790 research outputs found
Mobile Device Background Sensors: Authentication vs Privacy
The increasing number of mobile devices in recent years has caused the collection of a large amount of personal information that needs to be protected. To this aim, behavioural biometrics has become very popular. But, what is the discriminative power of mobile behavioural biometrics in real scenarios? With the success of Deep Learning (DL), architectures based on Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), such as Long Short-Term Memory (LSTM), have shown improvements compared to traditional machine learning methods. However, these DL architectures still have limitations that need to be addressed. In response, new DL architectures like Transformers have emerged. The question is, can these new Transformers outperform previous biometric approaches? To answers to these questions, this thesis focuses on behavioural biometric authentication with data acquired from mobile background sensors (i.e., accelerometers and gyroscopes). In addition, to the best of our knowledge, this is the first thesis that explores and proposes novel behavioural biometric systems based on Transformers, achieving state-of-the-art results in gait, swipe, and keystroke biometrics. The adoption of biometrics requires a balance between security and privacy. Biometric modalities provide a unique and inherently personal approach for authentication. Nevertheless, biometrics also give rise to concerns regarding the invasion of personal privacy. According to the General Data Protection Regulation (GDPR) introduced by the European Union, personal data such as biometric data are sensitive and must be used and protected properly. This thesis analyses the impact of sensitive data in the performance of biometric systems and proposes a novel unsupervised privacy-preserving approach. The research conducted in this thesis makes significant contributions, including: i) a comprehensive review of the privacy vulnerabilities of mobile device sensors, covering metrics for quantifying privacy in relation to sensitive data, along with protection methods for safeguarding sensitive information; ii) an analysis of authentication systems for behavioural biometrics on mobile devices (i.e., gait, swipe, and keystroke), being the first thesis that explores the potential of Transformers for behavioural biometrics, introducing novel architectures that outperform the state of the art; and iii) a novel privacy-preserving approach for mobile biometric gait verification using unsupervised learning techniques, ensuring the protection of sensitive data during the verification process
Conversations on Empathy
In the aftermath of a global pandemic, amidst new and ongoing wars, genocide, inequality, and staggering ecological collapse, some in the public and political arena have argued that we are in desperate need of greater empathy — be this with our neighbours, refugees, war victims, the vulnerable or disappearing animal and plant species. This interdisciplinary volume asks the crucial questions: How does a better understanding of empathy contribute, if at all, to our understanding of others? How is it implicated in the ways we perceive, understand and constitute others as subjects? Conversations on Empathy examines how empathy might be enacted and experienced either as a way to highlight forms of otherness or, instead, to overcome what might otherwise appear to be irreducible differences. It explores the ways in which empathy enables us to understand, imagine and create sameness and otherness in our everyday intersubjective encounters focusing on a varied range of "radical others" – others who are perceived as being dramatically different from oneself. With a focus on the importance of empathy to understand difference, the book contends that the role of empathy is critical, now more than ever, for thinking about local and global challenges of interconnectedness, care and justice
Desired sensory branding strategies in-store versus online: the skincare industry
Modern shoppers are inundated with purchasing options in every product category, with thousands of brands competing for their patronage. It has therefore become increasingly important for organisations to differentiate product offerings in the market if they want to be competitive. It has further been highlighted that an individual’s experience of a brand is of paramount importance, as it is directly linked to brand loyalty. A vehicle for creating memorable brand experiences is the utilisation of multi-sensory experiences or sensory branding. Within the context of traditional or in-store shopping, sensory branding encompasses the use of visual, auditory, olfactory, tactile and gustatory stimuli to adjust consumer purchasing behaviour. However, more and more consumers are opting for online shopping, spurred on by the effects of the global COVID-19 pandemic, and are no less demanding of brands online than they would be in-store. The cosmetics and personal care industry is one of the more predominant gainers from