193 research outputs found
Integrating Circular Economy and Constructability Research: An Initial Development of a Lifecycle "Circularity" Assessment Framework and Indicators
Exploring Dynamics in Construction Circular Supply Chains Using a Systematic Literature Review: New Supply-push and Demand-pull Perspectives
A framework of indicators to measure project circularity in construction circular economy.
The construction circular economy (CE) literature lacks a holistic framework for systematic assessment of project 'circularity', thereby impeding industry restructuring and full transition to CE. The proposed 'project life-cycle assessment circularity indicators and themes' (PLACIT) framework supports thematic circularity ratings in construction projects using 12 circularity indicators (CIs), representing high-level requirements of CE, grouped into five themes relevant to project life-cycle stages. This helps identify areas of good practice and those requiring circularity improvements. A systematic literature review, structured in line with PLACIT, revealed an increasing association between CE and 'constructability' but varying engagement with CIs. The predominant engagement with indicators within the industry's comfort zone indicates supply-push practices focusing on aspirational CE design solutions and CE management, missing opportunities from engaging with more demand-pull indicators – for example, reduced material inputs – and embedding circular materials in design practices. Full transition to CE will require engaging with a wide range of indicators throughout the whole project life cycle in a more complex network. Moreover, PLACIT has potentials to set clear boundaries between 'sustainability' and CE concepts, currently ill defined in the literature. Future research (Association for Project Management supported) will seek to validate PLACIT using expert feedback and use circularity ratings to support decision making in construction
CIRCULAR ECONOMY IN CONSTRUCTION: A SYSTEMATIC LITERATURE REVIEW OF THE APPLICATION OF MATERIAL PASSPORTS
Vegetation coverage classification using texture analysis on high resolution satellite images
Cet article présente une application de la télédétection pour la gestion des espaces forestiers des îles des
Caraïbes. La problématique générale est la protection des forêts par le suivi de leurs frontières avec les zones
agricoles. Cette problématique est particulièrement sensible du fait du caractère insulaire des forêts et
difficile du fait d’une occupation hétérogène du territoire. En effet, les parcelles agricoles sont de taille et
forme très variées, réparties sur tout le territoire et souvent mélées à la végétation. Le suivi des frontières
nécessite de reconnaître et localiser les diérents couverts végétaux. Après une recherche de l’espace couleur
hybride adapté à l’image et une fusion des différentes bandes acquises par un satellite (afin de combiner
haute résolution spatiale et spectrale), une caractérisation des différents couverts est obtenue en calculant
des descripteurs de couleur et de texture. Différentes méthodes d’extraction (matrices de co-occurrences,
moment de Hu, filtre de Laws, filtre de Gabor…) sont utilisées pour calculer ces descripteurs.
Une classification est ensuite appliquée pour segmenter l’image. Pour la validation de l’approche, l’absence de
vérité terrain a contraint les experts à réaliser une évaluation visuelle
Robust and Reliable Security Approach for IoMT: Detection of DoS and Delay Attacks through a High-Accuracy Machine Learning Model
Internet of Medical Things (IoMT ) refers to the network of medical devices and healthcare systems that are connected to the internet. However, this connectivity also makes IoMT vulnerable to cyberattacks such as DoS and Delay attacks , posing risks to patient safety, data security, and public trust. Early detection of these attacks is crucial to prevent harm to patients and system malfunctions. In this paper, we address the detection and mitigation of DoS and Delay attacks in the IoMT using machine learning techniques. To achieve this objective, we constructed an IoMT network scenario using Omnet++ and recorded network traffic data. Subsequently, we utilized this data to train a set of common machine learning algorithms. Additionally, we proposed an Enhanced Random Forest Classifier for Achieving the Best Execution Time (ERF-ABE), which aims to achieve high accuracy and sensitivity as well as low execution time for detecting these types of attacks in IoMT networks. This classifier combines the strengths of random forests with optimization techniques to enhance performance. Based on the results, the execution time has been reduced by implementing ERF-ABE, while maintaining high levels of accuracy and sensitivity
