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An Investigation Of The Effect Of Cyclic Loading Of Bone On Osteocyte Processes Spanning Micro-Cracks As A Driver Of Targeted Remodelling Of Bone, Morgana Pires Afonso Shirsath Jan 2023

An Investigation Of The Effect Of Cyclic Loading Of Bone On Osteocyte Processes Spanning Micro-Cracks As A Driver Of Targeted Remodelling Of Bone, Morgana Pires Afonso Shirsath

Doctoral

Bone remodelling is essential to maintain and improve the quality of bones. This occurs with the action of specialised cells - osteoclasts and osteoblasts - which replace the old bone tissue with new in regions where damage has occurred. Osteocytes are responsible for signalling the presence of damage and trigger the bone remodelling response. According to the Scissors Model, the presence of micro-cracks causes rupture of the osteocyte processes by fatigue because of the repeated stretching resulting from the relative movement of micro-crack faces, when bone is subjected to cyclic loads.

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Platinum Nanoparticles Inhibit Intracellular Ros Generation And Protect Against Cold Atmospheric Plasma-Induced Cytotoxicity, Sebnem Gunes, Zhonglei He, David Van Acken, Renee Malone, Patrick Cullen, James Curtin Jan 2023

Platinum Nanoparticles Inhibit Intracellular Ros Generation And Protect Against Cold Atmospheric Plasma-Induced Cytotoxicity, Sebnem Gunes, Zhonglei He, David Van Acken, Renee Malone, Patrick Cullen, James Curtin

Articles

Platinum nanoparticles (PtNPs) have been investigated for their antioxidant abilities in a range of biological and other applications. The ability to reduce off-target cold atmospheric plasma (CAP) cytotoxicity would be useful in Plasma Medicine; however, little has been published to date about the ability of PtNPs to reduce or inhibit the effects of CAP. Here we investigate whether PtNPs can protect against CAP-induced cytotoxicity in cancerous and non-cancerous cell lines. PtNPs were shown to dramatically reduce intracellular reactive species (RONS) production in U-251 MG cells. However, RONS generation was unaffected by PtNPs in medium without cells. PtNPs protect …

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Workplace Accident Analysis In The Algerian Oil And Gas Industry, Hamza Zerrouki Jan 2023

Workplace Accident Analysis In The Algerian Oil And Gas Industry, Hamza Zerrouki

Articles

A total of 42,032 workplace accidents were reported in 2021 by the Algerian National Social Insurance Fund for Salaried Workers in Algeria, of which 38,225 were accidents within the workplace and 3807 were related to traffic accidents or other reasons. Most of these accidents were recorded in the building and construction field, followed by the oil and gas company exploration and drilling, which comes at the forefront of the Sonatrach company. This study aims to analyze accidents in the workplace using quantitative and qualitative methods to determine the corresponding causes. Our study was carried out in collaboration with Sonatrach in …

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Optimizing Human Performance To Enhance Safety: A Case Study In An Automotive Plant, Maria Chiara Leva, Michaela Demichela, Carlos Albarran Morillo, Franco Modaffari, Lorenzo Comberti Jan 2023

Optimizing Human Performance To Enhance Safety: A Case Study In An Automotive Plant, Maria Chiara Leva, Michaela Demichela, Carlos Albarran Morillo, Franco Modaffari, Lorenzo Comberti

Articles

Human factors play a relevant role in the dynamic work environments of the manufacturing sector in terms of production efficiency, safety, and sustainable performance. This is particularly relevant in assembly lines where humans are widely employed alongside automated and robotic agents. In this situation, operators’ ability to adapt to different levels of task complexity and variability in each workstation has a strong impact on the safety, reliability, and efficiency of the overall production process. This paper presents an application of a theoretical and empirical method used to assess the matching of different workers to various workstations based on a quantified …

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Recovery Of Protein From Industrial Hemp Waste (Cannabis Sativa, L.) Using High-Pressure Processing And Ultrasound Technologies, Eduarda M. Cabral Jan 2023

Recovery Of Protein From Industrial Hemp Waste (Cannabis Sativa, L.) Using High-Pressure Processing And Ultrasound Technologies, Eduarda M. Cabral

