Patellar Tendinopathy (PT), commonly called "Jumper's Knee", is a condition resulting from repetitive loading of the patellar tendon that presents as anterior knee pain, which is commonly seen in basketball players due to the maneuvers in the sport. Diagnosis of PT often involves a clinical exam followed by ultrasound images for confirmation of the diagnosis to look for key factors of PT. Clinical assessment of ultrasound images of tendons is subjective and requires a high level of experience for reliable interpretation. Thus, there is a need for objective, quantitative methods to assess tendon abnormalities associated with pathology. Ultrasound image texture analysis has emerged as a reliable technique to augment the utility of conventional US imaging, and has recently been shown to distinguish healthy from abnormal tendon and myofascial tissues. The objective of the present study was to conduct image texture analysis to evaluate patellar tendons of collegiate basketball athletes over two seasons. Under an IRB-approved protocol with informed consent, a total of 33 Division 1 collegiate basketball athletes (16 male, 17 female, age 19.9 +/- 1.4 years) underwent clinical evaluation and ultrasound imaging. Four imaging sessions were collected over the course of two years (pre- and post-season). Participants were imaged using a GE LOGIQ S8 (General Electric, USA) ultrasound machine equipped with ML6-15 linear probe. At each imaging session, power Doppler images were collected in the longitudinal and transverse axis, at the proximal, central, and distal regions of the patellar tendon of both knees. Image texture analysis was performed using a custom MATLAB (Mathworks, USA) program to obtain first order (mean, median, variance, skewness, kurtosis, entropy), second order (contrast, energy, and homogeneity), and blob analysis (blob count, BC, and blob area, BA, for 5%, 25%, 50%, 75%, and 95% thresholding values) texture parameters in each image, based upon borders manually drawn by a single researcher. Statistical analysis was conducted to compare imaging sessions (JMP Pro 16, SAS). P-values <0.05 were considered statistically significant. Quantitative texture parameters are able to distinguish characteristics in patellar tendon ultrasound images to distinguish between anatomic region, gender, dominance and pre- to post- season. The 25% and 75% thresholding percentiles effectively showed characteristics of collagen fibers in the patellar tendon. The abnormal diagnosis does not greatly effect texture parameters, which needs to be investigated with more incorporation of grading criteria distinctions and a larger sample size. / Master of Science / Patellar Tendinopathy (PT) is a knee injury that commonly occurs in basketball players. The recovery for PT is often long and the player can still have knee pain when returning to the sport. Diagnosis of PT requires a high level of expertise to consider the patients history, conduct a physical exam and take ultrasound images to look for factors that indicate patellar tendon is damaged. The difficulty of diagnosing PT calls for an objective method to allow for accuracy in assessing patellar tendons. In order to create a more objective measure of ultrasound images, quantitative texture parameters are explored to understand what the brightness values of each pixel and the proximity of pixels together can convey about the image. The objective of this study is to understand what characteristics of the subject (anatomic region, knee dominance, gender, and time point) texture parameters are able to distinguish in patellar tendon ultrasound images.

No description available.

MySQL är ett databassystem som hör till typen relationsdatabaser och lagrar dataenligt relationsdatamodellen och använder sig av frågespråket SQL. MySQL har flertalet datatyper och sedan version 5.7.8 finns datatypen JSON som kan användas för lagring av data med JSON-format. JSON är idag den ledande standarden för datautbyte för webbapplikationer. Ett experiment genomförs där datatyperna JSON, BLOB och TEXT testas i MySQL. Detta för att ta reda på vilken datatyp som är att föredra med avseende på svarstid vid hämtning och uppdatering av specifika värden i lagrad JSON-data. En miljö sätts upp för att genomföra en pilotstudie följt av ett antal tester för att påvisa detta. Resultatet visar på att datatyperna BLOB och TEXT presterar snabbare svarstid än JSON förutom i de fall då specifika funktioneranpassade för datatypen i MySQL används.

