Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimization of behavioral dynamic treatment regimens based on the sequential, multiple assignment, randomized trial (SMART)

Background and purpose A behavioral intervention is a program aimed at modifying behavior for the purpose of treating or preventing disease, promoting health, and/or enhancing well-being. Many behavioral interventions are dynamic treatment regimens, that is, sequential, individualized multicomponent interventions in which the intensity and/or type of treatment is varied in response to the needs and progress of the individual participant. The multiphase optimization strategy (MOST) is a comprehensive framework for development, optimization, and evaluation of behavioral interventions, including dynamic treatment regimens. The objective of optimization is to make dynamic treatment regimens more effective, efficient, scalable, and sustainable. An important tool for optimization of dynamic treatment regimens is the sequential, multiple assignment, randomized trial (SMART). The purpose of this article is to discuss how to develop optimized dynamic treatment regimens within the MOST framework. Methods and results The article discusses the preparation, optimization, and evaluation phases of MOST. It is shown how MOST can be used to develop a dynamic treatment regimen to meet a prespecified optimization criterion. The SMART is an efficient experimental design for gathering the information needed to optimize a dynamic treatment regimen within MOST. One signature feature of the SMART is that randomization takes place at more than one point in time. Conclusion MOST and SMART can be used to develop optimized dynamic treatment regimens that will have a greater public health impact.
Upgrading cost modelling of capacity-exhausted static WDM networks

This paper proposes a methodology to evaluate the total cost (CapEx and OpEx) of a migration process from a capacity-exhausted static WDM network to different capacity-upgraded alternatives. The methodology has been applied for evaluating and comparing two migration alternatives: maintaining static operation at increased bit rate and changing to dynamic operation with increased bit rate. Results show that the methodology not only allows selecting the lowest cost alternative, but also identifying key aspects driving the cost of the migration process. We expect this methodology can be used as a planning tool by network operators to select the most suitable migration alternative, considering different types of network operation, topologies, traffic demands and network architectures.
Conceptual inferred TAM by gender in cyberlearning

The pace of adoption of cyberlearning is influenced by gender factors that need to be confronted. The technology acceptance model (TAM) designed by Davis in 1989 can be useful to measure the pace of receptivity to use of online resources. Writers try to show that Taiwanese women in highly technical programs are more resistant to computing and Web online distance courses than men. Educational programs need to be designed to encourage women to lead in diffusion of cyberlearning. The writers desire to use the TAM approach in a study of university students in Taiwan and try to find that gender, computing skills, and prior experiences with computing were the most significant factors to predict acceptance or resistance to change. Finally, the writers would like to create an overall conceptual model, which inferred from original TAM constructs relationships for showing that cyberspace advocates have yet to promote a concept.
Cognitive Behavioural Approaches for Post-Traumatic Stress Disorders

The sequelae of sexual assault affect the psychological, emotional, social, interpersonal, and financial domains in the short and long term. Victim’s sexual assault can experience considerable emotional and psychological distress, such as depression. PTSD is a psychiatric label for a collection of psychological symptoms following a traumatic event. In addition, mental contamination is an internal, emotional feeling of dirtiness that may be evoked by unwanted thoughts and images, as well as by memories of negative events, such as sexual assaults. CBT-based therapy appears to be beneficial in reducing or treating victims of sexual assault suffering from PTSD and mental contamination. The paper outlines the cognitive theory of PTSD and mental contamination in order to demonstrate how this problem can be treated. Sexual assault constitutes both physical and mental violence, and it is not easily recovered from. Victims/survivors of sexual assault may experience severe anxiety, stress, or fear. This paper demonstrates some mental health problems that sexual assault victims may experience, with a specific focus on Post-Traumatic Stress Disorder (PTSD) and mental contamination. Clinical experience and empirical studies have shown that many victims of sexual assault suffer from the distressing feeling of “contamination” for years or decades after experiencing sexual violence. This phenomenon is called mental contamination, and was first identified by Rachman (1994). Mental contamination is defined as the experience of contamination-related feelings of dirtiness in the absence of direct physical contact with a contaminant, and it is prominent among victims of sexual assault and patients with PTSD. Finally, the paper outlines the cognitive theory of mental contamination in order to demonstrate how this problem can be treated. In addition, the paper presents clinical guidelines for mental contamination based on cognitive behavioral therapy.
On PHY and MAC Performance of 3G-LTE in a Multi-Hop Cellular Environment

