Unmanned Aerial Vehicle–Based Traffic Analysis: Methodological Framework for Automated Multivehicle Trajectory Extraction

2017 ◽  
Vol 2626 (1) ◽  
pp. 25-33 ◽  
Author(s):  
Muhammad Arsalan Khan ◽  
Wim Ectors ◽  
Tom Bellemans ◽  
Davy Janssens ◽  
Geert Wets
Keyword(s):  
Traffic Safety ◽  
Video Processing ◽  
Traffic Monitoring ◽  
Future Research ◽  
Methodological Framework ◽  
Vehicle Detection And Tracking ◽  
Potential Applications ◽  
Multiple Vehicles ◽  
Processing Techniques ◽  
Optimal Data Analysis

Unmanned aerial vehicles (UAVs), commonly referred to as drones, are one of the most dynamic and multidimensional emerging technologies of the modern era. This technology has recently found multiple potential applications within the transportation field, ranging from traffic surveillance applications to traffic network analysis. To conduct a UAV-based traffic study, extremely diligent planning and execution are required followed by an optimal data analysis and interpretation procedure. In this study, however, the main focus was on the processing and analysis of UAV-acquired traffic footage. A detailed methodological framework for automated UAV video processing is proposed to extract the trajectories of multiple vehicles at a particular road segment. Such trajectories can be used either to extract various traffic parameters or to analyze traffic safety situations. The proposed framework, which provides comprehensive guidelines for an efficient processing and analysis of a UAV-based traffic study, comprises five components: preprocessing, stabilization, georegistration, vehicle detection and tracking, and trajectory management. Until recently, most traffic-focused UAV studies have employed either manual or semiautomatic processing techniques. In contrast, this paper presents an in-depth description of the proposed automated framework followed by a description of a field experiment conducted in the city of Sint-Truiden, Belgium. Future research will mainly focus on the extension of the applications of the proposed framework in the context of UAV-based traffic monitoring and analysis.

Polymeric nanocomposites reinforced with nanowhiskers: Design, development, and emerging applications

2020 ◽  
Vol 36 (3) ◽  
pp. 312-333
Author(s):  
Ayesha Kausar
Keyword(s):  
Antibacterial Agents ◽  
Water Resistance ◽  
Material Design ◽  
Future Research ◽  
Polymeric Nanocomposites ◽  
Design Development ◽  
Research Directions ◽  
Potential Applications ◽  
Future Research Directions ◽  
Processing Techniques

This article provides insights into nanowhisker nanofiller particles, different categories of polymer/nanowhisker nanocomposites, and broad span of applications. Nanowhiskers are hierarchical needle-like elementary crystallites, often used as nanofillers in polymers. Cellulose, chitin, zinc oxide, fullerene, and aluminum nitride-based nanowhiskers have been employed in matrices. Inclusion of organic and inorganic nanowhiskers in polymers has enhanced thermal conductivity, electrical conductivity, thermal stability, water resistance, and other physical properties of nanocomposites. Polymer/nanowhisker nanocomposites have found technical applications in supercapacitors, sensors, anticorrosion agents, antibacterial agents, and drug delivery systems. Future research directions for potential applications rely on material design, nanowhisker functionalization, better dispersion, better reinforcement, and better processing techniques.

The application of virtual reality in health professions� digital education: a narrative review (Preprint)

2018 ◽  
Author(s):  
Lorraine Tudor Car ◽  
Bhone Myint Kyaw ◽  
Josip Car
Keyword(s):  
Virtual Reality ◽  
Professional Education ◽  
Health Professions ◽  
Health Professions Education ◽  
Narrative Review ◽  
Current Evidence ◽  
Future Research ◽  
Educational Content ◽  
Potential Applications

