Miracle-dz/UniFAR-FTUs huggingface dataset:
Depth Error Elimination for RGB-D Cameras

The rapid spreading of RGB-D cameras has led to wide applications of 3D videos in both academia and industry, such as 3D entertainment and 3D visual understanding. Under these circumstances, extensive research efforts have been dedicated to RGB-D camera--oriented topics. In these topics, quality promotion of depth videos with the temporal characteristic is emerging and important. Due to the limited exposure time of RGB-D cameras, object movement can easily lead to motion blurs in intensive images, which can further result in obvious artifacts (holes or fake boundaries) in the corresponding depth frames. With regard to this problem, we propose a depth error elimination method based on time series analysis to remove the artifacts in depth images. In this method, we first locate the regions with erroneous depths in intensive images by using motion blur detection based on a time series analysis model. This is based on the fact that the depth image is calculated by intensive color images that are captured synchronously by RGB-D cameras. Then, the artifacts, such as holes or fake boundaries, are fixed by a depth error elimination method. To evaluate the performance of the proposed method, we conducted experiments on 250 images. Experimental results demonstrate that the proposed method can locate the error regions correctly and eliminate these artifacts effectively. The quality of depth video can be improved significantly by using the proposed method.
Instructional Model for Social Skills Intervention Children with Visual Impairment

This paper discusses a proposed instruction model for intervention of social skills children with visual impairment. Intervention model based on Badura’s Social Cognitive Learning Theory were proposed to help students with visual impairment in the development of their social skills. The emphasis of the theory was based on imitation, environment and cognition. The three elements are interrelated in the development of social skills and individual behavior. The theory stressed the process of learning behavior through imitation. Without visual information, the imitation was learnt from the information through hearing and touch as well as physical model. The process of imitation was received with reward, reinforcement and motivation will strengthen the social skills learned and the target behavior. In addition, teachers, parents and the communities have an important role in helping and training the visually impaired children to improve their social skills. The impact of the proposed intervention model, the social skill of visual impairment children will be improved so that they can be socialized effectively with typical children.
Performance-based building and innovation: balancing client and industry needs

One reason for the interest in performance-based building is that it is commonly advocated as a powerful way of enhancing innovation performance by articulating building performance outcomes, and by offering relevant procurement actors the discretion to innovate to meet these performance requirements more effectively and/or efficiently. The paper argues that the current approach to performance-based building assumes that relevant actors have the capacity, ability and motivation to innovate from a business perspective. It is proposed that the prevailing conceptualization of PBB is too restrictive and should be broadened explicitly to accommodate the required business logic that must be in place before actors will innovate. The relevant performance-based building and innovation literature is synthesized to support the assertion. The paper concludes with an innovation-focused definition of performance-based building.
Large-Scale Optimal PDDL 3 Planning with MIPS-XXL

State trajectory and preference constraints are the two language features introduced in PDDL3 (Gerevini & Long 2005) for describing benchmarks of the 5 international planning competition. State trajectory constraints provide an important step of the agreed fragment of PDDL towards the description of temporal control knowledge and temporally extended goals They assert conditions that must be met during the execution of a plan and are often expressed using quantification over domain objects. We suggest to compile the state trajectory and preference constraints into PDDL2 (Edelkamp 2006). Trajectory constraints are compiled into Büchi automata that are synchronized with the exploration of the planning problem, while preference constraints are transformed into numerical fluents that are changed upon violation. An internal weighted best-first search is invoked that tries to find a solution. Once a solution is found, the solution quality is inserted in the problem description and a new search is started using earlier solution cost as the minimization parameter. If the internal search fails to terminate with in a specified amount of time, we switch to a cost-optimal external breadth-first search procedure that utilizes harddisk to store the generated states.
How unfair can weighted fair queuing be?