Next generation cellular radio systems will exceed the limitations of UMTS. The convergence of data and voice traffic will be supported by a flexible OFDM-based PHY layer and an OFDMA-capable MAC layer. The long term evolution (LTE) successor of the 3G systems incorporates this. But problems concerning coverage and capacity at the cell border still remain for the classical cellular layout. Relaying or Multihop operation is an option to massively improve the coverage as well as the capacity issue at low cost, without the need of a cable or fibre access. For the performance analysis of such cellular systems models for ISO-OSI layers 1+2 (PHY+MAC) are needed. In this paper an analytic modelling framework and results are presented for the cellular LTE performance in two multihop scenarios.
Real-time stereo vision: Optimizing Semi-Global Matching

Semi-Global Matching (SGM) is arguably one of the most popular algorithms for real-time stereo vision. It is already employed in mass production vehicles today. Thinking of applications in intelligent vehicles (and fully autonomous vehicles in the long term), we aim at further improving SGM regarding its accuracy. In this study, we propose a straight-forward extension of the algorithm's parametrization. We consider individual penalties for different path orientations, weighted integration of paths, and penalties depending on intensity gradients. In order to tune all parameters, we applied evolutionary optimization. For a more efficient offline optimization and evaluation, we implemented SGM on graphics hardware. We describe the implementation using CUDA in detail. For our experiments, we consider two publicly available datasets: the popular Middlebury benchmark as well as a synthetic sequence from the . enpeda. project. The proposed extensions significantly improve the performance of SGM. The number of incorrect disparities was reduced by up to 27.5 % compared to the original approach, while the runtime was not increased.
The contributions of value-based decision-making and attentional bias to alcohol-seeking following devaluation

Aims To investigate the mediating role of attentional bias for alcohol cues on alcohol-seeking following devaluation of alcohol. Design Between subject. Setting Eye-tracking laboratory at the University of Liverpool. Participants Student social drinkers (n = 64). Measurements An operant choice task in which participants chose between simultaneously presented alcohol and non-alcohol drink rewards, while attentional bias for alcohol and non-alcohol drink cues was inferred from eye movements. Participants then consumed 30 mL of an alcoholic beverage, which was either presented alone (no devaluation: n = 32) or had been adulterated to taste unpleasant (devaluation: n = 32). Choice and attentional bias for the alcohol and non-alcohol drink pictures were then measured again. Findings Alcohol devaluation reduced behavioural choice for alcohol (F = 32.64, P < 0.001) and attentional bias for the alcohol pictures indexed by dwell time (F = 22.68, P < 0.001), initial fixation (F = 7.08, P = 0.01) and final fixation (F = 22.44, P < 0.001). Mediation analysis revealed that attentional bias partially mediated the effect of devaluation on alcohol choice; however, the proportion of the variance accounted for by attentional bias is low to moderate (∼30%). Conclusions Among student social drinkers, attentional bias is only a partial mediator of alcohol choice following devaluation of alcohol. Value-based decision-making may be a more important determinant of drinking behaviour among student social drinkers than attentional bias.
Position Statement: Supporting Coordinated Adaptation in Networked Systems

While adaptation is widely recognized as valuable, adaptations in most existing systems are limited to changing execution parameters in a single software module or on a single host. Our position is that the true potential of adaptation can only be realized if support is provided for more general solutions, including adaptations that span multiple hosts and multiple system components, and algorithmic adaptations that involve changing the underlying algorithms used by the system at runtime. Such a general solution must, however, address the difficult issues related to these types of adaptations. Adaptation by multiple related components, for example, must be coordinated so that these adaptations work together to implement consistent adaptation policies. Likewise, large-scale algorithmic adaptations need to be coordinated using graceful adaptation strategies in which as much normal processing as possible continues during the changeover. Here, we summarize our approach to addressing these problems in Cactus, a system for constructing highly-configurable distributed services and protocols [2]. When multiple related system components can adapt to changes in the system state, the adaptations performed by these components must be coordinated to achieve a consistent adaptation policy. To achieve this, we have implemented an adaptation controller architecture that is responsible for making adaptation decisions for related adaptive components. Adaptation policies are specified on a componentby-component basis using sets of fuzzy logic rules, and then composed along with rules to coordinate the actions of different components to form a single controller. The challenge, of course, is designing a set of fuzzy rules that reflect the best adaptation strategies for a given situation. Even when coordinated adaptation decisions are made, large-scale algorithmic adaptations still present a difficult challenge. Without special provisions, for example, an adaptive system may be unable to process normal application traffic while it is changing between different algorithms. To alleviate this problem, we have designed and implemented a graceful adaptation protocol that coordinates changes across
Play streets: women, children and the problem of urban traffic, 1930–1970

