scholarly journals An Extra Tree Regression Model for Discharge Coefficient Prediction: Novel, Practical Applications in the Hydraulic Sector and Future Research Directions

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Mohammed Majeed Hameed ◽  
Mohamed Khalid AlOmar ◽  
Faidhalrahman Khaleel ◽  
Nadhir Al-Ansari
Keyword(s):  
Discharge Coefficient ◽  
Basic Knowledge ◽  
Future Research ◽  
Geometrical Parameters ◽  
Practical Applications ◽  
Proposed Model ◽  
Future Research Directions ◽  
Learning Machine ◽  
Side Weirs ◽  
Tree Regression Model

Despite modern advances used to estimate the discharge coefficient ( C d ), it is still a major challenge for hydraulic engineers to accurately determine C d for side weirs. In this study, extra tree regression (ETR) was used to predict the C d of rectangular sharp-crested side weirs depending on hydraulic and geometrical parameters. The prediction capacity of the ETR model was validated with two predictive models, namely, extreme learning machine (ELM) and random forest (RF). The quantitative assessment revealed that the ETR model achieved the highest accuracy in the predictions compared to other applied models, and also, it exhibited excellent agreement between measured and predicted C d (correlation coefficient is 0.9603). Moreover, the ETR achieved 6.73% and 22.96% higher prediction accuracy in terms of root mean square error in comparison to ELM and RF, respectively. Furthermore, the performed sensitivity analysis shows that the geometrical parameter such as b/B has the most influence on C d . Overall, the proposed model (ETR) is found to be a suitable, practical, and qualified computer-aid technology for C d modeling that may contribute to enhance the basic knowledge of hydraulic considerations.

Social Networks in Sport: Parental Influence on the Coach-Athlete Relationship

2005 ◽  
Vol 19 (3) ◽  
pp. 267-287 ◽  
Author(s):  
Sophia Jowett ◽  
Melina Timson-Katchis
Keyword(s):  
Social Networks ◽  
Parental Influence ◽  
Future Research ◽  
Network Member ◽  
Relevant Research ◽  
Research Directions ◽  
Practical Applications ◽  
Proposed Model ◽  
Future Research Directions

The study aims to explore the nature of influences that parents exert on the quality of the dyadic coach-athlete relationship. A conceptual model was proposed as a guiding framework for the study. The proposed model incorporates Sprecher, Felmlee, Orbuch, and Willets’ (2002) notion of social networks and Jowett and Cockerill’s (2002) conceptualization of coach-athlete relationships. Fifteen participants from five coach-athleteparent triads were interviewed, and content analysis revealed that athletes’ parents (a “psychologically significant” network member) provided a range of information, opportunities, and extensive emotional support, all of which influenced the quality of the coach-athlete relationship as defined by closeness, commitment, and complementarity. Results are discussed based on previous relevant research along with recommendations for future research directions and practical applications.

scholarly journals Distributed Ledger Technology Applications in Food Supply Chains: A Review of Challenges and Future Research Directions

2021 ◽  
Vol 13 (8) ◽  
pp. 4206
Author(s):  
Jamilya Nurgazina ◽  
Udsanee Pakdeetrakulwong ◽  
Thomas Moser ◽  
Gerald Reiner
Keyword(s):  
Supply Chains ◽  
Food Supply ◽  
Information Exchange ◽  
Security And Privacy ◽  
Future Research ◽  
Research Directions ◽  
Practical Applications ◽  
Food Supply Chains ◽  
Distributed Ledger ◽  
Future Research Directions

The lack of transparency and traceability in food supply chains (FSCs) is raising concerns among consumers and stakeholders about food information credibility, food quality, and safety. Insufficient records, a lack of digitalization and standardization of processes, and information exchange are some of the most critical challenges, which can be tackled with disruptive technologies, such as the Internet of Things (IoT), blockchain, and distributed ledger technologies (DLTs). Studies provide evidence that novel technological and sustainable practices in FSCs are necessary. This paper aims to describe current practical applications of DLTs and IoT in FSCs, investigating the challenges of implementation, and potentials for future research directions, thus contributing to achievement of the United Nations’ Sustainable Development Goals (SDGs). Within a systematic literature review, the content of 69 academic publications was analyzed, describing aspects of implementation and measures to address the challenges of scalability, security, and privacy of DLT, and IoT solutions. The challenges of high costs, standardization, regulation, interoperability, and energy consumption of DLT solutions were also classified as highly relevant, but were not widely addressed in literature. The application of DLTs in FSCs can potentially contribute to 6 strategic SDGs, providing synergies and possibilities for more sustainable, traceable, and transparent FSCs.

