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"Hammad, Ahmed"
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Remote Sensing Methods for Flood Prediction: A Review
Floods are a major cause of loss of lives, destruction of infrastructure, and massive damage to a country’s economy. Floods, being natural disasters, cannot be prevented completely; therefore, precautionary measures must be taken by the government, concerned organizations such as the United Nations Office for Disaster Risk Reduction and Office for the coordination of Human Affairs, and the community to control its disastrous effects. To minimize hazards and to provide an emergency response at the time of natural calamity, various measures must be taken by the disaster management authorities before the flood incident. This involves the use of the latest cutting-edge technologies which predict the occurrence of disaster as early as possible such that proper response strategies can be adopted before the disaster. Floods are uncertain depending on several climatic and environmental factors, and therefore are difficult to predict. Hence, improvement in the adoption of the latest technology to move towards automated disaster prediction and forecasting is a must. This study reviews the adoption of remote sensing methods for predicting floods and thus focuses on the pre-disaster phase of the disaster management process for the past 20 years. A classification framework is presented which classifies the remote sensing technologies being used for flood prediction into three types, which are: multispectral, radar, and light detection and ranging (LIDAR). Further categorization is performed based on the method used for data analysis. The technologies are examined based on their relevance to flood prediction, flood risk assessment, and hazard analysis. Some gaps and limitations present in each of the reviewed technologies have been identified. A flood prediction and extent mapping model are then proposed to overcome the current gaps. The compiled results demonstrate the state of each technology’s practice and usage in flood prediction.
Journal Article
Planning universal accessibility to public health care in sub-Saharan Africa
Achieving universal health care coverage—a key target of the United Nations Sustainable Development Goal number 3—requires accessibility to health care services for all. Currently, in sub-Saharan Africa, at least one-sixth of the population lives more than 2 h away from a public hospital, and one in eight people is no less than 1 h away from the nearest health center. We combine high-resolution data on the location of different typologies of public health care facilities [J. Maina et al., Sci. Data 6, 134 (2019)] with population distribution maps and terrain-specific accessibility algorithms to develop a multiobjective geographic information system framework for assessing the optimal allocation of new health care facilities and assessing hospitals expansion requirements. The proposed methodology ensures universal accessibility to public health care services within prespecified travel times while guaranteeing sufficient available hospital beds. Our analysis suggests that to meet commonly accepted universal health care accessibility targets, sub-Saharan African countries will need to build ∼6,200 new facilities by 2030. We also estimate that about 2.5 million new hospital beds need to be allocated between new facilities and ∼1,100 existing structures that require expansion or densification. Optimized location, type, and capacity of each facility can be explored in an interactive dashboard. Our methodology and the results of our analysis can inform local policy makers in their assessment and prioritization of health care infrastructure. This is particularly relevant to tackle health care accessibility inequality, which is not only prominent within and between countries of sub-Saharan Africa but also, relative to the level of service provided by health care facilities.
Journal Article
Image-Based Crack Detection Methods: A Review
Annually, millions of dollars are spent to carry out defect detection in key infrastructure including roads, bridges, and buildings. The aftermath of natural disasters like floods and earthquakes leads to severe damage to the urban infrastructure. Maintenance operations that follow for the damaged infrastructure often involve a visual inspection and assessment of their state to ensure their functional and physical integrity. Such damage may appear in the form of minor or major cracks, which gradually spread, leading to ultimate collapse or destruction of the structure. Crack detection is a very laborious task if performed via manual visual inspection. Many infrastructure elements need to be checked regularly and it is therefore not feasible as it will require significant human resources. This may also result in cases where cracks go undetected. A need, therefore, exists for performing automatic defect detection in infrastructure to ensure its effectiveness and reliability. Using image processing techniques, the captured or scanned images of the infrastructure parts can be analyzed to identify any possible defects. Apart from image processing, machine learning methods are being increasingly applied to ensure better performance outcomes and robustness in crack detection. This paper provides a review of image-based crack detection techniques which implement image processing and/or machine learning. A total of 30 research articles have been collected for the review which is published in top tier journals and conferences in the past decade. A comprehensive analysis and comparison of these methods are performed to highlight the most promising automated approaches for crack detection.