This paper presents a study carried out on a weighted fair queuing implementation for Unix routers-the WFQ implementation of the ALTQ project. It shows the WFQ/ALTQ weaknesses and explains why we cannot expect an interesting behavior from a system using such a scheduler. The conclusions here presented are supported by a set of tests using UDP traffic only. With a tool developed in our laboratory, we were able to show that changing the classes' weights does not necessarily result on a different quality of service for each of the existing classes. To achieve this differentiation, the lengths of the queues which serve the scheduler (one for each class) must be increased beyond reasonable values. We found that the low-level dynamics of FreeBSD systems practically turns WFQ schedulers useless. The same is applicable to any other work-conserving discipline. Thus, an important conclusion of this paper, is that one must design very carefully the platforms that support work conserving disciplines in order to expect adequate behaviors from those systems, in terms of QoS provision.
Hausdorff leaf spaces for codim-1 foliations

The topology of the Hausdorff leaf spaces (HLS) for a codim-1 foliation is the main topic of this paper. At the beginning, the connection between the Hausdorff leaf space and a warped foliations is examined. Next, the author describes the HLS for all basic constructions of foliations such as transversal and tangential gluing, spinning, turbulization, and suspension. Finally, it is shown that the HLS for any codim-1 foliation on a compact Riemannian manifold is isometric to a finite connected metric graph. In addition, the author proves that for any finite connected metric graph G there exists a compact foliated Riemannian manifold (M,F,g) with codim-1 foliation such that the Hausdorff leaf space for F is isometric to G. Finally, the necessary and sufficient condition for warped foliations of codim-1 to converge to HLS(F) is given.
An algorithm for finding signals of unknown length in DNA sequences

Pattern discovery in unaligned DNA sequences is a challenging problem in both computer science and molecular biology. Several different methods and techniques have been proposed so far, but in most of the cases signals in DNA sequences are very complicated and avoid detection. Exact exhaustive methods can solve the problem only for short signals with a limited number of mutations. In this work, we extend exhaustive enumeration also to longer patterns. More in detail, the basic version of algorithm presented in this paper, given as input a set of sequences and an error ratio epsilon < 1, finds all patterns that occur in at least q sequences of the set with at most epsilonm mutations, where m is the length of the pattern. The only restriction is imposed on the location of mutations along the signal. That is, a valid occurrence of a pattern can present at most [epsiloni] mismatches in the first i nucleotides, and so on. However, we show how the algorithm can be used also when no assumption can be made on the position of mutations. In this case, it is also possible to have an estimate of the probability of finding a signal according to the signal length, the error ratio, and the input parameters. Finally, we discuss some significance measures that can be used to sort the patterns output by the algorithm.
Pipelined compressor tree optimization using integer linear programming

Compressor trees offer an effective realization of the multiple input addition needed by many arithmetic operations. However, mapping the commonly used carry save adders (CSA) of classical compressor trees to FPGAs suffers from a poor resource utilization. This can be enhanced by using generalized performance counters (GPCs). Prior work has shown that high efficient GPCs can be constructed by exploiting the low-level structure of the FPGA. However, due to their irregular shape, the selection of those is not straight forward. Furthermore, the compressor tree has to be pipelined to achieve the potential FPGA performance. Then, a selection between registered GPCs or flip-flops has to be done to balance the pipeline. This work defines the pipelined compressor tree synthesis as an optimization problem and proposes a (resource) optimal method using integer linear programming (ILP). Besides that, two new GPC mappings with high efficiency are proposed for Xilinx FPGAs.
Motivations and Usage Patterns on Social Network Sites

