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Full-Text Articles in Physical Sciences and Mathematics

Occurrence Of Microplastics In The Asian Freshwater Environments: A Review, Farah Akmal Idrus, Noradriena Mohd Fadhli, Mohd Nasarudin Harith Jan 2022

Occurrence Of Microplastics In The Asian Freshwater Environments: A Review, Farah Akmal Idrus, Noradriena Mohd Fadhli, Mohd Nasarudin Harith

Applied Environmental Research

Microplastics pollution has become a worldwide common problem. Despite the growing numbers in researches regarding the microplastics, the understanding of microplastics in the freshwater environment are still less. This paper overviews the present knowledge and findings on the occurrence of microplastics in water and sediment of the freshwater environments in Asia. The review also covers the size distribution, polymers, morphological characteristics and sources of microplastics to the freshwater systems. Perspective of the adsorption of heavy metals on the microplastics to the freshwater systems are also discussed in this review.

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Sustainable Energy Transition In Thailand: Drivers, Barriers And Challenges Of Waste-To-Energy At Krabi Province, Chariya Senpong, Dawan Wiwattanadate Jan 2022

Sustainable Energy Transition In Thailand: Drivers, Barriers And Challenges Of Waste-To-Energy At Krabi Province, Chariya Senpong, Dawan Wiwattanadate

Applied Environmental Research

Waste-to-Energy (WtE) has been considered as an option to eliminate Krabi’s problems of municipal solid waste (MSW) management. A survey on WtE potential as well as key drivers, barriers, and challenges to overcome the barriers was conducted in this study. The study found high WtE potential due to huge amount of many years accumulated MSW in couple with the increasing trend of new daily waste generation. Meanwhile, Krabi is an island having land limitation for landfill. The urgent need to eliminate the huge amount of MSW has become a key driver for WtE implementation. One more key driver of WtE …

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Biochar From Empty Date Fruit Bunch As An Adsorbent To Remove Eriochrome Black T And Methylene Blue From Aqueous Solution, Houari Bella, Hayet Bendaikha Jan 2022

Biochar From Empty Date Fruit Bunch As An Adsorbent To Remove Eriochrome Black T And Methylene Blue From Aqueous Solution, Houari Bella, Hayet Bendaikha

Applied Environmental Research

Date fruit has a significant role in Sahara countries' economies. In this study, a bunch of empty dates waste was used to produce biochar, which will be used to adsorb Eriochrome black T (EBT) and methylene blue (MB) dyes from aqueous solution. The dates bunch was washed, dried, and ground into small particles. Then it was heated in a muffle furnace at 850 °C. The biochar from empty date bunches (BEDB) characteristics before and after adsorption was determined by using scanning electron microscopy (SEM) and Fourier transform infrared (FTIR) spectroscopy. The experiment has used different parameters notably initial concentration (25 …

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Ecological And Human Health Risk Assessment Of Heavy Metals By Consuming The Aquatic Plant Species Near An Electronic Waste Open Dumpsite In Thailand, Thitima Parkpoom, Somsak Intamat, Uraiwan Phoonaploy, Lamyai Neeratanaphan Jan 2022

Ecological And Human Health Risk Assessment Of Heavy Metals By Consuming The Aquatic Plant Species Near An Electronic Waste Open Dumpsite In Thailand, Thitima Parkpoom, Somsak Intamat, Uraiwan Phoonaploy, Lamyai Neeratanaphan

Applied Environmental Research

Heavy metals from electronic waste (e-waste) accumulate in the environment and can affect human health. The purpose of this study was to determine As, Cd, Cr and Pb concentrations in water, sediment and three species of edible aquatic plants (Ottelia alismoides, Ipomoea aquatic and Marsilea crenata) near an e-waste open dumpsite. Samples were collected from six sampling points surrounding an e-waste open dumpsite and heavy metal concentrations were analyzed by inductively coupled plasma optical emission spectrometry (ICP-OES). Bioaccumulation factors (BAFs), estimated daily intake (EDI), hazard quotient (HQ), hazard index (HI) and carcinogenic risk (CR) were evaluated in …

