Browsing by Department "Department of Computer Science"
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- 3D Mitochondria Instance Segmentation with Spatio-Temporal Transformers
A4 Artikkeli konferenssijulkaisussa(2023) Thawakar, Omkar; Anwer, Rao Muhammad; Laaksonen, Jorma; Reiner, Orly; Shah, Mubarak; Khan, Fahad ShahbazAccurate 3D mitochondria instance segmentation in electron microscopy (EM) is a challenging problem and serves as a prerequisite to empirically analyze their distributions and morphology. Most existing approaches employ 3D convolutions to obtain representative features. However, these convolution-based approaches struggle to effectively capture long-range dependencies in the volume mitochondria data, due to their limited local receptive field. To address this, we propose a hybrid encoder-decoder framework based on a split spatio-temporal attention module that efficiently computes spatial and temporal self-attentions in parallel, which are later fused through a deformable convolution. Further, we introduce a semantic foreground-background adversarial loss during training that aids in delineating the region of mitochondria instances from the background clutter. Our extensive experiments on three benchmarks, Lucchi, MitoEM-R and MitoEM-H, reveal the benefits of the proposed contributions achieving state-of-the-art results on all three datasets. Our code and models are available at https://github.com/OmkarThawakar/STT-UNET. - 3PP-R: Enabling Natural Movement in 3rd Person Virtual Reality
A4 Artikkeli konferenssijulkaisussa(2020-11-02) Evin, Inan; Pesola, Toni; Kaos, Maximus; Takala, Tuukka M.; Hämäläinen, PerttuWe propose 3PP-R, a novel Virtual Reality display and interaction technique that allows natural movement in 3rd-person perspective (3PP), including body rotation without losing sight of the avatar. A virtual display such as a World-in-Miniature model orbits around the user when the user turns, but does not rotate except for the user’s avatar. From the user’s perspective, the display appears fixed in the field of vision, while the world rotates around the avatar. 3PP-R combines the strengths of 3PP and 1st-person perspective (1PP): Similar to 1PP, it allows interacting with rich natural movements, while also reaping the benefits of 3PP, i.e., superior spatial awareness and animating the avatar without nauseating viewpoint movement, e.g., for joystick-controlled locomotion. We test 3PP-R in a maze navigation study, which indicates considerably less cybersickness in 3PP-R than in 1PP. We also demonstrate 3PP-R in dynamic game interaction including running, jumping, swinging on bars, and martial arts. - 5G innovaatiot teollisuuden digitalisaation kiihdyttämiseksi - Datavetoiset käyttötapaukset
School of Science | D4 Julkaistu kehittämis- tai tutkimusraportti tai -selvitys(2023) Collin, Jari; Pellikka, Jarkko; Penttinen, Jyrki TJ; Öfversten, Janne; Koivula, Ella; Laiho, Perttu; Lahti, Roope; Rajani, Jagdeesh; Laars, Maarten van derThe digitalisation of products and services is shaping competition and existing industry boundaries. Today, traditional physical product-based business models are challenged by data-driven digital ecosystems that enable new ways to increase end-customer value. Modern digital platforms and the utilisation of real-time data enable significant value added – as numerous IoT (Internet of Things) applications for consumers have already demonstrated. In the corporate market, the lack of common business rules for sharing data between companies has hampered similar developments in Industrial IoT applications, even though the business opportunities of data-driven digital services are obvious. 5G mobile technology enables an open and reliable platform for industrial ecosystems to collaborate securely globally. The research deals with the ongoing industrial transformation and data-driven digital services that can be accelerated with the help of 5G technology. The purpose of the study is to identify and describe industrial 5G use cases to promote customer value, productivity, and sustainability in a selected industrial ecosystem. The research problem is how 5G can be utilised in the digital transformation of industry. Five different sectors are included in the study: mining, forestry, construction/elevator, telecommunications and oil refining, each of which has a pioneering case company. The research perspective is an industrial company seeking new business opportunities with the help of industrial 5G. Sharing lessons learned and best practices across industries is an essential part of research. The study represents the so-called. Multiple case study, which aims to create new theory from modern use cases and observations. The research results in a new understanding of how industrial 5G can be utilised in the digital transformation of industry, what are the biggest obstacles and prerequisites for successful deployment. The result will also identify new opportunities and areas where new 5G mobile technology opens up opportunities to create operational innovations and new digital services. The case studies also identified and described areas common to the industry sectors and areas that are very sector-specific. Based on the experience gained, three alternative approaches to implementing an industrial 5G network solution will be presented. Applications related to different use cases can also be implemented in several different ways, based on the purpose and environment of the applications. - AaltoNLP at SemEval-2022 Task 11: Ensembling Task-adaptive Pretrained Transformers for Multilingual Complex NER
