Miracle-dz/UniFAR-FTUs huggingface dataset:
A Sparse and Inlier Based SIFT and SURF Features for Automated Face Recognition

Face Recognition (FR) is a prolific form of biometric that has spawned a myriad of inventive applications for commercial and law-enforcement scenarios and has fostered several novel research directions. In the FR process, the choice of the feature extractor governs the overall efficiency and in that regard, SIFT and SURF are two prominent feature extraction mechanisms that are frequently employed due to their robustness with respect to scale, translation, illumination and rotation. Even though the SIFT and SURF descriptors are immensely effective, they are cluttered with redundant key-points and noise, which we aim to tackle by employing the Sparse Singular Value Decomposition (SSVD) method to perform Dimensionality Reduction, and RANSAC to remove noise in the form of outliers. In this paper, we will conclusively demonstrate by utilizing extensive mathematical arguments, and by performing exhaustive experimentations over the benchmark ORL and LFPW databases, that the proposed SIFT-SSVD-RANSAC and SURF-SSVD-RANSAC methodologies are more effective than their classical counterparts, as they are capable of handling extreme variations between the matched images in terms of scale, zoom, view-point and so on. The findings proffered by this work, coupled with our other studies, form a series intended to aid developers in making prudent decisions in order to build proficient FR systems.
A Study on Augmented Reality Application in Situational Simulation Learning

In recent years, hardware and software advances in digital technology have prompted not only the commercial use of augmented reality (AR) systems, but its implementation in education. Marker-based AR systems allow users to input pre-designed markers, and generate new scenes blending together the real world and computer-generated 3D images. Nevertheless, few AR systems permit simultaneous interactions of multiple markers. This study aims to construct an interactive multimedia learning system. The story script showcases the growth of flowers by applying a series of markers, where interactions with 3D objects can be achieved through AR technology. Learners can use a camera to capture the information of multiple AR markers, and 3D objects and media can be generated on-screen. With variations in AR markers, and time changes of the Arduino Clock, one can learn the growth of plants during day and night through a mixed-reality virtual experience that brings fun to learning. Accordingly, this e-learning system is capable of boosting students' learning interests and improving their learning effectiveness.
Averaged large signal model of boost power factor corrector in boundary conduction mode

A modeling approach of a power factor correction circuit operating in boundary conduction mode is presented. The PFC is controlled by a constant on-time of the switch. The effect of valley switching is simplified and taken into account as dead-time to generate a large signal model. On the basis a small signal model for the constant on-time controlled PFC voltage loop is derived. The large and small signal models are compared to measurements of the transfer function. For performing this low frequency transfer functions measurement a set-up using an oscilloscope and functional generator is described.
General properties of overlap probability distributions in disordered spin systems. Towards Parisi ultrametricity

For a very general class of probability distributions in disordered Ising spin systems, in the thermodynamical limit, we prove the following property for overlaps among real replicas. Consider the overlaps among s replicas. Add one replica s + 1. Then, the overlap between one of the first s replicas, let us say a, and the added s + 1 is either independent of the former ones, or it is identical to one of the overlaps , with b running among the first s replicas, excluding a. Each of these cases has equal probability .
AutoPilot: message passing parallel programming for a cache incoherent embedded manycore processor

The Renesas Electronics IMAPCAR2 embedded realtime image processor combines a single core with a 128-way SIMD array. At runtime, sections of the SIMD array can be reconfigured as additional CPU cores, interconnected via a message ring. Effective use is made difficult by the low-level message passing API and lack of cache coherency between processors. The AutoPilot library addresses this by providing a high-level message-oriented parallel programming model mirroring that of Pilot, itself a wrapper around the Message Passing Interface (MPI) for cluster computing. AutoPilot shows that Pilot's processes-and-channels architecture is a viable choice for parallel programming on cache-incoherent multicore and manycore architectures. It provides a simpler API for programmers, with built-in safety checks that eliminate some common sources of errors. Since the IMAPCAR2 is targeted chiefly at automotive applications, open source AutoPilot has a large degree of MISRA-C compliance.
Predicting most rated items in Weekly Recommendation with temporal regression

This paper presents our approach to contextual recommendation for the Filmtipset Weekly Recommendation Track of the CAMRA 2010 Challenge[5]. The goal of this task is to predict which items will be rated by each user on specific weeks of the year, namely the week containing Christmas day, and the week leading up to the Oscars, based on ratings collected prior to the test period. Our approach aims at modeling the short-term evolution of the probability that an item is rated before each test period (in a user-independent way), and then forecasting these probabilities on the test week. To that end, we use a temporal regression technique providing non-personalized recommendation with better test performances than other non-personalized recommendation baselines. We then tried, with success, to generate time-dependent collaborative personalized recommendations providing us our best results.
Querying Semistructured Data with Compression in Distributed Environments

