Miracle-dz/UniFAR-FTUs huggingface dataset:
A Case for Multi-Level Distributed

Most of the distributed recovery schemes proposed in the literature are designed to tolerate arbitrary number of failures, with a few notable exceptions of schemes designed to tolerate single failures. In this report, we demonstrate that, it is often advantageous to use \multi-level" recovery schemes. A \multi-level" recovery scheme is one that can tolerate diierent number of faults at diierent costs, tolerance of larger number of failures requiring larger costs. The costs are incurred during failure-free operation as well as during recovery. To demonstrate the advantages of multi-level recovery, we analyze a hypothetical 2-level recovery scheme that takes two diierent types of checkpoints, namely, 1-checkpoints and N-checkpoints. A single failure can be tolerated by rolling the system back to a 1-checkpoint, while multiple failure recovery is possible by rolling back to an N-checkpoint. The cost of a 1-checkpoint may be expected to be smaller than that of an N-checkpoint. For such a system, we demonstrate that to minimize the average overhead, it is often necessary to take both 1-checkpoints and N-checkpoints. While the conclusions of this report are intuitive, the work on appropriate recovery schemes is lacking. The objective of this report is to motivate research into recovery schemes that can provide multiple levels of fault tolerance.
Coset detection in MIMO systems based on spatial multiplexing

For multiple-input multiple-output (MIMO) spatial multiplexing systems the complexity of the maximum likelihood detector (MLD) can be prohibitively large when the number of transmitting antennas and constellation points is high. To simplify the MLD many linear and nonlinear techniques have been proposed. In this letter the principle of reduced state sequence detection, based on mapping by set partitioning, is applied to perform detection in spatial multiplexing MIMO systems based on non-binary constellations. Simulation results are presented to show the benefits of our proposal. An upper bound to the symbol error probability is also derived.
Does Technology Influence Teaching Practices in the Classroom

INTRODUCTION The world is experiencing an information explosion of unprecedented proportions. Not only is the volume of new information large, but it is also growing exponentially. Rapid changes in many fields are making basic knowledge and skills obsolete. In the technological world of the 21 st century, the meaning of the phrase " to know " means more than simply having information stored in one's memory; it means having access to information and knowing how to use it. The challenge for education is to design technologies for learning that draw both from knowledge about human cognition and from practical application of how technology can facilitate complex tasks in the workplace. " Like training wheels, " computers enable learners to do more advanced activities, and engage in more advanced thinking and problem-solving than they could without such help (Pea, 1985). In this rapidly transforming world, where employment requirements and fundamental literacy expectations are quickly changing, education must also change to meet these demands. The essence of education has been to transmit society's cultural heritage to successive generations and to foster competencies will permit children to successfully participate in a society. To that end, Information technology must become an integral part of the general education curriculum so students are prepared to meet future technology challenges. Many teachers now have access to an unprecedented amount of instructional technology in their classrooms. However, there is little evidence showing that teachers integrate technology within the curriculum on a regular basis. Several factors influence districts' or schools' to focus on hardware rather than the more complex issue of implementation. One reason is a weak implementation and planning process that fails to meet the needs of all teachers and provides little if any time for staff development. Before teachers can successfully implement technology, they need a change in their pedagogy. Such change requires a paradigm shift from viewing their role as a giver of knowledge to a facilitator of knowledge (Dexter, Anderson, & Becker, 1999). Researchers suggest the teacher has been the most important piece that makes learning occur (Soloway, 1996). Teachers have always been responsible for teaching content. With the expansion of Information Highways and technology teachers must
Parkinson's Disease Identification through Deep Optimum-Path Forest Clustering

Approximately 50,000 to 60,000 new cases of Parkinson's disease (PD) are diagnosed yearly. Despite being non-lethal, PD shortens life expectancy of the ones affected with such disease. As such, researchers from different fields of study have put great effort in order to develop methods aiming the identification of PD in its early stages. This work uses handwriting dynamics data acquired by a series of tasks and proposes the application of a deep-driven graph-based clustering algorithm known as Optimum-Path Forest to learn a dictionary-like representation of each individual in order to automatic identify Parkinson's disease. Experimental results have shown promising results, with results comparable to some state-of-the-art approaches in the literature.
Dynamic Lumbosacral Magnetic Resonance Imaging in a Dog with Tethered Cord Syndrome with a Tight Filum Terminale