e-commerce. The skincare industry exhibited one of the largest growth rates from 2019 – 2025 and had an estimated market value of 788.4 million by 2027 (Statista 2023). With reference to in-store shopping for skincare products, sensory marketing strategies have been known to be heavily relied on. Therefore, with consumers moving towards online shopping, it is essential for skincare businesses to consider how to deliver sensory experiences online as well as in-store. Whilst the importance of the use of sensory branding and marketing in the skincare industry is notable, both in-store and online, it was established that while there is research available on sensory branding, there is very limited academic research on digital sensory branding and the sensory branding of v skincare products. Moreover, to the researcher’s knowledge, no academic literature specifically investigates the digital sensory branding of skincare brands. Therefore, this study will contribute not only by adding academic research to the topic being investigated but also through rreccomendations made based on the outcomes of this study to skincare brands in South Africa. From the comprehensive literature review, a conceptual model was constructed to investigate the relationship between traditional and digital sensory branding strategies (independent variables) and brand loyalty (dependent variable). Two sets of hypotheses were formulated relating to the identified variables of this study and the empirical research conducted was utilised to deduce whether these hypotheses should be rejected or supported. To conduct the empirical research needed for this study, certain research methodology was employed. This study made use of a positivistic paradigm and a quantitative approach. The target population of this study constituted consumers who had purchased skincare products in-store as well as online and, as no true sample frame existed, respondents were selected through the use of non-probability sampling, more specifically, convenience sampling. To collect the data, an online survey was used, with the specific data collection instrument being a web-based self-administered questionnaire, which was distributed via social media platforms, such as Facebook and LinkedIn, as well as via email. Section A of the questionnaire focused on the demographic details of the respondents, while Section B – Section F related to the variables of the study. A total of 372 potential respondents started the questionnaire, however only 321 questionnaires were deemed usable after the data had been coded and cleaned, indicating a response rate of 86.3%. This study made use of both descriptive (measures of central tendency as well as standard deviation and skewness) and inferential (SEM Models, Primary Models, Pearson’s correlation coefficients, Chi-Square test of Association, ANOVAs and Welch Robust test, Tukey test and Games Howell Test as well as Cohen’s d) statistics to interpret the data, which was graphically illustrated. vi The empirical investigation conducted in this study between the variables and sub-variables revealed that significant relationships exist between traditional sensory branding strategies (traditional olfactory and tactile stimuli) and digital sensory branding strategies (digital visual, olfactory and tactile stimuli) and brand loyalty, with refence to the skincare industry. It was further notable that, with specific reference to the skincare industry, the sense of sight, smell and touch are key factors for sensory branding, whereas auditory stimuli were found to only be useful when used in unison with the other senses. Moreover, with reference to in-store shopping, it was deduced that consumers shop for skincare mostly via retail outlets, which could lead to sensory overload. Furthermore, the results of this study suggest that younger consumers are price sensitive. Based on the pertinent empirical results, and corresponding literature findings, of this study, recommendations were provided to businesses operating in the skincare industry. With reference to in-store trading, it was recommended that because skincare is mostly sold via retail outlets, the brand itself does not have control over all sensory stimuli to which the consumer is exposed. As a result, consumers may be subject to sensory overload and skincare brands should keep their sensory branding in-store simple. Moreover, skincare brands could make use of an in-store aesthetician or beautician, which would facilitate consumer-product interaction. With regards to online trading, a recommendation for skincare brands would be to use moving images or GIFs, which will allow the consumer to more easily imagine the feel of the product. Moreover, skincare brands can make use of brand ambassadors to create “unboxing” videos, which will convey more clearly the sensory information of the product and instil confidence in consumers. Reccomendations were also made with reference to the financial state of consumers, as the financial position of the respondents could influence their decision making. The