Miracle-dz/UniFAR-FTUs huggingface dataset:
Test anxiety and learned helplessness is moderated by student perceptions of teacher motivational support

Abstract The aim of the present study was to examine the interplay between test anxiety (i.e. worry and emotionality) and learned helplessness in a sample of adolescents (N = 845, aged 13–17 years) in secondary schools in Germany. In accordance with the buffering hypothesis, it was hypothesised that the detrimental association between both components of text anxiety and helplessness in school would be buffered by students’ perception of their teachers as positive motivators (TPM). TPM refers to student motivation within the academic context, which results from their perception of teacher support. Interesting differences between the two components of test anxiety were identified: emotionality was positively associated with helplessness in school, whereas worry was negatively associated. Using latent moderated structural equations (LMS), the findings revealed that TPM functions as a moderator in the interplay between emotionality and learned helplessness. Despite these results, TPM did not operate as a buffer between emotionality and learned helplessness since helplessness in school was the highest when students perceived some degree of TPM. These findings make a case for implementing specific psychological interventions within the school context in order to prevent helplessness in school.
Localization from connectivity in sensor networks

We propose an approach that uses connectivity information - who is within communications range of whom - to derive the locations of nodes in a network. The approach can take advantage of additional information, such as estimated distances between neighbors or known positions for certain anchor nodes, if it is available. It is based on multidimensional scaling (MDS), an efficient data analysis technique that takes O(n/sup 3/) time for a network of n nodes. Unlike previous approaches, MDS takes full advantage of connectivity or distance information between nodes that have yet to be localized. Two methods are presented: a simple method that builds a global map using MDS and a more complicated one that builds small local maps and then patches them together to form a global map. Furthermore, least-squares optimization can be incorporated into the methods to further improve the solutions at the expense of additional computation. Through simulation studies on uniform as well as irregular networks, we show that the methods achieve more accurate solutions than previous methods, especially when there are few anchor nodes. They can even yield good relative maps when no anchor nodes are available.
Activity Density Map Visualization and Dissimilarity Comparison for Eldercare Monitoring

In this paper, we present a methodology for analyzing passive infrared motion sensor data logged in the homes of seniors. The objective is to capture activity patterns that represent different health conditions. Recognizing changes in the activity patterns can then be used to provide early detection of health changes. A visualization of motion sensor data is introduced in the form of a density map that uses different colors to show varying levels of activity. For evaluating the activity density level accurately, time away from home is determined first using a system of fuzzy rules. In addition, a dissimilarity between two density maps is computed using texture features for automatically determining changes in activity patterns, which may indicate a health problem. The activity density maps are being used in an aging in place senior housing community to aid clinicians in early illness detection. Three case studies of elderly residents are included to illustrate how the density map and dissimilarity measure can be used to track general activity level and daily patterns over time, showing changes in physical, cognitive, and mental health.
Post-Stroke Language Remediation through Constraint-Induced Aphasia Therapy

ii List of Tables . xiiii List of Figures . xiiiii Chapter 1 Background & Motivation. 1 Constraint-Induced Aphasia Therapy . 2 Learned motor non-use . 2 Learned non-use of spoken communication . 3 Constraint-induced interventions . 4 Intensity . 5 Constraints . 6 Language shaping . 9 Implementation of language shaping through cueing paradigms . 12 Phonologic, visual and semantic language-shaping cueing hierarchies for word retrieval. 14 Discourse level language shaping cueing strategies. 16 Theories of language processing and production . 18 Clinician Training . 19 Documenting Gains in Discourse after CIAT . 22 Statement of the Problem . 24 Purpose . 25 Study 1: Constraint-Induced Aphasia: Examining Linguistic Gains in Discourse . 25 Research Design . 25 Research Questions and Hypotheses . 26 Study 2: Constraint Induced Aphasia Therapy: What about Shaping? 27 CIAT: Post-Stroke Language Remediation viii Research Design . 27 Research Questions and Hypotheses . 27 References . 29 Appendix Operational definitions of linguistic measures . 40 Chapter 2 Constraint-Induced Aphasia Therapy: Examing Linguistic Gains in Discourse . 41 Abstract . 43 Constraint-Induced Aphasia Therapy: Examining Linguistic Gains in Discourse . 44 Discourse Measures Utilized to Evaluate Aphasia Intervention . 46 Discourse outcomes following CIAT . 47 Method . 48 Research Design . 48 Participants . 49 Materials . 49 Assessment . 49 Motor speech disorders rating scale . 50 Equipment . 50 Stimulus cards . 50 Equipment . 50 Procedures . 51 Goal setting . 52 CIAT intervention . 52 Setting . 53 Recording and Transcriptions . 53 CIAT: Post-Stroke Language Remediation ix Linguistic Analysis . 53 Reliability . 54 Statistical Analyses . 54 Results . 55 Content . 56 Complexity . 56 Efficiency . 56 Communicative Success . 57 Discussion . 57 Discourse Measures Sensitive to Positive Changes Following CIAT . 57 Discourse Measures that May Display Positive Gains Following CIAT . 58 Limitations and Future Directions . 61 References . 65 Appendix A Perceptual rating scale to determine presence of concoitant motor speech disorders . 75 Appendix B Operational definitions of linguistic measures . 77 Chapter 3 Constraint-Induced Aphasia Therapy: What about Shaping? 78 Abstract . 80 Constraint-Induced Aphasia Therapy: What about Shaping? 82 What is Shaping? 82 Cueing Hierarchies in Aphasiology . 84 Purpose . 86 Method . 86. 80 Constraint-Induced Aphasia Therapy: What about Shaping? 82 What is Shaping? 82 Cueing Hierarchies in Aphasiology . 84 Purpose . 86 Method . 86 CIAT: Post-Stroke Language Remediation x Research Design . 86 Participants . 87 People with aphasia .
The Fluorescent Protein Color Palette

