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2021

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Articles 25591 - 25620 of 27884

Full-Text Articles in Physical Sciences and Mathematics

Determining Overfitting And Underfitting In Generative Adversarial Networksusing Fréchet Distance, Enes Eken Jan 2021

Determining Overfitting And Underfitting In Generative Adversarial Networksusing Fréchet Distance, Enes Eken

Turkish Journal of Electrical Engineering and Computer Sciences

Generative adversarial networks (GANs) can be used in a wide range of applications where drawing samples from a data probability distribution without explicitly representing it is essential. Unlike the deep convolutional neural networks (CNNs) trained for mapping an input to one of the multiple outputs, monitoring the overfitting and underfitting in GANs is not trivial since they are not classifying but generating a data. While training set and validation set accuracy give a direct sense of success in terms of overfitting and underfitting for CNNs during the training process, evaluating the GANs mainly depends on the visual inspection of the …

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Obround Trees: Sparsity Enhanced Feedback Motion Planning Of Differential Driverobotic Systems, Mustafa Mert Ankarali Jan 2021

Obround Trees: Sparsity Enhanced Feedback Motion Planning Of Differential Driverobotic Systems, Mustafa Mert Ankarali

Turkish Journal of Electrical Engineering and Computer Sciences

Robot motion planning & control is one of the most critical and prevalent problems in the robotics community. Even though original motion planning algorithms had relied on "open-loop" strategies and policies, researchers and engineers have been focusing on feedback motion planning and control algorithms due to the uncertainties, such as process and sensor noise of autonomous robotic applications. Recently, several studies proposed some robust feedback motion planning strategies based on sparsely connected safe zones. In this class of planning and control policies, local control policy inside a single zone computes and feeds the control actions that can drive the robot …

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Novel Ofdm Transmission Scheme Using Generalized Prefix With Subcarrierindex Modulation, Yusuf Acar Jan 2021

Novel Ofdm Transmission Scheme Using Generalized Prefix With Subcarrierindex Modulation, Yusuf Acar

Turkish Journal of Electrical Engineering and Computer Sciences

The cyclic prefix (CP) is a prefix technique widely used in orthogonal frequency division multiplexing (OFDM) systems in order to eliminate the intersymbol interference (ISI) caused by the dispersion of wireless channels. However, CP reduces the number of symbols that can be transmitted in one OFDM symbol. Therefore, CP is one of the bottlenecks of OFDM systems limiting their spectral efficiency (SE). This limitation on the SE of the classical CP-based OFDM system is the main motivation for this work to introduce a novel method. In this paper, the design of a new CP structure, which is based on the …

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Control Synthesis For Parametric Timed Automata Under Reachability, Ebru Aydin Göl Jan 2021

Control Synthesis For Parametric Timed Automata Under Reachability, Ebru Aydin Göl

Turkish Journal of Electrical Engineering and Computer Sciences

Timed automata is a fundamental modeling formalism for real-time systems. During the design of such real-time systems, often the system information is incomplete, and design choices can vary. These uncertainties can be integrated to the model via parameters and labelled transitions. Then, the design can be completed by tuning the parameters and restricting the transitions via controller synthesis. These problems, namely parameter synthesis and controller synthesis, are studied separately in the literature. Herein, these are combined to generate an automaton satisfying the given specification by both parameter tuning and controller synthesis, thus exploring all design choices. First, it is shown …

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A New Approach: Semisupervised Ordinal Classification, Ferda Ünal, Derya Bi̇rant, Özlem Şeker Jan 2021

A New Approach: Semisupervised Ordinal Classification, Ferda Ünal, Derya Bi̇rant, Özlem Şeker

Turkish Journal of Electrical Engineering and Computer Sciences

Semisupervised learning is a type of machine learning technique that constructs a classifier by learning from a small collection of labeled samples and a large collection of unlabeled ones. Although some progress has been made in this research area, the existing semisupervised methods provide a nominal classification task. However, semisupervised learning for ordinal classification is yet to be explored. To bridge the gap, this study combines two concepts ?semisupervised learning? and "ordinal classification" for the categorical class labels for the first time and introduces a new concept of "semisupervised ordinal classification". This paper proposes a new algorithm for semisupervised learning …

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Novel Fast Terminal Sliding Mode Controller With Current Constraint Forpermanent-Magnet Synchronous Motor, Yao Fang, Huifang Kong, Daoyuan Ding Jan 2021

