195 research outputs found

    RAISING INTERCULTURAL COMPETENCE OF AMERICAN STUDENTS: A PILOT STUDY

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    International students and study abroad programs are major components of internationalization efforts for institutions (Beelen & Jones, 2015). Domestic students however do not have any established practice of intercultural training or orientation, even though most universities in America accept international students and promote internationalization which is the increase of intergroup contact as part of globalization (Sakurauchi, 2014). It is crucial to raise the intercultural communication competence (ICC) of American students so they can benefit from the internationalization efforts of universities (Sakurauchi, 2014). This study attempted see if the ICC can be raised by implementing an IPM training in a treatment and control group in a basic communication course (BCC). The questionnaire revealed that students mostly improved only in two dimensions of the IPM: positioning and framing. The reflective question revealed empathy as a major theme of the ICC success. This pilot study shows that the IPM training is a promising training to include in the BCC

    Improving MPI Application Communication Time with an Introspection Monitoring Library

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    As IPDPS in-person meeting was cancelled, PDSEC will be onlineInternational audienceIn this paper we describe how to improve communication time of MPI parallel applications with the use of a library that enables to monitor MPI applications and allows for introspection (the program itself can query the state of the monitoring system). Based on previous work, this library is able to see how collective communications are decomposed into point-to-point messages. It also features monitoring sessions that allow suspending and restarting the monitoring, limiting it to specific portions of the code. Experiments show that the monitoring overhead is very small and that the proposed features allow for dynamic and efficient rank reordering enabling up to 2-time reduction of communication parts of some program

    MapNeXt: Revisiting Training and Scaling Practices for Online Vectorized HD Map Construction

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    High-Definition (HD) maps are pivotal to autopilot navigation. Integrating the capability of lightweight HD map construction at runtime into a self-driving system recently emerges as a promising direction. In this surge, vision-only perception stands out, as a camera rig can still perceive the stereo information, let alone its appealing signature of portability and economy. The latest MapTR architecture solves the online HD map construction task in an end-to-end fashion but its potential is yet to be explored. In this work, we present a full-scale upgrade of MapTR and propose MapNeXt, the next generation of HD map learning architecture, delivering major contributions from the model training and scaling perspectives. After shedding light on the training dynamics of MapTR and exploiting the supervision from map elements thoroughly, MapNeXt-Tiny raises the mAP of MapTR-Tiny from 49.0% to 54.8%, without any architectural modifications. Enjoying the fruit of map segmentation pre-training, MapNeXt-Base further lifts the mAP up to 63.9% that has already outperformed the prior art, a multi-modality MapTR, by 1.4% while being ∼1.8×\sim1.8\times faster. Towards pushing the performance frontier to the next level, we draw two conclusions on practical model scaling: increased query favors a larger decoder network for adequate digestion; a large backbone steadily promotes the final accuracy without bells and whistles. Building upon these two rules of thumb, MapNeXt-Huge achieves state-of-the-art performance on the challenging nuScenes benchmark. Specifically, we push the mapless vision-only single-model performance to be over 78% for the first time, exceeding the best model from existing methods by 16%

    Phenomenalism, Skepticism, and Sellars's Account of Intentionality

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    I take up two questions raised by Luz Christopher Seiberth's meticulous reconstruction of Wilfrid Sellars's theory of intentionality. The first is whether we should regard Sellars as a transcendental phenomenalist in the most interesting sense of the term: as denying that even an ideally adequate conceptual structure would enable us to represent worldly objects as they are in themselves. I agree with Seiberth that the answer is probably yes, but I suggest that this is due not to Sellars's rejection of the Myth of the Given or appeal to image-models (as Seiberth maintains), but to his view of modality as categorial but as absent from the world an sich. The second is whether, as Richard Rorty complained, Sellars's appeal to picturing lands his theory of intentionality in intractable skepticism. Pace Seiberth, I argue that the transcendental role of picturing does not mitigate this problem, and I suggest that Sellars's most fruitful resource for doing so is not his semantic externalism, but his purely pragmatic response to skepticism

    HyperDbg: Reinventing Hardware-Assisted Debugging (Extended Version)

