Miracle-dz/UniFAR-FTUs huggingface dataset:
Stock Selection Based on Data Clustering Method

Stock selection is stock market participants facing a difficult problem. This article aims to apply clustering in data mining techniques to analyze the financial data and stock trading data, give the classification of stocks, provide the decision support of stock selections for the dealer. The main work include: the construction of the financial data and stock market data, the pre-processing of the data in the data set, the analysis of the data set applying the clustering techniques, giving the stock's classification, verifying the classification results. The stock selection base on cluster analysis improves the success rate and yield, and have important practical value of guidance of investment decisions.
A comparison of Gaussian mixture and artificial neural network models for voiced-based access control system of building security

Secure buildings are currently protected from unauthorized access by a variety of devices. Nowadays, there are many kinds of devices to guarantee the building security such as PIN pads, keys both conventional and electronic, identity cards, cryptographic and dual control procedures. However, these conventional devices can be stolen, forgotten, lost, guessed or impersonated with accuracy. Biometric system based on behavioral and/or physiological characteristics of person becomes popular as an alternative method to overcome the problem of conventional method. In this paper, voice-based biometric system is introduced for access control of building security. The ability to verify the identity of a person by analyzing his/her speech, or speaker verification, is an attractive and relatively unobtrusive means of providing security for admission into an important or secured place. An individualpsilas voice cannot be stolen, lost, forgotten, guessed, or impersonated with accuracy. In the proposed system, the access may be authorized simply by means of an enrolled user speaking into a microphone attached to the system. The proposed system then will decide whether to accept or reject the userpsilas identity claim or possibly to report insufficient confidence and request additional input before making the decision. Two approaches are adopted and evaluated to model the authorized persons, namely classical Gaussian mixture model (GMM) and artificial neural network (ANN). Experimental result confirms that in terms of false acceptance rate (FAR) and false rejection rate (FRR), the proposed voice-based access control with ANN model is better than that with GMM.
From switchboard to fisher: telephone collection protocols, their uses and yields

In a process for producing a color television picture tube which comprises at least the step of coating phosphor slurries onto the inner surface of a panel to form a phosphor layer, the step of forming two layers each consisting of an aqueous filming emulsion containing an acrylic resin, the step of forming a metal film on the second layer, and the step of baking out the organic substances, a color television picture tube having a metal film which contains a few pores and cracks and no blister can be produced by using said phosphor slurries containing an acrylic resin and using the first aqueous filming emulsion containing an acrylic resin having an elongation of 10% or more and using the second aqueous filming emulsion containing an acrylic resin having an elongation of less than 10%.
Paper 11

During the recent years, the market of mobile software applications (apps) has maintained an impressive upward trajec-tory. Many small and large software development companies invest considerable resources to target available opportunities. As of today, the markets for such devices feature over 850K+ apps for Android and 900K+ for iOS. Availability, cost, functionality, and usability are just some factors that determine the success or lack of success for a given app. Among the other factors, reliability is an important criteria: users easily get frustrated by repeated failures, crashes, and other bugs; hence, abandoning some apps in favor of others. This paper reports a study analyzing how the fault-and change-proneness of APIs used by 7,097 (free) Android apps relates to applications' lack of success, estimated from user ratings. Results of this study provide important insights into a crucial issue: making heavy use of fault-and change-prone APIs can negatively impact the success of these apps.
K and evolutionary corrections from uv to ir

K and evolutionary corrections are given for the E, Sa and Sc Hubble types for the filters of the Johnson – Bessell & Brett photometric system and the gri filters of the modified Thuan & Gunn system up to the redshift . Their dependence on the time scale of star formation in ellipticals is investigated. The corrections are computed according to an evolutionary synthesis model that reproduces the integrated galaxy spectrum in the range A; such a model makes use of an infrared observed stellar library and its results are compared with nearby galaxies. Evolving spectral energy distributions of the various Hubble types, as well as optical-IR and IR-IR colour evolution and adopted filter response functions are also given.
Anti-Cancer Effect of Quercetin in Xenograft Models with EBV-Associated Human Gastric Carcinoma