limitations of this study comprised the availability of reliable existing sources to support the study as the concept of digital sensory branding is still relatively new and, due to the study being focused on the skincare industry, taste stimuli were excluded as they were found to have no relevance. Finally, vii based on all the literature findings and empirical results, recommendations for future areas of study were made. This study provides evidence that both traditional and digital sensory branding strategies have an influence on, or relationship with, brand loyalty. Through this study, the importance of sensory branding, with specific reference to the skincare industry, is brought to light. Furthermore, skincare brands can utilise the information provided to improve the experience of their consumers when shopping in-store, as well as online, thereby increasing their base of brand loyal consumers.Thesis (PhD) -- Faculty of Business and Economic Sciences, 202
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Reinforcement Learning-Based Test Case Generation with Test Suite Prioritization for Android Application Testing
This dissertation introduces a hybrid strategy for automated testing of Android applications that combines reinforcement learning and test suite prioritization. These approaches aim to improve the effectiveness of the testing process by employing reinforcement learning algorithms, namely Q-learning and SARSA (State-Action-Reward-State-Action), for automated test case generation. The studies provide compelling evidence that reinforcement learning techniques hold great potential in generating test cases that consistently achieve high code coverage; however, the generated test cases may not always be in the optimal order. In this study, novel test case prioritization methods are developed, leveraging pairwise event interactions coverage, application state coverage, and application activity coverage, so as to optimize the rates of code coverage specifically for SARSA-generated test cases. Additionally, test suite prioritization techniques are introduced based on UI element coverage, test case cost, and test case complexity to further enhance the ordering of SARSA-generated test cases. Empirical investigations demonstrate that applying the proposed test suite prioritization techniques to the test suites generated by the reinforcement learning algorithm SARSA improved the rates of code coverage over original orderings and random orderings of test cases
MentalSense. A ludic and didactic game for people with dementia
Com o envelhecimento da população, é cada vez mais comum encontrar pessoas com
demência. A demência é caracterizada pela perda de habilidades emocionais e
cognitivas. Nesta dissertação, propomos um novo sistema para estimulação cognitiva
através de jogos, o MentalSense, onde pessoas em estado demencial podem realizar
alguns exercícios cognitivos para cuidar de um animal de estimação, trabalhando no
mínimo cinco domínios cognitivos: atenção, memória episódica, raciocínio lógico,
pensamento abstrato e funções executivas. O jogo está implementado em tablet para
poder ser usado em diversos lugares e situações. Foram realizados diversos estudos,
desde questionários online e entrevistas a cuidadores formais e informais, e seguiu-se
um design participativo com psicólogo e psicomotricista, onde obtivemos informação
sobre as necessidades desta população e de quem presta cuidados a estes. Realizámos
um estudo piloto, o qual culminou em sugestões para o melhoramento da aplicação
final. O protótipo final foi testado através de um estudo de caso com dois participantes
acompanhados por um psicólogo, que realizaram várias sessões com o MentalSense,
com resultados positivos.As the population ages, it is increasingly common to find people with dementia.
Dementia is characterized by the loss of emotional and cognitive abilities. In this
dissertation, we propose a new system for cognitive stimulation through games,
MentalSense, where people with dementia can perform some cognitive exercises to take
care of a pet, working on at least five cognitive domains: attention, episodic memory,
logical reasoning, abstract thinking and executive functions. The game is implemented
on a tablet so it can be used in different places and situations. Several studies were
carried out, from online questionnaires and interviews with formal and informal
caregivers, and a participatory design with a psychologist and psychometrician was
followed, where we obtained information about the needs of this population and those
who provide care to them. We carried out a pilot study, which culminated in suggestions
for improving the final application. The final prototype was tested through a case study
with two participants accompanied by a psychologist, who carried out several sessions
with MentalSense, with positive results
Exploring the Behavioural Effects of Compound-21 Using Novel Object Recognition and Object in Place Tests in Long Evans Rats
