An extensive review on restoration technologies for mining tailings

2018 ◽  
Vol 25 (34) ◽  
pp. 33911-33925 ◽  
Author(s):  
Wei Sun ◽  
Bin Ji ◽  
Sultan Ahmed Khoso ◽  
Honghu Tang ◽  
Runqing Liu ◽  
...  
2018 ◽  
Vol 15 (2) ◽  
pp. 17
Author(s):  
Mohamad Rahimi Mohamad Rosman ◽  
Mohammad Azhan Abdul Aziz

Content management is an organisational effort of managing content, particularly in digital format. Although it has been over 25 years since content management was introduced, this field of study is still considered an emerging topic with unresolved issues-in particular, the subject of benefit achievement. Therefore, grounded on an extensive review of 135 articles, the purpose of this study is to investigate the benefits that organisations can gain through the proper use of an Enterprise Content Management System (ECMS). Subsequently, this paper identifies a list of ECMS benefits and proposes an ECMS benefit framework for further exploration into this field. Our result shows that although ECMS does bring benefits to organisations, these benefits are diverse; indicating that there are certain determinants or factors influencing the achievement of such benefits. Moreover, it is also found that in the context of the benefit framework of Shang and Seddon [10], three categories were found relevant to the field of content management: operational benefit, managerial benefit, and strategic benefit.


Heliyon ◽  
2021 ◽  
Vol 7 (2) ◽  
pp. e06093
Author(s):  
Larissa S.S. Araújo ◽  
Silvana Q. Silva ◽  
Mônica C. Teixeira

Author(s):  
M. G. Lemos ◽  
T. Valente ◽  
A. P. Marinho-Reis ◽  
R. Fonsceca ◽  
J. M. Dumont ◽  
...  

Technologies ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 2
Author(s):  
Ashish Jaiswal ◽  
Ashwin Ramesh Babu ◽  
Mohammad Zaki Zadeh ◽  
Debapriya Banerjee ◽  
Fillia Makedon

Self-supervised learning has gained popularity because of its ability to avoid the cost of annotating large-scale datasets. It is capable of adopting self-defined pseudolabels as supervision and use the learned representations for several downstream tasks. Specifically, contrastive learning has recently become a dominant component in self-supervised learning for computer vision, natural language processing (NLP), and other domains. It aims at embedding augmented versions of the same sample close to each other while trying to push away embeddings from different samples. This paper provides an extensive review of self-supervised methods that follow the contrastive approach. The work explains commonly used pretext tasks in a contrastive learning setup, followed by different architectures that have been proposed so far. Next, we present a performance comparison of different methods for multiple downstream tasks such as image classification, object detection, and action recognition. Finally, we conclude with the limitations of the current methods and the need for further techniques and future directions to make meaningful progress.


Technologies ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 22
Author(s):  
Eljona Zanaj ◽  
Giuseppe Caso ◽  
Luca De Nardis ◽  
Alireza Mohammadpour ◽  
Özgü Alay ◽  
...  

In the last years, the Internet of Things (IoT) has emerged as a key application context in the design and evolution of technologies in the transition toward a 5G ecosystem. More and more IoT technologies have entered the market and represent important enablers in the deployment of networks of interconnected devices. As network and spatial device densities grow, energy efficiency and consumption are becoming an important aspect in analyzing the performance and suitability of different technologies. In this framework, this survey presents an extensive review of IoT technologies, including both Low-Power Short-Area Networks (LPSANs) and Low-Power Wide-Area Networks (LPWANs), from the perspective of energy efficiency and power consumption. Existing consumption models and energy efficiency mechanisms are categorized, analyzed and discussed, in order to highlight the main trends proposed in literature and standards toward achieving energy-efficient IoT networks. Current limitations and open challenges are also discussed, aiming at highlighting new possible research directions.


2021 ◽  
Vol 35 (1) ◽  
pp. 24-28
Author(s):  
Rhishikesh Thakre

In October 2020, the neonatal resuscitation science update was published with several new treatment guidelines. The changes are based on an extensive review of literature using the GRADE process, addressing 22 topics. Topics for the review of interest include initial oxygen concentration for term and preterm infants, suctioning for clear and meconium-stained liquor, use of sustained lung inflation for ventilation, appropriate route for drug delivery, and extent of duration of resuscitation.


2013 ◽  
Vol 33 (10) ◽  
pp. 1457-1469 ◽  
Author(s):  
Kirsten E. Pijls ◽  
Daisy M. A. E. Jonkers ◽  
Elhaseen E. Elamin ◽  
Ad A. M. Masclee ◽  
Ger H. Koek

2016 ◽  
Vol 160 ◽  
pp. 6-11 ◽  
Author(s):  
Eleazar Salinas-Rodríguez ◽  
Juan Hernández-Ávila ◽  
Isauro Rivera-Landero ◽  
Eduardo Cerecedo-Sáenz ◽  
Ma. Isabel Reyes-Valderrama ◽  
...  

Author(s):  
Alessandro Varacca ◽  
Giovanni Guastella ◽  
Stefano Pareglio ◽  
Paolo Sckokai

Abstract The impact of the European Union common agricultural policy direct payments on land prices has received substantial attention in recent years, leading to heterogeneous evidence of capitalisation for both coupled and decoupled payments. In this paper, we provide an extensive review of the empirical works addressing this issue econometrically and compare their results through a Bayesian meta-regression model, focussing on the impact of decoupling and its implementation schemes. We find that the introduction of decoupled payments increased the capitalisation rate, although the extent of this increment hinges on the implementation scheme adopted by the member state.


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