Physical Sciences and Mathematics Commons^™

Implementing A Neural Network For Supervised Learning With A Random Configuration Of Layers And Nodes, Kane A. Phillips

Electronic Theses and Dissertations

Deep learning has a substantial amount of real-life applications, making it an increasingly popular subset of artificial intelligence over the last decade. These applications come to fruition due to the tireless research and implementation of neural networks. This paper goes into detail on the implementation of supervised learning neural networks utilizing MATLAB, with the purpose being to generate a neural network based on specifications given by a user. Such specifications involve how many layers are in the network, and how many nodes are in each layer. The neural network is then trained based on known sample values of a function …

Advancements In Bio-Based Novel (Co)Monomers For Polymeric Materials, Khristal Anne Monroe

Electronic Theses and Dissertations

Most current research in the area of sustainable and environmentally friendly materials relate to the use of renewable sources for the fabrication of bio-based polymers and composites. Using plant-based derivatives is a common strategy. Pine sap can be distilled into turpentines (light fraction) and pine rosin (heavy fraction). Pine rosin is obtained as a brittle solid and its major component is abietic acid. This project aims at investigating a synthetic approach for the synthesis of a pine rosin-based polymer that can be potentially used for manufacturing a collection device for pine sap. The synthetic strategy consisted in the preparation of …

Arnold Transformations As Applied To Data Encryption, Haley N. Anderson

Electronic Theses and Dissertations

As our world becomes increasingly digital, data security becomes key. Data must be encrypted such that it can be easily encrypted only by the intended recipient. Arnold Transformations are a useful tool in this because of its unpredictable periodicity. Our goal is to outline a method for choosing an Arnold Transformation that is both secure and easy to implement. We find the necessary and sufficient condition that a key matrix has periodicity. The chosen key matrix has a random structure, and it has a periodicity that is sufficiently high. We apply this method to several image and data string examples …

Lack Of Plasticity In Gopher Tortoise (Gopherus Polyphemus) Nesting Behavior And Fecundity In A Translocated Population, Jennifer N. Desha

Electronic Theses and Dissertations

Lack of Plasticity in Gopher Tortoise (Gopherus polyphemus) Nesting Behavior and Fecundity in a Translocated Population

Human Centeredness: The Foundation For Leadership-As-Practice In Complex Local/Regional Food Networks, Maryann Martinez

Antioch University Full-Text Dissertations & Theses

Our local and regional food systems are predominately modeled on a failed capitalist market-based economy. In the absence of corporate accountability, and/or support on the federal policy level, local and regional leadership and self-organized networks are critical to the scaling across and evolution of a moral and equitable food system. Networked food systems leaders are developing the capacity to solve wicked problems, and spark change. Understanding the values and practices of local food systems leadership that initiate, influence, and support activities is essential to understanding how to foster conditions for local and regional food network growth. My dissertation research is …

Decolonizing Food Systems Research – The Case Of Household Agricultural Food Access In Bikotiba, Togo, Katryna Maria Kibler

Antioch University Full-Text Dissertations & Theses

Indigenous West African farmers are among the most climate change threatened globally. Food insecurity is prevalent in West Africa because ecological, social, political, and economic instabilities, and globalization worsen climate pressures. In this study, I collaborated with the community of Bikotiba (bih-CO-ti-buh), Togo, to understand their household agricultural food access, one aspect of resilience to food insecurity. I adopted a feminist approach of reflexivity, radical vulnerability, and radical empathy, combined with decolonizing principles, to argue that there could be an ethical way for well-trained Western researchers to engage Indigenous communities, if negotiated carefully. Together, Indigenous Research Assistants and I developed …

White Pine Blister Rust Distribution In New Hampshire 1900-2018: Exploring The Impacts Of An Exotic Pathogen On Forest Composition And Succession, Janine Marr

Antioch University Full-Text Dissertations & Theses

White pine blister rust (WPBR) has been affecting New Hampshire’s white pines for more than a century, yet no data exist on the long-term effects of the non-native disease on the state’s forests, particularly with respect to the regeneration and sustainability of white pine, and forest succession. This study aimed to address the gaps in the literature by exploring: 1) the current distribution, incidence, and severity of WPBR in New Hampshire; 2) the application of two historical hazard ratings models, one climatic, and one biotic; and 3) the long-term effects of the disease on forest composition, structure, and succession. Historical …

Soil Carbon Stocks Vary Across Geomorphic Settings In Australian Temperate Tidal Marsh Ecosystems, Connor Gorham, Paul Lavery, Jeffrey J. Kelleway, Cristian Salinas, Oscar Serrano