Novel Fast Terminal Sliding Mode Controller With Current Constraint Forpermanent-Magnet Synchronous Motor, Yao Fang, Huifang Kong, Daoyuan Ding

Turkish Journal of Electrical Engineering and Computer Sciences

Under the noncascade structure, the balance between q-axis current constraint and dynamic performance in permanent-magnet synchronous motor system has become a critical problem. On the one hand, large transient current is required to provide high torque to achieve fast dynamic performance. On the other hand, current constraint becomes a state constraint problem, instead of governing q-axis reference current in the cascade structure directly. Aiming at this issue, a novel fast terminal sliding mode control (FTSMC)-based controller with current constraint is developed in this paper. The novelty of this scheme is related to the proposed penalty function based on interior point …

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Distributed Denial Of Service Attack Detection In Cloud Computing Using Hybridextreme Learning Machine, Gopal Singh Kushwah, Virender Ranga Jan 2021

Distributed Denial Of Service Attack Detection In Cloud Computing Using Hybridextreme Learning Machine, Gopal Singh Kushwah, Virender Ranga

Turkish Journal of Electrical Engineering and Computer Sciences

One of the major security challenges in cloud computing is distributed denial of service (DDoS) attacks. In these attacks, multiple nodes are used to attack the cloud by sending huge traffic. This results in the unavailability of cloud services to legitimate users. In this research paper, a hybrid machine learning-based technique has been proposed to detect these attacks. The proposed technique is implemented by combining the extreme learning machine (ELM) model and the blackhole optimization algorithm. Various experiments have been performed with the help of four benchmark datasets namely, NSL KDD, ISCX IDS 2012, CICIDS2017, and CICDDoS2019, to evaluate the …

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A Novel Hybrid Decision-Based Filter And Universal Edge-Based Logical Smoothingadd-On To Remove Impulsive Noise, Rajanbir Singh Ghumaan, Prateek Jeet Singh Sohi, Nikhil Sharma, Bharat Garg Jan 2021

A Novel Hybrid Decision-Based Filter And Universal Edge-Based Logical Smoothingadd-On To Remove Impulsive Noise, Rajanbir Singh Ghumaan, Prateek Jeet Singh Sohi, Nikhil Sharma, Bharat Garg

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a novel hybrid filter along with a universal extension to remove salt and pepper noise even at a very high noise density. The proposed filter initially specifies a threshold and then denoises the image using a combination of linear, nonlinear, and probabilistic techniques. Furthermore, to improve the quality, a universal add-on is presented which uses edge detection and smoothening techniques to brush out fine details from the restored image. To evaluate the efficacy, the proposed and existing filtering techniques are implemented in MATLAB and simulated with benchmark images. The simulation results show that the proposed filter is …

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Shapeshifter: A Morphable Microprocessor For Low Power, Nazli Tokatli, İsa Ahmet Güney, Sercan Sari, Merve Güney, Uğur Nezi̇r, Gürhan Küçük Jan 2021

Shapeshifter: A Morphable Microprocessor For Low Power, Nazli Tokatli, İsa Ahmet Güney, Sercan Sari, Merve Güney, Uğur Nezi̇r, Gürhan Küçük

Turkish Journal of Electrical Engineering and Computer Sciences

A composite core contains large and small heterogeneous microengines. The most important property of composite cores is their ability to select the most proper microengine for running applications to save power without sacrificing too much performance. To achieve this, a composite core tries to predict the performance of the passive microengine by collecting various processor statistics from the active microengine at runtime. In the method proposed in the literature, the microengine, which is more ideal for running the rest of the application, is determined by a migrationdecision circuitry that is bound to collected statistics and complex functions, which are run …

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Clustering Ensemble Selection Based On The Extended Jaccard Measure, Hajar Khalili, Mohsen Rabbani, Ebrahim Akbari Jan 2021

Clustering Ensemble Selection Based On The Extended Jaccard Measure, Hajar Khalili, Mohsen Rabbani, Ebrahim Akbari

