Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimisation of Likelihood for Bernoulli Mixture Models

The use of mixture models in statistical analysis is increasing for datasets with heterogeneity and/or redundancy in the data. They are likelihood based models, and maximum likelihood estimates of parameters are obtained by the use of the expectation maximization (EM) algorithm. Multi-modality of the likelihood surface means that the EM algorithm is highly dependent on starting points and poorly chosen initial points for the optimization may lead to only a local maximum, not the global maximum. In this thesis, different methods of choosing initialising points in the EM algorithm will be evaluated and two procedures which make intelligent choices of possible starting points and fast evaluations of their usefulness will be presented. Furthermore, several approaches to measure the best model to fit from a set of models for a given dataset, will be investigated and some lemmas and theorems are presented to illustrate the information criterion. This work introduces two novel and heuristic methods to choose the best starting points for the EM algorithm that are named Combined method and Hybrid PSO (Particle Swarm Optimisation). Combined method is based on a combination of two clustering methods that leads to finding the best starting points in the EM algorithm in comparison with the different initialisation point methods. Hybrid PSO is a hybrid method of Particle Swarm Optimization (PSO) as a global optimization approach and the EM algorithm as a local search to overcome the EM algorithm’s problem that makes it independent to starting points. Finally it will be compared with different methods of choosing starting points in the EM algorithm.
Co-ordinated Follow-Up of Transiting Planet Candidates with Robotic Telescope Facilities

Abstract There are now several large photometric surveys scanning millions of stellar light-curves for signs of planetary transits. All produce large candidate lists with a high false alarm rate, so that further observations are required to confirm new detections. One such survey, SuperWASP, produced ~150 candidates during the 2007–2008 season. Here we describe our campaign to follow-up 86 of these candidates using the robotic facilities of Las Cumbres Observatory Global Telescope Network and the Tenagra-II robotic telescope in Arizona. The aim of these observations was to eliminate false positives as far as possible ahead of spectroscopic follow-up and to provide additional photometry to help characterise the surviving targets.
Surface power distribution in cross field heating of thin nonmagnetic plates

The problem of nonuniformity of the induced surface power density in the workpieces of cross-field heating systems is analyzed. Assuming the workpiece to be very thin, the induced current density and the induced power density are obtained using a method based on circuit theory. Calculation of the total power agrees with the measured value. The results suggest that, to obtain uniform current density, one may have to try different shapes for the exciting coils. Varying the distance between the coils or their lengths does not produce the desired effect. >
Uniqueness of the maximum likelihood estimates of the parameters of an ARMA model

Estimation of the parameters in a mixed autoregressive moving average process leads to a nonlinear optimization problem. The negative logarithm of the likelihood function, suitably normalized, converges to a deterministic function as the sample length increases. The local and global extrema of this function are investigated. Conditions for the existence of a unique global and local minimum are given.
High-power red beam generation by frequency-doubling of a Nd:YAG laser

This letter reports the generation of 6.1 W of red laser radiation by frequency-doubling a Nd:YAG laser operating at a wavelength of 1.319 /spl mu/m with a KTP crystal. The conversion efficiency and the stability of the red output power were both improved through the suppression by means of a thin etalon of two-wavelength operation in the 1.3-/spl mu/m region.
Air index compensated interferometer as a prospective novel primary standard for baseline calibrations

We describe the status of the development of an interferometer for absolute distance measurements with an intrinsic compensation of the refractive index of air, intended as a primary standard for the calibration of geodetic baselines. Two frequency-doubled Nd:YAG lasers are offset locked with a frequency difference of ≈20 GHz at the infrared 1064 nm fundamental wavelength. The resulting synthetic wavelengths of 15 mm for the infrared and 7.5 mm for the frequency-doubled green light are used as the scale for the measurements. Longer synthetic wavelengths are generated by acousto-optic frequency shifters. Based on the dispersion in air between green and infrared light the refractive index can be compensated. The attempt is demanding since uncertainties of the interferometric measurements for the optical wavelengths are scaled by a factor of nearly 300 000 in the refractive index compensated result. First comparisons up to 50 m length between this interferometer and a HeNe reference are presented. The deviations are smaller than ± 200 µm and dominated by a non-linearity from problems in the collimation of the measurement beams. In the linear parts the deviations are below ± 100 µm.
Partially reflecting sheet arrays