A4 Artikkeli konferenssijulkaisussa(2022) Pietiläinen, Aapo; Ji, ShaoxiongThis paper presents the system description of team AaltoNLP for SemEval-2022 shared task 11: MultiCoNER. Transformer-based models have produced high scores on standard Named Entity Recognition (NER) tasks. However, accuracy on complex named entities is still low. Complex and ambiguous named entities have been identified as a major error source in NER tasks. The shared task is about multilingual complex named entity recognition. In this paper, we describe an ensemble approach, which increases accuracy across all tested languages. The system ensembles output from multiple same architecture task-adaptive pretrained transformers trained with different random seeds. We notice a large discrepancy between performance on development and test data. Model selection based on limited development data may not yield optimal results on large test data sets. - AATOS – A configurable tool for automatic annotation
A4 Artikkeli konferenssijulkaisussa(2017) Tamper, Minna; Leskinen, Petri; Ikkala, Esko; Oksanen, Arttu; Mäkelä, Eetu; Heino, Erkki; Tuominen, Jouni; Koho, Mikko; Hyvönen, EeroThis paper presents an automatic annotation tool AATOS for providing documents with semantic annotations. The tool links entities found from the texts to ontologies defined by the user. The application is highly configurable and can be used with different natural language Finnish texts. The application was developed as a part of the WarSampo (http://seco.cs.aalto.fi/projects/sotasampo/en/) and Semantic Finlex (http://seco.cs.aalto.fi/projects/lawlod/en/) projects and tested using Kansa Taisteli magazine articles and consolidated Finnish legislation of Semantic Finlex. The quality of the automatic annotation was evaluated by measuring precision and recall against existing manual annotations. The results showed that the quality of the input text, as well as the selection and configuration of the ontologies impacted the results. - ABC of the future
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2023-08) Pesonen, Henri; Simola, Umberto; Köhn-Luque, Alvaro; Vuollekoski, Henri; Lai, Xiaoran; Frigessi, Arnoldo; Kaski, Samuel; Frazier, David T.; Maneesoonthorn, Worapree; Martin, Gael M.; Corander, JukkaApproximate Bayesian computation (ABC) has advanced in two decades from a seminal idea to a practically applicable inference tool for simulator-based statistical models, which are becoming increasingly popular in many research domains. The computational feasibility of ABC for practical applications has been recently boosted by adopting techniques from machine learning to build surrogate models for the approximate likelihood or posterior and by the introduction of a general-purpose software platform with several advanced features, including automated parallelisation. Here we demonstrate the strengths of the advances in ABC by going beyond the typical benchmark examples and considering real applications in astronomy, infectious disease epidemiology, personalised cancer therapy and financial prediction. We anticipate that the emerging success of ABC in producing actual added value and quantitative insights in the real world will continue to inspire a plethora of further applications across different fields of science, social science and technology. - Ability-based optimization of touchscreen interactions
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2018-01-01) Sarcar, Sayan; Jokinen, Jussi P.P.; Oulasvirta, Antti; Wang, Zhenxin; Silpasuwanchai, Chaklam; Ren, XiangshiAbility-based optimization is a computational approach for improving interface designs for users with sensorimotor and cognitive impairments. Designs are created by an optimizer, evaluated against task-specific cognitive models, and adapted to individual abilities. The approach does not necessitate extensive data collection and could be applied both automatically and manually by users, designers, or caretakers. As a first step, the authors present optimized touchscreen layouts for users with tremor and dyslexia that potentially improve text-entry speed and reduce error. - AbODE: Ab initio antibody design using conjoined ODEs
A4 Artikkeli konferenssijulkaisussa(2023-07) Verma, Yogesh; Heinonen, Markus; Garg, VikasAntibodies are Y-shaped proteins that neutralize pathogens and constitute the core of our adaptive immune system. De novo generation of new antibodies that target specific antigens holds the key to accelerating vaccine discovery. However, this co-design of the amino acid sequence and the 3D structure subsumes and accentuates, some central challenges from multiple tasks including protein folding (sequence to structure), inverse folding (structure to sequence), and docking (binding). We strive to surmount these challenges with a new generative model AbODE that extends graph PDEs to accommodate both contextual information and external interactions. Unlike existing approaches, AbODE uses a single round of full-shot decoding, and elicits continuous differential attention that encapsulates, and evolves with, latent interactions within the antibody as well as those involving the antigen. We unravel fundamental connections between AbODE and temporal networks as well as graph-matching networks. The proposed model significantly outperforms existing methods on standard metrics across benchmarks. - Absence makes the heart grow fonder: social compensation when failure to interact risks weakening a relationship