Articles

Hemp seeds are currently used mainly for oil extraction, generating waste that could be potentially exploited further as a source of proteins and other bio-actives. This study aims to valorise hemp waste (Cannabis sativa, L.) from previous oil extraction as a source of protein by analysing the effect of high-pressure processing (HPP) pre-treatments (0–600 MP a; 4–8 min) combined with conventional or ultrasound-assisted extraction (UAE) methods on protein recovery/purity, amino acid composition, and protein structure. Overall, maximum protein recovery (62%) was achieved with HPP (200 MP a, 8 min) with UAE. The highest protein purity (76%) was achieved with HPP …

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Enhancing Control Room Operator Decision Making: An Application Of Dynamic Influence Diagrams In Formaldehyde Manufacturing, Joseph Mietkiewicz, Anders L. Madsen Jan 2023

Enhancing Control Room Operator Decision Making: An Application Of Dynamic Influence Diagrams In Formaldehyde Manufacturing, Joseph Mietkiewicz, Anders L. Madsen

Articles

Intoday’s rapidly evolving industrial landscape, control room operators must grapple with an ever-growing array of tasks and respon sibilities. One major challenge facing these operators is the potential for task overload, which can lead to decision fatigue and increased reliance on cognitive biases. To address this issue, we propose the use of dynamic influence diagrams (DID) as the core of our decision support system. By monitoring the process over time and identifying anomalies, DIDs can recommend the most effective course of action based on a probabilistic assessment of future outcomes. Instead of letting the operator choose or search for the …

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Series-Fed Omnidirectional Mm-Wave Dipole Array, Neeraj Kumar Maurya, Max Ammann, Patrick Mcevoy Jan 2023

Series-Fed Omnidirectional Mm-Wave Dipole Array, Neeraj Kumar Maurya, Max Ammann, Patrick Mcevoy

Articles

THE rapid expansion in the millimeter-wave (mm-wave) frequency domain has completely changed the course of wireless communication. One of the most important steps to make smart cities, the Internet-of-Things (IoT), smart homes, and vehicular communication a reality is to use mm-wave frequencies for wireless applications. The rise in the number of wireless appliances has also led to a rise in data traffic [1]. The adoption of mm-wave frequencies enabled several gigahertz of bandwidth, allowing data rate and latency limits to be exceeded. The availability of a broad electromagnetic spectrum and frequency reusability are the most important characteristics of mm-wave deployment …

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Exploiting Multimode Antennas For Mimo And Aoa Estimation In Size-Constrained Iot Devices, Abel Zandamela, Alessandro Chiumento Alessandro Chiumento, Alessandro Chiumento, Nicola Marchetti, Max Ammann, Adam Narbudowicz Jan 2023

Exploiting Multimode Antennas For Mimo And Aoa Estimation In Size-Constrained Iot Devices, Abel Zandamela, Alessandro Chiumento Alessandro Chiumento, Alessandro Chiumento, Nicola Marchetti, Max Ammann, Adam Narbudowicz

Articles

This work proposes compact multimode Multiple-Input–Multiple-Output (MIMO) antennas for Angle of Arrival (AoA) estimation in miniaturized Internet of Things (IoT) systems. The method excites different orthogonal radiating modes (TM 21 , TM 02 , and TM 31 modes) for beamforming capabilities, and the AoA performance is investigated using the Multiple Signal Classification (MUSIC) algorithm, executed using numerical and experimental data. The technique is tested at 2.238GHz , while using an antenna diameter

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Pattern And Polarization Diversity Multisector Annular Antenna For Iot Applications, Abel Zandamela, Nicola Marchetti, Max Ammann, Adam Narbudowicz Jan 2023

Pattern And Polarization Diversity Multisector Annular Antenna For Iot Applications, Abel Zandamela, Nicola Marchetti, Max Ammann, Adam Narbudowicz

Articles

This work proposes a small pattern and polarization diversity multisector annular antenna with electrical size and profile of ka = 1.2 and 0.018λ, respectively. The antenna is planar and comprises annular sectors that are fed using different ports to enable digital beamforming techniques, with efficiency and gain of up to 78% and 4.62 dBi, respectively. The cavity model analysis is used to describe the design concept and the antenna diversity. The proposed method can produce different polarization states (e.g., linearly and circularly polarized patterns) and pattern diversity characteristics covering the elevation plane. Owing to its small electrical size, low-profile and …