Antioxidant activity, Total Phenolic and Flavonoid Contents and Cytotoxic activity of Euphorbia aegyptiaca
Euphorbia aegyptiaca is a herbaceous plant traditionally used in Sudan for treatment of various diseases, and the study of this plant is still limited. The aim of the present study was to screen the phytochemicals and to assess the Antioxidant activity, total phenolic, flavonoid contents and cytotoxic activity of Euphorbia aegyptiaca. The plant material was extracted successively by Soxhlet apparatus using n-hexane, chloroform and methanol. The chemical constituents of the extracts were carried out using the standard procedures. The Folin- Ciocalteu and Aluminium chloride method was employed to calculate the total phenolic and flavonoid content, respectively. The antioxidant activity, was assessed by measuring the scavenging activity of the DPPH (2.2Di (4-tert-octylphenyl)-1-picryl-hydrazyl) and Propyl Gallate as standard antioxidants. While cytotoxic activities were screened using brine shrimp. Phytochemical screening studies revealed that flavonoids, tannins, coumarins, saponins, sterols, terpenes, anthraquinones and alkaloids were the main phytochemicals present in extracts of E. aegyptiaca. The methanol extract showed the highest level of total phenolic contents (173.49±2.427 mg GAE/g) and flavonoid content (239.53±7.90 mg QE/g), and the highest antioxidant activity 89% with least (IC50 0.0449µg/ml), and the no toxicity against brine shrimp (LD50 3423.156). Furthermore, no toxicity in all extracts was observed. The present study is the first evaluation regarding the characterization of E. aegyptiaca and its safety, and the results demonstrate its antioxidant potential and suggest its safe therapeutic use. The results suggest that methanol extract is a rich source of phytochemicals and exhibits highest amount of and total phenolic, flavonoid content and significant antioxidant activity and it has no cytotoxic activity. E. aegyptiaca plant can be regarded as a promising Source of naturally occurring potential antioxidants.
Keywords: Euphorbia aegyptiaca, Sudan, Antioxidant, Total phenolic, total flavonoid, Cytotoxicity
Fractal time series analysis of postural stability in elderly and control subjects
<p>Abstract</p> <p>Background</p> <p>The study of balance using stabilogram analysis is of particular interest in the study of falls. Although simple statistical parameters derived from the stabilogram have been shown to predict risk of falls, such measures offer little insight into the underlying control mechanisms responsible for degradation in balance. In contrast, fractal and non-linear time-series analysis of stabilograms, such as estimations of the Hurst exponent (H), may provide information related to the underlying motor control strategies governing postural stability. In order to be adapted for a home-based follow-up of balance, such methods need to be robust, regardless of the experimental protocol, while producing time-series that are as short as possible. The present study compares two methods of calculating H: Detrended Fluctuation Analysis (DFA) and Stabilogram Diffusion Analysis (SDA) for elderly and control subjects, as well as evaluating the effect of recording duration.</p> <p>Methods</p> <p>Centre of pressure signals were obtained from 90 young adult subjects and 10 elderly subjects. Data were sampled at 100 Hz for 30 s, including stepping onto and off the force plate. Estimations of H were made using sliding windows of 10, 5, and 2.5 s durations, with windows slid forward in 1-s increments. Multivariate analysis of variance was used to test for the effect of time, age and estimation method on the Hurst exponent, while the intra-class correlation coefficient (ICC) was used as a measure of reliability.</p> <p>Results</p> <p>Both SDA and DFA methods were able to identify differences in postural stability between control and elderly subjects for time series as short as 5 s, with ICC values as high as 0.75 for DFA.</p> <p>Conclusion</p> <p>Both methods would be well-suited to non-invasive longitudinal assessment of balance. In addition, reliable estimations of H were obtained from time series as short as 5 s.</p
Using a Convolutional Neural Network to Predict Readers' Estimates of Mammographic Density for Breast Cancer Risk Assessment
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