23,755 research outputs found
Recommended from our members
Design and modeling of an on-site greywater treatment system for a hotel building
As the United States is making a significant move towards rejoining the Paris Agreement on climate change, there is a high demand for sustainable solutions across various industries, including construction and hospitality sectors. The aim of this project was to design and model an on-site greywater treatment system for a hotel building for the effective reuse of sewage water. The study considered Los Angeles, California, as a case study location and referred to respective climate conditions and construction standards. This study considered various options of greywater treatment plants such as Membrane Bioreactor (MBR), Sequencing Batch Reactor (SBR), and Reverse Osmosis with Upflow Anaerobic Sludge Blanket (RO with UASB) which were carefully reviewed and modeled through the GPS-X software. The design and modeling results were verified by hand calculations and were followed by the estimation of capital and operational expenses required for the implementation of the plants. Having relatively low capital and operational expenditure requirements as well as superior technical performance, the MBR plant proved to be the most effective solution for the considered location and standards and was recommended for use in hotel buildings
Machine learning based adaptive soft sensor for flash point inference in a refinery realtime process
In industrial control processes, certain characteristics are sometimes difficult to measure by a physical sensor due to technical and/or economic limitations. This fact is especially true in the petrochemical industry. Some of those quantities are especially crucial for operators and process safety. This is the case for the automotive diesel Flash Point Temperature (FT). Traditional methods for FT estimation are based on the study of the empirical inference between flammability properties and the denoted target magnitude. The necessary measures are taken indirectly by samples from the process and analyzing them in the laboratory, this process implies time (can take hours from collection to flash temperature measurement) and thus make it very difficult for real-time monitorization, which in fact results in security and economical losses. This study defines a procedure based on Machine Learning modules that demonstrate the power of real-time monitorization over real data from an important international refinery. As input, easily measured values provided in real-time, such as temperature, pressure, and hydraulic flow are used and a benchmark of different regressive algorithms for FT estimation is presented. The study highlights the importance of sequencing preprocessing techniques for the correct inference of values. The implementation of adaptive learning strategies achieves considerable economic benefits in the productization of this soft sensor. The validity of the method is tested in the reality of a refinery. In addition, real-world industrial data sets tend to be unstable and volatile, and the data is often affected by noise, outliers, irrelevant or unnecessary features, and missing data. This contribution demonstrates with the inclusion of a new concept, called an adaptive soft sensor, the importance of the dynamic adaptation of the conformed schemes based on Machine Learning through their combination with feature selection, dimensional reduction, and signal processing techniques. The economic benefits of applying this soft sensor in the refinery's production plant and presented as potential semi-annual savings.This work has received funding support from the SPRI-Basque Gov-
ernment through the ELKARTEK program (OILTWIN project, ref. KK-
2020/00052)
Studies of strategic performance management for classical organizations theory & practice
Nowadays, the activities of "Performance Management" have spread very broadly in actually every part of business and management. There are numerous practitioners and researchers from very different disciplines, who are involved in exploring the different contents of performance management. In this thesis, some relevant historic developments in performance management are first reviewed. This includes various theories and frameworks of performance management. Then several management science techniques are developed for assessing performance management, including new methods in Data Envelopment Analysis (DEA) and Soft System Methodology (SSM). A theoretical framework for performance management and its practical procedures (five phases) are developed for "classic" organizations using soft system thinking, and the relationship with the existing theories are explored. Eventually these results are applied in three case studies to verify our theoretical development. One of the main contributions of this work is to point out, and to systematically explore the basic idea that the effective forms and structures of performance management for an organization are likely to depend greatly on the organizational configuration, in order to coordinate well with other management activities in the organization, which has seemingly been neglected in the existing literature of performance management research in the sense that there exists little known research that associated particular forms of performance management with the explicit assumptions of organizational configuration. By applying SSM, this thesis logically derives some main functional blocks of performance management in 'classic' organizations and clarifies the relationships between performance management and other management activities. Furthermore, it develops some new tools and procedures, which can hierarchically decompose organizational strategies and produce a practical model of specific implementation steps for "classic" organizations. Our approach integrates popular types of performance management models. Last but not least, this thesis presents findings from three major cases, which are quite different organizations in terms of management styles, ownership, and operating environment, to illustrate the fliexbility of the developed theoretical framework