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Impact Of Character N-Grams Attention Scores For English And Russian News Articles Authorship Attribution, Liliya Mukhmutova, Robert J. Ross, Giancarlo Salton Jan 2023

Impact Of Character N-Grams Attention Scores For English And Russian News Articles Authorship Attribution, Liliya Mukhmutova, Robert J. Ross, Giancarlo Salton

Conference papers

Language embeddings are often used as black-box word-level tools that provide powerful language analysis across many tasks, but yet for many tasks such as Authorship Attribution access to feature level information on character n-grams can provide insights to help with model refinement and development. In this paper we investigate and evaluate the importance of character n-grams within an embeddings context in authorship attribution through the use of attention scores. We perform this investigation both for English (Reuters_50_50) and Russian (Taiga) news authorship datasets. Our analysis show that character n-grams attention score is higher for n-grams that are considered to be …

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Subnetwork Ensembling And Data Augmentation: Effects On Calibration, A. Çağrı Demir, Simon Caton, Pierpaolo Dondio Jan 2023

Subnetwork Ensembling And Data Augmentation: Effects On Calibration, A. Çağrı Demir, Simon Caton, Pierpaolo Dondio

Articles

Deep Learning models based on convolutional neural networks are known to be uncalibrated, that is, they are either overconfident or underconfident in their predictions. Safety-critical applications of neural networks, however, require models to be well-calibrated, and there are various methods in the literature to increase model performance and calibration. Subnetwork ensembling is based on the over-parametrization of modern neural networks by fitting several subnetworks into a single network to take advantage of ensembling them without additional computational costs. Data augmentation methods have also been shown to enhance model performance in terms of accuracy and calibration. However, ensembling and data augmentation …

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Gated Deep Reinforcement Learning With Red Deer Optimization For Medical Image Classification, Narayanan Ganesh, Sambandan Jayalakshmi, Rama Chandran Narayanan, Miroslav Mahdal, Hossam Zawbaa, Ali Wagdy Mohamed Jan 2023

Gated Deep Reinforcement Learning With Red Deer Optimization For Medical Image Classification, Narayanan Ganesh, Sambandan Jayalakshmi, Rama Chandran Narayanan, Miroslav Mahdal, Hossam Zawbaa, Ali Wagdy Mohamed

Articles

The brain is one of the most important and complex organs in the body, consisting of billions of individual cells. Uncontrolled growth and expansion of aberrant cell populations within or around the brain are the main causes of brain tumors. These cells have the potential to harm healthy cells and impair brain function [1]. Tumors can be detected using medical imaging techniques, which are considered the most popular and accurate way to classify different types of cancer, and this procedure is even more crucial as it is noninvasive [2]. Magnetic resonance imaging (MRI) is one such medical imaging technique that …

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Ontology-Based Case Study Management Towards Bridging Training And Actual Investigation Gaps In Digital Forensics, Hung Q. Ngo, Nhien-An Le-Khac Jan 2023

Ontology-Based Case Study Management Towards Bridging Training And Actual Investigation Gaps In Digital Forensics, Hung Q. Ngo, Nhien-An Le-Khac

Articles

The training programs in digital forensics have contributed many case study models to guide digital forensic analyses. However, they only account for a small number of real cases and they are usually too abstract while actual cybercrime investigations are more diverse and complex. This gap leads to difficulties in giving immediate and straightforward actions for law enforcement during cybercrime investigations. In this paper, we propose an ontology-based knowledge map model, which is a foundation model for building a case study management system for Digital Forensic Intelligence (DFINT) and Open Source Intelligence (OSINT) in digital forensics. The main idea of this …

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Pattern And Polarization Diversity Multisector Annular Antenna For Iot Applications, Abel Zandamela, Nicola Marchetti, Max Ammann, Adam Narbudowicz, Wroclaw University Of Science And Technology Jan 2023

Pattern And Polarization Diversity Multisector Annular Antenna For Iot Applications, Abel Zandamela, Nicola Marchetti, Max Ammann, Adam Narbudowicz, Wroclaw University Of Science And Technology

