Miracle-dz/UniFAR-FTUs huggingface dataset:
QRS complex detection in noisy holter ECG based on wavelet singularity analysis

In this paper, we propose a QRS complex detector based on the Mallat and Hwang singularity analysis algorithm which uses dyadic wavelet transform. We design a spline wavelet that is suitable for QRS detection. The scales of this decomposition are chosen based on the spectral characteristics of electrocardiogram records. By proceeding with the multiscale analysis we can find the location of a rapid change of a signal, and hence the location of the QRS complex. The performance of the algorithm was tested using the records of the MIT-BIH Arrhythmia Database. The method is less sensitive to time- varying QRS complex morphology, minimizes the problems associated with baseline drift, motion artifacts and muscular noise, and allows R waves to be differentiated from large T and P waves. We propose an original, new approach to adaptive threshold algorithm that exploits statistical properties of the observed signal and additional heuristic. The threshold is independent for each successive ECG signal window and the algorithm uses the properties of a series of distribution with a compartments class. The noise sensitivity of the new proposed adaptive thresholding QRS detector was also tested using clinical Holter ECG records from the Medical University of Bialystok. We illustrate the performance of the wavelet-based QRS detector by considering problematic ECG signals from a Holter device. We have compared this algorithm with the commercial Holter system - Del Mar's Reynolds Pathfinder on the special episodes selected by cardiologist.
Towards the Development of a Conceptual Framework for Internationalizing Higher Education Institutions (HEIs) in the Philippines

This study developed a conceptual framework for internationalizing Higher Education Institutions in the Philippines based on the conceptions and practices of internationalization from four groups of stake holders (258 students, 82 faculty, 40 non-teaching staff and 45 administrators selected from 14 HEIs in the NCR. Data were obtained using a survey questionnaire and a two-pronged instrument. The quantitative data were interpreted using frequency, percentage and weighted mean while the qualitative data were classified, coded and after which, patterns and themes were identified. Findings revealed that at the conceptual level, the stakeholders share common conceptions of internationalization in higher education institutions with some minor disagreements from the students. At the practical level, HEIs have been found to have varied processes of realizing their conceptions of internationalization. Based on these revelations, a conceptual framework for internationalizing HEIs was developed and recommended for adoption by HEIs.
Survivor Benefits and the Gender Tax-Gap in Public Pension Schemes Work Incentives and Options for Reform

Since its inception, the traditional form of providing survivor benefits through public pension schemes has lost much of its legitimacy. As a result of fundamental changes in marriage behaviour and the typical division of labour between married spouses, offering non-contributory benefits of this kind can not only be seen as inequitable. Since they usually substitute for non-derived pension entitlements based on the survivant spouse’s own contributions, they can also lead to incentive effects, especially for married women with some degree of labour force attachment, that appear to be far from optimal. The present paper highlights this problem based on empirical estimates regarding the wage elasticities of labour supply for German females vs males and shows how it could be resolved by installing a joint annuitisation of a given couple’s pension entitlements.
Simulation analysis of congestion control in WSN based on AQM

In view of the good performance of active queue management (AQM) on congestion control in wired networks, we introduce AQM algorithm into wireless sensor networks (WSN) for avoiding congestion. For studying the performance of the three AQM algorithms including RED, REM and PI in the WSN environment, we compile powerful simulation script, modify NS2 source code and simulate them using the NS2 simulator. The simulation results show that in WSN, RED and REM have their disadvantages respectively in the aspect of queue length and throughput; the performance of PI is relatively good, but there still exists queue shake because of the characteristic of wireless link.
Searching for Galileo

BIOGRAPHIES Mark L. Psiaki is a Professor in the Sibley School of Mechanical and Aerospace Engineering. He received a B.A. in Physics and M.A. and Ph.D. degrees in Mechanical and Aerospace Engineering from Princeton University. His research interests are in the areas of estimation and filtering, spacecraft attitude and orbit determination, and GNSS technology and applications. Todd E. Humphreys is a graduate student in the Sibley School of Mechanical and Aerospace Engineering. He received his B.S. and M.S. degrees in Electrical and Computer Engineering from Utah State University. His research interests are in estimation and filtering, spacecraft attitude determination, GNSS technology, and GNSS-based study of the ionosphere and neutral atmosphere.
Assessing Student Perceptions and Current Adoption of E-Textbooks

This study looks into students’ perception about E-textbooks and assess current adoption of E-textbook in a medium-size university in the Midwest of the United States. Literature reviews indicated some inconsistencies related to E-book adoptions. This study will investigate some of those inconsistencies including prior usage as factors in E-book adoption. Other factors considered in this study are: trialability, perceived values, and technology savvy. The theory of Technology Acceptance Model will be used in this study. An E-textbook adoption model is proposed and survey methodology will be used in this study. Survey will be administered among students on campus.
Optimal Detection using

