Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved Structure Regularization for Chinese Part-of-Speech Tagging

Chinese part-of-speech (POS) tagging is important for Chinese NLP applications. While Chinese POS tagging is typically casted as a sequential tagging task, we find that it is easy to be structurally overfitting on the training data. We propose an “improved structure regularization (ISR)” method for Chinese POS tagging, which regularize the training sample into multiple mini-samples. By regularizing the training samples, we can simplify the structures, further improve the accuracy, and at the same time accelerate the training speed of the tagger. Experiments on standard Chinese POS tagging benchmark dataset show that our tagger achieves 95.56% on the test data, and at the same time with a by-product of 5× faster training speed. To our knowledge, this result is better than the existing best report.
An Empirical Assessment of the MODIS Land Cover Dynamics and TIMESAT Land Surface Phenology Algorithms

Observations of vegetation phenology at regional-to-global scales provide important information regarding seasonal variation in the fluxes of energy, carbon, and water between the biosphere and the atmosphere. Numerous algorithms have been developed to estimate phenological transition dates using time series of remotely sensed spectral vegetation indices. A key challenge, however, is that different algorithms provide inconsistent results. This study provides a comprehensive comparison of start of season (SOS) and end of season (EOS) phenological transition dates estimated from 500 m MODIS data based on two widely used sources of such data: the TIMESAT program and the MODIS Global Land Cover Dynamics (MLCD) product. Specifically, we evaluate the impact of land cover class, criteria used to identify SOS and EOS, and fitting algorithm (local versus global) on the transition dates estimated from time series of MODIS enhanced vegetation index (EVI). Satellite-derived transition dates from each source are compared against each other and against SOS and EOS dates estimated from PhenoCams distributed across the Northeastern United States and Canada. Our results show that TIMESAT and MLCD SOS transition dates are generally highly correlated (r = 0.51-0.97), except in Central Canada where correlation coefficients are as low as 0.25. Relative to SOS, EOS comparison shows lower agreement and higher magnitude of deviations. SOS and EOS dates are impacted by noise arising from snow and cloud contamination, and there is low agreement among results from TIMESAT, the MLCD product, and PhenoCams in vegetation types with low seasonal EVI amplitude or with irregular EVI time series. In deciduous forests, SOS dates from the MLCD product and TIMESAT agree closely with SOS dates from PhenoCams, with correlations as high as 0.76. Overall, our results suggest that TIMESAT is well-suited for local-to-regional scale studies because of its ability to tune algorithm parameters, which makes it more flexible than the MLCD product. At large spatial scales, where local tuning is not feasible, the MLCD product provides a readily available data set based on a globally consistent approach that provides SOS and EOS dates that are comparable to results from TIMESAT.
Applications of Telemedicine on the Integral Management of Chronic Obstructive Pulmonary Disease : A Systematic Review

Introduction: Chronic Obstructive Pulmonary Disease is a common, preventable and treatable disease. It is currently the 4th cause of mortality worldwide with an upward trend. It is a under diagnosed entity, which implies a high cost to Public Health, and a huge loss of quality of life for the people who suffer it. Currently, there is no effective screening program, and follow-up is a difficult task. Methods: A systematic review was made of articles related to the management of COPD based on the use of the technologies. The databases used were: MEDLINE, Web of Science and Cochrane Library in addition to the websites of organizations such as WHO, SEPAR and GOLD. A total of 12 articles have been included. Results: Of the total of 12 articles, 7 found statistically significant benefits of the application of these interventions in comparison with the usual healthcare. Among the benefits there is an increase in treatment adherence, an increase in quality of life, better control of their symptoms and a reduction in the number of acute exacerbations. Conclusions: Telemedicine is a powerful tool that offers a wide range of possibilities for the management of COPD: telemonitoring, electronic coaching, early prevention of exacerbations, screening, telerehabilitation. However, the existing evidence is weak so it is required the development of powerful studies in order to establish firm conclusions.
Diversity and abundance of lactobacilli during ulcerative colitis in North Indian patients: a case control study

