Smooth Interaction Research Articles

Tangible images of real life scenes

Haptic technologies allow for adding a new “touching” modality into virtual scenes. 3D reconstruction of a real life scene results, however, often in millions of polygons which cannot be simultaneously visualized and haptically rendered. In this paper, we propose a way of haptic interaction with real life scenes where multiple original images of the real scenes are augmented with reconstructed polygon meshes. We present our solution to the problems of haptic model alignment with the images and interactive haptic rendering of large polygon meshes with reconstruction artifacts. In particular, the presented collision detection algorithm is not restricted by any hypothesis and robust enough to support smooth interaction with millions of polygons. The feasibility and usability of the proposed solution is evaluated in a user study.

Animating Wall-Bounded Turbulent Smoke via Filament-Mesh Particle-Particle Method.

Turbulent vortices in smoke flows are crucial for a visually interesting appearance. Unfortunately, it is challenging to efficiently simulate these appealing effects in the framework of vortex filament methods. The vortex filaments in grids scheme allows to efficiently generate turbulent smoke with macroscopic vortical structures, but suffers from the projection-related dissipation, and thus the small-scale vortical structures under grid resolution are hard to capture. In addition, this scheme cannot be applied in wall-bounded turbulent smoke simulation, which requires efficiently handling smoke-obstacle interaction and creating vorticity at the obstacle boundary. To tackle above issues, we propose an effective filament-mesh particle-particle (FMPP) method for fast wall-bounded turbulent smoke simulation with ample details. The Filament-Mesh component approximates the smooth long-range interactions by splatting vortex filaments on grid, solving the Poisson problem with a fast solver, and then interpolating back to smoke particles. The Particle-Particle component introduces smoothed particle hydrodynamics (SPH) turbulence model for particles in the same grid, where interactions between particles cannot be properly captured under grid resolution. Then, we sample the surface of obstacles with boundary particles, allowing the interaction between smoke and obstacle being treated as pressure forces in SPH. Besides, the vortex formation region is defined at the back of obstacles, providing smoke particles flowing by the separation particles with a vorticity force to simulate the subsequent vortex shedding phenomenon. The proposed approach can synthesize the lost small-scale vortical structures and also achieve the smoke-obstacle interaction with vortex shedding at obstacle boundaries in a lightweight manner. The experimental results demonstrate that our FMPP method can achieve more appealing visual effects than vortex filaments in grids scheme by efficiently simulating more vivid thin turbulent features.

Mean Field Limit of Interacting Filaments and Vector Valued Non-linear PDEs

Families of $N$ interacting curves are considered, with long range, mean field type, interaction. A family of curves defines a 1-current, concentrated on the curves, analog of the empirical measure of interacting point particles. This current is proved to converge, as $N$ goes to infinity, to a mean field current, solution of a nonlinear, vector valued, partial differential equation. In the limit, each curve interacts with the mean field current and two different curves have an independence property if they are independent at time zero. This set-up is inspired from vortex filaments in turbulent fluids, although for technical reasons we have to restrict to smooth interaction, instead of the singular Biot-Savart kernel. All these results are based on a careful analysis of a nonlinear flow equation for 1-currents, its relation with the vector valued PDE and the continuous dependence on the initial conditions.

Exact finite volume particle method with spherical-support kernels

The Finite Volume Particle Method (FVPM) is a meshless method for simulating fluid flows which includes many of the desirable features of mesh-based finite volume methods. In this paper, we develop a new 3-D FVPM formulation that features spherical kernel supports. The formulation is based on exact integration of interaction vectors constructed from top-hat kernels. The exact integration is obtained by an innovative surface partitioning algorithm as well as precise area computation of the sphere subsurfaces. Spherical-support FVPM improves the recently developed cubic-support version in two main aspects: spherical kernels have no directionality and result in smooth interactions between particles, leading to an improved method. We present three test cases that illustrate the improved accuracy and robustness brought by the spherical kernel. Although computations are 1.5 times slower on spherical support than cubic support, the cost is more than compensated by lower error with a higher convergence rate.