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Spatial Distribution Of Bioavailable Metal Concentrations And Total Metal Concentration-Depth Relationship Along The Sediment Profile Within Phuket Bay, Pensiri Akkajit, Danai Tipmanee, Kaimook Jaileak Jan 2022

Spatial Distribution Of Bioavailable Metal Concentrations And Total Metal Concentration-Depth Relationship Along The Sediment Profile Within Phuket Bay, Pensiri Akkajit, Danai Tipmanee, Kaimook Jaileak

Applied Environmental Research

Heavy metals in coastal sediments can adversely affect human health and the environment. The distribution and metal bioavailability of Pb and Zn in 21 sediment samples collected from Phuket Bay, Phuket, Thailand using the first-two steps of sequential extraction proposed by the Standards, Measurements and Testing programme (known as BCR) was determined. The results showed that Pb formed weak complexes contributing up to 11.2% to 33% of its total concentration (1.7 to 7.5 mg kg-1) in the first fraction (BCR1), while Zn in the BCR1 fraction ranged from 4.9% to 9.9%. The results suggest that Pb could easily enter the …

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Assessing Vegetation Cover Change Using Remote Sensing: Case Study At Binh Duong Province, Vietnam, Nguyen Thi Huyen, Le Hoang Tu, Le Truong Ngoc Han, Vuong Thi Thuy, Dang Nguyen Dong Phuong, Nguyen Kim Loi Jan 2022

Assessing Vegetation Cover Change Using Remote Sensing: Case Study At Binh Duong Province, Vietnam, Nguyen Thi Huyen, Le Hoang Tu, Le Truong Ngoc Han, Vuong Thi Thuy, Dang Nguyen Dong Phuong, Nguyen Kim Loi

Applied Environmental Research

This study aims to present the application of remote sensing in monitoring vegetation change in Binh Duong Province, Vietnam. The study used Landsat 5 images in the year 2010 and Landsat 8 images in the years 2015 and 2020 to investigate the area of vegetation. The maximum likelihood classification method (MLC) was used to classify land cover and an accuracy matrix was computed to validate the classification results. The references data were collected to support classification and accuracy assessment processes including land use maps in 2010, 2015, and 2020. In addition, collected field points and UAV (unmanned aerial vehicle) in …

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Performance Of Porous Substrates For Domestic Wastewater Treatment Under Prolonged Hydraulic Retention Time, Pakawat Janyasupab, Arunothai Jampeetong Jan 2022

Performance Of Porous Substrates For Domestic Wastewater Treatment Under Prolonged Hydraulic Retention Time, Pakawat Janyasupab, Arunothai Jampeetong

Applied Environmental Research

Physicochemical characteristics of porous substrates (longan biochar, corn biochar, and pumice) including specific surface area (SSA), pore volume (Vp), and cation exchange capacity (CEC) were determined. Longan biochar had the highest SSA, Vp, and CEC, followed by corn biochar and pumice. Then, columns filled with each of these 3 substrates together with gravel as a control treatment, were evaluated to compare wastewater treatment efficiency under different hydraulic retention times (HRTs). Each system had been acclimatized with wastewater for 8 weeks. Then, influent and effluent were analyzed at 1, 3, 5, and 7 day intervals. Water analysis revealed that biochar-based systems …

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Advances In Chemotactic And Non-Chemotactic Bioremediation Of Water: A Comprehensive Review, Sheetal Pardeshi, Prafulla Shede Jan 2022

Advances In Chemotactic And Non-Chemotactic Bioremediation Of Water: A Comprehensive Review, Sheetal Pardeshi, Prafulla Shede

