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The growing interest in more electrified vehicles has been pushing the industry and academia to pursue new and more accurate ways to estimate the xEV batteries State-of-Charge (SOC). The battery system still represents one of the many technical barriers that need to be eliminated or reduced to enable the proliferation of more xEV in the market, which in turn can help reduce CO2 emissions. Battery modelling and SOC estimation of Lithium-ion batteries (Li-ion) at a wide temperature range, including negative temperatures, has been a challenge for many engineers. For SOC estimation, several models configurations and approaches were developed and tested as results of this work, including different non-recurrent neural networks, such as Feedforward deep neural networks (FNN) and recurrent neural networks based on long short-term memory recurrent neural networks (LSTM-RNN). The approaches have considerably improved the accuracy presented in the previous state-of-the-art. They have expanded the application throughout five different Li-ion at a wide temperature range, achieving error as low as 0.66% Root Mean Square Error at -10⁰C using an FNN approach and 0.90% using LSTM-RNN. Therefore, the use of deep neural networks developed in this work can increase the potential for xEV application, especially where accuracy at negative temperatures is essential. For Li-ion modelling, a cell model using LSTM-RNN (LSTM-VM) was developed for the first time to estimate the battery cell terminal voltage and is compared against a gated recurrent unit (GRU-VM) approach and a Third-order Equivalent Circuit Model based on Thevenin theorem (ECM). The models were extensively compared for different Li-ion at a wide range of temperature conditions. The LSTM-VM has shown to be more accurate than the two other benchmarks, where could achieve 43 (mV) Root Mean Square Error at -20⁰C, a third when compared to the same situation using ECM. Although the difference between LSTM-VM and GRU-VM is not that steep. Finally, throughout the work, several methods to improve robustness, accuracy and training time have been introduced, including Transfer Learning applied to the development of SOC estimation models, showing great potential to reduce the amount of data necessary to train LSTM-RNN as well as improve its accuracy. / Thesis / Doctor of Philosophy (PhD) / For electric vehicle State-of-Charge estimation, several models configurations and approaches were developed and tested as results of this work, including different non-recurrent neural networks, such as Feedforward deep neural networks (FNN) and recurrent neural networks based on long short-term memory recurrent neural networks (LSTM-RNN). The approaches have considerably improved the accuracy presented in the previous state-of-the-art. They have expanded the application throughout five different Li-ion at a wide temperature range, achieving error as low as 0.66% Root Mean Square Error at -10⁰C using an FNN approach and 0.90% using LSTM-RNN. Therefore, the use of deep neural networks developed in this work can increase the potential for xEV application, especially where accuracy at negative temperatures is essential. For Li-ion modelling, a cell model using LSTM-RNN (LSTM-VM) was developed for the first time to estimate the battery cell terminal voltage and is compared against a gated recurrent unit (GRU-VM) approach and a Third-order Equivalent Circuit Model based on Thevenin theorem (ECM). The models were extensively compared for different Li-ion at a wide range of temperature conditions. The LSTM-VM has shown to be more accurate than the two other benchmarks, where could achieve 43 (mV) Root Mean Square Error at -20⁰C, a third when compared to the same situation using ECM. Although the difference between LSTM-VM and GRU-VM is not that steep.

The U.S. health care delivery system faces serious challenges such as an increasing demand for services due to an aging population, unhealthy lifestyles, growth in the number of uninsured individuals, and an increase in chronic diseases. At the same time, the system has to cope with a limited supply of money, physicians, and nurses inferior quality of care delivered by U.S. hospitals. While the U.S. hospital industry is adapting to address these issues, not much progress in improving the quality of care delivered has been made over the last decade. However, theories exist that management systems, organizational traits, and leadership are key factors for hospitals to improve quality of care outcomes. This study takes a holistic look at these factors to identify and analyze critical drivers for better quality of care outcomes of U.S. hospitals. The study also aims to identify differences between chief executive officers' (CEOs) leadership traits among lean (mediocre performance), high (top 20th percentile), and low performing (bottom 20th percentile) U.S. hospitals in regards to their quality of care measures. Two separate online surveys were conducted. The first online survey was targeted at all 4,697 U.S. hospitals that are required to disclose quality of care measures to the Federal government. Results of this first survey revealed that two management system factors drive quality of care outcomes of U.S. hospitals. Furthermore, findings also show that critical access hospitals have a lower quality of care performance than acute care hospitals. Thus, based on the results from this survey, we concluded that management system factors are main drivers of hospital performance, whereas organizational trait and leadership factors did not significantly contribute to hospital performance. A second survey to CEOs and CEO followers in 9 selected hospitals found significant differences between CEO traits leading lean and low performing hospitals, and, to a lesser degree, significant differences among high and low performing hospitals. However, the study did not find any significant differences in CEO traits between lean and high performing hospitals. Findings also include that some management system factors differed significantly between lean and high performing hospitals, but no evidence for such differences could be found between lean and high and high and low performing hospitals, respectively. These results suggest that management systems and CEO leadership traits play an important role in determining U.S. hospital performance as measured by their quality of care. / Ph. D.

