Miracle-dz/UniFAR-FTUs huggingface dataset:
Segment-Level Sequence Modeling using Gated Recursive Semi-Markov Conditional Random Fields

Most of the sequence tagging tasks in natural language processing require to recognize segments with certain syntactic role or semantic meaning in a sentence. They are usually tackled with Conditional Random Fields (CRFs), which do indirect word-level modeling over word-level features and thus cannot make full use of segment-level information. Semi-Markov Conditional Random Fields (Semi-CRFs) model segments directly but extracting segment-level features for Semi-CRFs is still a very challenging problem. This paper presents Gated Recursive Semi-CRFs (grSemi-CRFs), which model segments directly and automatically learn segmentlevel features through a gated recursive convolutional neural network. Our experiments on text chunking and named entity recognition (NER) demonstrate that grSemi-CRFs generally outperform other neural models.
Adaptive spline neural networks for signal processing applications

In this paper, we study the properties of a new kind of real and complex domain artificial neural networks called adaptive spline neural networks (ASNN), which are able to adapt their activation functions by varying the control points of a Catmull-Rom cubic spline. Most of all, we are interested in generalization capability and we can show that this architecture can be seen as a sub-optimal realization of the additive spline based model obtained by the reguralization theory. This new kind of neural network can be implemented as a very simple structure being able to improve the generalization capabilities using few training epochs. Due to its low architectural complexity this network can be used to cope with several nonlinear DSP problem at high throughput rate.
Investigating microRNA-Target Interaction-Supported Tissues in Human Cancer Tissues Based on miRNA and Target Gene Expression Profiling

Recent studies have revealed that a small non-coding RNA, microRNA (miRNA) down-regulates its mRNA targets. This effect is regarded as an important role in various biological processes. Many studies have been devoted to predicting miRNA-target interactions. These studies indicate that the interactions may only be functional in some specific tissues, which depend on the characteristics of an miRNA. No systematic methods have been established in the literature to investigate the correlation between miRNA-target interactions and tissue specificity through microarray data. In this study, we propose a method to investigate miRNA-target interaction-supported tissues, which is based on experimentally validated miRNA-target interactions. The tissue specificity results by our method are in accordance with the experimental results in the literature. Availability and Implementation Our analysis results are available at http://tsmti.mbc. nctu.edu. tw/ and http://www.stat.nctu.edu. tw/hwang/tsmti.html.
Multi Source Streaming for Robust Video Transmission in Mobile Ad-Hoc Networks

Video transmission over networks is getting increasingly important, thus upcoming network types like mobile ad-hoc networks (MANETs) can also become a suitable platform for exchanging/sharing real-time video streams. We present an approach using different sources with linear independent representations of a layered video stream for increasing the robustness in transmission. This approach is based on the scalable video coding (SVC) extensions of H.264/MPEG-4 AVC with different layers for assigning importance for transmission. Additionally a novel unequal packet loss protection (UPLP) scheme based on Raptor forward error correction codes is employed. This scheme allows for reception from different sources and benefits from it. While the reception of a single stream guarantees base quality at least, the combined reception enables play-back of video of full quality and/or lower error rates.
Semidefinite relaxation for detection of 16-QAM signaling in MIMO channels

We develop a computationally efficient approximation of the maximum likelihood (ML) detector for 16 quadrature amplitude modulation (16-QAM) in multiple-input multiple-output (MIMO) systems. The detector is based on a convex relaxation of the ML problem. The resulting optimization is a semidefinite program that can be solved in polynomial time with respect to the number of inputs in the system. Simulation results in a random MIMO system show that the proposed algorithm outperforms the conventional decorrelator detector by about 2.5 dB at high signal-to-noise ratios.
Controlling Experiment-wise Type I Error of Meta-analysis in the Solomon Four-group Design