Applied Environmental Research

Pollution has reached to a critical threshold affecting the climate and diversity of the planet Earth. All global authorities have included pollution control in their agenda for near future. Most of the environmental research nowadays is focused on removing waste generated by anthropogenic activities, may it be solid, liquid or gaseous waste. Bioremediation is believed to be the most eco-friendly approach for reducing or removing pollutants contaminating different matrices of the environment. There are various methods covered under the umbrella term of bioremediation. Chemotaxis-mediated bioremediation attracted attention of several research groups since early decade of twenty first century due to …

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Soil Contamination And Risk Assessments On Selected Dumpsites Within The Basement Complex And Sedimentary Formations Of Ogun State, South-Western Nigeria, Akintayo O. Ojo, Oluwaseun T. Olurin, Oluseyi O. Adeleke Jan 2022

Soil Contamination And Risk Assessments On Selected Dumpsites Within The Basement Complex And Sedimentary Formations Of Ogun State, South-Western Nigeria, Akintayo O. Ojo, Oluwaseun T. Olurin, Oluseyi O. Adeleke

Applied Environmental Research

The concentrations of inorganic elements in soils of Saje, Ita-Oshin, Premier, and Oke-Diya dumpsites were determined using an X-Ray Fluorescence spectrometer to assess the soil quality through chronological changes with depths. A soil core sampler collects 56 samples at 20, 40, 60, and 80 cm depths. Saje showed high mean concentrations of Ca, K, Fe, Rb, and Ti at all depths, while Oke-Diya revealed high mean concentrations of Ca, K, Fe, Rb, Ti, Mn, Zn, V, Cr, and Ni at all depths. These concentrations were in a closed range suggesting a build-up of elements in the soil profiles. Oke-Diya had …

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Amm Problem #12279, Brad Isaacson Jan 2022

Amm Problem #12279, Brad Isaacson

Publications and Research

No abstract provided.

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Groundwater Potential Model Using Statistics And Hybrid Machine Learning Approaches, Ngoc Thanh Nguyen Jan 2022

Groundwater Potential Model Using Statistics And Hybrid Machine Learning Approaches, Ngoc Thanh Nguyen

Chulalongkorn University Theses and Dissertations (Chula ETD)

The present study was conducted to delineate the groundwater potential in Kanchanaburi Province, Thailand based on groundwater yield, groundwater contamination risk, and groundwater quality. In this study, an ensemble model was created by combining Analytical Hierarchy Process, Frequency Ratio, and Random Forest to evaluate the spatial distribution map of the groundwater resources. Additionally, a new hybrid approach was developed based on maximum entropy and analytical hierarchy process to delineate the Ni contamination risk in groundwater. Finally, four machine-learning models, including Random Forest - Cross validation, Random Forest – Bootstrap, Artificial Neural Network - Cross validation, and Artificial Neural Network - …

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A Comparison Of Imbalanced Data Handling Methods For Pre-Trained Model In Multi-Label Classification Of Stack Overflow, Arisa Umparat Jan 2022

A Comparison Of Imbalanced Data Handling Methods For Pre-Trained Model In Multi-Label Classification Of Stack Overflow, Arisa Umparat

Chulalongkorn University Theses and Dissertations (Chula ETD)

Tag classification is essential in Stack Overflow. Instead of combining through pages or replies of irrelevant information, users can easily and quickly pinpoint relevant posts and answers using tags. Since User-submitted posts can have multiple tags, classifying tags in Stack Overflow can be challenging. This results in an imbalance problem between labels in the whole labelset. Pretrained deep learning models with small datasets can improve tag classification accuracy. Common multi-label resampling techniques with machine learning classifiers can also fix this issue. Still, few studies have explored which resampling technique can improve the performance of pre-trained deep models for predicting tags. …

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An Application Of Reinforcement Learning To Credit Scoring Based On The Logistic Bandit Framework, Kantapong Visantavarakul Jan 2022

An Application Of Reinforcement Learning To Credit Scoring Based On The Logistic Bandit Framework, Kantapong Visantavarakul

Chulalongkorn University Theses and Dissertations (Chula ETD)