A 1-year and 11-month- old English Cocker Spaniel was evaluated for clinical signs of progressive right pelvic limb lameness and urinary incontinence. Neurological examination was suggestive of a lesion localized to the L4–S3 spinal cord segments. No abnormalities were seen on magnetic resonance imaging (MRI) performed in the dog in dorsal recumbency and the hips in a neutral position and the conus medullaris ended halfway the vertebral body of L7. An MRI of the hips in extended and flexed positions demonstrated minimal displacement of the conus medullaris in the cranial and caudal directions, respectively. Similar to the images in neutral position, the conus medullaris ended halfway the vertebral body of L7 in both the extended and flexed positions. In comparison, an MRI of the hips in neutral, extended, and flexed positions performed in another English Cocker Spaniel revealed obvious cranial displacement of the conus medullaris with the hips in extension and caudal displacement with hips in flexion. A standard dorsal lumbosacral laminectomy was performed. Visual inspection of the vertebral canal revealed excessive caudal traction on the conus medullaris. After sectioning the distal aspect of the filum terminale, the conus medullaris regained a more cranial position. A neurological examination 4 weeks after surgery revealed clinical improvement. Neurological examinations at 2, 4, 7, and 12 months after surgery did not reveal any abnormalities, and the dog was considered to be clinically normal. Tethered cord syndrome with a tight filum terminale is a very rare congenital anomaly and is characterized by an abnormally short and inelastic filum terminale. Therefore, this disorder is associated with abnormal caudal traction on the spinal cord and decreased physiological craniocaudal movements of the neural structures within the vertebral canal. Although further studies are necessary to evaluate and quantify physiological craniocaudal movement of the spinal cord and conus medullaris in neurologically normal dogs, the results of this report suggest further exploration of dynamic MRI to demonstrate decreased craniocaudal displacement of the conus medullaris in dogs with tethered cord syndrome with a tight filum terminale.
A Pedestrian Multiple Hypothesis Tracker Fusing Head and Body Detections

We present a multiple hypothesis pedestrian tracker for surveillance video that combines head and whole-body detections. The multiple hypothesis tracker deals with ambiguity in track-to-observation matching by maintaining the most likely valid data association hypotheses. Observations are head and body detections from HOG sliding window detectors. The head detector has a high probability of detection and high false alarm rate, whereas for the body detector these probabilities are lower. The two detection types are fused in a probabilistic framework to achieve robust pedestrian tracking in a crowded environment with clutter and partial occlusions. Experiments show that the use of head and body detections along with multiple hypothesis tracking can improve online track-by-detect methods.
Antibacterial Silver Loaded Hydroxyapatite Coating Prepared Through the Reduction of Phytic Acid-Silver Ion Complex

Hydroxyapatite coating was built on the surface of materialsby mineralization of phytic acid-metallic ion complex, whichfurther absorbednbspsurplusnbspphytic acidonnbspthe outer layer.nbspThen, silver ions werenbspstabilizedbased on their chelation with phytic acid.nbspFinally,nbspwe obtained silver-loadednbsphydroxyapatite coatingnbspwhen the silver ions were reducednbspto nano silver particlesnbspunder the effect of glucose.nbspThe successful loading of silver particles were proved bynbspscanning electron microscopy, Raman and EDS measurement.nbspThis coating exhibitednbspbroadnbspantibacterial propertiesnbspagainstnbspEscherichia colinbsp(gram negative bacteria) and Staphylococcus aureus (gram positive bacteria). nbspThenbspantibacterial hydroxyapatite coatingnbspdeveloped here might have potential applications innbspthe area of biomedical, such asnbspbone and dental implant.
Using Memory-style Storage to Support Fault Tolerance in Data Centers

Next-generation nonvolatile memories combine byteaddressability and high performance of memory with nonvolatility of disk/flash. They promise emerging memory-style storage (MSS) systems that are directly attached to the memory bus, offering fast load/store access and data persistence in a single level of storage. MSS can be especially attractive in data centers, where fault tolerance support through storage systems is critical to performance and energy. Yet existing fault tolerance mechanisms, such as logging and checkpointing, are designed for slow block-level storage interfaces; their design choices are not wholly suitable for MSS. The goal of this work is to explore efficient fault tolerance techniques that exploit the fast memory interface and the nature of single-level storage. Our preliminary exploration shows that, by reducing data duplication and increasing application parallelism, such techniques can substantially improve system performance and energy consumption.
A Survey on Real Time Object Detection, Tracking and Recognition in Image Processing

Object detection, tracking and recognition in real time is a very essential task in computer vision. There are lots of research work have been done in this area. Yet it needs to be accuracy in recognizing object. The most objective of this review is to present an overview of the approaches used and also the challenges involved. In this paper we concentrate on different object detection methods, tracking and recognition methods are discussed.
Low-Power 10-Gb/s Transmitter for High-Speed Graphic DRAMs Using 0.18- $\mu\hbox{m}$ CMOS Technology

