Phishing attacks employ social engineering to target end-users, with the goal of stealing identifying or sensitive information. This information is used in activities such as identity theft or financial fraud. During a phishing campaign, attackers distribute URLs which; along with false information, point to fraudulent resources in an attempt to deceive users into requesting the resource. These URLs are made obscure through the use of several techniques which make automated detection difficult. Current methods used to detect malicious URLs face multiple problems which attackers use to their advantage. These problems include: the time required to react to new attacks; shifts in trends in URL obfuscation and usability problems caused by the latency incurred by the lookups required by these approaches. A new method of identifying malicious URLs using Artificial Neural Networks (ANNs) has been shown to be effective by several authors. The simple method of classification performed by ANNs result in very high classification speeds with little impact on usability. Samples used for the training, validation and testing of these ANNs are gathered from Phishtank and Open Directory. Words selected from the different sections of the samples are used to create a `Bag-of-Words (BOW)' which is used as a binary input vector indicating the presence of a word for a given sample. Twenty additional features which measure lexical attributes of the sample are used to increase classification accuracy. A framework that is capable of generating these classifiers in an automated fashion is implemented. These classifiers are automatically stored on a remote update distribution service which has been built to supply updates to classifier implementations. An example browser plugin is created and uses ANNs provided by this service. It is both capable of classifying URLs requested by a user in real time and is able to block these requests. The framework is tested in terms of training time and classification accuracy. Classification speed and the effectiveness of compression algorithms on the data required to distribute updates is tested. It is concluded that it is possible to generate these ANNs in a frequent fashion, and in a method that is small enough to distribute easily. It is also shown that classifications are made at high-speed with high-accuracy, resulting in little impact on usability.

Spatial-temporal distribution of soil moisture in the vadose zone is an important aspect of the hydrological cycle that plays a fundamental role in water resources management, including modeling of water flow and mass transport. The vadose zone is a critical transfer and storage compartment, which controls the partitioning of energy and mass linked to surface runoff, evapotranspiration and infiltration. This dissertation focuses on integrating hydraulic characterization methods with remote sensing technologies to estimate the soil moisture distribution by modeling the spatial coverage of soil moisture in the horizontal and vertical dimensions with high temporal resolution. The methodology consists of using satellite images with an ultrafine 3-m resolution to estimate soil surface moisture content that is used as a top boundary condition in the hydrologic model, SWAP, to simulate transport of water in the vadose zone. To demonstrate the methodology, herein developed, a number of model simulations were performed to forecast a range of possible moisture distributions in the Everglades National Park (ENP) vadose zone. Intensive field and laboratory experiments were necessary to prepare an area of interest (AOI) and characterize the soils, and a framework was developed on ArcGIS platform for organizing and processing of data applying a simple sequential data approach, in conjunction with SWAP. An error difference of 3.6% was achieved when comparing radar backscatter coefficient (σ0) to surface Volumetric Water Content (VWC); this result was superior to the 6.1% obtained by Piles during a 2009 NASA SPAM campaign. A registration error (RMSE) of 4% was obtained between model and observations. These results confirmed the potential use of SWAP to simulate transport of water in the vadose zone of the ENP. Future work in the ENP must incorporate the use of preferential flow given the great impact of macropore on water and solute transport through the vadose zone. Among other recommendations, there is a need to develop procedures for measuring the ENP peat shrinkage characteristics due to changes in moisture content in support of the enhanced modeling of soil moisture distribution.

Assessing the genetics of wild animal populations aims to understand selective pressures, and factors whether it be inbreeding or adaptation, that affect the genome. Although numerous techniques are available for assessing population structure, a major obstacle in studying wild populations is obtaining samples from the animals without having to capture them, which can lead to undue distress and injury. Therefore, biologists often use non-invasive sampling methods (i.e., collection of feces, hair) to extract host DNA. In this study, new DNA extraction protocols were developed that improved the quality and quantity of DNA obtained from fecal matter. Fecal samples aged up to Day 6 as well as field samples with unknown days since defecation were successful in individualization of the contributors using microsatellites and were further used to demonstrate kinship. Neutral markers such as short tandem repeat, and mitochondrial D-loop sequences are used for assessing relatedness and evolutionary relationships and can mutate without detrimental effects on the organism. Loci, such as the major histocompatibility complex (MHC), adapt more rapidly under selective pressure such as parasite load, or resistance to diseases and support natural selection processes. Analysis of the neutral microsatellites in Big Summit feral horse population demonstrated a population lacking diversity and trending towards being an inbred population. However, examination of the MHC genes showed maintenance of greater variation that may be the result of selection pressures. The MHC similarity and lower genetic demarcation between geographically separated horse populations further indicated effect of selection pressures in preserving diversity at the MHC genes. Although such molecular markers are used in profiling populations, the current study was also successful in demonstrating the use of individual odor profiles as an additional profiling tool. Volatile organic compounds (VOC) obtained from hair of domestic horses were able to individualize horses as well as differentiate between horse breeds and display kinship. The relation of genetics to odor phenotype is of interest as the inherent polymorphic nature of MHC genes has the potential to generate unique combinations of genotypes that presumably produce distinct odor phenotypes. Subsequently, this study was able to show a significant correlation between MHC genotypes and VOC odor profiles in horses. Understanding the relationship between MHC and odor using domestic horses with known relatedness provides evidence that these same correlations may be applicable to wild equids and dictates their harem hierarchal social structure.

