Miracle-dz/UniFAR-FTUs huggingface dataset:
Integration and Publications as Indicators of "Yield" From Mixed Methods Studies

A mixed methods study has the potential to produce knowledge that is unavailable to a qualitative study and a quantitative study undertaken independently. Any unique insight or ``yield'' from a mixed methods study may be difficult to assess in practice. However, given that integration of data or findings from different components of a study is a core characteristic of mixed methods research, two possible indicators of yield can be used: first, the extent to which researchers exploit the potential for integration in mixed methods studies; and second, the way in which this integration is communicated in peer-reviewed journal articles. Here, the authors apply these indicators to mixed methods studies in health services research in the United Kingdom.
A new robust adaptive scheme using auxiliary errors: nominally relative-degree-two case

In this paper, a robust adaptive control algorithm based on Krstic et al. (1994) new adaptive scheme is proposed by introducing auxiliary errors for plants with unmodeled dynamics and/or unmeasurable output disturbances. The use of auxiliary errors means we have made use of more information about the closed loop system and thus improve the transient performance.
A new reduced-reference metric for measuring spatial resolution enhanced images

Assessment of image quality is critical for many image processing algorithms, such as image acquisition, compression, restoration, enhancement, and reproduction. In general, image quality assessment algorithms are classified into three categories: full-reference (FR), reduced-reference (RR), and no-reference (NR) algorithms. The design of NR metrics is extremely difficult and little progress has been made. FR metrics are easier to design and the majority of image quality assessment algorithms are of this type. A FR metric requires the reference image and the test image to have the same size. This may not the case in real life of image processing. In spatial resolution enhancement of hyperspectral images, such as pan-sharpening, the size of the enhanced images is larger than that of the original image. Thus, the FR metric cannot be used. A common approach in practice is to first down-sample an original image to a low resolution image, then to spatially enhance the down-sampled low resolution image using a subject enhancement technique. In this way, the original image and the enhanced image have the same size and the FR metric can be applied to them. However, this common approach can never directly assess the image quality of the spatially enhanced image that is produced directly from the original image. In this paper, a new RR metric was proposed for measuring the visual fidelity of an image with higher spatial resolution. It does not require the sizes of the reference image and the test image to be the same. The iterative back projection (IBP) technique was chosen to enhance the spatial resolution of an image. Experimental results showed that the proposed RR metrics work well for measuring the visual quality of spatial resolution enhanced hyperspectral images. They are consistent with the corresponding FR metrics.
Data processing in the wake of massive multi-core processors

Developments in concurrency (massive multi-core, GPU, and architectures such as ARM) are changing the physics computing landscape. This paper will describe the use of GPU and massive multi-core, and the changes that result from massive parallelization and the impact on data processing. Major HEP event-processing framework software runs within the changing computing environment. These frameworks have been evolving to accommodate the changes. The framework changes need to go quite a bit further, to better handle coprocessors with alternative architectures.
Limits of tomographic depth estimation

This paper presents an approach for directly depth from multiple camera images based on directly estimating the scene in 3D space. We provide a framework that can include any arrangement of camera system, ranging from isolated sensor of very few light detectors to arrays of conventional pixellated cameras. We consider the resolution limits achievable by different camera configurations. Incorporating prior information about the 3D world improves our surface estimates allows us to reconstruct parts of a viewed scene which are partially occluded. Results for real imagery are presented.
An Analysis of Factors Influencing Foreign Language Self-Efficacy Based on C5.0 Decision Tree Algorithm in Data Mining

Based on inter-correlation and permeability among disciplines, the author makes an attempt to apply the information science to cognitive linguistics to provide a new perspective for the study of foreign languages. The correlation between self-efficacy and such four factors as anxiety, learning strategies, motivation and learners’ past achievement is analyzed by means of data mining and the extent to which the above factors affect self-efficacy in language learning is explored in this paper. The paper employs the decision tree algorithm in SPSS Clementine. C5.0 decision tree algorithm is adopted to analyze data in the study. The results are elicited from the researches carried out in this paper. The increased anxiety is bound to weaken learners’ motivation over time. It is obvious that learners have low self-efficacy. It is very important to employ strategies in foreign language learning. Ignorance of using learning strategies may result in unplanned learning with unsatisfactory achievements in spite of more efforts involved. Self-efficacy in foreign language learning may be weakened accordingly. Learners’ past achievement is a reference dimension in measuring self-efficacy with weaker influence.
A Novel Strategy for Improving Temporal Verification Efficiency of Scientific Workflow Based on Temporal Constraints Accordance Adjustment