Multiple reflections of electromagnetic waves between two planes are studied, and the increase in directivity that results by placing a partially reflecting sheet in front of an antenna with a reflecting screen is investigated at a wavelength of 3.2 cm. The construction and performance of various models of such arrays is discussed. Thus, for example, a "reflex-cavity antenna" with an outer diameter of 1.88 \lambda and an over-all length of only 0.65 \lambda is described which has half-power beamwidths of 34\deg and 41\deg in the E and H planes, respectively, and a gain of approximately 14 db. It is shown that larger systems produce considerably greater directivity but that their efficiency is poor.
Diminishing the asymmetry of Daubechies' wavelets

The author shows that the asymmetry of Daubechies' scaling functions and wavelets can be diminished using, as a measure of asymmetry for the wavelet generating discrete-time filter, a special second moment of energy distribution in time. The moment is involved in the uncertainty relation for discrete-time signals. The generating filter is chosen such that the moment is minimized. Some other measures of asymmetry are addressed too. <<ETX>>
Structurally Robust Similarity Search

Graph similarity search algorithms usually leverage the structural properties of a database. Hence, these algorithms are effective only on some structural variations of the data and are ineffective on other forms, which makes them hard to use. Ideally, one would like to design a data analytics algorithm that is structurally robust, i.e., it returns essentially the same accurate results over all possible structural variations of a dataset. We propose a novel approach to create a structurally robust similarity search algorithm over graph databases. We leverage the classic insight in the database literature that schematic variations are caused by having constraints in the database. We then present RelSim algorithm which is provably structurally robust under these variations. Our empirical studies show that our proposed algorithms are structurally robust while being efficient and as effective as or more effective than the state-of-the-art similarity search algorithms. PVLDB Reference Format: Y. Chodpathumwan, and A. Termehchy. Structurally Robust Similarity Search. PVLDB, 12(xxx): xxxx-yyyy, 2019. DOI: https://doi.org/10.14778/xxxxxxx.xxxxxxx
Theory of accelerated orbits and space charge effects in an AVF cyclotron

• A submitted manuscript is the author's version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers.
Visual-Aware Testing and Debugging for Web Performance Optimization

Web performance optimization services, or web performance optimizers (WPOs), play a critical role in today’s web ecosystem by improving page load speed and saving network traffic. However, WPOs are known for introducing visual distortions that disrupt the users’ web experience. Unfortunately, visual distortions are hard to analyze, test, and debug, due to their subjective measure, dynamic content, and sophisticated WPO implementations. This paper presents Vetter, a novel and effective system that automatically tests and debugs visual distortions. Its key idea is to reason about the morphology of web pages, which describes the topological forms and scale-free geometrical structures of visual elements. Vetter efficiently calculates morphology and comparatively analyzes the morphologies of web pages before and after a WPO, which acts as a differential test oracle. Such morphology analysis enables Vetter to detect visual distortions accurately and reliably. Vetter further diagnoses the detected visual distortions to pinpoint the root causes in WPOs’ source code. This is achieved by morphological causal inference, which localizes the offending visual elements that trigger the distortion and maps them to the corresponding code. We applied Vetter to four representative WPOs. Vetter discovers 21 unknown defects responsible for 98% visual distortions; 12 of them have been confirmed and 5 have been fixed.
18 Subjective and Objective Quality Assessment for Volumetric Video

Volumetric video (VV) is a novel form of video that allows recreation of real-world scenes in 3D with users consuming the content from any viewpoint they desire. This makes VV best suited for augmented reality (AR) or virtual reality (VR) applications. This freedom necessitates increased user interaction with the VV itself, which brings new challenges to its visual quality assessment. In this chapter, various aspects of VV quality assessment using subjective user studies and objective quality estimation methods are discussed. These aspects include the way or representing 3D models, mode of interaction, display settings (e
A computational neuroimaging study of reinforcement learning and goal-directed exploration in schizophrenia spectrum disorders

Abstract Background Prior evidence indicates that negative symptom severity and cognitive deficits, in people with schizophrenia (PSZ), relate to measures of reward-seeking and loss-avoidance behavior (implicating the ventral striatum/VS), as well as uncertainty-driven exploration (reliant on rostrolateral prefrontal cortex/rlPFC). While neural correlates of reward-seeking and loss-avoidance have been examined in PSZ, neural correlates of uncertainty-driven exploration have not. Understanding neural correlates of uncertainty-driven exploration is an important next step that could reveal insights to how this mechanism of cognitive and negative symptoms manifest at a neural level. Methods We acquired fMRI data from 29 PSZ and 36 controls performing the Temporal Utility Integration decision-making task. Computational analyses estimated parameters corresponding to learning rates for both positive and negative reward prediction errors (RPEs) and the degree to which participates relied on representations of relative uncertainty. Trial-wise estimates of expected value, certainty, and RPEs were generated to model fMRI data. Results Behaviorally, PSZ demonstrated reduced reward-seeking behavior compared to controls, and negative symptoms were positively correlated with loss-avoidance behavior. This finding of a bias toward loss avoidance learning in PSZ is consistent with previous work. Surprisingly, neither behavioral measures of exploration nor neural correlates of uncertainty in the rlPFC differed significantly between groups. However, we showed that trial-wise estimates of relative uncertainty in the rlPFC distinguished participants who engaged in exploratory behavior from those who did not. rlPFC activation was positively associated with intellectual function. Conclusions These results further elucidate the nature of reinforcement learning and decision-making in PSZ and healthy volunteers.
Out of Hypervisor (OoH): Efficient Dirty Page Tracking in Userspace Using Hardware Virtualization Features