Advances in fluorescent protein development over the past 10 years have led to fine‐tuning of the Aequorea victoria jellyfish color palette in the emission color range from blue to yellow, while a significant amount of progress has been achieved with reef coral species in the generation of monomeric fluorescent proteins emitting in the orange to far‐red spectral regions. It is not inconceivable that near‐infrared fluorescent proteins loom on the horizon. Expansion of the fluorescent protein family to include optical highlighters and FRET biosensors further arms this ubiquitous class of fluorophores with biological probes capable of photoactivation, photoconversion, and detection of molecular interactions beyond the resolution limits of optical microscopy. The success of these endeavors certainly suggests that almost any biological parameter can be investigated using the appropriate fluorescent protein–based application.
Placing user-generated content on the map with confidence

We describe a method that predicts the location of user-generated content using textual features alone. Unlike previous methods for geotagging text documents, our proposed method is not sensitive to how we discretize space. We also discover that spatial resolution has an impact on the prediction accuracy, which allows us to trade-off the spatial resolution of the predicted location against our confidence about its accuracy. Our method can be used to estimate the error in document's predicted location, enabling us to filter out poor quality predictions. We evaluate the proposed method extensively on user-generated content collected from two different social media sites, Flickr and Twitter. Our evaluation examines its performance on the geotagging task and with respect to different parameters. We achieve state-of-the-art results for all three tasks: location prediction, error estimation and result ranking and also provide a theoretical explanation of the effect of spatial resolution factor on geotagging accuracy. Our findings provide valuable insights into the design of geotagging systems and their quality control.
Reduction of substrate-mode effects in power-combining arrays

We report a simple theory for the reduction of substrate modes in quasi-optical power-combining arrays. This qualitative theory predicts that detrimental substrate-mode effects can be greatly reduced through a judicious choice of the array unit cell size. Experimental evidence from quasi-optical tripler grids is presented to confirm the theory. Measured results show a dramatic improvement in the radiation pattern and effective radiated power of arrays with both grounded and ungrounded substrates.
Determining the Structure of Decision Directed Acyclic Graphs for Multiclass Classification Problems

An usual strategy to solve multiclass classification problems in Machine Learning is to decompose them into multiple binary sub-problems. The final multiclass prediction is obtained by a proper combination of the outputs of the binary classifiers induced in their solution. Decision directed acyclic graphs (DDAG) can be used to organize and to aggregate the outputs of the pairwise classifiers from the one-versus-one (OVO) decomposition. Nonetheless, there are various possible DDAG structures for problems with many classes. In this paper evolutionary algorithms are employed to heuristically find the positions of the OVO binary classifiers in a DDAG. The objective is to place easier sub-problems at higher levels of the DDAG hierarchical structure, in order to minimize the occurrence of cumulative errors. For estimating the complexity of the binary sub-problems, we employ two indexes which measure the separability of the classes. The proposed approach presented sound results in a set of experiments on benchmark datasets, although random DDAGs also performed quite well.
Depth coding using depth discontinuity prediction and in-loop boundary reconstruction filtering

This paper presents a depth coding strategy that employs K-means clustering to segment the sequence of depth images into K clusters. The resulting clusters are losslessly compressed and transmitted as supplemental enhancement information to aid the decoder in predicting macroblocks containing depth discontinuities. This method further employs an in-loop boundary reconstruction filter to reduce distortions at the edges. The proposed algorithm was integrated within both H.264/AVC and H.264/MVC video coding standards. Simulation results demonstrate that the proposed scheme outperforms the state of the art depth coding schemes, where rendered Peak Signal to Noise Ratio (PSNR) gains between 0.1 dB and 0.5 dB were observed.
New Complexity Results for MAP in Bayesian Networks

