All Outputs (413)

Assessment of costs and benefits of green retrofit technologies: Case study of hotel buildings in Sri Lanka (2023)
Journal Article
Periyannan, E., Ramachandra, T., & Geekiyanage, D. (2023). Assessment of costs and benefits of green retrofit technologies: Case study of hotel buildings in Sri Lanka. Journal of Building Engineering, 78, 107631. https://doi.org/10.1016/j.jobe.2023.107631

With the rising impact of greenhouse gas emissions, resource depletion, and the global interest in sustainability advancements within all sectors, construction industry practitioners are also interested in incorporating sustainable features and pract... Read More about Assessment of costs and benefits of green retrofit technologies: Case study of hotel buildings in Sri Lanka.

Spectral–Spatial Features Exploitation Using Lightweight HResNeXt Model for Hyperspectral Image Classification (2023)
Journal Article
Prasad Yadav, D., Kumar, D., Singh Jalal, A., Kumar, A., Bhatia Khan, S., Gadekallu, T. R., …Malibari, A. A. (2023). Spectral–Spatial Features Exploitation Using Lightweight HResNeXt Model for Hyperspectral Image Classification. Canadian Journal of Remote Sensing, 49(1), https://doi.org/10.1080/07038992.2023.2248270

Hyperspectral image classification is vital for various remote sensing applications; however, it remains challenging due to the complex and high-dimensional nature of hyperspectral data. This paper introduces a novel approach to address this challeng... Read More about Spectral–Spatial Features Exploitation Using Lightweight HResNeXt Model for Hyperspectral Image Classification.

Modified Nonlinear Hysteresis Approach for a Tactile Sensor (2023)
Journal Article
Abdul-Hussain, G., Holderbaum, W., Theodoridis, T., & Wei, G. (in press). Modified Nonlinear Hysteresis Approach for a Tactile Sensor. Sensors, 23(16), 7293. https://doi.org/10.3390/s23167293

Soft tactile sensors based on piezoresistive materials have large-area sensing applications. However, their accuracy is often affected by hysteresis which poses a significant challenge during operation. This paper introduces a novel approach that emp... Read More about Modified Nonlinear Hysteresis Approach for a Tactile Sensor.

Harnessing the Potential of Biosurfactants for Biomedical and Pharmaceutical Applications (2023)
Journal Article
Ceresa, C., Fracchia, L., Sansotera, A. C., De Rienzo, M. A. D., & Banat, I. M. (in press). Harnessing the Potential of Biosurfactants for Biomedical and Pharmaceutical Applications. Pharmaceutics, 15(8), 2156. https://doi.org/10.3390/pharmaceutics15082156

Biosurfactants (BSs) are microbial compounds that have emerged as potential alternatives to chemical surfactants due to their multifunctional properties, sustainability and biodegradability. Owing to their amphipathic nature and distinctive structura... Read More about Harnessing the Potential of Biosurfactants for Biomedical and Pharmaceutical Applications.

Urban vegetable contamination - The role of adhering particles and their significance for human exposure. (2023)
Journal Article
Augustsson, A., Lundgren, M., Qvarforth, A., Engström, E., Paulukat, C., Rodushkin, I., …Hough, R. L. (2023). Urban vegetable contamination - The role of adhering particles and their significance for human exposure. #Journal not on list, 900, 165633. https://doi.org/10.1016/j.scitotenv.2023.165633

While urban-grown vegetables could help combat future food insecurity, the elevated levels of toxic metals in urban soils need to be met with measures that minimise transfer to crops. The study firstly examines soil/dust particle inclusion in leafy v... Read More about Urban vegetable contamination - The role of adhering particles and their significance for human exposure..

Detection of Alzheimer’s Disease Based on Cloud-Based Deep Learning Paradigm (2023)
Journal Article
Pruthviraja, D., Nagaraju, S. C., Mudligiriyappa, N., Raisinghani, M. S., Khan, S. B., Alkhaldi, N. A., & Malibari, A. A. (in press). Detection of Alzheimer’s Disease Based on Cloud-Based Deep Learning Paradigm. Diagnostics, 13(16), 2687. https://doi.org/10.3390/diagnostics13162687

Deep learning is playing a major role in identifying complicated structure, and it outperforms in term of training and classification tasks in comparison to traditional algorithms. In this work, a local cloud-based solution is developed for classific... Read More about Detection of Alzheimer’s Disease Based on Cloud-Based Deep Learning Paradigm.

Rate and temperature dependent viscoelastic cohesive zone model for mode-idelamination of composites (2023)
Conference Proceeding
Ammasai Sengodan, G. (2023). Rate and temperature dependent viscoelastic cohesive zone model for mode-idelamination of composites.

Introduction Initiation and propagation of delamination at room temperature and constant loading rates are modelled accurately by using bi-linear or exponential cohesive zone models (CZM) [1]. These "standard" traction-separation based models do not... Read More about Rate and temperature dependent viscoelastic cohesive zone model for mode-idelamination of composites.

