22,483 research outputs found

    Security and Privacy Problems in Voice Assistant Applications: A Survey

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    Voice assistant applications have become omniscient nowadays. Two models that provide the two most important functions for real-life applications (i.e., Google Home, Amazon Alexa, Siri, etc.) are Automatic Speech Recognition (ASR) models and Speaker Identification (SI) models. According to recent studies, security and privacy threats have also emerged with the rapid development of the Internet of Things (IoT). The security issues researched include attack techniques toward machine learning models and other hardware components widely used in voice assistant applications. The privacy issues include technical-wise information stealing and policy-wise privacy breaches. The voice assistant application takes a steadily growing market share every year, but their privacy and security issues never stopped causing huge economic losses and endangering users' personal sensitive information. Thus, it is important to have a comprehensive survey to outline the categorization of the current research regarding the security and privacy problems of voice assistant applications. This paper concludes and assesses five kinds of security attacks and three types of privacy threats in the papers published in the top-tier conferences of cyber security and voice domain.Comment: 5 figure

    UniverSeg: Universal Medical Image Segmentation

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    While deep learning models have become the predominant method for medical image segmentation, they are typically not capable of generalizing to unseen segmentation tasks involving new anatomies, image modalities, or labels. Given a new segmentation task, researchers generally have to train or fine-tune models, which is time-consuming and poses a substantial barrier for clinical researchers, who often lack the resources and expertise to train neural networks. We present UniverSeg, a method for solving unseen medical segmentation tasks without additional training. Given a query image and example set of image-label pairs that define a new segmentation task, UniverSeg employs a new Cross-Block mechanism to produce accurate segmentation maps without the need for additional training. To achieve generalization to new tasks, we have gathered and standardized a collection of 53 open-access medical segmentation datasets with over 22,000 scans, which we refer to as MegaMedical. We used this collection to train UniverSeg on a diverse set of anatomies and imaging modalities. We demonstrate that UniverSeg substantially outperforms several related methods on unseen tasks, and thoroughly analyze and draw insights about important aspects of the proposed system. The UniverSeg source code and model weights are freely available at https://universeg.csail.mit.eduComment: Victor and Jose Javier contributed equally to this work. Project Website: https://universeg.csail.mit.ed

    Technical Dimensions of Programming Systems

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    Programming requires much more than just writing code in a programming language. It is usually done in the context of a stateful environment, by interacting with a system through a graphical user interface. Yet, this wide space of possibilities lacks a common structure for navigation. Work on programming systems fails to form a coherent body of research, making it hard to improve on past work and advance the state of the art. In computer science, much has been said and done to allow comparison of programming languages, yet no similar theory exists for programming systems; we believe that programming systems deserve a theory too. We present a framework of technical dimensions which capture the underlying characteristics of programming systems and provide a means for conceptualizing and comparing them. We identify technical dimensions by examining past influential programming systems and reviewing their design principles, technical capabilities, and styles of user interaction. Technical dimensions capture characteristics that may be studied, compared and advanced independently. This makes it possible to talk about programming systems in a way that can be shared and constructively debated rather than relying solely on personal impressions. Our framework is derived using a qualitative analysis of past programming systems. We outline two concrete ways of using our framework. First, we show how it can analyze a recently developed novel programming system. Then, we use it to identify an interesting unexplored point in the design space of programming systems. Much research effort focuses on building programming systems that are easier to use, accessible to non-experts, moldable and/or powerful, but such efforts are disconnected. They are informal, guided by the personal vision of their authors and thus are only evaluable and comparable on the basis of individual experience using them. By providing foundations for more systematic research, we can help programming systems researchers to stand, at last, on the shoulders of giants

    Pathways to suicide among police in Rajasthan: perceptions and experiences of police personnel

