In this essay, I will examine the theory of territorial rights developed by Anna Stilz. The overarching project of hers is to defend a system of territorially sovereign states, the defense of which is grounded in the natural rights of individuals to personal autonomy and self-preservation. She begins her theoretic project by arguing for the plausibility of the preinstitutional occupancy right, intended to grant individuals usage-rights over the earth, existing irrespective of social or moral conventions, formally defined as follows: “Occupancy Rights. A person has a preinstitutional right to occupy a particular area if (1) access to spaces in that area is fundamental to his located life plans and (2) his connection to the territory was established without any wrongdoing on his part, involving (at a minimum) no expulsion or wrongful interference with prior occupants or infringement of others’ claims to an equitable distribution of geographical space.” The condition of equitable distribution expresses a concern for proportionality.  It seems as if Stilz believes that no territorial holding will be legitimate unless it is of an appropriate scale, with regard to the holdings of others. This condition is referred to by Stilz as the fair-use proviso. The fair-use proviso concerns the occupancy claims made by individuals. Stilz also introduces conditions for a legitimate global distribution of territory, named as the full proviso. Stilz’ defines the full proviso as follows: (conditions for a legitimate global distribution of territory): “The full proviso hold that a just distribution of the earth’s spaces must (i) satisfy everyone’s basic territorial interests and (ii) grant groups with shared practice-based interests the right to use geographical space in ways that reflect these interests, so long as the groups are of sufficient size, and so far as this is institutionally feasible.” For an individual occupancy claim to be legitimate is simply that it is consistent with the conditions for a legitimate global distribution of territory, i.e. the full proviso. The full proviso and the fair-use proviso are thus inseparable parts of a whole. In what follows, if not specified otherwise, I will alternate in referring to the fair-use proviso as the fair-use proviso or simply the proviso. The full proviso will always be italicized when discussed.  The purpose of this essay is to investigate whether the fair-use proviso is satisfying in the face of some criticism. In completing this task, I will draw on an objection put forth by Lea Ypi. The objection as formulated by her is not in direct response to Stilz, however I believe we might draw on her work to formulate a powerful objection from scarcity to Stilz’ fair-use proviso. The question at stake in this essay is thus if the objection of scarcity is successful against Stilz’ fair-use proviso.

abstract: Human land use and land cover change alter key features of the landscape that may favor habitat selection by some species. Lizards are especially sensitive to these alterations because they rely on their external environment for regulating their body temperature. However, because of their diverse life-history traits and strategies, some are able to respond well to disturbance by using their habitat in various ways. To understand how they use their habitat and how human modifications may impact their ability to do this, biologists must identify where they occur and the habitat characteristics on which they depend. Therefore, I used species occupancy modeling to determine (1) whether disturbance predicts the presence of two sympatric congeneric (species of the same genus) lizard species Sceloporus grammicus and S. torquatus, and (2) which habitat characteristics are essential for predicting their occupancy and detection. I focused my study in central Mexico, a region of prevalent land use and land cover change. Here, I conducted visual encounter and habitat surveys at 100 1-hectare sites during the spring of 2019. I measured vegetation and ground cover, average tree diameter, and abundance of refuges. I recorded air temperature, relative humidity, and elevation. I summarized sites as either undisturbed or disturbed, based on the presence of human development. I also summarized sites by ecosystem type, desert or forest, based on vegetation composition (i.e., desert-adapted vs. non-desert-adapted plants), evidence of remnant forest, air temperature, and relative humidity. I found that S. torquatus was more likely to be present in disturbed habitat, whereas S. grammicus was more likely to be present in areas with leaf litter, tree cover, and woody debris. S. torquatus was twice as likely to be detected in forests than deserts, and S. grammicus was more likely to be detected at sites with high elevation and high relative humidity, low temperature, and herbaceous and grass cover. These results emphasize the utility of species occupancy modeling for estimating detection and occupancy in dynamic landscapes. / Dissertation/Thesis / Masters Thesis Biology 2020

