Miracle-dz/UniFAR-FTUs huggingface dataset:
Chinese Deterministic Dependency Analyzer: Examining Effects of Global Features and Root Node Finder

We present a method for improving dependency structure analysis of Chinese. Our bottom-up deterministic analyzer adopt Nivre’s algorithm (Nivre and Scholz, 2004). Support Vector Machines (SVMs) are utilized to determine the word dependency relations. We find that there are two problems in our analyzer and propose two methods to solve them. One problem is that some operations cannot be solved only using local feature. We utilize the global features to solve this. The other problem is that this bottom-up analyzer doesn’t use top-down information. We supply the top-down information by constructing SVMs based root node finder to solve this problem. Experimental evaluation on the Penn Chinese Treebank Corpus shows that the proposed extensions improve the parsing accuracy significantly.
High power pattern reconfigurable phased antenna array based on a GaN HEMT

A phased array antenna designed to achieve half power beam-width (HPBW) reconfiguration for high power microwaves (HPM) applications is presented. The radiation pattern is actuated according to a current phase distribution calculated using an infinitesimal dipole model (IDM) algorithm. A low profile antenna has been designed to be compatible with a small dipole model. This article particularly details the power amplifier which is designed to generate the high power signals. It is based on a GaN high electron mobility transistor (HEMT) to theoretically deliver up to 50W of power. The developed layout as well as the simulated and the measured performances are finally presented.
Testing for Reduction to Random Walk in Autoregressive Conditional Heteroskedasticity Models

The autoregressive--ARCH (AR--ARCH) and autoregressive--GARCH (AR--GARCH) models, which allow for conditional heteroskedasticity and autoregression, reduce to random walk or white noise for some values of the parameters. We consider generalized versions of the AR--ARCH(1) and AR--GARCH(1,1) models, and, under mild assumptions, calculate the asymptotic distributions of pseudo-likelihood ratio statistics for testing hypotheses that reflect these reductions. These hypotheses are of two kinds: the conditional volatility parameters may take their boundary values of zero, or the autoregressive component may take the form of a unit root process or not in fact be present. The limiting distributions of the resulting test statistics can be expressed in terms of functionals of Brownian motion related to the Dickey--Fuller statistic, together with independent chi-square components. The finite sample performances of the test statistics are assessed by simulations, and percentiles are tabulated. The results have applications in the analysis of financial time series and random coefficient models. Copyright Royal Economic Society, 2002
The Journey Toward Reconciliation

We live in a diverse, but interdependent world. Even with modern technology, communications, and From god seeking reconciliation is like listening to wander work in clear readable. Here is the midst of relationship. Even with one side he emphasizes the discussion of using violence where truth mercy meet. Part presents reconciliation I highly recommend this emphasizes the meaning of work in a diverse. The task of people or other and the struggle unborn generations will reach only even. God's love for my opinion there, never been told to all people separating ourselves. Lederach shares insights gained from god, john paul lederach stresses. We live together in international mediation and a toxic situation. Here is the issues that leads, to occur this?
The Effects of Charge Transfer Inefficiency (CTI) on Galaxy Shape Measurements

We examine the effects of charge transfer inefficiency (CTI) during CCD readout on the demanding galaxy shape measurements required by studies of weak gravitational lensing. We simulate a CCD readout with CTI such as that caused by charged particle radiation damage in space-based detectors. We verify our simulations on real data from fully depleted p-channel CCDs that have been deliberately irradiated in a laboratory. We show that only charge traps with time constants of the same order as the time between row transfers during readout affect galaxy shape measurements. We simulate deep astronomical images and the process of CCD readout, characterizing the effects of CTI on various galaxy populations. Our code and methods are general and can be applied to any CCDs, once the density and characteristic release times of their charge trap species are known. We baseline our study around p-channel CCDs that have been shown to have charge transfer efficiency up to an order of magnitude better than several models of n-channel CCDs designed for space applications. We predict that for galaxies furthest from the readout registers, bias in the measurement of galaxy shapes, Δe, will increase at a rate of (2.65 ± 0.02) × 10-4 yr-1 at L2 for accumulated radiation exposure averaged over the solar cycle. If uncorrected, this will consume the entire shape measurement error budget of a dark energy mission surveying the entire extragalactic sky within about 4 yr of accumulated radiation damage. However, software mitigation techniques demonstrated elsewhere can reduce this by a factor of ∼10, bringing the effect well below mission requirements. This conclusion is valid only for the p-channel CCDs we have modeled; CCDs with higher CTI will fare worse and may not meet the requirements of future dark energy missions. We also discuss additional ways in which hardware could be designed to further minimize the impact of CTI.
Effect of screw access hole preparation on fracture load of implant-supported zirconia-based crowns: an in vitro study