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    Background: Evidence regarding the experience and perceptions of police personnel with suicide in South Asia is limited. This study explored the lived experiences and perceptions of suicide among police personnel in an Indian state. The focus was on explanations of and reasons for suicide. Methods: We conducted 20 qualitative interviews in 2021 with police of different ranks, guided by a topic guide. The reflexive thematic analysis approach was supported by the use of NVivo 12, a qualitative software package. Results: We explore three intersecting key themes around suicide in the police force, including: (1) the stressful police environment; (2) expectations of mental strength; and (3) police image and help-seeking. We discuss the tensions between these themes and how to address the challenges of supporting police personnel. Conclusions: To support and improve police personnel’s mental well-being training and support are needed but also broader changes at the organisational level. These need to take social and historical factors into account. An increased level of suicide and mental health literacy will not only benefit the police force but also the general public, and it would be very timely with recent changes in the Indian mental health and suicide policy context

    Ausubel's meaningful learning re-visited

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    This review provides a critique of David Ausubel’s theory of meaningful learning and the use of advance organizers in teaching. It takes into account the developments in cognition and neuroscience which have taken place in the 50 or so years since he advanced his ideas, developments which challenge our understanding of cognitive structure and the recall of prior learning. These include (i) how effective questioning to ascertain previous knowledge necessitates in-depth Socratic dialogue; (ii) how many findings in cognition and neuroscience indicate that memory may be non-representational, thereby affecting our interpretation of student recollections; (iii) the now recognised dynamism of memory; (iv) usefully regarding concepts as abilities or simulators and skills; (v) acknowledging conscious and unconscious memory and imagery; (vi) how conceptual change involves conceptual coexistence and revision; (vii) noting linguistic and neural pathways as a result of experience and neural selection; and (viii) recommending that wider concepts of scaffolding should be adopted, particularly given the increasing focus on collaborative learning in a technological world

    Grasping nothing: a study of minimal ontologies and the sense of music

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    If music were to have a proper sense – one in which it is truly given – one might reasonably place this in sound and aurality. I contend, however, that no such sense exists; rather, the sense of music takes place, and it does so with the impossible. To this end, this thesis – which is a work of philosophy and music – advances an ontology of the impossible (i.e., it thinks the being of what, properly speaking, can have no being) and considers its implications for music, articulating how ontological aporias – of the event, of thinking the absolute, and of sovereignty’s dismemberment – imply senses of music that are anterior to sound. John Cage’s Silent Prayer, a nonwork he never composed, compels a rerethinking of silence on the basis of its contradictory status of existence; Florian Hecker et al.’s Speculative Solution offers a basis for thinking absolute music anew to the precise extent that it is a discourse of meaninglessness; and Manfred Werder’s [yearn] pieces exhibit exemplarily that music’s sense depends on the possibility of its counterfeiting. Inso-much as these accounts produce musical senses that take the place of sound, they are also understood to be performances of these pieces. Here, then, thought is music’s organon and its instrument

    Copy-paste data augmentation for domain transfer on traffic signs

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    City streets carry a lot of information that can be exploited to improve the quality of the services the citizens receive. For example, autonomous vehicles need to act accordingly to all the element that are nearby the vehicle itself, like pedestrians, traffic signs and other vehicles. It is also possible to use such information for smart city applications, for example to predict and analyze the traffic or pedestrian flows. Among all the objects that it is possible to find in a street, traffic signs are very important because of the information they carry. This information can in fact be exploited both for autonomous driving and for smart city applications. Deep learning and, more generally, machine learning models however need huge quantities to learn. Even though modern models are very good at gener- alizing, the more samples the model has, the better it can generalize between different samples. Creating these datasets organically, namely with real pictures, is a very tedious task because of the wide variety of signs available in the whole world and especially because of all the possible light, orientation conditions and con- ditions in general in which they can appear. In addition to that, it may not be easy to collect enough samples for all the possible traffic signs available, cause some of them may be very rare to find. Instead of collecting pictures manually, it is possible to exploit data aug- mentation techniques to create synthetic datasets containing the signs that are needed. Creating this data synthetically allows to control the distribution and the conditions of the signs in the datasets, improving the quality and quantity of training data that is going to be used. This thesis work is about using copy-paste data augmentation to create synthetic data for the traffic sign recognition task