Licorice extracts have been widely used in herbal and folk medications. Glycyrrhiza contains diverse range of biological compounds including triterpenes (glycyrrhizin, glycyrrhizic acid) and flavonoids (quercetin, liquiritin, liquiritigenin, glabridin, licoricidin, isoliquiritigenin). The flavonoids in licorice are known to have strong anti-cancer activities. Quercetin, the most abundant flavonoid, has been shown to have anti-ulcer, anti-cancer, antioxidant, and anti-inflammatory properties. Latent Epstein-Barr virus (EBV) infection can lead to serious malignancies, such as, Burkitt’s lymphoma, Hodgkin’s disease and gastric carcinoma(GC), and (Epstein-Barr virus associated gastric carcinoma) EBVaGC is one of the most common EBV-associated cancers. In this study, the authors first examined the anti-cancer effects of quercetin and isoliquiritigenin in vivo xenograft animal models implanted with EBV(+) human gastric carcinoma (SNU719) or EBV(−) human gastric carcinoma (MKN74), and then explored the molecular mechanisms responsible for their anti-cancer activities. The results obtained showed that anti-cancer effect of quercetin was greater than isoliquiritigenin in mice injected with EBV(+) human gastric carcinoma (SNU719) cells. On the other hand, quercetin and isoliquiritigenin had similar anti-cancer effects in mice injected with EBV(−) human gastric carcinoma (MKN74) cells. Interestingly, quercetin inhibited EBV viral protein expressions, including EBNA-1 and LMP-2 proteins in tumor tissues from mice injected with EBV(+) human gastric carcinoma. Quercetin more effectively induced p53-dependent apoptosis than isoliquiritigenin in EBV(+) human gastric carcinoma, and this induction was correlated with increased expressions of the cleaved forms of caspase-3, -9, and Parp. In EBV(−)human gastric carcinoma (MKN74), both quercetin and isoliquiritigenin induced the expressions of p53, Bax, and Puma and the cleaved forms of caspase-3 and -9 and Parp at similar levels.
Re-estimation of linear predictive parameters in sparse linear prediction

In this work, we propose a novel scheme to re-estimate the linear predictive parameters in sparse speech coding. The idea is to estimate the optimal truncated impulse response that creates the given sparse coded residual without distortion. An all-pole approximation of this impulse response is then found using a least square approximation. The all-pole approximation is a stable linear predictor that allows a more efficient reconstruction of the segment of speech. The effectiveness of the algorithm is proved in the experimental analysis.
Signal processing techniques for stabilization of marching-on-in-time method

This paper deals with the stabilization of MOT method by digital filters. We propose how to design such a filter with using the optimization techniques. The proposed procedure takes into account the important part of the spectrum of excitation signal, so the designed filter do not degrade the accuracy of MOT method. Further, the issue of successful stabilization of MOT method by set of filters is discussed.
Estimating regional carbon exchange in New England and Quebec by combining atmospheric, ground-based and satellite data

We derive regional-scale (∼104 km2) CO2 flux estimates for summer 2004 in the northeast United States and southern Quebec by assimilating extensive data into a receptor-oriented model-data fusion framework. Surface fluxes are specified using the Vegetation Photosynthesis and Respiration Model (VPRM), a simple, readily optimized biosphere model driven by satellite data, AmeriFlux eddy covariance measurements and meteorological fields. The surface flux model is coupled to a Lagrangian atmospheric adjoint model, the Stochastic Time-Inverted Lagrangian Transport Model (STILT) that links point observations to upwind sources with high spatiotemporal resolution. Analysis of CO2 concentration data from the NOAA-ESRL tall tower at Argyle, ME and from extensive aircraft surveys, shows that the STILT– VPRM framework successfully links model flux fields to regionally representative atmospheric CO2 data, providing a bridge between ‘bottom-up’ and ‘top-down’ methods for estimating regional CO2 budgets on timescales from hourly to monthly. The surface flux model, with initial calibration to eddy covariance data, produces an excellent a priori condition for inversion studies constrained by atmospheric concentration data. Exploratory optimization studies show that data from several sites in a region are needed to constrain model parameters for all major vegetation types, because the atmosphere commingles the influence of regional vegetation types, and even high-resolution meteorological analysis cannot disentangle the associated contributions. Airborne data are critical to help define uncertainty within the optimization framework, showing for example, that in summertime CO2 concentration at Argyle (107 m) is ∼0.6 ppm lower than the mean in the planetary boundary layer.
Fast and Efficient Operational Time Series Storage: The Missing Link in Dynamic Software Analysis

Distributed applications, cloud systems, the Internet of Things, etc. are generating increasing amounts of operational data, such as CPU loads, thread states, memory consumptions, method runtimes, or logs. Many tools continuously collect and analyze such data that is best represented as time series. Typical analyses try to ﬁnd and localize run-time incidents like outliers, leaks, or trend anomalies. However, these analyses need an eﬃcient use of storage and a fast interactive query execution, that general purpose storage systems do not provide: neither storing operational time series data in general-purpose databases nor in conventional time series databases fulﬁlls these requirements. We present Chronix, a novel time series storage that is optimized for operational time series and that improves the link between storage and analysis in a dynamic software analysis toolchain. With Chronix a toolchain not only stores data 4–33 times faster and it takes 5–171 times less storage space than with other time series databases, it also executes queries in 15–74% and analyses in 25–74% of the time.
Examining Comparative Shopping Agents from Two Types of Search Results