Stouffer=s Z, a meta-analytic technique, was proposed by W. Braver and Braver (1988) for analyzing data collected from a Solomon Four-group Design. Sawilowsky, Kelley, Blair, and Markman (1994) showed that this technique produces inflated Type I error rates. Recommendations are made to control the false positive inflation of their procedure. According to Campbell and Stanley (1963), the Solomon Four-group Design (Solomon, 1949) has “higher prestige” than most other quantitative research designs, because it permits “explicit consideration of external validity factors” (p. 24). It contains both pretested and nonpretested treatment and control groups. Campbell and Stanley noted the lack of a single statistic for analyzing all of the data collected from this design. To resolve this data analysis problem, W. Braver and Braver (1988) proposed the use metaanalysis. They provided a flowchart that documents a sequence of testing procedures. The first test (Test A) is a 2×2 ANOVA on the means of the four posttests= scores, which examines the interaction of Pretest Treatment. If this test is significant, pretest sensitization is indicated, which is an undesirable situation where the outcome is confounded by the effect of the pretest (see, e.g., Willson & Putnam, 1982; Lana, 1959). W. Braver and Braver (1988) suggested a variety of followup tests (called Test B and Test C) to further investigate the nature of the pretest effects. If Test A is not significant, the sequence continues with Test D, which is a test of main effects for the treatment vs. control group. Conditioned on these two preliminary tests being non-significant, the procedure continues with Test E, an ANCOVA on the posttest scores for the treatment and control group that was pretested, with the pretest scores used as the covariate. (W. Braver & Braver, 1988, suggested other tests, referred to as Test F and Test G, which could be substituted for the ANCOVA.) If the ANCOVA is not significant, the next step is to conduct an independent samples t test on the posttest scores for the non-pretested treatment and control groups, which they referred to as Test H. A significant result of Test E (ANCOVA) or Test H (t test) indicates a significant treatment outcome. If neither of the final two classical tests (Test E and Test H) are significant, the sequence of testing concludes with Test I, Stouffer=s Z (Stouffer, et al., 1949) which is a meta-analytic procedure. W. Braver and Braver (1988) noted that nothing precludes the use of meta-analysis in
Conditions for uniform solvability of parameter-dependent Lyapunov equations with applications

We consider the problem of finding a common quadratic Lyapunov function to demonstrate stability of a family of matrices which incorporate design freedoms. Generically, this can be viewed as picking a family of controller (or observer) gains so that the family of closed-loop system matrices admits a common Lyapunov function. We provide several conditions, necessary and sufficient, for various structures of matrix families. Families of matrices containing a subset of diagonal matrices invariant under the design freedoms is also considered since this is a case that occurs in many applications. Conditions for uniform solvability of the Lyapunov equations are explicitly given and involve inequalities regarding relative magnitudes of terms in the matrices. Motivating applications of the obtained results to observer and controller designs for time-varying, switched, and nonlinear systems are highlighted.
Towards Parallel Czech-Russian Dependency Treebank

Proceedings of the Workshop on Annotation and Exploitation of Parallel Corpora AEPC 2010. Editors: Lars Ahrenberg, Jorg Tiedemann and Martin Volk. NEALT Proceedings Series, Vol. 10 (2010), 44-52. © 2010 The editors and contributors. Published by Northern European Association for Language Technology (NEALT) http://omilia.uio. no/nealt . Electronically published at Tartu University Library (Estonia) http://hdl.handle. net/10062/15893 .
POWER SYSTEM STABILITY ENHANCEMENT USING FACTS CONTROLLERS: A REVIEW