This study applies reinforcement learning to credit scoring by using the logistic bandit framework. The credit scoring and the credit underwriting are modeled into a single sequential decision problem where the credit underwriter takes a sequence of actions over an indefinite number of time steps. The traditional credit scoring approach considers the model construction separately from the underwriting process. This approach is identified as a greedy algorithm in the reinforcement learning literature, which is commonly believed to be inferior to an efficient reinforcement learning approach such as Thompson sampling. This is true under the simple setting, i.e., granting credit to …

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Multi-Output Learning For Predicting Evaluation And Reopening Of Github Pull Requests On Open-Source Projects, Peerachai Banyongrakkul Jan 2022

Multi-Output Learning For Predicting Evaluation And Reopening Of Github Pull Requests On Open-Source Projects, Peerachai Banyongrakkul

Chulalongkorn University Theses and Dissertations (Chula ETD)

GitHub's pull-based development model is widely used by software development teams to manage software complexity. Contributors create pull requests for merging changes into the main codebase, and integrators review these requests to maintain quality and stability. However, a high volume of pull requests can overburden integrators, causing feedback delays. Previous studies have used machine learning and statistical techniques with tabular data as features, but these may lose meaningful information. Additionally, acceptance and latency may not be sufficient for the pull request evaluation. Moreover, reopened pull requests can add maintenance costs and burden already-busy developers. This thesis proposes a novel multi-output …

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Formal Models For Consent Management In Healthcare Software System Development, Neda Peyrone Jan 2022

Formal Models For Consent Management In Healthcare Software System Development, Neda Peyrone

Chulalongkorn University Theses and Dissertations (Chula ETD)

In the era of data-driven opportunities, many businesses are missing the data-privacy challenge, which leads to risks in safeguarding their customers’ data. To empower individuals (data subjects) to control their data, the General Data Protection Regulation (GDPR) mandated businesses or organizations (data controllers) to protect individuals’ data (personal data) within data protection law. Nevertheless, many businesses still struggle to enhance and develop their software systems to comply with the GDPR because it is difficult to interpret and apply to software development practices. Besides, the processing of personal data begins when the data subject provides explicit consent to the data controller, …

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Deep Reinforcement Learning For Electricity Energy Trading, Manassakan Sanayha Jan 2022

Deep Reinforcement Learning For Electricity Energy Trading, Manassakan Sanayha

Chulalongkorn University Theses and Dissertations (Chula ETD)

The deregulation and liberalization of the energy market in the 1990s prompted short-term electricity trading, allowing energy markets to produce net output over a range of time periods as a result of this decentralized system, most commonly minutes to days ahead of time. The energy industry urgently requires a system that has undergone substantial modernization in place to handle a variety of issues, including the current climate, renewable resources, and the energy framework. In this dissertation, we investigate a deep reinforcement learning framework for both wholesale and local energy trading, which probes the challenge of RL to optimize the real-world …

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Recasnet: Reducing Mismatch Within The Two-Stage Mitosis Detection Framework, Chawan Piansaddhayanon Jan 2022

Recasnet: Reducing Mismatch Within The Two-Stage Mitosis Detection Framework, Chawan Piansaddhayanon

Chulalongkorn University Theses and Dissertations (Chula ETD)

Mitotic count (MC) is an important histological parameter for cancer diagnosis and grading, but the manual process to obtain this metric is tedious and not fully reproducible across different pathologists. To mitigate this problem, several deep learning models have been utilized to speed up the process. Typically, the problem is formulated as a two-stage deep learning pipeline: the detection stage for proposing the potential candidates for mitotic cells and the classification stage for refining prediction confidences from the former stage. However, this paradigm can lead to inconsistencies in the classification stage due to the poor prediction quality of the detection …

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Leverage Graph Neural Network For Molecular Properties Prediction, Kamol Punnachaiya Jan 2022

Leverage Graph Neural Network For Molecular Properties Prediction, Kamol Punnachaiya

Chulalongkorn University Theses and Dissertations (Chula ETD)