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    Software analysis, debugging, and reverse engineering have a crucial impact in today's software industry. Efficient and stealthy debuggers are especially relevant for malware analysis. However, existing debugging platforms fail to address a transparent, effective, and high-performance low-level debugger due to their detectable fingerprints, complexity, and implementation restrictions. In this paper, we present HyperDbg, a new hypervisor-assisted debugger for high-performance and stealthy debugging of user and kernel applications. To accomplish this, HyperDbg relies on state-of-the-art hardware features available in today's CPUs, such as VT-x and extended page tables. In contrast to other widely used existing debuggers, we design HyperDbg using a custom hypervisor, making it independent of OS functionality or API. We propose hardware-based instruction-level emulation and OS-level API hooking via extended page tables to increase the stealthiness. Our results of the dynamic analysis of 10,853 malware samples show that HyperDbg's stealthiness allows debugging on average 22% and 26% more samples than WinDbg and x64dbg, respectively. Moreover, in contrast to existing debuggers, HyperDbg is not detected by any of the 13 tested packers and protectors. We improve the performance over other debuggers by deploying a VMX-compatible script engine, eliminating unnecessary context switches. Our experiment on three concrete debugging scenarios shows that compared to WinDbg as the only kernel debugger, HyperDbg performs step-in, conditional breaks, and syscall recording, 2.98x, 1319x, and 2018x faster, respectively. We finally show real-world applications, such as a 0-day analysis, structure reconstruction for reverse engineering, software performance analysis, and code-coverage analysis

    Enabling autistic sociality: unrealised potentials in two-sided social interaction

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    Research on autism, which is defined as a life-long developmental disability affecting social interaction, has focussed predominantly on how autistic individuals perceive and interact with others with less emphasis on the perspectives of their interactional partners. Yet autistic viewpoints have highlighted how other people are part of a two-way breakdown in interaction originating from differences between people rather than the deficit of any one individual, a phenomenon known as the double empathy problem. A gap therefore exists in the literature in terms of understanding how autistic sociality (i.e. the range of social opportunities possible for a given individual on the spectrum) is shaped by different interactional partners. This thesis examines the double empathy problem in three interactional contexts. Study 1 examines relationships between autistic people and their family members through focussing on perspective-taking, the ability to impute mental states to others. In light of prior research where autistic abilities have been assessed using abstract scenarios, Study 1 implements a two-way measure of perspective-taking which considers both sides of 22 real-life relationships (n=44) consisting of autistic adults and their family members, to understand how autistic people are seen by familiar others as well as vice versa. It uses a mixed-methods approach, where members of each dyad were individually asked about 12 topics, providing quantitative scores and qualitative explanation of their rating of Self, their rating of their partner, and their predicted rating by their partner. Comparison of perspectives provided a means for detecting misunderstandings and their underlying rationale. The contribution of Study 1 is that it shows perspective-taking is two-sided: family members can be biased in underestimating the perspective-taking of their autistic relatives, while autistic adults are aware of being negatively viewed despite disagreeing with such views. Study 2 examines interactions between autistic adults (n=30) partaking in a naturally occurring activity of video-gaming at a charity. It is a qualitative study using participant observation, with each conversational turn systematically rated in terms of coherence, affect and symmetry to identify the key features of neurodivergent intersubjectivity, the process through which autistic people build shared understanding in their own non-normative ways. The contribution of Study 2 is to identify two forms of neurodivergent intersubjectivity which enable shared understanding to be achieved, but which have traditionally been viewed as undesirable from a normative social viewpoint: a generous assumption of common ground that, when understood, lead to rapid rapport, and, when not understood, resulted in potentially disruptive utterances; and a low demand for coordination that ameliorated many challenges associated with disruptive turns. Study 3 examines interactions involving lay people (n=256) who believe they are interacting with an autistic partner through an online collaborative game, when in fact they are playing with an intelligent virtual agent (IVA) who behaves the same way for all participants. Its contribution is methodological as it develops a new application for simulating interactions in experimental research called Dyad3D. Study 3 uses Dyad3D to explore how disclosure of an autism diagnosis by the IVA affects social perception and social behaviour in comparison to a disclosure of dyslexia and a condition where there is no diagnostic disclosure. Combined with a post-game questionnaire, Study 3 triangulates self-reported (quantitative rating scales and qualitative explanation) and behavioural measures (quantitative scores of actions within the game) to understand the interplay of positive and negative discrimination elicited through using the label of autism. It highlights that diagnostic disclosure of autism leads to significant positive bias in social perception when compared to a disclosure of dyslexia or a no disclosure condition; yet participants are not as helpful towards the autistic IVA as they think they are, indicating a potential bias in helping behaviour. The thesis takes an abductive methodological approach which integrates with a wider call for a more participatory model of research in the study of autism. Abduction is a form of reasoning which involves the iterative development of a hypothesis that holds the best explanatory scope for the underlying phenomena observed. It is inherently aligned with a participatory model of research because abduction involves the ongoing exploration of ideas that may originate from multiple sources (i.e. interactions with autistic people as well as research outputs). Taking a more holistic approach to the development of knowledge with autistic people which recognises the legitimacy of different claims to knowledge is important, because prior research in the field has often failed to critically reflect on researcherparticipant positionality and the principals underlying the development of research agenda. For this reason, the thesis details the participatory activities which surround and interconnect with the development of the three empirical studies. Overall the thesis contributes to understanding autistic sociality as a dynamic, interactionally shaped process. It reasons that autistic people have unrealised social potential, both in terms of imagining other perspectives (Study 1) and coordinating with others (Study 2). However, such social potential may not be easily recognised by other non-autistic people who may be biased in their assumptions about autism (Study 1 and Study 3). Consequently, the evidence presented in this thesis helps to explain some of the processes that underscore the double empathy problems reported in literature, including poor mental health (because autistic people are aware that they are misunderstood by others, see Study 1), employment prospects (because autistic social potential is under-recognised by others, see Study 1 and 3), and quality of life (because neurotypical standards of communication are not compatible with neurodivergent forms of intersubjectivity, see Study 2). The thesis therefore makes suggestions for how we design enabling environments which are sensitive to the dynamic factors that can enable autistic sociality to flourish