Lactic acid bacteria execute beneficial health effects by adhering to the intestinal epithelial layer. We compared the abundance and diversity of genus Lactobacillus in the fecal sample of ulcerative colitis (UC) patients vs. healthy control. About 40 samples belonging to moderate, severe, remission category and controls were subjected to fluorescent in situ hybridization (FISH) and quantitative Polymerase Chain Reaction (qPCR) analysis to study the abundance. To check the diversity, same samples were subjected to denaturing polyacrylamide gel electrophoresis (PAGE) fingerprinting. The FISH (p=0.0001) and qPCR (p=0.0432) analysis shows that the population of Lactobacilli was higher in severe category of samples. This was further supported by increase in lactate level by Gas chromatography (GC) (p=0.032). We observed high degree of diversity in moderate (p=0.002) and severe (p=0.003) category of patient samples as compared to controls. The profile in remission category exhibited similarities with the controls. Real time PCR analysis showed decreased expression of MUC9 (Mucin gene) (p=0.011) in biopsy samples of patients compared to controls. Summary-We speculate that increased fecal lactobacilli population during active condition is due to loss of mucin necessary for their adherence to the intestinal epithelial cell lining. This is the first report analyzing the fluctuation of lactobacilli during ulcerative colitis in North Indian individuals.
Study of Short Channel Effects for Si and GaN based n-channel FinFETs

This paper presents the comparative study of short channel effects (SCEs) namely Drain Induced Barrier Lowering (DIBL) and Subthreshold Swing (SS) for Si and GaN based n-FinFETs considering various gate dielectric materials such as SiO2, SiON, Al2O3 and La2O3. These simulation results are based on the self consistent solution of Poisson and drift-diffusion equations which assumes the saturated carrier velocity in the channel for all the materials. It has been observed that GaN based n-FinFET has the excellent capability of suppressing the SCEs for all the gate dielectric materials relative to Si based n-FinFET. However, for both Si and GaN, La2O3 plays an effective role in reducing the DIBL and SS. Keywords—Double gate FinFET, short channel effects (SCEs); lanthanum oxide (La2O3) drain induced barrier lowering (DIBL); Subthreshold swing (SS).
Hygro-thermochemical modeling of high-performance concrete . II : Numerical implementation , calibration , and validation

This paper presents the numerical implementation, calibration, and validation of the hygro-thermochemical model formulated theoretically in the companion paper [Di Luzio G, Cusatis G. Hygrothermo-chemical modeling of high-performance concrete. I: Theory. Cem Concr Compos, in press, doi:10.1016/j.cemconcomp. 2009.02. 015. ]. Calibration and validation are based on experimental data gathered from the literature and relevant to hydration, self-desiccation, and drying of standard and high-performance concrete with and without silica fume. 2009 Elsevier Ltd. All rights reserved.
Study of Wi-Fi Fingerprint-Based Indoor Positioning on a smartphone

摘 要) Nowadays, there is a high demand of Location Based Services (LBS) for indoor environments. Because the widely used Global Positioning System (GPS) is unavailable indoors, many technologies and methods have been investigated to address this problem. Indoor positioning based on Wi-Fi fingerprinting has attracted significant interest due to its potential to obtain high accuracy at low costs. It can be applied to any indoor scenario where Wi-Fi networks are deployed without any additional hardware. This thesis first examines the current developments in the field of indoor positioning and it investigates the problems with Wi-Fi fingerprinting in particular. In a second stage an Indoor Positioning System (IPS) is developed based on a novel implementation using a modified Weighted K-Nearest-Neighbors (WKNN) algorithm with prior Spearman’s Rank Correlation Coefficient (SRCC) calculation. The proposed positioning algorithm also takes into account the number of signals being omitted during localization. Therefore, unreliable results have a smaller impact on the final result. The proposed system consists of two parts: an Android smartphone application and a webserver provided with the proposed algorithm written in Erlang. The proposed IPS achieves an exceptional accuracy with an average positioning error of approximately 80 cm using an up-to-date fingerprint database. On the basis of the results of this research, it can be concluded that it is possible to use Wi-Fi fingerprinting for indoor positioning to obtain a state-of-the-art accuracy.
Analyzing Behavior Intention of Customer towards the Adoption of Self-ticketing on CGV Cinemas by Using UTAUT2: (Case Study on CGV Cinemas Bandung)

