Coordinated voltage control for improved power system voltage stability by incorporating the reactive power reserve from wind farms

The absorption and output characteristics of reactive power of the doubly-fed induction generator (DFIG) greatly influence the voltage stability of PCC (Point of Common Coupling) where the wind farms are integrated into the bulk power grid. This study proposes a reactive power compensation strategy for coordinated voltage control (CVC) of PCC with large-scale wind farms to achieve the expected voltage quality of the power grid through a minimum amount of control actions in emergencies. To this end, the mechanism of reactive power and voltage control inside DFIG is first analyzed. Then, the concept of reactive power reserve (RPR) sensitivity concerning control actions is introduced and an index of voltage stability margin is proposed to evaluate and analyze the distance between the current operating point and the voltage collapse point by analyzing the relationship between reactive power reserve and voltage stability margin. In the event of an emergency, critical reactive power reserves are obtained to reduce the dimension and complexity of the control problem. The sensitivity of reactive power reserve and the control are formulated into a convex quadratic programming problem to optimize the control strategies for voltage stability. The proposed technology has been validated on the IEEE 39-bus system

The association of two single nucleotide polymorphisms (SNPs) in growth hormone (GH) gene with litter size and superovulation response in goat-breeds

Two active mutations (A 781 G and A 1575 G) in growth hormone (GH) gene, and their associations with litter size (LS), were investigated in both a high prolificacy (Matou, n = 182) and a low prolificacy breed (Boer, n = 352) by using the PCR-RFLP method. Superovulation experiments were designed in 57 dams, in order to evaluate the effect of different genotypes of the GH gene on superovulation response. Two genotypes (AA and AB, CC and CD) in each mutation were detected in these two goat breeds. Neither BB nor DD homozygous genotypes were observed. The genotypic frequencies of AB and CC were significantly higher than those of AA and CD. In the third parity, Matou dams with AB or CC genotypes had significantly larger litter sizes than those with AA and CD (p < 0.05). On combining the two loci, both Matou and Boer dams with ABCD genotype had the largest litter sizes when compared to the other genotypes (p < 0.05). When undergoing like superovulation treatments, a significantly higher number of corpora lutea and ova, with a lower incidence of ovarian cysts, were harvested in the AB and CC genotypes than in AA and CD. These results show that the two loci of GH gene are highly associated with abundant prolificacy and superovulation response in goat breeds

Oral delivery of encapsulated hormone for fish spawning

In response to the growing global need for fish production, this study proposes an innovative alternative to the conventional method of hormone-induced fish spawning, which currently relies on manual hormone injections, a process that introduces risks of injury, infection, and mortality. The research focuses on developing a safe and efficient oral hormone delivery system. Prior studies on oral hormone administration have demonstrated successful spawning across several fish species. However, these methods necessitate 50-125 times more hormone dosage compared to injection, due to low oral bioavailability, making such delivery impractical and no commercially available oral hormone product exists yet. The study's primary innovation is the combination of Solid Lipid Microparticles (SLMs) and an acidic modifier to encapsulate hormones. This encapsulation technology is hypothesised to protect the hormones from leaching during feeding and degradation in the fish's stomach and ensure safe delivery to the targeted receptor to stimulate spawning. The study validated its hypothesis by synthesising encapsulated hormones and subsequently evaluating them through both in vitro and in vivo analyses. The results showed negligible leakage, minimal degradation, and safe hormone release. Fish trials revealed significantly elevated sex hormone levels and successful spawning, demonstrating the efficacy of this oral administration method. This research's encapsulation strategy not only offers a promising solution to the challenges of leaching and degradation but also presents profound implications for the aquaculture industry by providing a safer, more efficient alternative to manual hormone injections, potentially enhancing the efficiency and welfare of fish spawning practices, and thereby augmenting fish production.Master of Engineerin

Study and Implementation of Patient Data Collection and Presentation for an eHealth Application

This degree project is a part of information and communication technology supported self-care system for the diabetes, mainly in diabetes data collection and visualization. The report is organized in four main sections: investigation and internet search, literature review, application design and implementation, system test and evaluation. Existed applications and research studies has been compared and, a responsive web application is developed aiming at providing relevant functionalities and services regarding diabetes self-management

Spatio-Temporal Transformer Recommender: Next Location Recommendation with Attention Mechanism by Mining the Spatio-Temporal Relationship between Visited Locations

Location-based social networks (LBSN) allow users to socialize with friends by sharing their daily life experiences online. In particular, a large amount of check-ins data generated by LBSNs capture the visit locations of users and open a new line of research of spatio-temporal big data, i.e., the next point-of-interest (POI) recommendation. At present, while some advanced methods have been proposed for POI recommendation, existing work only leverages the temporal information of two consecutive LBSN check-ins. Specifically, these methods only focus on adjacent visit sequences but ignore non-contiguous visits, while these visits can be important in understanding the spatio-temporal correlation within the trajectory. In order to fully mine this non-contiguous visit information, we propose a multi-layer Spatio-Temporal deep learning attention model for POI recommendation, Spatio-Temporal Transformer Recommender (STTF-Recommender). To incorporate the spatio-temporal patterns, we encode the information in the user’s trajectory as latent representations into their embeddings before feeding them. To mine the spatio-temporal relationship between any two visited locations, we utilize the Transformer aggregation layer. To match the most plausible candidates from all locations, we develop on an attention matcher based on the attention mechanism. The STTF-Recommender was evaluated with two real-world datasets, and the findings showed that STTF improves at least 13.75% in the mean value of the Recall index at different scales compared with the state-of-the-art models

Study and implementation of patient data collection and presentation for an eHealth application

Informationsteknik som stöd i egenvård vid kronisk sjukdom – Diabetes Typ

Effect of Thermal Aging on Microstructure and Mechanical Properties of China Low-Activation Martensitic Steel at 550 °C

The thermal aging effects on mechanical properties and microstructures in China low-activation martensitic steel have been tested by aging at 550 °C for 2,000 hours, 4,000 hours, and 10,000 hours. The microstructure was analyzed by scanning and transmission electron microscopy. The results showed that the grain size and martensitic lath increased by about 4 μm and 0.3 μm, respectively, after thermal exposure at 550 °C for 10,000 hours. MX type particles such as TaC precipitated on the matrix and Laves-phase was found on the martensitic lath boundary and grain boundary on aged specimens. The mechanical properties were investigated with tensile and Charpy impact tests. Tensile properties were not seriously affected by aging. Neither yield strength nor ultimate tensile strength changed significantly. However, the ductile–brittle transition temperature of China low-activation martensitic steel increased by 46 °C after aging for 10,000 hours due to precipitation and grain coarsening

Fault diagnosis of underground water pump based on fuzzy Petri net and condition monitoring

In order to rapidly find out causes of failure of underground water pump, a fault diagnosis model of underground water pump based on fuzzy Petri net and condition monitoring was established. Firstly, vibration signal of the water pump was measured by the condition monitoring system of underground drainage equipment, training was carried out on the water pump fault samples after vibration analysis. Then, on the structure of fuzzy Petri net model of water pump fault diagnosis, BP algorithm of neural network was introduced to train parameters such as weight values, threshold values and credibility. The results of instances analysis show that the model can be used to find out the causes of pump failure accurately, and has good accuracy, rapidity and adaptability