Miracle-dz/UniFAR-FTUs huggingface dataset:
The Relationship between Elementary Principals' Conceptualization of Instructional Leadership and their Perceived Use of Time

The Relationship between Elementary Principals‘ Conceptualization of Instructional Leadership and their Perceived Use of Time Mardel Smith Higginson Department of Education, BYU Doctor of Philosophy The purpose of this study was to learn about how elementary principals conceptualized instructional leadership and whether the way they thought about leadership influenced their allotted use of time for instructional leadership. In order to answer this question, two subquestions needed to be answered about how elementary principals conceptualized instructional leadership and how elementary principals perceived they used their time. This mixed-method study interviewed 30 principals in an urban-suburban school district in Utah to produce data. Each principal participated in a newly constructed survey of 84 questions. The survey consisted of four parts including demographics, open-ended questions about instructional leadership, and paper and pencil questions about both instructional leadership and how the principal thought they spent their time. The findings of the study showed that the principals recognized and agreed with a broad definition of instructional leadership when prompted, but they were only able to articulate a limited definition made up of between three and ten sub-concepts. Every principal‘s self constructed combination of the sub-concepts differed. However, when the principal‘s conceptualization of instructional leadership was translated into the time they spent on each task associated with that conceptualization, 68% of the responses fell into those tasks associated with the narrow definition of instructional leadership, however only 60% of their time was used for tasks associated with the narrow definition of instructional leadership. (The principals conformed their instructional leadership time to their self constructed conceptualization from 10.7% to 100% of their time.) Principals committed between 7.0-38% of their total time to instructional leadership, but the average amount of time spent on instructional leadership was 20% of their total time. Principals who had more time tasks associated with the narrow definition of instructional leadership committed more of their total time to instructional leadership. The principals who indicated that coaching, mentoring, and collaboration as the most important activities of instructional leadership spent more time doing these instructional leadership tasks than principals who said other activities were most important. The task most often associated with instructional leadership when principals self constructed their responses was ―being in classrooms and evaluating teachers. ‖
The effect of the inclusion of a computer-based interviewing system on patient-clinician communication during the subsequent consultation

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Fusion of SPOT HRV XS and Orthophoto Data Using a Markov Random Field Model

: In remote sensing there is usually a trade-off between spatial resolution and spectral resolution. It is often desirable to present a combination of the data which merges the low resolution spectral (colour) information with the high resolution spatial information. If the ratio in spatial resolution between the greyscale image and the colour image becomes too great the image resulting from usual itensity substitution techniques will tend to look as if it has “squares” of colour information overlaid on the greyscale image. A new way of “fusing” the colour information with the greyscale information is presented here. The technique is based on Markov random ﬁeld (MRF) assumptions and the maximum a posteriori (MAP) estimate is found by means of iterated conditional modes (ICM). The design of the speciﬁc Markov random ﬁeld used here allows the user to control three properties of the resulting “merged” image: 1) degree of colour smoothness between neighbouring pixels, 2) degree of conﬁdence in the original colour information (e.g. SPOT HRV XS), and 3) degree of conﬁdence in the original panchromatic information (e.g. orthophoto). As a possible fourth control element, we may exclude neighbours belonging to other segments of the segmented orthophoto from the neighbourhood of the MRF. The data used here as an example are from the town of Sorø in Denmark. The data consist of a digital orthophoto (62.5 cm pixels) and a SPOT HRV XS (20 m pixels) giving a linear ratio
Research of Vehicle Video Analysis System Based on SVM

In the process of building a safe city, security is an important task in the daily management of the government, and with the construction of the city alarm and monitoring system, the analysis of monitoring data is also increasingly important. In this paper, analysis of surveillance video and the development of the license plate analysis system based on SVM recognition technology is proposed. It is shown that the development of the system can help to improve the level of vehicle analysis and promote traffic management and supervision means.
Optimal amplitude quadrature control of an optical squeezer using an integral LQG approach

Squeezed states of light possess an asymmetric noise distribution whereby the uncertainty in one quadrature is less than the standard quantum noise limit. These states can be generated through a nonlinear optical process in an optical parametric oscillator (OPO). In this paper, we model such an optical squeezer and design an LQG controller which includes integral action to optimize the level of squeezing achieved in one of the quadratures of the fundamental optical field.
Comparison of three Monte Carlo conformational search strategies for a proteinlike homopolymer model: Folding thermodynamics and identification of low-energy structures