Articles

This work proposes a small pattern and polarization diversity multisector annular antenna with electrical size and profile of ka=1.2 and 0.018λ, respectively. The antenna is planar and comprises annular sectors that are fed using different ports to enable digital beamforming techniques, with efficiency and gain of up to 78%and 4.62 dBi, respectively. The cavity model analysis is used to describe the design concept and the antenna diversity. The proposed method can produce different polarization states (e.g., linearly and circularly polarized patterns) and pattern diversity characteristics covering the elevation plane. Owing to its small electrical size, low-profile and diversity properties, the …

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Development Of Holographic Recording Material For Fabrication Of Solar Concentrators For Micro Satellites, Brian Rogers Jan 2023

Development Of Holographic Recording Material For Fabrication Of Solar Concentrators For Micro Satellites, Brian Rogers

Doctoral

Holographic solar concentration has been a topic of increasing interest over recent years because of the lightweight and physically compact nature of holograms, which gives them an advantage over other, conventional concentration methods. As holographic recording materials develop further, their characteristics prove to meet the demands required of them to make more effective holographic solar concentrators. The development of photovoltaics in tandem with holographic materials has led to a host of solar concentrating device designs that take advantage of the unique properties of diffractive optics. Compared to refractive optics, holographic devices are more lightweight and compact. This makes holographic devices …

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Towards The Development Of A Balanced Legislative Framework For Consumer Data Protection In Electronic Commerce: The Case Of The Sultanate Of Oman, Talib Al Kharusi Jan 2023

Towards The Development Of A Balanced Legislative Framework For Consumer Data Protection In Electronic Commerce: The Case Of The Sultanate Of Oman, Talib Al Kharusi

Doctoral

This research aims to investigate whether the law as it currently stands in Oman provides adequate legal protection for personal data, to determine the current obstacles facing the electronic commerce sector, and to identify ways of overcoming such challenges. The empirical focus of this study will be electronic commerce transactions between companies and consumers. In this regard, the research will explore the perceptions of the main stakeholders towards privacy regulation and what implications these have for the growth of electronic commerce in Oman. The privacy that this research aims to explore is a complex issue since it concerns human feelings …

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Comparing And Extending The Use Of Defeasible Argumentation With Quantitative Data In Real-World Contexts, Lucas Rizzo, Luca Longo Jan 2023

Comparing And Extending The Use Of Defeasible Argumentation With Quantitative Data In Real-World Contexts, Lucas Rizzo, Luca Longo

Articles

Dealing with uncertain, contradicting, and ambiguous information is still a central issue in Artificial Intelligence (AI). As a result, many formalisms have been proposed or adapted so as to consider non-monotonicity. A non-monotonic formalism is one that allows the retraction of previous conclusions or claims, from premises, in light of new evidence, offering some desirable flexibility when dealing with uncertainty. Among possible options, knowledge-base, non-monotonic reasoning approaches have seen their use being increased in practice. Nonetheless, only a limited number of works and researchers have performed any sort of comparison among them. This research article focuses on evaluating the inferential …

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Exploring The Impact Of Noise And Degradations On Heart Sound Classification Models, Davoud Shariat Panah, Andrew Hines, Susan Mckeever Jan 2023

Exploring The Impact Of Noise And Degradations On Heart Sound Classification Models, Davoud Shariat Panah, Andrew Hines, Susan Mckeever

Articles

The development of data-driven heart sound classification models has been an active area of research in recent years. To develop such data-driven models in the first place, heart sound signals need to be captured using a signal acquisition device. However, it is almost impossible to capture noise-free heart sound signals due to the presence of internal and external noises in most situations. Such noises and degradations in heart sound signals can potentially reduce the accuracy of data-driven classification models. Although different techniques have been proposed in the literature to address the noise issue, how and to what extent different noise …

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Comparing Poor And Favorable Outcome Prediction With Machine Learning After Mechanical Thrombectomy In Acute Ischemic Stroke, Matthias A. Mutke, Vince I. Madai, Adam Hilbert, Esra Zihni, Arne Potreck, Charlotte S. Weyland, Markus A. Mohlenbruch, Sabine Heiland, Peter A. Ringleb, Simon Nagel, Martin Beendszus, Dietmar Frey Jan 2023