Turkish Journal of Electrical Engineering and Computer Sciences

Clustering ensemble selection has shown high efficiency in the improvement of the quality of clustering solutions. This technique comprises two important metrics: diversity and quality. It has been empirically proved that ensembles of higher effectiveness can be achieved through taking into consideration the diversity and quality simultaneously. However, the relationships between these two metrics in base clusterings have remained uncertain. This paper suggests a new hierarchical selection algorithm using a diversity/quality measure based on the Jaccard similarity measure. In the proposed algorithm, the selection of the subsets of the clustering partitions is done based on their diversity measures. The proposed …

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Fecal Sample Collection Methods And Time Of Day Impact Microbiome Composition And Short Chain Fatty Acid Concentrations, Jacquelyn Jones, Stacey N. Reinke, Alishum Ali, Debra J. Palmer, Claus T. Christophersen Jan 2021

Fecal Sample Collection Methods And Time Of Day Impact Microbiome Composition And Short Chain Fatty Acid Concentrations, Jacquelyn Jones, Stacey N. Reinke, Alishum Ali, Debra J. Palmer, Claus T. Christophersen

Research outputs 2014 to 2021

Associations between the human gut microbiome and health outcomes continues to be of great interest, although fecal sample collection methods which impact microbiome studies are sometimes neglected. Here, we expand on previous work in sample optimization, to promote high quality microbiome data. To compare fecal sample collection methods, amplicons from the bacterial 16S rRNA gene (V4) and fungal (ITS2) region, as well as short chain fatty acid (SCFA) concentrations were determined in fecal material over three timepoints. We demonstrated that spot sampling of stool results in variable detection of some microbial members, and inconsistent levels of SCFA; therefore, sample homogenization …

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Association Between Community-Based Self-Reported Covid-19 Symptoms And Social Deprivation Explored Using Symptom Tracker Apps: A Repeated Cross-Sectional Study In Northern Ireland, Jennifer M. Mckinley, David Cutting, Neil Anderson, Conor Graham, Brian Johnston, Ute Mueller, Peter M. Atkinson, Hugo Van Woerden, Declan T. Bradley, Frank Kee Jan 2021

Association Between Community-Based Self-Reported Covid-19 Symptoms And Social Deprivation Explored Using Symptom Tracker Apps: A Repeated Cross-Sectional Study In Northern Ireland, Jennifer M. Mckinley, David Cutting, Neil Anderson, Conor Graham, Brian Johnston, Ute Mueller, Peter M. Atkinson, Hugo Van Woerden, Declan T. Bradley, Frank Kee

Research outputs 2014 to 2021

Objectives: The aim of the study was to investigate the spatial and temporal relationships between the prevalence of COVID-19 symptoms in the community-level and area-level social deprivation. Design: Spatial mapping, generalised linear models, using time as a factor and spatial-lag models were used to explore the relationship between self-reported COVID-19 symptom prevalence as recorded through two smartphone symptom tracker apps and a range of socioeconomic factors using a repeated cross-sectional study design. Setting: In the community in Northern Ireland, UK. The analysis period included the earliest stages of non-pharmaceutical interventions and societal restrictions or 'lockdown' in 2020. Participants: Users of …

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Kelp-Associated Microbes Facilitate Spatial Subsidy In A Detrital-Based Food Web In A Shoreline Ecosystem, Charu Lata Singh, Megan J. Huggett, Paul S. Lavery, Christin Säwström, Glenn A. Hyndes Jan 2021

Kelp-Associated Microbes Facilitate Spatial Subsidy In A Detrital-Based Food Web In A Shoreline Ecosystem, Charu Lata Singh, Megan J. Huggett, Paul S. Lavery, Christin Säwström, Glenn A. Hyndes

Research outputs 2014 to 2021

Microbes are ubiquitous but our knowledge of their effects on consumers is limited in benthic marine systems. Shorelines often form hotspots of microbial and detritivore activity due to the large amounts of detrital macrophytes that are exported from other coastal ecosystems, such as kelp forests, and accumulate in these systems. Shoreline ecosystems therefore provide a useful model system to examine microbial-detritivore interactions. We experimentally test whether bacteria in the biofilm of kelp provide a bottom-up influence on growth and reproductive output of detritivores in shorelines where detrital kelp accumulates, by manipulating the bacterial abundances on kelp (Ecklonia radiata). The growth …

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Design, Development, And Characterization Of Low Distortion Advanced Semitransparent Photovoltaic Glass For Buildings Applications, Mohammad Khairul Basher, Mohammad N. E. Alam, Kamal Alameh Jan 2021