This paper presents new results for the (partial) maximum a posteriori (MAP) problem in Bayesian networks, which is the problem of querying the most probable state configuration of some of the network variables given evidence. It is demonstrated that the problem remains hard even in networks with very simple topology, such as binary polytrees and simple trees (including the Naive Bayes structure), which extends previous complexity results. Furthermore, a Fully Polynomial Time Approximation Scheme for MAP in networks with bounded treewidth and bounded number of states per variable is developed. Approximation schemes were thought to be impossible, but here it is shown otherwise under the assumptions just mentioned, which are adopted in most applications.
Mid-infrared imaging and modelling of the dust shell around post-AGB star HD 187885 (IRAS 19500–1709)

We present 10- and 20-μm images of IRAS 19500-1709 taken with the mid-infrared camera, OSCIR, mounted on the Gemini North Telescope. An extended circumstellar envelope is detected, with the N-band image indicating an elongation in a north-east-south-west direction. We use a dust radiation transport code to fit the spectral energy distribution from ultraviolet to submillimetre wavelengths, with a detached dust shell model. A good fit is achieved using dust composed of amorphous carbon, silicon carbide and magnesium sulphide. We derive estimates for the inner and outer radius, density and mass of the dust in the shell. The inner radius is not resolved in our OSCIR imaging, giving an upper limit of 0.4 arcsec. With this constraint, we conclude that IRAS 19500-1709 must be at least 4 kpc away in order to have the minimum luminosity consistent with a post-asymptotic giant branch status.
Generalization of Multi-Channel Linear Prediction Methods for Blind MIMO Impulse Response Shortening

The performance of many microphone array processing techniques deteriorates in the presence of reverberation. To provide a widely applicable solution to this longstanding problem, this paper generalizes existing dereverberation methods using subband-domain multi-channel linear prediction filters so that the resultant generalized algorithm can blindly shorten a multiple-input multiple-output (MIMO) room impulse response between a set of unknown number of sources and a microphone array. Unlike existing dereverberation methods, the presented algorithm is developed without assuming specific acoustic conditions, and provides a firm theoretical underpinning for the applicability of the subband-domain multi-channel linear prediction methods. The generalization is achieved by using a new cost function for estimating the prediction filter and an efficient optimization algorithm. The proposed generalized algorithm makes it easier to understand the common background underlying different dereverberation methods and future technical development. Indeed, this paper also derives two alternative dereverberation methods from the proposed algorithm, which are advantageous in terms of computational complexity. Experimental results are reported, showing that the proposed generalized algorithm effectively achieves blind MIMO impulse response shortening especially in a mid-to-high frequency range.
A new hybrid artificial bee colony algorithm for the traveling salesman problem

This paper presents a novel hybrid artificial bee colony algorithm (ABC&PR) to solve the traveling salesman problem (TSP). The main feature of this hybrid algorithm is to hybridize the solution construction mechanism of the artificial bee colony (ABC) algorithm with path relinking (PR), an evolutionary method, which introduce progressively attributes of the guiding solution into the initial solution to obtain the high quality solution as quickly as possible. Moreover, the hybrid ABC algorithm considers both solution diversification and solution quality, and it adopts the dynamic updating strategy of the reference set and the criterion function restricting the frequencies of using the path-relinking procedure to accelerate the convergence towards high-quality regions of the search space. Finally, the experimental results for benchmark TSP instances have shown that our proposed method is very efficient and competitive to solve the traveling salesman problem compared with the best existing methods in terms of solution quality.
Australian social work academics’ perceptions of their teaching roles within higher education

ABSTRACT The marketisation of higher education (HE) has created a number of tensions and ideological dilemmas that may influence how academics see their roles and teaching practices. This paper explores how academics in the discipline of social work (who were also in leadership roles) perceive their roles and identities and manage the tensions and dilemmas that arise for them as teachers in the current HE environment. Unless the tensions and dilemmas are articulated, it is not possible to understand and manage their impact on academics. This may lead to the loss of quality learning experiences for students and lower workplace satisfaction. This paper addresses the research question: were there ideological dilemmas experienced by social work academics in the current environment and if so, what subject positions did they adopt in response to these? A discursive psychology approach was used to answer this question. Data showed a range of ideological dilemmas represented by each of the different subject positions adopted. The paper concludes with questions for readers to consider, generating ideas for transferring understanding of these ideological dilemmas into positive action within the workplace.
Multiplicative Update for Projective Nonnegative Matrix Factorization with Bregman Divergence