ABSTRACT This article explores women’s participation in campaigns for urban play streets in England c.1930–1970. Concentrating on activities in ‘traditional’ terraced streets, it argues that working-class street sociability was strongly connected to children’s play and that rising levels of traffic were beginning to threaten this before the Second World War, feeding growing anxieties over the high rate of road accidents to children. One response to this from the 1930s was a series of local experiments aimed at separating traffic from children (a radical alternative to the more usual response of keeping children away from traffic) through the creation of ‘play streets’, closed to traffic for much of the day. The idea was taken up by national government and became popular in post-war decades, often due to the efforts of local women to defend the public life of their communities. The growing controversy over the introduction and maintenance of play streets from the 1960s shows women struggling to maintain traditional street sociability against the gathering power of business interests and rising car ownership in the period.
A Genetic Algorithm for Creating a Set of Color Spaces for Ear Authentication

An ensemble of 2D ear matchers is built by training each matcher using a set of Gabor filters and color spaces selected by a genetic algorithm (GA). First, using gray level images, we select the best Gabor filters applying Sequential Forward Floating Selection. Second, using the RGB images, several color spaces are obtained using a GA. Finally, an ensemble of 1-nearest neighbor matchers use the color spaces and filters for classification. The performance of the proposed approach is measured using the Notre-Dame EAR dataset. To create the color spaces, the dataset is divided into training and testing sets using ear samples from different individuals. System parameters are selected using samples of individuals that belong to the training set. The method is then tested on the testing set. In this way, we consider our protocol a reliable blind testing protocol. Our system obtains rank-1 of ~81% and
Wetbrush

We present a real-time painting system that simulates the interactions among brush, paint, and canvas at the bristle level. The key challenge is how to model and simulate sub-pixel paint details, given the limited computational resource in each time step. To achieve this goal, we propose to define paint liquid in a hybrid fashion: the liquid close to the brush is modeled by particles, and the liquid away from the brush is modeled by a density field. Based on this representation, we develop a variety of techniques to ensure the performance and robustness of our simulator under large time steps, including brush and particle simulations in non-inertial frames, a fixed-point method for accelerating Jacobi iterations, and a new Eulerian-Lagrangian approach for simulating detailed liquid effects. The resulting system can realistically simulate not only the motions of brush bristles and paint liquid, but also the liquid transfer processes among different representations. We implement the whole system on GPU by CUDA. Our experiment shows that artists can use the system to draw realistic and vivid digital paintings, by applying the painting techniques that they are familiar with but not offered by many existing systems.
Tai Chi: An Alternative Exercise Form for Seniors

Tai Chi, an ancieni form of Chinese fitness exercise, affords its participants a variety of physical and psychological benefits. Research has suggested that individuals engaging in Tai Chi exercises improve cardiovascular fitness and motor control while reducing stress, anxiety and depression. Tai Chi is particularly suitable for seniors, who are often at risk for a variety of problems associated with aging (e.g. arthritis, neurological dysfunction, and general decline of balance, coordination, and locomotor function). Because of its self-paced. nonstressful, and noncompetitive nature, and its ability to afford economy of lime, space, and equipment, Tai Chi presents an effective, functional alternative exercise form for the senior adult population. This article presents the background of Tai Chi practice and introduces several key elements and suggestions for teaching Tai Chi to senior participants. Finally, some selected resources for Tai Chi practice are listed.
Sensor integration in task-level programming and industrial robotic task execution control

Presents an approach to improved performance and flexibility in industrial robotics by means of sensor integration and feedback control in task‐level programming and task execution. Also presents feasibility studies in support of the ideas. Discusses some solutions to the problem using six degrees of freedom force control together with the ABB S4CPlus system as an illustrative example. Consider various problems in the design of an open sensor interface for industrial robotics and discusses possible solutions. Finally, presents experimental results from industrial force controlled grinding.
Virtual Reality Classrooms Strategies for Creating a Social Presence

— Delivering course material via a virtual environment is beneficial to today’s students because it offers the interactivity, real-time interaction and social presence that students of all ages have come to accept in our gaming rich community. It is essential that the Net Generation also known as Generation Why, have exposure to learning communities that encompass interactivity to form social and educational connections. As student and professor become interconnected through collaboration and interaction in a virtual learning space, relationships develop and students begin to take on an individual identity. With this in mind the research project was developed to investigate the use of virtual environments on student satisfaction and the effectiveness of course delivery. Furthermore, the project was designed to integrate both interactive (real-time) classes conducted in the Virtual Reality (VR) environment while also creating archived VR sessions for student use in retaining and reviewing course content.
A novel packet-pair-based inferring bandwidth congestion control mechanism for layered multicast