Design, Development, And Characterization Of Low Distortion Advanced Semitransparent Photovoltaic Glass For Buildings Applications, Mohammad Khairul Basher, Mohammad N. E. Alam, Kamal Alameh

Research outputs 2014 to 2021

Aesthetic appearance of building-integrated photovoltaic (BIPV) products, such as semi-transparent PV (STPV) glass, is crucial for their widespread adoption and contribution to the net-zero energy building (NZEB) goal. However, the visual distortion significantly limits the aesthetics of STPV glass. In this study, we investigate the distortion effect of transparent periodic-micropattern-based thin-film PV (PMPV) panels available in the market. To minimize the visual distortion of such PMPV glass panel types, we design and develop an aperiodic micropattern-based PV (APMP) glass that significantly reduces visual distortion. The developed APMP glass demonstrates a haze ratio of 3.7% compared to the 10.7% of PMPV …

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Proteome Analysis And Epitope Mapping In A Commercial Reduced-Gluten Wheat Product, Mitchell G. Nye-Wood, Angela Juhasz, Utpal Bos, Michelle L. Colgrave Jan 2021

Proteome Analysis And Epitope Mapping In A Commercial Reduced-Gluten Wheat Product, Mitchell G. Nye-Wood, Angela Juhasz, Utpal Bos, Michelle L. Colgrave

Research outputs 2014 to 2021

Gluten related disorders, such as coeliac disease, wheat allergy and baker's asthma are triggered by proteins present in food products made from wheat and related cereal species. The only treatment of these medical illnesses is a strict gluten-free diet; however, gluten-free products that are currently available in the market can have lower nutritional quality and are more expensive than traditional gluten containing cereal products. These constraints have led to the development of gluten-free or gluten-reduced ingredients. In this vein, a non-GMO wheat flour that purports to contain “65% less allergenic gluten” was recently brought to market. The present study aims …

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Green Underwater Wireless Communications Using Hybrid Optical-Acoustic Technologies, Kazi Y. Islam, Iftekhar Ahmad, Daryoush Habibi, M. Ishtiaque A. Zahed, Joarder Kamruzzaman Jan 2021

Green Underwater Wireless Communications Using Hybrid Optical-Acoustic Technologies, Kazi Y. Islam, Iftekhar Ahmad, Daryoush Habibi, M. Ishtiaque A. Zahed, Joarder Kamruzzaman

Research outputs 2014 to 2021

Underwater wireless communication is a rapidly growing field, especially with the recent emergence of technologies such as autonomous underwater vehicles (AUVs) and remotely operated vehicles (ROVs). To support the high-bandwidth applications using these technologies, underwater optics has attracted significant attention, alongside its complementary technology – underwater acoustics. In this paper, we propose a hybrid opto-acoustic underwater wireless communication model that reduces network power consumption and supports high-data rate underwater applications by selecting appropriate communication links in response to varying traffic loads and dynamic weather conditions. Underwater optics offers high data rates and consumes less power. However, due to the severe …

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Sensing Of Surface And Bulk Refractive Index Using Magnetophotonic Crystal With Hybrid Magneto-Optical Response, Daria Ignatyeva, Pavel Kapralov, Polina Golovko, Polina Shilina, Anastasiya Khramova, Sergey Sekatskii, Mohammad Nur-E-Alam, Kamal Alameh, Mikhail Vasiliev, Andrey Kalish, Vladimir Belotelov Jan 2021

Sensing Of Surface And Bulk Refractive Index Using Magnetophotonic Crystal With Hybrid Magneto-Optical Response, Daria Ignatyeva, Pavel Kapralov, Polina Golovko, Polina Shilina, Anastasiya Khramova, Sergey Sekatskii, Mohammad Nur-E-Alam, Kamal Alameh, Mikhail Vasiliev, Andrey Kalish, Vladimir Belotelov

Research outputs 2014 to 2021

We propose an all-dielectric magneto-photonic crystal with a hybrid magneto-optical response that allows for the simultaneous measurements of the surface and bulk refractive index of the analyzed substance. The approach is based on two different spectral features of the magneto-optical response corresponding to the resonances in p-and s-polarizations of the incident light. Angular spectra of p-polarized light have a step-like behavior near the total internal reflection angle which position is sensitive to the bulk refractive index. S-polarized light excites the TE-polarized optical Tamm surface mode localized in a submicron region near the photonic crystal surface and is sensitive to the …