The industry movie in Indonesia in 2017 saw an increase in audience of 42.7 million people. This is a number of dramatic improvements compared to last year, namely the Head of the Creative Economy Agency's 16 million viewers said sentence. Moreover, CGV cinema's revenue noted that in 2017 it increased by 47.30% from the previous income. CGV cinema has expanded 16 new cinemas to be spread in the city of Indonesia and in 2017 this was an amazing year for the company because it was able to gain operating profit for the first time. However, the researchers see that the use of the self-ticketing machine in Bandung is still less interested. This is seen from the results of my interview with CGV manager Paris van java Bandung about 70% of customers still using conventional ticket purchases. This study analyzes factors influencing behavior intent of self-ticketing in Bandung CGV cinema. The researcher used a modified Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model which eliminated price value and added trust variables. There are 7 variables proposed in this study, which are Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Condition, Hedonic Motivation, Habit, Trust. This study using qualitative method; therefore, the data collected through an online questionnaire with 387 respondent and the respondents aged 15-60 years ever try use self-ticketing. The data obtained will be tested for reliability and validity using SPSS. The model analysis used in his study is a Variance Based Structural Equation Modeling with a Partial Least Square (PLS). The result showed that Trust, Habit, Facilitating Condition, Hedonic Motivation, Performance Expectancy has a significant influence towards Behavioral Intention.
Robust Pricing in Dynamic Mechanism Design

Motivated by the repeated sale of online ads via auctions, optimal pricing in repeated auctions has attracted a large body of research. While dynamic mechanisms offer powerful techniques to improve on both revenue and efﬁciency by optimizing auctions across different items, their reliance on exact distributional information of buyers’ valuations (present and future) limits their use in practice. In this paper, we propose robust dynamic mechanism design . We develop a new framework to design dynamic mechanisms that are robust to both estimation errors in value distributions and strategic behavior. We apply the framework in learning environments, leading to the ﬁrst policy that achieves provably low regret against the optimal dynamic mechanism in contextual auctions, where the dynamic benchmark has full and accurate distributional information.
Efficient Neural Architecture Search for Language Modeling

Neural networks have achieved great success in many difficult learning tasks like image classification, speech recognition and natural language processing. However, neural architectures are hard to design, which requires lots of knowledge and time of human experts. Therefore, there has been a growing interest in automating the process of designing neural architectures. Though these searched architectures have achieved competitive performance on various tasks, the efficiency of NAS still needs to be improved. Moreover, current neural architecture search approach disregards the dependency between a node and its predecessors and successors. This thesis builds upon BayesNAS which employs the classic Bayesian learning method to search for CNN architectures, and extends it to the problem of neural architecture search for recurrent architectures. Hierarchical sparse priors are used to model the architecture parameters to alleviate the dependency issue. Since the update of posterior variance is based on Laplace approximation, an efficient method to compute the Hessian of recurrent layer is proposed. We can find candidated architectures after training the over-parameterized network for only one epoch. Our experiments on Penn Treebank and WikiText-2 show that competitive architectures can be found in 0.3 GPU days using a single GPU for language modeling task. We find that our algorithm is more efficient than state-of-the-art.
Investigate the Conduction Path of Stakeholder Conflict of Urban Regeneration Sustainability in China: the Application of Social-Based Solutions