Entropy sampling Monte Carlo, the replica method, and the classical Metropolis scheme were applied in numerical studies of the collapse transition in a simple face-centered cubic lattice polymer. The force field of the model consists of pairwise, contact-type, long-range interactions and a short-range potential based on the β-sheet definition assumed in the model. The ability to find the lowest energy conformation by various Monte Carlo methods and the computational cost associated with each was examined. It is shown that all of the methods generally provide the same picture of the collapse transition. However, the most complete thermodynamic description of the transition derives from the results of entropy sampling Monte Carlo simulations, but this is the most time-consuming method. The replica method is shown to be the most effective and efficient in searching for the lowest energy conformation. The possible consequences of these findings for the development of simulation strategies for the folding of m.
Adaptive identification and control for manipulators without using joint accelerations

We present a new scheme for the adaptive control of mechanical manipulators along with proof of convergence. This work is an extension of our earlier work [Craig, Hsu and Sastry] [1]. The new scheme does not require the measurement of joint accelerations and needs less computation. We illustrate the theory with some simulations.
The relational tacit dimensions of knowledge used within the explicit standardised processes of professional practice in the Irish Forensic Science Laboratory

The organisational literature explaining tacit knowledge as a whole has remained conceptual and there is now a need to know empirically about the nature of tacit knowledge at the process level where the knowledge worker carries out work. This doctoral research case study empirically examines the tacit dimensions of knowledge that occur between knowledge worker practitioners especially within an explicit environment of codified standardised, operating procedures and intranet knowledge databases. In this case the evidence comes from a multi-method approach. The empirical findings are based on a case study of a forensic science community of practice, at the micro-level between knowledge workers, where quantitative social network analysis and qualitative interviewing, ethnographic studies, and document review were carried out. The quantitative picture, using social network analysis was used to give a fixed perspective on the actors sharing tacit knowledge during advice seeking transactions within the communities. An interpretive qualitative approach was used where the intent was to understand the relational dimensions of tacit knowledge being shared between the same actors. Social theories of learning perspectives are used, in particular with the emphasis on communities of practice as a framework, to study structured relational mechanisms that shape tacit knowledge flows. Organisational learning can be seen as a function of relationships between actors within a dynamic environment of social interaction, and matter most when collegiate interactions involve the exchange of tacit knowledge. Within a micro-level case study of a highly technical forensic science expert community, this research emphasizes the relational tacit dimensions of knowledge provided by human social capital surrounding and encircling the standardised organisational production process. Trust, respect, friendship, identity and
Mechanisms of clearance of nontypeable Haemophilus influenzae from cigarette smoke-exposed mouse lungs

Inflammation is prevalent in all stages of chronic obstructive pulmonary disease, and, furthermore, individuals undergo periods of exacerbation, during which pulmonary inflammation increases, often a result of bacterial infection. The present study investigates the in vivo consequences of cigarette smoke exposure on bacterial challenge with nontypeable Haemophilus influenzae (NTHi). BALB/c and C57 black 6 (C57BL/6) mice were exposed to cigarette smoke once or twice daily for a total period of 8 weeks. Exacerbated inflammation was observed in cigarette smoke-exposed compared to room-air-exposed mice following challenge with live or heat-inactivated NTHi. Accelerated clearance of live NTHi from cigarette smoke-exposed mice was independent of the establishment of chronic inflammation or direct toxic effects of cigarette smoke components on bacteria. Mechanistically, a cell-free factor in the bronchoalveolar lavage fluid contributed to accelerated clearance following passive transfer to naive mice. Further investigation demonstrated increased titres of immunoglobulin A in the bronchoalveolar lavage fluid, but not the blood, of cigarette smoke-exposed mice, including increased titres of NTHi-specific immunoglobulin A, whereas heavy chain joining element (JH)-/- B-cell-deficient cigarette smoke-exposed mice did not demonstrate decreased bacterial burden following challenge. The present results demonstrate that cigarette smoke exposure results in exacerbated inflammation following challenge with NTHi, as well as increased titres of antibodies that contribute to bacterial clearance.
Fast implementation of density-weighted average derivative estimation