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Classification Of Skin Disease Using Deep Learning Neural Networks With Mobilenet V2 And Lstm, Parvathaneni N. Srinivasu, Jalluri G. Siva Sai, Muhammad F. Ijaz, Akash K. Bhoi, Wonjoon Kim, James J. Kang Jan 2021

Classification Of Skin Disease Using Deep Learning Neural Networks With Mobilenet V2 And Lstm, Parvathaneni N. Srinivasu, Jalluri G. Siva Sai, Muhammad F. Ijaz, Akash K. Bhoi, Wonjoon Kim, James J. Kang

Research outputs 2014 to 2021

Deep learning models are efficient in learning the features that assist in understanding complex patterns precisely. This study proposed a computerized process of classifying skin disease through deep learning-based MobileNet V2 and Long Short Term Memory (LSTM). The MobileNet V2 model proved to be efficient with a better accuracy that can work on lightweight computational devices. The proposed model is efficient in maintaining stateful information for precise predictions. A grey-level co-occurrence matrix is used for assessing the progress of diseased growth. The performance has been compared against other state-of-the-art models such as Fine-Tuned Neural Networks (FTNN), Convolutional Neural Network (CNN), …

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Infrequent Pattern Detection For Reliable Network Traffic Analysis Using Robust Evolutionary Computation, A. N. M. Bazlur Rashid, Mohiuddin Ahmed, Al-Sakib K. Pathan Jan 2021

Infrequent Pattern Detection For Reliable Network Traffic Analysis Using Robust Evolutionary Computation, A. N. M. Bazlur Rashid, Mohiuddin Ahmed, Al-Sakib K. Pathan

Research outputs 2014 to 2021

While anomaly detection is very important in many domains, such as in cybersecurity, there are many rare anomalies or infrequent patterns in cybersecurity datasets. Detection of infrequent patterns is computationally expensive. Cybersecurity datasets consist of many features, mostly irrelevant, resulting in lower classification performance by machine learning algorithms. Hence, a feature selection (FS) approach, i.e., selecting relevant features only, is an essential preprocessing step in cybersecurity data analysis. Despite many FS approaches proposed in the literature, cooperative co-evolution (CC)-based FS approaches can be more suitable for cybersecurity data preprocessing considering the Big Data scenario. Accordingly, in this paper, we have …

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A Novel Augmented Deep Transfer Learning For Classification Of Covid-19 And Other Thoracic Diseases From X-Rays, Fouzia Atlaf, Syed M. S. Islam, Naeem K. Janjua Jan 2021

A Novel Augmented Deep Transfer Learning For Classification Of Covid-19 And Other Thoracic Diseases From X-Rays, Fouzia Atlaf, Syed M. S. Islam, Naeem K. Janjua

Research outputs 2014 to 2021

Deep learning has provided numerous breakthroughs in natural imaging tasks. However, its successful application to medical images is severely handicapped with the limited amount of annotated training data. Transfer learning is commonly adopted for the medical imaging tasks. However, a large covariant shift between the source domain of natural images and target domain of medical images results in poor transfer learning. Moreover, scarcity of annotated data for the medical imaging tasks causes further problems for effective transfer learning. To address these problems, we develop an augmented ensemble transfer learning technique that leads to significant performance gain over the conventional transfer …

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Evaluating The Impact Of Sandbox Applications On Live Digital Forensics Investigation, Reem Bashir, Helge Janicke, Wen Zeng Jan 2021

Evaluating The Impact Of Sandbox Applications On Live Digital Forensics Investigation, Reem Bashir, Helge Janicke, Wen Zeng

Research outputs 2014 to 2021

Sandbox applications can be used as anti-forensics techniques to hide important evidence in the digital forensics investigation. There is limited research on sandboxing technologies, and the existing researches on sandboxing are focusing on the technology itself. The impact of sandbox applications on live digital forensics investigation has not been systematically analysed and documented. In this study, we proposed a methodology to analyse sandbox applications on Windows systems. The impact of having standalone sandbox applications on Windows operating systems image was evaluated. Experiments were conducted to examine the artefacts of three sandbox applications: Sandboxie, BufferZone and ToolWiz Time Freeze on Windows …