Social network sites count millions of members these days. For a growing number of Internet users, maintaining a profile on a social network site is part of their everyday life today. The debate of the social use of the Internet has focused on the one hand, on whether persons establish new relationships online and, on the other hand, on how persons use the Internet to maintain relationships. Social network sites explicitly aim at supporting people in both aspects. The number of members shows their success, but do social network sites really afford the maintenance of existing and establishment of new contacts? As yet, there has been no systematic investigation of the motivations and usage patterns on social network sites. This study lays the groundwork describing the social networks displayed as well as the perceptions members have of the displayed connections between others. Furthermore, the frequency, motivations and outcome of the creation of links to yet unknown persons are investigated. Participants of a German SNS were surveyed with an online questionnaire. The results show rather small networks which consist of both work and private contacts suggesting a substantial overlap with the offline networks. Regarding new links, over half of the users have added an as yet unknown person to their contact list, but many of new relationships do not develop further.
Mechanical Approaches Combined With Intra-Arterial Pharmacological Therapy Are Associated With Higher Recanalization Rates Than Either Intervention Alone in Revascularization of Acute Carotid Terminus Occlusion

Background and Purpose— Acute stroke attributable to internal carotid artery terminus occlusion carries a poor prognosis. Vessel recanalization is crucial to improve clinical outcome. Historically, pharmacological thrombolysis alone has low recanalization rates. We sought to determine whether adjunctive mechanical approaches achieve better vessel recanalization and functional outcome. Methods— We retrospectively reviewed 75 consecutive endovascular cases of acute internal carotid artery terminus occlusions treated at our center between 1998 and 2008. Mechanical approaches (MERCI retrieval/angioplasty/stent) with and without adjunctive intra-arterial pharmacological therapy (urokinase or tissue plasminogen activator) was compared to intra-arterial lytics alone. Univariate and multivariate analyses were performed to determine predictors of recanalization (thrombolysis in myocardial infarction grades 2 to 3) and favorable functional outcome (modified Rankin score ≤2) at 3 months. Results— Lowest recanalization rates were observed with intra-arterial lytics alone (3/17, 17.6%). MERCI embolectomy combined with intra-arterial lytics was associated with the highest recanalization rates (18/21, 85.7%; P<0.0001). MERCI embolectomy alone achieved 46.2% recanalization rates (6/13; P=0.23). Angioplasty or stenting and intra-arterial lytics achieved 25% (2/8; P=0.65) and 40% (4/10; P=0.085) recanalization, respectively. In multivariate analysis, combination of MERCI embolectomy with intra-arterial lytics (OR, 16.2; CI, 4.6–77.6), or any mechanical technique with intra-arterial lytics (OR, 6.7; CI, 2.5–19.5) independently predicted thrombolysis in myocardial infarction 2 to 3 recanalization. Clinically significant parenchymal hemorrhage rates were 7.5% with combination (3/38) and 12.5% with pharmacological therapies (2/16; P=0.46). Using stepwise logistic regression, age (OR, 0.95; CI, 0.90–0.995), baseline NIHSS (OR, 0.82; CI, 0.70–0.96), and thrombolysis in myocardial infarction 2 to 3 recanalization (OR, 4.0; CI, 1.1–14.4) were associated with favorable functional outcome. Conclusions— Combined mechanical and intra-arterial pharmacological therapy is associated with higher recanalization rates than either intervention alone in acute internal carotid artery terminus occlusion revascularization.
Complete Sequence and Molecular Epidemiology of IncK Epidemic Plasmid Encoding bla CTX-M-14

the 21st century with the emergence of resistant bacterial strains worldwide. Transferable resistance to β-lactam antimicrobial drugs, mediated by production of extendedspectrum β-lactamases (ESBLs), is of particular concern. In 2004, an ESBL-carrying IncK plasmid (pCT) was isolated from cattle in the United Kingdom. The sequence was a 93,629-bp plasmid encoding a single antimicrobial drug resistance gene, blaCTX-M-14. From this information, PCRs identifying novel features of pCT were designed and applied to isolates from several countries, showing that the plasmid has disseminated worldwide in bacteria from humans and animals. Complete DNA sequences can be used as a platform to develop rapid epidemiologic tools to identify and trace the spread of plasmids in clinically relevant pathogens, thus facilitating a better understanding of their distribution and ability to transfer between bacteria of humans and animals.
First Order Learning, Zeroth Order Data