Research outputs 2014 to 2021

Tidal marshes rank among the ecosystems with the highest capacity to sequester and store organic carbon (C_org) on earth. To inform conservation of coastal vegetated ecosystems for climate change mitigation, this study investigated the factors driving variability in carbon storage. We estimated soil C_org stocks in tidal marshes across temperate Western Australia and assessed differences among geomorphic settings (marine and fluvial deltas, and mid-estuary) and vegetation type (Sarcocornia quinqueflora and Juncus kraussii) linked to soil biogeochemistry. Soil C_org stocks within fluvial and mid-estuary settings were significantly higher (209 ± 14 and 211 ± 20 …

Titanium Nitride Thin Film Based Low‐Redox‐Interference Potentiometric Ph Sensing Electrodes, Shimrith Paul Shylendra, Wade Lonsdale, Magdalena Wajrak, Mohammad Nur‐E‐Alam, Kamal Alameh

Research outputs 2014 to 2021

© 2020 by the authors. Licensee MDPI, Basel, Switzerland.

In this work, a solid‐state potentiometric pH sensor is designed by incorporating a thin film of Radio Frequency Magnetron Sputtered (RFMS) Titanium Nitride (TiN) working electrode and a commercial Ag|AgCl|KCl double junction reference electrode. The sensor shows a linear pH slope of −59.1 mV/pH, R2 = 0.9997, a hysteresis as low as 1.2 mV, and drift below 3.9 mV/hr. In addition, the redox interference performance of TiN electrodes is compared with that of Iridium Oxide (IrO2) counterparts. Experimental results show −32mV potential shift (E0 value) in 1 mM ascorbic acid (reducing …

A Temporal Record Of Microplastic Pollution In Mediterranean Seagrass Soils, Martin Dahl, Sanne Bergman, Mats Björk, Elena Diaz-Almela, Maria Granberg, Martin Gullström, Carmen Leiva-Dueñas, Kerstin Magnusson, Candela Marco-Méndez, Nerea Piñeiro-Juncal, Miguel Ángel Mateo

Research outputs 2014 to 2021

© 2021 Elsevier Ltd Plastic pollution is emerging as a potential threat to the marine environment. In the current study, we selected seagrass meadows, known to efficiently trap organic and inorganic particles, to investigate the concentrations and dynamics of microplastics in their soil. We assessed microplastic contamination and accumulation in 210Pb dated soil cores collected in Posidonia oceanica meadows at three locations along the Spanish Mediterranean coast, with two sites located in the Almería region (Agua Amarga and Roquetas) and one at Cabrera Island (Santa Maria). Almería is known for its intense agricultural industry with 30 000 ha of plastic-covered …

An Energy-Efficient And Secure Data Inference Framework For Internet Of Health Things: A Pilot Study, James Jin Kang, Mahdi Dibaei, Gang Luo, Wencheng Yang, Paul Haskell-Dowland, Xi Zheng

Research outputs 2014 to 2021

© 2021 by the authors. Licensee MDPI, Basel, Switzerland. Privacy protection in electronic healthcare applications is an important consideration, due to the sensitive nature of personal health data. Internet of Health Things (IoHT) networks that are used within a healthcare setting have unique challenges and security requirements (integrity, authentication, privacy, and availability) that must also be balanced with the need to maintain efficiency in order to conserve battery power, which can be a significant limitation in IoHT devices and networks. Data are usually transferred without undergoing filtering or optimization, and this traffic can overload sensors and cause rapid battery consumption …

A Secured Privacy-Preserving Multi-Level Blockchain Framework For Cluster Based Vanet, A. F.M.Suaib Akhter, Mohiuddin Ahmed, A. F.M.Shahen Shah, Adnan Anwar, Ahmet Zengin

Research outputs 2014 to 2021

© 2021 by the authors. Licensee MDPI, Basel, Switzerland. Existing research shows that Cluster-based Medium Access Control (CB-MAC) protocols perform well in controlling and managing Vehicular Ad hoc Network (VANET), but requires ensuring improved security and privacy preserving authentication mechanism. To this end, we propose a multi-level blockchain-based privacy-preserving authentication protocol. The paper thoroughly explains the formation of the authentication centers, vehicles registration, and key generation processes. In the proposed architecture, a global authentication center (GAC) is responsible for storing all vehicle information, while Local Authentication Center (LAC) maintains a blockchain to enable quick handover between internal clusters of vehicle. …

Led Illumination Spectrum Manipulation For Increasing The Yield Of Sweet Basil (Ocimum Basilicum L.), Md Momtazur Rahman, Mikhail Vasiliev, Kamal Alameh

Research outputs 2014 to 2021

© 2021 by the authors. Licensee MDPI, Basel, Switzerland. Manipulation of the LED illumination spectrum can enhance plant growth rate and development in grow tents. We report on the identification of the illumination spectrum required to significantly enhance the growth rate of sweet basil (Ocimum basilicum L.) plants in grow tent environments by controlling the LED wavebands illuminating the plants. Since the optimal illumination spectrum depends on the plant type, this work focuses on identifying the illumination spectrum that achieves significant basil biomass improvement compared to improvements reported in prior studies. To be able to optimize the illumination spectrum, several …