Journal Article
Smart Buildings: Systems and Drivers
Since the 1980s, smart buildings have aroused the interest of researchers. However, there is still no consensus on what the intelligence of a building is, and what enhances that intelligence. The purpose of this paper is to identify and correlate the main drivers and systems of smart buildings, by associating them with the main beneficiaries: users, owners, and the environment. To identify the main drivers and systems of these buildings, we carried out a comprehensive, detailed, and interpretative literature search. From the selected articles, we sorted the information, extracted the main concepts and knowledge, and, finally, identified the set of potential drivers and systems. Results showed eleven drivers and eight systems, and these can be enhanced by more than one driver. By analyzing the main beneficiaries, we grouped the drivers into three categories: users, owners, and the environment. Given the lack of consensus on the key drivers that make buildings smarter, this article contributes to filling this gap by identifying them, together with the key systems. It is also relevant for detecting the relationships between drivers and systems, and pointing out which drivers have the greatest potential to affect a particular system, keeping in mind the main beneficiary.
Journal Article
Thin films based on electrochromic materials for energy storage performance and smart windows applications: a review
This review covers electrochromic (EC) cells that use different ion electrolytes. In addition to EC phenomena in inorganic materials, these devices can be used as energy storage systems. Lithium-ion (Li
+
) electrolytes are widely recognized as the predominant type utilized in EC and energy storage devices. These electrolytes can exist in a variety of forms, including solid layers, such as Li:Ta
2
O
5
or LiAlO
x
/Ta
2
O
5
/LiAlO
x
. These cells have a significantly longer cycling life, ranging from 5000 to 10,000 cycles. Additionally, the coloration efficiency of the electrochromic device (ECD) containing the ITO glass/WO
3
/Li
+
-polyvinyl butyral-based gel electrolyte was 175.34 cm
2
/C. ECDs utilizing Na
+
or K
+
ions commonly integrate a Prussian blue compound owing to its open-framework structure. The utilization of Zn
2+
ion electrolytes as energy storage systems has been observed, demonstrating compatibility with aqueous electrolytes and showcasing a notable capacity of 820 mAh/g. EC cells and batteries can use aluminum-ion (Al
3+
) electrolytes. The cathode is indium hexacyanoferrate, and the anode is amorphous WO
3
, giving a power density of 2433.8 mW/m
2
. The morphology and structure of the EC layer are critical to improving the EC performance of protons (H
+
) as an electrolytic ion. In an effort to enhance the performance and stability of energy storage systems and ECDs, multi-ion electrolytes have emerged as a recent trend. These electrolytes consist of Zn
2+
and Al
3+
ions, Li
+
and Al
3+
ions, and electrolytes based on Zn
2+
and K
+
ions. By regulating the switching time, these devices are capable of attaining a remarkable optical modulation of 75%.
Journal Article
BIM adoption model for small and medium construction organisations in Australia
Purpose
The purpose of this paper is to present a model for building information modelling (BIM) implementation at small and medium-sized construction contractor organisations (SMOs). The proposed BIM adoption model assesses BIM implementation benefits, costs and challenges faced by SMOs. Correlation between BIM adoption in SMOs and the associated impacting factors, including knowledge support and BIM adoption motivation, is captured through the model.
Design/methodology/approach
A literature review of BIM adoption in construction was first presented. Research data, collected from 80 SMOs in Australia through a conducted survey, are then analysed. Descriptive analysis and structural equation modelling were used to investigate SMOs’ understanding of BIM, and to qualify the correlations among the proposed latent variables impacting BIM implementation at SMOs, respectively. Additionally, this study used χ2 test to compare differences between BIM users and non-BIM users regarding BIM understanding, interested applications and attitudes towards implementation benefits and challenges.
Findings
Potential benefits associated with BIM implementation are a major motivation factor when it comes to BIM adoption at SMOs. In addition, existing staff’s capability in using BIM tools positively affects the establishment of an organisational knowledge-support system, which determines the decision of adopting BIM eventually. Ultimately, there is a need for further emphasis on staff engagement in the implementation process.
Research limitations/implications
The results presented in this paper are applicable to SMOs in the building sector of construction. BIM implementation at organisations involved in non-building activities, including civil works and infrastructure, needs to be assessed in the future.
Practical implications
The results indicate that rather than placing the focus mainly on benefits of BIM implementation, successful implementation of BIM in practice requires adequate effort to assess implementation problems, establish knowledge support and engage staff in using BIM.