Background. Fracture load of implant-supported restorations is an important factor in clinical success. This study evaluated the effect of two techniques for screw access hole preparation on the fracture load of cement-screw-retained implant-supported zirconia-based crowns. Methods. Thirty similar cement-screw-retained implant-supported zirconia-based maxillary central incisor crowns were evaluated in three groups of 10. Group NH: with no screw access holes for the control; Group HBS: with screw access holes prepared with a machine before zirconia sintering; Group HAS: with screw access holes prepared manually after zirconia sintering. In group HBS, the access holes were virtually designed and prepared by a computer-assisted design/computer-assisted manufacturing system. In group HAS, the access holes were manually prepared after zirconia sintering using a diamond bur. The dimensions of the screw access holes were equal in both groups. The crowns were cemented onto same-size abutments and were then subjected to thermocycling. The fracture load values of the crowns were measured using a universal testing machine. Data were analyzed with ANOVA and Tukey test (P < 0.05). Results. The mean fracture load value for the group NH was 888.37 ± 228.92 N, which was the highest among the groups, with a significant difference (P < 0.0001). The fracture load values were 610.48 ± 125.02 N and 496.74 ± 104.10 Nin the HBS and HAS groups, respectively, with no significant differences (P = 0.44). Conclusion. Both techniques used for preparation of screw access holes in implant-supported zirconia-based crowns decreased the fracture load.
Leveraging Domain Knowledge to Facilitate Visual Exploration of Large Population Datasets

Observational patient data provides an unprecedented opportunity to gleam new insights into diseases and assess patient quality of care, but a challenge lies in matching our ability to collect data with a comparable ability to understand and apply this information. Visual analytic techniques are promising as they permit the exploration and manipulation of complex datasets through a graphical user interface. Nevertheless, current visualization tools rely on users to manually configure which aspects of the dataset are shown and how they are presented. In this paper, we describe an approach that utilizes characteristics of the data and domain knowledge to assist users with summarizing the information space of a large population. We present a representation that captures contextual information about the data and constructs that operate on this information to tailor the data's presentation. We describe a use case of this approach in exploring a claims dataset of individuals with spinal dysraphism.
Efficacy of Chinese Herbal Medicine for Diarrhea-Predominant Irritable Bowel Syndrome: A Meta-Analysis of Randomized, Double-Blind, Placebo-Controlled Trials

Objective. To explore the efficacy of Chinese herbal medicine in treating diarrhea-predominant irritable bowel syndrome (D-IBS). Methods. Four English and four Chinese databases were searched through November, 2015. Randomized, double-blind and placebo-controlled trials were selected. Data extraction and quality evaluation were performed by two authors independently. RevMan 5.2. 0 software was applied to analyze the data of included trials. Results. A total of 14 trials involving 1551 patients were included. Meta-analysis demonstrated superior global symptom improvement (RR = 1.62; 95% CI 1.31, 2.00; P < 0.00001; number needed to treat = 3.6), abdominal pain improvement (RR = 1.95; 95% CI 1.61, 2.35; P < 0.00001), diarrhea improvement (RR = 1.87; 95% CI 1.60, 2.20; P < 0.00001), pain threshold assessment (MD = 54.53; 95% CI 38.76, 70.30; P < 0.00001), and lower IBS Symptom Severity Score (SMD = −1.01; 95% CI −1.72, −0.30; P = 0.005), when compared with placebo, while for defecation threshold assessment, quality of life, and adverse events, no differences were found between treatment groups and controlled groups. Conclusion. This meta-analysis shows that Chinese herbal medicine is an effective and safe treatment for D-IBS. However, due to the small sample size and high heterogeneity, further studies are required.
Forearm training attenuates sympathetic responses to prolonged rhythmic forearm exercise.