A search engine provides two distinct types of results, organic and paid, each of which uses different mechanisms for selecting and ranking relevant web pages for a query. A comparative shopping agent (CSA), such as a price comparison website, conveniently provides web consumers with companies that sell desired product and the prices they offer on one page, which greatly reduces search costs. We identify 168 digital camera models from seven major camera makers, manually search each of the models in a popular search engine, empirically compare CSAs between the two types of search results in terms of the number of CSAs, number of vendors inside CSAs, lowest and average prices, and price dispersion. The paid results contain more CSAs and vendors than do organic results; vendors inside CSAs in paid results offer the lowest prices more often than do companies from CSAs in organic results; the average price for vendors in CSAs from paid results is not significant lower than that from companies in CSAs from organic results; the price dispersion among vendors in CSAs is greater from paid results than from organic results. In addition, companies with unsatisfactory ratings offer the lowest prices and lower average prices more often than do companies with satisfactory ratings.
Advances in sensitivity encoding with arbitrary k‐space trajectories

New, efficient reconstruction procedures are proposed for sensitivity encoding (SENSE) with arbitrary k‐space trajectories. The presented methods combine gridding principles with so‐called conjugate‐gradient iteration. In this fashion, the bulk of the work of reconstruction can be performed by fast Fourier transform (FFT), reducing the complexity of data processing to the same order of magnitude as in conventional gridding reconstruction. Using the proposed method, SENSE becomes practical with nonstandard k‐space trajectories, enabling considerable scan time reduction with respect to mere gradient encoding. This is illustrated by imaging simulations with spiral, radial, and random k‐space patterns. Simulations were also used for investigating the convergence behavior of the proposed algorithm and its dependence on the factor by which gradient encoding is reduced. The in vivo feasibility of non‐Cartesian SENSE imaging with iterative reconstruction is demonstrated by examples of brain and cardiac imaging using spiral trajectories. In brain imaging with six receiver coils, the number of spiral interleaves was reduced by factors ranging from 2 to 6. In cardiac real‐time imaging with four coils, spiral SENSE permitted reducing the scan time per image from 112 ms to 56 ms, thus doubling the frame‐rate. Magn Reson Med 46:638–651, 2001. © 2001 Wiley‐Liss, Inc.
A weighted waveguide for surface acoustic waves based on two-dimensional pizoelectric phononic crystals

This paper has proposed a weighted waveguide for surface acoustic waves (SAW) based on two-dimensional piezoelectric phononic crystals (PnCs). In order to analyze the transmission of the weighted waveguide based on PnCs, SAW delay line model was built. In the model, period boundary condition was adopted to reduce the time and memory of model cost and perfect matching layer was adopted to absorb the reflection of the waves. Three-dimensional finite element method (FEM) was used to calculate the transmission coefficients and analyze the acoustic field distribution. Results showed that the band gaps and band passes are separated in the x and y direction. Thus the weighted waveguide can prohibit the waves in one direction while permit the waves in another direction. This property of weighted waveguide can be used in the SAW devices in the future study.
Full-Duplex Cooperative Cognitive Radio with Transmit Imperfections

This paper studies the cooperation between a primary system and a cognitive system in a cellular network where the cognitive base station (CBS) relays the primary signal using amplify-and-forward or decode-and-forward protocols, and in return it can transmit its own cognitive signal. While the commonly used half-duplex (HD) assumption may render the cooperation less efficient due to the two orthogonal channel phases employed, we propose that the CBS can work in a full-duplex (FD) mode to improve the system rate region. The problem of interest is to find the achievable primary-cognitive rate region by studying the cognitive rate maximization problem. For both modes, we explicitly consider the CBS transmit imperfections, which lead to the residual self-interference associated with the FD operation mode. We propose closed-form solutions or efficient algorithms to solve the problem when the related residual interference power is non-scalable or scalable with the transmit power. Furthermore, we propose a simple hybrid scheme to select the HD or FD mode based on zero-forcing criterion, and provide insights on the impact of system parameters. Numerical results illustrate significant performance improvement by using the FD mode and the hybrid scheme.
Multiphase CT Angiography versus Single-Phase CT Angiography: Comparison of Image Quality and Radiation Dose

