5,639 research outputs found
Bio-inspired optimization in integrated river basin management
Water resources worldwide are facing severe challenges in terms of quality and quantity. It is essential to conserve, manage, and optimize water resources and their quality through integrated water resources management (IWRM). IWRM is an interdisciplinary field that works on multiple levels to maximize the socio-economic and ecological benefits of water resources. Since this is directly influenced by the river’s ecological health, the point of interest should start at the basin-level. The main objective of this study is to evaluate the application of bio-inspired optimization techniques in integrated river basin management (IRBM). This study demonstrates the application of versatile, flexible and yet simple metaheuristic bio-inspired algorithms in IRBM.
In a novel approach, bio-inspired optimization algorithms Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) are used to spatially distribute mitigation measures within a basin to reduce long-term annual mean total nitrogen (TN) concentration at the outlet of the basin. The Upper Fuhse river basin developed in the hydrological model, Hydrological Predictions for the Environment (HYPE), is used as a case study. ACO and PSO are coupled with the HYPE model to distribute a set of measures and compute the resulting TN reduction. The algorithms spatially distribute nine crop and subbasin-level mitigation measures under four categories. Both algorithms can successfully yield a discrete combination of measures to reduce long-term annual mean TN concentration. They achieved an 18.65% reduction, and their performance was on par with each other. This study has established the applicability of these bio-inspired optimization algorithms in successfully distributing the TN mitigation measures within the river basin.
Stakeholder involvement is a crucial aspect of IRBM. It ensures that researchers and policymakers are aware of the ground reality through large amounts of information collected from the stakeholder. Including stakeholders in policy planning and decision-making legitimizes the decisions and eases their implementation. Therefore, a socio-hydrological framework is developed and tested in the Larqui river basin, Chile, based on a field survey to explore the conditions under which the farmers would implement or extend the width of vegetative filter strips (VFS) to prevent soil erosion. The framework consists of a behavioral, social model (extended Theory of Planned Behavior, TPB) and an agent-based model (developed in NetLogo) coupled with the results from the vegetative filter model (Vegetative Filter Strip Modeling System, VFSMOD-W). The results showed that the ABM corroborates with the survey results and the farmers are willing to extend the width of VFS as long as their utility stays positive. This framework can be used to develop tailor-made policies for river basins based on the conditions of the river basins and the stakeholders' requirements to motivate them to adopt sustainable practices.
It is vital to assess whether the proposed management plans achieve the expected results for the river basin and if the stakeholders will accept and implement them. The assessment via simulation tools ensures effective implementation and realization of the target stipulated by the decision-makers. In this regard, this dissertation introduces the application of bio-inspired optimization techniques in the field of IRBM. The successful discrete combinatorial optimization in terms of the spatial distribution of mitigation measures by ACO and PSO and the novel socio-hydrological framework using ABM prove the forte and diverse applicability of bio-inspired optimization algorithms
PARAMETRIC APPROACHES TO BALANCE STORMWATER MANAGEMENT AND HUMAN WELLBEING WITHIN URBAN GREEN SPACE
Through rapid urbanisation, urban green spaces (UGS) have become increasingly limited and valuable in high-density urban environments. However, meeting the diverse requirements of sustainable urban development often leads to conflicts in UGS usage. For example, the presence of stormwater treatment facilities may hinder residents' access to adjacent UGS.
Traditional approaches to UGS design typically focus on separate evaluations of human wellbeing and stormwater management. However, using questionnaires, interviews, and surveys for human wellbeing evaluation can be challenging to generalise across different projects and cities. Additionally, professional hydrological models used for stormwater management require extensive knowledge of hydrology and struggle to integrate their 2D evaluation methods with 3D models.
To address these challenges, this thesis proposes a novel framework to integrate the two types of analysis within a system for balancing the needs of human wellbeing and stormwater management in UGS design. The framework incorporates criteria and parameters for evaluating human wellbeing and stormwater management in a 3D model and introduces an approach to compare these two needs in terms of UGS area and suitable location. The contributions of this thesis to multi-objective UGS design are as follows: (1) defining human wellbeing evaluation through Accessibility and Usability assessment, which considers factors such as connectivity, walking distance, space enclosure, and space availability; (2) simplifying stormwater evaluation using particle systems and design curves to streamline complex hydrological models; (3) integrating the two evaluations by comparing their quantified requirements for UGS area and location; and (4) incorporating parameters to provide flexibility and accommodate various design scenarios and objectives.
