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Performance of a new Risk Score in a Patient Monitoring System in Low-Resource Settings in a Hospital in Zomba, Malawi
(2025) Morrenhof, Kelly
In Low- and Middle-Income countries (LMIC), it is hard to provide adequate healthcare
to critically ill children due to limited resources in staff and equipment. Within
these Low-Resource settings (LRS), pediatric mortality and the occurrence of Critical
Illness Events (CIE) are high. Continuous patient monitoring of vital signs
can be particularly helpful in LRS, especially for critically ill children. GOAL 3
designed a Continuous Patient Monitoring System (CPMS), service, and training fit
for LRS, IMPALA, and implemented it in the Pediatric High-Dependency Unit of
Zomba Central Hospital in Malawi, Africa. To this IMPALA CPMS, a newly developed
Risk Score was added. This Risk Score, adjusted from an earlier developed
physiological score, can potentially assign a health risk level with a score between
0-100, show the progress of the patient over time, and function as an early warning
system. In this study, the performance of the Risk Score is assessed, based on its
distinctive ability to assign a high-risk level to patients who eventually passed away
and to patients who had one or more CIE. The study consisted of 192 participants
under 5 years of age, whose clinical and score data were analyzed. With a mortality
rate of 12% and 140 CIE in total, there were many critically ill children. That
group showed the highest average Risk Score of 64 in the death subset, and 37 in
all patients with one or more CIE, significantly different from an average score of
23 in participants who had no CIE and survived. With an AUROC in the range
of comparable literature, it shows that the Risk Score can distinguish and potentially
predict patients who pass away moderately to well, especially in the last 6-8
hours before discharge. Observations and data analysis revealed challenges with the
Risk Score availability, which results in an average score coverage of 82%, mainly
due to problems with the oxygen saturation probe and nurses not implementing the
score system in their routines at the beginning of the study. Optimization and more
research have to be done to improve these challenges and validate the Risk Score.
Fault Detection of HVDC Transformer Windings using Impedance Protection
(2025) Meegodage, Sewwandi Subhashini Meegoda
Power transformers play a key role in high voltage direct current (HVDC) systems to overcome the limitations of conventional AC transmission and are expensive and fundamental
components in power systems. Transformer winding faults are among the most frequent issues in transformers. Since winding faults are inherently aggravated, transformer winding short circuits need to be detected at an early stage. The existing transformer protection methods encounter difficulties in detecting winding faults in transformers. This study investigates and develops a reliable method for transformer winding fault detection based on impedance protection by calculating the winding impedance utilizing the terminal voltage and current measurements, and comparing the impedance values under fault conditions with their steady-state condition values. A three-phase transformer was modelled in PSCAD simulation software using three multi-winding single-phase transformers to model internal faults. Turn-to-turn faults were simulated for different fault locations, and analyzed impedance values of each scenario using a conventional impedance protection method and Machine Learning algorithms (ML) i.e. Support Vector Machine (SVM), Decision Tree and
Artificial Neural Networks (ANNS) to detect and classify the winding faults and identify their locations. The fault studies were conducted on a symmetric monopolar Voltage Source Converter (VSC) based HVDC system. The terminal voltage and current measurements were utilized to derive impedance values for each fault condition. The obtained voltage, current, and impedance measurements were fed to train the developed Machine Learning algorithm Models. A higher accuracy is obtained by optimizing the ML model parameters in fault detection, classification, and fault location detection.
Investigation of linear correlations between soil indicators
(2025) Westergren, Sofia
The soil is an important part of the world that contributes to ecosystem services
such as food production, water purification, and protection from climate changes.
Despite that, knowledge and understanding of the structure and functions of the soil
system is deficient. The world faces challenges related to crop production and food
consumption. These challenges are predicted to become even greater in the future.
