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Norr om Järna vid den befintliga hästgården Bergtorp fanns förutsättningar för en ny typ av byggnad som kombinerar flera aktiviteter. Hästarnas betydelse på platsen fick genomsyra Folkets hus genom en ridhall med diversitet och flexibilitet för ett hållbart socialt liv i landsbygden. Ladans betydelse och historia i lantbruksorten Järna är den stora inspirationen till mitt Folkets Hus. Den långa strukturen med sadeltak liknar en lada till form och färg, men formgivning och interiör skapar en ny tolkning där en samtida mötesplats för flera målgrupper står i fokus. Byggnaden består av ett yttre och ett inre skal som tillsammans skapar en ytterligare dimension när ljus och årstid påverkar de skuggor som skapas. Målet har varit att skapa en byggnad där flera målgrupper känner sig delaktiga även om de inte deltar aktivt i den aktivitet som sker. Det har möjliggjorts genom en öppning i bjälklaget som förbinder Folkets hus med ridhallen. Genom hållbara val, såväl materialmässigt som socialt, hålls landsbygden levande och kan nyttjas av flera generationer. / North of Järna at the existing horse farm Bergtorp were conditions for a new type of building which combines several activities. The importance of the horses at the chosen spot was permeated in the People's house through a riding hall with diversity and flexibility for a sustainable social life in the rural.  The significance and history of the barn in the agricultural town of Järna is the main inspiration for my People's house. The long structure with a saddle roof resembles a barn in shape and form, however design and interior creates a new interpretation where a contemporary meeting place for several target groups is the main focus. The building consists of an outer and an inner shell that together creates an additional dimension when light and season affects the shadows created. The goal has been to create a building where several target groups feels involved even if they don't actively participate in the activity that takes place. It has been made possible through an opening in the floor which connects the People's house with the riding hall. Through sustainable choices, both materially and socially, the countryside is kept alive and can be used by several generations.

<p> Effects of electron correlations on a two dimensional quantum spin Hall system are studied. We examine possible phases of a generalized Hubbard model on a bilayer honeycomb lattice with a spin-orbit coupling and short range electron-electron repulsions at half filling, based on the slave rotor mean-field theory. The phase diagram of the model is found for a special case where the interlayer Coulomb repulsion is comparable to the intralayer Coulomb repulsion.</p> <p> Besides the conventional quantum spin Hall phase and a broken-symmetry insulating phase, we find a new phase, a fractionalized quantum spin Hall phase, where the quantum spin Hall effect arises for fractionalized spinons which carry only spin but not charge. Experimental manifestations of the exotic phase and effects of fluctuations beyond the saddle point approximation are also discussed.</p> <p> We finally study a toy Bose-Hubbard model for the charge sector of the theory to gain some insight into the phase diagram away from the special Coulomb repulsion values.</p> / Thesis / Master of Science (MSc)

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The Goodwin Hall building on the Virginia Tech campus is the most instrumented building for vibration monitoring. It houses 225 hard-wired accelerometers which record vibrations arising due to internal as well as external activities. The recorded vibration data can be used to develop real-time applications for monitoring the health of the building or detecting human activity in the building. However, the lack of infrastructure to handle the massive scale of the data, and the steep learning curve of the tools required to store and process the data, are major deterrents for the researchers to perform their experiments. Additionally, researchers want to explore the data to determine the type of experiments they can perform. This work tries to solve these problems by providing a system to store and process the data using existing big data technologies. The system simplifies the process of big data analysis by supporting code re-usability and multiple programming languages. The effectiveness of the system was demonstrated by four case studies. Additionally, three visualizations were developed to help researchers in the initial data exploration. / Master of Science / The Goodwin Hall building on the Virginia Tech campus is an example of a ‘smart building.’ It uses sensors to record the response of the building to various internal and external activities. The recorded data can be used by algorithms to facilitate understanding of the properties of the building or to detect human activity. Accordingly, researchers in the Virginia Tech Smart Infrastructure Lab (VTSIL) run experiments using a part of the complete data. Ideally, they want to run their experiments continuously as new data is collected. However, the massive scale of the data makes it difficult to process new data as soon as it arrives, and to make it available immediately to the researchers. The technologies that can handle data at this scale have a steep learning curve. Starting to use them requires much time and effort. This project involved building a system to handle these challenges so that researchers can focus on their core area of research. The system provides visualizations depicting various properties of the data to help researchers explore that data before running an experiment. The effectiveness of this work was demonstrated using four case studies. These case studies used the actual experiments conducted by VTSIL researchers in the past. The first three case studies help in understanding the properties of the building whereas the final case study deals with detecting and locating human footsteps, on one of the floors, in real-time.