Urban regeneration, as an important way to enhance urban sustainable development capacity, is advancing at a high speed in China. However, urban regeneration involves various stakeholders, and there are frequent conflicts between these stakeholders due to the vast differences in their interests. When conflicts among stakeholders are not effectively controlled, they can have serious negative social and economic impacts, such as increased pressure on the government to maintain stability, increased costs to developers and reduced willingness of property owners to participate. These are all critical factor affecting the sustainability of urban regeneration. Therefore, this paper explored the mechanism underlying stakeholder conflict conduction in urban regeneration. Next, a literature review and case study were conducted to identify key conflict factors. Then, the factors of stakeholder conflict were assessed using questionnaire survey. Finally, the structural equation model (SEM) was used to analyze the pathways of stakeholder conflict conduction in urban regeneration; and 35 conflict conduction paths were found. Based on Pareto’s Law, 7 of the 35 stakeholder conflict paths were identified as critical paths with coefficients between 0.245–0.364. Empirical results revealed that different types of conflict factors have different impacts on stakeholder conflict conduction, among which interest distribution and stakeholder coordination were the critical factors to be considered. The findings provide alternatives Social-Based Solutions (SBS) for resolving stakeholder conflicts and provide practical guidance for integrating stakeholders, which is important to ensuring the sustainability of urban regeneration.
Status in Frequency of Transfusion and Impact on Outcome in Cardiac Surgery

Blood transfusion is associated with increased morbidity and mortality and numerous reports have emphasised the need for reduction. Following this there is increased attention to the concept of patient blood management. However, bleeding is relatively common following cardiac surgery and is further enhanced by the continued antiplatelet therapy policy. Another important issue is that cardiopulmonary bypass leads to haemodilution and a potential blood loss. The basic role of blood is oxygen transport to the organs. The determining factors of oxygen delivery are cardiac output, haemoglobin, and saturation. If oxygen delivery/consumption is out of balance, the compensation mechanisms are simple, as a decrease in one factor results in an increase in one or two other factors. Patients with coexisting cardiac diseases may be of particular risk, but studies indicate that patients with coexisting cardiac diseases tolerate moderate anaemia and may even benefit from a restrictive transfusion regimen. Further it has been shown that patients with reduced left ventricular function are able to compensate with increased cardiac output in response to bleeding and haemodilution if normovolaemia is maintained. In conclusion the evidence supports that each institution establishes its own patient blood management strategy to both conserve blood products and maximise outcome.
Stochastic Geometry Analysis of a Class of Cooperative Relaying Protocols

Stochastic Geometry Analysis of a Class of Cooperative Relaying Protocols Sri Lakshmi Phani Balineni This thesis examines wireless relay networks that use hybrid-ARQ protocols. Relays networks efficiently combat fading and exploit the spatial diversity present in the channel. Hybrid-ARQ involves re-transmitting the signal if it is not decoded correctly. In conventional HARQ, the re-transmission comes from the source, but in cooperative HARQ the re-transmission could come from a relay that has successfully decoded the message, thus attaining transmit diversity. A Markov chain model is conceived and used to compute the effective throughput and outage probability in the presence of Rayleigh fading. The analytical results are validated with simulations. The spatial configuration of the network plays an important role in the performance of the network. The behavior of the protocols for fixed network topologies and random topologies is examined. The impact of parameters such as path loss exponent, number of relays, and Signal to Noise Ratio are determined. Spatial averaging is helpful in capturing the spatial variations present in the system. When network topology is random, the analysis proceeds by first assuming the number of relays is fixed, in which case they are drawn from a Binomial Point Process (BPP). For each network realization, the outage probability, throughput and effective throughput are found, and the spatial average of these quantities are found by averaging over a large number of network realizations. Moreover, the maximum throughput is found for each network realization, leading to a characterization of the distribution of throughputs achievable in a random network. Finally, networks with a random number of relays are considered, including the important case that the number of relays in a given area is Poisson distributed, in which case they are drawn from a Poisson Point Process (PPP).
12237 Education and Risk Compensation in Wages : A Quantile Regression Approach MARCH 2019