In recent years, power demand has increased substantially while the expansion of power generation and transmission has been severely limited due to limited resources and environmental restrictions. As a consequence, some transmission lines are heavily loaded and the system stability becomes a power transfer-limiting factor. Flexible AC transmission systems (FACTS) controllers have been mainly used for solving various power system steady state control problems. However, recent studies reveal that FACTS controllers could be employed to enhance power system stability in addition to their main function of power flow control. The literature shows an increasing interest in this subject for the last two decades, where the enhancement of system stability using FACTS controllers has been extensively investigated. This paper presents a comprehensive review on the research and developments in the power system stability enhancement using FACTS damping controllers. Several technical issues related to FACTS installations have been highlighted and performance comparison of different FACTS controllers has been discussed. In addition, some of the utility experience, real-world installations, and semiconductor technology development have been reviewed and summarized. Applications of FACTS to other power system studies have also been discussed. About two hundred twenty seven research publications have been classified and appended for a quick reference.
Using Cultural Brokering Strategies to Improve the Early Childhood Education of Roma, Gypsy and Traveller Children: Case Studies from the UK and Serbia

This thesis explores the use of cultural brokering to promote the inclusion of Roma children in early childhood education through examining case studies of the Traveller Education Support Services in the UK and Pedagogic Assistants in Serbia. It suggests that cultural brokers add value to systems through extending the social capital of marginalised communities by linking them with broader social institutions. It uses Bronfenbrenner’s ecological model of human development as a tool for understanding the value of integrating cultural brokers at various levels of early education, and specifically in both early education services (preschools and primary schools) as well as at municipal levels. It develops a definition of cultural brokering in early childhood education, which incorporates four key functions: 1) provision of direct support to children, families, preschools and schools; 2) liaising between communities and early education services; 3) enabling linkages of families with other necessary resources and services; and, 4) serving as advocates and role models to support social inclusion and counter discriminatory practices. It creates an argument for extending cultural brokering across early childhood education systems to support social inclusion of the most marginalised groups and illustrates the importance of strong engagement of both national and municipal governments in establishing enabling conditions. Finally, this thesis suggests that significantly improving the social inclusion of the Roma population in Europe will require earlier and more complex interventions that support children’s development well before they enter the formal education system.
Mapping Sparse Representation to State Likelihoods in Noise-Robust Automatic Speech Recognition

This paper proposes learning-based methods for mapping a sparse representation of noisy speech to state likelihoods in an automatic speech recognition system. We represent speech as a sparse linear combination of exemplars extracted from training data. The weights of exemplars are mapped to speech state likelihoods using Ordinary Least Squares (OLS) and Partial Least Squares (PLS) regression. Recognition experiments are conducted using the CHiME noisy speech database. According to the results, both algorithms can be successfully used for training the mapping. We achieve improvements over the previous binary labeling system, and recognition scores close to 70% at -6 dB SNR. Index Terms: automatic speech recognition, sparse representations, exemplar-based, regression
Demonstration of a Robot-Based Raman Spectroscopic Detector for the Identification of CBE Threat Agents

Abstract : This paper describes the feasibility demonstration of a chemical, biological and explosive (CBE) detection system based on Raman spectroscopic measurements integrated to a commercially available unmanned ground vehicle (UGV) platform. Raman detection of CBE agents is reagentless and offers the ability to detect a broad range of threats in a single measurement and is well suited to remote operation. The performance of this sensor system for the detection of chemical and biological warfare agents was validated through comparison of results from a system performance model and from laboratory testing of a breadboard system. This breadboard was successfully integrated on a Joint Architecture for Unmanned Systems (JAUS)- compliant Remotec ANDROS Wolverine UGV and the ability of the unit to target and detect a biothreat simulant on a complex background was demonstrated. High-level detector functions, as well as the reporting of results to the operator were performed through the UGV wireless communications link to the operator control unit. This work has application to the remote detection of chemical, biological and explosive agents in military/civilian medical and emergency response applications.
An Essential Role for the Saccharomyces cerevisiae DEAD-Box Helicase DHH1 in G1/S DNA-Damage Checkpoint Recovery