BACKGROUND Digital technology called Virtual Reality (VR) is increasingly employed in health professions’ education. Yet, based on the current evidence, its use is narrowed around a few most applications and disciplines. There is a lack of an overview that would capture the diversity of different VR applications in health professions’ education and inform its use and research. OBJECTIVE This narrative review aims to explore different potential applications of VR in health professions’ education. METHODS The narrative synthesis approach to literature review was used to analyse the existing evidence. RESULTS We outline the role of VR features such as immersion, interactivity and feedback and explain the role of VR devices. Based on the type and scope of educational content VR can represent space, individuals, objects, structures or their combination. Application of VR in medical education encompasses environmental, organ and micro level. Environmental VR focuses on training in relation to health professionals’ environment and human interactions. Organ VR educational content targets primarily human body anatomy; and micro VR microscopic structures at the level of cells, molecules and atoms. We examine how different VR features and health professional education areas match these three VR types. CONCLUSIONS We conclude by highlighting the gaps in the literature and providing suggestions for future research.

scholarly journals A review of infant cry analysis and classification

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Chunyan Ji ◽  
Thosini Bamunu Mudiyanselage ◽  
Yutong Gao ◽  
Yi Pan
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Signal Analysis ◽  
Future Research ◽  
Prosodic Features ◽  
Infant Cry ◽  
Machine Learning Classification ◽  
Machine Learning Classifiers ◽  
Learning Classifiers ◽  
Processing Techniques

AbstractThis paper reviews recent research works in infant cry signal analysis and classification tasks. A broad range of literatures are reviewed mainly from the aspects of data acquisition, cross domain signal processing techniques, and machine learning classification methods. We introduce pre-processing approaches and describe a diversity of features such as MFCC, spectrogram, and fundamental frequency, etc. Both acoustic features and prosodic features extracted from different domains can discriminate frame-based signals from one another and can be used to train machine learning classifiers. Together with traditional machine learning classifiers such as KNN, SVM, and GMM, newly developed neural network architectures such as CNN and RNN are applied in infant cry research. We present some significant experimental results on pathological cry identification, cry reason classification, and cry sound detection with some typical databases. This survey systematically studies the previous research in all relevant areas of infant cry and provides an insight on the current cutting-edge works in infant cry signal analysis and classification. We also propose future research directions in data processing, feature extraction, and neural network classification fields to better understand, interpret, and process infant cry signals.

scholarly journals Shall I Work with Them? A Knowledge Graph-Based Approach for Predicting Future Research Collaborations

Entropy ◽  
2021 ◽  
Vol 23 (6) ◽  
pp. 664
Author(s):  
Nikos Kanakaris ◽  
Nikolaos Giarelis ◽  
Ilias Siachos ◽  
Nikos Karacapilidis
Keyword(s):  
Language Processing ◽  
Scientific Knowledge ◽  
Link Prediction ◽  
Performance Metrics ◽  
Future Research ◽  
Knowledge Graph ◽  
Prediction Problem ◽  
Textual Information ◽  
Research Collaborations ◽  
Processing Techniques

We consider the prediction of future research collaborations as a link prediction problem applied on a scientific knowledge graph. To the best of our knowledge, this is the first work on the prediction of future research collaborations that combines structural and textual information of a scientific knowledge graph through a purposeful integration of graph algorithms and natural language processing techniques. Our work: (i) investigates whether the integration of unstructured textual data into a single knowledge graph affects the performance of a link prediction model, (ii) studies the effect of previously proposed graph kernels based approaches on the performance of an ML model, as far as the link prediction problem is concerned, and (iii) proposes a three-phase pipeline that enables the exploitation of structural and textual information, as well as of pre-trained word embeddings. We benchmark the proposed approach against classical link prediction algorithms using accuracy, recall, and precision as our performance metrics. Finally, we empirically test our approach through various feature combinations with respect to the link prediction problem. Our experimentations with the new COVID-19 Open Research Dataset demonstrate a significant improvement of the abovementioned performance metrics in the prediction of future research collaborations.

scholarly journals Potential applications of biogenic selenium nanoparticles in alleviating biotic and abiotic stresses in plants: A comprehensive insight on the mechanistic approach and future perspectives

