Author
Saleh A. Wasimi
Other affiliations: Bangladesh University of Engineering and Technology
Bio: Saleh A. Wasimi is an academic researcher from Central Queensland University. The author has contributed to research in topics: Climate change & Water resources. The author has an hindex of 12, co-authored 43 publications receiving 684 citations. Previous affiliations of Saleh A. Wasimi include Bangladesh University of Engineering and Technology.
Papers
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TL;DR: An extensive review on cloud computing with the main focus on gaps and security concerns is presented, which identifies the top security threats and their existing solutions and investigates the challenges/obstacles in implementing threat remediation.
288 citations
TL;DR: In this article, the authors analyzed historical data revealed that the region is experiencing climate change to a degree higher than other parts of the world, and that it is vulnerable to climate change.
Abstract: Iraq has been experiencing water resources scarcity, and is vulnerable to climate change. Analysis of historical data revealed that the region is experiencing climate change to a degree higher than ...
67 citations
TL;DR: RF and SVM algorithms are efficient and practical to use, and can be implemented easily for detecting weed from UAV images.
Abstract: This paper explores the potential of machine learning algorithms for weed and crop classification from UAV images. The identification of weeds in crops is a challenging task that has been addressed through orthomosaicing of images, feature extraction and labelling of images to train machine learning algorithms. In this paper, the performances of several machine learning algorithms, random forest (RF), support vector machine (SVM) and k-nearest neighbours (KNN), are analysed to detect weeds using UAV images collected from a chilli crop field located in Australia. The evaluation metrics used in the comparison of performance were accuracy, precision, recall, false positive rate and kappa coefficient. MATLAB is used for simulating the machine learning algorithms; and the achieved weed detection accuracies are 96% using RF, 94% using SVM and 63% using KNN. Based on this study, RF and SVM algorithms are efficient and practical to use, and can be implemented easily for detecting weed from UAV images.
65 citations
TL;DR: In this article, the authors revisited, reviewed, modified and recast the underlying theories of periodic autoregressive (PAR) models and proposed new techniques for generating synthetic data from any PAR model with provision to constrain some parameter values to zero.
38 citations
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Journal Article•
9,185 citations
Journal Article•
TL;DR: In this paper, a documento: "Cambiamenti climatici 2007: impatti, adattamento e vulnerabilita" voteato ad aprile 2007 dal secondo gruppo di lavoro del Comitato Intergovernativo sui Cambiamentsi Climatici (Intergovernmental Panel on Climate Change).
Abstract: Impatti, adattamento e vulnerabilita Le cause e le responsabilita dei cambiamenti climatici sono state trattate sul numero di ottobre della rivista Cda. Approfondiamo l’argomento presentando il documento: “Cambiamenti climatici 2007: impatti, adattamento e vulnerabilita” votato ad aprile 2007 dal secondo gruppo di lavoro del Comitato Intergovernativo sui Cambiamenti Climatici (Intergovernmental Panel on Climate Change). Si tratta del secondo di tre documenti che compongono il quarto rapporto sui cambiamenti climatici.
3,979 citations
TL;DR: This paper carefully analyzed and discussed the properties of a monitoring system for the Cloud, the issues arising from such properties and how such issues have been tackled in literature, and identifies open issues, main challenges and future directions in the field of Cloud monitoring.
543 citations
TL;DR: This paper surveys the works on cloud security issues, making a comprehensive review of the literature on the subject and proposes a taxonomy for their classification, addressing several key topics, namely vulnerabilities, threats, and attacks.
Abstract: In the last few years, the appealing features of cloud computing have been fueling the integration of cloud environments in the industry, which has been consequently motivating the research on related technologies by both the industry and the academia. The possibility of paying-as-you-go mixed with an on-demand elastic operation is changing the enterprise computing model, shifting on-premises infrastructures to off-premises data centers, accessed over the Internet and managed by cloud hosting providers. Regardless of its advantages, the transition to this computing paradigm raises security concerns, which are the subject of several studies. Besides of the issues derived from Web technologies and the Internet, clouds introduce new issues that should be cleared out first in order to further allow the number of cloud deployments to increase. This paper surveys the works on cloud security issues, making a comprehensive review of the literature on the subject. It addresses several key topics, namely vulnerabilities, threats, and attacks, proposing a taxonomy for their classification. It also contains a thorough review of the main concepts concerning the security state of cloud environments and discusses several open research topics.
423 citations
TL;DR: The factors affecting Cloud computing adoption, vulnerabilities and attacks are surveyed, and relevant solution directives to strengthen security and privacy in the Cloud environment are identified.
Abstract: Cloud computing offers scalable on-demand services to consumers with greater flexibility and lesser infrastructure investment. Since Cloud services are delivered using classical network protocols and formats over the Internet, implicit vulnerabilities existing in these protocols as well as threats introduced by newer architectures raise many security and privacy concerns. In this paper, we survey the factors affecting Cloud computing adoption, vulnerabilities and attacks, and identify relevant solution directives to strengthen security and privacy in the Cloud environment.
376 citations