Given random variables X isin R/sup d/ and Y such that E[Y|X=x]=m(x), the average derivative delta /sub 0/ is defined as delta /sub 0/=E[ nabla m(X)], i.e., as the expected value of the gradient of the regression function. Average derivative estimation has several applications in econometric theory (T.M. Stoker, 1992) and thus it is crucial to have a fast implementation of this estimator for practical purposes. We present such an implementation for a variation known as density weighted average derivative estimation. This algorithm is based on the ideas of binning or Weighted Averaging of Rounded Points (WARPing). The basic idea of this method is to discretize the original data into a d variate histogram and to replace in the nonparametric smoothing steps the actual observations by the appropriate bincenters. The nonparametric smoothing steps become thus a (multidimensional) convolution between the (discretized) data and the (discretized) smoothing kernel. A Monte Carlo study demonstrates that with this binned implementation substantial reduction in computing time can be achieved. But it will also become clear that in higher dimension the choice of how to bin is crucial.
Tensor Clustering for Rendering Many‐Light Animations

Rendering animations of scenes with deformable objects, camera motion, and complex illumination, including indirect lighting and arbitrary shading, is a long‐standing challenge. Prior work has shown that complex lighting can be accurately approximated by a large collection of point lights. In this formulation, rendering of animation sequences becomes the problem of efficiently shading many surface samples from many lights across several frames. This paper presents a tensor formulation of the animated many‐light problem, where each element of the tensor expresses the contribution of one light to one pixel in one frame. We sparsely sample rows and columns of the tensor, and introduce a clustering algorithm to select a small number of representative lights to efficiently approximate the animation. Our algorithm achieves efficiency by reusing representatives across frames, while minimizing temporal flicker. We demonstrate our algorithm in a variety of scenes that include deformable objects, complex illumination and arbitrary shading and show that a surprisingly small number of representative lights is sufficient for high quality rendering. We believe out algorithm will find practical use in applications that require fast previews of complex animation.
Turning Points: Stories of How Students Get Beyond Antipathy Toward an Academic Course

Turning Points: Stories of How Students Get Beyond Antipathy Toward an Academic Course Cheryl Beck Morse Department of Instructional Psychology and Technology Master of Science The purpose of this qualitative study was to examine the narratives of 10 students who began an academic course with strong negative attitudes but finished the course with strong positive attitudes. In the beginning of the course, each student exhibited one of these three tendencies: apathetic, compliant, or disillusioned; however, by the end of the course, they exhibited a transformed disposition. This study attempts to answer the question of what the turning points were for their transformation and how they made the change. The findings of this study were that regardless of individual tendencies, the ability to exercise agency was the principal turning point for these students, followed by seeing that relevance in their own lives, and taking the initiative to approach the teacher with problems. An unexpected finding was how students with a transforming tendency tend to see learning as a spiritual activity and that through faith, acknowledging others, reverence, and humility, they can change their strong negative attitudes toward a course.
Blueprint Flow: A Declarative Service Composition Framework for Cloud Applications

Cloud applications provides users with services that can be accessed on demand through the Internet. Fertile service frameworks are considered one of the most critical ingredients for the envisaged benefits so as to further interactions among cloud computing resources and application components. Such foundations should lead to the proliferation of new innovative services and applications. The research community has been exploring the Open Service Gateway initiative’s (OSGi) potential as a top candidate for cloud application platforms. Although the current OSGi specification provides some level of support for dynamic service discovery, tracking, and composition, more should be done to be able to adequately address the need for diverse interaction patterns for cloud applications. This paper introduces a novel service framework built upon OSGi platforms that supports a directed-acyclic-graph style composition of constituent services. Given a declarative blueprint of service interconnections and interactions, the framework can find and assemble corresponding component services to form a real application. Our proposal can enable a realistic topology of service component interlinkings beyond linear chaining interactions as supported by the status quo. The design, implementation details, and validation results of our workflow-based service composition framework architecture are discussed in the paper.
Using Data Clustering in Oral Medicine