This brief presents a 10-Gb/s transmitter using a low-power one-stage 8:1 multiplexer. In the proposed transmitter, a differential current-steering output driver with a multiphase multiplexer architecture is used to alleviate speed limitations of the DRAM process. The current-steering output driver reduces the required output swing and increases the bandwidth of the multiplexer. The proposed multiplexer accomplishes not only high-speed operation but also low power dissipation by using a pseudo-nMOS configuration with one-stacked switches and reducing the short-circuit current of the gate driver in the multiplexer. The prototype of the transmitter using a 0.18- μm CMOS technology achieves the power efficiency of 5.69 mW/Gb/s at the data rate of 10 Gb/s.
The role of empathy in promoting change

Abstract Since Rogers identified empathy as an important variable in therapy, it has been found to be a consistent predictor of client change; less clear is how this occurs. The objective in this study was to test a mediation model to determine whether clients' self-reported experience of therapists' empathy contributed to changes in their attachment styles and treatment of self, after 16 weeks of psychotherapy for depression. There was a significant direct relationship between therapists' empathy and outcome and a significant indirect effect, showing that clients' perceptions of therapists' empathy was associated with significant improvement in attachment insecurity and significant decreases in negative self-treatment at the end of therapy as well as reductions on BDI, IIP, DAS and SCL-90-R, GSI, and increases on RSE. The findings suggest that clients' perception of their therapists as empathic is an important mechanism of change in psychotherapy that warrants further investigation.
Fast filtered-x affine projection algorithm for active noise control

An efficient affine projection (AP) algorithm, the filtered-x AP algorithm (FXAP), is presented for multichannel active noise control. This algorithm is based on the filtered-x scheme and uses the fast error vector computation and a recursive method to calculate matrix inversions. The new approach provides a significant saving in computational cost compared with other fast versions of the AP algorithm and a faster convergence speed than the filtered-x LMS (FXLMS). The performance of the FXAP is evaluated in a practical ANC system. The proposed algorithm is specially suitable for real time multichannel ANC applications running on a digital signal processing (DSP) card.
Root canal system in the mesiobuccal root of the maxillary first molar: an in vitro comparison study of computed tomography and histology.

OBJECTIVES The purpose of this study was to investigate a new diagnostic approach to the examination of the canal configuration of the mesiobuccal root of the maxillary first molar. MATERIALS AND METHODS High-resolution computed tomography (CT) was compared with histology in vitro. There were 152 teeth investigated and classified according to Weine and Vertucci. RESULTS CT describes the exact canal configuration, verifying information identical to histology, and thus serving as the "gold standard" in vitro. With regard to canal position, 9 (5.92%) of the teeth examined were Vertucci type 1, 48 (31.58%) were Vertucci type 2, 91 (59.87%) were Vertucci type 4, 1 (0.66%) was Vertucci type 5, 1 (0.66%) was Vertucci type 6. Of the 152 teeth examined, 3 (1.97%) could not be classified using Weine, 2 (1.31%) could not be classified according to either Weine or Vertucci, and no Vertucci types 3, 7 or 8 were identified. CONCLUSIONS CT offers complete information on the number and configuration of root canals. As the root canal configuration of the adult does not change rapidly, CT investigations can be used for multiple subsequent treatments.
The role of "hierarchy" in the design of fuzzy logic controllers

This paper investigates the role of hierarchy in the systematic approach to the design of fuzzy logic controllers (FLC's). The key concept here is that the implementation of fuzzy engines at higher levels of the control hierarchy (where more reasoning is involved) yields more versatile fuzzy controllers with generally fewer control rules. At the same time, the structured nature of a hierarchical approach considerably simplifies the design procedure.
How Good Can the Characteristic Polynomial Be for Correlations?

The aim of this study was to investigate the characteristic polynomials resulting from the molecular graphs used as molecular descriptors in the characterization of the properties of chemical compounds. A formal calculus method is proposed in order to identify the value of the characteristic polynomial parameters for which the extremum values of the squared correlation coefficient are obtained in univariate regression models. The developed calculation algorithm was applied to a sample of nonane isomers. The obtained results revealed that the proposed method produced an accurate and unique solution for the best relationship between the characteristic polynomial as molecular descriptor and the property of interest.
A Recent Trend in Individual Counting Approach Using Deep Network

In video surveillance scheme, counting individuals is regarded as a crucial task. Of all the individual counting techniques in existence, the regression technique can offer enhanced performance under overcrowded area. However, this technique is unable to specify the details of counting individual such that it fails in locating the individual. On contrary, the density map approach is very effective to overcome the counting problems in various situations such as heavy overlapping and low resolution. Nevertheless, this approach may break down in cases when only the heads of individuals appear in video scenes, and it is also restricted to the feature’s types. The popular technique to obtain the pertinent information automatically is Convolutional Neural Network (CNN). However, the CNN based counting scheme is unable to sufficiently tackle three difficulties, namely, distributions of non-uniform density, changes of scale and variation of drastic scale. In this study, we cater a review on current counting techniques which are in correlation with deep net in different applications of crowded scene. The goal of this work is to specify the effectiveness of CNN applied on popular individuals counting approaches for attaining higher precision results.
School Programs and Characteristics and Their Influence on Student BMI: Findings from Healthy Passages