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2017) Bhattacharya, Kunal; Ghosh, Asim; Monsivais-Velazquez, Daniel; Dunbar, Robin; Kaski, KimmoSocial networks require active relationship maintenance if they are to be kept at a constant level of emotional closeness. For primates, including humans, failure to interact leads inexorably to a decline in relationship quality, and a consequent loss of the benefits that derive from individual relationships. As a result, many social species compensate for weakened relationships by investing more heavily in them. Here we study how humans behave in similar situations, using data from mobile call detail records from a European country. For the less frequent contacts between pairs of communicating individuals we observe a logarithmic dependence of the duration of the succeeding call on the time gap with the previous call. We find that such behaviour is likely when the individuals in these dyadic pairs have the same gender and are in the same age bracket as well as being geographically distant. Our results indicate that these pairs deliberately invest more time in communication so as to reinforce their social bonding and prevent their relationships decaying when these are threatened by lack of interaction. - Access Control and Machine Learning: Evasion and Defenses
School of Science | Doctoral dissertation (article-based)(2019) Juuti, MikaMachine learning (ML) and artificial intelligence (AI) systems have experienced significant proliferation during the recent years, for example in the new market of "machine learning as a service". ML is also increasingly being deployed in security-critical applications, such as access control systems. ML can be used to make security systems easier to use, or to defend against specific attacks, such as the "relay attack". Such ML applications are particularly sensitive to the recent development of "adversarial machine learning", where weaknesses in machine learning systems are exploited to undermine some security-critical property. For example, "evasion attacks" undermine a ML system's prediction integrity, while "model extraction attacks" undermine the system's confidentiality. It has become increasingly important to evaluate ML applications against such undesired behavior. The work described in this dissertation is divided into three parts. In the first part, I evaluate how security properties in so-called transparent authentication systems can be improved using machine learning, and describe how to evaluate security against strong adversaries. In the second part, I present state-of-the-art evasion and model extraction attacks against image classification systems. In the third part, I evaluate state-of-the-art hate speech classifiers against evasion attacks, and present a method of artificially creating credible fake restaurant reviews. Finally, I present general observations and conclusions about both transparent authentication, and the feasibility of using ML for purposes such as moderation. - Access Control for Implantable Medical Devices
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2021) Camara, Carmen; Peris-Lopez, Pedro; De Fuentes, Jose Maria; Marchal, SamuelThe telemetry incorporate in the new generation of Implantable Medical Devices (IMDs) allows remote access and re-programming without interfering with the daily routine of their holders. Despite the benefits of this new feature, such remote access raises new threats related to the access of unauthorized entities to IMDs. Cardiac implants represent the most deployed types of IMD nowadays. Current solutions, to control their remote access, usually use a single feature for authentication. However, this feature is easily replicable, making these authentication schemes vulnerable to attacks. To overcome this limitation, we propose in this article a distance bounding protocol to manage access control of IMDs: ACIMD. ACIMD combines two security mechanisms, namely, identity verification (authentication) and proximity verification (distance checking). The authentication mechanism, formally and informally verified, conforms to the ISO/IEC 9798-2 standard. The distance checking is performed using the whole Electrocardiogram (ECG) signal and relies on the correlation coefficient (comparing an external versus an internal ECG signal) in the Hadamard domain. We evaluate the accuracy and security of ACIMD access control using ECG signals of 199 individuals recorded over 24 hours while considering three adversary strategies. Our results show that ACIMD is 92.92% accurate. - Access Time Improvement Framework for Standardized IoT Gateways