Many climatic and geophysical processes are cyclostationary and exhibit appreciable cyclic (monthly, daily, etc.) variation of their statistics in addition to interannual uctuations. Utilization of this nested variation of statistics will lead to a better chance of detecting a signal in such a varying background noise eld especially when the signal is strongly phase locked with the nested cycle. In this study, a detection technique is constructed in terms of cyclostationary empirical orthogonal functions, which take the nested periodicity of noise statistics into account. To investigate the improved performance of the cyclostationary approach the developed algorithm is applied to three speci c detection examples: El Ni~ no, greenhouse warming, and sunspot uctuations. In all the test cases, signal-to-noise ratio is raised between 2 and 43% compared with that of a stationary detection technique. The variation of signal strength when a detection lter is constructed based on a di erent section of modeled noise is within the range of mean signal-to-noise ratio for small to moderate signals. There is a signi cant variation, however, of signal strength when a detection lter is constructed based on a di erent model dataset. This implies that model discrepancy is a more important factor than sampling error for the accuracy of the detection method and that climate models need to improved further in their noise statistics.
Optimal Dynamic Routing for the Wireless Relay Channel

Consider a communication network with a source, a relay and a destination. Each time interval, the source may dynamically choose between a few possible coding schemes, based on the channel state, traffic pattern and its own queue status. For example, the source may choose between a direct route to the destination and a relay-assisted scheme. Clearly, due to the difference in the performance achieved, as well as the resources each scheme uses, a sender might wish to choose the most appropriate one based on its status. In this work, we formulate the problem as a Semi-Markov Decision Process. This formulation allows us to find an optimal policy, expressed as a function of the number of packets in the source queue and other parameters. In particular, we show a general solution which covers various configurations, including different packet size distributions and varying channels. Furthermore, for the case of exponential transmission times, we analytically prove the optimal policy has a threshold structure, that is, there is a unique value of a single parameter which determines which scheme (or route) is optimal. Results are also validated with simulations for several interesting models.
Advance Notice and Job Search The Value of an Early Start

Recent studies of the effect of advance notice on jobless duration following displacement misspecify the relationship between these two variables by treating advance notice as a dummy regressor in conventional survival time models. Job search theory, however, suggests that the major impact of advance notice is not to alter the efficiency of search after job loss, but rather to allow workers to begin search before job loss. The authors develop a "sequential-regimes" job search model which allows search prior to displacement for workers with advance knowledge of layoff, with different search intensities before and after layoff. Maximum-likelihood estimates of the model are then computed using a pooled data set from the 1984 and 1986 Displaced Worker Surveys. Advance knowledge is found to significantly shorten jobless duration for most labor force groups. Using these estimates, the authors simulate the effect of various levels of advance knowledge on jobless duration. Their results indicate that relatively modest advance notice substantially benefits many displaced workers.
Attractive density: A new node similarity index of link prediction in complex networks

Link prediction plays an important role in data mining, which aims at estimating the probability of the connection between two unlinked nodes according to the information of network structure. Many link prediction methods have been proposed so far, while most of them only consider the node similarity based on individual information of common neighbors. In the perspective of interactions between common neighbors, we present a new node similarity measurement-inner attractive density of the cluster formed by common neighbors. The proposed index not only applies the effect of individual node in common neighbors set, but also considers the interactions among common neighbors. Experimental results on synthetic and real networks show that compared with the typical prediction algorithms, the proposed method enjoys impressive efficiency and effectiveness, and it improves the accuracy of prediction while maintaining low time complexity.
Foreign Students' Demand for United States Higher Education

The demand for college education is expected to decline absolutely in the decades ahead as the size of the young college eligible population declines.1 However, the supply of student slots in higher education is relatively inelastic due to a large fixed capital stock and a high proportion of tenured faculty. The result is likely to be excess capacity in American higher education in the coming decades. In response to this potential decline in demand and the difficulties in reducing their existing capacity, institutions of higher education are expected to explore alternatives for increasing or maintaining their enrollment levels. The feasible alternatives are to lower
Differential Geometric SLAM

The simultaneous localization and mapping (SLAM) problem is considered in three dimensions. The proposed algorithm, differential geometric SLAM (DG-SLAM), employs methods from differential geometry to propagate the state and map estimates. Unlike EKF SLAM, the proposed filter is provably asymptotically stable under the assumption of no measurement noise or biases. The robustness of the DG-SLAM algorithm is assessed in simulation with measurement noise. The simulation demonstrates successful localization and mapping.
Disambiguating translation strategies in MT using automatic named entity recognition