As data management applications grow more complex, they are likely to need efficient distributed query processing. In Distributed Database Systems complete replication consists of maintaining complete copies of the database at each site; this has advantages such as highest locality of reference, highest reliability, availability, and is best for reading. The most promising and dominant data format for data processing and representing on the Internet is the semistructured data form termed XML. XML data has no fixed schema; it evolved and is self describing which results in management difficulties compared to, for example relational data. It is therefore a major challenge for the database community to design query languages and storage methods that can retrieve semistructured data. In this paper, we present a storing and querying scheme for semistructured data views of relational form in distributed environments. The proposed technique stores path dictionary, word dictionary, attribute dictionary, and the complete compressed replication of semistructured data in each distributed site of the DDBS. The presented technique provides query performance improvement due to the compression of semistructured data.
Secure Data Transmission Using Qubits

A quantum protocol for secure transmission of data using qubits is presented. This protocol sends one qubit in a round-trip to transmit one bit of data. The protocol offers an improvement over the BB84 QKD protocol. BB84, in conjunction with one-time pad encryption, has been shown to be unconditionally secure. However its security relies on the assumption that the qubit source device does not emit multiple replicas of the same qubit for each transmitted bit. If this happens a multi-qubit emission attack can be launched. In addition, BB84 cannot be used to send predetermined bit strings as it generates a random bit string in the process. Our protocol does not have the above drawbacks, but requires an authenticated public channel in order to detect an intruder, in the way as BB84. Our protocol does not require a shared secret key.
Repair Strategies for Storage on Mobile Clouds

We study the data reliability problem for a community of devices forming a mobile cloud storage system. We consider the application of regenerating codes for file maintenance within a geographically-limited area. Such codes require lower bandwidth to regenerate lost data fragments compared to file replication or reconstruction. We investigate threshold-based repair strategies where data repair is initiated after a threshold number of data fragments have been lost due to node mobility. We show that at a low departure-to-repair rate regime, a lazy repair strategy in which repairs are initiated after several nodes have left the system outperforms eager repair in which repairs are initiated after a single departure. This optimality is reversed when nodes are highly mobile. We further compare distributed and centralized repair strategies and derive the optimal repair threshold for minimizing the average repair cost per unit of time, as a function of underlying code parameters. In addition, we examine cooperative repair strategies and show performance improvements compared to non-cooperative codes. We investigate several models for the time needed for node repair including a simple fixed time model that allows for the computation of closed-form expressions and a more realistic model that takes into account the number of repaired nodes. We derive the conditions under which the former model approximates the latter. Finally, an extended model where additional failures are allowed during the repair process is investigated. Overall, our results establish the joint effect of code design and repair algorithms on the maintenance cost of distributed storage systems.
Global hypothesis test to compare the likelihood ratios of multiple binary diagnostic tests with ignorable missing data

In this article, a global hypothesis test is studied to simultaneously compare the likelihood ratios of multiple binary diagnostic tests when in the presence of partial disease verification the missing data mechanism is ignorable. The hypothesis test is based on the chi-squared distribution. Simulation experiments were carried out to study the type I error and the power of the global hypothesis test when comparing the likelihood ratios of two and three diagnostic tests respectively. The results obtained were applied to the diagnosis of coronary stenosis.
THE ECONOMICS OF TAX COMPLIANCE: FACT AND FANTASY

Announcements by both the Internal Revenue Service and private analysts that in recent years unreported taxable income in the United States has been averaging 10-15 percent of total taxable income and that noncompliance seems to be growing rapidly have produced a certain sense of panic among commentators in academia, the private bar, government and the news media. One commentator went so far as to say: “the dramatic deterioration in compliance levels witnessed thus far, if not reversed quickly and forcefully, will gain further momentum and eventually erode, beyond repair, the integrity of our present income tax system. ”
Cost-related medication nonadherence and spending on basic needs following implementation of Medicare Part D.