A4 Artikkeli konferenssijulkaisussa(2019-03-01) Javed, Asad; Yousefnezhad, Narges; Robert, Jeremy; Heljanko, Keijo; Framling, KaryInternet of Things (IoT) is a computing infrastructure underlying powerful systems and applications, enabling autonomous interconnection of people, vehicles, devices, and information systems. Many IoT sectors such as smart grid or smart mobility will benefit from the recent evolutions of the smart city initiatives for building more advanced IoT services, from the collection of human- and machine-generated data to their storage and analysis. It is therefore of utmost importance to manage the volume, velocity, and variety of the data, in particular at the IoT gateways level, where data are published and consumed. This paper proposes an access time improvement framework to optimize the publication and consumption steps, the storage and retrieval of data at the gateways level to be more precise. This new distributed framework relies on a consistent hashing mechanism and modular characteristics of microservices to ensure a flexible and scalable solution. Applied and assessed on a real case study, experimental results show how the proposed framework improves data access time for standardized IoT gateways. - Accounting for environmental variation in co-occurrence modelling reveals the importance of positive interactions in root-associated fungal communities
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2020-07-01) Abrego, Nerea; Roslin, Tomas; Huotari, Tea; Tack, Ayco J.M.; Lindahl, Björn D.; Tikhonov, Gleb; Somervuo, Panu; Schmidt, Niels Martin; Ovaskainen, OtsoUnderstanding the role of interspecific interactions in shaping ecological communities is one of the central goals in community ecology. In fungal communities, measuring interspecific interactions directly is challenging because these communities are composed of large numbers of species, many of which are unculturable. An indirect way of assessing the role of interspecific interactions in determining community structure is to identify the species co-occurrences that are not constrained by environmental conditions. In this study, we investigated co-occurrences among root-associated fungi, asking whether fungi co-occur more or less strongly than expected based on the environmental conditions and the host plant species examined. We generated molecular data on root-associated fungi of five plant species evenly sampled along an elevational gradient at a high arctic site. We analysed the data using a joint species distribution modelling approach that allowed us to identify those co-occurrences that could be explained by the environmental conditions and the host plant species, as well as those co-occurrences that remained unexplained and thus more probably reflect interactive associations. Our results indicate that not only negative but also positive interactions play an important role in shaping microbial communities in arctic plant roots. In particular, we found that mycorrhizal fungi are especially prone to positively co-occur with other fungal species. Our results bring new understanding to the structure of arctic interaction networks by suggesting that interactions among root-associated fungi are predominantly positive. - Accounting for spatial dependence improves relative abundance estimates in a benthic marine species structured as a metapopulation
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2021-08) Cavieres, Joaquin; Monnahan, Cole C.; Vehtari, AkiSea urchin (Loxechinus albus) is one of the most important benthic resource in Chile. Due to their large-scale spatial metapopulation structure, sea urchin subpopulations are interconnected by larval dispersion, so the recovery of local abundance depends on the distance and hydrodynamic characteristics of their spatial domain. Currently, this resource is evaluated with classical stock assessment models, using standardized catch per unit effort (an index of relative abundance) as a key piece of information to determine catch quotas and achieve sustainability. However, these estimates assume hyperstability for the total population, ignoring spatial dependence among fishing sites, which is a fundamental concept for populations structured as metapopulation. We develop a Bayesian catch standardization model with explicit spatial dependence to better address the structure of this population. The proposed model performs statistically better compared to a model without spatial dependence, based on leave-one-out cross-validation, and predictive distributions also show that parameter estimation is consistent with the data. We argue that incorporating spatial structure improves the estimated relative abundance index in a population structured as a metapopulation. Our improved index of abundance will lead to better assessments and management advice, thus improving the sustainability of the stock. - Accounting for stellar activity signals in radial-velocity data by using change point detection techniques star