The eastern whip-poor-will (Antrostomus vociferus: hereafter whip-poor-will) has been declining from historical population levels throughout its range in the northeast. Although whip-poor-wills have been reported to use a variety of habitats, most recent studies have associated whip-poor-wills with open habitat, such as early-successional habitats or forest edges. Population declines of other early-successional bird species have been attributed to the loss of early-successional disturbance-dependent habitats in the northeast, and it has been suggested that habitat loss is a significant factor in whip-poor-will population declines, as well. However, there remain substantial gaps in our understanding of whip-poor-will habitat associations, and quantitative habitat data in the literature are lacking. As forest management plays an important role in creating and maintaining habitat for many disturbance-dependent bird species, further characterization of whip-poor-will habitat preferences is necessary to determine whether management efforts may benefit this species as well. In order to derive quantitative estimates of habitat requirements, I studied whip-poor-will habitat associations at Fort Drum in upstate New York. In 2015 and 2016, whip-poor-wills were surveyed at night at randomly-selected point count locations and vegetation measurements were collected in the point count radii to relate whip-poor-will occupancy with structural and compositional habitat variables. Whip-poor-will occupancy was strongly related to intermediate amounts of basal area, with values that generally correspond to forest denser than most shrublands, but more open than closed-canopy forest. Occupancy was also related to lower understory height values, which supports evidence that whip-poor-wills may prefer habitat with a relatively open understory. In 2016, I also measured habitat at locations where whip-poor-wills were foraging, roosting, and nesting, to investigate the theory that whip-poor-wills require open habitat for foraging, but more closed habitat for nesting. Ten adult whip-poor-wills were tracked using radio telemetry and vegetation measurements were collected at a subset at these points where the birds were either foraging or roosting during the day, as well as at any identified nest sites. Comparisons of the vegetation measurements revealed that foraging habitat was significantly more open than roosting habitat, as foraging habitat had lower tree density, basal area, and understory height. Contrary to conventional thought, the few nest sites found in this study were in areas that had low basal area, similar to the habitat at foraging locations. The results suggest that while creating more open-canopy habitat may benefit whip-poor-wills by providing suitable foraging habitat, and potentially nesting habitat, maintaining denser forest within proximity to these open areas may also provide valuable cover for roosting whip-poor-wills. In conclusion, I suggest that land owners looking to create or maintain suitable habitat for whip-poor-wills apply forest management treatments that create openings but still maintain intermediate levels of basal area, such as shelterwood or group tree selection. Foraging habitat for whip-poor-wills appears to be generally more open than roosting habitat, both in terms of lower basal area and a more open understory, so having areas where tree and understory removal is concentrated in proximity to areas that are denser may also benefit this species.

The ways that people use libraries have changed drastically over the past few decades. Proliferation of computers and the internet have led to the purpose of libraries expanding from being only places where information is stored, to spaces where people teach, learn, create, and collaborate. Due to this, the ways that people occupy the space in a library have also changed. To keep up with these changes and improve patron experience, institutions collect data to determine how their spaces are being used. This thesis involves the development a system that collects, stores, and analyzes data relevant to occupancy to learn how a space is being utilized. Data is collected from a temperature and humidity sensor, passive Infrared sensor, and an Infrared thermal sensor array to observe people as they occupy and move through a space. Algorithms were developed to analyze the collected sensor data to determine how many people are occupying a space or the directions that people are moving through a space. The algorithms demonstrate the ability to track multiple people moving through a space as well as count the number of people in a space with an RMSE of roughly 0.39 people.