Reforming the United Nations
The thesis deals with the financial crisis that the United Nations faced starting in 1985 when the US Congress decided to withhold a significant part of the US contribution to the UN regular budget in order to force a greater say for the major contributors on budgetary issues, budgetary restraint and greater efficiency. The UN responded by the adoption of resolution 41/213 of 19 December 1986 that was based on the recommendations of a Group of High-level Intergovernmental Experts ("G-18") set up a year earlier. A new system was introduced regarding the formulation of the regular budget of the United Nations Organisation and a broader process of reform was initiated including a restructuring of the Secretariat and of the intergovernmental machinery in the economic and social fields. After an introductory chapter (Chapter I), the thesis examines the UN problems at the budgetary/financial and administrative/structural levels, the solutions proposed from within and without the United Nations established framework and the actual attempts at reform (Chapters II and ifi). The realisation that the implementation of reforms is rather disjointed and often unsuccessful (e.g. the failure to restructure the intergovernmental machi.neiy) prompts a search for the deeper causes of the UN problems at the political level and the attitudes of the main actors, namely the USA, the USSR, some up-and-coming states, notably Japan, the Third World states and, finally, of the UN Secretary-General and the Secretariat (Chapter 1V). Although the financial crisis may have subsided since 1988 and the USA seem committed to paying up their dues, the deeper UN crisis of identity has not been resolved and is expected to resurface if no bold steps are taken. In that direction, some possible alternative courses for the UN in the future are discussed drawing upon theory and practice (Chapte
Working in ministries or public organizations in Saudi Arabia : A study of career development and job satisfaction of the Saudi Arabian middle managers
Career development and job satisfaction studies carried out in developing countries are very limited in number. Saudi Arabia is one of those developing countries which appeared on the political scene quite recently, but striving hard to develop its human resources due to its heavy dependence on expatriate labour to initiate and execute its development plans. The genesis of the study began when General Civil Service Bureau officials noticed a large movement of employees from ministries to other sectors (i.e. public organizations and the private sector). The purpose of this dissertation is to examine and analyze the factors behind this movement and relate this to the studies of career development and job satisfaction. The position of government organizations in Saudi Arabia is rather unique. Most of their employees are drawn from Universities due to the regulations of the GCSB of compelling them to work in ministries for a period equivalent to that spent in their University education until graduation. This situation has prevented such graduates from choosing their own occupations and seem to hinder their career development. As a consequence, this study, not only analyzes career development and job satisfaction in Saudi Arabia, but (v) job satisfaction in Saudi Arabia, but also makes a comprehensive evaluation of economic, social and organisational environments which seem to have an effect of the occupational choice of the Saudis. We take the assumption that the ideology of free occupational choice is not properly applied in Saudi Arabia due to some cultural variables (e.g. nepotism and strong family ties). Hence, this thesis will develop a definition of the concept of occupational choice and career development and the process of personnel flow and the ways in which such movement can be influenced within the Saudi context. The study will be primarily concerned with middle managers in two types of organization - government ministries and public organizations. This will hopefully give a profile of the Saudi situation as far as occupational choice, career development and job satisfaction are concerned
Patterns of subspecies diversity in the giraffe, Giraffa camelopardalis (L. 1758): comparison of systematic methods and their implications for conservation policy
This thesis examines the subspecific taxonomic status of the giraffe and considers the role of formal taxonomy in the formulation of conservation policy. Where species show consistent. geographically structured phenotypic variation such geographic patterns may indicate selective forces (or other population-level effects) acting. upon local populations. These consistent geographic patterns may be recognised formally as subspecies and may be of interest in single or multi-species biodiversity or biogeography studies for delimiting areas of conservation priority. Subspecies may also be used in the formulation of management policies and legislation. Subspecies are, by definition, allopatric. This thesis explicitly uses methodology of systematic biology and phylogenetic reconstruction to investigate patterns of variation between geographic groups. The taxonomic status of the giraffe is apposite for review. The species provides three independent data sets that may be analysed quantitatively for geographic structure; pelage