Miracle-dz/UniFAR-FTUs huggingface dataset:
Instantaneous frequency measurement using double-frequency probing

This paper presents a new double-frequency method for the instantaneous frequency and amplitude measurement of unknown microwave signal. Using the specific interaction of double-frequency radiation and FBG (fiber Bragg grating) with a π phase shift allowed us to obtain measuring characteristics, that are independent of the energy fluctuations of the optical carrier and the microwave signal, and reduce measurement inaccuracy caused by temperature instability of the spectral characteristics of used elements.
Behaviour analysis of HTTP based slow denial of service attack

The technological advancement of computer network and popularity of Internet introduces many on-line services. As the services like e-governance, banking, e-commerce and trading etc. are becoming Internet based, the timely availability of these services to the users have gained paramount importance. Denial of Service (DoS) attack is one of the common attack used by the attacker to interrupt or block availability of the services to the genuine users. Recently, slow DoS attacks are getting popular among the attackers. Generally, the analysis of slow DoS attack is mainly based on the parameters derived from the host machine. In this paper, we analyze the network traffic pattern generated by four different types of slow DoS attack which is targeted on HTTP application. Our analysis focuses on the network based parameters such as window size and delta time of the packet which can be collected from the network gateway. By monitoring and analyzing these parameters, a host machine independent early detection of slow DoS attack is derived and preventive action can be initiated from the network gateway itself.
Neural-network-based cellular automata for simulating multiple land use changes using GIS

This paper presents a new method to simulate the evolution of multiple land uses based on the integration of neural networks and cellular automata using GIS. Simulation of multiple land use changes using cellular automata (CA) is difficult because numerous spatial variables and parameters have to be utilized. Conventional CA models have problems in defining simulation parameter values, transition rules and model structures. In this paper, a three-layer neural network with multiple output neurons is designed to calculate conversion probabilities for competing multiple land uses. The model involves iterative looping of the neural network to simulate gradual land use conversion processes. Spatial variables are not deterministic because they are dynamically updated at the end of each loop. A GIS is used to obtain site attributes and training data, and to provide spatial functions for constructing the neural network. The parameter values for modelling are automatically generated by the training procedure of neural networks. The model has been successfully applied to the simulation of multiple land use changes in a fast growing area in southern China.
Web Audio Evaluation Tool: A Browser-based Listening Test Environment

Perceptual evaluation tests where subjects assess certain qualities of different audio fragments are an integral part of audio and music research. These require specialised software, usually custom-made, to collect large amounts of data using meticulously designed interfaces with carefully formulated questions, and play back audio with rapid switching between different samples. New functionality in HTML5 included in the Web Audio API allows for increasingly powerful media applications in a platform independent environment. The advantage of a web application is easy deployment on any platform, without requiring any other application, enabling multiple tests to be easily conducted across locations. In this paper we propose a tool supporting a wide variety of easily configurable, multi-stimulus perceptual audio evaluation tests over the web with multiple test interfaces, preand post-test surveys, custom configuration, collection of test metrics and other features. Test design and setup doesn’t require programming background, and results are gathered automatically using web friendly formats for easy storing of results on a server.
Time samples selection in spiral acquisition for sparse magnetic resonance spectroscopic imaging

Magnetic resonance spectroscopic imaging (MRSI) has multiple interests in clinical practice, and especially for brain disease diagnosis. However, it faces quite long acquisition time in practice which limits their use in a clinical environment. Fast MRI acquisitions can help to reduce this acquisition time and intensify their clinical use. In this work, a new fast Magnetic Resonance Spectroscopic image acquisition method is introduced and evaluated based on a k-t space spiral sampling. The time-domain subsampling, below the Shannon-Nyquist rate, is allowed on the hypothesis of a sparse spectrum with an a priori known support. Then the nonzero components of the spectrum of each voxel are recovered using an over-determined least square problem. When data are noise-free the recovered spectrum is exact. In the real-world noisy scenario the error in the recovered spectrum highly depends on the acquired samples. We reduce this error to an acceptable level by selecting irregularly the samples using the Sequential Backward Selection algorithm. A realistic simulated irregular spiral acquisition proves the feasibility of the proposed approach.
DWPPT: Data Warehouse Performance Prediction Tool