2021 ◽  
Vol 10 (1) ◽  
pp. 456-475
Author(s):  
Efat Zohra ◽  
Muhammad Ikram ◽  
Ahmad A. Omar ◽  
Mujahid Hussain ◽  
Seema Hassan Satti ◽  
...  
Keyword(s):  
Abiotic Stresses ◽  
Crop Production ◽  
Plant Secondary Metabolites ◽  
Selenium Nanoparticles ◽  
Future Research ◽  
Biotic And Abiotic Stresses ◽  
Biotic Stresses ◽  
Agriculture Sector ◽  
Developmental Growth ◽  
Potential Applications

Abstract In the present era, due to the increasing incidence of environmental stresses worldwide, the developmental growth and production of agriculture crops may be restrained. Selenium nanoparticles (SeNPs) have precedence over other nanoparticles because of the significant role of selenium in activating the defense system of plants. In addition to beneficial microorganisms, the use of biogenic SeNPs is known as an environmentally friendly and ecologically biocompatible approach to enhance crop production by alleviating biotic and abiotic stresses. This review provides the latest development in the green synthesis of SeNPs by using the results of plant secondary metabolites in the biogenesis of nanoparticles of different shapes and sizes with unique morphologies. Unfortunately, green synthesized SeNPs failed to achieve significant attention in the agriculture sector. However, research studies were performed to explore the application potential of plant-based SeNPs in alleviating drought, salinity, heavy metal, heat stresses, and bacterial and fungal diseases in plants. This review also explains the mechanistic actions that the biogenic SeNPs acquire to alleviate biotic and abiotic stresses in plants. In this review article, the future research that needs to use plant-mediated SeNPs under the conditions of abiotic and biotic stresses are also highlighted.

Electrochemical polymerization for two-dimensional conjugated polymers

2018 ◽  
Vol 6 (40) ◽  
pp. 10672-10686 ◽  
Author(s):  
Qing Zhang ◽  
Huanli Dong ◽  
Wenping Hu
Keyword(s):  
Conjugated Polymers ◽  
Electrochemical Polymerization ◽  
Research Progress ◽  
Future Research ◽  
Special Focus ◽  
Two Dimensional ◽  
Research Directions ◽  
Potential Applications ◽  
Future Research Directions ◽  
Recent Research Progress

This article places special focus on the recent research progress of the EP method in synthesizing CPs. In particular, their potential applications as 2D CPs are summarized, with a basic introduction of the EP method, its use in synthesizing CPs as well as the promising applications of the obtained CPs in different fields. Discussions of current challenges in this field and future research directions are also given.

scholarly journals Advances in Convolution Neural Networks Based Crowd Counting and Density Estimation

2021 ◽  
Vol 5 (4) ◽  
pp. 50
Author(s):  
Rafik Gouiaa ◽  
Moulay A. Akhloufi ◽  
Mozhdeh Shahbazi
Keyword(s):  
Neural Networks ◽  
Density Estimation ◽  
Traffic Monitoring ◽  
Crowd Counting ◽  
Convolution Neural Networks ◽  
Potential Applications ◽  
Comprehensive Survey ◽  
Camera Perspective ◽  
Aerial Vehicle ◽  
Uav Images

Automatically estimating the number of people in unconstrained scenes is a crucial yet challenging task in different real-world applications, including video surveillance, public safety, urban planning, and traffic monitoring. In addition, methods developed to estimate the number of people can be adapted and applied to related tasks in various fields, such as plant counting, vehicle counting, and cell microscopy. Many challenges and problems face crowd counting, including cluttered scenes, extreme occlusions, scale variation, and changes in camera perspective. Therefore, in the past few years, tremendous research efforts have been devoted to crowd counting, and numerous excellent techniques have been proposed. The significant progress in crowd counting methods in recent years is mostly attributed to advances in deep convolution neural networks (CNNs) as well as to public crowd counting datasets. In this work, we review the papers that have been published in the last decade and provide a comprehensive survey of the recent CNNs based crowd counting techniques. We briefly review detection-based, regression-based, and traditional density estimation based approaches. Then, we delve into detail regarding the deep learning based density estimation approaches and recently published datasets. In addition, we discuss the potential applications of crowd counting and in particular its applications using unmanned aerial vehicle (UAV) images.