Originality/value
Results of this study provide an insight into the adoption challenges of BIM in SMOs, given that the focus of previous studies has been mostly placed on BIM adoption in architectural firms and large contractors.
Journal Article
Proposal for new diagnostic criteria for low skeletal muscle mass based on computed tomography imaging in Asian adults
Low skeletal muscle, referred to as sarcopenia, has been shown to be an independent predictor of lower overall survival in various kinds of diseases. Several studies have evaluated the low skeletal muscle mass using computed tomography (CT) imaging. However, the cutoff values based on CT imaging remain undetermined in Asian populations.
Preoperative plain CT imaging at the third lumbar vertebrae level was used to measure the psoas muscle mass index (PMI, cm2/m2) in 541 adult donors for living donor liver transplantation (LDLT). We analyzed PMI distribution according to sex or donor age, and determined the sex-specific cutoff values of PMI to define low skeletal muscle mass.
PMI in men was significantly higher than observed in women (8.85 ± 1.61 cm2/m2 versus 5.77 ± 1.21 cm2/m2; P < 0.001). PMI was significantly lower in individuals ≥50 y than in younger donors in both men and women (P < 0.001 and P < 0.001, respectively). On the basis of the younger donor data, we determined the sex-specific cutoff values for the low skeletal muscle mass were 6.36 cm2/m2 for men and 3.92 cm2/m2 for women (mean − 2 SD).
Data from healthy young Asian adults were used to establish new criteria for low skeletal muscle mass that would be applicable for defining sarcopenia in Asian populations.
•Low muscle mass is an independent predictor of poor survival in various diseases.•We investigated the psoas muscle mass index (PMI) using computed tomography imaging in 541 healthy adults in Japan.•PMI was significantly lower in women and in individuals ≥50 y.•We established the sex-specific cutoff values of PMI to define low muscle mass.•This new criterion would be applicable for defining sarcopenia in Asia.
Journal Article
Optical and spectroscopic properties of the novel BaO–Al2O3–P2O5: Sm2O3 glass system for orange-red light emission
The conventional melt-annealing technique was used to prepare barium aluminum phosphate glass containing samarium ions. The phosphate structural units vibrate as P–O in Q
2
and Q
3
modes. The glass density of the base glass was 3.366 g/cm
3
, which increased to 3.456 g/cm
3
at the 1.5% Sm
2
O
3
content. The Sm
3+
ions cause distinct and intense peaks to appear in the absorption spectra. The optical transition in these glasses decreased from 4.088 eV (the base) to 3.962 eV (1.5% Sm
2
O
3
). The Judd–Ofelt theory was used to analyze the absorption spectra, and the intensity parameters follow the order
Ω
4
>
Ω
6
>
Ω
2
for the high samarium content. The intensity of the emission decreased due to the concentration quenching of samarium ions. The high and intense emission transition of
4
G
5/2
→
6
H
7/2
led to the emission of an orange-red color. The glass sample containing 1.0% Sm
2
O
3
has the highest color purity at 81.97%.
Journal Article
Dynamic control of hybrid grafted perfect vector vortex beams
Perfect vector vortex beams (PVVBs) have attracted considerable interest due to their peculiar optical features. PVVBs are typically generated through the superposition of perfect vortex beams, which suffer from the limited number of topological charges (TCs). Furthermore, dynamic control of PVVBs is desirable and has not been reported. We propose and experimentally demonstrate hybrid grafted perfect vector vortex beams (GPVVBs) and their dynamic control. Hybrid GPVVBs are generated through the superposition of grafted perfect vortex beams with a multifunctional metasurface. The generated hybrid GPVVBs possess spatially variant rates of polarization change due to the involvement of more TCs. Each hybrid GPVVB includes different GPVVBs in the same beam, adding more design flexibility. Moreover, these beams are dynamically controlled with a rotating half waveplate. The generated dynamic GPVVBs may find applications in the fields where dynamic control is in high demand, including optical encryption, dense data communication, and multiple particle manipulation.
A metasurface is used to generate a hybrid grafted perfect vector vortex beam, which can be dynamically controlled with a half waveplate. The beam has spatially variant rates of polarization change due to the involvement of more topological charges.
Journal Article