Abstract — The vast amount of information hidden in huge databases has created tremendous interests in the field of data mining. This paper examines the possibility of using data clustering techniques in oral medicine to identify functional relationships between different attributes and classification of similar patient examinations. Commonly used data clustering algorithms have been reviewed and as a result several interesting results have been gathered. Keywords — Oral Medicine, Cluto, Data Clustering, Data Mining. I. I NTRODUCTION N this paper, potential pitfalls and practical issues about data mining in oral medicine using data clustering techniques are discussed. In oral medicine, theoretical education to dental students is usually given through lectures, books and scientific papers. Text books often present a small number of cases for each diagnosis. The information students receive may therefore not reflect the reality a clinician in oral medicine encounters in daily practice. When the students graduate the learning that comes with experience from treatment outcomes may therefore be missing. mEduWeb is a program that was written and designed earlier to give students the possibility to study oral medicine through a web interface. mEduWebII used Medview database which contains several thousand patient examinations [1]. The purpose of our work has been to seek improvements in the current mEduWebII program. The objective is to explore data clustering techniques for finding patient examinations that are similar to each other. Several interesting and useful results have been gathered through a series of experiments. Clustering is the unsupervised classification of patterns into clusters [2]. Finding interesting patterns in large datasets has attracted considerable interest recently [5]. Clustering classifies similar objects into different groups [3]. An example of clustering is shown in Fig. 1 [2]. The input patterns are shown in Fig. 1(a), and desired clusters are shown in Fig. 1 (b). Here points belonging to same cluster are given same label [2].
Cooperative Base Station Switching Off in Multi-Operator Shared Heterogeneous Network

The dense deployment of high and low power nodes, i.e., eNodeBs (eNBs) and small cells (SCs), respectively, is expected to be the core element of fifth generation (5G) networks. Given the massive SC deployment, the aggregate power consumption attributed to SCs in the coverage area of a macrocell becomes considerable, thus raising issues for the network energy efficiency. However, the coexistence of multiple mobile network operators (MNOs) in the same geographic area fosters cooperation agreements that suggest further energy and cost saving. In this paper, with a view to address the aforementioned issues, we attempt to study the energy efficiency aspects in the case of next generation outdoor Long Term Evolution (LTE) heterogeneous networks (HetNets) owned by rival MNOs. More specifically, we propose a cooperative switching off scheme for low-traffic hours that applies to both eNBs and SCs and exploits roaming-based infrastructure sharing to guarantee the provided quality of service (QoS). To gain insights, we study the energy consumption impact compared to existing switching off schemes. It is shown that the proposed scheme achieves notable energy saving, without compromising the QoS to the network users.
Multi-tier Non-uniform Unit Selection for Corpus-based Speech Synthesis

In this paper, a corpus-based speech synthesis system KB2006 was developed using the speech database provided by Blizzard Challenge 2006. We proposed a novel unit selection method called multi-tier non-uniform unit selection in our corpus-base speech synthesis system. Non-uniform unit (NUU) in our system was defined as a unit sequences that contains one or more joint phoneme units. By using CART algorithm, NUUs with the same phoneme sequence in the inventory were clustered into different classes according to their prosody and acoustic difference. In the unit selection stage, a multi-tier NUUs selection algorithm was adopted by treating different NUUs with several criterions. With the discrimination, proper candidate units that close to the target unit can be selected for speech concatenation.
SINS Rapid In-Motion Alignment Based on Nonlinear Filter

Strapdown inertial navigation system (SINS) is a dead-reckoning navigation system. Hence, the navigation performance of SINS heavily depends on the proper initial alignment, which determines the transformation matrix from the body frame to the navigation frame. The velocity and attitude matching scheme is known as one of the best combined matching algorithm of SINS in-motion alignment, since it can achieve sub- milliradian alignment accuracy without the lateral acceleration requirement and lengthy time requirement. In this paper, a new SINS/GPS in-motion alignment model based on the quaternion is presented for the velocity and attitude matching algorithm. It directly uses the quaternion form of the misalignment angles as the state variables. By the simulation of the on-sea alignment, six nonlinear filters are compared. These filters include the unscented Kalman filter (UKF), the unscented particle filter (UPF), the Gaussian particle filter (GPF), the Rao-Blackwellized unscented Kalman filter (RBUKF), the Rao-Blackwellized unscented particle filter (RBUPF) and the Rao-Blackwellized Gaussian particle filter (RBGPF). The simulation results show that the estimation value of the azimuth misalignment can converge at the round of the true value with the same convergent velocity as the level misalignment if using the proposed model in this paper. Although only 20 particles are used in each particle filter, the estimation values of the misalignments can rapidly converge at the round of the true values in less than 0.1 second (two steps in this paper). Moreover, the estimation accuracy of the azimuth misalignment could achieve sub-milliradian in less than 1 second for the small initial misalignments, sub- decimilliradian in less than 20 seconds for the large initial misalignments. Furthermore, the estimation performance of RBGPF is best, and one of UPF is worst in these considered filters.