The increasing demands for interactive response time from the users makes query performance one of the central problems of Data warehouse systems today. Performance is an important quality aspect of Data warehouse systems. Predicting the performance of Data warehouse systems during early design stages of their development is significant. Software Performance Engineering(SPE) promotes the idea that the integration of performance analysis into the software development process, from the earliest stages to the end, can ensure that the system will meet its performance objectives. This paper describes the features and use of a prototype tool, DWPPT(Data Warehouse Performance Prediction Tool) which is designed to analyze the performance of the Data warehouse in different environmental conditions. The tool supports SPE process for Data warehouse systems. The tool is useful for Data warehouse managers in identifying critical components, diagnosing problems and hence optimizing the overall design. Our objective is to investigate the impact of Data warehouse design factors on OLAP performance for different user populations and hardware configurations. An analytical and simulation modeling approach is used for the tool to predict performance of Data warehouse systems.
Investigation of Optimal Split Ratio in Brushless Dual-Rotor Flux-Switching Permanent Magnet Machine Considering Power Allocation

This paper investigates an optimal split ratio for a brushless dual-rotor flux-switching permanent magnet (BDR-FSPM) machine. Based on the design theory of conventional FSPM machine, the split ratio of the BDR-FSPM machine is deduced and redefined. And the crucial factors which have close relationship with the split ratio are determined, consisting of power split ratio, magnetic loading, PM pole width, and stator pole width. To conveniently explore the optimal split ratio, the response surface method is purposely utilized for conducting optimization, where the magnetic loading and output torque are chosen to be the objectives. In addition, considering the application requirement of hybrid electric vehicles, the concept of power allocation is proposed and integrated into the optimization process of split ratio. Then based on the optimal split ratio, the machine performances are analyzed in detail, including air gap flux density, back-electromotive force (EMF), coupled-EMF, and torque performances. Finally, a prototyped BDR-FSPM machine is manufactured and tested to verify the validity of the proposed split ratio optimization and machine design approach.
A discrete convolution kernel for No-DC MRI

An analytical inversion formula for the exponential Radon transform with an imaginary attenuation coefficient was developed in 2007 (2007 Inverse Problems 23 1963–71). The inversion formula in that paper suggested that it is possible to obtain an exact MRI (magnetic resonance imaging) image without acquiring low-frequency data. However, this un-measured low-frequency region (ULFR) in the k-space (which is the two-dimensional Fourier transform space in MRI terminology) must be very small. This current paper derives a FBP (filtered backprojection) algorithm based on You’s formula by suggesting a practical discrete convolution kernel. A point spread function is derived for this FBP algorithm. It is demonstrated that the derived FBP algorithm can have a larger ULFR than that in the 2007 paper. The significance of this paper is that we present a closed-form reconstruction algorithm for a special case of under-sampled MRI data. Usually, under-sampled MRI data requires iterative (instead of analytical) algorithms with L1-norm or total variation norm to reconstruct the image.
Performance of the Rheumatoid Arthritis Impact of Disease (RAID) score in relation to other patient-reported outcomes in a register of patients with rheumatoid arthritis