<p dir="ltr">Traffic Incident Management (TIM) is an important tool for agencies to reduce secondary crashes, improve travel reliability, and ensure safety of first responders. Having “eyes” on the scene from roadside traffic cameras can assist operators to dispatch appropriate personnel, provide situational awareness, and allow for quick response when incident conditions change. Many intelligent traffic systems (ITS) centers deploy pan-tilt-zoom (PTZ) cameras that provide broad coverage but require operators to position. When incidents occur or a public safety vehicle stops for roadside assistance, Traffic Management Center (TMC) operators need to reposition cameras to monitor the event. The camera positioning time depends on operator experience, accuracy of 911 call, location, public safety radio reports, and in some cases, GPS positions. This research outlines the methodology to use GPS data sources to automate camera position to a scene for event nature verification. In general, this GPS information can come from either connected vehicles or public safety vehicles, such as Indiana Department of Transportation (INDOT) Hoosier Helpers. Implementing this research into INDOT daily operations has increased the number of events that cameras verify, while decreasing the time from event occurrence to camera verification from a median of 5 minutes to a median of approximately 90 seconds. The time is driven by the accuracy and frequency of GPS data from devices. With increased telematics polling rates and availability of enhanced vehicle data such as door open/close and seatbelt latch events, this latency is expected to further decline. </p>

Learning Management Systems (LMSs) have been an essential part of the e-Learning ecosystem since the 1990s. LMSs have been developed and widely adopted by higher education institutions around the world. Despite the instructional and financial benefits of using LMSs, the adoption and diffusion of LMSs by faculty members continues to be challenging in higher education institutions, and particularly in developing countries. The purpose of this study is to determine the factors influencing the adoption of learning management systems (LMSs) by faculty members in Saudi Arabian higher education. The study employed a mixed method approach and applied the Unified Theory of Acceptance and Use of Technology (UTAUT) to explore these factors. Specifically, the study aims to determine the extent at which Performance Expectancy (PE), Effort Expectancy (EE), Facilitating Conditions (FC), and Social Norms (SN) influence faculty members' Behavioral Intention (BI) to adopt the Blackboard LMS. It also examines the moderating roles of age, gender, experience, perceived voluntariness, and computer self-efficacy on Performance Expectancy (PE), Effort Expectancy (EE), Social Norms (SN), and Facilitating Conditions (FC). The results of the study revealed a strong and positive correlation between performance expectancy and behavioral intention for Blackboard usage. The study also found Effort Expectancy, Facilitating Conditions, and Social Norms to be significant predictors of Behavioral Intention for Blackboard usage. Additionally, the findings show no moderation effects of age, gender, perceived voluntariness, and computer self-efficacy on Performance Expectancy, Effort Expectancy, Social Norms, and Facilitating Conditions. Experience was found to have a moderation effect on the relationship between Social Norms and Behavioral Intention. / Doctor of Philosophy / Learning Management Systems (LMSs) have been an essential part of the Electronic-Learning ecosystem since the 1990s. LMSs have been developed and widely adopted by higher education institutions around the world. Despite the instructional and financial benefits of using LMSs, the usage rate of LMSs by faculty members continues to be challenging in higher education institutions, and particularly in developing countries. The purpose of this study is to determine the factors influencing the usage of learning management systems (LMSs) by faculty members in Saudi Arabian higher education. The study employed a mixed method approach and applied the Unified Theory of Acceptance and Use of Technology (UTAUT) to explore these factors. Specifically, the study aims to determine the extent at which Performance Expectancy (PE), Effort Expectancy (EE), Facilitating Conditions (FC), and Social Norms (SN) influence faculty members' Behavioral Intention (BI) to adopt the Blackboard LMS. It also examines the moderating roles of age, gender, experience, perceived voluntariness, and computer self-efficacy on Performance Expectancy (PE), Effort Expectancy (EE), Social Norms (SN), and Facilitating Conditions (FC). The results of the study revealed a strong and positive correlation between performance expectancy and behavioral intention for Blackboard usage. The study also found Effort Expectancy, Facilitating Conditions, and Social Norms to be strong predictors of Behavioral Intention for Blackboard usage.

