Miracle-dz/UniFAR-FTUs huggingface dataset:
Wound Healing Assessment Using Digital Photography: A Review

Digital photography as a non-invasive, simple, objective, reproducible, and practical imaging modality has been investigated for the wound healing assessment over the last three decades, and now has been widely used in clinical daily routine. Advances in the field of image analysis and computational intelligence techniques along with the improvements in digital camera instrumentation, expand the applications of standardized digital photography in diagnostic dermatology such as evaluation of tumours, erythema, and ulcers. A series of digital images taken at regular intervals carries the most informative wound healing indexes, color and dimension, that may help clinicians to evaluate the effectiveness of a particular treatment regimen, to relieve patient discomfort, to globally assess the healing kinetics, and to quantitatively compare different therapies; however, the extent of underlying tissue damage cannot be fully detected. This paper is an introductory review of the important investigations proposed by researchers in the context of clinical wound assessment. The principles of wound assessment using digital photography were shortly described, followed by review of the related literature in four main domains: wound tissue segmentation, automated wound area measurement, wound three dimensional (3D) analysis and volumetric measurement, and monitoring and evaluation of wound tissue changes during healing.
A dual block coordinate proximal algorithm with application to deconvolution of interlaced video sequences

Inverse problems encountered in video processing often require to minimize criteria involving a high number of variables. Among available optimization techniques, proximal methods have shown their efficiency in solving large-scale possibly nonsmooth problems. When some of the proximity operators involved in these methods do not have closed form expressions, they may constitute a bottleneck in terms of computational complexity and memory requirements. In this paper, we address this problem and propose accelerated techniques for solving it. A new dual block-coordinate forward-backward algorithm computing the proximity operator of a sum of convex functions composed with linear operators is proposed and theoretically analyzed. The numerical performance of the approach is assessed through an application to deconvolution and super-resolution of interlaced video sequences.
Research-Based Strategies for Teaching Play Skills to Children with Autism

‘‘I see a toy train. I see a toy train. I see a toy train. ’’ Looking at the train with one eye squinted, Sam, a 4-year-old identified with autism spectrum disorder, has his arm fully extended in front of himself and is holding his toy train in such a way as to enjoy the toy’s shape or, perhaps, the glimmer from its wheels. Sam is reciting the phrase his teacher, Ms. Baker, used earlier that week when she introduced the toy to Sam. Ms. Baker knows Sam loves trains and thought introducing the toy train to Sam would allow him to be included with his peers during center time. Unfortunately, Sam has isolated himself and is very engrossed with looking at the wheels of the toy train. Ms. Baker is not sure what to do, but wants to find a way for Sam to play with his peers. Ms. Baker’s story is not unique. Many teachers and parents of young children identified with autism spectrum disorder (ASD) seek ways to motivate and include children with ASD in play with reinforcing toys and/or activities. Because play appears to come so naturally to many young children who are not identified with ASD, it can be highly frustrating and challenging for educators and parents to identify ways to teach play skills. This article reviews highly practical, evidencebased strategies for explicitly teaching play to young children with ASD. In addition, the authors provide avenues for generalization of play skills to inclusive settings.
Optimization of Gateway Deployment with Load Balancing and Interference Minimization in Wireless Mesh Networks

In a wireless mesh network (WMN), gateways act as the bridges between the mesh backbone and the Internet, and significantly affect the performance of the whole network. Hence, how to determine the optimal number and positions of gate- ways, i.e., gateway deployment, is one of the most important and challenging topics in practical and theoretical research on designing a WMN. Although several approach- es have been proposed to address this problem, few of them take load balancing and interference minimization into account. In this paper, we study the Load-balancing and Interference-minimization Gateway Deployment Problem (LIGDP), which aims to achieve four objectives, i.e. minimizing deployment cost, minimizing MR-GW path length, balancing gateway load and minimizing link interference. We formulate it as a multi-objective integer linear program (ILP) issue first, and then propose an efficient gateway deployment approach, called LIGDP Heuristic. The approach joints two heuristic algorithms, i.e., MSC-based location algorithm (MLA) and load-aware and interference-aware association algorithm (LIAA), to determine gateway positions and construct GW-rooted trees. Simulation results not only show that the trade-off be- tween deployment cost and network performance can be achieved by adjusting R-hop, GW throughput and MR throughput constraints, but also demonstrate that, compared with other existing approaches, LIGDP Heuristic performs better on MR-GW path, load balancing and interference minimization without deploying more gateways.
Measuring integrity on mobile phone systems