The advantages of this evaluation framework are demonstrated through two case studies: (1) the human wellbeing analysis based on spatial parameters in the framework shows sensitivity to site variations, including UGS quantity and distribution, population density, terrain, road context, height of void space, and more; (2) the simplified stormwater analysis effectively captures site variations represented by UGS quantity and distribution, building distribution, as well as terrain, providing recommendations for each UGS with different types and sizes of stormwater facilities. (3) With the features of spatial parameter evaluation, the framework is feasible to adjust relevant thresholds and include more parameters to respond to specific project needs. (4) By quantifying the two different requirements for UGS and comparing them, any UGS with high usage conflicts can be easily identified. By evaluating all proposed criteria for UGSs in the 3D model, designers can conveniently observe simulation and adjust design scenarios to address identified usage conflicts. Thus, the proposed evaluation framework in this thesis would be valuable in effectively supporting further multi-objective UGS design
2023-2024 Boise State University Undergraduate Catalog
This catalog is primarily for and directed at students. However, it serves many audiences, such as high school counselors, academic advisors, and the public. In this catalog you will find an overview of Boise State University and information on admission, registration, grades, tuition and fees, financial aid, housing, student services, and other important policies and procedures. However, most of this catalog is devoted to describing the various programs and courses offered at Boise State
Presentation, Technology, and Content – Studies on Consumer Behaviour in Journalism
The goal of this thesis is to extend the understanding of the effects the presentation and visuality of journalism can have on users and consumers. Further, this thesis makes a case that a focus on the presentation and visuality of journalism is a possibility for audience orientation without compromising journalistic quality. The visual presentation of journalism has become very important because of technological developments that make the reproduction of design, pictures, layout and any other relevant presentation modes so much easier. While practitioners are handling this on a daily basis, management researchers are just starting to empirically investigate related phenomena, especially in the context of journalism.
Along five empirical studies conducted in the journalism field, this thesis establishes links between the presentation, technology and content of journalism and consumer behaviour. It further identifies frameworks to approach the presentation of journalism and theoretically explains how the presentation can provide a possibility for audience orientation without compromising content. Thereupon, this research derives recommendations for theory and practitioners in order to uphold the business viability of news production
Tiny Machine Learning Environment: Enabling Intelligence on Constrained Devices
Running machine learning algorithms (ML) on constrained devices at the extreme edge of the network is problematic due to the computational overhead of ML algorithms, available resources on the embedded platform, and application budget (i.e., real-time requirements, power constraints, etc.). This required the development of specific solutions and development tools for what is now referred to as TinyML. In this dissertation, we focus on improving the deployment and performance of TinyML applications, taking into consideration the aforementioned challenges, especially memory requirements. This dissertation contributed to the construction of the Edge Learning Machine environment (ELM), a platform-independent open source framework that provides three main TinyML services, namely shallow ML, self-supervised ML, and binary deep learning on constrained devices. In this context, this work includes the following steps, which are reflected in the thesis structure. First, we present the performance analysis of state of the art shallow ML algorithms including dense neural networks, implemented on mainstream microcontrollers. The comprehensive analysis in terms of algorithms, hardware platforms, datasets, pre-processing techniques, and configurations shows similar performance results compared to a desktop machine and highlights the impact of these factors on overall performance. Second, despite the assumption that TinyML only permits models inference provided by the scarcity of resources, we have gone a step further and enabled self-supervised on-device training on microcontrollers and tiny IoT devices by developing the Autonomous Edge Pipeline (AEP) system. AEP achieves comparable accuracy compared to the typical TinyML paradigm, i.e., models trained on resource-abundant devices and then deployed on microcontrollers. Next, we present the development of a memory allocation strategy for convolutional neural networks (CNNs) layers, that optimizes memory requirements. This approach reduces the memory footprint without affecting accuracy nor latency. Moreover, e-skin systems share the main requirements of the TinyML fields: enabling intelligence with low memory, low power consumption, and low latency. Therefore, we designed an efficient Tiny CNN architecture for e-skin applications. The architecture leverages the memory allocation strategy presented earlier and provides better performance than existing solutions. A major contribution of the thesis is given by CBin-NN, a library of functions for implementing extremely efficient binary neural networks on constrained devices. The library outperforms state of the art NN deployment solutions by drastically reducing memory footprint and inference latency. All the solutions proposed in this thesis have been implemented on representative devices and tested in relevant applications, of which results are reported and discussed. The ELM framework is open source, and this work is clearly becoming a useful, versatile toolkit for the IoT and TinyML research and development community
Environmental Protection Strategies
Methodological bases of ecological safety, its origins, essence, evolution are analyzed. The main
problems of ecological safety of mankind are considered. Materials on the main branches of human
production activity are presented. Their influence on the atmospheric air, hydrosphere, lithosphere
is analyzed and ways of overcoming of negative consequences are suggested. The ecological bases
of rational use of nature, methods of management of processes of use of nature, modern waste–
free technologies and processes, development of means of waste utilization, integrated use of
secondary raw materials are presented.Проаналізовано методологічні засади екологічної безпеки, її витоки, суть, еволюція.