Comparing Poor And Favorable Outcome Prediction With Machine Learning After Mechanical Thrombectomy In Acute Ischemic Stroke, Matthias A. Mutke, Vince I. Madai, Adam Hilbert, Esra Zihni, Arne Potreck, Charlotte S. Weyland, Markus A. Mohlenbruch, Sabine Heiland, Peter A. Ringleb, Simon Nagel, Martin Beendszus, Dietmar Frey

Articles

Outcome prediction after mechanical thrombectomy (MT) in patients with acute ischemic stroke (AIS) and large vessel occlusion (LVO) is commonly performed by focusing on favorable outcome (modified Rankin Scale, mRS 0–2) after 3 months but poor outcome representing severe disability and mortality (mRS 5 and 6) might be of equal importance for clinical decision-making.

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Corrigendum: Human Mental Workload: A Survey And A Novel Inclusive Definition, Luca Longo, Christopher D. Wickens, Gabriella Hancock, P. A. Hancock Jan 2023

Corrigendum: Human Mental Workload: A Survey And A Novel Inclusive Definition, Luca Longo, Christopher D. Wickens, Gabriella Hancock, P. A. Hancock

Articles

In the published article, the name of Gabriella Hancock was incorrectly written as “Gabriela M. Hancock.” The correct name is “Gabriella Hancock.” In the published article, there was also an error in the author list as published. Gabriella Hancock was listed as the last author, but should have been listed as third author. P. A. Hancock was listed as third author but should be listed as the last author. The corrected author list appears below. Luca Longo1, Christopher D.Wickens, Gabriella Hancock and P. A. Hancock. The authors apologize for this error and state that this does not change the scientific …

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Towards Automated Weed Detection Through Two-Stage Semantic Segmentation Of Tobacco And Weed Pixels In Aerial Imagery, S. Imran Moazzam, Umar S. Khan, Waqar Qureshi, Tahir Nawaz, Faraz Kunwar Jan 2023

Towards Automated Weed Detection Through Two-Stage Semantic Segmentation Of Tobacco And Weed Pixels In Aerial Imagery, S. Imran Moazzam, Umar S. Khan, Waqar Qureshi, Tahir Nawaz, Faraz Kunwar

Articles

In precision farming, weed detection is required for precise weedicide application, and the detection of tobacco crops is necessary for pesticide application on tobacco leaves. Automated accurate detection of tobacco and weeds through aerial visual cues holds promise. Precise weed detection in crop field imagery can be treated as a semantic segmentation problem. Many image processing, classical machine learning, and deep learning-based approaches have been devised in the past, out of which deep learning-based techniques promise better accuracies for semantic segmentation, i.e., pixel-level classification. We present a new method that improves the precision of pixel-level inter-class classification of the crop …

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Detection Of Grape Clusters In Images Using Convolutional Neural Network, Mohammad Osama Shahzad, Anas Bin Aqeel, Waqar Shahid Qureshi Jan 2023

Detection Of Grape Clusters In Images Using Convolutional Neural Network, Mohammad Osama Shahzad, Anas Bin Aqeel, Waqar Shahid Qureshi

Articles

Convolutional Neural Networks and Deep Learning have revolutionized every field since their inception. Agriculture has also been reaping the fruits of developments in mentioned fields. Technology is being revolutionized to increase yield, save water wastage, take care of diseased weeds, and also increase the profit of farmers. Grapes are among the highest profit-yielding and important fruit related to the juice industry. Pakistan being an agricultural country, can widely benefit by cultivating and improving grapes per hectare yield. The biggest challenge in harvesting grapes to date is to detect their cluster successfully; many approaches tend to answer this problem by harvest …

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How Visual Stimuli Evoked P300 Is Transforming The Brain–Computer Interface Landscape: A Prisma Compliant Systematic Review, Jai Kalra, Prashasti Mittal, Nirmiti Mittal, Abhishek Arora, Utkarsh Tewari, Aviral Chharia, Rahul Upadhyay, Vinay Kumar, Luca Longo Jan 2023