Layered transmission of data is the generally recommended solution to the problem of varying bandwidth constraints and heterogeneity in multicast applications. In this paper, we describe a new multicast congestion control mechanism for layered multicast (PLMCC), which is based on packet-pair inferring bandwidth. In PLMCC, intermediate nodes and receivers infer local available bandwidth accurately and quickly using hop-by-hop downward packet-pair. Compared with PLM introduced by Legout et al., PLMCC eliminates the problem associated with large Internet group management protocol (IGMP) leave latencies, it has faster convergence speed. Moreover, our simulation results show that PLMCC is also TCP-friendly and scalable.
Semi-supervised Coupled Dictionary Learning for Cross-modal Retrieval in Internet Images and Texts

Nowadays massive amount of images and texts has been emerging on the Internet, arousing the demand of effective cross-modal retrieval such as text-to-image search and image-to-text search. To eliminate the heterogeneity between the modalities of images and texts, the existing subspace learning methods try to learn a common latent subspace under which cross-modal matching can be performed. However, these methods usually require fully paired samples (images with corresponding texts) and also ignore the class label information along with the paired samples. This may inhibit these methods from learning an effective subspace since the correlations between two modalities are implicitly incorporated. Indeed, the class label information can reduce the semantic gap between different modalities and explicitly guide the subspace learning procedure. In addition, the large quantities of unpaired samples (images or texts) may provide useful side information to enrich the representations from learned subspace. Thus, in this paper we propose a novel model for cross-modal retrieval problem. It consists of 1) a semi-supervised coupled dictionary learning step to generate homogeneously sparse representations for different modalities based on both paired and unpaired samples; 2) a coupled feature mapping step to project the sparse representations of different modalities into a common subspace defined by class label information to perform cross-modal matching. Experiments on a large scale web image dataset MIRFlickr-1M with both fully paired and unpaired settings show the effectiveness of the proposed model on the cross-modal retrieval task.
Optimum repeater insertion based on a CMOS delay model for on-chip RLC interconnect

A closed form expression for the propagation delay of a CMOS gate driving a distributed RLC line is introduced that is within 7% of SPICE simulations for a wide range of RLC loads. This expression is based on the alpha power law for deep submicrometer technologies. It is shown that the error in the propagation delay if inductance is neglected and the interconnect is treated as a distributed RC line can be over 30% for present on-chip interconnect. It is also shown that the traditional quadratic dependence of the propagation delay on the length of the interconnect for RC lines approaches a linear dependence as inductance effects increase, which is expected to have a profound effect on traditional design methodologies. The closed form CMOS delay model is applied to the problem of repeater insertion in RLC interconnect. Closed form solutions are presented for inserting repeaters into RLC lines that are highly accurate with respect to numerical solutions. It is shown that large errors in the repeater design process are encountered if inductance is neglected. Errors up to 30% can occur if repeaters are inserted without considering the effects of inductance. The error between the RC and RLC models increases as the gate parasitic impedances decrease. Thus, the importance of inductance in high performance VLSI design methodologies will increase as technologies scale.
An efficient interest point detection technique for real-time applications

Feature selection is a key step for image registration process. The success of feature selection has a fundamental effect on image matching. Corner points are considered as interest points as they are formed from two or more edges and edges usually define the boundary between two different objects or parts of the same objects. Corners determine the contours characteristics of the target image and the number of corners is far smaller than the number of image pixels, thus corner can be a good feature for image registration. Detection of corners for image registration is difficult task for an airborne real-time platform. Airborne platform suffers with many constraints like processing power, qualified hardware, real time constraints etc. In this paper, we propose an efficient interest point detection technique to meet airborne real-time constraints. It requires sorting in local neighborhood in spatial domain. Performance is evaluated quantitatively using SNR criteria in neighborhood and random location. The results are further validated against image translation and rotation.
Localization in Vehicular Ad Hoc Networks

Communications between vehicles constitute a Vehicular Ad hoc Network (VANET). Contrary to MANET in VANET nodes which are vehicles can move with high speed and generally must communicate quickly and reliably. When an accident occurs in a road or highway, alarm messages must be disseminated, instead of ad-hoc routed, to inform all other vehicles. To position a broken vehicle (or vehicle in danger) and locate the vehicles in its vicinity is very important for the safety of the road users. However, vehicles are not necessarily equipped with GPS and even they cannot obtain availability of line of sight access to satellites, particularly when they enter tunnels. In this paper, we propose an improvement to ODAM (optimized dissemination of alarm messages) protocol in order to support localization of GPS-unequipped vehicles. So, the number of vehicles discovering their localisation will be increased. This prevents pile-up of cars when fog, accidents or any other obstacle contributes to the driver safety. Analyses show that the optimal performances of ODAM can be reached even when the rate of GPS-unequipped vehicles is 40%