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This research studies the three market-leading RPA-tools, Automation Anywhere, Blue Prism and UiPath, in order to fill the lack of literature regarding methods for evaluating and comparing RPA-tools. Design science research was performed by designing and creating artefacts in the form of process implementations and an evaluative model. A typical process representing a common area of use was implemented using each of the three RPA-tools, in order to create an evaluative model. Official documentation, along with the three implementations, were studied. Evaluative questions specific to RPA-tool evaluation were created based on a quality model for product quality found in the ISO/IEC 25010 standard. Characteristics dependant on organisational context were not included in the evaluation, in order to create an evaluative model which is not dependant on any specific business environment. The results of the research provide knowledge of (1) how RPA-tools can be implemented and (2) the differences that exist between the three market-leading RPA tools. The research also contributes in the form of a method for investigating and evaluating the RPA-tools. When creating the evaluative model, some of the criteria found in the ISO/IEC 25010 quality model were concluded to be of low relevance and, therefore, not included in the model. By analysing and evaluating the created evaluative model, using a theoretical concept of digital resources and their evaluation, the validity of the evaluative model was reinforced. From an evaluative perspective, this research emphasises the need to appropriate and change existing evaluative methods in order to successfully evaluate the most relevant characteristics of RPA-tools. / Denna forskning studerar de tre marknadsledande RPA-verktygen, Automation Anywhere, Blue Prism och UiPath, för att fylla bristen på litteratur om metoder för utvärdering och jämförelse av RPA-verktyg. Design science research genomfördes genom att utforma och skapa artefakter i form av processimplementeringar och en utvärderingsmodell. En typisk process som representerar ett vanligt användningsområde implementerades med användning av vart och ett av de tre RPA-verktygen för att skapa en utvärderingsmodell. Officiell dokumentation, tillsammans med de tre implementeringarna, studerades. Utvärder-ingsfrågor specifika för RPA-verktygsutvärdering skapades baserat på en kvalitetsmodell för produktkvalitet som finns i ISO/IEC 25010-standarden. Egenskaper som är beroende av organisatoriskt sammanhang ingick inte i utvärderingen för att skapa en utvärderingsmodell som inte är beroende av någon specifik affärsmiljö. Resultaten av forskningen ger kunskap om (1) hur RPA-verktyg kan implementeras och (2) skillnaderna som finns mellan de tre marknadsledande RPA-verktygen. Forskningen bidrar också i form av en metod för att undersöka och utvärdera RPA-verktygen. Vid skapandet av utvärderingsmodellen drogs slutsatsen att några av kriterierna i kvalitetsmodellen i ISO/IEC 25010 var av låg relevans och de är därför inte inkluderade i den resulterande modellen. Genom att analysera och utvärdera den skapade utvärderingsmodellen, med hjälp av ett teoretiskt koncept av digitala resurser och deras utvärdering, förstärktes utvärderingsmodellens validitet. Ur ett utvärderingsperspektiv betonar denna forskning behovet av att anpassa och ändra befintliga utvärderingsmetoder för att framgångsrikt utvärdera de mest relevanta egenskaperna hos RPA-verktyg.

Autonomous robots are becoming a bigger part of our society. This thesis aims to evaluate a robot testing dashboard (RTD) that can be used as a new way of finding improvements when developing autonomous robots that do not use machine learning. The method that is used is design science research, which is used when creating and evaluating an artifact to address a practical problem. In our case the artifact isthe RTD. This project was performed at a company called Greenworks, which among other things develops and sells autonomous lawn mowers. The company wants to find new testing methods to help develop their autonomous lawnmowers. The RTD is created to visualize the inputs that the lawn mower utilizes to perform its tasks. A human pilot will then control the lawn mower, by only looking at that visualized data. If the pilot using the RTD can execute the same tasks as the lawn mower in its autonomous mode, the test results can be analyzed to see whether the human has done some parts of the tasks differently. The best outcome from the analysis of the test results is to find areas of improvement that can be implemented into the autonomous lawn mower design, both in software and hardware. For this purpose, an RTD was built and tested at Greenworks. From the tests using the RTD we concluded that it is helpful in the testing process, and we could find areas of improvements after analysis of our tests. However, the use of the RTD will require more time and resources compared to other methods. Each company that uses a similar dashboard concept will have to evaluate if the benefits are worth the time. Furthermore, the concept may not suit all areas of robotics but does seem to suit situations where a human can have an advantage over robots, such as in creative problem solving.