Mobile phone security is a relatively new field that is gathering momentum in the wake of rapid advancements in phone system technology. Mobile phones are now becoming sophisticated smart phones that provide services beyond basic telephony, such as supporting third-party applications. Such third-party applications may be security-critical, such as mobile banking, or may be untrusted applications, such as downloaded games. Our goal is to protect the integrity of such critical applications from potentially untrusted functionality, but we find that existing mandatory access control approaches are too complex and do not provide formal integrity guarantees. In this work, we leverage the simplicity inherent to phone system environments to develop a compact SELinux policy that can be used to justify the integrity of a phone system using the Policy Reduced Integrity Measurement Architecture (PRIMA) approach. We show that the resultant policy enables systems to be proven secure to remote parties, enables the desired functionality for installing and running trusted programs, and the resultant SELinux policy is over 90% smaller in size. We envision that this approach can provide an outline for how to build high integrity phone systems.
A variable selection method based on KPCA and FNN for nonlinear system modeling

The kernel principal components analysis (KPCA) can be used to convert a set of nonlinear variables into a linearly separable factors and overcome difficulties encountered with the existing multicollinearity between the factors. However the nonlinear system modeling method does not reduce the number of original features. This paper presents a novel method based on KPCA and selection of false nearest neighbor method (FNN) for secondary variables selection. In the proposed approach, it is inspired by FNN that interpretation of primary variable would be estimated by calculating the variables' map distance in the KPCA space to select secondary variables. The results show that the method is effective and suitable for variable selection by comparing with the fully parametric model form the production processing of hydrogen cyanide.
Three episodes of jet activity in the FRII radio galaxy B0925+420

We present Very Large Array images of a "Double-Double Radio Galaxy", a class of objects in which two pairs of lobes are aligned either side of the nucleus. In this object, B0925+420, we discover a third pair of lobes, close to the core and again in alignment with the other lobes. This first-known "Triple-Double" object strongly increases the likelihood that these lobes represent mutiple episodes of jet activity, as opposed to knots in an underlying jet. We model the lobes in terms of their dynamical evolution. We find that the inner pair of lobes is consistent with the outer pair having been displaced buoyantly by the ambient medium. The middle pair of lobes is more problematic - to the extent where an alternative model interpreting the middle and inner "lobes" as additional bow shocks within the outer lobes may be more appropriate - and we discuss the implications of this on our understanding of the density of the ambient medium.
Fragile X Protein FMRP Is Required for Homeostatic Plasticity and Regulation of Synaptic Strength by Retinoic Acid

Homeostatic synaptic plasticity adjusts the strength of synapses during global changes in neural activity, thereby stabilizing the overall activity of neural networks. Suppression of synaptic activity increases synaptic strength by inducing synthesis of retinoic acid (RA), which activates postsynaptic synthesis of AMPA-type glutamate receptors (AMPARs) in dendrites and promotes synaptic insertion of newly synthesized AMPARs. Here, we show that fragile X mental retardation protein (FMRP), an RNA-binding protein that regulates dendritic protein synthesis, is essential for increases in synaptic strength induced by RA or by blockade of neural activity in the mouse hippocampus. Although activity-dependent RA synthesis is maintained in Fmr1 knock-out neurons, RA-dependent dendritic translation of GluR1-type AMPA receptors is impaired. Intriguingly, FMRP is only required for the form of homeostatic plasticity that is dependent on both RA signaling and local protein synthesis. Postsynaptic expression of wild-type or mutant FMRP(I304N) in knock-out neurons reduced the total, surface, and synaptic levels of AMPARs, implying a role for FMRP in regulating AMPAR abundance. Expression of FMRP lacking the RGG box RNA-binding domain had no effect on AMPAR levels. Importantly, postsynaptic expression of wild-type FMRP, but not FMRP(I304N) or FMRPΔRGG, restored synaptic scaling when expressed in knock-out neurons. Together, these findings identify an unanticipated role for FMRP in regulating homeostatic synaptic plasticity downstream of RA. Our results raise the possibility that at least some of the symptoms of fragile X syndrome reflect impaired homeostatic plasticity and impaired RA signaling.
MIXDES 2008 Proceedings

In this paper a new structure for a multiplying-by-two amplifier is proposed. It is implemented by switching MOS capacitors with floating sources from inversion into depletion dropping the capacitance values in the amplification phase. Low-power is achieved since no operational amplifiers are required but, instead, simple sourcefollowers are used to provide the required isolation. Simulation results show that linearity levels better than 60dB and gain accuracies of better than 1.6% are achieved making this circuit well suited to be used in ultra low-power highspeed 6-to-8 bits pipeline or multi-stage algorithmic ADCs.
A Novel Hybrid Optimization Method with Application in Cascade-Correlation Neural Network Training