Designer Receptors Exclusively Activated by Designer Drugs (DREADDs) have gained popularity as a tool to investigate the neural substrates of behaviour in rodents. When used with spontaneous behavioural tests of memory in rodents, DREADDs allow for a unique opportunity to advance our understanding of how specific neuronal populations contribute to cognition. While data on the use of DREADDs to study memory with spontaneous tasks in rats is somewhat limited, there is evidence to suggest that the canonical DREADD agonist, clozapine-N-oxide (CNO), exhibits off target effects on recognition memory assessed with the Novel Object Recognition (NOR) test. While newer DREADD agonists are available, an understanding of how these novel compounds impact rat behaviour unspecific to DREADD activation is lacking. Therefore, I sought to test whether the DREADD agonist, Compound 21 (C21), affected recognition memory assessed by NOR or, associative memory assessed by the Object-in-Place (OiP) test. I also investigated whether DREADD-mediated inhibition of parvalbumin (PV+) gamma-amino butyric acid (GABA)ergic interneurons of the medial prefrontal cortex (mPFC) would impair associative memory as measured by OiP. I showed that C21 did not affect either sex in NOR, or females in OiP. Male rats failed to exhibit robust discrimination in OiP following either control or C21 treatment; however, total object exploration times of male rats were not altered by C21. Lastly, PV-Cre rats transfected with an inhibitory DREADD in the mPFC and treated with C21 showed normal exploration of objects in OiP. Poor discrimination in OiP and low vector co-expression of DREADD with mPFC parvalbumin-containing interneurons precluded conclusions about potential impacts of inhibiting these cells on associative memory. While C21 did not impair discrimination of objects in females tested in OiP, further work is needed to replicate this finding in males
Cognitive Load Reduction in Commanding Heterogeneous Robotic Teams
With the proliferation of multi-robot systems, the interfaces required to operate them have become increasingly complex compared to those used for single robot systems. This can present challenges for operators who need to extract relevant information in order to make informed decisions about how to operate the robots. To address this issue, this thesis explores a variety of strategies aimed at improving the intuitiveness and usability of such systems. These strategies encompass a range of approaches, from designing user interfaces to integrating physical input devices, knowledge representations, and other modalities to assist operators. In this context, the thesis proposes a decision support system that provides operators with additional information in an intuitive way, focusing specifically on handling a set of distinct commands for a heterogeneous robotic team. A key constraint during the development of this system was the lack of historical data available to train the modules on. As a result, the proposed system was tested in a few-shot environment and was specifically designed for this circumstance. The support system comprises two modules: one that probabilistically classifies the next command using a data mining approach called sequence prediction, which is used to reorder the available commands in the interface; and a second that creates higher-level commands by mining frequent sequences from the historical dataset. These command sequences are presented to the operator, who can add them as additional executable commands. To evaluate the advantages and disadvantages of this novel approach, a user study was conducted, which showed that both modules increased the efficiency and usability of the system, while also identifying opportunities for further improvement
WearPut : Designing Dexterous Wearable Input based on the Characteristics of Human Finger Motions
Department of Biomedical Engineering (Human Factors Engineering)Powerful microchips for computing and networking allow a wide range of wearable devices to be miniaturized with high fidelity and availability. In particular, the commercially successful smartwatches placed on the wrist drive market growth by sharing the role of smartphones and health management. The emerging Head Mounted Displays (HMDs) for Augmented Reality (AR) and Virtual Reality (VR) also impact various application areas in video games, education, simulation, and productivity tools. However, these powerful wearables have challenges in interaction with the inevitably limited space for input and output due to the specialized form factors for fitting the body parts. To complement the constrained interaction experience, many wearable devices still rely on other large form factor devices (e.g., smartphones or hand-held controllers). Despite their usefulness, the additional devices for interaction can constrain the viability of wearable devices in many usage scenarios by tethering users' hands to the physical devices. This thesis argues that developing novel Human-Computer interaction techniques for the specialized wearable form factors is vital for wearables to be reliable standalone products.