scholarly journals Multimedia Image Processing Lab Experiment/Simulation

2020 ◽  
Vol 3 (1) ◽  
pp. 1-13
Author(s):  
Md Mamunur Rashid
Keyword(s):  
Image Processing ◽  
Video Compression ◽  
Video Processing ◽  
Multimedia Systems ◽  
Multimedia System ◽  
Image And Video Processing ◽  
Indexing And Retrieval ◽  
Video Indexing And Retrieval ◽  
Multimedia Image ◽  
Processing Techniques

Image Processing in Multimedia Applications treats a number of critical topics in multimedia systems, with respect to image and video processing techniques and their implementations. These techniques include the Image and video compression techniques and standards, and Image and video indexing and retrieval techniques. Image Processing is an important tool to develop a Multimedia system design.

scholarly journals Entre l’individuel et le social : les motivations d’usage de pornographie

2018 ◽  
Vol 43 (4) ◽  
Author(s):  
Maude Lecompte ◽  
Simon Corneau ◽  
Kim Bernatchez
Keyword(s):  
Sexual Satisfaction ◽  
Qualitative Studies ◽  
Future Research ◽  
Methodological Framework ◽  
Identity Exploration ◽  
Pornography Use ◽  
Intrinsic And Extrinsic Motivations

Background  Although pornography use is widespread, motivations for use may differ depending on certain identity categories.Analysis  This article presents the motivations related to pornography use identified following a metasynthesis as a methodological framework. Using theoretical notions of intrinsic and extrinsic motivations, the metasynthesis allowed us to combine results derived from thirteen qualitative studies that examined motivations for pornography use among various audiences.Conclusions and implications  The motivations identified are: entertainment, sexual satisfaction, fantasy and identity exploration, creation and strengthening of social or emotional ties, learning and information, transgression, and protection. Our results demonstrate that pornography use can be motivated by both social and personal considerations, and suggest that future research should consider the importance of gender and sexual orientation.Contexte  Bien que l’usage de pornographie soit répandu, les motivations pour son usage peuvent différer en fonction de certaines catégories identitaires.Analyse  Cet article présente les motivations d’usage de pornographie documentées au moyen d’une métasynthèse comme cadre méthodologique. Utilisant les notions théoriques de motivation intrinsèque et extrinsèque, la métasynthèse a permis la mise en commun des résultats de treize études qualitatives réalisées auprès de publics variés.Conclusions et implications  Les motivations recensées sont : le divertissement, la satisfaction sexuelle, l’exploration fantasmatique et identitaire, la création et le renforcement de liens sociaux ou affectifs, l’apprentissage et l’information, la transgression et la protection. Les résultats montrent que l’usage de pornographie peut être motivé tant par des considérations sociales que personnelles et soulèvent l’importance de considérer le sexe et l’orientation sexuelle dans les recherches futures.

PLAYER'S POSITIONAL DEPENDENCE OF FRACTAL BEHAVIORS IN A SOCCER GAME

Fractals ◽  
2006 ◽  
Vol 14 (01) ◽  
pp. 71-76 ◽  
Author(s):  
SANGRAK KIM
Keyword(s):  
Time Series ◽  
Video Processing ◽  
Fractal Dimensions ◽  
Two Dimensional ◽  
Severe Attack ◽  
Soccer Game ◽  
Relative Dominance ◽  
Processing Techniques

This paper describes fractal behaviors in a soccer game according to the player's position. It is quite important for us to characterize the fractal motion behaviors of the objects during the game. We obtained two-dimensional coordinates of the objects using standard video processing techniques from a computer soccer game. We calculated values of regularization dimensions of the time series to characterize their fractal behaviors. To see positional dependence, we averaged individual player's values over the same position in the same team. When a team is one-sidedly experiencing a severe attack, its defenders have higher fractal dimensions than those of the opponent's corresponding players. We propose a new measure of relative dominance in attack against the opponent team.

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