Background Little is known about the contribution of school contextual factors to individual student body mass index (BMI). We set out to determine if school characteristics/resources: (1) are associated with student BMI; (2) explain racial/ethnic disparities in student BMI; and (3) explain school-level differences in student BMI. Methods Using gender-stratified multi-level modeling strategies we examined the association of school characteristics/resources and individual BMI in 4,387 5th graders in the Healthy Passages Longitudinal Study of Adolescent Health. Additionally, we examined the association of race/ethnicity and individual BMI as well as the between-school variance in BMI before and after adding individual and school characteristics to test for attenuation. Results The school-level median household income, but not physical activity or nutrition resources, was inversely associated with female BMI (β = −0.12, CI: −0.21,−0.02). Neither school demographics nor physical activity/nutrition resources were predictive of individual BMI in males. In Black females, school characteristics attenuated the association of race/ethnicity and BMI. Individual student characteristics—not school characteristics/resources-reduced the between-school variation in BMI in males by nearly one-third and eliminated it in females. Conclusions In this cohort of 5th graders, school SES was inversely associated with female BMI while school characteristics and resources largely explained Black/White disparities in female weight status. Between-school differences in average student weight status were largely explained by the composition of the student body not by school characteristics or programming.
View composition for digital libraries

We propose a novel visual interface for digital libraries, which employs a collection of views and a compositional mechanism of views. While the views capture and visualize specific aspects of digital libraries, their compositions can be utilized to give deeper and richer insights into a set of retrieved data. Two types of compositions-superimposition and neighboring-of views are introduced. Some mathematical properties and functions associated with view composition are also described.
The continuous distributed monitoring model

In the model of continuous distributed monitoring, a number of observers each see a stream of observations. Their goal is to work together to compute a function of the union of their observations. This can be as simple as counting the total number of observations, or more complex non-linear functions such as tracking the entropy of the induced distribution. Assuming that it is too costly to simply centralize all the observations, it becomes quite challenging to design solutions which provide a good approximation to the current answer, while bounding the communication cost of the observers, and their other resources such as their space usage. This survey introduces this model, and describe a selection results in this setting, from the simple counting problem to a variety of other functions that have been studied.
Naturalistic driving study of rear seat child occupants: Quantification of head position using a Kinect™ sensor

ABSTRACT Objective: Restraint performance is evaluated using anthropomorphic test devices (ATDs) positioned in prescribed, optimal seating positions. Anecdotally, humans—children in particular—assume a variety of positions that may affect restraint performance. Naturalistic driving studies (NDSs), where cameras and other data acquisition systems are placed in a vehicle used by participants during their regular transportation, offer means to collect these data. To date, these studies have used conventional video and analysis methods and, thus, analyses have largely been qualitative. This article describes a recently completed NDS of child occupants in which their position was monitored using a Kinect sensor to quantify their head position throughout normal, everyday driving trips. Methods: A study vehicle was instrumented with a data acquisition system to measure vehicle dynamics, a set of video cameras, and a Kinect sensor providing 3D motion capture at 1 Hz of the rear seat occupants. Participant families used the vehicle for all driving trips over 2 weeks. The child occupants' head position was manually identified via custom software from each Kinect color image. The 3D head position was then extracted and its distribution summarized by seat position (left, rear, center) and restraint type (forward-facing child restraint system [FFCRS], booster seat, seat belt). Results: Data from 18 families (37 child occupants) resulted in 582 trips (with children) for analysis. The average age of the child occupants was 45.6 months and 51% were male. Twenty-five child occupants were restrained in FFCRS, 9 in booster seats, and 3 in seat belts. As restraint type moved from more to less restraint (FFCRS to booster seat to seat belt), the range of fore–aft head position increased: 218, 244, and 340 mm on average, respectively. This observation was also true for left–right movement for every seat position. In general, those in the center seat position demonstrated a smaller range of head positions. Conclusions: For the first time in a naturalistic setting, the range of head positions for child occupants was quantified. More variability was observed for those restrained in booster seats and seat belts than for those in FFCRS. The role of activities, in particular interactions with electronic devices, on head position was notable; this will be the subject of further analysis in other components of the broader study. These data can lead to solutions for optimal protection for occupants who assume positions that differ from prescribed, optimal testing positions.
Least-squares migration of incomplete data sets with regularization in the subsurface-offset domain

In general, in one aspect, the disclosure describes storing identification of one or more memory buckets associated with different, respective, queued write commands, and, based on the stored identification, determining whether at least one bucket associated with a read command is included in one or more buckets associated with at least one queued write command.