Miracle-dz/UniFAR-FTUs huggingface dataset:
MSR-TR-2005-154 , November 2005 LazyCut : Content-Aware Template Based Media Authoring

The rapid adoption of digital cameras and camcorder s leads to an explosive growth of personal photos and home video in digital form. There is a huge demand for new tools and syst ems that enables average users to more efficiently and more effectively process, manage, author and share these digital med ia contents, in particular, a powerful video authoring tool that ca n dramatically reduce the users’ efforts in editing home video. T hough there are many commercial video authoring tools available tod ay, video authoring remains as a tedious and extremely time c onsuming task that often requires trained professional skills. To tackle this problem, this paper presents a novel end-to-end sys tem that enables fast, flexible and personalized video autho ring and sharing. The novel system, called LazyCut, is based on both content analysis techniques and the proposed conten t-aware twolayer authoring templates: content description temp late and content representation template. Moreover, it is d e igned as an open and extensible framework that can support dyna mic update of core components such as content analysis algorit hms, editing methods, and the two-layer authoring templates. Fu rthermore, the two layers of authoring templates separate the vide o authoring from video representation. Once authored with LazyC ut, the video contents can be easily and flexibly represented in other forms according to users’ preference. LazyCut provides a semiautomatic video authoring and sharing system that s ignificantly reduces users’ efforts in video editing while prese ving sufficient flexibility and personalization.
On becoming a skilled migrant: towards habitus transformation through higher education

ABSTRACT Research on the labour market experiences of highly skilled migrants has revealed the crippling employability challenges they face in the UK workplace resulting from the devaluation of their homeland qualifications and experiences. Studies on highly skilled migrants from Zimbabwe have revealed how migrants have to resort to semi-skilled and unskilled work for survival. Little is known, however, about the education and labour market experiences of migrants who come into the UK without degrees and subsequently acquire a UK degree. Drawing on Bourdieu’s theory of cultural capital and habitus, this article explores the higher education and labour market experiences of this group, as revealed by in-depth interviews with 20 participants. Findings reveal that these participants’ habitus is a complex dynamic interaction of diverse (pre)dispositions and strategies which result in them reporting better labour market success than Zimbabwe-degreed migrants. Arguably, their experiences suggest the emergence of a new UK-based habitus for Zimbabwean migrants.
Market Power Mitigation Clearing Mechanism Based on Constrained Bidding Capacities

Market power has been a problematic issue for fair and transparent trades in various electricity markets. To deal with the problems of existing market power mitigation methods, such as complicated judgment criteria, excessive supervision probability, impersonal cost data accounting, and the requirements on perfect information circumstances, a novel spot market power mitigation clearing mechanism (MPMCM) is proposed, which manages to limit potential market power execution while avoiding overregulation and maintaining a real market supply–demand situation. The MPMCM consists of three processes, namely, market power evaluation, bidding capacity division, and bidding capacity constraint. The MPMCM is transformed into a set of bidding constraints and properly integrated in the common market clearing procedure. A bilevel mathematical problem with equilibrium constraints market equilibrium model is proposed to formulate the MPMCM for market simulation, and the mixed integer linear problem reformulation of the bilevel model is derived. Finally, an illustrative example is proposed to observe the strategic behaviors under various situations, thereby proving the validity and effectiveness of the MPMCM. A large-scale numerical example based on a modified IEEE 200-node system is proposed to prove the adaptivity of the MPMCM.
Graduate registered nurses’ reflections on implementing safety and quality improvement projects

ABSTRACT Registered nurses are required to be involved in quality improvement activities as part of delivering safe, high-quality care for patients. Graduate registered nurses often have limited knowledge and practical application of quality improvement processes and their link to clinical care. Graduate nurse programs provide ideal opportunities to embed knowledge and practice of quality standards and quality improvement processes and for graduates to utilise reflection as an important tool in learning and practice review. An innovative approach was implemented at an Australian private hospital where registered nurses in a graduate nurse program worked in groups to conduct a quality improvement project relating to one of the Australian National Safety and Quality Health Service Standards. As part of the project, reflection was used as a strategy for graduates to understand and learn from their experience. Using a descriptive qualitative approach, the reflections of 20 graduate registered nurses who conducted a quality improvement project as part of a graduate nurse program were analysed. The results showed that reflection enabled the graduate nurses to better understand their experience of implementing a quality and safety project with a team of peers, including reflecting on their own learning and also reflecting on quality improvement projects and how they can contribute to improved practices at the hospital.
A Survey on Routing Protocol for Wireless Sensor Network