CONTEXT Cost-related medication nonadherence (CRN) has been a persistent problem for individuals who are elderly and disabled in the United States. The impact of Medicare prescription drug coverage (Part D) on CRN is unknown. OBJECTIVE To estimate changes in CRN and forgoing basic needs to pay for drugs following Part D implementation. DESIGN, SETTING, AND PARTICIPANTS In a population-level study design, changes in study outcomes between 2005 and 2006 before and after Medicare Part D implementation were compared with historical changes between 2004 and 2005. The community-dwelling sample of the nationally representative Medicare Current Beneficiary Survey (unweighted unique n = 24,234; response rate, 72.3%) was used, and logistic regression analyses were controlled for demographic characteristics, health status, and historical trends. MAIN OUTCOME MEASURES Self-reports of CRN (skipping or reducing doses, not obtaining prescriptions) and spending less on basic needs to afford medicines. RESULTS The unadjusted, weighted prevalence of CRN was 15.2% in 2004, 14.1% in 2005, and 11.5% after Part D implementation in 2006. The prevalence of spending less on basic needs was 10.6% in 2004, 11.1% in 2005, and 7.6% in 2006. Adjusted analyses comparing 2006 with 2005 and controlling for historical changes (2005 vs 2004) demonstrated significant decreases in the odds of CRN (ratio of odds ratios [ORs], 0.85; 95% confidence interval [CI], 0.74-0.98; P = .03) and spending less on basic needs (ratio of ORs, 0.59; 95% CI, 0.48-0.72; P < .001). No significant changes in CRN were observed among beneficiaries with fair to poor health (ratio of ORs, 1.00; 95% CI, 0.82-1.21; P = .97), despite high baseline CRN prevalence for this group (22.2% in 2005) and significant decreases among beneficiaries with good to excellent health (ratio of ORs, 0.77; 95% CI, 0.63-0.95; P = .02). However, significant reductions in spending less on basic needs were observed in both groups (fair to poor health: ratio of ORs, 0.60; 95% CI, 0.47-0.75; P < .001; and good to excellent health: ratio of ORs, 0.57; 95% CI, 0.44-0.75; P < .001). CONCLUSIONS In this survey population, there was evidence for a small but significant overall decrease in CRN and forgoing basic needs following Part D implementation. However, no net decrease in CRN after Part D was observed among the sickest beneficiaries, who continued to experience higher rates of CRN.
Multi-Atlas Segmentation with Joint Label Fusion

Multi-atlas segmentation is an effective approach for automatically labeling objects of interest in biomedical images. In this approach, multiple expert-segmented example images, called atlases, are registered to a target image, and deformed atlas segmentations are combined using label fusion. Among the proposed label fusion strategies, weighted voting with spatially varying weight distributions derived from atlas-target intensity similarity have been particularly successful. However, one limitation of these strategies is that the weights are computed independently for each atlas, without taking into account the fact that different atlases may produce similar label errors. To address this limitation, we propose a new solution for the label fusion problem in which weighted voting is formulated in terms of minimizing the total expectation of labeling error and in which pairwise dependency between atlases is explicitly modeled as the joint probability of two atlases making a segmentation error at a voxel. This probability is approximated using intensity similarity between a pair of atlases and the target image in the neighborhood of each voxel. We validate our method in two medical image segmentation problems: hippocampus segmentation and hippocampus subfield segmentation in magnetic resonance (MR) images. For both problems, we show consistent and significant improvement over label fusion strategies that assign atlas weights independently.
Chronic intravitreous infusion of ciliary neurotrophic factor modulates electrical retinal stimulation thresholds in the RCS rat.

PURPOSE To determine whether the sustained intravitreous delivery of CNTF modulates cortical response thresholds to electrical retinal stimulation in the RCS rat model of retinal degeneration. METHODS Animals were assigned to four groups: untreated, nonsurgical control and infusion groups of 10 ng/d CNTF, 1 ng/d CNTF, and PBS vehicle control. Thresholds for electrically evoked cortical potentials (EECPs) were recorded in response to transcorneal electrical stimulation of the retina at p30 and again at p60, after a three-week infusion. RESULTS As the retina degenerated over time, EECP thresholds in response to electrical retinal stimulation increased. Eyes treated with 10 ng/d CNTF demonstrated significantly greater retinal sensitivity to electrical stimulation when compared with all other groups. In addition, eyes treated with 1 ng/d CNTF demonstrated significantly greater retinal sensitivity than both PBS-treated and untreated control groups. CONCLUSIONS Retinal sensitivity to electrical stimulation was preserved in animals treated with chronic intravitreous infusion of CNTF. These data suggest that CNTF-mediated retinal neuroprotection may be a novel therapy that can lower stimulus thresholds in patients about to undergo retinal prosthesis implantation. Furthermore, it may maintain the long-term efficacy of these devices in patients.
Support of Design Reuse by Software Product Lines: Leveraging Commonality and Managing Variability

One of the goals of the Motorola/FAU “One Pass to Production” (OPP) project is to drastically shorten the software development cycle. This research supports this goal through the reuse of design artifacts by software product lines. In particular, we propose to develop a method for identifying commonality and variability in core design assets (as represented by UML diagrams).
Visualization of the Distribution of Autophosphorylated Calcium/Calmodulin-Dependent Protein Kinase II after Tetanic Stimulation in the CA1 Area of the Hippocampus