patterns, morphology and genetics. Museum specimens. grouped according to geographic origin, were favoured for study as more than one type of data was often available for an individual. Population aggregation analysis of forty pelage pattern characters maintained six separate subspecies, while agglomerating some neighbouring populations into a subspecies. A 'traditional' morphometric approach, using multivariate statistical analysis of adult skull measurements, was complemented by a geometric morphometric approach; landmarkrestricted eigenshape analysis. Four morphologically distinct groups were recognised by both morphological analyses. Phylogenetic analysis of mitochondrial DNA control region sequences indicates five major cIades. Nested cIade analysis identifies population fragmentation, range expansion and genetic isolation by distance as contributing to the genetic structure of the giraffe. The results of the analyses show remarkable congruence. These results are discussed in terms of the formulation of conservation policy and the differing requirements of'blological and legal classification systems. The value of a formal taxonomic framework to the recognition, and subsequent conservation, of biodiversity is emphasised
3D printed Microneedles for Transdermal Drug Delivery
3D printing is a revolutionary manufacturing and prototyping technology that has altered the outlooks of numerous industrial and scientific fields since its introduction. Recently, it has attracted attention for its potential as a manufacturing tool for transdermal microneedles for drug delivery. In the present thesis, the 3D printability of solid and hollow microneedles via photopolymerisation-based 3D printing was investigated, aiming at establishing robust manufacturing strategies for reproducible, mechanically strong and versatile microneedles. The developed microneedles were employed as drug delivery systems for the treatment of diabetes via insulin administration.
Solid microneedles featuring different geometries were designed and 3D printed. It was demonstrated that the printing and post-printing parameters affected the printed quality, a finding that was employed to optimise the manufacturing strategy. Microneedle geometry was also found to have an impact on the piercing and fracture behaviour; however all microneedle designs were found to be mechanically safe upon application. The solid microneedles were subsequently coated with insulin-polymer films, using a 2D inkjet printing technology. The coating process achieved spatial control of the drug deposition, with quantitative accuracy. The microneedle geometry was shown to influence the morphology of the coating film, an effect that was pronounced during in the in vitro delivery studies of insulin to porcine skin.
Furthermore, hollow microneedles were designed and 3D printed, featuring different heights. Two photopolymerisation-based technologies were studied, and their performance was compared. The key influential parameters of the printing outcome and microneedle quality were identified to be the printing angle and the size of the microneedle opening. The hollow microneedles were found to be effective in piercing porcine skin without structural damaging. The hollow microneedles were incorporated into complex patches with internal microfluidic structures for the provision and distribution of drug-containing solutions. The developed complex hollow microneedle patches were coupled with a microelectromechanical system to create a novel platform device for controlled, personalised transdermal drug delivery. Advanced imaging techniques revealed that the device achieved distribution of the liquid within porcine skin tissue without the creation of depots that would delay absorption. The device was evaluated for its efficacy to transdermally deliver a model dye and insulin in vitro. In vivo trials were also conducted using diabetic rodents, with the device achieving faster onset of insulin action and sustained glycemic control, in comparison to subcutaneous injections.
Overall, the findings of the present research are anticipated to elucidate key problematic areas associated with the application of 3D printing for microneedle manufacturing and propose feasible solutions. The outermost goal of this work is to contribute to the advancement of knowledge in the field of 3D printed transdermal drug delivery systems, in order to bring them one step closer to their adoption in the clinical setting
Combined vehicle to building (V2B) and vehicle to home (V2H) strategy to increase electric vehicle market share
.Buildings are one of the most important energy consumers in modern economy countries. The massive use of electrical vehicles could help decarbonizing the economy by using electricity produced using renewable energy. Combined use of Vehicle to Grid (V2G), Vehicle to Home (V2H) and Vehicle to Building (V2B) is one of the strategies to increase the number of electrical vehicles, ensure a better coupling between energy generation and consumption, reducing peak demand and increasing global energy efficiency. This research presents a novel approach of combined use of V2H and V2B that can be applied in different scenarios such as when the building workers own EVs, company shared car fleets or leasing, among others. Recharged energy at workers homes during night hours is delivered in the building during daily working hours lowering peak demand, reducing carbon intensity and energy cost savings. The results show that the methodology is feasible and can be extended to other cases and greatly contribute to better energy efficiency, reduces peak demand in buildings and increase electric vehicles penetration in transport to workplaces.S
Facial expression recognition and intensity estimation.