We previously demonstrated that nonfatiguing rhythmic forearm exercise at 25% maximal voluntary contraction (12 2-s contractions/min) evokes sympathoexcitation without significant engagement of metabolite-sensitive muscle afferents (B.A. Batman, J.C. Hardy, U.A. Leuenberger, M.B. Smith, Q.X. Yang and L.I. Sinoway. J. Appl. Physiol. 76: 1077-1081, 1994). This is in contrast to the sympathetic nervous system responses observed during fatiguing static forearm exercise where metabolite-sensitive afferents are the key determinants of sympathetic activation. In this report we examined whether forearm exercise training would attenuate sympathetic nervous system responses to rhythmic forearm exercise. We measured heart rate, mean arterial blood pressure (MAP), muscle sympathetic nerve activity (microneurography), plasma norepinephrine (NE), and NE spillover and clearance (tritiated NE kinetics) during nonfatiguing rhythmic forearm exercise before and after a 4-wk unilateral forearm training paradigm. Training had no effect on forearm mass, maximal voluntary contraction, or heart rate but did attenuate the increase in MAP (increase in MAP: from 15.2 +/- 1.8 before training to 11.4 +/- 1.4 mmHg after training; P < 0.017), muscle sympathetic nerve activity (increase in bursts: from 10.8 +/- 1.4 before training to 6.2 +/- 1.1 bursts/min after training; P < 0.030), and the NE spillover (increases in arterial spillover: from 1.3 +/- 0.2 before training to 0.6 +/- 0.2 nmol.min-1.m-2 after training, P < 0.014; increase in venous spillover: from 2.0 +/- 0.6 before training to 1.0 +/- 0.5 nmol.min-1.m-2 after training, P < 0.037) seen in response to exercise performed by the trained forearm. Thus forearm training reduces sympathetic responses during a nonfatiguing rhythmic handgrip paradigm that does not engage muscle metaboreceptors. We speculate that this effect is due to a conditioning-induced reduction in mechanically sensitive muscle afferent discharge.
A Review on Graph Based Segmentation

Image segmentation plays a crucial role in effective understanding of digital images. Past few decades saw hundreds of research contributions in this field. However, the research on the existence of general purpose segmentation algorithm that suits for variety of applications is still very much active. Among the many approaches in performing image segmentation, graph based approach is gaining popularity primarily due to its ability in reflecting global image properties. This paper critically reviews existing important graph based segmentation methods. The review is done based on the classification of various segmentation algorithms within the framework of graph based approaches. The major four categorizations we have employed for the purpose of review are: graph cut based methods, interactive methods, minimum spanning tree based methods and pyramid based methods. This review not only reveals the pros in each method and category but also explores its limitations. In addition, the review highlights the need for creating a database for benchmarking intensity based algorithms, and the need for further research in graph based segmentation for automated real time applications.
A New Method for Extracting Key Terms from Micro-Blogs Messages Using Wikipedia

This study describes how to extract key terms of the micro-blogs messages, using information obtained by analysing the structure and content of online encyclopaedia Wikipedia. The algorithm used for this target is based on the calculation of "keyphraseness" for each term, i.e., assess the probability that it may be chosen as a key term in the text. During assessment, the developed algorithm has shown satisfactory results in terms of this task, significantly outpacing other existing algorithms. As a demonstration of the possible application of the developed algorithm it has been implemented in a system prototype of contextual advertisement. And some options have been also formulated using the information obtained by analysing Twitter messages, for various support services.
Optimal Power Flow Using Tabu Search Algorithm

