scholarly journals UAS-Based Archaeological Remote Sensing: Review, Meta-Analysis and State-of-the-Art

Drones ◽  
2020 ◽  
Vol 4 (3) ◽  
pp. 46 ◽  
Author(s):  
Efstathios Adamopoulos ◽  
Fulvio Rinaudo
Keyword(s):  
Remote Sensing ◽  
State Of The Art ◽  
Meta Analysis ◽  
Visible Spectrum ◽  
Unmanned Aircraft ◽  
Future Research ◽  
Radar Sensors ◽  
Technological Developments ◽  
Aerial Platforms ◽  
Historical Sites

Over the last decade, we have witnessed momentous technological developments in unmanned aircraft systems (UAS) and in lightweight sensors operating at various wavelengths, at and beyond the visible spectrum, which can be integrated with unmanned aerial platforms. These innovations have made feasible close-range and high-resolution remote sensing for numerous archaeological applications, including documentation, prospection, and monitoring bridging the gap between satellite, high-altitude airborne, and terrestrial sensing of historical sites and landscapes. In this article, we track the progress made so far, by systematically reviewing the literature relevant to the combined use of UAS platforms with visible, infrared, multi-spectral, hyper-spectral, laser, and radar sensors to reveal archaeological features otherwise invisible to archaeologists with applied non-destructive techniques. We review, specific applications and their global distribution, as well as commonly used platforms, sensors, and data-processing workflows. Furthermore, we identify the contemporary state-of-the-art and discuss the challenges that have already been overcome, and those that have not, to propose suggestions for future research.

scholarly journals Meta-Analysis of Wetland Classification Using Remote Sensing: A Systematic Review of a 40-Year Trend in North America

2020 ◽  
Vol 12 (11) ◽  
pp. 1882 ◽  
Author(s):  
Masoud Mahdianpari ◽  
Jean Elizabeth Granger ◽  
Fariba Mohammadimanesh ◽  
Bahram Salehi ◽  
Brian Brisco ◽  
...  
Keyword(s):  
Remote Sensing ◽  
North America ◽  
Spatial Resolution ◽  
Meta Analysis ◽  
Future Research ◽  
Wetland Classification ◽  
Classification Methods ◽  
Wetland Ecosystems ◽  
Sensing Technology ◽  
Recreational Benefits

North America is covered in 2.5 million km2 of wetlands, which is the remainder of an estimated 56% of wetlands lost since the 1700s. This loss has resulted in a decrease in important habitat and services of great ecological, economic, and recreational benefits to humankind. To better manage these ecosystems, since the 1970s, wetlands in North America have been classified with increasing regularity using remote sensing technology. Since then, optimal methods for wetland classification by numerous researchers have been examined, assessed, modified, and established. Over the past several decades, a large number of studies have investigated the effects of different remote sensing factors, such as data type, spatial resolution, feature selection, classification methods, and other parameters of interest on wetland classification in North America. However, the results of these studies have not yet been synthesized to determine best practices and to establish avenues for future research. This paper reviews the last 40 years of research and development on North American wetland classification through remote sensing methods. A meta-analysis of 157 relevant articles published since 1980 summarizes trends in 23 parameters, including publication, year, study location, application of specific sensors, and classification methods. This paper also examines is the relationship between several remote sensing parameters (e.g., spatial resolution and type of data) and resulting overall accuracies. Finally, this paper discusses the future of remote sensing of wetlands in North America with regard to upcoming technologies and sensors. Given the increasing importance and vulnerability of wetland ecosystems under the climate change influences, this paper aims to provide a comprehensive review in support of the continued, improved, and novel applications of remote sensing for wetland mapping across North America and to provide a fundamental knowledge base for future studies in this field.

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.

Chasing the Anchor: A Systematic Review and Meta-analysis of Perceptual Anchoring Deficits in Developmental Dyslexia

2020 ◽  
Author(s):  
Kurt D Shulver ◽  
Nicholas A Badcock
Keyword(s):  
Systematic Review ◽  
Reading Ability ◽  
English Language ◽  
Prediction Interval ◽  
Meta Analysis ◽  
Visual Assessment ◽  
Individual Performance ◽  
Future Research ◽  
Significant Heterogeneity ◽  
Eligibility Criteria

We report the results of a systematic review and meta-analysis investigating the relationship between perceptual anchoring and dyslexia. Our goal was to assess the direction and degree of effect between perceptual anchoring and reading ability in typical and atypical (dyslexic) readers. We performed a literature search of experiments explicitly assessing perceptual anchoring and reading ability using PsycInfo (Ovid, 1860 to 2020), MEDLINE (Ovid, 1860 to 2019), EMBASE (Ovid, 1883 to 2019), and PubMed for all available years up to June (2020). Our eligibility criteria consisted of English-language articles and, at minimum, one experimental group identified as dyslexic - either by reading assessment at the time, or by previous diagnosis. We assessed for risk of bias using an adapted version of the Newcastle-Ottawa scale. Six studies were included in this review, but only five (n = 280 participants) were included in the meta-analysis (we were unable to access the necessary data for one study).The overall effect was negative, large and statistically significant; g = -0.87, 95% CI [-1.47, 0.27]: a negative effect size indicating less perceptual anchoring in dyslexic versus non-dyslexic groups. Visual assessment of funnel plot and Egger’s test suggest minimal bias but with significant heterogeneity; Q (4) = 9.70, PI (prediction interval) [-2.32, -0.58]. The primary limitation of the current review is the small number of included studies. We discuss methodological limitations, such as limited power, and how future research may redress these concerns. The variability of effect sizes appears consistent with the inherent variability within subtypes of dyslexia. This level of dispersion seems indicative of the how we define cut-off thresholds between typical reading and dyslexia populations, but also the methodological tools we use to investigate individual performance.