English for Medical Purposes for Saudi Medical and Health Professionals

This study explored the English language needs of 156 Saudi fellowship doctors and students of medical majors who are enrolled at medical and training programs in Australian hospitals and universities. Data were collected via a questionnaire adopted from a previous study. Participants’ responses showed the most frequently used language sub-skills were those sub-skills they considered highly important. Results emphasize the findings of previous studies that learners usually attach high importance to any skills that they use frequently to help them achieve the utmost aim of improving their language abilities. In addition, the study findings suggest current college English language courses for medical majors need to focus more on improving language-related aspects like fluency, understanding, accuracy, and structure. Such changes are necessary to prepare doctors and medical professionals for work in medical jobs that depend on heavy usage of the English language and also improving communicative competence aspects to ensure smooth cultural interaction with co-workers from all around the world. The study concludes by pointing that there is a critical need to restructure English for medical purposes programs in Saudi Arabia to make better course design, content, and materials responsive to target language learners’ own future goals. Keywords: Saudi; English language skills; Needs analysis (NA); English for specific purposes (ESP); English for medical purposes (EMP)

Research and Stability Analysis of Active-Disturbance-Rejection-Control-Based Microgrid Controllers

With the rapid development of microgrid technology, the microgrid projects are no longer limited to laboratory demonstration and pilot platform. It shows greater value in practical applications. Hence, the smooth interaction between microgrid and the main grid plays a critical role. In this paper, a control method based on active disturbance rejection control (ADRC) is proposed in order to realize the seamless transition between grid-connected and islanding operation modes and stable operation with variable loads. It is verified by simulation that the proposed ADRC-based method features better performance compared to conventional proportional-integral-differential (PID) control. Meanwhile, the stability of the third-order extended state observer (ESO) in second-order ADRC is validated by using Lyapunov stability criteria.

Age-Related Changes in Axonal and Mitochondrial Ultrastructure and Function in White Matter.

The impact of aging on CNS white matter (WM) is of general interest because the global effects of aging on myelinated nerve fibers are more complex and profound than those in cortical gray matter. It is important to distinguish between axonal changes created by normal aging and those caused by neurodegenerative diseases, including multiple sclerosis, stroke, glaucoma, Alzheimer's disease, and traumatic brain injury. Using three-dimensional electron microscopy, we show that in mouse optic nerve, which is a pure and fully myelinated WM tract, aging axons are larger, have thicker myelin, and are characterized by longer and thicker mitochondria, which are associated with altered levels of mitochondrial shaping proteins. These structural alterations in aging mitochondria correlate with lower ATP levels and increased generation of nitric oxide, protein nitration, and lipid peroxidation. Moreover, mitochondria-smooth endoplasmic reticulum interactions are compromised due to decreased associations and decreased levels of calnexin and calreticulin, suggesting a disruption in Ca(2+) homeostasis and defective unfolded protein responses in aging axons. Despite these age-related modifications, axon function is sustained in aging WM, which suggests that age-dependent changes do not lead to irreversible functional decline under normal conditions, as is observed in neurodegenerative diseases. Aging is a common risk factor for a number of neurodegenerative diseases, including stroke. Mitochondrial dysfunction and oxidative damage with age are hypothesized to increase risk for stroke. We compared axon-myelin-node-mitochondrion-smooth endoplasmic reticulum (SER) interactions in white matter obtained at 1 and 12 months. We show that aging axons have enlarged volume, thicker myelin, and elongated and thicker mitochondria. Furthermore, there are reduced SER connections to mitochondria that correlate with lower calnexin and calreticulin levels. Despite a prominent decrease in number, elongated aging mitochondria produce excessive stress markers with reduced ATP production. Because axons maintain function under these conditions, our study suggests that it is important to understand the process of normal brain aging to identify neurodegenerative changes.

Boosted structured additive regression for Escherichia coli fed-batch fermentation modeling.

The quality of biopharmaceuticals and patients' safety are of highest priority and there are tremendous efforts to replace empirical production process designs by knowledge-based approaches. Main challenge in this context is that real-time access to process variables related to product quality and quantity is severely limited. To date comprehensive on- and offline monitoring platforms are used to generate process data sets that allow for development of mechanistic and/or data driven models for real-time prediction of these important quantities. Ultimate goal is to implement model based feed-back control loops that facilitate online control of product quality. In this contribution, we explore structured additive regression (STAR) models in combination with boosting as a variable selection tool for modeling the cell dry mass, product concentration, and optical density on the basis of online available process variables and two-dimensional fluorescence spectroscopic data. STAR models are powerful extensions of linear models allowing for inclusion of smooth effects or interactions between predictors. Boosting constructs the final model in a stepwise manner and provides a variable importance measure via predictor selection frequencies. Our results show that the cell dry mass can be modeled with a relative error of about ±3%, the optical density with ±6%, the soluble protein with ±16%, and the insoluble product with an accuracy of ±12%. Biotechnol. Bioeng. 2017;114: 321-334. © 2016 Wiley Periodicals, Inc.