Artificial intelligence (AI) is revolutionizing contemporary industries and being applied in application domains ranging from recommendation systems to self-driving cars. In scenarios in which humans are interacting with an AI, inaccurate algorithms could lead to human mistreatment or even harmful events. Human-in-the-loop computing is a machine learning approach desiring hybrid intelligence, the combination of human and machine intelligence, to achieve accurate and interpretable results. This thesis applies human-in-the-loop computing in a Design Science Research project with a Swedish manufacturing company to make operational processes more efficient. The thesis aims to investigate emerging design principles useful for designing machine learning algorithms of hybrid intelligence. Hereby, the thesis has two key contributions: First, a theoretical framework is built that comprises general design knowledge originating from Information Systems (IS) research. Second, the analysis of empirical findings leads to the review of general IS design principles and to the formulation of useful design principles for human-in-the-loop computing. Whereas the principle of AI-readiness improves the likelihood of strategical AI success, the principle of hybrid intelligence shows how useful it can be to trigger a demand for human-in-the-loop computing in involved stakeholders. The principle of use case-marketing might help designers to promote the customer benefits of applying human-in-the-loop computing in a research setting. By utilizing the principle of power relationship and the principle of human-AI trust, designers can demonstrate the humans’ power over AI and build a trusting human-machine relationship. Future research is encouraged to extend and specify the formulated design principles and employ human-in-the-loop computing in different research settings. With regard to technological advancements in brain-machine interfaces, human-in-the-loop computing might even become much more critical in the future.

Opioids such as morphine are frequently used in the clinic to treat pain. However, the perennial bane of chronic opioid use is the rapid development of tolerance to the analgesic effects but delayed development of tolerance to the respiratory depressant and constipating effects. As constipation is one of the most common opioid-related adverse effects in humans, it is important to delineate mechanisms that drive opioid tolerance in the ileum and lack of it in the colon. The overarching goal of this thesis was to investigate mechanisms of morphine tolerance in the ileum by comparing the mechanism of morphine tolerance in ileum myenteric plexus neurons and dorsal root ganglia (DRG) neurons. Myenteric plexus neurons are integral to the motor function of the ileum, whereas DRG neurons are important components of peripheral nociceptive sensation. We also examined the mechanism of morphine tolerance development to small intestinal transit and to antinociception at the systemic level in male and female mice. Studies presented in this dissertation demonstrate that the mechanism of morphine tolerance in the mouse ileum is not contingent on b-arrestin 2. In fact, tolerance in the small intestine might be mediated by a b-arrestin 2-independent mechanism following protein kinase C-induced phosphorylation of the m-opioid receptor. We also demonstrate that morphine tolerance to antinociception is not solely dependent on b-arrestin 2, and is mediated by b-arrestin 2-dependent and-independent mechanisms. Lastly, we have shown how sex of the animal can influence mechanisms underlying the development of morphine tolerance. Collectively, the findings presented here increase our understanding of the mechanisms by which morphine tolerance develops in the ileum and to antinociception.

C1q TNF Related Protein 3 (CTRP3), is a cytokine that is primarily secreted from adipose tissue, which classifies it as an adipokine. Our previous research has shown that CTRP3 prevents alcoholic fatty liver disease (ALD) in male mice. However, even when accounting for confounding factors such as absolute and relative alcohol intake, females are more sensitive to the effects of consumption compared to male mice. Therefore, the goal of this project was to determine whether CTRP3 prevented ALD in female mice. Methods: Female wild type (WT) and female CTRP3 transgenic over expressing (Tg) mice were fed an ethanol containing liquid diet (5% v/v) for 6 weeks. Daily weight and food intake measurements were taken and external heat-pads were placed under a portion of the cage to facilitate thermoregulation. Hepatic steatosis was determined by total triglyceride quantification and lipid droplet quantitation in liver sections. Data were analyzed by repeated measures ANOVA, t-test, or Log-rank (Mantel-Cox) test as appropriate. Results: There was no difference between WT and Tg mice in food intake or body weight. There was no difference in survival between WT and Tg mice, however, Tg mice trended towards a reduced rate of survival compared with WT mice (78% in WT versus 44% in Tg, p=0.13). Stereological analysis indicated no difference in the percent of lipid liver volume between the two groups (WT 7.2±3.6 vs Tg 5.1±4.1%). This finding was consistent with no difference in total hepatic triglyceride accumulation observed between WT and Tg mice (12.7±4.4 vs. 13.1±6.8 mg triglycerides/gram liver protein). Conclusion: Combined these data indicate that unlike previous studies with male mice, CTRP3 is not protective against alcohol-induced hepatic steatosis in female mice. Combined, these data indicate that the adipokines such as CTRP3 contribute to physiology in a sex-specific manner.

A rising problem exists regarding the ownership of memes. This research proposes a solution consisting of an IT artefact that solves this problem by utilising design science research in combination with affordance theory and non-fungible tokens (NFTs). This artefact is designed by identifying the problem areas and creating affordances that guide the design process, using the design science research methodology by Peffers et al. (2007). The artefact is evaluated and considered a potential solution to the problem with meme ownership. The affordances are connected to the designed features and offer contributions in the form of a novel artefact and documented design processes. By using affordance theory as a lens to help the design, further research can build upon this idea and expand research by combining design science with affordances. The practical implementation of NFTs gives insights into how NFTs can be applied in the case of tokenising digital goods and allows people without knowledge of blockchains to participate.