Розглянуто основні проблеми екологічної безпеки людства. Представлено матеріали щодо
основних галузей виробничої діяльності людини. Проаналізовано їх вплив на атмосферне
повітря, гідросферу, літосферу та запропоновано шляхи подолання негативних наслідків.
Представлені екологічні основи раціонального природокористування, методи управління
процесами природокористування, сучасні безвідходні технології та процеси, розробка
засобів утилізації відходів, комплексного використання вторинної сировини
Real Estate Investment Trusts (REITs) Corporate Governance and Investment Decision-Making in the United Kingdom, South Africa and Nigeria
Adopting Real Estate Investment Trusts (REITs) has been relatively slow due to corporate governance issues and a limited understanding of investment decision-making processes. This study aims to enhance the performance of REITs by developing a Corporate Governance Scoring Framework and improving the investment decision-making process. A mixed-method research strategy was employed to gather data on investment decisionmaking processes and corporate governance in the UK, SA, and Nigeria from 2014-2019. Qualitative data was collected through semi-structured telephone interviews with key decision-makers in the three regimes and analysed using content and discourse analysis techniques. Quantitative data was obtained from the annual financial reports of listed
REITs during the study period and analysed using OLS, fixed effects, and random effect models. The Integrated Corporate Governance Index (ICGI), a self-scoring framework,
was used to measure the quality of corporate governance strength.
The qualitative analysis identified four stages in the investment decision-making process: strategy, search, analysis and adjustment, and consultation or decision and review. The interviews revealed that the board, remuneration, and fee proxies were relevant factors across all three regimes, with audit and ownership also significant in the developing regimes of SA and Nigeria. The board's reputation, experience, and management role were highlighted as crucial during the decision-making process. Performance factors such as 'Operational Stability,' 'Tenant Quality,' 'Experience,' and metrics including 'Rental Income,' 'Dividend Payment,' and 'Yield' were identified. The quantitative analysis demonstrated that adherence to corporate governance codes was highest in the UK, followed by SA and Nigeria. Regression analysis results showed that a higher ICGI score improved return on assets (ROA) and return on equity (ROE) in the UK but not in SA and Nigeria. The index did not significantly impact firm value in the UK and pooled country analysis, but it led to better firm valuation in SA. In the Nigeria REIT regime, the ICGI harmed firm valuation. The study concluded that adherence to country-level corporate governance was more predictive of operational performance than firm valuation.
In summary, this study contributes to the existing knowledge by providing insights into the investment decision-making processes of REITs and the importance of corporate governance in improving their performance. The developed Corporate Governance Scoring Framework offers a valuable tool for evaluating the quality of corporate governance in REITs, but further refinement is necessary to keep up with evolving policies
Reasoning in criminal intelligence analysis through an argumentation theory-based framework
This thesis provides an in-depth analysis of criminal intelligence analysts’ analytical reasoning process and offers an argumentation theory-based framework as a means to support that reasoning process in software applications. Researchers have extensively researched specific areas of criminal intelligence analysts’ sensemaking and reasoning processes over the decades. However, the research is fractured across different research studies and those research studies often have high-level descriptions of how criminal intelligence analysts formulate their rationale (argument). This thesis addresses this gap by offering low level descriptions on how the reasoning-formulation process takes place. It is presented as a single framework, with supporting templates, to inform the software implementation process.
Knowledge from nine experienced criminal intelligence analysts from West Midlands Police and Belgium’s Local and Federal Police forces were elicited through a semi-structured interview for study 1 and the Critical Decision Method (CDM), as part of the Cognitive Task Analysis (CTA) approach, was used for study 2 and study 3. The data analysis for study 1 made use of the Qualitative Conventional Content Analysis approach. The data analysis for study 2 made use of a mixed method approach, consisting out of Qualitative Directed Content Analysis and the Emerging Theme Approach. The data analysis for study 3 made use of the Qualitative Directed Content Analysis approach.
