Miracle-dz/UniFAR-FTUs huggingface dataset:
Single-unit recording and stimulation in superior colliculus of the alert rhesus monkey.

RECENT SINGLE-UNIT recording studies of the alert rhesus monkey superior colliculus have disclosed that the deeper layers of this structure contain cells which discharge in association with eye movement (15-17, 23, 24). Such units fire selectively prior to saccades of a specific direction and size, irrespective of the position of the eye in orbit. Stimulation studies of the superior colliculus have so far produced conflicting results. Some reports suggest that in the alert cat stimulation brings the eye to a certain position in orbit irrespective of eye position prior to stimulation (1, 9, 19). Thus, the size and direction of elicited saccades is reported to vary as a function of initial eye position. By contrast, in the alert monkey it has recently been reported that stimulation produces conjugate saccades of a specific size and direction; these parameters are the same no matter where the eye is in the orbit prior to stimulation (12, 15, 16). The stimulation map of Robinson (12) shows a reasonable correspondence with the receptive-field map of the superior colliculus reported by Cynader and Berman (5). The aim of this study was to clarify the relationship between recording and stimulation data by using methods which allow a direct comparison. We used alert rhesus monkeys which had one eye immobilized for the mapping of visual receptive fields. The other eye was normal, thus permitting the study of eye movement. Stimulation and recording were carried out using the same low-resistance microelectrode; for each site sampled, records were obtained for both single-unit activity and for electrical stimulation.
Towards a Better Understanding of the Effect of Reverberation on Speech Recognition Performance

In order to tailor dereverberation approaches to automatic speech recognition (ASR) systems, it is important to thoroughly understand the effect of reverberation on ASR performance. In this work, the effect is analyzed by varying the shape of the room impulse response (RIR) using two design parameters that are useful for defining the target response of typical dereverberation algorithms. The parameters determine the amount of attenuation of the coefficients that correspond to reflections arriving with at least a delay of T after the direct-path component. By convolving clean speech signals with the modified RIRs, ideal late-reverberation suppression is simulated. By varying the level of attenuation A and the delay T , the influence of these design parameters on the recognition rates is investigated. Thus, guidelines for adjusting dereverberation algorithms to ASR systems are deduced.
Combining Alignment Results for Historical Handwritten Document Analysis

In this paper we propose a new strategy for combining the outputs of several alignment systems. Based on the word boundaries retrieved from a number of individual alignment systems, the new boundaries are estimated. We investigate three strategies for this estimation. First, the mean value of the individual boundaries is taken, second the median is selected, and third, confidence values of the alignment systems are considered. We apply the combination strategies on a word mapping system for historical handwritten manuscripts. After some preprocessing and normalizing steps, three differently trained hidden Markov model based handwriting recognizers are applied to the text lines in forced alignment mode. As a result, the positions of the word boundaries are obtained. In in a number of experiments it is shown that a combination strategy based on the median outperforms the others and all individual alignment systems with a word mapping rate of about 95%.
Getting more data - Schoolkids as annotators

We present a new way to get more morphologically and syntactically annotated data. We have developed an annotation editor tailored to school children to involve them in text annotation. Using this editor, they practice morphology and dependency-based syntax in the same way as they normally do at (Czech) schools, without any special training. Their annotation is then automatically transformed into the target annotation schema. The editor is designed to be language independent, however the subsequent transformation is driven by the annotation framework we are heading for. In our case, the object language is Czech and the target annotation scheme corresponds to the Prague Dependency Treebank annotation framework.
SemFilter: A Simple and Efficient Semantic Filtering of XML Messages

Until now, most researches for XML message filtering have focused on the efficient and scalable path matching of a large number of XPath queries over a continuous XML data stream. However, we think there is another key problem of the semantic interoperability of subscribed XPath queries against heterogeneous data sources. Recent studies only assume that the filtering system maintains a single global schema covering all data sources, or the data sources follow the defined global schema. However, beyond the simple assumption, the data sources can have various different element tag structures and names, although related with a similar subject. Therefore, the path expression of a subscribed query against a specific data source cannot be matched with other data sources that have semantically the same information. In order to resolve this problem, a query translation method rewriting the subscribed path expression into one corresponding to each data source is required. In this paper, we introduce the problem of semantic interoperability in XML message filtering and suggest a novel query translation method.
Paying Interest on Reserve Balances: It's More Significant than You Think