BACKGROUND AND PURPOSE: Conventional CT angiography (CTA) is acquired during only a short interval in the arterial phase, which limits its ability to evaluate the cerebral circulation. Our aim was to compare the image quality and radiation dose of conventional single-phase CTA (SP-CTA) with a multiphase CTA (MP-CTA) algorithm reconstructed from a perfusion CT (PCT) dataset. MATERIALS AND METHODS: Fifty consecutive patients undergoing head CTA and PCT in 1 examination were enrolled. The PCT dataset was obtained with 40.0-mm-detector coverage, 5.0-mm axial thickness, 80 kilovolt peak (kVp), 180 mA, and 30 mL of contrast medium. MP-CTA was reconstructed from the same PCT dataset with an axial thickness of 0.625 mm by using a new axial reconstruction algorithm. A conventional SP-CTA dataset was obtained with 0.625-mm axial thickness, 120 kVp, 350 mA, and 60 mL of contrast medium. We compared image quality, vascular enhancement, and radiation dose. RESULTS: SP-CTA and MP-CTA of 50 patients (male/female ratio, 31/19; mean age, 59.25 years) were analyzed. MP-CTA was significantly better than SP-CTA in vascular enhancement (P = .002), in the absence of venous contamination (P = .006), and was significantly higher in image noise (P < .001). MP-CTA used less contrast medium than SP-CTA and could demonstrate hemodynamic information. The effective dose of MP-CTA was 5.73 mSv, which was equal to that in conventional PCT, and it was 3.57 mSv in SP-CTA. CONCLUSION: It is feasible that MP-CTA may provide both CTA and PCT results. Compared with SP-CTA, MP-CTA provides comparable image quality, better vascular enhancement, hemodynamic information, and more noise with less detail visibility with a lower tube voltage. The radiation dose of MP-CTA is higher than that of SP-CTA, but the dose can be reduced by altering the sampling interval.
Foreign object detection in chest X-rays

Automatic analysis of chest X-ray images is one important approach for screening/identifying pulmonary diseases. The existence of foreign objects in the images hinders the performance of such processing. In this paper, we focus on one type of foreign objects that is often shown in the images of a large dataset of chest X-rays we are working on-the buttons on the gown that the patient is wearing. The method we propose involves four major steps: intensity normalization, low contrast image identification and enhancement, segmentation of lung regions, and button object extraction. Based on the characteristics of the button objects, we applied two methods for the step of button object extraction. One was based on the circular Hough transform; the other was based on the Viola-Jones algorithm. We tested and compared both methods using a ground truth dataset containing 505 button objects. The results demonstrate the effectiveness of the proposed method.
Flow-aware link dimensioning for guaranteed-QoS services in broadband convergence networks

In this work,1 we propose an analytic framework for dimensioning the link capacity of broadband access networks which provide universal broadband access services to a diverse kind of customers such as patient and impatient customers. The proposed framework takes into account the flow-level quality of service (QoS) of a connection as well as the packet-level QoS, via which a simple and systematic provisioning and operation of the network are provided. To that purpose, we first discuss the necessity of flow-aware network dimensioning by reviewing the networking technologies of the current and future access network. Next, we propose an analytic model for dimensioning the link capacity for an access node of broadband convergence networks which takes into account both the flow and packet level QoS requirements. By carrying out extensive numerical experiment for the proposed model assuming typical parameters that represent real network environment, the validity of the proposed method is assessed.
Effects ofTransmission Error Rates on Saturation Performance of the IEEE 802 . 11 MAC

Analyzing the effect of transmission errors on the performance of IEEE 802.11 is important since the wireless channels are error-prone. Most of the existing work on the performance analysis of IEEE 802.11 distributed coordination function (DCF) assumes ideal channel conditions. Although a few recent papers consider the impact of packet error rate, they assume the same packet error rate for all the nodes in the system. Obviously, this is an unreasonable assumption for practical environments. In this paper, a new analytical model is developed to evaluate the performance of DCF, in which nodes incur different transmission error rates. An improved Markov chain model is presented to analyze the impact of packet error rates on the transmission probability. A state transition matrix is set up to derive the stationary performance. Our analytical model is validated via simulations using ns-2.
Antiviral Activity of a Zymolytic Grain Based Extract on Human Immunodeficiency Virus Type 1 In Vitro

Increasing evidence shows that grains may play a role in disease prevention beyond the simple provision of energy and nutrients. It has been reported that some components contained in grains exert their functional effects on viral and bacterial infections and protect against various cancers. However, until now, hardly any intervention studies have investigated the effects of grains or grain based extracts on the inhibition of HIV-1 infection. In this study, the antiviral function of a zymolytic grain based extract (ZGE) was detected in vitro and in rats, and the antiviral mechanism was investigated. Results showed that ZGE had an inhibition effect on HIV-1 infection in vitro with low cytotoxic effects. The study of the mechanism demonstrated that this functional food possibly acted on the viral surface structure protein gp120 which is responsible for cell binding, as well as on the postattachment stage of the virus. The sera of model rats administrated with this food by gavage presented anti-infection abilities against HIV-1 in vitro during a serum concentration associated period of time. These findings provide valuable insights into the application of ZGE on the control of viral load, which may contribute to future anti-HIV treatment with less adverse effects.