How Visual Stimuli Evoked P300 Is Transforming The Brain–Computer Interface Landscape: A Prisma Compliant Systematic Review, Jai Kalra, Prashasti Mittal, Nirmiti Mittal, Abhishek Arora, Utkarsh Tewari, Aviral Chharia, Rahul Upadhyay, Vinay Kumar, Luca Longo

Articles

Non-invasive Visual Stimuli evoked-EEGbased P300 BCIs have gained immense attention in recent years due to their ability to help patients with disability using BCI-controlled assistive devices and applications. In addition to the medical field, P300 BCI has applications in entertainment, robotics, and education. The current article systematically reviews 147 articles that were published between 2006-2021*. Articles that pass the pre-defined criteria are included in the study. Further, classification based on their primary focus, including article orientation, participants’ age groups, tasks given, databases, the EEG devices used in the studies, classification models, and application domain, is performed. The application-based classification considers …

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Schizo-Net: A Novel Schizophrenia Diagnosis Framework Using Late Fusion Multimodal Deep Learning On Electroencephalogram-Based Brain Connectivity Indices, Nitin Grover, Aviral Chharia, Rahul Upadhyay, Luca Longo Jan 2023

Schizo-Net: A Novel Schizophrenia Diagnosis Framework Using Late Fusion Multimodal Deep Learning On Electroencephalogram-Based Brain Connectivity Indices, Nitin Grover, Aviral Chharia, Rahul Upadhyay, Luca Longo

Articles

Schizophrenia (SCZ) is a serious mental condition that causes hallucinations, delusions, and disordered thinking. Traditionally, SCZ diagnosis involves the subject’s interview by a skilled psychiatrist. The process needs time and is bound to human errors and bias. Recently, brain connectivity indices have been used in a few pattern recognition methods to discriminate neuro-psychiatric patients from healthy subjects. The study presents Schizo-Net , a novel, highly accurate, and reliable SCZ diagnosis model based on a late multimodal fusion of estimated brain connectivity indices from EEG activity. First, the raw EEG activity is pre-processed exhaustively to remove unwanted artifacts. Next, six brain …

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A Big Data Smart Agricultural System: Recommending Optimum Fertilisers For Crops, Vuong Ngo, Thuy-Van T. Duong, Nguyen Nguyen, Cach N. Dang, Owen Conlan Jan 2023

A Big Data Smart Agricultural System: Recommending Optimum Fertilisers For Crops, Vuong Ngo, Thuy-Van T. Duong, Nguyen Nguyen, Cach N. Dang, Owen Conlan

Articles

Nutrients are important to promote plant growth and nutrient deficiency is the primary factor limiting crop production. However, excess fertilisers can also have a negative impact on crop quality and yield, cause an increase in pollution and decrease producer profit. Hence, determining the suitable quantities of fertiliser for every crop is very useful. Currently, the agricultural systems with internet of things make very large data volumes. Exploiting agricultural Big Data will help to extract valuable information. However, designing and implementing a large scale agricultural data warehouse are very challenging. The data warehouse is a key module to build a smart …

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An Aggregation-Based Algebraic Multigrid Method With Deflation Techniques And Modified Generic Factored Approximate Sparse Inverses, Anastasia Natsiou, George A. Gravvanis, Christos K. Filelis-Papadopoulos, Konstantinos M. Giannoutakis Jan 2023

An Aggregation-Based Algebraic Multigrid Method With Deflation Techniques And Modified Generic Factored Approximate Sparse Inverses, Anastasia Natsiou, George A. Gravvanis, Christos K. Filelis-Papadopoulos, Konstantinos M. Giannoutakis

Articles

In this paper, we examine deflation-based algebraic multigrid methods for solving large systems of linear equations. Aggregation of the unknown terms is applied for coarsening, while deflation techniques are proposed for improving the rate of convergence. More specifically, the V-cycle strategy is adopted, in which, at each iteration, the solution is computed by initially decomposing it utilizing two complementary subspaces. The approximate solution is formed by combining the solution obtained using multigrids and deflation. In order to improve performance and convergence behavior, the proposed scheme was coupled with the Modified Generic Factored Approximate Sparse Inverse preconditioner. Furthermore, a parallel version …