Physiological mechanisms for stabilizing the limb when acting against physical constraints.

Smooth physical interaction with our environment, such as when working with tools, requires adaptability to unpredictable perturbations that can be achieved through impedance control of multi-joint limbs. Modulation of arm stiffness can be achieved either increasing co-contraction of antagonistic muscles or by increasing the gain of spinal reflex loops. According to the "automatic gain scaling" principle, the spinal reflex gain, as measured via the H-reflex, scales with muscle activation. A previous experiment from our labs suggested, however, that reflex gains might instead be scaled to the force exerted by the limb, perhaps as a means to counteract destabilizing external forces. The goal of our experiment was to test whether force output, rather than the muscular activity per se, could be the critical factor determining reflex gain. Five subjects generated different levels of force at the wrist with or without assistance to dissociate applied force from agonist muscular activity. We recorded contact force, EMG and H-reflex response from a wrist flexor. We did not find a strict relationship between reflex gain and contact force but nor did we observe consistent modulation of reflex gain simply as a function of agonist muscle activity. These results are discussed in relation to the stability of the task constraints.

A High-Fidelity and Low-Interaction-Delay Screen Sharing System

The pervasive computing environment and wide network bandwidth provide users more opportunities to share screen content among multiple devices. In this article, we introduce a remote display system to enable screen sharing among multiple devices with high fidelity and responsive interaction. In the developed system, the frame-level screen content is compressed and transmitted to the client side for screen sharing, and the instant control inputs are simultaneously transmitted to the server side for interaction. Even if the screen responds immediately to the control messages and updates at a high frame rate on the server side, it is difficult to update the screen content with low delay and high frame rate in the client side due to non-negligible time consumption on the whole screen frame compression, transmission, and display buffer updating. To address this critical problem, we propose a layered structure for screen coding and rendering to deliver diverse screen content to the client side with an adaptive frame rate. More specifically, the interaction content with small region screen update is compressed by a blockwise screen codec and rendered at a high frame rate to achieve smooth interaction, while the natural video screen content is compressed by standard video codec and rendered at a regular frame rate for a smooth video display. Experimental results with real applications demonstrate that the proposed system can successfully reduce transmission bandwidth cost and interaction delay during screen sharing. Especially for user interaction in small regions, the proposed system can achieve a higher frame rate than most previous counterparts.

See You See Me: the Role of Eye Contact in Multimodal Human-Robot Interaction.

We focus on a fundamental looking behavior in human-robot interactions - gazing at each other's face. Eye contact and mutual gaze between two social partners are critical in smooth human-human interactions. Therefore, investigating at what moments and in what ways a robot should look at a human user's face as a response to the human's gaze behavior is an important topic. Toward this goal, we developed a gaze-contingent human-robot interaction system, which relied on momentary gaze behaviors from a human user to control an interacting robot in real time. Using this system, we conducted an experiment in which human participants interacted with the robot in a joint attention task. In the experiment, we systematically manipulated the robot's gaze toward the human partner's face in real time and then analyzed the human's gaze behavior as a response to the robot's gaze behavior. We found that more face looks from the robot led to more look-backs (to the robot's face) from human participants and consequently created more mutual gaze and eye contact between the two. Moreover, participants demonstrated more coordinated and synchronized multimodal behaviors between speech and gaze when more eye contact was successfully established and maintained.

The effect of oxytocin on attention to angry and happy faces in chronic depression.

BackgroundChronic depression is characterized by a high degree of early life trauma, psychosocial impairment, and deficits in social cognition. Undisturbed recognition and processing of facial emotions are basic prerequisites for smooth social interactions. Intranasal application of the neuropeptide oxytocin has been reported to enhance emotion recognition in neuropsychiatric disorders and healthy individuals. We therefore investigated whether oxytocin modulates attention to emotional faces in patients with chronic depression.MethodsIn this double-blind, randomized, controlled study, 43 patients received a single dose of oxytocin or placebo nasal spray and were tested while fulfilling a facial dot probe task. We assessed reaction times to neutral probes presented at the location of one of two faces depicting happy, angry, or neutral expressions as a prime.ResultsWhen comparing reaction times to the congruent (prime and probe at the same location) with incongruent presentation of facial emotions, neither the placebo nor oxytocin group showed an attentional preference for emotional facial expressions in terms of a threat bias. However, oxytocin treatment did reveal two specific effects: it generally reduced the allocation of attention towards angry facial expressions, and it increased sustained attention towards happy faces, specifically under conditions of heightened awareness, i.e. trials with longer primes.ConclusionsWe investigated a heterogeneous group of medicated male and female patients. We conclude that oxytocin does modulate basic factors of facial emotion processing in chronic depression. Our findings encourage further investigations assessing the therapeutic potential of oxytocin in chronic depression.Trial registrationEUDRA-CT 2010-020956-69. Date registered: 23 February 2011.