Objective Delegates at the Outcome Measures in Rheumatology (OMERACT) 10 conference (Borneo, 4–8 May 2010) questioned how the new seven-domain Rheumatoid Arthritis Impact of Disease (RAID) score performs as a global measure. Score distributions and associations between the RAID score and patient-reported outcomes (PROs) and demographic variables were examined in a large sample of rheumatoid arthritis (RA) patients. Methods 1086 patients in the Oslo RA Register responded to a postal survey with commonly used PROs. Bivariate associations between the RAID score and other measures are reported as Pearson correlation coefficients. Results The mean RAID was 3.37±2.17. The distribution of the RAID score showed a slight floor effect: 17.5% had a score between 0 and 1, and 14.4% between 1 and 2, whereas only 1.0% and 0.3% had scores between 8 and 9, and 9 and 10, respectively. Correlations between the RAID score and the patient global assessment, Rheumatoid Arthritis Disease Activity Index, Short-Form (SF)-6D and EQ-5D were 0.82, 0.82, −0.77 and −0.73, respectively. Strong correlation was also seen between RAID and pain, the domain with highest weight, whereas correlations to measures of other RAID domains were moderate. The RAID score was higher in women than men (3.49 vs 2.95, p=0.001). Conclusion The RAID score was correlated more strongly to other global measures than to PROs, reflecting single health domains.
Design of Highly Stable Tungsten-Doped IZO Thin-Film Transistors With Enhanced Performance

High-performance thin-film transistors (TFTs) were obtained by incorporating small amount of tungsten (<inline-formula> <tex-math notation="LaTeX">${W}$ </tex-math></inline-formula>) into amorphous indium zinc oxide (IZO)-based thin films via a solution process. Compared with original IZO TFTs, 0.2-wt% <inline-formula> <tex-math notation="LaTeX">${W}$ </tex-math></inline-formula>-doped IZO TFTs exhibit improved bias stress stability and field-effect mobility of 30.5 cm<sup>2</sup>/<inline-formula> <tex-math notation="LaTeX">$\text{V}\cdot \text{s}$ </tex-math></inline-formula>. Meanwhile, the bias stress stability of IZO TFTs can be further enhanced with 0.5-wt% W-doping. The pulsed current–voltage (<inline-formula> <tex-math notation="LaTeX">${I}$ </tex-math></inline-formula>–<inline-formula> <tex-math notation="LaTeX">${V}$ </tex-math></inline-formula>) method is employed to study the hysteresis and charging behavior of the <inline-formula> <tex-math notation="LaTeX">${W}$ </tex-math></inline-formula>-doped IZO TFTs. The X-ray photoelectron spectroscopy analysis and the pulsed <inline-formula> <tex-math notation="LaTeX">${I}$ </tex-math></inline-formula>–<inline-formula> <tex-math notation="LaTeX">${V}$ </tex-math></inline-formula> measurement results suggest that these desirable performances could be attributed to the suppression of excessive oxygen vacancies and improved interface quality because of <inline-formula> <tex-math notation="LaTeX">${W}$ </tex-math></inline-formula>-doping. The results represent an effective strategy to achieve high-performance solution-processed amorphous oxide-based TFTs with desirable stability by <inline-formula> <tex-math notation="LaTeX">${W}$ </tex-math></inline-formula>-doping.
Ligand-activated epidermal growth factor receptor (EGFR) signaling governs endocytic trafficking of unliganded receptor monomers by non-canonical phosphorylation

The canonical description of transmembrane receptor function is initial binding of ligand, followed by initiation of intracellular signaling and then internalization en route to degradation or recycling to the cell surface. It is known that low concentrations of extracellular ligand lead to a higher proportion of receptor that is recycled and that non-canonical mechanisms of receptor activation, including phosphorylation by the kinase p38, can induce internalization and recycling. However, no connections have been made between these pathways; i.e. it has yet to be established what happens to unbound receptors following stimulation with ligand. Here we demonstrate that a minimal level of activation of epidermal growth factor receptor (EGFR) tyrosine kinase by low levels of ligand is sufficient to fully activate downstream mitogen-activated protein kinase (MAPK) pathways, with most of the remaining unbound EGFR molecules being efficiently phosphorylated at intracellular serine/threonine residues by activated mitogen-activated protein kinase. This non-canonical, p38-mediated phosphorylation of the C-tail of EGFR, near Ser-1015, induces the clathrin-mediated endocytosis of the unliganded EGFR monomers, which occurs slightly later than the canonical endocytosis of ligand-bound EGFR dimers via tyrosine autophosphorylation. EGFR endocytosed via the non-canonical pathway is largely recycled back to the plasma membrane as functional receptors, whereas p38-independent populations are mainly sorted for lysosomal degradation. Moreover, ligand concentrations balance these endocytic trafficking pathways. These results demonstrate that ligand-activated EGFR signaling controls unliganded receptors through feedback phosphorylation, identifying a dual-mode regulation of the endocytic trafficking dynamics of EGFR.
A Parameter Communication Optimization Strategy for Distributed Machine Learning in Sensors