IZA DP No. 12237 MARCH 2019 Education and Risk Compensation in Wages: A Quantile Regression Approach This paper examines the effect of wage variation on individual wages. The results reveal that wage variation by educational classifications positively affects wages, while the skewness has a negative effect. As has been referred in previous literature on the issue, both results are consistent with the notion of wage compensation for risk-averse workers. However, our results show that the impact of wage-variation on wages is not reasonably described by a single parameter for all individuals. Such an effect is heterogeneous and varies throughout the conditional wage distribution. Indeed, the positive effect of dispersion increases, and the negative effect of skewness decreases, as we move up on the conditional wage distribution. Apparently, those at the upper end of the conditional wage distribution have both higher risk-aversion and higher affection for skewness. JEL Classification: J31, J33
PART-BASED FEATURES OF VEHICLE IMAGES

Part-based image representation is to represent an object as the combination of partial features of an object or partial shapes of an object. Non-negative matrix factorization (NMF) is one of representative part-based decomposition mehtods to exploit local feature. We apply three approaches of NMF to the representation and the recognition of vehicle images. The recognition rate is about 89.3% using NMF of 150 basis vectors and learning vector quantization (LVQ) neural network. Keywords—local feature, non-negative matrix factorization, occlusion, part-based representation, vehicle recognition.
1 ECONOMISTS : TRUTH-SEEKERS OR RENT-SEEKERS ?

This paper proposes to extend economic analysis to the process of production of scientific knowledge in general, and of economic knowledge in particular. The model which is outlined here is based upon two fundamental assumptions: that the members of a scientific discipline can agree on a ‘methodological constitution’ (a system of methodological norms which make it compulsory to accept some data, hypotheses or theories when they have passed some predetermined tests), and that, when disagreement is allowed, the capacity to form coalitions among scientists tends to promote the epistemic efficiency of research. It is also argued that economic science presents some obstacles to the successful application of these mechanisms.
In Situ Imaging of Cold Atomic Gases

In general, the complex atomic susceptibility, that dictates both the amplitude and phase modulation imparted by an atom on a probing monochromatic light source, is highly dependent upon the local magnetic environment of the atom. While it is of great interest to study the dynamics of cold and ultra-cold atomic gases in strongly confining magnetic traps, the spatially dependent, and often quite complex, vector fields within these traps makes direct imaging difficult. Several novel techniques have been developed and implemented within the past two decades to image dense atomic clouds, not only in situ, but also non-destructively. In this letter we present two of these methods (dark-ground imaging and phase contrast imaging) and propose a new, third method that is designed to image few-atom clouds such as those found in modern, chip-based microtraps. odern experiments conducted on cold and ultracold atomic gases, be they bosonic or fermionic, rely heavily on probing the density profile of the system via the light-matter interaction. Traditional imaging techniques require each atom in the system be placed in a known, constant magnetic field; this requirement is often at odds with the preference that the system be probed in situ. Advanced imaging techniques were developed shortly after the first observations of Bose-Einstein condensation (BEC) that enabled the direct, non-destructive imaging of dense atomic clouds in situ [1,2]. These techniques, however, were developed to address the problem of very dense atomic clouds with optical densities much greater than 1 (typically >100) and are ill-suited to the low atom numbers typically found in modern chip-based microtraps. In general, the atomic scattering cross section and, by extension, the complex refractive index within a gas of neutral atoms depends upon both the magnitude and direction of the local magnetic field [3]. It is the goal of in situ imaging to remove this dependence, resulting in a constant effective cross section for all atoms within a magnetic trap. ATOMIC ABSORPTION IMAGING A laser of initial intensity passing through a general absorbing medium can be described by the equation: