If researchers are able to derive usability simply by analysing gaze data it provides a quick, objective and potentially automatic way of measuring the usability of an interface. In order to do that it is essential to know which traits of the gaze data that have an impact on usability. This paper investigates these traits by analysing different eye tracking metrics in the data. The goal is to see which of these metrics have a general correlation with usability. Previous research provides a clue about which metrics are useful when analysing usability. However, much of the research is based on subjective analysis or lacks in general applicability. This research provides an objective analysis that is independent of characteristics of the interface. A user study is done on 20 participants. They complete tasks on nine different ecommerce websites while their eye movements are recorded. Correlation is measured between usability and eye tracking metrics in order to investigate which metrics that are sensitive to changes in usability. The results show that fixational backtracks and number of fixations have the strongest correlation with usability. Previous research did suggest that both of these eye tracking metrics have an impact on usability. / Om det är möjligt för forskare att härleda användbarhet endast genom att analysera ögondata så tillhandahålls ett snabbt, objektivt och potentiellt automatiserat sätt att mäta användbarheten hos ett gränssnitt. För att göra detta är det avgörande att veta vilka karakteristiska drag i ögondatan som påverkar användbarheten. Denna rapport utforskar dessa drag genom att analysera olika mått i ögondatan. Målet är att se vilka av dessa mått som uppvisar en generell korrelation med användbarhet. Tidigare forskning förser oss med ledtrådar om vilka mått som är lämpliga att analysera när användbarhet ska mätas. Dock så är mycket av denna forskning baserad på subjektiv analys eller saknar generell tillämpbarhet. Denna rapport tillhandahåller en objektiv analys som är oberoende av karakteristiken hos gränssnittet. En användarstudie utförs på 20 deltagare. De utför uppgifter på nio olika webbsidor för e-handel medan deras ögonrörelser spelas in. Korrelation mäts mellan användbarhet och mått i ögondatan för att undersöka vilka mått som är känsliga för förändringar i användbarhet. Resultatet visar att tillbakabildande sackader och antal fixeringar har starkast korrelation med användbarhet. Tidigare forskning visade att båda dessa mått påverkades av användbarheten.

Smarta enheter blir allt vanligare och teknologierna de använder blir allt mer avancerade. Som en följd av detta uppstår bekväma och effektiva lösningar till vardagliga problem. En stor mängd sammankopplade smarta enheter leder dock till system som är svåra att förstå och att använda. Detta ställer krav på lösningar som hjälper användare att interagera med enheter på ett intuitivt och effektivt sätt. En teknik som under de senaste åren blivit allt mer kommersiellt brukbar och som kan användas i detta syfte är augmented reality. Vidare så är spårning av ögonpositioner ett lovande tillvägagångssätt för att navigera virtuella menyer.Denna uppsats har som syfte att utvärdera hur ögon- och huvudrörelser kan kombineras för att låta användare på ett intuitivt sätt interagera med ett gränssnitt i augmented reality. För att uppnå detta tas två interaktionsmetoder fram som använder ögon- och huvudrörelser på något olika sätt. För att utvärdera deras prestanda och användbarhet så utförs ett experiment där deltagarna navigerar en uppsättning menyer både med hjälp av de framtagna metoderna och en beprövad referensmetod.Resultaten från experimentet visar att referensmetoden både är den snabbaste och den minst felbenägna ut av de tre utvärderade metoderna. Trots detta så föredrar deltagarna en av de framtagna metoderna, och båda dessa metoder uppnår adekvata resultat. Vidare så visar den kvantitativa datan inte på några mätbara skillnader mellan de framtagna metoderna. Däremot så uppnår en av dem högre resultat i de subjektiva utvärderingarna. / Smart devices are becoming increasingly common and technologically advanced. As aresult, convenient and effective approaches to everyday problems are emerging. However,a large amount of interconnected devices result in systems that are difficult to understandand use. This necessitates solutions that help users interact with their devices in anintuitive and effective way. One such possible solution is augmented reality, which hasbecome a viable commercial technology in recent years. Furthermore, tracking the positionof users’ eyes to navigate virtual menus is a promising approach that allows for interestinginteraction techniques.In this thesis, we explore how eye and head movements can be combined in an effortto provide intuitive input to an augmented reality user interface. Two novel interactiontechniques that combine these modalities slightly differently are developed. To evaluatetheir performance and usability, an experiment is conducted in which the participantsnavigate a set of menus using both our proposed techniques and a baseline technique.The results of the experiment show that out of the three evaluated techniques, thebaseline is both the fastest and the least error-prone. However, participants prefer oneof the proposed techniques over the baseline, and both of these techniques perform adequately.Furthermore, the quantitative data shows no measurable differences betweenthe proposed techniques, although one of them receives a higher score in the subjectiveevaluations.

Vibration analysis is a method that studies patterns in vibration data and measures vibration levels. It is usually performed on time waveforms of the vibration signal directly and on thefrequency spectrum derived by applying the Fourier Transform on the time waveform. Conventional vibration analysis methods are either expensive, need a complicated setup, or both. Non-contact measurement systems, such as high-speed cameras coupled with computer vision and motion magnification methods, are suitable options for monitoring vibrations of any system. In this work, many classic and state-of-the-art computer vision tracking algorithms were compared. Low and high frame rate videos are used to evaluate their ability to track the oscillatory movement that characterizes vibrations. The trackers are benchmarked with literature and experimental study. Two sets of experiments were carried out in this work, one using a cantilever and another using a robot. The resonance frequencies obtained from the vision camera method are compared to the Laser vibrometer method, which is industry standard. The results show that the resonance frequencies of both methods are closer to each other. The limitations of the tracking algorithm-based approach used for vibration analysis were discussed at the end. Since the methods provided are generic, they may be easily modified for other relevant applications. / Vibrationsanalys är en metod som studerar mönster i vibrationsdata och mäter vibrationsnivåer. Det utförs vanligtvis på tidvågformer av vibrationssignalen direkt och på frekvensen, spektrum som härleds genom att applicera Fourier Transform på tidvågform. Konventionella vibrationsanalysmetoder är antingen dyra, kräver en komplicerad installation eller båda. Beröringsfria mätsystem, till exempel höghastighetskameror i kombination med datorsyn och rörelseförstoringsmetoder, är lämpliga alternativ för att övervaka vibrationer i alla system. I detta arbete jämfördes många klassiska och toppmoderna datorsynsspårningsalgoritmer. Videor med låg och hög bildhastighet används för att utvärdera deras förmåga att spåra den oscillerande rörelsen som kännetecknar vibrationer. Spårarna jämförs med litteratur och experimentell studie. I detta arbete utfördes två uppsättningar experiment, ett med en fribärare och ett annat med en robot. De resonans frekvenser som erhålls från visionkamerametoden jämförs med Laservibrometer metoden, som är branschstandard. Resultaten visar att resonansfrekvenserna för båda metoderna ligger närmare varandra. Begränsningarna av det spårningsalgoritmbaserade tillvägagångssättet som används för vibrationsanalys diskuterades i slutet. Eftersom de angivna metoderna är generiska kan de enkelt modifieras för andra relevanta applikationer.

<p dir="ltr">FemTech is a booming subset of mHealth applications that was worth $51 billion in 2021 (Stewart, 2022b). FemTech largely focuses on menstruation, pregnancy, and fertility tracking. As with any technology, it comes with privacy and security risks for users, but these risks are more acute due to the sensitive nature of the data being collected. While privacy and security shortcomings have been highlighted for years, concerns were discussed widely in the United States after the Supreme Court released its <i>Dobbs v. Jackson</i> decision on June 24, 2022, which overturned <i>Roe v. Wade</i>, a 1973 decision that protected abortion as a constitutional right and limited states’ abilities to place restrictions on abortions. With abortion no longer a constitutional right, many states have outlawed or heavily restricted the procedure, and individuals expressed concern about their digital data being used in investigations as it has been in select previous cases (e.g., <i>State of Indiana v. Purvi Patel</i>, 2015; <i>State of Mississippi v. Latice Fisher</i>, 2018; <i>The State of Nebraska v. Celeste Burgess</i>, 2023; <i>The State of Nebraska v. Jessica Burgess</i>, 2023). While Big Tech has been scrutinized for turning user data over to law enforcement, many have more heavily questioned the protections offered by period tracking app companies due to the abundant amount of health data these companies possess about their users (e.g., Basu, 2022; Bradley et al., 2022; Cole, 2022). These apps have historically fallen short in protections for their user data in general (e.g., Beilinson, 2020; <i>Developer of Popular Women’s Fertility-Tracking App Settles FTC Allegations That It Misled Consumers About the Disclosure of Their Health Data</i>, 2021; Quintin, 2017). Clue is one of the most popular FemTech apps with millions of downloads across the Apple App Store and Google Play Store, and the company has spoken out widely about their privacy protections in the wake of the <i>Dobbs v. Jackson</i> decision (<i>‎Clue Period Tracker & Calendar</i>, n.d.; <i>Clue Period Tracker & Calendar</i>, n.d.; <i>Clue’s Response to Roe vs Wade Decision</i>, 2022). This research presents a forensic analysis of Clue on both iOS and Android after two months of data population, finding that some user-entered data was available in the app cache or .db-wal files on both iOS and Android but was entirely erased after the deletion of the app on the phones. This research also presents results from a survey of 31 menstruators in the United States, finding that online privacy in general is a concern for many users, and most find it unacceptable for period tracking applications to share user health data with advertisers or law enforcement.</p>

Questo studio è composto da due ricerche. La prima riguarda bambini della scuola dell’infanzia di età compresa tra 4 e 6 anni (N=44) ed esplora la comprensione dell’ironia e la sua possibile correlazione tra la comprensione di norme sociali, la teoria della mente e la competenza emotiva. I risultati mostrano come la comprensione delle norme sociali, della loro violazione e le competenze emotive possono aiutare i bambini nella comprensione dell’ironia La seconda ricerca relativa agli adulti (N=88) esplora la correlazione tra teoria della mente ed elaborazione di informazioni ironiche attraverso l’utilizzo dello strumento eye tracker. Lo studio evidenzia relazioni significative tra lo sviluppo della teoria della mente di tipo emotivo e l’elaborazione di informazioni ironiche: nello specifico, si verifica che in presenza di un enunciato ironico, soggetti con una teoria della mente elevata osservano frasi/ disegni che descrivono la realtà dei fatti, mentre soggetti con una teoria della mente meno elevata osservano frasi/ disegni relativi al significato letterale dell’ironia. Ciò sembra confermare il ruolo della teoria della mente nell’elaborare forme di comunicazione non letterali già ad un livello di base, pre-riflessivo come quello qui indagato. / This research consists of two studies. The first, involving school children aged between 4 and 6 years (N = 44), explores the understanding of irony and its possible correlation between social norms understanding, theory of mind and emotional competence. The results show that the understanding of social norms, their violation and emotional skills can help children in irony understanding. The second study related to adults (N = 88), explores the relationship between theory of mind and irony visual elaboration with the eye tracker Instrument. Results found relationships between the development of emotional theory of mind and irony visual elaboration, confirming the role of theory of mind during the growth of the individual to elaborate ironic sentences.

A large area time of flight (TOF) detector based on multi-gap resistive plate chamber (MRPC) technology has been developed for the STAR (Solenoidal Tracker at RHIC) experiment at the Relativistic Heavy Ion Collider at the Brookhaven National Laboratory, New York. The TOF detector replaces STAR's Central Trigger Barrel detector with 120 trays, each with 32 MRPCs. Each MRPC has 6 channels. The TOF detector improves by a factor of about 2 STAR's particle identification reach in transverse momenta and enhances STARs physics research program.

近年來隨著電腦科技的進步，發展出了各種人機介面的應用。不同於傳統的滑鼠與鍵盤，新的人機介面往往在其他不同的領域能夠得到更好的發揮，眼動（eye movement）即是一個例子，利用眼球移動在螢幕上的眼動軌跡來操控電腦。另一方面，螢幕所呈現的內容也會影響使用者的眼動行為，例如閱讀文章時不同的文章內容就會影響使用者在看文章時的眼動行為，因此我們就可以從眼動軌跡去推測出使用者對於螢幕的內容（如文章或圖片）的反應。本論文的目的就是要找出閱讀文章時的眼動軌跡和閱讀者對該文章的理解程度之間的關連性，最後發展出一個系統，利用閱讀文章時的眼動軌跡就能去推測閱讀者對於文章的理解程度，而無需後續的閱讀測驗。 / 一般人通常對自身的眼動軌跡的進行方式不甚了解，認為閱讀文章的眼動應該是順著字句的進行而移動。其實仔細觀察細小的眼動軌跡會發現比想像中複雜的多，例如當我們閱讀到文意較為困難的片段時，通常都會放慢速度，或是反覆閱讀，又例如看到自己有興趣的主題時會凝視在某些區塊較久的時間等等行為，這些都是在各種不同的情境之下做出相對的反應。本論文提出了資料探勘的方法來分析複雜的眼動軌跡，能針對每個人不同的閱讀模式找出不同的眼動規則。此方法能適應各種使用者的閱讀習性，對閱讀理解程度的預測能達到更精確的效果。 / With the advance of the computer technology, there are many kinds of HCI (Human Computer interface) applications been developed in recent years. Different from mouse and keyboard, new interface will bring more benefits in different area, and eye-movement is an example. It extracts the trace of eye movement to control the computer. Furthermore, the screen content will also affect the eye-movement. For example, when the user reads the articles, the content will affect the eye-movement, so we can speculate the reaction of the user after seen the screen content (such as article or picture) by eye-movement. The goal of the paper is to find out the relationship between eye-movement and the degree of comprehension, and develop a system which can automatically measure reading comprehension without any follow-up comprehension test. / Most people don’t realize how there eye move. They think eye movements should be carried out along the words. In fact, eye movement will find more complex than imagined, for example, when we read the context of the article is more difficult, we often slow down or read over and over again. In another example, people will gaze at some of the subjects that they are interest in for a longer period of time. These reactions correspond to a variety of different situations. This paper presents a data mining approach to analyze complex eye movement. It can find out the different rules of eye movement for users who have different reading strategy. This method will be able to adapt to a variety of users reading habits, and make more accurate prediction with the degree of the comprehension.

The introduction of input devices with natural user interfaces in gaming hardware has changed the way we interact with games. Hardware with motion-sensing and gesture recognizing capabilities remove the constraint of interacting with games through typical traditional devices like mouse-keyboard and gamepads. This changes the way we approach games and how the game communicates back to us as the player opening new levels of interactivity. This thesis covers how eye tracker technology can be used to affect rendering effects in games.

Microplitis croceipes, one of the nectar feeding parasitoid wasps, has been found to associatively learn chemical cues through feeding. The experiments on M. croceipes are performed and recorded by a Sony camcorder in the USDA-ARS Biological Control Laboratory in Tifton, GA, USA. The experimental videos have shown that M. croceipes can respond to Coffee odour in this study. Their detection capabilities and the behaviour of M. croceipes with different levels of coffee odours were studied. First, the data that are related to trained M. croceipes behaviour was extracted from the experimental videos and stored in a Microsoft Excel database. The extracted data represent the behaviour of M. croceipes trained to 0.02g and then exposed to 0.001g, 0.005g, 0.01g, 0.02g and 0.04g of coffee. Secondly, indices were developed to uniquely characterise the behaviour of trained M. croceipes under different coffee concentrations. Thirdly, a preliminary model and its parameters were developed to classify the response of trained wasps when exposed to these five different coffee odours. In summary, the success of this thesis demonstrates the usefulness of data analysis for interpreting experimental data, developing indices, as well as understanding the design principles of a simple model based on trained wasps.

Les collisions d'ions lourds ultra-relativistes sont produites expérimentalement dans le but d'observer la matière dense et chaude. Un des objectifs majeurs est de prouver l'existence du plasma de quarks et de gluons (QGP pour Quark Gluon Plasma) et de l'étudier. Cet état serait celui de la matière dans les conditions de température et de densité suffisamment élevées pour rompre le confinement des quarks à l'intérieur de hadrons. Ces conditions sont obtenues auprès des collisionneurs d'ions lourds travaillant dans les domaines d'énergies les plus élevées. Le RHIC (pour Relativistic Heavy Ion Collider) a notamment permis de réaliser des collisions p+p et Au+Au avec une énergie dans le centre de masse de $\sqrt(s_(NN))=$ 200 GeV. Cette thèse porte sur la production des $\Lambda (1520)$ dans ces deux systèmes grâce au dispositif expérimental de la collaboration STAR (pour Solenoid Tracker At RHIC). La production de cette résonance a été également mesurée dans les collisions du SPS (pour Super Proton Synchrotron) à une énergie égale à $\sqrt(s_(NN))=$ 17.3 GeV. Cette mesure a révélé une diminution importante du signal de $\Lambda (1520)$ observé dans les collisions d'ions lourds ultra-relativistes. Cette tendance est confirmée à RHIC grâce au calcul des rapports $\Lambda (1520)/\Lambda $ pour les collisions p+p et Au+Au à $\sqrt(s_(NN))=$ 200 GeV. Ce rapport diminue pour les collisions Au+Au par rapport aux collisions p+p et est par ailleurs surestimé par les modèles statistiques qui supposent une production de particules en équilibre thermique. Ces résultats constituent entre autres choses une forte présomption de l'existence d'un découplement des particules produites en deux étapes : un découplement chimique, à partir duquel les multiplicités sont fixées, suivi par un découplement thermique où cessent toutes les interactions. Cette conclusion constitue une étape importante dans notre compréhension des collisions d'ions lourds ultra-relativistes et du comportement de la matière dans ces conditions.