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Viral-Mediated Microbe Mortality Modulated By Ocean Acidification And Eutrophication: Consequences For The Carbon Fluxes Through The Microbial Food Web, Andrea Malits, Julia A. Boras, Vanessa Balagué, Eva Calvo, Josep M. Gasol, Cèlia Marrasé, Carles Pelejero, Jarone Pinhassi, Maria Montserrat Sala, Dolors Vaqué Jan 2021

Viral-Mediated Microbe Mortality Modulated By Ocean Acidification And Eutrophication: Consequences For The Carbon Fluxes Through The Microbial Food Web, Andrea Malits, Julia A. Boras, Vanessa Balagué, Eva Calvo, Josep M. Gasol, Cèlia Marrasé, Carles Pelejero, Jarone Pinhassi, Maria Montserrat Sala, Dolors Vaqué

Research outputs 2014 to 2021

Anthropogenic carbon emissions are causing changes in seawater carbonate chemistry including a decline in the pH of the oceans. While its aftermath for calcifying microbes has been widely studied, the effect of ocean acidification (OA) on marine viruses and their microbial hosts is controversial, and even more in combination with another anthropogenic stressor, i.e., human-induced nutrient loads. In this study, two mesocosm acidification experiments with Mediterranean waters from different seasons revealed distinct effects of OA on viruses and viral-mediated prokaryotic mortality depending on the trophic state and the successional stage of the plankton community. In the winter bloom situation, low …

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The Efficacy Of Aligning Lessons Learnt From Significant Bushfire Incidents To The Organisational Stratum, Jennifer Medbury, David J. Brooks, Michael Coole Jan 2021

The Efficacy Of Aligning Lessons Learnt From Significant Bushfire Incidents To The Organisational Stratum, Jennifer Medbury, David J. Brooks, Michael Coole

Research outputs 2014 to 2021

Australia's bushfire seasons are expected to become longer and more severe due to the effects of climate change and an increasing population living in rural-urban fringes. Social and economic vulnerability to extreme natural hazards means that Australia’s emergency services sector plays a significant role in community safety and wellbeing. Therefore, it is important that the sector continually improves. Australia has a long history of conducting external reviews into significant bushfires. While these reviews receive good support and seek to identify relevant lessons, barriers remain that prevent these lessons from being effectively learnt. It is possible that some of these barriers …

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Friedel–Crafts Addition Of Indoles To Nitrones Promoted By Trimethylsilyl Trifluoromethanesulfonate, Zachary Z. Oracheff, Helen L. Xia, Christopher D. Poff, Scott E. Isaacson, C. Wade Downey Jan 2021

Friedel–Crafts Addition Of Indoles To Nitrones Promoted By Trimethylsilyl Trifluoromethanesulfonate, Zachary Z. Oracheff, Helen L. Xia, Christopher D. Poff, Scott E. Isaacson, C. Wade Downey

Chemistry Faculty Publications

N-alkylindoles undergo Friedel–Crafts addition to aryl and secondary alkyl nitrones in the presence of trimethylsilyl trifluoromethanesulfonate and a trialkylamine to produce 3-(1- (silyloxyamino)alkyl)indoles. Spontaneous conversion to the bisindolyl(aryl)methanes, which is thermodynamically favored for nitrones derived from aromatic aldehydes, is suppressed under the reaction conditions. The silyloxyamino group can be deprotected with tetrabutylammonium fluoride to yield the hydroxylamine.

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Assessment Of Empirical And Semi-Analytical Algorithms Using Modis-Aqua For Representing In-Situ Chromophoric Dissolved Organic Matter (Cdom) In The Bering, Chukchi, And Western Beaufort Seas Of The Pacific Arctic Region, Melishia I. Santiago, Karen E. Frey Jan 2021

Assessment Of Empirical And Semi-Analytical Algorithms Using Modis-Aqua For Representing In-Situ Chromophoric Dissolved Organic Matter (Cdom) In The Bering, Chukchi, And Western Beaufort Seas Of The Pacific Arctic Region, Melishia I. Santiago, Karen E. Frey