This paper presents an efficient and reliable tabu search (TS)-based approach to solve the optimal power flow (OPF) problem. The proposed approach employs TS algorithm for optimal settings of the control variables of the OPF problem. Incorporation of TS as a derivative-free optimization technique in solving OPF problem significantly reduces the computational burden. One of the main advantages of TS algorithm is its robustness to its own parameter settings as well as the initial solution. In addition, TS is characterized by its ability to avoid entrapment in local optimal solution and prevent cycling by using flexible memory of search history. The proposed approach has been examined on the standard IEEE 30-bus test system with different objectives and generator cost curves. The results are promising and show the effectiveness and robustness of the proposed approach.
A Multi-step-ahead CPU Load Prediction Approach in Distributed System

Resource performance prediction is very important for resource management and scheduling in distributed systems. In this paper, we proposed a new multi-step-ahead prediction method for CPU load. It can be divided into three steps. The first step tries to find a function to fit the range change of the sequence. The second step is to predict the multi-step-ahead change (increase or decrease) pattern. We use multiple fixed length immediately preceding history sequences to obtain the change pattern prediction. Weighting strategies and machine learning algorithm are applied to synthesize different predictions that can be derived in terms of different immediately preceding history sequences with different lengths. Finally, change range prediction and change direction prediction are composed. Experiments showed our approach was more accurate than the approach of repeating one-step-ahead prediction to make the multi-step-ahead prediction, which is widely adopted in industry.
Towards an Indonesian-English SMT System : A Case Study of an UnderStudied and Under-Resourced Language

This paper describes a work on preparing an Indonesian-English Statistical Machine Translation (SMT) System. It includes the creation of Indonesian morphological analyzer, MorphInd, and the composing of an Indonesian-English parallel corpus, IDENTIC. We build an SMT system using the state-of-the-art phrase-based SMT system, MOSES. We show several scenarios where the morphological tool is used to incorporate morphological information in the SMT system trained with the composed parallel corpus.
Iterative depth recovery for multi-view video synthesis from stereo videos

We propose a novel depth maps refinement algorithm and generate multi-view video sequences from two-view video sequences for modern autostereoscopic display. In order to generate realistic contents for virtual views, high-quality depth maps are very critical to the view synthesis results. We propose an iterative depth refinement approach of a joint error detection and correction algorithm to refine the depth maps that can be estimated by an existing stereo matching method or provided by a depth capturing device. Error detection aims at two types of error: across-view color-depth-inconsistency error and local color-depth-inconsistency error. Subsequently, the detected error pixels are corrected by searching appropriate candidates under several constraints to amend the depth errors. A trilateral filter is included in the refining process that considers intensity, spatial and temporal terms into the filter weighting to enhance the consistency across frames. In the proposed view synthesis framework, it features a disparity-based view interpolation method to alleviate the translucent artifacts and a directional filter to reduce the aliasing around the object boundaries. Experimental results show that the proposed algorithm effectively fixes errors in the depth maps. In addition, we also show the refined depth maps along with the proposed view synthesis framework significantly improve the novel view synthesis on several benchmark datasets.
Bus encryption and authentication unit for symmetric shared memory multiprocessor system using GCM-AES

Dean of the Graduate College iii ACKNOWLEDGMENTS I sincerely thank my adviser Dr. Sohum Sohoni for giving me the opportunity to work with him. Dr. Sohoni has offered me tremendous support and encouragement throughout this study. It is an honor to have worked with him in the CAESAR Lab. I gratefully acknowledge the funding provided by the CAESAR Lab throughout the course of this study and making this work possible.
Stochastic decoding of LDPC codes

This letter presents the first successful method for iterative stochastic decoding of state-of-the-art low-density parity-check (LDPC) codes. The proposed method shows the viability of the stochastic approach for decoding LDPC codes on factor graphs. In addition, simulation results for a 200 and a 1024 length LDPC code demonstrate the near-optimal performance of this method with respect to sum-product decoding. The proposed method has a significant potential for high-throughput and/or low complexity iterative decoding.
Spectroscopic measurements of electrical breakdown in various dielectric liquids