This paper gives the survey on routing protocol for wireless sensor networks. In recent years, many approaches and techniques have been proposed for consuming the energy efficiency of the Wireless Sensor Network. In order to gather information more efficiently, Wireless Sensor Network is partitioned into clusters. Clustering is an important mechanism in large Wireless Sensor Network for obtaining scalability, reducing energy consumption and activity for better network performance. Those methods are proposed already for Wireless Sensor Network is not without problem. Routing protocols for wireless sensor networks are responsible for maintaining the routes in the network and have to ensure reliable multi-hop communication. In this paper, We gives a survey on routing protocols for Wireless Sensor Networks and compare their relative strengths and limitations.
The influence of personal and environmental factors on typically developing children’s activity participation

ABSTRACT Participation is a multidimensional concept that has evolved from the International Classification of Functioning, Disability and Health as one’s engagement in life. This study investigated the impact that personal and environmental factors have on typically developing children’s activity participation (n = 18). Children and parents/caregivers completed self-report questionnaires. Children completed the Children’s Assessment of Participation and Enjoyment & Preferences for Activities of Children (CAPE/PAC) and the Children’s Leisure Assessment Scale (CLASS) while parents completed the Children Participation Questionnaire (school-aged) (CPQS), Performance Skill Questionnaire (school-aged) (PSQS), and Environmental Restriction Questionnaire (school-aged) (ERQS). Pearson correlations were performed to determine whether there were correlations between the independent variables (PSQS and ERQS) and dependent variables (CAPE, PAC, CLASS, CPQS), total scores and subscale scores. The Pearson r correlation analyses were also bootstrapped. Linear regressions analyses were used to determine whether the positive correlations identified between the variables were predictive. Personal factors (which included the child’s motor, process, and communication skills) were predictive of five out of the six dimensions of participation, diversity (40.8% variance accounted for in the dependent variables), intensity (32% variance), where (54.3% variance), with whom (30% variance), and enjoyment (54% variance). Environmental factors that include the child’s community, educational, and home environment were predictive of all six dimensions of participation. Diversity (32.4% variance accounted for in the dependent variables), intensity (32.8% variance), where (22.4% variance), with whom (25.3% variance), enjoyment (44.9% variance), and preference (49.1% variance). The results indicated that motor, process, and communication skills were significantly predictive of a child’s diversity and intensity of participation, with whom and where they completed activities, their enjoyment and parental satisfaction. Community and education environments were also found to be predictive of these elements of participation, while the home was predictive of a child’s activity preference.
Non-decimation FIR filter for digital RF sampling receiver with wideband operation capability

In order to realize a discrete-time filter for wideband signal processing, a new finite impulse response filter (FIR) has been developed. The filter maintains the moving average effect, but the decimation function is removed in order to realize a cascadable filter. By cascading the proposed FIR filter with a conventional FIR filter, about −60 dB attenuation across 50 MHz signal bandwidth is possible, and by the cascade more stages, the bandwidth can be even wider. This bandwidth is wide enough to process the signals of the next generation systems, opening up the way of utilizing the sampling receiver.
PKA Compartmentalization via AKAP220 and AKAP12 Contributes to Endothelial Barrier Regulation

cAMP-mediated PKA signaling is the main known pathway involved in maintenance of the endothelial barrier. Tight regulation of PKA function can be achieved by discrete compartmentalization of the enzyme via physical interaction with A-kinase anchoring proteins (AKAPs). Here, we investigated the role of AKAPs 220 and 12 in endothelial barrier regulation. Analysis of human and mouse microvascular endothelial cells as well as isolated rat mesenteric microvessels was performed using TAT-Ahx-AKAPis peptide, designed to competitively inhibit PKA-AKAP interaction. In vivo microvessel hydraulic conductivity and in vitro transendothelial electrical resistance measurements showed that this peptide destabilized endothelial barrier properties, and dampened the cAMP-mediated endothelial barrier stabilization induced by forskolin and rolipram. Immunofluorescence analysis revealed that TAT-Ahx-AKAPis led to both adherens junctions and actin cytoskeleton reorganization. Those effects were paralleled by redistribution of PKA and Rac1 from endothelial junctions and by Rac1 inactivation. Similarly, membrane localization of AKAP220 was also reduced. In addition, depletion of either AKAP12 or AKAP220 significantly impaired endothelial barrier function and AKAP12 was also shown to interfere with cAMP-mediated barrier enhancement. Furthermore, immunoprecipitation analysis demonstrated that AKAP220 interacts not only with PKA but also with VE-cadherin and ß-catenin. Taken together, these results indicate that AKAP-mediated PKA subcellular compartmentalization is involved in endothelial barrier regulation. More specifically, AKAP220 and AKAP12 contribute to endothelial barrier function and AKAP12 is required for cAMP-mediated barrier stabilization.
Automatic Generation of Fast and Certified Code for Polynomial Evaluation