During the age of deep learning technologies, which have exhibited significant potential in reducing costs and expediting medical development, predicting molecular properties has become a prevalent task that capitalizes on the capabilities of deep learning. This thesis proposed a multimodal Graph Neural Network (GNN) model that utilizes the topology information obtained from molecular graphs through a baseline GNN, facilitating precise property predictions. The thesis improves the baseline CMPNN model by exploring various methods to address potential missing gaps. These methods include incorporating the multimodal module, such as a Bidirectional LSTM module capable of processing text sequences in SMILES format or …

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Indoor And Outdoor Localization In An Unknown Environment With Window Detection For Unmanned Aerial Vehicles, Laphonchai Jirachuphun Jan 2022

Indoor And Outdoor Localization In An Unknown Environment With Window Detection For Unmanned Aerial Vehicles, Laphonchai Jirachuphun

Chulalongkorn University Theses and Dissertations (Chula ETD)

In this thesis, we design and build a system for unmanned aerial vehicles (UAVs). We combine, adjust and improve existing open-source algorithms for localization tasks in an indoor and outdoor environment with window detection for transitioning between the two environments. For outdoor localization, we mainly use GPS, while for indoor localization, we use Extended Kalman Filter (EKF). However, for the transitioning area where the GPS is unreliable and the environment has too few structures for EKf, we use an opening such as a window or a door for localization with a stereo camera. We compare our technique with GPS only, …

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Surface-Enhanced Raman Scattering Technique For Nanoplastics Detection, Boonphop Chaisrikhwun Jan 2022

Surface-Enhanced Raman Scattering Technique For Nanoplastics Detection, Boonphop Chaisrikhwun

Chulalongkorn University Theses and Dissertations (Chula ETD)

The size-dependent effect of nanoplastics (NPLs) restricts the quantification of NPLs by surface-enhanced Raman scattering (SERS) technique. In this study, we successfully established an innovative preparation method to eliminate this effect. This developed SERS method allowed us to quantify 100-, 300-, 600-, and 800-nm polystyrene nanospheres (PSNSs) in diverse aqueous conditions at a low concentration. The SERS substrate was easily fabricated and used as NPLs signal enhancement with sputtering gold particles onto a glass cover slide. By preconcentrating and dissolving PSNSs in toluene, SERS technique can be successfully quantify NPLs at extremely low concentrations with a limit of detection (LOD) …

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Enzyme-Free Hydrogen Peroxide Sensor From Dual-Shaped Plasmonic Silver Nanoparticles, Charles Oliver Avenido Jan 2022

Enzyme-Free Hydrogen Peroxide Sensor From Dual-Shaped Plasmonic Silver Nanoparticles, Charles Oliver Avenido

Chulalongkorn University Theses and Dissertations (Chula ETD)

A novel growth-based strategy for the determination of hydrogen peroxide has been developed using a mixture of silver nanospheres (AgNSs) and citrate-capped silver nanoprisms (AgNPrs). The unique ability of hydrogen peroxide to oxidize silver nanoparticles and reduce silver metal consequently was exploited to produce a highly sensitive and selective sensor (AgNSs/NPrs). Citrate-capping of the AgNPrs only allows the lateral growth that resulted in a red shift and intensity enhancement of the in-plane dipole plasmon resonance (IPDPR) band. Consequently, distinct hues from yellow, orange, red, purple to blue were produced from the diluted sensors. Ratiometric analysis was employed to quantify H2O2 …

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Theoretical Study Of Lithium Absorption In Silicon Nanostructures For Application As Anodes In Lithium-Ion Batteries, Fadjar Mulya Jan 2022

Theoretical Study Of Lithium Absorption In Silicon Nanostructures For Application As Anodes In Lithium-Ion Batteries, Fadjar Mulya

Chulalongkorn University Theses and Dissertations (Chula ETD)