The purpose of this work was to determine the liquidus surface of the cryolite-rich portion of the ternary system Na₃AlF₆-CaF₂-AlF₃ and to establish the effect of Al₂O₃ on the operation of the Hall cell electrolysis. A series of isotherm of the cryolite-rich portion were graphed. It was shown that pseudo-binary phase diagrams of Al₂O₃ and bulk composition in the cryolite-rich portion of the Na₃AlF₆-CaF₂-AlF₃ system were found to be simple eutectic. The temperatures and the alumina contents of the double solubility limit, two important parameters for the Hall cell, of the joins 95 Na₃AlF₆/5 AlF₃-Na₃AlF₆, 90 Na₃AlF₆/ 10 NaCaAlF₆ and 85 Na₃AlF₃/15 AlF₃-NaCaAlF₆ were determined. The cryolite liquidus temperature of the quaternary system Na₃AlF₆-CaF₂-AlF₃-Al₂O₃ was found to be expressed by: T_Liq.. (C) = 1009.4 + 4.059(CaF₂) - 1.167(CaF₂)² + 0.968 x (CaF₂)(AlF₃) - 0.105(CaF₂)(AlF₃)² + 0.073 x (CaF₂)²(AlF₃) + 0.002(CaF₂)² (AlF₃)² - 4.165 x (AlF₃) - 0.054(AlF₃)² - 5.33(Al₂O₃) for CaF₂ 3.8~11.25%, AlF₃ 5~20%. / M.S.

A residence hall is a temporary home. Yet, it can be the most impactful campus environment on a student's education and life. From lifelong friendships to retention rates, residence halls affect students as many experience their first opportunity to express their individuality and personal responsibility. No study can conclusively determine that one residence hall type is better than another. Rather, it is a hall's overall gestalt that determines student satisfaction and a positive perception of community. The question of my thesis explores how residence hall architecture can anticipate its role as an inspiring distraction to the individual that provokes interaction, engagement, and community as a building type that is not quite transient and not quite permanent. / Master of Architecture

The ability to classify occupants in a building has far-reaching applications in security, monitoring human health, and managing energy resources effectively. In this work, gender and weight of walkers are classified via machine learning or pattern recognition techniques. Accelerometers mounted beneath the floor of Virginia Tech's Goodwin Hall measured walkers' gait. These acceleration measurements serve as the inputs to machine learning techniques allowing for classification. For this work, the gait of fifteen individual walkers was recorded via fourteen accelerometers as they, alone, walked down the instrumented hallway, in multiple trials. These machine learning algorithms produce an 88 % accurate model for gender classification. The machine learning algorithms included are Bagged Decision Trees, Boosted Decision Trees, Support Vector Machines (SVMs), and Neural Networks. Data reduction techniques achieve a higher gender classification accuracy of 93 % and classify weight with 64% accuracy. The data reduction techniques are Discrete Empirical Interpolation Method (DEIM), Q-DEIM, and Projection Coefficients. A two-part methodology is proposed to implement the approach completed in this thesis work. The first step validates the algorithm design choices, i.e. using bagged or boosted decision trees for classification. The second step reduces the walking data measured to truncate accelerometers which do not aid in increasing characteristic classification. / Master of Science