In this paper, based on the fusion of the clonal selection algorithm (CSA) and differential evolution (DE) method, we propose a novel optimization scheme: CSA-DE. The DE is employed here to increase the affinities of the clones of the antibodies (Abs) in the CSA. Several nonlinear functions are used to verify and demonstrate the effectiveness of this hybrid optimization approach. It is further applied for the construction of the cascade-correlation (C-C) neural network, in which the optimal hidden nodes can be obtained.
Script for Ndaona demo Dinoj Surendran

That page also has several 3d models made by Ndaona, documentation, and a couple of movies made using the 3d models. Each demo consists of some data in a Matlab . mat file, commands to call Ndaona from Matlab, and a zip file with the files created by Ndaona for Partiview and the Partiview binaries. To run an unzipped demo, the user just needs to click on a . bat file on Windows 2. This brings up a 3d model that the user can spin, etc. The key is moving the mouse with the left or right mouse button pressed — the Ndaona page has more details. The demo proposed for HLT-NAACL 2006 just uses a couple of the available demos, both showing visual-izations of classification results. >> load damaptask >> whos Name Size Bytes Class L 14810x1 118480 double array ProbEst 14810x13 1540240 double array RawText 14810x1 1964842 cell array daclassnames 1x13 940 cell array SomePros 14810x7 829360 double array SomeProsNames 1x7 514 cell array This data has 14810 (test) examples of dialog acts (DAs) from the MapTask corpus. Each DA is tagged with one of 13 tags, and was classified by a support vector machine (SVM) that produced probability outputs 3. 1 It often runs on Unix-based systems too, more on this later. 2 Linux users need to make the *. csh file executable before running it (there have been problems reported with the Linux binary, however, in which case the user will have to compile Partiview using the source code available on the Partiview website. OS X users can try clicking on the corresponding *. command file, but this does not always work. 3 Specifically, it was a combination of six binary support vector machine with a linear kernel. Each SVM output was Platt
Complex dynamics in neuromorphic memristor circuits

A deep study of the nonlinear dynamics of nonlinear circuits with memristors represents a fundamental step towards the development of memristor-based systems for bio-inspired applications and dense nonvolatile memories. A rich variety of complex dynamic behaviors, including chaos, may be observed even in a simple memristor oscillator. This article is organized according to the regulations of the ECCTD 2013 Special Sessions. We present a short summary of the state-of-the-art of memristor theory, model and applications. In addition, we briefly introduce a comprehensive Nonlinear Circuit Theory-based foundation for circuit implementation of the Hodgkin-Huxley neural model with memristors.
Signal detection theory as a tool for successful student selection

Abstract Prediction accuracy of academic achievement for admission purposes requires adequate sensitivity and specificity of admission tools, yet the available information on the validity and predictive power of admission tools is largely based on studies using correlational and regression statistics. The goal of this study was to explore signal detection theory as a tool to extend the available information; signal detection theory allows for comparisons of selection outcomes on both group and individual levels and the development of tailor-made criteria for specific programmes and admission goals. We investigated who would or would not have been admitted applying specific criteria for each of three common admission tools, how many admitted students would fail and how many applicants who would have been successful would be rejected. Both comparisons at an individual level and the receiver operating characteristic curves at a group level revealed that scores obtained in a programme-specific matching programme and non-cognitive factors appear more valuable than regression statistics suggest when it comes to admitting applicants who will become successful students. Signal detection theory allows not only for admission-goal-specific and programme-specific fine-tuning of the content of admission tools, it also informs about the effects of criteria and thus allows the setting of criteria.
Audio Content-based Highlight Detection Using Adaptive Hidden Markov Model

A hidden Markov model (HMM) is employed in this paper to model the structure, and thus generate highlights, of table tennis games. Unlike existing approaches, we use only one HMM for the table tennis games, which combines domain knowledge during initialization, and can be easily adapted to new games through a training phase. Both the homogeneity and heterogeneity are taken into account during this modeling. With this HMM embedded, a multi-level audio content-based highlight detection system, incorporating four audio keywords that are created according to time and frequency domain low-level audio features, is proposed to perform highlight detection in table tennis games. Encouraging results are obtained in the experiments carried out on six table tennis matches
3 D Scene Reconstruction Using Partial RGB + Depth Maps

We present a complex approach to 3D scene reconstruction using both RGB images and depth maps provided by a Microsoft Kinect sensor. The sequence of frames recorded by the freely moving camera fully controlled by human user is processed in order to obtain point cloud representation of the recorded scene. An ICP method is used to align point clouds of subsequent frames, using matched SURF descriptors extracted from RGB images as the initial alignment estimate. Nearest neighbour search for an ICP is accelerated by a kd-tree. The alignment of subsequent frames allows to fully reconstruct camera movement in 3D space and thus to create a complex, colored point cloud model of the recorded scene or object.
Early prenatal critical period for chorda tympani nerve terminal field development