Luleå kommun (2008) har en vision om att år 2050 ska det dagliga livet gå att klara utan egen bil och det ska vara möjligt för alla att säkert ta sig fram kollektivt eller till fots. Samtidigt visar många studier på att fotgängare står för ca en tredjedel av alla som skadas i trafiken och är därmed den mest utsatta gruppen i trafiken (bland annat Öberg 2011 och Nilsson 1986). Den officiella statistiken i Sverige, som rapporterats från polisen, exkluderar singelolyckor för fotgängare då det inte anses vara en vägtrafikolycka då inget fordon varit inblandad (Trafikverket 2016). Det finns även ett stort mörkertal i registreringen och troligen redovisas endast 35-50 % av det faktiska antalet trafikskadade personer i landet (Vägverket 2007). Åtgärder och utredningar sker konstant i landet och antalet olyckor minskar för varje år, men inte i utsträckning för att nå nollvisionen inom en snar framtid (Larsson 2009). Många studier visar på att personer över 65 år löper stor risk att omkomma i trafiken på grund av att de är skörare och mindre toleranta mot krockvåldet (Vägverket konsult 2007). Av dödsfallen för fotgängare har 66 skett på eller i närheten av övergångsställen (Larsson 2009). Två av tre som omkommer på övergångställen är 65 år eller äldre (Vägverket konsult 2007). Åldersgruppen 65 år och äldre utgör 19-20 % av befolkningen, vilket motsvarar närmare 1,9 miljoner personer (Brundell 2014). Det är sedan länge känt att den bebyggda miljön påverkar vårt sätt att röra oss, men hur påverkar den vår säkerhet och upplevda trygghet? Detta utreds genom att studera olycksstatistiken för fotgängare från Strada med dels avgränsning Luleå centrum och dels med avgränsning kring 6 övergångsställen i Luleå centrum – som även utreds via en gåtur och via platsinventering. Olycksstatistiken från Strada ger en inblick i säkerheten för fotgängare medan gåturen ger en inblick i äldre fotgängares säkerhet och upplevda trygghet. Platsinventeringen beskriver den bebyggda miljön och dessa fyra olika metoder ger slutligen en indikator på faktorer i den bebyggda miljön som påverkar säkerheten och tryggheten på övergångsställen i Luleå centrum. De flesta fotgängarolyckor som rapporterats i Luleå centrum under perioden 2003-2014 berodde på ojämn terräng och dålig sikt för fordonsförarna i fordonet som de blev påkörda av. De faktorer som främst påverkar säkerheten och tryggheten för fotgängare på de 6 övergångsställen som undersökts i detta arbete är hastigheten på övriga trafikslag, belysningen, sikten, uppmärksamheten av fordon och vägunderlaget/terrängen. Resultatet från gåturen visar på att människors närvaro inte har så stor påverkan på den upplevda tryggheten. Belysningen från busshållplatser och affärer har desto större påverkan på tryggheten. Däremot upplevde många att andra människor bidrar till en ökad uppmärksamhet från fordon, vilket minskar risken att bli påkörd, dvs. ökar säkerheten. Deltagarna ansåg att separeringen av cyklister och gående bidrog till en tryggare känsla, men där framkomligheten för cyklister var prioriterade hade cyklisterna för höga hastigheter vilket gav motsatt effekt för säkerheten och tryggheten för fotgängarna.

Though the American marten (Martes americana) is widely distributed across northern North America, habitat use and population abundance vary widely across the range. Due to its status as a furbearer, the species has been extensively researched, resulting in a large body of knowledge about the species’ ecology, distribution, and abundance, as well as drivers of population structure and dynamics. More recently, marten research has shifted focus to genetics, habitat associations, and estimation of population state variables. The rapid increase in estimation of states such as occupancy, abundance, and density has likely been driven by the increasing accessibility of noninvasive field technology, such as noninvasive genetic sampling and remote camera trapping, and by the statistical development of ecological hierarchical models. This convergence of advances in field and analytical methods is most apparent in the now widespread application of spatial capture-recapture, an approach that produces robust estimates of population densities and abundance that can be compared across time and space. These new models are especially valuable near the edges of marten distribution where populations are often recovering from historic overexploitation, and expanding into areas they have previously been absent from. In these areas, detailed, landscape-scale understanding of marten populations is necessary in order to establish current conditions, effectively monitor changes, and predict what effect management actions may have on marten populations. I utilized these models to study marten populations in New Hampshire where marten are a species of management interest, and recent recovery has led to their removal from the state endangered species list. Through a collaborative effort with New Hampshire Fish and Game Department in the winters of 2017 and 2018, marten were surveyed across northern New Hampshire using a novel camera trap design that allows for the identification of individuals. These data were analyzed using spatial capture-recapture models, allowing me to evaluate habitat associations that explain spatial variation in marten density and provide a population status assessment for the New Hampshire marten population. Marten densities are highest in the White Mountain National Forest, though other protected lands in northern New Hampshire also appear to support larger populations. The greatest population densities coincided with deeper snows, increased canopy closure, and intermediate boreal biomass. These results provide additional support for several hypotheses explaining marten habitat use across their range while also providing novel insight that will inform active management of both marten and the habitat they occur in. In addition to the population status assessment, I evaluated the relationship between estimates of occupancy and density in New Hampshire. Though utility of non-invasive methodology can decrease research costs, the need for individual identification in spatial capture-recapture models represents a cost increase over occupancy models. My results suggest that the two are positively correlated; however, occupancy is a poor predictor of the entire range of density, especially because the variables used to predict each of the state variables are different. Thus, occupancy is likely not a good proxy for density in New Hampshire, however it could be used to track general trends through time so long as density is re-evaluated periodically.