The eukaryotic cell cycle displays a degree of plasticity in its regulation; cell cycle progression can be transiently arrested in response to environmental stresses. While the signaling pathways leading to cell cycle arrest are beginning to be well understood, the regulation of the release from arrest has not been well characterized. Here we show that DHH1, encoding a DEAD-box RNA helicase orthologous to the human putative proto-oncogene p54/RCK, is important in release from DNA-damage-induced cell cycle arrest at the G1/S checkpoint. DHH1 mutants are not defective for DNA repair and recover normally from the G2/M and replication checkpoints, suggesting a specific function for Dhh1p in recovery from G1/S checkpoint arrest. Dhh1p has been suggested to play a role in partitioning mRNAs between translatable and nontranslatable pools, and our results implicate this modulation of mRNA metabolism in the recovery from G1/S cell cycle arrest following DNA damage. Furthermore, the high degree of conservation between DHH1 and its human ortholog suggests that this mechanism is conserved among all eukaryotes and potentially important in human disease.
Prediction of Associations between microRNAs and Gene Expression in Glioma Biology

Despite progress in the determination of miR interactions, their regulatory role in cancer is only beginning to be unraveled. Utilizing gene expression data from 27 glioblastoma samples we found that the mere knowledge of physical interactions between specific mRNAs and miRs can be used to determine associated regulatory interactions, allowing us to identify 626 associated interactions, involving 128 miRs that putatively modulate the expression of 246 mRNAs. Experimentally determining the expression of miRs, we found an over-representation of over(under)-expressed miRs with various predicted mRNA target sequences. Such significantly associated miRs that putatively bind over-expressed genes strongly tend to have binding sites nearby the 3′UTR of the corresponding mRNAs, suggesting that the presence of the miRs near the translation stop site may be a factor in their regulatory ability. Our analysis predicted a significant association between miR-128 and the protein kinase WEE1, which we subsequently validated experimentally by showing that the over-expression of the naturally under-expressed miR-128 in glioma cells resulted in the inhibition of WEE1 in glioblastoma cells.
Manipulability-based configuration evaluation of cooperative payload transport by mobile robot collectives

Interest in cooperative systems typically arises when certain tasks are either too complex to be performed by a single agent or when there are distinct benefits that accrue by cooperation of many simple agents. A quantitative examination of performance enhancement, due to the implementation of cooperation, is critical. In this paper, we focus on the development of a quantitative performance-analysis framework for a cooperative system with multiple wheeled mobile manipulators physically transporting a common payload. Each mobile manipulator module consists of a differentially-driven wheeled mobile robot with a mounted planar three-degree-of-freedom (d.o.f.) manipulator. A composite cooperative system is formed when a payload is placed at the end-effectors of multiple such modules. Such a system possesses the ability to change its relative configuration as well as accommodate relative positioning errors of the mobile bases. However, the combination of nonholonomic constraints due to the mobile bases, holonomic constraints due to the closed kinematic loops formed and the varying actuation of the joints within the cooperative system requires careful treatment for realizing the payload transport task. In this paper, we will analyze the cooperative composite system within a constrained mechanical system framework, by extending methods developed for treatment of articulated-closed-chain systems. Specifically, we will focus on the velocity-level kinematic modeling, while taking into account the nonholonomic/holonomic constraints and different joint-actuation schemes within the system. We then examine the applicability of a manipulability measure (isotropy index), to quantitatively analyze the system-level performance of the cooperative system, with these different joint-actuation schemes, with representative case-studies.Copyright © 2004 by ASME
Adult Learners and Distance Education Evaluation: Implications for Success.