Doctoral Degree. University of KwaZulu-Natal, Durban.Facial Expression is one of the profound non-verbal channels through which human emotion state is inferred from the deformation or movement of face components when facial muscles are activated. Facial Expression Recognition (FER) is one of the relevant research fields in Computer Vision (CV) and Human-Computer Interraction (HCI). Its application is not limited to: robotics, game, medical, education, security and marketing. FER consists of a wealth of information. Categorising the information into primary emotion states only limit its performance. This thesis considers investigating an approach that simultaneously predicts the emotional state of facial expression images and the corresponding degree of intensity. The task also extends to resolving FER ambiguous nature and annotation inconsistencies with a label distribution learning method that considers correlation among data. We first proposed a multi-label approach for FER and its intensity estimation using advanced machine learning techniques. According to our findings, this approach has not been considered for emotion and intensity estimation in the field before. The approach used problem transformation to present FER as a multilabel task, such that every facial expression image has unique emotion information alongside the corresponding degree of intensity at which the emotion is displayed. A Convolutional Neural Network (CNN) with a sigmoid function at the final layer is the classifier for the model. The model termed ML-CNN (Multilabel Convolutional Neural Network) successfully achieve concurrent prediction of emotion and intensity estimation. ML-CNN prediction is challenged with overfitting and intraclass and interclass variations. We employ Visual Geometric Graphics-16 (VGG-16) pretrained network to resolve the overfitting challenge and the aggregation of island loss and binary cross-entropy loss to minimise the effect of intraclass and interclass variations. The enhanced ML-CNN model shows promising results and outstanding performance than other standard multilabel algorithms. Finally, we approach data annotation inconsistency and ambiguity in FER data using isomap manifold learning with Graph Convolutional Networks (GCN). The GCN uses the distance along the isomap manifold as the edge weight, which appropriately models the similarity between adjacent nodes for emotion predictions. The proposed method produces a promising result in comparison with the state-of-the-art methods.Author's List of Publication is on page xi of this thesis
Recommended from our members
Using Digital Storytelling in Science: Meaning Making with Students aged 10-12 years old
Meaning making is an essential aspect of learning as a process of interpreting and negotiating information while sharing it with others. One way of meaning making is through (digital) storytelling. The process of creating and telling a story depends on how one can see their understanding of something come together and make sense and it is considered a (socio) constructivist strategy of learning. The purpose and contribution of this research are to explore how digital storytelling may support engagement in meaning-making as students externalise their understanding of the science topic of matter. To this aim, two digital storytelling activities were constructed – SEeDS (Sequencing of Events enabling Digital Storytelling) and Narration. The two activities included the same content but differed in structure. SEeDS presented the story scenes in an order that was not predefined and Narration in a predefined order. Both activities derived elements from the theoretical concept of Tricky Topics and Stumbling Blocks (SBs). This research was informed by the theory of Problem-based learning.
Participants were sixty-one Greek primary students aged 10-12 years old and twenty-two English secondary students aged 11-12 years old. Half students worked through the SEeDS activity and the rest through the Narration activity. Students worked cooperatively in small teams to implement the two activities. A systematic analysis of the collected data was conducted using qualitative methods. Findings revealed that the two activities had supported the Greek and English students in externalising their understanding of many scientific concepts included in the topic of matter, while it identified gaps in their prior knowledge. The two activities have also facilitated the instinctive use of exploratory talk over the other two types (cumulative and disputational talk) that can often be found in peer talk in science learning. Finally, the two activities appeared to have engaged students in the two contexts, as they allowed them to own the story creation whilst working independently. Finally, the Greek and English students viewed the SEeDS activity as challenging, making it hard to complete and at times tiring and confusing, and the Narration activity as easy to implement, giving students the opportunity to mainly focus on inventing the story plot.
This research makes a valuable contribution to the literature on making meaning in science, offering new insights about the use of problem-based stories supported by mobile technology. The findings provide opportunities to further explore the practical application of problem-based digital storytelling activities, which are hard thinking and challenging, across different age groups and cultural contexts. There is a need for teaching practices to be based on socio-constructivist learning approaches that focus on students’ thinking, not performance. Therefore, the implications of this research are relevant to a number of educational contexts and levels
- …