This thesis seeks to address the issue of constrained interaction experience with novel interaction techniques by exploring finger motions during input for the specialized form factors of wearable devices. The several characteristics of the finger input motions are promising to enable increases in the expressiveness of input on the physically limited input space of wearable devices. First, the input techniques with fingers are prevalent on many large form factor devices (e.g., touchscreen or physical keyboard) due to fast and accurate performance and high familiarity. Second, many commercial wearable products provide built-in sensors (e.g., touchscreen or hand tracking system) to detect finger motions. This enables the implementation of novel interaction systems without any additional sensors or devices. Third, the specialized form factors of wearable devices can create unique input contexts while the fingers approach their locations, shapes, and components. Finally, the dexterity of fingers with a distinctive appearance, high degrees of freedom, and high sensitivity of joint angle perception have the potential to widen the range of input available with various movement features on the surface and in the air. Accordingly, the general claim of this thesis is that understanding how users move their fingers during input will enable increases in the expressiveness of the interaction techniques we can create for resource-limited wearable devices.
This thesis demonstrates the general claim by providing evidence in various wearable scenarios with smartwatches and HMDs. First, this thesis explored the comfort range of static and dynamic touch input with angles on the touchscreen of smartwatches. The results showed the specific comfort ranges on variations in fingers, finger regions, and poses due to the unique input context that the touching hand approaches a small and fixed touchscreen with a limited range of angles. Then, finger region-aware systems that recognize the flat and side of the finger were constructed based on the contact areas on the touchscreen to enhance the expressiveness of angle-based touch input. In the second scenario, this thesis revealed distinctive touch profiles of different fingers caused by the unique input context for the touchscreen of smartwatches. The results led to the implementation of finger identification systems for distinguishing two or three fingers. Two virtual keyboards with 12 and 16 keys showed the feasibility of touch-based finger identification that enables increases in the expressiveness of touch input techniques. In addition, this thesis supports the general claim with a range of wearable scenarios by exploring the finger input motions in the air. In the third scenario, this thesis investigated the motions of in-air finger stroking during unconstrained in-air typing for HMDs. The results of the observation study revealed details of in-air finger motions during fast sequential input, such as strategies, kinematics, correlated movements, inter-fingerstroke relationship, and individual in-air keys. The in-depth analysis led to a practical guideline for developing robust in-air typing systems with finger stroking. Lastly, this thesis examined the viable locations of in-air thumb touch input to the virtual targets above the palm. It was confirmed that fast and accurate sequential thumb touch can be achieved at a total of 8 key locations with the built-in hand tracking system in a commercial HMD. Final typing studies with a novel in-air thumb typing system verified increases in the expressiveness of virtual target selection on HMDs.
This thesis argues that the objective and subjective results and novel interaction techniques in various wearable scenarios support the general claim that understanding how users move their fingers during input will enable increases in the expressiveness of the interaction techniques we can create for resource-limited wearable devices. Finally, this thesis concludes with thesis contributions, design considerations, and the scope of future research works, for future researchers and developers to implement robust finger-based interaction systems on various types of wearable devices.ope
Autonomisten metsäkoneiden koneaistijärjestelmät
A prerequisite for increasing the autonomy of forest machinery is to provide robots with digital situational awareness, including a representation of the surrounding environment and the robot's own state in it. Therefore, this article-based dissertation proposes perception systems for autonomous or semi-autonomous forest machinery as a summary of seven publications. The work consists of several perception methods using machine vision, lidar, inertial sensors, and positioning sensors. The sensors are used together by means of probabilistic sensor fusion. Semi-autonomy is interpreted as a useful intermediary step, situated between current mechanized solutions and full autonomy, to assist the operator.
In this work, the perception of the robot's self is achieved through estimation of its orientation and position in the world, the posture of its crane, and the pose of the attached tool. The view around the forest machine is produced with a rotating lidar, which provides approximately equal-density 3D measurements in all directions. Furthermore, a machine vision camera is used for detecting young trees among other vegetation, and sensor fusion of an actuated lidar and machine vision camera is utilized for detection and classification of tree species. In addition, in an operator-controlled semi-autonomous system, the operator requires a functional view of the data around the robot. To achieve this, the thesis proposes the use of an augmented reality interface, which requires measuring the pose of the operator's head-mounted display in the forest machine cabin. Here, this work adopts a sensor fusion solution for a head-mounted camera and inertial sensors.