In order to utilize the distributed characteristic of sensors, distributed machine learning has become the mainstream approach, but the different computing capability of sensors and network delays greatly influence the accuracy and the convergence rate of the machine learning model. Our paper describes a reasonable parameter communication optimization strategy to balance the training overhead and the communication overhead. We extend the fault tolerance of iterative-convergent machine learning algorithms and propose the Dynamic Finite Fault Tolerance (DFFT). Based on the DFFT, we implement a parameter communication optimization strategy for distributed machine learning, named Dynamic Synchronous Parallel Strategy (DSP), which uses the performance monitoring model to dynamically adjust the parameter synchronization strategy between worker nodes and the Parameter Server (PS). This strategy makes full use of the computing power of each sensor, ensures the accuracy of the machine learning model, and avoids the situation that the model training is disturbed by any tasks unrelated to the sensors.
Information dissemination dynamics in delay tolerant network: a bipartite network approach

In this paper, we present a model of a delay tolerant network(DTN) and identify that this model can be suitably reformulated as a bipartite network and that the major predictions from the former are equivalent to that of the latter. In particular, we show that the coverage of the information dissemination process in the DTN matches accurately with the size of the largest component in the suitably thresholded one-mode projection of the corresponding bipartite network. In the process of this analysis, some of the important insights gained are that (a) arbitrarily increasing the number of agents participating in the dissemination process cannot increase the coverage once the system has reached the stationary state for a given buffer time (i.e., the time for which a message resides in the buffer of the places visited by the agents), (b) the coverage varies inversely with the square of the number of places in the system and directly with the square of the average social participation of the agents and (c) it is possible to design an optimal buffer time for a desired cost of coverage. To the best of our knowledge, this is the first such work that employs the rich theoretical backbone of bipartite networks as a "proxy" for the analysis of the otherwise intractable DTN dynamics thus allowing for various novel analytical estimates.
Annealing Effect on Small Molecules Blend Organic Light-Emitting Diodes

This research work investigates the influence of the annealing process upon the performance of photo-emissive layer of organic light-emitting diode (OLED). The photo-emissive layer consists of a ternary blend of N, N-diphenyl-N,N-bis (3-methylphenyl)-(1,1-biphenyl)-4,4-diamine (TPD), 2-(4-biphenylyl)-5-phenyl-1,3,4-oxadiazole (PBD) and tris-8-hydroxyquinoline (Alq3), to produce TPD:PBD:Alq3 (at 1:1:1 ratio) blend thin films, in which the material solutions are deposited onto clean substrate via spin-coating method. The samples were annealed at 100°C in 10, 20 and 30 minute of time in an open-air condition. The results reveal that the annealing process at 10 minutes produces an optimum performance of the ternary OLED.
New insights into the evolution of C-1 family cadherins