It has long been recognized that uncompensated reserve balances act like a tax on banks and that banks as a result expend scarce resources to avoid holding them. The Fed itself has historically supported legislation to enable it to pay interest on reserve balances (e.g., Kohn 2003), as have economists (e.g., Goodfriend 2002), both for reasons of economic efficiency and to improve the implementation of monetary policy. The traditional argument against interest payment has been that it would reduce the Fed’s earnings that are subsequently turned over to the Treasury (Feinman 1993b; Abernathy 2003). The purpose of this paper is to demonstrate the implications of paying interest on reserve balances on the daily operations of both the Fed and the Treasury. While the arguments here - for different reasons - generally are in favor of enabling the Fed to pay interest on reserve balances, more important than the actual payment of such interest is the perspective gained when considering in detail the operations of both in an environment where reserve balances earn interest.
On Implementing Sparse Matrix Multi-vector Multiplication on GPUs

Sparse matrix-vector and multi-vector multiplications (SpMV and SpMM) are performance bottlenecks operations in numerous HPC applications. A variety of SpMV GPU kernels using different matrix storage formats have been developed to accelerate these applications. Unlike SpMV, where matrix elements are accessed only once, multiplying by k vectors requires accessing matrix elements k times. In this paper we explore the design of efficient GPU SpMM kernels that exploit two common matrix sparsity patterns, diagonal matrices and matrices with uniform row lengths. Our kernels use GPU registers to exploit the potential data reuse in SpMM. For evaluating the performance of our SpMM kernels we use 28 structured matrices and 29 matrices with uniform row lengths. Executing on the NVIDIAs Kepler-based Tesla K20 GPU and for structured grid matrices, the average speedup over the best performing state of the art SpMV kernel including NVIDIA's kernels is 2.3x and the maximum is 4.6x. For unstructured mesh matrices, the average speedup is 2.6x and the maximum is 4.1x. Compared to NVIDIA's cuSPARSE SpMM kernel the average speedup is 1.8x and the maximum is 2.4x for structured grid matrices. For unstructured mesh matrices, the average speedup is 1.5x and the maximum is 2.6x.
Preload — An Adaptive Prefetching Daemon

Preload — An Adaptive Prefetching Daemon Behdad Esfahbod Master of Science Graduate Department of Computer Science University of Toronto 2006 In this thesis we develop preload, a daemon that prefetches binaries and shared libraries from the hard disk to main memory on desktop computer systems, to achieve faster application start-up times. Preload is adaptive: it monitors applications that the user runs, and by analyzing this data, predicts what applications she might run in the near future, and fetches those binaries and their dependencies into memory. We build a Markov-based probabilistic model capturing the correlation between every two applications on the system. The model is then used to infer the probability that each application may be started in the near future. These probabilities are used to choose files to prefetch into the main memory. Special care is taken to not degrade system performance and only prefetch when enough resources are available. Preload is implemented as a user-space application running on Linux 2.6 systems.
Predicting Product Aesthetic Quality Using Virtual Environments

This paper describes a previously unreported application of virtual environments, the prediction of product aesthetic quality. Successful prediction of aesthetic quality without the production of a physical prototype requires the integration of a number of 'software' models: an assembly model representing the manner in which the product is put together; an environment model providing a real world graphical context for the product; a behavior model representing how the product moves and deforms under use conditions; and a tolerance model representing the allowable variation in the product due to manufacturing variation. This paper presents the results of applying these models within an automotive design and manufacturing process during the development of a new automobile.
An Analysis of the Earnings of Canadian Immigrants

This paper reports estimates of simple wage equations fit to cross-sectional and pseudo-longitudinal data for Canadian immigrants in the 1971 and 1981 Canadian censuses. The estimates are used to assess (1) the usefulness of cross-sectional analyses for measuring the pace of immigrant earnings growth, (2) the labor market implications of admissions policies that place different weights on the work skills possessed by prospective entrants, and (3) the relative impact of selective outmigration and job-matching on the shape of immigrant earnings distributions as duration of stay increases. The estimates provide evidence of a small to moderate assimilation effect that suggests that immigrants make up for relatively low entry wages, although the wage catch-up is not complete until 13 to 22 years after entry into Canada. These results are revealed clearly in both the pseudo-longitudinal and the cross-sectional analyses. The estimates also provide evidence that the unobserved quality of immigrants' labor market skills declined following changes in Canada's immigration policies in 1974 that led to a sharp increase in the proportion of immigrants admitted on the basis of family ties. Finally, since there is no evidence that the variance of immigrant earnings increases with their duration of stay in Canada, and since there are no differential immigrant-native changes in higher-order moments of the earnings distribution as duration of stay increases, the results are inconclusive with respect to the importance of selective outmigration and job matching in the evolution of immigrant earnings distributions over time.
Visibility Enhancement of Single Hazy Images Using Hybrid Dark Channel Prior

Outdoor images captured during inclement weather conditions generally exhibit visibility degradation. Localized light sources often result from activation of streetlights and vehicle headlights and are common scenarios in these conditions. The presence of localized light sources in hazy images may cause the generation of over saturation artifacts when those images are restored by traditional state-of-the-art haze removal techniques. Therefore, we propose a novel haze removal approach based on the proposed hybrid dark channel prior technique in order to remedy the problems associated with localized light sources during image restoration. The overall results show that the proposed haze removal approach can recover haze-free images more effectively than can the other previous state-of-the-art haze removal approach while avoiding over-saturation.
HIGH DEFINITON TECHNOLOGY:A REVIEW