Several pyrene-labeled polymers and polypeptides were synthesized and their chain dynamics were characterized using steady-state and time-resolved fluorescence techniques. Firstly, four series of pyrene-labeled polystyrenes (Py-PS) were synthesized to determine the effect that the method used for pyrene attachment, the linker connecting pyrene to the backbone, and the distribution of pyrene along the backbone all have on excimer formation. It was found that the amount of excimer formed was different in each case. The differences were described by utilizing the fluorescence blob model (FBM) analysis of the time-resolved monomer and excimer fluorescence decays. Secondly, two Py-PS series were studied in several different solvents with viscosities ranging from 0.36 to 1.19 mPa.s to demonstrate the effect of viscosity on the FBM parameters. The rate constant for excimer formation within a blob, kblob, was found to remain constant with viscosity while the number of monomer units per blob, Nblob, increased with decreasing viscosity. Thirdly, in a technical note, the inherent analogy existing between the aggregation number of surfactant micelles, Nagg, and Nblob, is taken advantage of to establish a “model-free” procedure to determine Nblob. This procedure was validated through the analysis of the time-resolved fluorescence decays of five different pyrene-labeled polymers in seven different solvents. Fourthly, the side-chain dynamics of alpha-helical pyrene-labeled poly(glutamic acid) were investigated. A longer linker connecting pyrene to the backbone resulted in an increase in Nblob which agreed quantitatively with predictions made by molecular modeling. Decreasing the lifetime of the excited pyrene from 215 ns to 50 ns with a quencher increased kblob significantly, while Nblob decreased slightly. Finally, the backbone dynamics of pyrene-labeled poly(aspartic acid) (Py-PAA) were investigated and quantified using the FBM. It was determined that excimer formation was controlled by the very rigid polypeptide backbone and not by the solvent viscosity, contrary to previous results obtained with other pyrene-labeled vinyl polymers.

Several pyrene-labeled polymers and polypeptides were synthesized and their chain dynamics were characterized using steady-state and time-resolved fluorescence techniques. Firstly, four series of pyrene-labeled polystyrenes (Py-PS) were synthesized to determine the effect that the method used for pyrene attachment, the linker connecting pyrene to the backbone, and the distribution of pyrene along the backbone all have on excimer formation. It was found that the amount of excimer formed was different in each case. The differences were described by utilizing the fluorescence blob model (FBM) analysis of the time-resolved monomer and excimer fluorescence decays. Secondly, two Py-PS series were studied in several different solvents with viscosities ranging from 0.36 to 1.19 mPa.s to demonstrate the effect of viscosity on the FBM parameters. The rate constant for excimer formation within a blob, kblob, was found to remain constant with viscosity while the number of monomer units per blob, Nblob, increased with decreasing viscosity. Thirdly, in a technical note, the inherent analogy existing between the aggregation number of surfactant micelles, Nagg, and Nblob, is taken advantage of to establish a “model-free” procedure to determine Nblob. This procedure was validated through the analysis of the time-resolved fluorescence decays of five different pyrene-labeled polymers in seven different solvents. Fourthly, the side-chain dynamics of alpha-helical pyrene-labeled poly(glutamic acid) were investigated. A longer linker connecting pyrene to the backbone resulted in an increase in Nblob which agreed quantitatively with predictions made by molecular modeling. Decreasing the lifetime of the excited pyrene from 215 ns to 50 ns with a quencher increased kblob significantly, while Nblob decreased slightly. Finally, the backbone dynamics of pyrene-labeled poly(aspartic acid) (Py-PAA) were investigated and quantified using the FBM. It was determined that excimer formation was controlled by the very rigid polypeptide backbone and not by the solvent viscosity, contrary to previous results obtained with other pyrene-labeled vinyl polymers.

Det finns intresse för att forska på data från Github. Genom ett API, Github REST API, kan man få data från Github i JSON-format som sen kan lagras i en databas för forskning och analysering. Från och med MySQL 5.7.8 finns det en specifik datatyp för JSON, men det finns även argument för respektive datatyp för BLOB. Med tanke på att stor vikt ligger på databasen för att erhålla snabbhet, effektivitet och bearbetning av data analyseras respektive datatyp för att avgöra vilken datatyp som presterar bäst vid hämtning av data. Genom att utföra ett experiment där tiden det tar för databasen att hantera en fråga påvisar resultatet vilken datatyp som är mest lämplig. Resultatet visar att respektive datatyp för BLOB presterar bättre än datatypen JSON, särskilt ju större JSON-objekten är.

Den här studien jämför bildhanteringsprestanda mellan tre olika relationsdatabashanterare.MySQL, MariaDB och PostgreSQL jämförs för att se vilken databashanterare som kan hämtabilder med kortast svarstid. I den här studien utförs experiment för att svara på frågan:“Vilken databas av MySQL, MariaDB och PostgreSQL kommer ha den kortaste svarstidenfrån att en request att visa en bild till att den är hämtad och utritad på skärmen.”. Fråganbesvaras genom att mäta svarstider för respektive databashanterare. Resultatet indikerar attMariaDB hämtar bilder med kortast svarstid i de fall en bild hämtas per sökning, medanPostgreSQL hämtar bilder med kortast svarstid när flera bilder hämtas per sökning. Iframtiden är det intressant att utöka studien med fler databashanterare, samt testa flerbildformat och bildstorlekar.

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The ability to count people from video is a challenging problem. The scientific challenge arises from the fact that although the task is pretty well defined, the imaging scenario is not well constrained. The background scene is uncontrolled. Lighting is complex and varying. And, image resolution, both in terms of spatial and temporal is usually poor, especially in pre-stored surveillance videos. Passive counting of people from video has many practical applications such as in monitoring the number of people sitting in front of a TV set, counting people in an elevator, counting people passing through a security door, and counting people in a mall. This has led to some research in automated counting of people. The context of most of the work in people counting is in counting pedestrians in outdoor settings or moving subjects in indoor settings. There is little work done in counting of people who are not moving around and very little work done in people counting that can handle harsh variations in illumination conditions. In this thesis, we explore a design that handles such issues at pixel level using photometry based normalization and at feature level by exploiting spatiotemporal coherence that is present in the change seen in the video. We have worked on home and laboratory dataset. The home dataset has subjects watching television and the laboratory dataset has subjects working. The design of the people counter is based on video data that is temporally sparsely sampled at 15 seconds of time difference between consecutive frames. Specific computer vision methods used involves image intensity normalization, frame to frame differencing, motion accumulation using autoregressive model and grouping in spatio-temporal volume. The experimental results show: The algorithm is less susceptible to lighting changes. Given an empty scene with just lighting change it usually produces a count of zero. It can count in varying illumination conditions. It can count people even if they are partially visible. Counts are generated for any moving objects in the scene. It does not yet try to distinguish between humans and non-humans. Counting errors are concentrated around frames with large motion events, such as a person moving out from a scene.

Idag används vanligtvis lösenord som autentiseringsmetod i moderna applikationer. Men allt fler företag och applikationer övergår från denna metod och i stället använda krypterade nycklar och certifikat för att öka säkerheten. Dessutom har telefoner och datorer utvecklats som har hårdvarusäkerhetsmoduler för att lagra och skydda sådan information. Projektet utgick på att bekanta sig med olika kryptografiska standarder i en modern webbläsare, med fokus på WebAuthn. Därefter utvecklades och designades en Proof Of Concept-applikation i Amazon webservice som använde sig av WebAuthn för autentisering. Tilläggsfunktioner som möjliggör återanvändning av den privata nyckeln som genereras av WebAuthn implementerades och testades. Dessa tillägg inkluderar pseudo-random function (PRF) och large blob. Resultatet blev en fungerande webbapplikation i Amazon webservice som använder sig av WebAuthn-standarden där en användare har möjlighet att registrera samt autentisera sig med hjälp av biometriska metoder i stället för lösenord. Implementationen av tillägg för återanvändning av privata nycklar visade sig vare en utmaning. Tekniska svårigheter med webbläsare, protokoll och autentiseringsenheter, samt det faktum att WebAuthn-standarden är relativt ny, påverkade implementationen av tilläggen. Det kan vara värt att notera att med tiden kommer fler webbläsare och autentiseringsenheter troligtvis stödja dessa funktioner, vilket kan möjliggöra återanvändning av privata nycklar. Avslutningsvis visade projektet att det är möjligt att skapa en webbapplikation i Amazon webservice som använder sig av WebAuthN-standarden och möjliggör autentisering med biometriska metoder. Trots de tekniska utmaningarna med pseudo-random function (PRF) och large blob, är det en lovande riktning för framtida implementeringar när standarden mognar och stöd för tilläggsfunktionerna förbättras. / Today, passwords are commonly used as an authentication method in modern applications. However, more and more companies and applications are moving away from this method and instead using encrypted keys and certificates to increase security. Additionally, phones and computers have been developed that have hardware security modules to store and protect such information. The project was based on getting to know different cryptographic standards in a modern browser, with a focus on WebAuthn. Next, a Proof-of-Concept application was developed and designed in AWS that used WebAuthn for authentication. Additional features that allow reuse of the private key generated by WebAuthn were implemented and tested. These extensions include pseudo-random function (PRF) and large blob. The result was a functioning web application in AWS that uses the WebAuthn standard where a user can register and authenticate themselves using biometric methods instead of passwords. The implementation of private key reuse extensions proved to be a challenge. Technical difficulties with browsers, protocols, and authenticators, as well as the fact that the WebAuthnstandard is relatively new, affected the implementation of the extensions. It may be worth noting that over time, more browsers, and authentication devices will likely support these features, which may allow private key reuse. In conclusion, the project showed that it is possible to create a web application in AWS that uses the WebAuthn-standard and enables authentication with biometric methods. Despite the technical challenges with pseudo-random function (PRF) and large blob, it is a promising direction for future implementations as the standard matures and support for the extension functions improves.