Designing an efficient floating-point implementation of a function based on polynomial evaluation requires being able to find an accurate enough evaluation code, exploiting at most the target architecture features. This article introduces CGPE, a tool dealing with the generation of fast and certified codes for the evaluation of bivariate polynomials. First we discuss the issue underlying the evaluation scheme combinatorics before giving an overview of the CGPE tool. The approach we propose consists in two steps: the generation of evaluation schemes by using some heuristics so as to quickly find some of low latency, and the selection that mainly consists in automatically checking their scheduling on the given target and validating their accuracy. Then, we present on-going development and ideas for possible improvements of the whole process. Finally, we illustrate the use of CGPE on some examples, and show how it allows us to generate fast and certified codes in a few seconds and thus to reduce the development time of libms like FLIP.
The effect of regularization on variance error

This note addresses the problem of quantifying the effect of noise induced error(so called "variance error") in system estimates found via a regularised cost criterion. It builds on recent work by the authors in which expressions for nonregularised criterions are derived which are exact for finite model order. Those new expressions were established to be very different to previous quantifications that are widely used but based on asymptotic in model order arguments. A key purpose of this note is to expose a rapprochement between these new finite model order, and the pre-existing asymptotic model order quantifications. In so doing, a further new result is established. Namely, that variance error in the frequency domain is dependent on the choice of the point about which regularization is affected.
Psychological Capital and Self‐Reported Employee Creativity: The Moderating Role of Supervisor Support and Job Characteristics

Although the positive effect of psychological capital (PsyCap) on employee performance is well documented, the conditions under which PsyCap exerts the most influence on creativity warrant further research. Complementing and extending prior studies, we theorize and examine how two critical contextual factors (supervisor support for creativity [SSC] and job characteristics) effectively activate PsyCap associated with self-reported employee creativity. Drawing on an interactional perspective, we use trait activation theory to examine the moderating effects of SSC and job characteristics on the relationship between PsyCap and self-reported employee creativity. Through rigorous hypotheses testing (N = 356 individuals from multiple industries in Chinese firms), our results demonstrate that both SSC and job characteristics positively moderate the PsyCap–creativity relationship. Additional analyses reveal that PsyCap is most effective at enhancing creativity when both SSC and job characteristics are high. Implications of these findings for theory, future research and practice are discussed.
Range and Doppler Cell Migration in Wideband Automotive Radar

The automobile industry has a strategic intent to develop vehicles capable of higher and higher levels of autonomy. Radar is a key sensing component, being the only viable option for all weather, 24-hour-a-day use. Autonomy will require the radar to provide much greater levels of detailed information than is available from today's cruise control and collision avoidance systems. In particular, much wider bandwidths are needed for high range resolution. Furthermore, high Doppler resolution, requiring long integration times, is needed for moving object classification. These two opposing requirements create significant design and signal processing challenges. This paper examines the way in which choices in the key design parameters effect performance, showing that as both range and Doppler resolutions are enhanced, the potential for received energy to migrate across resolution cells increases and must be corrected to enable measurement of both focused high-resolution imagery and micro-Doppler signatures, as well as restoring system sensitivity. An advanced range and Doppler cell migration correction algorithm is introduced and performance evaluated using both theory and experimentation.
Using continuous statistical machine learning to enable high-speed performance prediction in hybrid instruction-/cycle-accurate instruction set simulators

Functional instruction set simulators perform instruction-accurate simulation of benchmarks at high instruction rates. Unlike their slower, but cycle-accurate counterparts however, they are not capable of providing cycle counts due to the higher level of hardware abstraction. In this paper we present a novel approach to performance prediction based on statistical machine learning utilizing a hybrid instruction- and cycle-accurate simulator. We introduce the concept of continuous machine learning to simulation whereby new training data points are acquired on demand and used for on-the-fly updates of the performance model. Furthermore, we show how statistical regression can be adapted to reduce the cost of these updates during a performance-critical simulation. For a state-of-the-art simulator modeling the ARC 750D embedded processor we demonstrate that our approach is highly accurate, with average error <2.5% while achieving a speed-up of approx. 50% over the baseline cycle-accurate simulation.
Tiled shadow maps