The augmentation of FOIL to include the handling of data with continuous variables and data with missing values enables it to be applied to a wider range of problems, including conventional attribute-value classiication problems. This paper reports the results of experiments applying this variant of FOIL to such problems in two ways: restricting theories to the conventional form in which each test involves a single attribute, and allowing an extended range of tests in which one attribute is compared to another. The experiments indicate that both kinds of learning are computationally practical by comparison with C4.5rules and that there is little diierence in accuracy on the domains tried. It thus appears that FOIL has a broad range of potential applicability, but no great advantage on zeroth order learning tasks.
Alliances, Assemblages, and Affects: Three Moments of Building Collective Working-Class Literacies

This article explores how assemblage and affect theories can enable research into the formation of a collective working-class identity, inclusive of written, print, publication, and organizational literacies through the origins of the Federation of Worker Writer and Community Publishers, an organization that expanded its collectivity as new heritages, ethnicities, and immigrant identities altered the organization’s membership and “class” identity.
Achieving Participant Acceptance of their Avatars

An experiment was carried out to examine the extent to which an avatar can be perceived by people as similar to themselves, including their face and body. The avatar was judged by the participants themselves rather than by third parties. The experiment was organized in two phases. The initial phase consisted of a forced-choice, paired comparison method used to create a ranking of 10 virtual faces in order of preference. This set of faces included a facial mesh, created by a custom software pipeline to rapidly generate avatars that resembled the experimental participants. Six more faces, derived from the participants' own face, were also shown in order to gain insight into the acceptance of a variety of facial similarities. In the second phase, full-body avatars with the most and least preferred faces were presented along with the direct pipeline output. Participants rated their level of satisfaction with those avatars as virtual self-representations and provided the level of perceived resemblance to themselves. The results show that our avatars are perceived to be similar to the self, rated at 7.5/10. Those avatars with faces derived from the participants' face mixed with an ethnically similar face were also rated with high scores. These results differ significantly from how arbitrary avatars are perceived. Therefore, reasonably physically similar avatars can also be expected to be perceived as similar by participants.
Recent Transmission of a Novel Alphacoronavirus, Bat Coronavirus HKU10, from Leschenault's Rousettes to Pomona Leaf-Nosed Bats: First Evidence of Interspecies Transmission of Coronavirus between Bats of Different Suborders

ABSTRACT Although coronaviruses are known to infect various animals by adapting to new hosts, interspecies transmission events are still poorly understood. During a surveillance study from 2005 to 2010, a novel alphacoronavirus, BatCoV HKU10, was detected in two very different bat species, Ro-BatCoV HKU10 in Leschenault's rousettes (Rousettus leschenaulti) (fruit bats in the suborder Megachiroptera) in Guangdong and Hi-BatCoV HKU10 in Pomona leaf-nosed bats (Hipposideros pomona) (insectivorous bats in the suborder Microchiroptera) in Hong Kong. Although infected bats appeared to be healthy, Pomona leaf-nosed bats carrying Hi-BatCoV HKU10 had lower body weights than uninfected bats. To investigate possible interspecies transmission between the two bat species, the complete genomes of two Ro-BatCoV HKU10 and six Hi-BatCoV HKU10 strains were sequenced. Genome and phylogenetic analyses showed that Ro-BatCoV HKU10 and Hi-BatCoV HKU10 represented a novel alphacoronavirus species, sharing highly similar genomes except in the genes encoding spike proteins, which had only 60.5% amino acid identities. Evolution of the spike protein was also rapid in Hi-BatCoV HKU10 strains from 2005 to 2006 but stabilized thereafter. Molecular-clock analysis dated the most recent common ancestor of all BatCoV HKU10 strains to 1959 (highest posterior density regions at 95% [HPDs], 1886 to 2002) and that of Hi-BatCoV HKU10 to 1986 (HPDs, 1956 to 2004). The data suggested recent interspecies transmission from Leschenault's rousettes to Pomona leaf-nosed bats in southern China. Notably, the rapid adaptive genetic change in BatCoV HKU10 spike protein by ∼40% amino acid divergence after recent interspecies transmission was even greater than the ∼20% amino acid divergence between spike proteins of severe acute respiratory syndrome-related Rhinolophus bat coronavirus (SARSr-CoV) in bats and civets. This study provided the first evidence for interspecies transmission of coronavirus between bats of different suborders.
Pyramidal Watershed Segmentation Algorithm for High-resolution Remote Sensing Images Using Discrete Wavelet Transforms