Specific cell-cell adhesion and intracellular communication are key processes in multicellular animals, and members of the cadherin superfamily are essential players in these processes. Evolutionary origin of the modern C-1 family in metazoan has been established based on bioinformatic tools using Neighbor-Joining (NJ) algorithm and the EC1 first cadherin-repeat sequence a very narrow segment of the protein full-length but responsible of adhesive recognition and their cytoplasmic domain. Searching for insights that reveal organizational changes in cadherin superfamily C-1 members, a phylogenetic analysis of full extracellular (EC) and cytoplasmic domains (CD) was performed, using Maximum Likelihood (ML) phylogenetic algorithm. We compiled literature data and performed an in-depth phylogenetic analysis of 145 members of this superfamily from 8 species, covering several representative branches within metazoan evolution. We analyzed the amino acids sequence homology between extracellular and cytoplasmic domains, and we reviewed protein structural data architecture. Analysing EC full-length with the Maximum Likelihood approach we could reclassify the solitary CDH13 group, as keeping within the classical type I cadherins.
Focus prior estimation for salient object detection

In the past five years, salient object detection has become one of the hot topics in the field of computer vision. Focus is a naturally strong indicator for the salient object detection task, but is not well studied. In this paper, a novel method is proposed to estimate the focus prior map for an arbitrary image. Different from the current edge density estimation based methods, the proposed method is based on the sparse defocus dictionary learning on a newly designed dataset. The focus strength is measured by the number of non-zero coefficients of the dictionary atoms. Objectness proposal method is introduced to improve the performance. Comparison with the other focusness estimation methods, the proposed focus prior map is more accurate and easier to be integrated by the other salient object detection methods. Experiments have confirmed the effectiveness and importance of the proposed focus prior.
Palm Vein Recognition Algorithm Using Curvelet and Wavelet

In this paper we report on a curvelet and wavelet based palm vein recognition algorithm. Using our palm vein image database, we employed minimum distance classifier to test the performance of the system. Experimental results show that the algorithm based on cuvelet transform can reach equal error rate of 1.7%, and the algorithm based on wavelet transform can only reach equal error rate of 2.3%, indicating that the curvelet based palm vein recognition system improves representation.
Ternary complex formation and IGFBP-3 proteolytic activity during childhood: age-dependent changes.

BACKGROUND IGF-I is mainly sequestered in a 150-kDa ternary complex with IGF binding protein (IGFBP)-3 and the acid-labile subunit. Data on complex formation and factors influencing formation have not been established. Dissociation of IGF-I from the ternary complex is in part regulated by proteolysis of IGFBP-3, which reduces its affinity for IGF-I. Short small for gestational age (SGA) children have lower IGF-I and IGFBP-3 levels compared with healthy peers. OBJECTIVE The objective of the study was to determine complex formation in healthy normal-statured children and assess variables influencing complex formation. Second, we determined complex formation in short SGA children. DESIGN/METHODS Complex formation was assessed using (125)I-hIGF-I column chromatography in 70 controls (40 boys), median age 10.6 years, and 40 short SGA children (25 boys), median age 8.6 years. IGFBP-3 was determined by Western immunoblotting. RESULTS (125)I-hIGF-I complex formation showed an age-specific pattern in healthy controls. Variables positively influencing ternary complex formation were higher serum IGF-I levels compared with IGFBP-3 levels (P < .001) and lower serum IGF-II (P < .001) and IGFBP-1 levels (P < .001). In addition, a higher presence of proteolyzed IGFBP-3 negatively influenced 150-kDa complex formation (P = .006). At a young age, healthy children showed considerable IGFBP-3 proteolytic activity, which declined with aging (P < .001). IGFBP-3 proteolytic activity was negatively correlated with IGF-I levels (P < .001). Compared with healthy controls, short SGA children showed reduced IGF-I levels (-1.3 vs 0.1 SD score) and increased proteolyzed IGFBP-3 (35.1% vs 12.2%). CONCLUSION Age-specific normative values for (125)I-hIGF-I 150-kDa ternary complex formation are presented. A decrease in IGF-I and an increase in IGF-II, IGFBP-1, and IGFBP-3 proteolytic activity associate with reduced (125)I-hIGF-I ternary complex formation. Our results suggest that in conditions in which IGF-I levels are low, such as young age and in short SGA children, IGFBP-3 proteolytic activity is increased to ensure IGF-I bioavailability.