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2022-08-23) Simola, U.; Bonfanti, A.; Dumusque, X.; Cisewski-Kehe, J.; Kaski, S.; Corander, J.Context. Active regions on the photosphere of a star have been the major obstacle for detecting Earth-like exoplanets using the radial velocity (RV) method. A commonly employed solution for addressing stellar activity is to assume a linear relationship between the RV observations and the activity indicators along the entire time series, and then remove the estimated contribution of activity from the variation in RV data (overall correction method). However, since active regions evolve on the photosphere over time, correlations between the RV observations and the activity indicators will correspondingly be anisotropic. Aims. We present an approach that recognizes the RV locations where the correlations between the RV and the activity indicators significantly change in order to better account for variations in RV caused by stellar activity. Methods. The proposed approach uses a general family of statistical breakpoint methods, often referred to as change point detection (CPD) algorithms; several implementations of which are available in R and python. A thorough comparison is made between the breakpoint-based approach and the overall correction method. To ensure wide representativity, we use measurements from real stars that have different levels of stellar activity and whose spectra have different signal-to-noise ratios. Results. When the corrections for stellar activity are applied separately to each temporal segment identified by the breakpoint method, the corresponding residuals in the RV time series are typically much smaller than those obtained by the overall correction method. Consequently, the generalized Lomb-Scargle periodogram contains a smaller number of peaks caused by active regions. The CPD algorithm is particularly effective when focusing on active stars with long time series, such as alpha Cen B. In that case, we demonstrate that the breakpoint method improves the detection limit of exoplanets by 74% on average with respect to the overall correction method. Conclusions. CPD algorithms provide a useful statistical framework for estimating the presence of change points in a time series. Since the process underlying the RV measurements generates anisotropic data by its intrinsic properties, it is natural to use CPD to obtain cleaner signals from RV data. We anticipate that the improved exoplanet detection limit may lead to a widespread adoption of such an approach. Our test on the HD 192310 planetary system is encouraging, as we confirm the presence of the two hosted exoplanets and we determine orbital parameters consistent with the literature, also providing much more precise estimates for HD 192310 c. - Accurate Estimate of the Advantage of Impossible Differential Attacks
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2017-09-19) Blondeau, CélineImpossible differential attacks, which are taking advantage of differentials that cannot occur, are powerful attacks for block cipher primitives. The power of such attacks is often measured in terms of the advantage — number of key-bits found during the key sieving phase — which determines the time complexity of the exhaustive key search phase. The statistical model used to compute this advantage has been introduced in the seminal work about the resistance of the DEAL cipher to impossible differential attacks. This model, which has not been modified since the end of the 1990s, is implicitly based on the Poisson approximation of the binomial distribution. In this paper, we investigate this commonly used model and experimentally illustrate that random permutations do not follow it. Based on this observation, we propose more accurate estimates of the advantage of an impossible differential attack. The experiments illustrate the accuracy of the estimate derived from the multivariate hypergeometric distribution. The maximal advantage –using the full codebook– of an impossible differential attack is also derived. - Achievement Goal Orientation Profiles and Performance in a Programming MOOC
A4 Artikkeli konferenssijulkaisussa(2020-06-15) Polso, Kukka Maaria; Tuominen, Heta; Hellas, Arto; Ihantola, PetriIt has been suggested that performance goals focused on appearing talented (appearance goals) and those focused on outperforming others (normative goals) have different consequences, for example, regarding performance. Accordingly, applying this distinction into appearance and normative goals alongside mastery goals, this study explores what kinds of achievement goal orientation profiles are identified among over 2000 students participating in an introductory programming MOOC. Using Two-Step cluster analysis, five distinct motivational profiles are identified. Course performance and demographics of students with different goal orientation profiles are mostly similar. Students with Combined Mastery and Performance Goals perform slightly better than students with Low Goals. The observations are largely in line with previous studies conducted in different contexts. The differentiation of appearance and normative performance goals seemed to yield meaningful motivational profiles, but further studies are needed to establish their relevance and investigate whether this information can be used to improve teaching. - Acoustic Coatings—A Discreet Way to Control Acoustic Environment