Shadow mapping is a commonly used technique for generating hard shadows in computer graphics, but the generated shadow boundaries often suffer from aliasing due to the discrete nature of the shadow map. In this paper we introduce a new hardware accelerated algorithm which is capable of adjusting shadow map sampling rates inside a shadow map of constant size. This is achieved by tiling the light view and changing the sampling quality according to a heuristical analysis. The implementation is straightforward on current consumer level graphics hardware and the algorithm can therefore be included into existing applications. In our test scenarios the cost of the improved image quality was moderate, making this method a viable option for increasing the quality of hard shadows
Efficient learning of general Bayesian network Classifier by Local and Adaptive Search

General Bayesian network classifier (GBNC) contains only features necessary for classification, so an ideal structure learning solution is to learn GBNC without having to learn the whole Bayesian network (BN). A local search based algorithm called LAS-GBNC is proposed. Given faithfulness assumption, LAS-GBNC relies on the information about each variable's appearance in the so-called d-separator(cut set) to sort candidate CI tests dynamically, performing `effective' ones with priority. Experimental studies indicate that (1) LAS-GBNC achieves the same quality of networks as PC and IPC-BNC, (2)It is much more efficient than PC due to its local search design, and (3) It is obviously faster than IPC-BNC because of its adaptive search strategy.
A logical analysis of Mamdani-type fuzzy inference, I theoretical bases

This paper is divided into two parts. In the present Part I, our main objective is to analyse Mamdani-type fuzzy control systems in logical terms, with special emphasis on the fuzzy inference process. To that end, we provide our own inference procedure, cast in the language of standard many-valued logics. We give an ample discussion of the logical meaning of our procedure. We eventually show how to fully recover Mamdani-type fuzzy inference from the latter. In this sense, then, our proposal may be regarded as a logical interpretation of Mamdani-type fuzzy inference. In Part II of this paper, we report on the results of an experiment on the technical analysis of the financial markets based on fuzzy techniques. The core algorithm implements the inference procedure described in this first part of the paper. In Part II, we will argue that the experimental results support the claim that our present theoretical analysis provides a sound interpretation of Mamdani-type fuzzy inference.
Emergent emergency response: Speed, event suppression and the chronopolitics of resilience

Emergency responses are premised on the hope that, even when events cannot be wholly predicted and prevented, timely action in the present can be exercised to strip an emergent event of its disruptive potential. Yet, while the speed of emergency responses plays a critical role in underpinning UK resilience, it has been a relatively neglected subject in studies of resilience advanced through the paradigm of preparedness. This article aims to contribute to and extend work in the field of emergency governance by arguing that concerns surrounding the speed of response contribute to a distinct form of security enacted in contemporary emergency response strategies, which I term ‘event suppression’. Drawing on policy analysis, preparedness exercise observations and practitioner interviews, this article investigates how speed operates as a core problematic informing the design of UK emergency responses, organized through the Integrated Emergency Management framework. Integrated Emergency Management promises to accelerate emergency response operations by utilizing advances in communications technologies to drive the bottom-up emergent self-organization of emergency responses. Event suppression ensures security not by preventing an event from happening, but by quickly closing down the ‘disruptive’ time of the emergency event and restoring the linear historical time of standard political processes.
A method for evaluating management capability of workshop production scheduling

The management capability of workshop production scheduling has been recognized as one of the important factors for the resource efficiency, delivery time and customer satisfaction of manufacturing enterprises. Therefore, a method for evaluating the management capability of production scheduling is proposed to optimize the production management. The accuracy, timeliness and effectiveness of production scheduling are measured by the formulation, execution, change and completion of the management process of production. The index model for management capability of production scheduling is established, which was driven by the data of actual production. Then, (1) scheduling generation time index, (2) scheduling execution deviation index, (3) scheduling change index and (4) scheduling completion index are built to quantitatively evaluate the capacity of production scheduling management. Finally, the usefulness and feasibility have been proved in an automobile parts–manufacturing enterprise. This article quantitatively evaluates the management capability of production scheduling. Both theoretical and results are demonstrated that the method is highly effective. The evaluation can help decision makers to better organize the production scheduling.
A Comparison of Fuzzy C-means Clustering and Rough Sets Based Classification in Network Data Analysis

This paper compares two different classification methods, Fuzzy C-means clustering and rough sets. After introducing some basic concepts of both, the methods are tested with data collected from a test network. It becomes evident that the two methods are quite different from the beginning. They require different preprocessing of the data, have different features and give different results. Fuzzy C-means clustering and rough sets are also compared in the light of the results obtained. Each one has its advantages, and the choice of method should be made in accordance with the classification problem.