An increased understanding, will contribute to the work to assess the status of soils
and preserve or regain the functions from soil. The aim of this study is to increase
the understanding of how soil indicators can be used to describe soil and specifically
to investigate the existence of linear correlations between soil indicators. The investigation
includes calculation of biological soil indicators based on environmental
DNA from The Land Use/Cover Area frame statistical Survey (LUCAS). The calculated
biological soil indicators are the ratio of gram-positive and gram-negative
bacteria, diversity index and presence of actinomycetes bacteria, mycorrhiza forming
fungi, and saprotrophic fungi. The data analysis includes regression analysis and
principal component analysis between the biological soil indicators and characteristic
soil indicators (see Table 4.5). The results indicate that there may be no linear
correlations between the chosen biological soil indicators and the characteristic soil
indicators.
Evaluation of system strength in a converterdominated power system
(2025) Rosengren, Malte
The steady increase in power electronic-interfaced generation, driven by the continued growth of renewable energy sources, is altering the dynamic behavior of modern power systems. While traditional system dynamics have been dictated by the characteristics of synchronous generators, the increasing penetration of Converter-Based Resources (CBRs) is contributing to a gradual transition toward converter dominated power systems. This transition introduces new challenges to power system stability and raises questions regarding the applicability of conventional system strength metrics, particularly the Short Circuit Ratio (SCR), which has historically been used to assessgrid strength. The aim of this thesis is to evaluate the limitations of the SCR metric in grid strength assessment for converter-dominated power systems and to assess alternative system strength metrics that may be more suitable under these changing conditions. Furthermore, the alternative system strength metrics need to be applicable during grid planning and is therefore restricted to the data available at this stage. The study was structured into three phases: (1) an initial review of the traditional grid strength metric, SCR, supported by Electromagnetic Transient (EMT) simulations; (2) initial evaluation and selection of alternative system strength metrics through comparative evaluation using small-scale case study with EMT simulations; and (3) implementation and evaluation in PSS®E, of the most promising metrics selected in (2), followed by validation of PSS®E results through detailed EMT simulations to determine the most reliable metric for system strength assessment.
The results indicate that traditional SCR metric consistently overestimates system strength in systems with high CBR penetration. The preliminary grid strength asessment conducted in phase 2 identified the Available Fault Level (AFL), Equivalent Short Circuit Ratio (EqSCR), and Site-Dependent Short Circuit Ratio (SDSCR) as the most appropriate alternative metrics for evaluating grid strength. While the AFL demonstrated promise in the initial small-scale review, it exhibited inconsistencies in the estimation of system strength during the validation process in phase 3. The results obtained from the EqSCR and SDSCR metrics were closely aligned. This outcome is expected, as both methods are fundamentally similar, differing primarily
in the specific computational approaches they employ. For both small-scale (phase 2) and more complex system models (phase 3), the two metrics consistently identified the point of instability. System weakness and instability were observed at EqSCR values ranging from 1.1 to 1.3, and SDSCR values between 1.2 and 1.4. Given their comparable performance, EqSCR was identified as the more suitable metric due to its greater computational efficiency. Based on these findings, this thesis recommends the use of EqSCR for system strength screening in converter dominated power systems.
Enabling a Broader Use of Time-Coupled Building Information Modeling: Understanding current barriers and investigating takt planning as a catalyst for implementation
(2025) Hjelmqvist, Axel; Sandros, Ronja
Time-coupled Building Information Modeling (BIM) is a powerful tool for integrat ing BIM and production planning. This paper reviews the literature and interviews
conducted with practitioners in the construction industry to test the benefits men tioned in the literature. The interviews showed that StreamBIM has the potential
to integrate BIM into existing workflows and tools. It also enables the development
of automated methods for this integration. In addition, the interviews show that
BIM’s flexibility and ability to visualize 3D for production planning can be improved
by combining BIM with a takt-time plan. The results from the interviews suggest
that iterative and continuous usage of time-coupled BIM needs to be done to make
on-boarding easier for both clients, designers, and contractors.