In order to determine whether the developing central gustatory system responds to dietary manipulation during restricted developmental periods, terminal fields of the chorda tympani nerve within the nucleus of the solitary tract were investigated via anterograde transport of horseradish peroxidase in control rats and in rats in which a low sodium diet was systematically fed during specific periods of development. Rats fed a low sodium diet (0.03% NaCl) from embryonic day 3 (E3) to day E12 and then fed a sodium replete diet to at least 60 days postnatal exhibited enlarged and irregularly shaped chorda tympani terminal fields. Specifically, the dorsal zone of the field was the smallest in controls, whereas it was the largest in restricted rats, occupying more territory within the nucleus. This alteration in the terminal field was apparent in all groups of rats fed the low‐NaCl diet beginning at E3, and continuing beyond E12. In contrast, no effects of the dietary manipulation on the developing chorda tympani field was evident when it occurred from E3 to day E9, from E0 to day E9 or when it occurred at adulthood only. Therefore, only 9 days of maternal exposure to a sodium‐restricted diet is required for a permanent expansion of the chorda tympani terminal field in the offspring. Moreover, a brief period from E9 to E12 must be included within the 9‐day dietary restriction to yield the expanded field. Since this period is before taste receptors appear on the tongue, it is likely that nonactivity‐dependent factors determine the formation of the chorda tympani terminal field during later development. J. Comp. Neurol. 378:254–264, 1997. © 1997 Wiley‐Liss, Inc.
Organizational Adaption and Implementation of Product life Management system

The advent of the product lifecycle management (PLM) system provides a Web-based IT platform that streamlines new product development (NPD) related processes by closely integrating the project team and the broader organization. However, there is a lack of systematic research on the use of PLM for better NPD management. The adaptation process for new technology is not yet well understood. This study analyzes how an intraorganizational team successfully adapted a PLM system to meet organizational objectives, achieved through interactions between multilevel users and the modification of system. The theoretical contribution of this study is the combination of product strategy and PLM system implementation, leading to the conceptualization of system usage for the analysis of adaptive behavior. Great research opportunities exist in applying this system adaptation concept to other areas of product development, e.g., how supply chain partners can adapt the system and achieve better performance.
Retransmission in distributed media streaming

This paper considers the use of Automatic Request Request (ARQ) schemes in distributed media streaming. We analytically model three different ARQ schemes and derive effective packet loss rate and burst length of these schemes. Our model is verified through simulations and experiments over wide-area network. Our results show that retransmitting lost packet from senders other than the one who lost the packet could reduce effective loss rate and burst length. We also find that ARQ with a dedicated retransmitter outperforms other schemes if the retransmitter is chosen appropriately.
Model identification for closed-loop multivariable processes based on min-max critical frequency search

This paper presents an improved method of model parameters identification in frequency-domain for closed-loop multivariable processes. Based on reference input and process output data during the closed-loop sequence step tests, the process frequency-responses are estimated with signal frequency analysis. Using a min-max critical frequency search algorithm, only a least possible number of frequency points are obtained for model fitting. Then the first order plus delay time transfer functions are determined by implementing the linear least-square method. Compared with existing methods, the proposed identification technique has the advantage of less computation burden and is easy for industrial applications. Simulation results show the simplicity and effectiveness of the proposed method.
Discrimination Between Closed and Open Shell (Turkish) Pistachio Nuts Using Undecimated Wavelet Packet Transform

Due to low consumer acceptance and the possibility of immature kernels, closed-shell pistachio nuts should be separated from open-shell nuts before reaching the consumer. A system using impact acoustics as a means of classifying closed-shell nuts from open-shell nuts has already been shown to be feasible and have better discrimination performance than a mechanical system.The accuracy of an impact acoustics based system is determined by the signal processing and feature extraction procedures. In this article, a new time-frequency plain feature extraction and classification algorithm was developed to discriminate between open- and closed-shell pistachio nuts produced in the Gaziantep region of Turkey. The proposed approach relies on the analysis of the impact acoustics signal of pistachio nuts, which are emitted from their impact with a steel plate after dropping from a certain height. Features are extracted by decomposing the acoustic signals into time and frequency components, using double-tree undecimated wavelet packet transform. The most discriminative features from the dual tree nodes are selected by a wrapper strategy that includes the structural pruning of the double-tree feature dictionary. The proposed approach requires no prior knowledge of the relevant time or frequency content of the acoustic signals. The algorithm used a small number of features and achieved a classification accuracy of 91.7% on the validation data set, while separating the closed shells from the open ones. A previously implemented algorithm, which uses maximum signal amplitude, absolute integration, and gradient features, achieved 82% classification accuracy on the same dataset. The results show that the time-frequency features extracted from impact acoustics can be used successfully for classification of open- and closed-shell Turkish pistachios.