highest for number of publications and h-index followed by University Oulu and AALTO University Finland. IEEE Access, Sensors and IEEE Internet of Things Journal are the top publication venues in the field of 5G security. Using VOSViewer aided analysis with respect to productivity, research areas and keywords, the authors have identified research trends in 5G security among scientific community whilst highlighting specific challenges which require further efforts.Originality/valueExisting studies have focused on surveys covering state-of-the art research in secure 5G network (Zhang et al. 2019), physical layer security (Wu et al., 2018), security and privacy of 5G technologies (Khan et al., 2020) and security and privacy challenges when 5G is used in IoT (Sicari et al. 2020). However, our research has revealed no existing bibliometric studies in this area and therefore, to our best knowledge, this paper represents pioneering such effort for security within 5G.

scholarly journals Advances in Agriculture Robotics: A State-of-the-Art Review and Challenges Ahead

Robotics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 52
Author(s):  
Luiz F. P. Oliveira ◽  
António P. Moreira ◽  
Manuel F. Silva
Keyword(s):  
Computer Vision ◽  
State Of The Art ◽  
Research Work ◽  
Development Stage ◽  
Robotic Systems ◽  
Future Research ◽  
Yield Estimation ◽  
Commercial Development ◽  
Land Preparation ◽  
Smart Agriculture

The constant advances in agricultural robotics aim to overcome the challenges imposed by population growth, accelerated urbanization, high competitiveness of high-quality products, environmental preservation and a lack of qualified labor. In this sense, this review paper surveys the main existing applications of agricultural robotic systems for the execution of land preparation before planting, sowing, planting, plant treatment, harvesting, yield estimation and phenotyping. In general, all robots were evaluated according to the following criteria: its locomotion system, what is the final application, if it has sensors, robotic arm and/or computer vision algorithm, what is its development stage and which country and continent they belong. After evaluating all similar characteristics, to expose the research trends, common pitfalls and the characteristics that hinder commercial development, and discover which countries are investing into Research and Development (R&D) in these technologies for the future, four major areas that need future research work for enhancing the state of the art in smart agriculture were highlighted: locomotion systems, sensors, computer vision algorithms and communication technologies. The results of this research suggest that the investment in agricultural robotic systems allows to achieve short—harvest monitoring—and long-term objectives—yield estimation.

PZT Sensors and their Application in Structural Health Monitoring

2011 ◽  
Vol 128-129 ◽  
pp. 669-675 ◽  
Author(s):  
Xuan Sun
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Lamb Wave ◽  
State Of The Art ◽  
Research Work ◽  
Mechanical Systems ◽  
The State ◽  
Theoretical Studies ◽  
Engineering Systems ◽  
Experimental And Theoretical Studies

This paper provides the state of the art in methods to detect damage in structural and mechanical systems by PZT sensors, which include impedance methods and lamb wave propagations. The basic idea behind these technologies is to use impedance of PZT embedded on surface or lamb wave propagations. A brief overview of research work on experimental and theoretical studies on various structures and mechanical systems is descried. Past, current and applications of this technology in actual engineering systems are summarized. Finally, desirable developments for further advancement of this field are discussed.

scholarly journals Advances and Trends in Real Time Visual Crowd Analysis

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5073
Author(s):  
Khalil Khan ◽  
Waleed Albattah ◽  
Rehan Ullah Khan ◽  
Ali Mustafa Qamar ◽  
Durre Nayab
Keyword(s):  
Real Time ◽  
Large Scale ◽  
State Of The Art ◽  
Research Work ◽  
Future Research ◽  
Crowd Analysis ◽  
Crowd Management ◽  
Public Events ◽  
Advantages And Disadvantages ◽  
Art Methods

Real time crowd analysis represents an active area of research within the computer vision community in general and scene analysis in particular. Over the last 10 years, various methods for crowd management in real time scenario have received immense attention due to large scale applications in people counting, public events management, disaster management, safety monitoring an so on. Although many sophisticated algorithms have been developed to address the task; crowd management in real time conditions is still a challenging problem being completely solved, particularly in wild and unconstrained conditions. In the proposed paper, we present a detailed review of crowd analysis and management, focusing on state-of-the-art methods for both controlled and unconstrained conditions. The paper illustrates both the advantages and disadvantages of state-of-the-art methods. The methods presented comprise the seminal research works on crowd management, and monitoring and then culminating state-of-the-art methods of the newly introduced deep learning methods. Comparison of the previous methods is presented, with a detailed discussion of the direction for future research work. We believe this review article will contribute to various application domains and will also augment the knowledge of the crowd analysis within the research community.