It is necessary for large companies to understand and be able to adapt to the industrial transformation towards an increasing focus on energy efficiency, which takes place today. The Energy Efficiency Directive (EED)issued by the European Union has enlarged the focus on working with energy efficiency within large companies. Further, the Swedish government has introduced the law about energy auditing in large companies, which is based on the EED. These regulations encourage companies to develop a management system that includes requirements on conducting energy audits and propose cost effective measures.  Energy efficiency is already an important aspect within many companies environmental work, however a more developed and systematic approach to energy efficiency than most companies already have is needed in order to fulfill the legal requirements. The Company investigated in this study is one the world’s leading technology companies with more than 9000 employees in Sweden. Currently, they have energy as a significant aspect in their environmental work according to the international management system standard ISO 14001. Today they are also developing their energy work by conducting energy audits in order to comply with the new legislation. This gives a more detailed view of the energy use and potential improvements that can be done, but in order to ensure continual improvements over a long period of time further measures are needed.  Within this study it was investigated what measures a large company needs to implement in order to increase their energy performance and comply with the legislation. By a literature review focusing on management systems as well as interviews within the Company, a complementary study with two companies covered by the EED and three expert interviews, five key factors were identified. These factors are top management commitment, awareness, goals, measurements and evaluation. A model was then developed aligning these factors. Further, concrete proposals for action to manage these factors were presented. By increasing focus on these key factors and implement proposed measures companies will increase their energy performance and make the organization aware of how actions affect a company’s energy performance.

Med digitaliseringens framväxt har så även industriernas förutsättningar förändrats. I dag återfinns en vid portfölj av digitala hjälpmedel och maskinteknik som bidrar till genomförandet av producerande industriers många processer, men den verkliga implementeringen varierar. Livsmedelsindustrin ses som en av dem tillverkande industrier med långsammare adoption och en försiktigare inställning till förändrade processer, vilket för verksamma organisationer har försvårat navigationen bland digitala lösningar och hur dessa kan nyttjas. En organisation som vittnar om dessa osäkerheter är livsmedelsproducenten Norrmejerier Ekonomisk Förening som i samband med stora organisatoriska omställningar behöver förändra nuvarande materialhantering och därför börjat se över informationstekniska systemstöd som en del av lösningen. Denna studie ämnar därför att kartlägga och sammanställa organisatoriska behov som bör beaktas i implementering av systemstöd för material och insatsvaror inom livsmedelsindustrin. För att kunna göra det delades syftet in i två delsyften: 1. Kartlägga och sammanställa olika avdelningars behov på systemstöd i strävan efter relevans och reducerat motstånd vid förändring. 2. Identifiera funktioner och parametrar motsvarande nuvarande arbetsprocesser och behovsbilder givna ur delsyfte 1.   För att uppnå dessa syften genomfördes en fallstudie på Norrmejerier via semistrukturerade intervjuer med anställda inom olika avdelningar som skulle påverkas av förändringen. Intervjuerna genomfördes med stöd från tidigare studier inom de industriella revolutionernas bidrag och studier avseende förändringsledning samt förändringsmotstånd. Utöver intervjuer samlades data in via kompletterande organisatorisk mikroetnografi, vars data nyttjades till formulering av intervjufrågor samt som kompletterande insikter vid analys av intervjusvar. Resultaten av studien visade behov att förbättra materialflödets spårbarhet och automation, samtidigt som en sådan förändring förutsatte att berörda får utbildning i valt systemstöd respektive nya arbetssätt. Därtill identifierades warehouse management systems (WMS) tillsammans med RFID-teknologi som en potentiell lösning som för det interna materialflödet skulle innebära en ökad effektivitet, precision och spårbarhet med automatisk informationsinsamling och kommunikation mellan uppkopplade databaser och enheter. En sådan implementering bar enligt tidigare studier även potentialen till ett förbättrat kvalitetsarbete och ökad livsmedelssäkerhet, vilket sedermera inte enkom skulle resultera i fördelar för materialflödeshanteringen på lång sikt.