The watershed transformation is a useful morphological segmentation tool for a variety of grey-scale images. However, over segmentation and under segmentation have become the key problems for the conventional algorithm. In this paper, an efficient segmentation method for high-resolution remote sensing image analysis is presented. Wavelet analysis is one of the most popular techniques that can be used to detect local intensity variation and hence the wavelet transformation is used to analyze the image. Wavelet transform is applied to the image, producing detail horizontal, vertical, and diagonal and Approximation coefficients. The image gradient with selective regional minima is estimated with the grey-scale morphology for the Approximation image at a suitable resolution, and then the watershed is applied to the gradient image to avoid over segmentation. The segmented image is projected up to high resolutions using the inverse wavelet transform. The watershed segmentation is applied to small subset size image, demanding less computational time. We have applied our new approach to analyze remote sensing images. The algorithm was implemented in MATLAB. Experimental results demonstrated the method to be effective.
Distinguishing between Heterogeneity and Inefficiency: Stochastic Frontier Analysis of the World Health Organization S Panel Data on National Health Care Systems

The most commonly used approaches to parametric (stochastic frontier) analysis of efficiency in panel data, notably the fixed and random effects models, fail to distinguish between cross individual heterogeneity and inefficiency. This blending of effects is particularly problematic in the World Health Organization's (WHO) panel data set on health care delivery, which is a 191 country, 5-year panel. The wide variation in cultural and economic characteristics of the worldwide sample produces a large amount of unmeasured heterogeneity in the data. This study examines several alternative approaches to stochastic frontier analysis with panel data, and applies some of them to the WHO data. A more general, flexible model and several measured indicators of cross country heterogeneity are added to the analysis done by previous researchers. Results suggest that there is considerable heterogeneity that has masqueraded as inefficiency in other studies using the same data.
Toward Mixed-Initiative Email Clustering

Organizing data into hierarchies is natural for humans. However, there is little work in machine learning that explores human-machine mixed-initiative approaches to organizing data into hierarchical clusters. In this paper we consider mixed-initiative clustering of a user’s email, in which the machine produces (initial and retrained) hierarchical clusterings of email, and the user reviews and edits the initial hierarchical clustering, providing constraints on the re-trained clustering model. Key challenges include (a) determining types of feedback that users will find natural to provide, (b) developing hierarchical clustering and retraining algorithms capable of accepting these types of user feedback, (c) understanding how machine’s clustering results and user feedback affect each other.
The State of the Art in Topology‐Based Visualization of Unsteady Flow

Vector fields are a common concept for the representation of many different kinds of flow phenomena in science and engineering. Methods based on vector field topology are known for their convenience for visualizing and analysing steady flows, but a counterpart for unsteady flows is still missing. However, a lot of good and relevant work aiming at such a solution is available. We give an overview of previous research leading towards topology‐based and topology‐inspired visualization of unsteady flow, pointing out the different approaches and methodologies involved as well as their relation to each other, taking classical (i.e. steady) vector field topology as our starting point. Particularly, we focus on Lagrangian methods, space–time domain approaches, local methods and stochastic and multifield approaches. Furthermore, we illustrate our review with practical examples for the different approaches.