This is a review paper describing the characteristics and benefits of high definition (HD) technology. Digital techniques offer greater accuracy and stability, with better signal to noise ratios than analogue method. Here the overview of High Definition is presented; basic terminology, working, fundamentals, applications and future of this technology are listed. The scanning methods have been explained also software and hardware architecture is mentioned. The analysis of the current HD market and a commercial survey of the HD services and its providers have been carried out. Then the future of High Definition is considered with new research directions. If we narrow down the issue to a single parameter, that of resolution, aside from possible future displays that are integer multiples of 1920 x 1080 serving to diminish pixel structure then, claims of “live-the-picture” and “feelthe-picture” would become a reality.
Extending the visual field of a head-mounted eye tracker for pervasive eye-based interaction

Pervasive eye-based interaction refers to the vision of eye-based interaction becoming ubiquitously usable in everyday life, e. g. across multiple displays in the environment. While current head-mounted eye trackers work well for interaction with displays at similar distances, the scene camera often fails to cover both remote and close proximity displays, e. g. a public display on a wall and a handheld portable device. In this paper we describe an approach that allows for robust detection and gaze mapping across multiple such displays. Our approach uses an additional scene camera to extend the viewing and gaze mapping area of the eye tracker and automatically switches between both cameras depending on the display in view. Results from a pilot study show that our system achieves a similar gaze estimation accuracy to a single-camera system while at the same time increasing usability.
A Systematic Review of Trauma-Focused Interventions for Domestic Violence Survivors

Intimate partner violence (IPV) is a form of trauma that can result in significant mental health distress for victims. Rates of clinical depression and posttraumatic stress disorder are higher among abused versus non-abused women, particularly if victims have experienced other lifetime trauma. While there are numerous interventions designed to reduce trauma-induced mental health symptoms, most were originally developed to address events that have occurred in the past (e.g., combat, childhood sexual abuse). Many IPV survivors are still under threat of ongoing abuse or stalking, which not only directly impacts their physical and psychological safety but impacts treatment options, as well. Little is known about the extent to which existing evidence-based trauma treatment modalities are applicable to, or require modification for, IPV survivors. This paper, then, reviews the trauma-based treatments that have been designed or modified specifically for IPV survivors and provides cautions and recommendations for moving forward. 2 shorter in duration and less severe and they have access to resources and support (Bonanno, 2004). Others, particularly those who experience more frequent or severe abuse, may develop symptoms that make daily functioning more difficult. Ongoing abuse and violence can induce feelings of shock, disbelief, confusion, terror, isolation, and despair, and can undermine a person's sense of self. These, in turn, can manifest as psychiatric symptoms (e.g., reliving the traumatic event, hyperarousal, avoiding reminders of the trauma, depression, anxiety, and sleep disruption). Some trauma survivors experience one or more of these symptoms for a brief period of time, while others develop chronic posttraumatic stress disorder (PTSD), a disorder that is a common response to overwhelming trauma and that can persist for years. Survivors are also at risk for developing depression, which has been found to significantly relate to the For those who have also experienced abuse in childhood and/ or other types of trauma (i.e., cumulative trauma), the risk for developing PTSD is elevated (Campbell,
Codepoint Registry for the Flags Field in the Resource Reservation Protocol-Traffic Engineering (RSVP-TE) Session Attribute Object

This document provides instructions to IANA for the creation of a new codepoint registry for the flags field in the Session Attribute object of the Resource Reservation Protocol Traffic Engineering (RSVP-TE) signaling messages used in Multiprotocol Label Switching (MPLS) and Generalized MPLS (GMPLS) signaling. This memo provides information for the Internet community.
Semantic clustering of XML documents

Dealing with structure and content semantics underlying semistructured documents is challenging for any task of document management and knowledge discovery conceived for such data. In this work we address the novel problem of clustering semantically related XML documents according to their structure and content features. XML features are generated by enriching syntactic with semantic information based on a lexical knowledge base. The backbone of the proposed framework for the semantic clustering of XML documents is a data representation model that exploits the notion of tree tuple to identify semantically cohesive substructures in XML documents and represent them as transactional data. This framework is equipped with two clustering algorithms based on different paradigms, namely centroid-based partitional clustering and frequent-itemset-based hierarchical clustering. An extensive experimental evaluation was conducted on real data sets from various domains, showing the significance of our approach as a solution for the semantic clustering of XML documents.
Chapter 15 Object Recognition