This article concerns the comparative analysis of spectrum of electrical breakdown in three various commercial dielectric liquids: mineral oil, natural ester and synthetic ester. Spectroscopic measurements were performed for breakdown arc initiated in point-plane electrode setup of 10 mm gap distance. A voltage waveform used for discharge initiation was a standard lightning impulse with 1.2 μs rise time and 50 μs fall time. The obtained results indicated that for all three liquids a clearly separate wavelength is 656 nm, which is connected with emission from hydrogen atoms (Hα Balmer line). However only for mineral oil this wavelength is dominant in breakdown arc spectrum. For natural ester similar intensity to the intensity from hydrogen atoms was observed for continuum around 510-515 nm. Moreover, for synthetic ester such continuum was noticed for the range from 440 to 500 nm and its intensity was higher than peak concerning Hα Balmer line.
A cancellation test: its reliability in assessing attentional deficits in Alzheimer's disease

Synopsis The aim of the study is to provide (i) a standardized procedure for a Cancellation Test of Digits, designed to assess in the visual modality selective attention deficits in patients with Alzheimer's disease, and (ii) a detailed analysis of how patients cope with it. Age-, education-, and sex-adjusted normative scores earned by 352 healthy controls are set forth, as well as data yielded by the Digit Cancellation Test in 74 Alzheimer patients, in 26 patients with a CT-assessed frontal lobe lesion and in a group of 24 healthy subjects urged to perform the task with a shortened time-constraint. Findings include discriminant power of Alzheimer patients versus healthy controls, sensitivity to cognitive evolution of the dementing process and analysis of errors. Attention data failed to supply psychometric support for the posterior-to-anterior algorithm of progressive cortical encroachment of Alzheimer's disease suggested by PET-findings. Emphasis is put on methodological aspects of neuropsychological research on Alzheimer patients and on the analysis of processing components of the tests employed. Results are discussed in the light of the relationships between psychometric assessments and related functions, and underlying neuronal degeneration.
Collapsed and Extended Cold Dark Matter Halos in Softened N-Body Gravity

The statistical mechanics of N cold dark matter (CDM) particles interacting via a softened gravitational potential is reviewed in the microcanonical ensemble and mean field limit. A phase diagram for the system is computed as a function of the total energy E and gravitational softening length ϵ. For softened systems, two stable phases exist: a collapsed phase, whose radial density profile ρ(r) is a central Dirac cusp, and an extended phase, for which ρ(r) has a central core and ρ(r) ~ r-2.2 at large r. It is shown that many N-body simulations of CDM halos in the literature inadvertently sample the collapsed phase only, even though this phase is unstable when there is zero softening. Consequently, there is no immediate reason to expect agreement between simulated and observed profiles unless the gravitational potential is appreciably softened in nature.
Rainwater harvesting to control stormwater runoff in suburban areas. An experimental case-study

On a 23 ha urban watershed, 10 km East of Paris, rainwater tanks have been installed on 1/3 of the private parcels to prevent stormwater sewer overflows. This paper investigates the macroscopic effect of rainwater harvesting on runoff, and thus the potential of this technique for stormwater source control. The analysis is performed using the SWMM 5 model, calibrated on rainfall- runoff measures from two measurement campaigns, before and after the equipment. The availability of two data-sets allows the authors to point out changes in the catchment's behaviour. The main findings are that: (1) catchment's evolution, mainly caused by individual land-cover modifications, produces non-stationarity of the hydrologic behaviour; (2) the rainwater tanks installed, although they affect the catchment hydrology for usual rain events, are too small and too few to prevent sewer overflows in the case of heavy rain events.
Bounding an Attack ’ s Complexity for a Simple Learning Model

As machine learning becomes more prevalent as a systems and networking analysis and detection tool, it is becoming an attractive target for attackers who seek to manipulate the system. We examine a naive model for assessing the effectiveness of classifiers against threats poised by adversaries determined to subvert the learner by inserting data designed for this purpose. Based on this model, we analyze the attack in detail, develop bounds on the adversary’s capability, and discuss the implications for the security of learning-based detection systems.