Autobiographical Memory Impairments as a Transdiagnostic Feature of Mental Illness: A meta-analysis of autobiographical memory specificity and overgenerality amongst people with psychiatric diagnoses

2020 ◽  
Author(s):  
Tom Joseph Barry ◽  
David John Hallford ◽  
Keisuke Takano
Keyword(s):  
Autobiographical Memory ◽  
Memory Retrieval ◽  
Keyword Search ◽  
Meta Analysis ◽  
Future Research ◽  
Psychiatric Diagnoses ◽  
Schizophrenia Spectrum Disorders ◽  
Memory Impairments ◽  
Memory Specificity ◽  
Causal Mechanisms

Decades of research has examined the difficulty that people with psychiatric diagnoses, such as Major Depressive Disorder, Schizophrenia Spectrum Disorders, and Posttraumatic Stress Disorder, have in recalling specific autobiographical memories from events that lasted less than a day. Instead, they seem to retrieve general events that have occurred many times or which occurred over longer periods of time, termed overgeneral memory. We present the first transdiagnostic meta-analysis of memory specificity/overgenerality, and the first meta-regression of proposed causal mechanisms. A keyword search of Embase, PsycARTICLES and PsycINFO databases yielded 74 studies that compared people with and without psychiatric diagnoses on the retrieval of specific (k = 85) or general memories (k = 56). Multi-level meta-analysis confirmed that people with psychiatric diagnoses typically recall fewer specific (g = -0.864, 95% CI[-1.030, -0.698]) and more general (g = .712, 95% CI[0.524, 0.900]) memories than diagnoses-free people. The size of these effects did not differ between diagnostic groups. There were no consistent moderators; effect sizes were not explained by methodological factors such as cue valence, or demographic variables such as participants’ age. There was also no support for the contribution of underlying processes that are thought to be involved in specific/general memory retrieval (e.g., rumination). Our findings confirm that deficits in autobiographical memory retrieval are a transdiagnostic factor associated with a broad range of psychiatric problems, but future research should explore novel causal mechanisms such as encoding deficits and the social processes involved in memory sharing and rehearsal.

Challenges and Opportunities for Neuroimaging in Young Patients with Traumatic Brain Injury: a Coordinated Effort towards Advancing Discovery from the ENIGMA Pediatric Moderate/Severe TBI Group

2019 ◽  
Author(s):  
Emily L. Dennis ◽  
Karen Caeyenberghs ◽  
Robert F. Asarnow ◽  
Talin Babikian ◽  
Brenda Bartnik-Olson ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Meta Analysis ◽  
Young Patients ◽  
Future Research ◽  
Childhood And Adolescence ◽  
Developmental Issues ◽  
Challenges And Opportunities ◽  
Severe Tbi ◽  
Advance Research

Traumatic brain injury (TBI) is a major cause of death and disability in children in both developed and developing nations. Children and adolescents suffer from TBI at a higher rate than the general population; however, research in this population lags behind research in adults. This may be due, in part, to the smaller number of investigators engaged in research with this population and may also be related to changes in safety laws and clinical practice that have altered length of hospital stays, treatment, and access to this population. Specific developmental issues also warrant attention in studies of children, and the ever-changing context of childhood and adolescence may require larger sample sizes than are commonly available to adequately address remaining questions related to TBI. The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Pediatric Moderate-Severe TBI (msTBI) group aims to advance research in this area through global collaborative meta-analysis. In this paper we discuss important challenges in pediatric TBI research and opportunities that we believe the ENIGMA Pediatric msTBI group can provide to address them. We conclude with recommendations for future research in this field of study.

The Changing Nature of Knowledge and Service Work in the Age of Intelligent Machines

2020 ◽  
pp. 343-368
Author(s):  
Crispin Coombs ◽  
Donald Hislop ◽  
Stanimira Taneva ◽  
Sarah Barnard
Keyword(s):  
Ethical Issues ◽  
Work Practice ◽  
Academic Disciplines ◽  
Service Work ◽  
Future Research ◽  
Human Capabilities ◽  
Academic Knowledge ◽  
Intelligent Machines ◽  
Technological Developments ◽  
The Impact

One of the most significant recent technological developments concerns the application of intelligent machines to jobs that up to now have been considered safe from automation. These changes have generated considerable debate regarding the impacts that the widespread adoption of intelligent machines could have on the nature of work. This chapter provides a thematic review, across multiple academic disciplines, of the current state of academic knowledge regarding the impact of intelligent machines on knowledge and service work. Adopting a work-practice perspective, the chapter reviews the extant literature concerning changing relations between workers and intelligent machines, the adoption and acceptance of intelligent machines, and ethical issues associated with greater machine human collaboration. A key finding is that much of the research discusses intelligent machines complementing and extending human capabilities rather than removing humans from work processes. The concept of augmentation of humans and human work, rather than wholesale replacement from automation, flows through the literature across a range of domains. The chapter concludes with a discussion of the main gaps in existing knowledge and ways in which future research may provide a deeper understanding of how people (currently and in the near future) experience intelligent machines in their day-to-day work practice. These include the need for multi-disciplinary research, the role of contexts, the need for more and better empirical research, the changing relationships between humans and intelligent machines, the adoption and acceptance of the technology, and ethical issues.

Sign in / Sign up

Export Citation Format

Share Document