Temporal consistency is a crucial aspect of the scientiflc work∞ow quality of service. In order to improve the e‐ciency of temporal veriflcation to guarantee the work∞ow complete on time, many efiorts have been made in selecting more efiective and e‐cient checkpoints to conduct temporal veriflcation. In recent years, several checkpoint selection strategies for such a purpose have been proposed. However all of these strategies do not distinguish the relationships of upper bound constraints and verify some constraints whose temporal consistency can be deduced by others. To improve the temporal veriflcation e‐ciency, the accordant relationships between temporal constraints are deflned flrstly in this paper, then the Nested situation and the Intersected situation are discussed to clarify the relative position of temporal constraints, later two novel strategies based on accordance are proposed to adjust the temporal constraints with the Nested situation and Intersected situation respectively. Finally the simulation experiments demonstrate the strategies we presented are very efiective for improving the temporal veriflcation along scientiflc work∞ow.
Simulations, assessment and student learning

This paper reports on the use of a simulation in an introductory operations management course. Much of the literature on simulations treats them as a teaching method. In this paper, the simulation is used for student learning assessment. It was found that student performance was not very good and that financial performance in the game was not related to performance on tests. As a result of these findings it is proposed that simulations assess a different type of student learning. This is called the ability to interpret in a largely unfamiliar context. An additional exploratory experiment with an extra simulation round was conducted. Evidence from this additional experiment indicates that simulations might be an excellent method to assess this new indicator.
Verification of a network ASIC Component using Bounded Model Checking

Recently, a new technique called bounded model checking has been proposed that uses fast satisfiability solvers instead of binary decision diagrams (BDDs). This paper presents the experiences on formally verifying the behaviour and implementation of an Asynchronous Transfer Mode (ATM) network switching module using Nusmv2 tool. A number of properties described by linear temporal logic (LTL) are provided, and their verification in reasonable central processing unit (CPU) time is accomplished by estimating a more precise bound k which is determined by the circuit structure. Moreover, equivalence checking between the structural and behavioural descriptions of the whole switch module as one model is performed, and the results compared with those of the BDD-based approach. Based on that experience, bounded model checking will be the mainstream of industrial chip verification.
On coronal transparency

This article is concerned with the internal structure of coronals. Although coronals are often considered the least marked consonants on the basis of frequency and acquisition, current models of feature geometry assign coronality no special status among places of articulation.1 In this paper, we argue that the structure of coronals differs from that of other consanats in that coronals lack a Place node altogether.
Designing Networked Control Architectures for Incremental Robustness

Abstract We apply a recent result from Lazar and Heemels. [2009] that analytically relates a model predictive control suboptimal solution to performance loss in order to quantify the number of iterations necessary for the incremental primal decomposition algorithm to achieve a solution that guarantees stability. We use this result to explore the idea of “incremental robustness”, meaning that the overall system is robustly stable and its performance varies gracefully with the inclusion of sub-systems and sub-controllers. We demonstrate these ideas in a consensus seeking problem and provide simulation results. To our best knowledge, this is the first time the result in Lazar and Heemels. [2009] is applied to a distributed model predictive control framework based on primal decomposition.
Structural Investigation of Websites’ Ranking Systems in view of Information Retrieval

For years, search engines have been considered as one of the most frequently used information seeking tools through the web. Efficiency, ease of use and search quality are the main factors for giving precedence over search engines. Search quality is assessed based on the concept of page rank which is applied to scoring web documents. The structures designed for linkage among the pages of a site as well as the linkage structure among the sites inside a web are known as the most effective factor on page rank. This paper is to describe the concept of ranking web pages and investigate the structure of inter-linkage of pages.
Density Visualization and Mode Hunting Using Trees

Mode hunting, a task related to cluster analysis and density estimation, is carried out in a variety of fields. The objective is to find (distinct) regions of the feature space that have relatively high density. Although existing algorithms for clustering and density estimation can be applied to this problem, they have difficulties dealing with datasets that have large numbers of observations and/or variables. This article presents and discusses a mode-hunting algorithm, based on recursively partitioning the feature space, that is particularly applicable to such data. The algorithm is fast, but avoids many of the pitfalls of other fast methods (e.g., single link clustering). The results from the analysis are amenable to visualization as a binary tree, thus allowing us to gain further insights about the data. We apply the method to a number of simulated and real datasets.
Semiconductor‐Type MEMS Gas Sensor for Real‐Time Environmental Monitoring Applications