In order to increase the level of automation and productivity of forest machines, the work focuses on scientifically novel solutions that are also adaptable for industrial use in forest machinery. Therefore, all the proposed perception methods seek to address a real existing problem within current forest machinery. All the proposed solutions are implemented in a prototype forest machine and field tested in a forest. The proposed methods include posture measurement of a forestry crane, positioning of a freely hanging forestry crane attachment, attitude estimation of an all-terrain vehicle, positioning a head mounted camera in a forest machine cabin, detection of young trees for point cleaning, classification of tree species, and measurement of surrounding tree stems and the ground surface underneath.Metsäkoneiden autonomia-asteen kasvattaminen edellyttää, että robotilla on digitaalinen tilannetieto sekä ympäristöstä että robotin omasta toiminnasta. Tämän saavuttamiseksi työssä on kehitetty autonomisen tai puoliautonomisen metsäkoneen koneaistijärjestelmiä, jotka hyödyntävät konenäkö-, laserkeilaus- ja inertia-antureita sekä paikannusantureita. Työ liittää yhteen seitsemässä artikkelissa toteutetut havainnointimenetelmät, joissa useiden anturien mittauksia yhdistetään sensorifuusiomenetelmillä. Työssä puoliautonomialla tarkoitetaan hyödyllisiä kuljettajaa avustavia välivaiheita nykyisten mekanisoitujen ratkaisujen ja täyden autonomian välillä.
Työssä esitettävissä autonomisen metsäkoneen koneaistijärjestelmissä koneen omaa toimintaa havainnoidaan estimoimalla koneen asentoa ja sijaintia, nosturin asentoa sekä siihen liitetyn työkalun asentoa suhteessa ympäristöön. Yleisnäkymä metsäkoneen ympärille toteutetaan pyörivällä laserkeilaimella, joka tuottaa lähes vakiotiheyksisiä 3D-mittauksia jokasuuntaisesti koneen ympäristöstä. Nuoret puut tunnistetaan muun kasvillisuuden joukosta käyttäen konenäkökameraa. Lisäksi puiden tunnistamisessa ja puulajien luokittelussa käytetään konenäkökameraa ja laserkeilainta yhdessä sensorifuusioratkaisun avulla. Lisäksi kuljettajan ohjaamassa puoliautonomisessa järjestelmässä kuljettaja tarvitsee toimivan tavan ymmärtää koneen tuottaman mallin ympäristöstä. Työssä tämä ehdotetaan toteutettavaksi lisätyn todellisuuden käyttöliittymän avulla, joka edellyttää metsäkoneen ohjaamossa istuvan kuljettajan lisätyn todellisuuden lasien paikan ja asennon mittaamista. Työssä se toteutetaan kypärään asennetun kameran ja inertia-anturien sensorifuusiona.
Jotta metsäkoneiden automatisaatiotasoa ja tuottavuutta voidaan lisätä, työssä keskitytään uusiin tieteellisiin ratkaisuihin, jotka soveltuvat teolliseen käyttöön metsäkoneissa. Kaikki esitetyt koneaistijärjestelmät pyrkivät vastaamaan todelliseen olemassa olevaan tarpeeseen nykyisten metsäkoneiden käytössä. Siksi kaikki menetelmät on implementoitu prototyyppimetsäkoneisiin ja tulokset on testattu metsäympäristössä. Työssä esitetyt menetelmät mahdollistavat metsäkoneen nosturin, vapaasti riippuvan työkalun ja ajoneuvon asennon estimoinnin, lisätyn todellisuuden lasien asennon mittaamisen metsäkoneen ohjaamossa, nuorten puiden havaitsemisen reikäperkauksessa, ympäröivien puiden puulajien tunnistuksen, sekä puun runkojen ja maanpinnan mittauksen
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