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2021-05-11) Cucharero, Jose; Hänninen, Tuomas; Makkonen, Marko; Lokki, TapioAcoustic comfort is directly related to enhanced well-being and performance of people. A typical challenge faced by architects and acousticians is to achieve adequate acoustics while maintaining the aesthetics of the space and reducing the visual aspects of acoustic materials and elements. In this study, we present a biofiber-based acoustic coating as a feasible solution to improve acoustic environments while preserving the aesthetics of spaces. An acoustic coating is a thin layer of absorption material, but the coating can be sprayed on other sound absorbing structures to make it more effective on a wide frequency range. In addition, this biofiber-based coating acts as a carbon sink during its operating life, thus reducing the carbon footprint of the building. Therefore, the coating is sustainable and is an environmental friendly solution. The absorption properties of the biofiber-based coating are demonstrated in the present study with three case studies, which all had demanding requirements to conceal the acoustic structures. - Acoustic Scattering for Spatial Audio Applications
School of Science | Doctoral dissertation (article-based)(2022) Gonzalez, RaimundoModeling of sound propagation on the context of acoustic design and interactive applications have mainly focused on room acoustics as well as source and receiver modeling. In order to enrich the description and perceptual immersion of virtual sound-fields, modeling frameworks can also include the effects of scattering of bodies within the physical space. One of the main challenges in modeling the effects of scattering, is that its behaviour not only depends on the geometry of the scatterer but also the direction of arrival of the incident field. This thesis is a collection of five publications, the first two studies focus on the effects of near-field sources, and the last three studies involve the effects of scattering within spatial audio applications. The first publication explores the effects of near-field sources on High-order Ambisonics recording, processing and binaural reproduction. Results indicate that while near-field sources introduce low-frequency proximity gains in high-order microphones arrays, the regularization stages in Ambisonics recording prevents excessive gains. The second publication explores the directivity of near-field speech of 24 subjects and evaluates various repeatable speech reproduction alternatives. The third publication presents a scheme for encoding the acoustic scattering of arbitrary geometries into the spherical harmonic domain. After encoding, the scattering is represented as a multiple-input multiple-output matrix which describes the relation between the incoming and outgoing scattering modes of a geometry. This method allows for the standard transformations in the spherical harmonic domain (rotation, translation, scaling) and it is compatible with existing spatial audio frameworks such as Ambisonics and image-source methods. This method is validated using boundary element method simulations and indicates minimal synthesis error. The fourth publication presents a method to encode the space domain signals from a microphone array with arbitrary geometry and irregularly distributed sensors into Ambisonics. The algorithm relies on the array response and its enclosure's scattering properties to solve the direction of various active sources as well as the diffuse properties of the sound-field. Objective and subjective evaluations indicate that the proposed method outperforms traditional linear encoding. The fifth publication extends the method presented in the third publication by allowing sector-based encoding of acoustic scattering, optimal for geometries and surfaces which do not require entire spherical radiation. This last publication also presents a method to compress the data of the scattering matrix, allowing for more efficient memory storage. Methods proposed in the third and fifth publications can be used to introduce scattering geometries into interactive sound environments to produce more descriptive sound-fields while the fourth publication can be used to develop Ambisonic recording arrays on practical devices such as wearables and head-mounted displays. - Acoustic Transparency and the Changing Soundscape of Auditory Mixed Reality
A4 Artikkeli konferenssijulkaisussa(2020-04-21) McGill, Mark; Brewster, Stephen; McGookin, David; Wilson, GrahamAuditory headsets capable of actively or passively intermixing both real and virtual sounds are in-part acoustically transparent. This paper explores the consequences of acoustic transparency, both on the perception of virtual audio content, given the presence of a real-world auditory backdrop, and more broadly in facilitating a wearable, personal, private, always-available soundspace. We experimentally compare passive acoustically transparent, and active noise cancelling, orientation-tracked auditory headsets across a range of content types, both indoors and outdoors for validity. Our results show differences in terms of presence, realness and externalization for select content types. Via interviews and a survey, we discuss attitudes toward acoustic transparency (e.g. Being perceived as safer), the potential shifts in audio usage that might be precipitated by adoption, and reflect on how such headsets and experiences fit within the area of Mixed Reality.