    A life ‘in and with nature?’ Developing nature engaging and nature enhancing pedagogies for babies and toddlers

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    The holistic relationship between children and nature is at the heart of Froebel’s philosophy and practice: he took for granted that young children would grow up ‘in’ and ‘with’ nature. This paper explores the contemporary relevance of this thinking to babies and toddlers in early childhood education and care (ECEC) settings. It is based on a research project funded by the Froebel Trust which explores outdoor provision in English settings. Our findings suggest that whilst the pedagogic potential of the outdoors for babies and toddlers appears to be generally recognised, there is little emphasis on supporting them to engage with the natural characteristics of the outdoor environment. Concerns about safety and an emphasis on physical activity mean that natural elements may be discouraged in favour of manufactured alternatives such as artificial grass or commercially produced resources. We argue that Froebelian philosophy offers a much-needed theoretical lens that can illuminate the limitations of such practices for both the human and non-human world. Importantly, we highlight the interconnectedness of human and environmental health and suggest the need to develop nature engaging and nature enhancing pedagogies from birth

    Implementing Health Impact Assessment as a Required Component of Government Policymaking: A Multi-Level Exploration of the Determinants of Healthy Public Policy

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    It is widely understood that the public policies of ‘non-health’ government sectors have greater impacts on population health than those of the traditional healthcare realm. Health Impact Assessment (HIA) is a decision support tool that identifies and promotes the health benefits of policies while also mitigating their unintended negative consequences. Despite numerous calls to do so, the Ontario government has yet to implement HIA as a required component of policy development. This dissertation therefore sought to identify the contexts and factors that may both enable and impede HIA use at the sub-national (i.e., provincial, territorial, or state) government level. The three integrated articles of this dissertation provide insights into specific aspects of the policy process as they relate to HIA. Chapter one details a case study of purposive information-seeking among public servants within Ontario’s Ministry of Education (MOE). Situated within Ontario’s Ministry of Health (MOH), chapter two presents a case study of policy collaboration between health and ‘non-health’ ministries. Finally, chapter three details a framework analysis of the political factors supporting health impact tool use in two sub-national jurisdictions – namely, Québec and South Australia. MOE respondents (N=9) identified four components of policymaking ‘due diligence’, including evidence retrieval, consultation and collaboration, referencing, and risk analysis. As prospective HIA users, they also confirmed that information is not routinely sought to mitigate the potential negative health impacts of education-based policies. MOH respondents (N=8) identified the bureaucratic hierarchy as the brokering mechanism for inter-ministerial policy development. As prospective HIA stewards, they also confirmed that the ministry does not proactively flag the potential negative health impacts of non-health sector policies. Finally, ‘lessons learned’ from case articles specific to Québec (n=12) and South Australia (n=17) identified the political factors supporting tool use at different stages of the policy cycle, including agenda setting (‘policy elites’ and ‘political culture’), implementation (‘jurisdiction’), and sustained implementation (‘institutional power’). This work provides important insights into ‘real life’ policymaking. By highlighting existing facilitators of and barriers to HIA use, the findings offer a useful starting point from which proponents may tailor context-specific strategies to sustainably implement HIA at the sub-national government level

    Beyond the icon: Core cognition and the bounds of perception

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    This paper refines a controversial proposal: that core systems belong to a perceptual kind, marked out by the format of its representational outputs. Following Susan Carey, this proposal has been understood in terms of core representations having an iconic format, like certain paradigmatically perceptual outputs. I argue that they don’t, but suggest that the proposal may be better formulated in terms of a broader analogue format type. Formulated in this way, the proposal accommodates the existence of genuine icons in perception, and avoids otherwise troubling objections
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