scholarly journals Beyond Intra-modality: A Survey of Heterogeneous Person Re-identification

2020 ◽  
Author(s):  
Zheng Wang ◽  
Zhixiang Wang ◽  
Yinqiang Zheng ◽  
Yang Wu ◽  
Wenjun Zeng ◽  
...  
Keyword(s):  
Video Analysis ◽  
State Of The Art ◽  
Future Research ◽  
Low Resolution ◽  
Research Directions ◽  
Comprehensive Review ◽  
Practical Applications ◽  
Future Research Directions

An efficient and effective person re-identification (ReID) system relieves the users from painful and boring video watching and accelerates the process of video analysis. Recently, with the explosive demands of practical applications, a lot of research efforts have been dedicated to heterogeneous person re-identification (Hetero-ReID). In this paper, we provide a comprehensive review of state-of-the-art Hetero-ReID methods that address the challenge of inter-modality discrepancies. According to the application scenario, we classify the methods into four categories --- low-resolution, infrared, sketch, and text. We begin with an introduction of ReID, and make a comparison between Homogeneous ReID (Homo-ReID) and Hetero-ReID tasks. Then, we describe and compare existing datasets for performing evaluations, and survey the models that have been widely employed in Hetero-ReID. We also summarize and compare the representative approaches from two perspectives, i.e., the application scenario and the learning pipeline. We conclude by a discussion of some future research directions. Follow-up updates are available at https://github.com/lightChaserX/Awesome-Hetero-reID

When and Why Does Passion for Work Predict Well- and Ill-Being?

2019 ◽  
pp. 263-300
Author(s):  
Claude Fernet ◽  
Sarah-Geneviève Trépanier ◽  
Stéphanie Austin ◽  
Louise Clément
Keyword(s):  
Work Environment ◽  
Work Stress ◽  
Psychological Health ◽  
Future Research ◽  
Psychological Processes ◽  
Proposed Model ◽  
Future Research Directions ◽  
Moderating Role ◽  
Passion For Work

The present chapter provides an integrative review of the work stress literature while referring to the empirical evidence on passion for work in relation to psychological health, that is, well- and ill-being manifestations. Drawing on recent scientific literature, the chapter presents an extended dualist model of passion in adaptation to the work environment, which aims to identify work environment factors that are associated with well- and ill-being, and to examine the moderating role of passion for work in the psychological processes associated with psychological health. Results confirming the proposed model are presented, as well as future research directions.

scholarly journals Advancements in Deep Learning Theory and Applications: Perspective in 2020 and beyond

2020 ◽  
Author(s):  
Md Nazmus Saadat ◽  
Muhammad Shuaib
Keyword(s):  
Deep Learning ◽  
Open Source ◽  
Language Processing ◽  
Future Research ◽  
Learning In Context ◽  
Postgraduate Students ◽  
History Of ◽  
Learning Platforms ◽  
Future Research Directions ◽  
Learning Machine

The aim of this chapter is to introduce newcomers to deep learning, deep learning platforms, algorithms, applications, and open-source datasets. This chapter will give you a broad overview of the term deep learning, in context to deep learning machine learning, and Artificial Intelligence (AI) is also introduced. In Introduction, there is a brief overview of the research achievements of deep learning. After Introduction, a brief history of deep learning has been also discussed. The history started from a famous scientist called Allen Turing (1951) to 2020. In the start of a chapter after Introduction, there are some commonly used terminologies, which are used in deep learning. The main focus is on the most recent applications, the most commonly used algorithms, modern platforms, and relevant open-source databases or datasets available online. While discussing the most recent applications and platforms of deep learning, their scope in future is also discussed. Future research directions are discussed in applications and platforms. The natural language processing and auto-pilot vehicles were considered the state-of-the-art application, and these applications still need a good portion of further research. Any reader from undergraduate and postgraduate students, data scientist, and researchers would be benefitted from this.

FORECASTING FOREIGN EXCHANGE RATES WITH ARTIFICIAL NEURAL NETWORKS: A REVIEW

2004 ◽  
Vol 03 (01) ◽  
pp. 145-165 ◽  
Author(s):  
WEI HUANG ◽  
K. K. LAI ◽  
Y. NAKAMORI ◽  
SHOUYANG WANG
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Exchange Rates ◽  
Network Architecture ◽  
Future Research ◽  
Promising Alternative ◽  
Practical Applications ◽  
Future Research Directions ◽  
Artificial Neural ◽  
Input Variables