An object recognition system finds objects in the real world from an image of the world, using object models which are known a priori. This task is surprisingly difficult. Humans perform object recognition effortlessly and instantaneously. Algorithmic description of this task for implementation on machines has been very difficult. In this chapter we will discuss different steps in object recognition and introduce some techniques that have been used for object recognition in many applications. We will discuss the different types of recognition tasks that a vision system may need to perform. We will analyze the complexity of these tasks and present approaches useful in different phases of the recognition task. The object recognition problem can be defined as a labeling problem based on models of known objects. Formally, given an image containing one or more objects of interest (and background) and a set of labels corresponding to a set of models known to the system, the system should assign correct labels to regions, or a set of regions, in the image. The object recognition problem is closely tied to the segmentation problem: without at least a partial recognition of objects, segmentation cannot be done, and without segmentation, object recognition is not possible. In this chapter, we discuss basic aspects of object recognition. We present the architecture and main components of object recognition and discuss their role in object recognition systems of varying complexity.
H-ARQ-Aided Systematic Luby Transform Codes

Hybrid Automatic-Repeat-Request (H-ARQ) Aided Systematic Luby Transform (SLT) Coded Modulation is proposed, where SLT codes are used both for correcting erroneous bits and for detecting as well as retransmitting erroneous Internet Protocol (IP) based packets. Erroneous IP packet detection is implemented using syndrome checking with the aid of the SLT codes’ Parity Check Matrix (PCM). Optimizing the mapping of SLT-encoded bits to modulated symbols and then using iterative decoding for exchanging extrinsic information between the SLT decoder and the demapper substantially improves the achievable Bit Error Ratio (BER) performance of the scheme. Quantitatively, at Eb/N0 in excess of 3.8 dB, this scheme is capable of achieving a BER 10? 5 and up to 1.5 times higher throughput in comparison to less sophisticated benchmarker schemes such as SLT codes, dispensing with ARQ-assistance or joint SLT coded modulation and H-ARQ-SLT codes, when communicating over AWGN channels, using 16-QAM and a half-rate SLT code.
Fibrinogen but not factor XIII deficiency is associated with bleeding after craniotomy.

BACKGROUND Postoperative haemorrhage in neurosurgery is associated with significant morbidity and mortality. There is controversy whether or not factor XIII (FXIII) deficiency leads to bleeding complications after craniotomy. Decreased fibrinogen levels have been associated with an increased incidence of bleeding complications in cardiac and orthopaedic surgery. The aim of this study was to assess perioperative fibrinogen and FXIII levels in patients undergoing elective intracranial surgery with and without severe bleeding events. METHODS Perioperative FXIII and fibrinogen levels were prospectively assessed in 290 patients undergoing elective craniotomy. Patients were divided into two groups according to the presence or absence of severe bleeding requiring surgical revision. Coagulation test results of these groups were compared using Student's t-test. RESULTS The incidence of postoperative severe bleeding was 2.4%. No differences in FXIII levels were observed, but postoperative fibrinogen levels were significantly lower in patients suffering from postoperative haematoma compared with those without postoperative intracranial bleeding complications [237 mg dl(-1) (standard deviation, SD 86) vs 170 mg dl(-1) (SD 35), P=0.03]. The odds ratio for postoperative haematoma in patients with a postoperative fibrinogen level below 200 mg dl(-1) was 10.02 (confidence interval: 1.19-84.40, P=0.03). CONCLUSIONS This study emphasizes the role of fibrinogen as potentially modifiable risk factor for perioperative bleeding in intracranial surgery. Future randomized controlled trials will be essential to identify patients who might benefit from fibrinogen substitution during neurosurgical procedures.
PIE: A Pipeline Energy-Efficient Accelerator for Inference Process in Deep Neural Networks

It has been a new research hot topic to speed up the inference process of deep neural networks (DNNs) by hardware accelerators based on field programmable gate arrays (FPGAs). Because of the layer-wise structure and data dependency between layers, previous studies commonly focus on the inherent parallelism of a single layer to reduce the computation time but neglect the parallelism between layers. In this paper, we propose a pipeline energy-efficient accelerator named PIE to accelerate the DNN inference computation by pipelining two adjacent layers. Through realizing two adjacent layers in different calculation orders, the data dependency between layers can be weakened. As soon as a layer produces an output, the next layer reads the output as an input and starts the parallel computation immediately in another calculation method. In such a way, computations between adjacent layers are pipelined. We conduct our experiments on a Zedboard development kit using Xilinx Zynq-7000 FPGA, compared with Intel Core i7 4.0GHz CPU and NVIDIA K40C GPU. Experimental results indicate that PIE is 4.82x faster than CPU and can reduce the energy consumptions of CPU and GPU by 355.35x and 12.02x respectively. Besides, compared with the none-pipelined method that layers are processed in serial, PIE improves the performance by nearly 50%.