We report on the results of an experiment aimed at enabling a machine translation system to select the appropriate strategy for dealing with words and phrases which have different translations depending on whether they are used as proper names or common nouns in the source text. We used the ANNIE named entity recognition system to identify named entities in the source text and pass them to MT systems in the form of "do-not-translate" lists. A consistent gain of about 20% in translation accuracy was achieved for all tested systems. The results suggest that successful translation strategy selection is dependent on accurate segmentation and disambiguation of the source text – aspects which could be significantly improved by named entity recognition. We further suggest an automatic method for distinguishing and lexical differences in MT output that could have applications in automated MT evaluation for morphologically rich languages.
Korean Text Detection and Binarization in Color Signboards

Text detection and binarization are very important steps in text understanding. Natural scene images bring new challenges to correctly extract interested text regions. In the paper, efficient text detection and binarization methods are used to extract Korean text from color signboards of shops. First, we detect the main Korean text in color signboards by combining the horizontal edge profile in the image and some knowledge of the Korean text specified in our application. Then the detected Korean text is segmented to Korean words by using the vertical edge profile. Finally, each Korean word is fed into binarization module which uses 3-means clustering method in L*a*b* color space to extract text from the background. The experimental results show that our method successfully extracts text with low complexity and therefore can be used in the mobile devices which have limited capability.
A self-service portal for service-based applications

Enterprises today constantly seek to reduce the cost of their IT-operations. One popular approach is to outsource (parts) of these IT-operations. With the advent of Cloud computing, the outsourcing of infrastructure, runtime platforms and even whole applications has been greatly facilitated. With platforms such as Amazon's EC2 or Salesforce's Force.com customers can select from a set of pre-defined machine images or applications that they can then run on-demand. However, all these platforms employ proprietary technology that does not permit to model, offer, configure and automatically deploy applications in the cloud in a generic manner. In this paper we introduce metamodels, algorithms and tools for application vendors to describe composite service-based cloud applications independently of the provider that later offers them. We describe how customers can customize such service-based applications and how providers can automatically provision the individual services required by the application, thus offering customized applications to their customers while minimizing costs by sharing services and infrastructure across customers. We report on the architecture and implementation of our prototype and show sample applications.
Dose-Dependent Effects of Platelet-Derived Growth Factor-B on Glial Tumorigenesis

Platelet-derived growth factor (PDGF) is expressed in many different tumors, but its precise roles in tumorigenesis remain to be fully defined. Here, we report on a mouse model that demonstrates dose-dependent effects of PDGF-B on glial tumorigenesis. By removing inhibitory regulatory elements in the PDGFB mRNA, we are able to substantially elevate its expression in tumor cells using a retroviral delivery system. This elevation in PDGF-B production results in tumors with shortened latency, increased cellularity, regions of necrosis, and general high-grade character. In addition, elevated PDGF-B in these tumors also mediates vascular smooth muscle cell recruitment that supports tumor angiogenesis. PDGF receptor (PDGFR) signaling appears to be required for the maintenance of these high-grade characteristics, because treatment of high-grade tumors with a small molecule inhibitor of PDGFR results in reversion to a lower grade tumor histology. Our data show that PDGFR signaling quantitatively regulates tumor grade and is required to sustain high-grade oligodendrogliomas.
Towards Automatic Pharmacovigilance: Analysing Patient Reviews and Sentiment on Oncological Drugs

The collection, detection and monitoring of information such as side effects, adverse effects, warnings, precautions of pharmaceutical products is a challenging task. With the advent of user forums, online reviews have become a significant source of information about products. In this work, we aim to utilize pharmaceutical drugs reviews by patients on various health communities to identify frequently occurring issues. We compare these issues with food and drug administration (FDA) approved drug labels for possible improvements. We focus on Oncological drugs and develop a scalable system for mapping of interventions against indication and the respective symptoms from patient comments. Using these mappings, our system is able to compare different sections of FDA labels for recommendations. We use SVM based framework for sentiment analysis to give an overall rating to the drugs. We further incorporate aspect based sentiment analysis for finding the orientation of drug reviews for specific targets.
A Low Complexity Fading Filter Design for Multipath Rayleigh Fading Simulation

A number of different methods have been proposed and used for the simulation of Rayleigh fading. In this paper a variant of the method of filtering of the white Gaussian noise is presented where the filter design is accomplished in the analog domain and transferred into the digital domain, and implemented as an ARMA or as an AR filter. Comparisons to other methods are then made by using quantitative measures to show the merit of the method.
The use of permanent and temporary jobs across Spanish regions: Do unit labour cost differentials offer an explanation?