Accessing The Effect Of Renewables On The Wholesale Power Market, Mohammad Nure Alam

Research outputs 2014 to 2021

© 2021, Econjournals. All rights reserved. The purpose of this paper is to examine how rising wind energy generation (in MWh) impact the wholesale power market’s volatility (in SEK) across four bidding regions in Sweden. Prior investigations show that though the increase in electricity production from wind energy lowers the average day-ahead electricity wholesale prices, however, uncertainty and volatility of market price could rise due to wind energy’s intermittent nature. This study results show that Swedish power market experiences higher price volatility in long-run frequency when the generation of wind electricity increases. The reason for this high and volatile electricity …

Detecting Sex-Related Changes To The Metabolome Of A Critically Endangered Freshwater Crayfish During The Mating Season, Emily Lette, Quinton Burnham, Nathan Lawler, Pierre Horwitz, Mary C. Boyce, David I. Broadhurst, Rodney Duffy, Annette Koenders

Research outputs 2014 to 2021

Captive breeding is a vital tool in the conservation of highly endangered species, as it is for the Margaret River hairy marron, Cherax tenuimanus, from the south west of Australia. A close relative, Cherax cainii, has almost completely displaced C. tenuimanus in the wild and is a successful aquaculture species, whereas C. tenuimanus has performed poorly in captivity. We used untargeted liquid chromatography-mass spectrometry to obtain metabolomic profiles of female and male C. tenuimanus held in controlled aquarium conditions during their reproductive period. Using repeated haemolymph sampling we tracked the metabolomic profiles of animals just prior to and …

Imputation, Modelling And Optimal Sampling Design For Digital Camera Data In Recreational Fisheries Monitoring, Ebenezer Afrifa-Yamoah

Theses: Doctorates and Masters

Digital camera monitoring has evolved as an active application-oriented scheme to help address questions in areas such as fisheries, ecology, computer vision, artificial intelligence, and criminology. In recreational fisheries research, digital camera monitoring has become a viable option for probability-based survey methods, and is also used for corroborative and validation purposes. In comparison to onsite surveys (e.g. boat ramp surveys), digital cameras provide a cost-effective method of monitoring boating activity and fishing effort, including night-time fishing activities. However, there are challenges in the use of digital camera monitoring that need to be resolved. Notably, missing data problems and the cost …

An Investigation Into The Efficacy Of Url Content Filtering Systems, Brett Ronald Turner

Theses: Doctorates and Masters

Content filters are used to restrict to restrict minors from accessing to online content deemed inappropriate. While much research and evaluation has been done on the efficiency of content filters, there is little in the way of empirical research as to their efficacy. The accessing of inappropriate material by minors, and the role content filtering systems can play in preventing the accessing of inappropriate material, is largely assumed with little or no evidence. This thesis investigates if a content filter implemented with the stated aim of restricting specific Internet content from high school students achieved the goal of stopping students …

A Defensive Strategy For Detecting Targeted Adversarial Poisoning Attacks In Machine Learning Trained Malware Detection Models, Adrian Michael Wood

Theses: Doctorates and Masters

Machine learning is a subset of Artificial Intelligence which is utilised in a variety of different fields to increase productivity, reduce overheads, and simplify the work process through training machines to automatically perform a task. Machine learning has been implemented in many different fields such as medical science, information technology, finance, and cyber security. Machine learning algorithms build models which identify patterns within data, which when applied to new data, can map the input to an output with a high degree of accuracy. To build the machine learning model, a dataset comprised of appropriate examples is divided into training and …

Evaluating The Relative Importance Of Stormwater For Nutrient And Metal Contamination To The Urban, Groundwater Dependent Yellagonga Wetlands, Through Wetland Budgeting, Jonas Polifka

Theses: Doctorates and Masters

Wetlands provide numerous ecosystem services and can be utilised as pollutant sinks, however excessive contamination of wetlands can induce adverse effects to wetland ecology and lead to degradation of its values. Runoff from precipitation mobilizes contaminants from impervious surfaces which are, in some case, transported directly to wetlands through stormwater drainage. Urban stormwater can be a significant source of contaminants to wetlands, although its overall importance needs to be assessed for each wetland individually. Wetland budgeting is a management tool used to evaluate the relative importance of contaminant sources to wetlands, by comparing contaminant loads. Environmental management of the Yellagonga …