This study identifies barriers to participation perceived by adults. It analyzes barriers and the factor structure underlying these barriers, and compares this structure to Cross' (1981) situational, institutional and dispositional categories. The study found six factors with no extraneous items. The six were bad experience, institutional reasons, lack of resources, course offerings, cost/benefit ratio and childcare. This complex set of findings fits with barriers established in the literature. Bad Experience, a dispositional barrier, and the Institutional factor correspond to Cross' typology. Lack of Resources and Course Offerings are spread among situational, institutional and dispositional factors. Cost/Benefit Ratio is situational and institutional. Childcare is situational. This study contributes to a complex model of deterrents to participation. A full model could be combined with existing knowledge to form a dynamic model of participation in adult education.
A Machine Learning Regression scheme to design a FR-Image Quality Assessment Algorithm

A crucial step in image compression is the evaluation of its performance, and more precisely available ways to measure the quality of compressed images. In this paper, a machine learning expert, providing a quality score is proposed. This quality measure is based on a learned classification process in order to respect that of human observers. The proposed method namely Machine Learning-based Image Quality Measurment (MLIQM) first classifies the quality using multi Support Vector Machine (SVM) classification according to the quality scale recommended by the ITU. This quality scale contains 5 ranks ordered from 1 (the worst quality) to 5 (the best quality). To evaluate the quality of images, a feature vector containing visual attributes describing images content is constructed. Then, a classification process is performed to provide the final quality class of the considered image. Finally, once a quality class is associated to the considered image, a specific SVM regression is performed to score its quality. Obtained results are compared to the one obtained applying classical Full-Reference Image Quality Assessment (FRIQA) algorithms to judge the efficiency of the proposed method.
Beamforming Codebooks for Two Transmit Antenna Systems Based on Optimum Grassmannian Packings

Precoding codebook design for limited feedback MIMO systems is known to reduce to a discretization problem on a Grassmann manifold. The case of two-antenna beamforming is special in that it is equivalent to quantizing the real sphere. The isometry between the Grassmannian G2,1ℂ and the real sphere S2 shows that discretization problems in the Grassmannian G2,1ℂ are directly solved by corresponding spherical codes. Notably, the Grassmannian line packing problem in ℂ2, namely maximizing the minimum distance, is equivalent to the Tammes problem on the real sphere, so that optimum spherical packings give optimum Grassmannian packings. Moreover, a simple isomorphism between G2,1ℂ and S2 enables to analytically derive simple codebooks in closed-form having low implementation complexity. Using the simple geometry of some of these codebooks, we derive closed-form expressions of the probability density function of the relative SNR loss due to limited feedback. We also investigate codebooks based on other spherical arrangements, such as solutions maximizing the harmonic mean of the mutual distances among the codewords, which is known as the Thomson problem. We find that in some special cases, Grassmannian codebooks based on these other spherical arrangements outperform codebooks from Grassmannian packing.
Applying Sum and Max Product Algorithms of Belief Propagation to 3D Shape Matching and Registration

3D shape matching based on meshed surfaces can be formulated as an energy function minimisation problem under a Markov random field (MRF) framework. However, to solve such a global optimisation problem is NP-hard. So research mainly focuses on approximation algorithms. One of the best known is belief propagation (BP), which has shown success in early vision and many other practical applications. In this paper, we investigate the application of both sum and max product algorithms of belief propagation to 3D shape matching. We also apply the 3D shape matching results to a 3D registration problem.
OPTIMIZATIONS OF AIRFOIL AND WING USING GENETIC ALGORITHM

The present study demonstrates how the Genetic Algorithm (GA), coupled with the CFD solvers ARC2D for 2D and KTRAN for 3D problems, can successfully be applied to the airfoil and wing aerodynamic drag minimization. The geometry of airfoil and wing sections is represented by a B-spline curve. The actual values of the coordinates of the control nodes for the B-spline curve are designated as the design variables. The NACA0012 airfoil is optimized for a free stream Mach number M∞ =0.30, at which the drag coefficient is reduced by 46.1% for a constant lift coefficient of CL = 0.55. For the corresponding straight wing, the Mach number is set at M∞ =0.80. The drag coefficient is reduced by 13.5% under the constant lift coefficient of CL = 0.30. The results demonstrates the powerful reliability and robustness of this technique.