Nonnegative Matrix Factorization (NMF) has been widely used in dimensionality reduction, machine learning, and data mining, etc. It aims to find two nonnegative matrices whose product can well approximate the nonnegative data matrix, which naturally lead to parts-based representation. In this paper, we present a family of projective nonnegative matrix factorization algorithm, PNMF with Bregman divergence. Several versions of divergence such as Euclidean distance and Kullback-Leibler (KL) divergence with PNMF have been studied. In this paper, we investigate the MU rules to solve the PNMF with some other divergence, such as β-divergence, IS-divergence. It has been shown that the base matrix by Bregman PNMF is better suitable for orthoganal, localized and sparse representation than by traditional NMF.
Accelerating Database Processing at Database-Driven Web Sites

Most commercial Web sites dynamically generate their contents through a three-tier server architecture composed of a Web server, an application server, and a database server. In such an architecture, the database server easily becomes a bottleneck to the overall performance. In this paper, we propose WDBAccel, a high-performance database server accelerator that significantly improves the throughput of database processing. WDBAccel eliminates costly, complex query processing needed to obtain query results by reusing the results from previous queries for subsequent queries. This differentiates WDBAccel from other database cache systems, which employ traditional query processing. WDBAccel further improves its performance by fully utilizing main memory as the primary storage. This paper presents the design and implementation of the WDBAccel as well as the results of performance evaluation with a prototype.
Stochastic MPC for Systems with both Multiplicative and Additive Disturbances

Abstract A stochastic MPC strategy is proposed to handle systems with both multiplicative and additive random uncertainty. Through a dual mode strategy, the system can be divided into a nominal dynamics and an error dynamics. The errors are further decomposed into two parts: one for which it is possible to construct probabilistic tubes offline with the explicit use of the disturbance distribution information, and the other which can be handled through the use of a set of robust tubes with bounding facets of fixed orientation, whose distances from the origin are optimized online. The robust tubes can exhibit little conservativeness on account of the fact that the number of the bounding facets of tubes in the predictions can be varying through online optimization. A tailored terminal set is investigated to ensure the recursive feasibility and stability of the algorithm. The online computation is turned into a standard quadratic program, which is of comparable order of complexity as that of robust MPC. A numerical example is given to illustrate the effectiveness of the algorithm.
CS264: Beyond Worst-Case Analysis Lecture #11: LP Decoding

This lecture covers our final subtopic within the “exact and approximate recovery” part of the course. The problem we study concerns error-correcting codes, which solve the problem of encoding information to be robust to errors (i.e., bit flips). We consider only binary codes, so the objects of study are n-bit vectors. Recall that a code is simply a subset of {0, 1}; elements of this subset are codewords. Recall that the Hamming distance dH(x, y) between two vectors is the number of coordinates in which they differ, and that the distance of a code is the minimum Hamming distance between two different codewords. For example, consider the code {x ∈ {0, 1} : x has even parity}, where the codewords are vectors that have an even number of 1s. One way to think about this code is as the set of all (n − 1)-bit vectors, with an extra “parity bit” appended at the end. The distance of the code is exactly 2. If an odd number of bit flips is suffered during transmission, the error can be detected, and the receiver can request a retransmission from the sender. If an even number of bit flips occurs, then the receiver gets a codeword different from the one intended by the sender. For a code with distance d, up to d− 1 adversarial errors can be detected. If the number of errors is less than d/2, then no retransmission is required: there is a unique codeword closest (in Hamming distance) to the transmission, and it is the message originally sent by the receiver. That is, the corrupted transmission can be decoded by the receiver. This lecture studies the computational problem of decoding a corrupted codeword, and conditions under which the problem can be solved efficiently using linear programming. This approach works well for a useful family of codes, described next.
Fine-grained federation of geographic information services through metadata aggregation

Large scale Geographic Information Systems (GIS) require experts from different areas, such as data maintenance and handling, data rendering and displaying, and data processing. However, it is challenging to host data, processing capabilities, and experts in the same geographical location. To enable remote coupling of these data and processing services, interoperable distributed system architectures have been developed. This paper presents a distributed Service Oriented Architecture (SOA) framework for understanding and managing the production of knowledge from distributed observations, simulations, and analyses through integrated data-views. Open GIS standards enable us to develop such a distributed framework by defining the standard common data models and corresponding web service components. The composability nature of these components has inspired us to develop a federated information system framework enabling both application-based hierarchical data definitions and performance enhancing designs. Key words: Geographic information systems, federation, web services, data models, metadata.