The absorption and adsorption of lithium in silicon nanostructures: silicon quantum dots (SiQDs), silicon nanowires (SiNWs) and silicon nanopores (SiNPs) were studied using density functional theory (DFT) with M06-2X hybrid functional and 6-31G+(d) basis set. The tetrahedral sites, both Tdinner and Tdsurface, are the most preferred sites for lithiation due to their favorable binding energy profiles. For single lithium absorption and adsorption, SiQDs exhibit a binding energy of 1 eV, SiNWs demonstrate a binding energy of 1.28 eV, and SiNPs display a binding energy of 0.73 eV. Similarly, multiple lithium adsorptions yield binding energies of 1.12 eV for SiQDs, 1.21 …

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Dna-Templated Synthesis Of Cationic Styryl Dyes, Kriangsak Faikhruea Jan 2022

Dna-Templated Synthesis Of Cationic Styryl Dyes, Kriangsak Faikhruea

Chulalongkorn University Theses and Dissertations (Chula ETD)

Styryl dye is a class of pi-conjugated dye that shows several desirable optical properties, such as high photostability, solvatochromic characteristics, and high fluorescence quantum yields. Due to the responsiveness to the binding with the target biomolecules such as nucleic acids, some of these dyes have been widely employed for biomolecular detection and cellular imaging. These dyes are typically synthesized via an aldol-type reaction between a methyl heterocycle and an aromatic aldehyde in the presence of acid or base as a catalyst. However, the conventional method of synthesizing these dyes is inefficient, time-consuming, and involves the use of excessive chemicals, as …

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A One-Dimensional Field Dislocation Mechanics Model Using Discontinuous Galerkin Method, Ja'nya Breeden, Dow Drake, Jay Gopalakrishnan, Saurabh Puri Jan 2022

A One-Dimensional Field Dislocation Mechanics Model Using Discontinuous Galerkin Method, Ja'nya Breeden, Dow Drake, Jay Gopalakrishnan, Saurabh Puri

Mathematics and Statistics Faculty Publications and Presentations

A numerical solution strategy for a one-dimensional field dislocation mechanics (FDM) model using the Discontinuous Galerkin (DG) method is developed. The FDM model is capable of simulating the dynamics of discrete, nonsingular dislocations using a partial differential equation involving a conservation law for the Burgers vector content with constitutive input for nucleation and velocity. Modeling of individual dislocation lines with an equilibrium compact core structure in the context of this continuum elastoplastic framework requires a non-convex stored energy density. Permanent deformation and stress redistribution caused by the dissipative transport of dislocations is modeled using thermodynamics-based constitutive laws. A DG method …

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Periodic Points Of Polynomials Over Finite Fields, Derek Garton Jan 2022

Periodic Points Of Polynomials Over Finite Fields, Derek Garton

Mathematics and Statistics Faculty Publications and Presentations

Fix an odd prime p. If r is a positive integer and f is a polynomial with coefficients in Fpr, let Pp,r⁡(f) be the proportion of P1⁢(Fpr) that is periodic with respect to f. We show that as r increases, the expected value of Pp,r⁡(f), as f ranges over quadratic polynomials, is less than 22/(log⁡log⁡pr). This result follows from a uniformity theorem on specializations of dynamical systems of rational functions over residually finite Dedekind domains. The specialization theorem generalizes previous work by Juul et al. that holds for rings of integers of number fields. Moreover, under stronger hypotheses, we effectivize …

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Power, Passion And Politics: A Grounded Theory Study Of Academic Experiences In Policy Development And Implementation In Higher Education, Marie Brennan Jan 2022

Power, Passion And Politics: A Grounded Theory Study Of Academic Experiences In Policy Development And Implementation In Higher Education, Marie Brennan

Doctoral

This research study is designed to investigate the lived experiences and perspectives of the academic community on policy development in Irish higher education. A review of the current policy landscape in Ireland and Europe and in particular empirical studies concerning policy implementation provided the focus of the study. The initial study focused on contemporary literature on policy development practices affected by globalisation and subsequently the issues at a national level. Where the gaps in knowledge were identified were in terms of policy implementation at the local level and where the study is aligned. The participants in the study are academics …