The results from the three studies along with the concepts from the existing literature informed the construction of the argumentation theory-based framework. The evaluation study for the framework’s components made use of Paper Prototype Testing as a participatory design method over an electronic medium. The low-fidelity prototype was constructed by turning the frameworks’ components into software widgets that resembled widgets on a software application’s toolbar. Eight experienced criminal intelligence analysts from West Midlands Police and Belgium’s Local and Federal Police forces took part in the evaluation study. Participants had to construct their rationale using the available components as part of a simulated robbery crime scenario, which used real anonymised crime data from West Midlands Police force. The evaluation study made use of a Likert scale questionnaire to capture the participant’s views on how the frameworks’ components aided participants with; understanding what was going on in the analysis, lines-of-enquiry and; the changes in their level of confidence pertaining to their rationale. A non-parametric, one sample z-test was used for reporting the statistical results. The significance is at 5% (α=0.05) against a median of 3 for the z-test, where μ =3 represents neutral. The participants reported a positive experience with the framework’s components and results show that the framework’s components aided them with formulating their rationale and understanding how confident they were during different phases of constructing their rationale
Investigating drivers of cyanobacterial blooms in Aotearoa – New Zealand lakes using sedimentary ancient DNA
Healthy lake ecosystems support biodiversity and human populations. They provide many ecosystem services such as water, food and energy. Lakes can be impacted by natural disturbances, but they are increasingly threatened by human-induced disturbances. Studies have shown that eutrophication and climate change often enhance cyanobacteria over other photosynthetic taxa. As cyanobacterial blooms are becoming more frequent and intense throughout the world, more lake systems are being investigated. In some cases there is not a clear link between eutrophication and cyanobacterial blooms. One such example is Lake Pounui (Wairarapa, New Zealand), which has little intensive agriculture in its catchment but water quality has degraded markedly in the last decade. The lake now experiences heavy cyanobacterial blooms every summer. This could be due to the presence of a non-native fish population, the European perch (Perca fluviatilis). This thesis examined the relationship between cyanobacterial blooms and perch introduction in New Zealand
lakes, including a multi-trophic study in Lake Pounui. Perch were introduced c. 1870 in New Zealand but introduction records are patchy and sometimes non-existent. Moreover, most lake systems are not studied until they are already degraded. This thesis used a combination of traditional proxies (pollen, charcoal, pigments) and modern proxies (sedimentary ancient DNA, XRF scanning) from lake sediment cores to reconstruct lake ecology in pre-human times, after M¯aori settlement between the 13th to 15th century, and after European settlement from 1840 AD. Timelines and intensity of human impact were reconstructed with pollen, charcoal analysis, and sediment dating when possible.
Cyanobacterial communities in six lakes were reconstructed through their sedimentary ancient DNA (sedaDNA) using metabarcoding and droplet digital PCR (ddPCR) in Chapter 2. Bloom-forming species were present in all lakes prior to human arrival; however their overall abundance was low. Total cyanobacteria abundance and richness increased in all lakes after European settlement but was very pronounced in four lakes, where bloom-forming taxa became dominant. The trends in cyanobacterial abundance from ddPCR were then compared to cyanobacterial pigments (canthaxanthin, echinenone, myxoxanthophyll and zeaxanthin) using highperformance liquid chromatography in Chapter 3, to assess the likelihood of the historical increase observed. Pigments / sedaDNA relationships were more consistent when all pigments were summed, which is likely due to differences in species composition across lakes. The positive correlations confirmed an increase in cyanobacterial biomass since European arrival.
Due to patchy records for fish introduction, fish sedimentary DNA was compared to environmental DNA (eDNA) from water samples as a methodological check (Chapter 4) before applying this method to the sediment cores. This study was undertaken in three small and shallow lowland lakes by targeting perch and rudd (Scardinius erythrophthalmus). Fish DNA was evenly distributed across the whole lake except when the fish population was low. Samples collected from the sediment contained fish DNA more often than water samples in two out of the three small shallow lakes (including Lake Pounui). Sediment geochemistry probably impeded detection in the third lake. Perch sedaDNA was therefore used as an indication of fish presence in Lake Pounui for Chapter 5, which explored multitrophic changes in Lake Pounui over the last c. 1,000 years. In addition to pollen, charcoal, and 14C dating, XRF scanning was used to reconstruct mineralogic shifts from the catchment (Ti/inc, K/inc) and within the lake (inc/coh). Biological trends were reconstructed
by targeting the sedaDNA of bacteria (16S rRNA), microeukaryotes (18S rRNA), metazoans (CO1), and macrophytes (rbcL, trnL). Complemented by historical records and studies, the data produced in this thesis indicated that the biggest changes in Lake Pounui happened after European settlement (c. 1845), with land clearance, perch introduction, climate change, and probable fertiliser application driving the degradation of the water quality in c. 180 years. This study revealed shifts in native communities (macrophytes, bacteria, oligochaete worms) and the appearance of new species (perch, macrophytes, freshwater nematodes) previously undocumented using sedaDNA. The results highlight just how complex yet fragile lake ecosystems can be and how little we still know about them. Sedimentary ancient DNA is a useful tool to study the insidious and long-lasting impact of nonnative species on freshwater ecosystems because it widens the range of species that can be studied. However, it needs to be complemented with other proxies. This thesis provides a framework to study fish DNA in small shallow lakes (Chapter 4). It can also inform future management and restoration strategies in lakes, especially in Lake Pounui, by retracing historical water quality (Chapter 2) and identifying taxa present prior to, during, and after lake degradation (Chapter 5)
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