Endothelial and Smooth Muscle Cell Interactions in the Pathobiology of Pulmonary Hypertension.

In the pulmonary vasculature, the endothelial and smooth muscle cells are two key cell types that play a major role in the pathobiology of pulmonary vascular disease and pulmonary hypertension. The normal interactions between these two cell types are important for the homeostasis of the pulmonary circulation, and any aberrant interaction between them may lead to various disease states including pulmonary vascular remodeling and pulmonary hypertension. It is well recognized that the endothelial cell can regulate the function of the underlying smooth muscle cell by releasing various bioactive agents such as nitric oxide and endothelin-1. In addition to such paracrine regulation, other mechanisms exist by which there is cross-talk between these two cell types, including communication via the myoendothelial injunctions and information transfer via extracellular vesicles. Emerging evidence suggests that these nonparacrine mechanisms play an important role in the regulation of pulmonary vascular tone and the determination of cell phenotype and that they are critically involved in the pathobiology of pulmonary hypertension.

Do No Harm: the Extended Mind Model and the Problem of Delayed Damage

I argue in this essay that there can be harm due to philosophy that is not directly expressed in violent imagery. The harm is instead a concealed and delayed detrimental effect of an assumption of non-violence in a working model, defined as a picture of a field of enquiry and the methods required to approach it. Theses for the extended mind, as developed by Andy Clark and others, lead to a form of harm that follows from the models they work with. These engineering, tool and function-based models seek smooth interactions and transparency. Following points made by Kim Sterelny in the philosophy of biology, I argue that claims for smoothness and transparency conceal underlying conflict in the situations they seek to describe and explain. This concealment leads to harm, defined as a diminishing of our capacities to flourish in a given environment.

The Effect of Expression Media Activities on Cognitive Function, Depression and Social Interaction of the Elders with Dementia Residing in Facilities

본 연구는 시설 치매 노인에게 표현매체 활동을 적용하여 인지기능 및 우울, 사회적 상호작용에 미치는 영향을 알아봄으로써, 치료적 활동으로서의 가치와 효과성을 검증하고자 하였다. 연구기간은 2015년 9월 15일부터 10월 22일까지 전남 H군 노인요양시설에 등록된 치매 노인 중 연구의 목적을 이해하고 자발적으로 참여에 동의한 20명을 대상으로 하였다. 연구결과는 표현매체 활동에 따른 인지기능과 사회적 상호작용은 증가하였고, 우울은 감소하였다. 또한 인지기능이 높을수록 사회적 상호 작용이 증가하는 양적 상관관계를 나타내었다. 따라서 시설 치매 노인의 현존 능력을 고려한 표현매체 활동은 인지적 기능뿐만 아니라 구성원과의 언어 및 비언어 소통기술을 향상시키고, 원활한 사회적 상호작용으로 우울을 감소시킨다. 이에 시설 치매 노인에게 목적 있고 의미 있는 작업을 통해 잔존능력을 강화 및 촉진시킬 수 있는 표현매체 활동의 치료적 사용을 제안하는 바이다.

Vision-Based Pose Estimation for Robot-Mediated Hand Telerehabilitation.

Vision-based Pose Estimation (VPE) represents a non-invasive solution to allow a smooth and natural interaction between a human user and a robotic system, without requiring complex calibration procedures. Moreover, VPE interfaces are gaining momentum as they are highly intuitive, such that they can be used from untrained personnel (e.g., a generic caregiver) even in delicate tasks as rehabilitation exercises. In this paper, we present a novel master–slave setup for hand telerehabilitation with an intuitive and simple interface for remote control of a wearable hand exoskeleton, named HX. While performing rehabilitative exercises, the master unit evaluates the 3D position of a human operator’s hand joints in real-time using only a RGB-D camera, and commands remotely the slave exoskeleton. Within the slave unit, the exoskeleton replicates hand movements and an external grip sensor records interaction forces, that are fed back to the operator-therapist, allowing a direct real-time assessment of the rehabilitative task. Experimental data collected with an operator and six volunteers are provided to show the feasibility of the proposed system and its performances. The results demonstrate that, leveraging on our system, the operator was able to directly control volunteers’ hands movements.