Self-driving cars have recently become a challenging research topic, with the aim of making transportation safer and more efficient. Current advanced driving assistance systems (ADAS) allow cars to drive autonomously by following lane markings, identifying road signs and detecting pedestrians and other vehicles. In this thesis work we improve the robustness of autonomous cars by designing an on-road obstacle detection system. The proposed solution consists on the low-level fusion of radar and lidar through the occupancy grid framework. Two inference theories are implemented and evaluated: Bayesian probability theory and Dempster-Shafer theory of evidence. Obstacle detection is performed through image processing of the occupancy grid. Last, the Dempster-Shafer additional features are leveraged by proposing a sensor performance estimation module and performing advanced conflict management. The work has been carried out at Volvo Car Corporation, where real experiments on a test vehicle have been performed under different environmental conditions and types of objects. The system has been evaluated according to the quality of the resulting occupancy grids, detection rate as well as information content in terms of entropy. The results show a significant improvement of the detection rate over single-sensor approaches. Furthermore, the Dempster-Shafer implementation may slightly outperform the Bayesian one when there is conflicting information, although the high computational cost limits its practical application. Last, we demonstrate that the proposed solution is easily scalable to include additional sensors.

Since white-nose syndrome (WNS) arrived in the northeastern U.S. in 2006, several affected bat species have exhibited marked population declines (> 90%). For areas such as Fort Drum in northern New York that are subject to regulatory mandates because of the presence of the endangered Indiana bat (Myotis sodalis), acoustic monitoring is now likely more effective than traditional capture methodologies. In the summers of 2011 and 2012, I implemented intensive acoustic sampling using Anabat detectors at Fort Drum to develop a summer acoustic monitoring protocol that is both cost efficient and effective at detecting species of high conservation or management interest, such as the Indiana bat and the little brown bat (Myotis lucifugus). Habitat analysis of radio telemetry data and occupancy models of acoustic data were congruent in confirming nocturnal spatial use of forested riparian zones by little brown bats.  Additionally, occupancy models of passive versus active sampling revealed that passive acoustic sampling is preferable to active sampling for detecting declining species in the post-WNS context. Finally, assessment of detection probabilities at various arrays of acoustic detector layouts in an expected area of use revealed that a grid of detectors covering a wide spatial extent was more effective at detecting Indiana and little brown bats than permanent stations, transects, or double transects. My findings suggest that acoustic monitoring can be affectively implemented for monitoring Indiana and little brown bats even in areas of severe decline. Future efforts should be aimed at determining effective sampling designs for additional declining species. / Master of Science