Geography

We analyzed a variety of satellite-based ocean color products derived using MODIS-Aqua to investigate the most accurate empirical and semi-analytical algorithms for representing in-situ chromophoric dissolved organic matter (CDOM) across a large latitudinal transect in the Bering, Chukchi, and western Beaufort Seas of the Pacific Arctic region. In particular, we compared the performance of empirical (CDOM index) and several semi-analytical algorithms (quasi-analytical algorithm (QAA), Carder, Garver-Siegel-Maritorena (GSM), and GSM-A) with field measurements of CDOM absorption (aCDOM) at 412 nanometers (nm) and 443 nm. These algorithms were compared with in-situ CDOM measurements collected on cruises during July 2011, 2013, 2014, 2015, …

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Running Whidbey: The Physiological And Psychological Impacts Of A 60 Mile Ultramarathon, Bree Daigneault Jan 2021

Running Whidbey: The Physiological And Psychological Impacts Of A 60 Mile Ultramarathon, Bree Daigneault

WWU Honors College Senior Projects

No abstract provided.

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Evaluating The Biotic Condition Of Restored Streams In Kentucky’S Inner Bluegrass Region, Charles Cole Crankshaw Jan 2021

Evaluating The Biotic Condition Of Restored Streams In Kentucky’S Inner Bluegrass Region, Charles Cole Crankshaw

Theses and Dissertations--Biosystems and Agricultural Engineering

Numerous stream restoration projects have been implemented in Kentucky’s Inner Bluegrass region to offset anthropogenic impacts. These projects range from full channel realignments to volunteer-led riparian installations. To assess the ability of said projects to restore stream habitat and biota, full restoration (n=12) and riparian (n=6) sites were compared to reference (n=6) and disturbed (n=12) sites using RBP and SVAP protocols, macroinvertebrate samples, and geomorphology. General trends for SVAP, RBP, and BI scores, starting with highest habitat or biotic quality, were reference sites, full and riparian restoration sites, then disturbed sites. The number of EPT taxa, another indicator of biological …

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The Effects Of Saline Soil On Microbiome And The Isolation Of Root-Associated Microbes To Relieve Salinity Stress, Duncan Jakubowski Jan 2021

The Effects Of Saline Soil On Microbiome And The Isolation Of Root-Associated Microbes To Relieve Salinity Stress, Duncan Jakubowski

Electronic Theses and Dissertations

Increasing levels of salinity in once-viable lands for crop production is a serious and growing problem in the Northern Great Plains. The objectives of this study were to determine the effects of saline soil on the microbial composition of plant roots and bulk soil, to measure metabolic changes in plant roots from saline soil, to determine the viability of root-associated microbes as inoculants to increase stress tolerance in plants, as well as determine the impact of saline soil on nitrogen cycling genes linked to greenhouse gas production. This study hypothesizes that high soil salinity levels have a significant impact on …

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College Students Conceptions Of Particulate Nature Of Matter And The Impact On Research Instrumentation, Bridget Klutse Jan 2021

College Students Conceptions Of Particulate Nature Of Matter And The Impact On Research Instrumentation, Bridget Klutse

Electronic Theses and Dissertations

The main objective of this research was to explore the understanding and conceptions of Particulate Nature of Matter (PNM) with Chem 115 L students as the participants. Conceptions were defined specifically as beliefs and alternative beliefs about topics. The research also assessed the impact of analytical instrumentation in the chemistry laboratory on learning chemistry concepts. Eight questions (8) with multiple choice answers were administered to 10 students at the beginning and after the Fall 2018 semester via selective/purposeful sampling. Data were collected using surveys (pre- and post-surveys) and interviews (pre- and postinterviews), then analyzed quantitatively and qualitatively. The eight questions …

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A Study Of Geographic Information System-Based Watershed Processing For Hydrologic Analysis Of Ungauged Watersheds, Philip Adanbe Adalikwu Jan 2021

A Study Of Geographic Information System-Based Watershed Processing For Hydrologic Analysis Of Ungauged Watersheds, Philip Adanbe Adalikwu

Electronic Theses and Dissertations

The increasing application of geographic information system (GIS) technology in watershed modeling makes is necessary to further evaluate its impacts on runoff characteristics as a basis for improved hydrologic analysis in ungauged watersheds. Experts in the field of water resources and hydrology have recommended the practice of subdivision when modeling a watershed, and the use of observed data from hydrologically similar watershed to calibrate and validate an ungauged watershed’s model. However, previous studies have failed to adequately address the issues of watershed heterogeneity, spatial and temporal variability in physical parameters, GIS data resolution issues, including artifacts in automated extraction of …

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