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Nesnet: A Deep Network For Estimating Near-Surface Pollutant Concentrations, Prasanjit Dey, Bibhash Pran Das, Yee Hui Lee, Soumyabrata Dev Jan 2023

Nesnet: A Deep Network For Estimating Near-Surface Pollutant Concentrations, Prasanjit Dey, Bibhash Pran Das, Yee Hui Lee, Soumyabrata Dev

Articles

Atmospheric pollution has become a serious threat in recent years. The advancements and expansion of industrial activity and civilization have been the major catalysts. With serious consequences like climate change and global warming, the onset of which is already being observed, keeping a check on atmospheric pollutant levels is now more important than ever. Trace gases play a major role in atmospheric chemistry. Many of these are also regarded as major atmospheric pollutants. The concentration of gases, such as (SO2), (O3), (NO2), etc., are indicators of air quality. Therefore, in this study, we primarily concern ourselves with concentrations of NO2, …

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Towards Sweetness Classification Of Orange Cultivars Using Short‑Wave Nir Spectroscopy, Ayesha Zeb, Waqar Shahid Qureshi, Abdul Ghafoor, Amanullah Malik, Muhammad Imran, Alina Mirza, Mohsin Islam Tiwana, Eisa Alanazi Jan 2023

Towards Sweetness Classification Of Orange Cultivars Using Short‑Wave Nir Spectroscopy, Ayesha Zeb, Waqar Shahid Qureshi, Abdul Ghafoor, Amanullah Malik, Muhammad Imran, Alina Mirza, Mohsin Islam Tiwana, Eisa Alanazi

Articles

The global orange industry constantly faces new technical challenges to meet consumer demands for quality fruits. Instead of traditional subjective fruit quality assessment methods, the interest in the horticulture industry has increased in objective, quantitative, and non-destructive assessment methods. Oranges have a thick peel which makes their non-destructive quality assessment challenging. This paper evaluates the potential of short-wave NIR spectroscopy and direct sweetness classification approach for Pakistani cultivars of orange, i.e., Red-Blood, Mosambi, and Succari. The correlation between quality indices, i.e., Brix, titratable acidity (TA), Brix: TA and BrimA (Brix minus acids), sensory assessment of the fruit, and short-wave NIR …

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Do Games Reduce Math Anxiety? A Meta-Analysis, Pierpaolo Dondio, Viacheslav Filonenko, Mariana Rocha Jan 2023

Do Games Reduce Math Anxiety? A Meta-Analysis, Pierpaolo Dondio, Viacheslav Filonenko, Mariana Rocha

Articles

In this paper, we meta-analyse the empirical evidence about the effectiveness of game-based interventions to reduce students' level of math anxiety. After performing a search for randomised controlled studies relevant to game-based intervention for math anxiety, 16 experimental studies with a total of 686 participants described in 11 peer-review articles met the selection criteria.A random-effects meta-analysis indicated a small and non-significant reduction of math anxiety (mean effect size ES=-0.32, CI=[-0.64,0.01]). The results were moderated by several factors: non-digital games were more effective, while digital games had a negligible mean effect size of $ES=-0.13$, $CI=[-0.33,0.08]$. The effect size was moderated also …

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Rate Of Change Of Direct-Axis Current Component Protection Scheme For Inverter-Based Islanded Microgrids, Abdolhamid Farshadi, Behzad Keyvani Eydi, Hamed Nafisi, Hossein Askarian-Abyaneh, Arash Beiranvand Jan 2023

Rate Of Change Of Direct-Axis Current Component Protection Scheme For Inverter-Based Islanded Microgrids, Abdolhamid Farshadi, Behzad Keyvani Eydi, Hamed Nafisi, Hossein Askarian-Abyaneh, Arash Beiranvand

Articles

Rapid growth in the utilization of the inverter-interfaced distributed energy resources (IIDERs) in microgrids has brought new challenges in the network protection area. Microgrid protection specifically becomes a concern during operation in the islanded mode. There is a considerable reduction in fault current levels in this mode compared to when the microgrid is connected to the grid, which makes conventional algorithms operate with significant delay or, in many cases, not even pick up the fault. This paper proposes a protection algorithm based on the rate of change of direct-axis current component ( id ) to protect inverter-based microgrids (IBMGs). The …

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