A novel CNN gap layer for growth prediction of palm tree plantlings (2023)
Journal Article
Kumar, T. A., Rajmohan, R., Adeola Ajagbe, S., Gaber, T., Zeng, X., & Masmoudi, F. (in press). A novel CNN gap layer for growth prediction of palm tree plantlings. PloS one, 18(8), e0289963. https://doi.org/10.1371/journal.pone.0289963

Monitoring palm tree seedlings and plantlings presents a formidable challenge because of the microscopic size of these organisms and the absence of distinguishing morphological characteristics. There is a demand for technical approaches that can prov... Read More about A novel CNN gap layer for growth prediction of palm tree plantlings.

Acoustic and Psychoacoustic Characterisation of Small-Scale Contra-Rotating Propellers (2023)
Journal Article
Casagrande Hirono, F., Robertson, J., & Torija Martinez, A. J. (2023). Acoustic and Psychoacoustic Characterisation of Small-Scale Contra-Rotating Propellers. Journal of Sound and Vibration, 569, https://doi.org/10.1016/j.jsv.2023.117971

This paper reports an experimental investigation of noise radiation and psychoacoustic evaluation of contra-rotating propellers with different blade counts over multiple emission angles and thrust settings. A series of aeroacoustic and psychoacoustic... Read More about Acoustic and Psychoacoustic Characterisation of Small-Scale Contra-Rotating Propellers.

Highly sensitive multifunction protection coordination scheme for improved reliability of power systems with distributed generation (PVs) (2023)
Journal Article
Alasali, F., El‐Naily, N., Saidi, A. S., Itradat, A., Holderbaum, W., & Mohamed, F. A. (in press). Highly sensitive multifunction protection coordination scheme for improved reliability of power systems with distributed generation (PVs). IET Renewable Power Generation, https://doi.org/10.1049/rpg2.12820

The high penetration of distribution generators (DGs), such as photovoltaic (PV), has made optimal overcurrent coordination a major concern for power protection. In the literature, the conventional single or multi‐objective function (OF) for phase ov... Read More about Highly sensitive multifunction protection coordination scheme for improved reliability of power systems with distributed generation (PVs).

An Approach to Binary Classification of Alzheimer’s Disease Using LSTM (2023)
Journal Article
Salehi, W., Baglat, P., Gupta, G., Khan, S. B., Almusharraf, A., Alqahtani, A., & Kumar, A. (in press). An Approach to Binary Classification of Alzheimer’s Disease Using LSTM. Bioengineering, 10(8), 950. https://doi.org/10.3390/bioengineering10080950

In this study, we use LSTM (Long-Short-Term-Memory) networks to evaluate Magnetic Resonance Imaging (MRI) data to overcome the shortcomings of conventional Alzheimer’s disease (AD) detection techniques. Our method offers greater reliability and accur... Read More about An Approach to Binary Classification of Alzheimer’s Disease Using LSTM.

Seasonal development of a tidal mixing front drives shifts in community structure and diversity of bacterioplankton (2023)
Journal Article
King, N. G., Wilmes, S., Browett, S. S., Healey, A., McDevitt, A. D., McKeown, N. J., …Malham, S. (in press). Seasonal development of a tidal mixing front drives shifts in community structure and diversity of bacterioplankton. Molecular Ecology, https://doi.org/10.1111/mec.17097

Bacterioplankton underpin biogeochemical cycles and an improved understanding of the patterns and drivers of variability in their distribution is needed to determine their wider functioning and importance. Sharp environmental gradients and dispersal... Read More about Seasonal development of a tidal mixing front drives shifts in community structure and diversity of bacterioplankton.

HemiPy: A Python module for automated estimation of forest biophysical variables and uncertainties from digital hemispherical photographs (2023)
Journal Article
Brown, L. A., Morris, H., Leblanc, S., Bai, G., Lanconelli, C., Gobron, N., …Dash, J. (in press). HemiPy: A Python module for automated estimation of forest biophysical variables and uncertainties from digital hemispherical photographs. Methods in Ecology and Evolution, https://doi.org/10.1111/2041-210x.14199

Digital hemispherical photography (DHP) is widely used to derive forest biophysical variables including leaf, plant, and green area index (LAI, PAI and GAI), the fraction of intercepted photosynthetically active radiation (FIPAR), and the fraction of... Read More about HemiPy: A Python module for automated estimation of forest biophysical variables and uncertainties from digital hemispherical photographs.

Climate determines transmission hotspots of Polycystic Echinococcosis, a life-threatening zoonotic disease, across Pan-Amazonia (2023)
Journal Article
San-José, A., Mayor, P., Carvalho, B., El Bizri, H. R., Antunes, A. P., Antunez Correa, M., …Munari, D. P. (2023). Climate determines transmission hotspots of Polycystic Echinococcosis, a life-threatening zoonotic disease, across Pan-Amazonia. Proceedings of the National Academy of Sciences of the United States of America, 120(33), e2302661120. https://doi.org/10.1073/pnas.2302661120

Polycystic Echinococcosis (PE), a neglected life-threatening zoonotic disease caused by the cestode is endemic in the Amazon. Despite being treatable, PE reaches a case fatality rate of around 29% due to late or missed diagnosis. PE is sustained in... Read More about Climate determines transmission hotspots of Polycystic Echinococcosis, a life-threatening zoonotic disease, across Pan-Amazonia.