Low power consuming and highly responsive semiconductor‐type microelectromechanical systems (MEMS) gas sensors are fabricated for real‐time environmental monitoring applications. This subsystem is developed using a gas sensor module, a Bluetooth module, and a personal digital assistant (PDA) phone. The gas sensor module consists of a NO2 or CO gas sensor and signal processing chips. The MEMS gas sensor is composed of a microheater, a sensing electrode, and sensing material. Metal oxide nanopowder is drop‐coated onto a substrate using a microheater and integrated into the gas sensor module. The change in resistance of the metal oxide nanopowder from exposure to oxidizing or deoxidizing gases is utilized as the principle mechanism of this gas sensor operation. The variation detected in the gas sensor module is transferred to the PDA phone by way of the Bluetooth module.
Region-based volumetric medical image retrieval

Volumetric medical images contain an enormous amount of visual information that can discourage the exhaustive use of local descriptors for image analysis, comparison and retrieval. Distinctive features and patterns that need to be analyzed for finding diseases are most often local or regional, often in only very small parts of the image. Separating the large amount of image data that might contain little important information is an important task as it could reduce the current information overload of physicians and make clinical work more efficient. In this paper a novel method for detecting key-regions is introduced as a way of extending the concept of keypoints often used in 2D image analysis. In this way also computation is reduced as important visual features are only extracted from the detected key regions. The region detection method is integrated into a platform-independent, web-based graphical interface for medical image visualization and retrieval in three dimensions. This web-based interface makes it easy to deploy on existing infrastructures in both small and large-scale clinical environments. By including the region detection method into the interface, manual annotation is reduced and time is saved, making it possible to integrate the presented interface and methods into clinical routine and workflows, analyzing image data at a large scale.
Developing a Theory of Gamified Learning

Background and Aim Gamification has been defined as the use of characteristics commonly associated with video games in non-game contexts. In this article, I reframe this definition in terms of the game attribute taxonomy presented by Bedwell and colleagues. This linking is done with the goal of aligning the research literatures of serious games and gamification. A psychological theory of gamified learning is developed and explored. Conclusion In the theory of gamified learning, gamification is defined as the use of game attributes, as defined by the Bedwell taxonomy, outside the context of a game with the purpose of affecting learning-related behaviors or attitudes. These behaviors/attitudes, in turn, influence learning by one or two processes: by strengthening the relationship between instructional design quality and outcomes (a moderating process) and/or by influencing learning directly (a mediating process). This is contrasted with a serious games approach in which manipulation of game attributes is typically intended to affect learning without this type of behavioral mediator/moderator. Examples of each game attribute category as it might be applied in gamification are provided, along with specific recommendations for the rigorous, scientific study of gamification.
Learned Pattern Recognition Using Synthetic-Discriminant-Functions

A method of using synthetic-discriminant-functions to facilitate learning in a pattern recognition system is discussed. Learning is accomplished by continually adding images to the training set used for synthetic discriminant functions (SDF) construction. Object identification is performed by efficiently searching a library of SDF filters for the maximum optical correlation. Two library structures are discussed--binary tree and multilinked graph--along with maximum ascent, back-tracking, perturbation, and simulated annealing searching techniques. By incorporating the distortion invariant properties of SDFs within a library structure, a robust pattern recognition system can be produced.
Methyl (E)-3-(5-cyano-2-furyl)-2-phenylacrylate

In the title compound, C_15H_11NO_3, the dihedral angle between the mean planes of the furan and phenyl rings is 64.7 (1)degrees. The molecules are linked into infinite chains by C— H.O and C— H.pi interactions.
Adding tactile realism to a virtual reality laparoscopic surgical simulator with a cost-effective human interface device

The laparoscopic technique for performing abdominal surgery requires a very high degree of skill in the medical practitioner. Much interest has been focused on using computer graphics to provide simulators for training surgeons. Unfortunately, these tend to be complex and have a very high cost, which limits availability and restricts the length of time over which individuals can practice their skills. With computer game technology able to provide the graphics required for a surgical simulator, the cost does not have to be high. However, graphics alone cannot serve as a training simulator. Human interface hardware, the equivalent of the force feedback joystick for a flight simulator game, is required to complete the system. This paper presents a design for a very low cost device to address this vital issue. The design encompasses: the mechanical construction, the electronic interfaces and the software protocols to mimic a laparoscopic surgical set-up. Thus the surgeon has the capability of practicing two-handed procedures with the possibility of force feedback. The force feedback and collision detection algorithms allow surgeons to practice realistic operating theatre procedures with a good degree of authenticity.
Edge Detection of Binary Image Based on Memristors