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Identification Of Nanotechnology Skill Shortages In Ireland’S Agri-Food Sector: Towards The Safe, Innovative And Sustainable Development Of Nano-Food Technology, Eileen Mccarron Jan 2022

Identification Of Nanotechnology Skill Shortages In Ireland’S Agri-Food Sector: Towards The Safe, Innovative And Sustainable Development Of Nano-Food Technology, Eileen Mccarron

Doctoral

The purpose of this research was to assess the nanotechnology skill and capacity shortages in Irelands Agri-food sector. In 2008 the Food Safety Authority of Ireland (FSAI) published its statement on ‘The Relevance for Food Safety of Applications of Nanotechnology in the Food and Feed Industries’. The importance of the food sector to the Irish economy was clearly emphasised by the FSAI’s statement. The report identified the urgent need for focused research programs into the potential of nanotechnology in the agri-food sector and it highlighted the need for a multi-organisation approach between state agencies, industry and academia to ensure safe …

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Trapped Under Ice: Spatial And Seasonal Dynamics Of Dissolved Organic Matter Composition In Tundra Lakes, Martin R. Kurek, Karen E. Frey, François Guillemette, David C. Podgorski, Amy Townsend-Small, Christopher D. Arp, Anne M. Kellerman, Robert G.M. Spencer Jan 2022

Trapped Under Ice: Spatial And Seasonal Dynamics Of Dissolved Organic Matter Composition In Tundra Lakes, Martin R. Kurek, Karen E. Frey, François Guillemette, David C. Podgorski, Amy Townsend-Small, Christopher D. Arp, Anne M. Kellerman, Robert G.M. Spencer

Geography

Arctic lakes store, modify, and transport large quantities of carbon from terrestrial environments to the atmosphere; however, the spatial and temporal relationships between quantity and composition of dissolved organic matter (DOM) have not been well characterized across broad arctic regions. Moreover, most arctic lake DOM compositions have been examined during the ice-free summer, whereas DOM cycling between the ice-covered winter months and summer have not been addressed. To resolve these spatial and seasonal uncertainties in DOM cycling, we sampled a series of arctic lakes from the North Slope of Alaska across a latitudinal gradient in the winter and summer over …

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Secure Storage Model For Digital Forensic Readiness, Avinash Singh, Richard Adeyemi Ikuesan, Hein Venter Jan 2022

Secure Storage Model For Digital Forensic Readiness, Avinash Singh, Richard Adeyemi Ikuesan, Hein Venter

All Works

Securing digital evidence is a key factor that contributes to evidence admissibility during digital forensic investigations, particularly in establishing the chain of custody of digital evidence. However, not enough is done to ensure that the environment and access to the evidence are secure. Attackers can go to extreme lengths to cover up their tracks, which is a serious concern to digital forensics – particularly digital forensic readiness. If an attacker gains access to the location where evidence is stored, they could easily alter the evidence (if not remove it altogether). Even though integrity checks can be performed to ensure that …

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Loguad: Log Unsupervised Anomaly Detection Based On Word2vec, Jin Wang, Changqing Zhao, Shiming He, Yu Gu, Osama Alfarraj, Ahed Abugabah Jan 2022

Loguad: Log Unsupervised Anomaly Detection Based On Word2vec, Jin Wang, Changqing Zhao, Shiming He, Yu Gu, Osama Alfarraj, Ahed Abugabah

All Works

System logs record detailed information about system operation and are important for analyzing the system's operational status and performance. Rapid and accurate detection of system anomalies is of great significance to ensure system stability. However, large-scale distributed systems are becoming more and more complex, and the number of system logs gradually increases, which brings challenges to analyze system logs. Some recent studies show that logs can be unstable due to the evolution of log statements and noise introduced by log collection and parsing. Moreover, deep learning-based detection methods take a long time to train models. Therefore, to reduce the computational …

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