Functional screening reveals Toxoplasma prenylated proteins required for endocytic trafficking and rhoptry protein sorting (2023)
Journal Article
Wang, Q., Sun, M., Tang, T., Lai, D., Liu, J., Maity, S., …Long, S. (2023). Functional screening reveals Toxoplasma prenylated proteins required for endocytic trafficking and rhoptry protein sorting. mBio, https://doi.org/10.1128/mbio.01309-23

In the apicomplexans, endocytosed cargos (e.g., hemoglobin) are trafficked to a specialized organelle for digestion. This follows a unique endocytotic process at the micropore/cytostome in these parasites. However, the mechanism underlying endocytic... Read More about Functional screening reveals Toxoplasma prenylated proteins required for endocytic trafficking and rhoptry protein sorting.

Remotely sensed localised primary production anomalies predict the burden and community structure of infection in long‐term rodent datasets (2023)
Journal Article
Jackson, J. A., Bajer, A., Behnke-Borowczyk, J., Gilbert, F., Grzybek, M., Alsarraf, M., & Behnke, J. (in press). Remotely sensed localised primary production anomalies predict the burden and community structure of infection in long‐term rodent datasets. Global Change Biology, https://doi.org/10.1111/gcb.16898

The increasing frequency and cost of zoonotic disease emergence due to global change have led to calls for the primary surveillance of wildlife. This should be facilitated by the ready availability of remotely sensed environmental data, given the imp... Read More about Remotely sensed localised primary production anomalies predict the burden and community structure of infection in long‐term rodent datasets.

Inoculation with Glomus mosseae: An Efficient Biological Management Strategy for Arsenic Mitigation in Wheat (Triticum Aestivum L.) Under Arsenic-Contaminated Soil (2023)
Journal Article
Singh, M., chakraborty, D., Mandal, J., Kumar Chaudhary, D., & Kumar Jha, A. (2023). Inoculation with Glomus mosseae: An Efficient Biological Management Strategy for Arsenic Mitigation in Wheat (Triticum Aestivum L.) Under Arsenic-Contaminated Soil. Communications in Soil Science and Plant Analysis, 54(19), 2645-2656. https://doi.org/10.1080/00103624.2023.2240367

A pot experiment was conducted to evaluate the effects of Arbuscular Mycorrhizal (AM) fungi on mitigation of arsenic (As) in As-contaminated soils with wheat (variety – HD 2967) as the test crop. Soil inbulk was collected from Bihar Agricultural Univ... Read More about Inoculation with Glomus mosseae: An Efficient Biological Management Strategy for Arsenic Mitigation in Wheat (Triticum Aestivum L.) Under Arsenic-Contaminated Soil.

On-field noise measurements and acoustic characterisation of multi-rotor small unmanned aerial systems (2023)
Journal Article
Ramos-Romero, C., Green, N., Torija, A. J., & Asensio, C. (2023). On-field noise measurements and acoustic characterisation of multi-rotor small unmanned aerial systems. Aerospace science and technology, 141, 108537. https://doi.org/10.1016/j.ast.2023.108537

The noise signature of small Unmanned Aerial Systems (sUAS) is highly influenced by specific operating and weather conditions. Accurate noise assessment of sUAS operations requires field noise measurements that capture all the compl... Read More about On-field noise measurements and acoustic characterisation of multi-rotor small unmanned aerial systems.

An evolutionary-based polynomial regression modeling approach to predicting discharge flow rate under sheet piles (2023)
Journal Article
Asr, A. A., Johari, A., & Javadi, A. A. (2023). An evolutionary-based polynomial regression modeling approach to predicting discharge flow rate under sheet piles. Engineering with Computers, 39(6), 4093-4101. https://doi.org/10.1007/s00366-023-01872-1

The discharge flow rate beneath sheet plies is an essential parameter in designing these water retaining structures. This paper presents a unified framework for modeling and predicting discharge flow rate using an evolutionary-based polynomial regres... Read More about An evolutionary-based polynomial regression modeling approach to predicting discharge flow rate under sheet piles.

An improved long short term memory network for intrusion detection (2023)
Journal Article
Awad, A. A., Ali, A. F., & Gaber, T. (in press). An improved long short term memory network for intrusion detection. PloS one, 18(8), e0284795. https://doi.org/10.1371/journal.pone.0284795

Over the years, intrusion detection system has played a crucial role in network security by discovering attacks from network traffics and generating an alarm signal to be sent to the security team. Machine learning methods, e.g., Support Vector Machi... Read More about An improved long short term memory network for intrusion detection.