    Development of a Locomotion and Balancing Strategy for Humanoid Robots

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    The locomotion ability and high mobility are the most distinguished features of humanoid robots. Due to the non-linear dynamics of walking, developing and controlling the locomotion of humanoid robots is a challenging task. In this thesis, we study and develop a walking engine for the humanoid robot, NAO, which is the official robotic platform used in the RoboCup Spl. Aldebaran Robotics, the manufacturing company of NAO provides a walking module that has disadvantages, such as being a black box that does not provide control of the gait as well as the robot walk with a bent knee. The latter disadvantage, makes the gait unnatural, energy inefficient and exert large amounts of torque to the knee joint. Thus creating a walking engine that produces a quality and natural gait is essential for humanoid robots in general and is a factor for succeeding in RoboCup competition. Humanoids robots are required to walk fast to be practical for various life tasks. However, its complex structure makes it prone to falling during fast locomotion. On the same hand, the robots are expected to work in constantly changing environments alongside humans and robots, which increase the chance of collisions. Several human-inspired recovery strategies have been studied and adopted to humanoid robots in order to face unexpected and avoidable perturbations. These strategies include hip, ankle, and stepping, however, the use of the arms as a recovery strategy did not enjoy as much attention. The arms can be employed in different motions for fall prevention. The arm rotation strategy can be employed to control the angular momentum of the body and help to regain balance. In this master\u27s thesis, I developed a detailed study of different ways in which the arms can be used to enhance the balance recovery of the NAO humanoid robot while stationary and during locomotion. I model the robot as a linear inverted pendulum plus a flywheel to account for the angular momentum change at the CoM. I considered the role of the arms in changing the body\u27s moment of inertia which help to prevent the robot from falling or to decrease the falling impact. I propose a control algorithm that integrates the arm rotation strategy with the on-board sensors of the NAO. Additionally, I present a simple method to control the amount of recovery from rotating the arms. I also discuss the limitation of the strategy and how it can have a negative impact if it was misused. I present simulations to evaluate the approach in keeping the robot stable against various disturbance sources. The results show the success of the approach in keeping the NAO stable against various perturbations. Finally,I adopt the arm rotation to stabilize the ball kick, which is a common reason for falling in the soccer humanoid RoboCup competitions

    An Activity System As A Behavioristic Framework For The Elaboration Of Promotion Techniques

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    In this paper, we intended to examine the possibility to investigate two (2) influential theories: a. Activity Theory and b. Transformative Learning Theory (TLT) in order to develop a new behavioristic framework that could be introduced to aid the design and analysis of promotion techniques by approaching major promotion events of particular interest and with strategic content, as critical cases. First, we attempted to do this by categorizing sixty-eight (68) identified empirical papers into conceptual categories in accordance to the conceptual and theoretical framework. Second, we provided eleven (11) summary points and ten (10) interpretive claims. Third, we examined three (3) ISP Award Winners as critical cases studies [2002, 2004 and 2006 from three (3) different award categories: (a) Promotional Communication Point of Purchase, b) The Most Effective Loyalty Campaign and c) Digital Communications]. This examination gave us valuable information on the potentiality of developing an activity system for the design and analysis of promotion techniques. Thus, the phenomenon studied, through our new proposed micro-model, became more visible with some interesting theoretical and practical implications
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