Image processing is a type of memory-access-intensive application which puts a great pressure on memory access speed and bandwidth. Memristors has the ability of both memory and computing. With this property, we have designed and implemented image logic operations in memristor memory system, which could save a large amount of memory access at relatively low memory space price. Based on this work, we use image logic operations with memristors into edge detection of binary image. The main idea is as follows. First, we use XOR operation of neighboring pixels to determine whether there is an edge and get the vertical edges and horizontal edges, respectively. Then, we combine the edges in two directions to obtain the whole edge image of the original image. The experimental results show that, our design is right in function, and could reduce memory access considerably.
Prototyping Expressive 3D Social Worlds

D virtual worlds are increasingly popular arenas for social interaction. There are new opportunities and possi- bilities for the style of communication but important aspects present in face-to-face meetings are absent in the artificial environment, including the visual cues of emotion that are provided by facial expressions, and a realistic representation of one's geographical location. Our research attempts to enhance social interaction within virtual worlds by proposing a framework that would enable fully expressive Internet communication with the use of 3D expressive models. The frame- work contains three separate systems that support different aspects of social interaction within virtual worlds. Firstly, the Virtual City Maker creates a believable environment by automatically creating realistic identifiable geo-referenced 3D environments from a variety of aerial and GIS image data. Secondly, an automated 3D head modelling system provides a mechanism for generating and displaying expressions. Thirdly, the Emotion Analyser provides a mechanism for triggering the display of appropriate expressions by automatically identifying emotional words contained in text messages, the per- son to whom the emotional words refer to and the intensity. Each system in the framework is discussed with reference to their contribution to enhancing social interaction within 3D social worlds.
A new Long-Chain Secondary Alkanediol from the Flowers of Argemone mexicana

An ethanolic extract of the dried flower petals of Argemone mexicana afforded a new and optically active secondary C31-alkanediol characterised as hentriacontane-3,20-diol on the basis of spectroscopic studies including IR, HRMS, 1H and 13C NMR.
Analysis of Media Cloud Architecture and Security Technology

Cloud computing is an emerging technology, which has been the focus of the world since its birth. It is bound to bring tremendous and far-reaching changes to the field of information technology with its development. Because of its wide development space and huge appreciation potential, media cloud, as a branch of cloud computing, has become a research hotpot in recent years. It has achieved some preliminary results. As the rapid development and application of cloud computing becoming more in-depth, the disadvantages of cloud computing in security and personal privacy protection is much more obvious, which hinders the popularity and improvement of cloud computing. Those problems also exist in Media Cloud. This paper will analyze the characteristics of current media cloud and security problems based on the existing research at first. Then we propose a security framework model to solve this problem. At last, we will analyze the architecture of media cloud and try to investigate the security model for media cloud.
Simulations, learning and real world capabilities

Purpose – The purpose of this paper is to consider how simulations are increasingly used in training programs for the development of skills such as leadership. However, the requirements of leadership development go beyond the development of task specific procedural knowledge or expertise that simulations have typically been used to develop. Leadership requires flexibility in the application of knowledge developed through simulations and the creation of linkages to behavioral execution skills needed to utilize that knowledge effectively in real world settings.Design/methodology/approach – The successful acquisition of flexible expertise and the related execution skills requires instructional techniques that manage cognitive load, delay automatization of responses, and provide diversity in simulated experiences to ensure richness of the mental models developed while working on simulations. The successful transfer of that knowledge to real world settings requires supplemental instructional techniques that li.
A parameterized statistical sonar image texture model

Single-point statistical properties of envelope-detected data such as signal returns from synthetic aperture radar and sonar have traditionally been modeled via the Rayleigh distribution and more recently by the K-distribution. Two-dimensional correlations that occur in textured non-Gaussian imagery are more difficult to model and estimate than Gaussian textures due to the nonlinear transformations of the time series data that occur during envelope detection. In this research, textured sonar imagery is modeled by a correlated K-distribution. The correlated K-distribution is explained via the compound representation of the one-dimensional K-distribution probability density function. After demonstrating the model utility using synthetically generated imagery, model parameters are estimated from a set of textured sonar images using a nonlinear least-squares fit algorithm. Results are discussed with regard to texture segmentation applications.