SAMURAI: A batch and streaming context architecture for large-scale intelligent applications and environments

Over the past decade intelligent environments have grown in sophistication. Many recent paradigm shifts − such as the Internet of Things (IoT), Ambient Assisted Living (AAL), e-health and telemedicine − envision large distributed networks of intelligent devices, applications and services that are sensitive to the presence of people and responsive to their needs. Cutting edge technologies will autonomously and collectively operate on a growing volume of information arriving at ever increasing velocities to transparently and non-intrusively support users during their activities. Especially the escalating variety of information that applications have to deal with is a non-trivial concern. Making sense out of heterogeneous and pervasive streams of sensor events to anticipate and address the needs of users is a ubiquitous challenge that many interactive context-aware applications in intelligent environments frequently face. Furthermore, software solutions that continuously interpret the tasks and contexts of a variety of individuals with different needs are often faced with scalability concerns. We present SAMURAI, a batch and streaming context architecture that integrates and exposes well-known components for complex event processing, machine learning, and knowledge representation. SAMURAI builds upon key concepts of the Lambda architecture and big data enabling technologies to achieve horizontal scalability and responsive interaction with its users. Two application cases validate the feasibility and performance of our context architecture, demonstrating near-linear scalability, flexible elasticity and smooth interaction capabilities.

Advances in the Form-finding of Structural Membranes

The present contribution presents the application of the newly developed isogeometric B-Rep analysis to the form-finding and structural analysis of structural membranes. Therefore, the necessary basis of the model description is briefly outlined. The result of this approach is the possibility to perform mechanically accurate form-finding (and follow-up analyses) directly within a CAD-environment on a full NURBS-based CAD-model.Selected benchmark examples show the accuracy and robustness of the developed method, assessed against analytical solutions if applicable. Two selected application examples that are entirely treated within the augmented CAD-environment highlight the potential of the method: Using one common model not only facilitates geometrical analysis and preparation of the model, but also allows for smooth and close interaction between design and analysis, which is of crucial importance in membrane design.

Sensor Network Infrastructure for AMI in Smart Grid

Utility companies incur financial loss due to transmission losses as well as non technical losses like power theft and billing irregularities. Smart meters with the required functionalities along with an intelligent grid form an Automated Meter Reading (AMR) infrastructure which can improve the distribution efficiency. AMR infrastructure can be expanded by allowing for bi-directional communication between the grid components to form an Advanced Metering Infrastructure (AMI). This helps for the smooth interaction between grid components to load and off-load the distributed energy sources while supporting an efficient Demand Side Management of power. Communication technologies play a vital role in the implementation of smart grid and Wireless Sensor Networks are gaining attraction in this field. Routing protocols with high reliability, low latency and that can co-exist with the established protocols are the need of the hour. Routing Protocol for Low Power Lossy Networks (RPL) fit into this space well. An attempt to build an automated infrastructure using RPL for collecting the metering information, which at a later stage can be easily upgraded to an AMI setup by simply adding the supporting end devices for a much more intelligent smart grid, is carried out in this paper

Multimap formation in visual cortex.

An extrastriate visual area such as V2 or V4 contains neurons selective for a multitude of complex shapes, all sharing a common topographic organization. Simultaneously developing multiple interdigitated maps--hereafter a "multimap"--is challenging in that neurons must compete to generate a diversity of response types locally, while cooperating with their dispersed same-type neighbors to achieve uniform visual field coverage for their response type at all orientations, scales, etc. Previously proposed map development schemes have relied on smooth spatial interaction functions to establish both topography and columnar organization, but by locally homogenizing cells' response properties, local smoothing mechanisms effectively rule out multimap formation. We found in computer simulations that the key requirements for multimap development are that neurons are enabled for plasticity only within highly active regions of cortex designated "learning eligibility regions" (LERs), but within an LER, each cell's learning rate is determined only by its activity level with no dependence on location. We show that a hybrid developmental rule that combines spatial and activity-dependent learning criteria in this way successfully produces multimaps when the input stream contains multiple distinct feature types, or in the degenerate case of a single feature type, produces a V1-like map with "salt-and-pepper" structure. Our results support the hypothesis that cortical maps containing a fine mixture of different response types, whether in monkey extrastriate cortex, mouse V1 or elsewhere in the cortex, rather than signaling a breakdown of map formation mechanisms at the fine scale, are a product of a generic cortical developmental scheme designed to map cells with a diversity of response properties across a shared topographic space.