Dynamics And Fate Of Blue Carbon In A Mangrove–Seagrass Seascape: Influence Of Landscape Configuration And Land-Use Change, Maria E. Asplund, Martin Dahl, Rashid O. Ismail, Ariane Arias-Ortiz, Diana Deyanova, João N. Franco, Linus Hammar, Arielle I. Hoamby, Hans W. Linderholm, Liberatus D. Lyimo, Diana Perry, Lina M. Rasmusson, Samantha N. Ridgway, Gloria Salgado Gispert, Stéphanie D’Agata, Leah Glass, Jamal Angelot Mahafina, Volanirina Ramahery, Pere Masque, Mats Björk, Martin Gullström

Research outputs 2014 to 2021

Context: Seagrass meadows act as efficient natural carbon sinks by sequestering atmospheric CO and through trapping of allochthonous organic material, thereby preserving organic carbon (C ) in their sediments. Less understood is the influence of landscape configuration and transformation (land-use change) on carbon sequestration dynamics in coastal seascapes across the land–sea interface. Objectives: We explored the influence of landscape configuration and degradation of adjacent mangroves on the dynamics and fate of C in seagrass habitats. Methods: Through predictive modelling, we assessed sedimentary C content, stocks and source composition in multiple seascapes (km-wide buffer zones) dominated by different seagrass communities in …

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 …

Association Between Fruit And Vegetable Intakes And Mental Health In The Australian Diabetes Obesity And Lifestyle Cohort, Joanna Rees, Simone Radavelli-Bagatini, Johnny Lo, Jonathan M. Hodgson, Claus T. Christophersen, Robin M. Daly, Dianna J. Magliano, Jonathan E. Shaw, Marc Sim, Catherine P. Bondonno, Lauren C. Blekkenhorst, Joanne M. Dickson, Joshua R. Lewis, Amanda Devine

Research outputs 2014 to 2021

Increasing prevalence of mental health disorders within the Australian population is a serious public health issue. Adequate intake of fruits and vegetables (FV), dietary fibre (DF) and resistant starch (RS) is associated with better mental and physical health. Few longitudinal studies exist exploring the temporal relationship. Using a validated food frequency questionnaire, we examined baseline FV intakes of 5845 Australian adults from the AusDiab study and estimated food group-derived DF and RS using data from the literature. Perceived mental health was assessed at baseline and 5 year follow up using SF-36 mental component summary scores (MCS). We conducted baseline cross-sectional …

A Secured Message Transmission Protocol For Vehicular Ad Hoc Networks, A. F. M. Suaib Akhter, A. F. M. Shahen Shah, Mohiuddin Ahmed, Nour Moustafa, Unal Çavuşoğlu, Ahmet Zengin

Research outputs 2014 to 2021

Vehicular Ad hoc Networks (VANETs) become a very crucial addition in the Intelligent Transportation System (ITS). It is challenging for a VANET system to provide security services and parallelly maintain high throughput by utilizing limited resources. To overcome these challenges, we propose a blockchain-based Secured Cluster-based MAC (SCB-MAC) protocol. The nearby vehicles heading towards the same direction will form a cluster and each of the clusters has its blockchain to store and distribute the safety messages. The message which contains emergency information and requires Strict Delay Requirement (SDR) for transmission are called safety messages (SM). Cluster Members (CMs) sign SMs …

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), …

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 …

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 …

Digital Forensic Readiness In Operational Cloud Leveraging Iso/Iec 27043 Guidelines On Security Monitoring, Sheunesu Makura, H. S. Venter, Victor R. Kebande, Nickson M. Karie, Richard A. Ikuesan, Sadi Alawadi

Research outputs 2014 to 2021

An increase in the use of cloud computing technologies by organizations has led to cybercriminals targeting cloud environments to orchestrate malicious attacks. Conversely, this has led to the need for proactive approaches through the use of digital forensic readiness (DFR). Existing studies have attempted to develop proactive prototypes using diverse agent-based solutions that are capable of extracting a forensically sound potential digital evidence. As a way to address this limitation and further evaluate the degree of PDE relevance in an operational platform, this study sought to develop a prototype in an operational cloud environment to achieve DFR in the cloud. …

Whisper: A Location Privacy-Preserving Scheme Using Transmission Range Changing For Internet Of Vehicles, Messaoud Babaghayou, Nabila Labraoui, Ado A. Abba Ari, Mohamed A. Ferrag, Leandros Maglaras, Helge Janicke

Research outputs 2014 to 2021

Internet of Vehicles (IoV) has the potential to enhance road-safety with environment sensing features provided by embedded devices and sensors. This benignant feature also raises privacy issues as vehicles announce their fine-grained whereabouts mainly for safety requirements, adversaries can leverage this to track and identify users. Various privacy-preserving schemes have been designed and evaluated, for example, mix-zone, encryption, group forming, and silent-period-based techniques. However, they all suffer inherent limitations. In this paper, we review these limitations and propose WHISPER, a safety-aware location privacy-preserving scheme that adjusts the transmission range of vehicles in order to prevent continuous location monitoring. We detail …

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 …

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 …