The need for faster and more reliable logistics solutions is rapidly increasing. This is due to higher demands on the logistical services to improve quality,  quantity, speed and reduce the error tolerance. An arising solution to these increased demands is automated solutions in warehouses, i.e., automated material  handling. In order to provide a satisfactory solution, the vehicles need to be smart and able to solve unexpected situations without human interaction.  The purpose of this thesis was to investigate if obstacle detection and avoidance in a semi-unknown environment could be achieved based on the data from a 2D LIDAR-scanner. The work was done in cooperation with the development of a new load-handling vehicle at Toyota Material Handling. The vehicle is navigating from a map that is created when the vehicle is introduced to the environment it will be operational within. Therefore, it cannot successfully navigate around new unrepresented obstacles in the map, something that often occurs in a material handling warehouse. The work in this thesis resulted in the implementation of a modified occupancy grid map algorithm, that can create maps of previously unknown environments if the position and orientation of the AGV are known. The generated occupancy grid map could then be utilized in a lattice planner together with the A* planning algorithm to find the shortest path. The performance was tested in different scenarios at a testing facility at Toyota Material Handling.  The results showed that the occupancy grid provided an accurate description of the environment and that the lattice planning provided the shortest path, given constraints on movement and allowed closeness to obstacles. However, some performance enhancement can still be introduced to the system which is further discussed at the end of the report.  The main conclusions of the project are that the proposed solution met the requirements placed upon the application, but could benefit from a more efficient usage of the mapping algorithm combined with more extensive path planning. / <p>Digital framläggning</p>

Mänskligt igenkännande med användning av sensorer och maskininlärning är ett fält med många praktiska tillämpningar. Det finns några kommersiella produkter som på ett tillförlitligt sätt kan känna igen människor med hjälp av videokameror. Dock ger videokameror ofta en oro för inkräktning i privatlivet, men genom att läsa det relaterade arbetet kan man hävda att i vissa situationer är en videokamera inte nödvändigtvis mer tillförlitlig än billiga, icke-inkräktande sensorer. Att känna igen antalet människor i ett litet studie / kontorsrum är en sådan situation. Även om det har gjorts många framgångsrika studier för igenkänning av människor med olika sensorer och maskininlärningsalgoritmer, kvarstår en fråga om vilken kombination av sensorer och maskininlärningsalgoritmer som är allmänt bättre. Denna avhandling utgår från att testa fem lovande sensorer i kombination med sex olika maskininlärningsalgoritmer för att bestämma vilken kombination som överträffade resten. För att uppnå detta byggdes en arduino prototyp för att samla in och spara läsningarna från alla fem sensorer i en textfil varje sekund. Arduinon, tillsammans med sensorerna, placerades i ett litet studierum på Malmö universitet för att samla data vid två separata tillfällen medan studenterna använde rummet som vanligt. Den insamlade datan användes sedan för att träna och utvärdera fem maskininlärningsklassificerare för var och en av de möjliga kombinationerna av sensorer och maskininlärningsalgoritmer, för både igenkänningsdetektering och igenkänningsantal. I slutet av experimentet konstaterades det att alla algoritmer kunde uppnå en precision på minst 90% med vanligtvis mer än en kombination av sensorer. Den högsta träffsäkerheten som uppnåddes var 97%. / Human recognition with the use of sensors and machine learning is a field with many practical applications. There exists some commercial products that can reliably recognise humans with the use of video cameras. Video cameras often raises a concern about privacy though, by reading the related work one could argue that in some situations a video camera is not necessarily more reliable than low-cost, non-intrusive, ambient sensors. Human occupancy recognition in a small sized study/office room is one such situation. While there has been a lot of successful studies done on human occupancy recognition with various sensors and machine learning algorithms, a question about which combination of sensors and machine learning algorithms is more viable still remains. This thesis sets out to test five promising sensors in combination with six different machine learning algorithms to determine which combination outperformed the rest. To achieve this, an arduino prototype was built to collect and save the readings from all five sensors into a text file every second. The arduino, along with the sensors, was placed in a small study room at Malmö University to collect data on two separate occasions whilst students used the room as they would usually do. The collected data was then used to train and evaluate five machine learning classifier for each of the possible combinations of sensors and machine learning algorithms, for both occupancy detection and occupancy count. At the end of the experiment it was found that all algorithms could achieve an accuracy of at least 90% with usually more than one combination of sensors. The highest hit-rate achieved was 97%.