We study the use of permanent and temporary contracts across Spanish regions during the period 1995-2001. First we show that there are significant differences among the regional rates of permanent employment and that these differences tend to persist over time. To understand the underlying factors behind these observed differences we estimate a binary choice model for the individual probability of having a permanent contract, taking advantage of the panel data dimension of the Spanish Labour Force Survey. Our main results are that unit labour cost differentials, and thus labour productivity and total labour cost differentials, partially explain the divergence of regional permanent employment rates. Moreover, compared to the influence of regional fixed effects and other possible explanations such as sector specialisation or the presence of small firms in the region, unit labour costs explain more than two thirds of the observed variance in the permanent employment rate across Spanish regions, once all the relevant heterogeneity is taken into account.
Unemployment, Disequilibrium, and the Short Run Phillips Curve: an Econometric Approach

The paper specifies a disequilibrium model for the aggregate labor market consisting of demand and supply functions for labor, an adjustment equation for wages as well as for prices, a transactions equation and, finally, an equation that relates measured unemployment to vacancies and to excess demand. The model has a more sophisticated treatment of dynamics than earlier disequilibrium models, and uses measured unemployment as an endogenous variable. Two of the error terms are assumed to be serially correlated and the coefficients are estimated by maximum likelihood. The parameter estimates and the goodness-of-fit are satisfactory and the model's implications for the behavior of several important variables are sensible. Excess demand estimates computed in various ways are reasonable. The model is used to estimate the natural rate of unemployment as well as a short run Phillips curve. Finally, the stability properties ofthe model are analyzed by considering the eigenvalues of the system; they are found to have moduli less than one.
Magnetoelectric Response of Magnetostrictive/Piezoelectric/Magnetostrictive Laminate Composite

The theoretical analysis of magnetoelectric performances in long-type magnetostrictive/ piezoelectric/ magnetostrictive (MPM) laminate composite is presented in this paper. The magnetostrictive laminate layers are designated to be magnetized in their longitudinal direction, while the piezoelectric layer is designated to be poled in its thickness direction. In terms of the equivalent circuit, it is straightforward to obtain the magnetoelectric response characteristics such as magnetoelectric voltage coefficient, short-circuit current, internal impedance and maximum output power of the laminate composite at low frequency condition, and which are dependent on various parameters of magnetostrictive and piezoelectric materials. The derivation is a development of the theory in the literatures. A numerical calculation of Terfenol-D/PZT/Terfenol-D laminate composite is given out as an example by utilizing the theory. With the simulation, a discussion is taken on the topics of magnetoelectric laminate composite used as a magnetic sensor and an energy harvesting transducer
Salt intake of the Slovene population assessed by 24 h urinary sodium excretion

Abstract Objective To investigate average sodium excretion in 24 h urine as a marker for salt intake in the Slovene population. Design Salt intake was determined by measuring sodium excretion in 24 h urine collected from a representative sample of geographically diverse Slovene adults. Setting Slovenia. Subjects A random sample of 600 adults aged 25–65 years was generated from census data. The effective sample yield was 143 people, 42·7 % men and 57·3 % women. Results Urinary sodium excretion was significantly higher in men (220·9 (sd 86·0) mmol Na/d) than in women (169·8 (sd 73·8) mmol Na/d); t test = 14·5, P < 0·001. Average salt intake was 11·3 (sd 4·9) g/d, higher in men than in women (13·0 (sd 5·1) v. 9·9 (sd 4·3) g/d, respectively). Average intakes of salt among regions were not significantly different. Salt intake increases slightly with increasing age, but there was no significant correlation between age and salt intake. Salt intake was increased with BMI (r = 0·384, P < 0·001). Conclusions Salt intake in Slovene adults, especially in men, exceeds the WHO recommended population nutrient intake goal of 5 g by more than twofold. A national programme for reducing salt intake in Slovenia needs to be implemented through systematic efforts including public education and involving the health-care sector and the food industry.
Single-Cell Microarray Analysis in Hippocampus CA1: Demonstration and Validation of Cellular Heterogeneity

Laser capture microdissection in combination with microarrays allows for the expression analysis of thousands of genes in selected cells. Here we describe single-cell gene expression profiling of CA1 neurons in the rat hippocampus using a combination of laser capture, T7 RNA amplification, and cDNA microarray analysis. Subsequent cluster analysis of the microarray data identified two different cell types: pyramidal neurons and an interneuron. Cluster analysis also revealed differences among the pyramidal neurons, indicating that even a single cell type in vivo is not a homogeneous population of cells at the gene expression level. Microarray data were confirmed by quantitative RT-PCR and in situ hybridization. We also report on the reproducibility and sensitivity of this combination of methods. Single-cell gene expression profiling offers a powerful tool to tackle the complexity of the mammalian brain.