A Systematic Literature Review of the EFQM Excellence Model from 1991 to 2019

1970 ◽  
Vol 2 (2) ◽  
pp. 11-15
Author(s):  
Muhammad Yousaf ◽  
Petr Bris
Keyword(s):  
Quality Management ◽  
Data Collection ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Quantitative Research ◽  
Web Of Science ◽  
State Of The Art ◽  
Future Research ◽  
European Foundation ◽  
The Subject

A systematic literature review (SLR) from 1991 to 2019 is carried out about EFQM (European Foundation for Quality Management) excellence model in this paper. The aim of the paper is to present state of the art in quantitative research on the EFQM excellence model that will guide future research lines in this field. The articles were searched with the help of six strings and these six strings were executed in three popular databases i.e. Scopus, Web of Science, and Science Direct. Around 584 peer-reviewed articles examined, which are directly linked with the subject of quantitative research on the EFQM excellence model. About 108 papers were chosen finally, then the purpose, data collection, conclusion, contributions, and type of quantitative of the selected papers are discussed and analyzed briefly in this study. Thus, this study identifies the focus areas of the researchers and knowledge gaps in empirical quantitative literature on the EFQM excellence model. This article also presents the lines of future research.

A Case Study: Analysis of Patents of Coronaviruses and Covid-19 for Technology Assesment and Future Research

2020 ◽  
Vol 26 ◽  
Author(s):  
Pankaj Musyuni ◽  
Geeta Aggarwal ◽  
Manju Nagpal ◽  
Ramesh K. Goyal
Keyword(s):  
Disease Management ◽  
Research And Development ◽  
Technological Development ◽  
Research Work ◽  
Large Family ◽  
Future Research ◽  
Biological Drugs ◽  
Ongoing Research ◽  
Patent Literature ◽  
Patent Documents

Background: Protecting intellectual property rights are important and particularly pertinent for inventions which are an outcome of rigorous research and development. While the grant of patents is subject to establishing novelty and inventive step, it further indicates the technological development and helpful for researchers working in the same technical domain. The aim of the present research work is to map the existing work through analysis of patent literature, in the field of Coronaviruses (CoV), particularly COVID-19 (2019-nCoV). CoV is a large family of viruses known to cause illness in human and animals, particularly known for causing respiratory infections as evidenced in earlier times such as in MERS i.e. Middle East Respiratory Syndrome; SRS i.e. Severe Acute Respiratory Syndrome. A recently identified novel-coronavirus has known as COVID-19 which has currently caused pandemic situation across the globe. Objective: To expand analysis of patents related to CoV and 2019-nCoV. Evaluation has been conducted by patenting trends of particular strains of identified CoV diseases by present legal status, main concerned countries via earliest priority years and its assignee types and inventors of identified relevant patents. We analyzed the global patent documents to check the scope of claims along with focuses and trends of the published patent documents for the entire CoV family including 2019- nCoV through the present landscape. Methods: To extract the results, Derwent Innovation database is used by a combination of different key-strings. Approximately 3800 patents were obtained and further scrutinized and analyzed. The present write-up also discusses the recent progress of patent applications in a period of the year 2010 to 2020 (present) along with the recent developments in India for the treatment options for CoV and 2019-nCoV. Results: Present analysis showed that key areas of the inventions have been focused on vaccines and diagnostic kits apart from the composition for treatment of CoV. We also observed that no specific vaccine treatments is available for treatment of 2019-nCov, however, developing novel chemical or biological drugs and kits for early diagnosis, prevention and disease management is the primarily governing topic among the patented inventions. The present study also indicates potential research opportunities for the future, particularly to combat 2019-nCoV. Conclusion: The present paper analyzes the existing patents in the field of Coronaviruses and 2019-nCoV and suggests a way forward for the effective contribution in this upcoming research area. From the trend analysis, it was observed an increase in filing of the overall trend of patent families for a period of 2010 to the current year. This multifaceted analysis of identified patent literature provides an understanding of the focuses on present ongoing research and grey area in terms of the trends of technological innovations in disease management in patients with CoV and 2019-nCoV. Further, the findings and outcome of the present study offer insights for the proposed research and innovation opportunities and provide actionable information in order to facilitate policymakers, academia, research driven institutes and also investors to make better decisions regarding programmed steps for research and development for the diagnosis, treatment and taking preventive measures for CoV and 2019-nCoV. The present article also emphasizes on the need for future development and the role of academia and collaboration with industry for speedy research with a rationale.

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