Forecasting exchange rates is an important financial problem that is receiving increasing attention especially because of its difficulty and practical applications. Artificial neural networks (ANNs) have been widely used as a promising alternative approach for a forecasting task because of several distinguished features. Research efforts on ANNs for forecasting exchange rates are considerable. In this paper, we attempt to provide a survey of research in this area. Several design factors significantly impact the accuracy of neural network forecasts. These factors include the selection of input variables, preparing data, and network architecture. There is no consensus about the factors. In different cases, various decisions have their own effectiveness. We also describe the integration of ANNs with other methods and report the comparison between performances of ANNs and those of other forecasting methods, and finding mixed results. Finally, the future research directions in this area are discussed.

scholarly journals Optical metasurfaces towards multifunctionality and tunability

Nanophotonics ◽  
2022 ◽  
Vol 0 (0) ◽  
Author(s):  
Kang Du ◽  
Hamdi Barkaoui ◽  
Xudong Zhang ◽  
Limin Jin ◽  
Qinghai Song ◽  
...  
Keyword(s):  
Research Field ◽  
Design Methods ◽  
Research Progress ◽  
Future Research ◽  
Innovative Design ◽  
Practical Applications ◽  
Light Manipulation ◽  
Optical Effects ◽  
New Material ◽  
Future Research Directions

Abstract Optical metasurfaces is a rapidly developing research field driven by its exceptional applications for creating easy-to-integrate ultrathin planar optical devices. The tight confinement of the local electromagnetic fields in resonant photonic nanostructures can boost many optical effects and offer novel opportunities for the nanoscale control of light–matter interactions. However, once the structure-only metasurfaces are fabricated, their functions will be fixed, which limits it to make breakthroughs in practical applications. Recently, persistent efforts have led to functional multiplexing. Besides, dynamic light manipulation based on metasurfaces has been demonstrated, providing a footing ground for arbitrary light control in full space-time dimensions. Here, we review the latest research progress in multifunctional and tunable metasurfaces. Firstly, we introduce the evolution of metasurfaces and then present the concepts, the basic principles, and the design methods of multifunctional metasurface. Then with more details, we discuss how to realize metasurfaces with both multifunctionality and tunability. Finally, we also foresee various future research directions and applications of metasurfaces including innovative design methods, new material platforms, and tunable metasurfaces based metadevices.

Motivations and Barriers to the Adoption of 3G Mobile Multimedia Services

2008 ◽  
pp. 182-192 ◽  
Author(s):  
M. Pagani ◽  
D. Schipani
Keyword(s):  
Technology Acceptance ◽  
Mobile Services ◽  
Future Research ◽  
Mobile Multimedia ◽  
End User ◽  
Multimedia Services ◽  
Italian Market ◽  
Proposed Model ◽  
Future Research Directions ◽  
Acceptance Model

This chapter provides an end-user perspective on mobile multimedia services that are likely to emerge with the roll out of Third Generation Mobile Services (3G). More specifically, the objectives of the study are: to provide an insight into current behavior in terms of attitudes towards, access and usage of multimedia mobile services by current end users; to establish main clusters of mobile users; to investigate the possible motivations and barriers of usage of new mobile multimedia services as viewed by current users. The remainder of this chapter is organized into the following four sections. The first section provides a brief review of the literature on the technology acceptance model. Next we present our research model based on a qualitative exploratory survey conducted in six markets. Then we test the proposed model on the Italian market and present the analysis and results of our study. Finally we make conclusions by discussing the implications of our study, followed by presenting future research directions.

A Survey on Privacy Preserving Dynamic Data Publishing

2021 ◽  
pp. 1635-1657
Author(s):  
Salheddine Kabou ◽  
Sidi mohamed Benslimane ◽  
Mhammed Mosteghanemi
Keyword(s):  
Data Privacy ◽  
Privacy Preservation ◽  
Personal Information ◽  
Privacy Preserving ◽  
Data Publishing ◽  
Future Research ◽  
Dynamic Data ◽  
Practical Applications ◽  
New Process ◽  
Future Research Directions

Many organizations, especially small and medium business (SMB) enterprises require the collection and sharing of data containing personal information. The privacy of this data must be preserved before outsourcing to the commercial public. Privacy preserving data publishing PPDP refers to the process of publishing useful information while preserving data privacy. A variety of approaches have been proposed to ensure privacy by applying traditional anonymization models which focused only on the single publication of datasets. In practical applications, data publishing is more complicated where the organizations publish multiple times for different recipients or after modifications to provide up-to-date data. Privacy preserving dynamic data publication PPDDP is a new process in privacy preservation which addresses the anonymization of the data for different purposes. In this survey, the author will systematically evaluate and summarize different studies to PPDDP, clarify the differences and requirements between the scenarios that can exist, and propose future research directions.

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