Autophosphorylation of calcium/calmodulin-dependent protein kinase II (CaMKII) at threonine-286 produces Ca2+-independent kinase activity and has been proposed to be involved in induction of long-term potentiation by tetanic stimulation in the hippocampus. We have used an immunocytochemical method to visualize and quantify the pattern of autophosphorylation of CaMKII in hippocampal slices after tetanization of the Schaffer collateral pathway. Thirty minutes after tetanic stimulation, autophosphorylated CaM kinase II (P-CaMKII) is significantly increased in area CA1 both in apical dendrites and in pyramidal cell somas. In apical dendrites, this increase is accompanied by an equally significant increase in staining for nonphosphorylated CaM kinase II. Thus, the increase in P-CaMKII appears to be secondary to an increase in the total amount of CaMKII. In neuronal somas, however, the increase in P-CaMKII is not accompanied by an increase in the total amount of CaMKII. We suggest that tetanic stimulation of the Schaffer collateral pathway may induce new synthesis of CaMKII molecules in the apical dendrites, which contain mRNA encoding its α-subunit. In neuronal somas, however, tetanic stimulation appears to result in long-lasting increases in P-CaMKII independent of an increase in the total amount of CaMKII. Our findings are consistent with a role for autophosphorylation of CaMKII in the induction and/or maintenance of long-term potentiation, but they indicate that the effects of tetanus on the kinase and its activity are not confined to synapses and may involve induction of new synthesis of kinase in dendrites as well as increases in the level of autophosphorylated kinase.
An Investigation of Predator Response in Robotic Herding of Sheep

 Abstract. Research into robotic herding of farm animals has so far been restricted to simulations or very limited artificial environments. Models of herd response to herders as perceived predators vary greatly in complexity but all assume a „flight distance‟ at which an animal will regard the threat as great enough to warrant movement. In this paper we report on an experiment to measure the flight distance for a flock of sheep with a robot herder in a real farm environment. Our results show that, rather than being stable, the flight distance decreases rapidly as the sheep become accustomed to the presence of the robot. This has significant implications for future work on intelligent robotic herding.
Segmentation of medical images using a geometric deformable model and its visualization

An automatic segmentation method for medical images that uses a geometric deformable model is presented, and the segmented results are visualized with the help of a modified marching cubes algorithm. The geometric deformable model is based on evolution theory and the level set method. In particular, the level set method utilizes a new derived speed function to improve the segmentation performance. This function is defined by the linear combination of three terms, namely, the alignment term, the minimal-variance term, and the smoothing term. The alignment term makes a level set as close as possible to the boundary of an object. The minimal-variance term best separates the interior and exterior of the contour. The smoothing term renders a segmented boundary less sensitive to noise. The use of the proposed speed function can improve the segmentation accuracy while making the boundaries of each object much smoother. Finally, it is demonstrated that the design of the speed function plays an important role in the reliable segmentation of synthetic and computed tomography (CT) images, and the segmented results are visualized effectively with the help of a modified marching cubes algorithm.
Regaining Motor Control in Musician's Dystonia by Restoring Sensorimotor Organization

Professional musicians are an excellent model of long-term motor learning effects on structure and function of the sensorimotor system. However, intensive motor skill training has been associated with task-specific deficiency in hand motor control, which has a higher prevalence among musicians (musician's dystonia) than in the general population. Using a transcranial magnetic stimulation paradigm, we previously found an expanded spatial integration of proprioceptive input into the hand motor cortex [sensorimotor organization (SMO)] in healthy musicians. In musician's dystonia, however, this expansion was even larger. Whereas motor skills of musicians are likely to be supported by a spatially expanded SMO, we hypothesized that in musician's dystonia this might have developed too far and now disrupts rather than assists task-specific motor control. If so, motor control should be regained by reversing the excessive reorganization in musician's dystonia. Here, we test this hypothesis and show that a 15 min intervention with proprioceptive input (proprioceptive training) restored SMO in pianists with musician's dystonia to the pattern seen in healthy pianists. Crucially, task-specific motor control improved significantly and objectively as measured with a MIDI (musical instrument digital interface) piano, and the amount of behavioral improvement was significantly correlated to the degree of sensorimotor reorganization. In healthy pianists and nonmusicians, the SMO and motor performance remained essentially unchanged. These findings suggest that the differentiation of SMO in the hand motor cortex and the degree of motor control of intensively practiced tasks are significantly linked and finely balanced. Proprioceptive training restored this balance in musician's dystonia to the behaviorally beneficial level of healthy musicians.
Protein structure comparison based on distances between secondary structure elements and backbone dihedral angles

Protein secondary structure comparison combined with an alignment of backbone dihedral angles is proposed as an approach for protein structure similarity detection. The biological background of the method is presented. Rules for construction of the models of compared proteins are considered. A measure of dihedral angles distance is defined to service the angle comparison. A similarity measure, based on this definition, is suggested. Experiments are carried out to determine the influence of the backbone dihedral angles comparison on the final precision of similarity detection.