<p dir="ltr">Engineering Technology (ET) programs are pivotal in preparing graduates for the demands of the modern workforce, particularly in quality management systems (QMS). This study examines the alignment between QMS knowledge and experience gained by graduates in ABET-accredited ET programs and the expectations of industry. Through a dual-survey approach, targeting both industry leaders and academic educators, the research elucidates current QMS practices in industry, the scope of QMS education, and the resulting preparedness of graduates for professional roles. Findings indicate a discernible gap between industry expectations and current academic offerings in QMS education. While industry professionals rely on established QMS frameworks such as ISO 9001 and Lean Six Sigma, academic programs often limit their coverage to theoretical underpinnings rather than hands-on, practical applications. This discrepancy highlights the need for a more robust, application-oriented curriculum that bridges theoretical knowledge with real-world practice. Recommendations include a call for greater integration of practical QMS training within academic programs and stronger partnerships between academia and industry to foster educational content that aligns with professional QMS applications.</p>

The main focus of this study is to determine if systems development methodologies are being utilised in the development of electronic learning systems in South Africa and if these methodologies are being applied effectively. Essentially this study can be viewed as exploratory research, utilising a conceptual research model to investigate the relationships between the constructs and measurements. Electronic learning, or e-learning, is being employed to educate millions of learners, students and employees around the world and it is a critical component of modern educational systems. E-learning systems, or learning management systems, as it is known in the field, sit at the heart of these educational systems and are used to systematically deliver on-line content and facilitate the learning experience around that content. There is still much confusion and misconceptions surrounding e-learning and learning management systems abound. This study will try and clarify some of these misconceptions. In e-learning systems, the effective use of information systems is especially relevant as it is used to educate the minds of the future. To ensure that e-learning systems of outstanding quality are being developed, it is therefore crucial that systems development methodologies are being used as they can have a significant impact on the development process. There is a dearth of empirical research available on the use and effectiveness of systems development methodologies in South Africa. This study aims, amongst other things to make a contribution to the availability of empirical results. By empirically evaluating the conceptual research model, utilising a survey as the main research method and statistically analysing the dataset, meaningful results were obtained. This study gave some insights into how learning management system procurement and development is being done in South Africa and revealed that the use of open-source systems currently exceeds the use of proprietary systems. The results of the research showed that systems development methodologies (e.g. Object-Oriented Analysis and Rapid Application Development) are being used effectively in the development of e-learning systems. Strong relationships exist between many of the systems development methodology factors identified (e.g. performance expectancy and the perceived support of the methodology) and the quality and productivity of the development process. This in turn has a strong influence on the impact systems development methodologies have on the quality of learning management systems. / MCom (Computer Science & Information Systems), North-West University, Potchefstroom Campus, 2014

The main focus of this study is to determine if systems development methodologies are being utilised in the development of electronic learning systems in South Africa and if these methodologies are being applied effectively. Essentially this study can be viewed as exploratory research, utilising a conceptual research model to investigate the relationships between the constructs and measurements. Electronic learning, or e-learning, is being employed to educate millions of learners, students and employees around the world and it is a critical component of modern educational systems. E-learning systems, or learning management systems, as it is known in the field, sit at the heart of these educational systems and are used to systematically deliver on-line content and facilitate the learning experience around that content. There is still much confusion and misconceptions surrounding e-learning and learning management systems abound. This study will try and clarify some of these misconceptions. In e-learning systems, the effective use of information systems is especially relevant as it is used to educate the minds of the future. To ensure that e-learning systems of outstanding quality are being developed, it is therefore crucial that systems development methodologies are being used as they can have a significant impact on the development process. There is a dearth of empirical research available on the use and effectiveness of systems development methodologies in South Africa. This study aims, amongst other things to make a contribution to the availability of empirical results. By empirically evaluating the conceptual research model, utilising a survey as the main research method and statistically analysing the dataset, meaningful results were obtained. This study gave some insights into how learning management system procurement and development is being done in South Africa and revealed that the use of open-source systems currently exceeds the use of proprietary systems. The results of the research showed that systems development methodologies (e.g. Object-Oriented Analysis and Rapid Application Development) are being used effectively in the development of e-learning systems. Strong relationships exist between many of the systems development methodology factors identified (e.g. performance expectancy and the perceived support of the methodology) and the quality and productivity of the development process. This in turn has a strong influence on the impact systems development methodologies have on the quality of learning management systems. / MCom (Computer Science & Information Systems), North-West University, Potchefstroom Campus, 2014