This paper introduces Out of Hypervisor (OoH), a new virtualization research axis. Instead of emulating full virtual hardware inside a VM to support a hypervisor, the OoH principle is to individually expose current hypervisor-oriented hardware virtualization features to the guest OS. This way, guest's processes could also take benefit from those features. We illustrate OoH with Intel PML (Page Modification Logging), a feature that allows efficient dirty page tracking to improve VM live migration. Because dirty page tracking is at the heart of many essential tasks including process checkpointing (e.g., CRIU) and concurrent garbage collection (e.g, Boehm GC), OoH exposes PML to accelerate these tasks in the guest. We present two OoH solutions namely Shadow PML (SPML) and Extended PML (EPML) that we integrated into CRIU and Boehm GC. Evaluation results showed that EPML speeds up CRIU checkpointing by about 13 x and Boehm garbage collection by up to 6x compared to SPML, /proc, and userfaultfd while reducing their overhead on monitored applications by about 16 x.
A discrete geometric conservation law (DGCL) for a cell vertex finite‐volume algorithm on moving domains

This paper revisits the classical discrete geometric conservation law for the arbitrary Lagrangian–Eulerian conservation equations in a moving domain when the conservation laws are mapped to a fixed reference domain. The discretized form of the equations is formulated by means of a cell vertex finite‐volume algorithm with special emphasis on the implications of the discrete time–space algorithm for the preservation of free‐stream flows. Under these circumstances, two corrections are introduced in order to guarantee the preservation of a free‐stream flow evolving in time. A time correction is required to resolve the integration errors in the Jacobian of the transformation or mapping between fixed referential and current domains. A spatial correction is also needed to account for the inexact surface integration in the faces of the dual mesh. Copyright © 2008 John Wiley & Sons, Ltd.
Improved dry rotating disk separator

The older version of the deflection-mode magnetic dry rotating disk separator has been improved by integrating a belt which forms a moving boundary to outside. The separation process has been considerably simplified, and the product quality has been enhanced with a matching flux density profile. Forces are basically similar to an isodynamic separation mode. A cost estimation based on permanent magnet excitation shows an interesting potential of the improved separator.
Implicit Sentiment Analysis of Chinese Texts based on Contextual Information and Knowledge Enhancement

The implicit sentiment analysis task makes the traditional explicit sentiment analysis methods no longer applicable due to the obscure and ambiguous expression of the sentiment text it focuses on and the lack of sentiment cue words containing obvious sentiment tendencies. In this paper, we propose a sentiment analysis method incorporating contextual information and external common sense knowledge for implicit sentiment analysis. We first propose a retrieval method to extract valid sentiment triples from a knowledge base and build an adaptive fusion of external common sense knowledge embedding layers to extend the semantic information of implicit sentiment expressions. Multipolar orthogonal attention mechanism is then used to learn embedding representations for implicit sentiment expressions, and an attention layer that incorporates context is introduced to mine and combine valid information in the context. Finally, the common sense knowledge information provided by the external knowledge base is fused with the contextual representation and the semantic information of the sentiment expression itself to achieve an effective extension of the implicit sentiment sentence representation and to perform sentiment label prediction. Experimental results on the SMP2019-ECISA dataset show that the method outperforms existing state-of-the-art methods and can fully exploit contextual information and external common sense knowledge to effectively improve the analysis of implicit sentiment expressions.
A WLAN-used helical antenna fully integrated with the PCMCIA carrier

The invention presented here is to embed the helical antenna inside an ejector of a Personal Computer Memory Card International Association (PCMCIA) carrier. The detail dimension of this antenna has been well designed to operate at the frequency 2.45 GHz, which is employed for the wireless LAN application. A low-cost electromagnetic simulation package-WIPL-D, is used to simulate this complex electromagnetic environment where the carrier metal is modeled as well, in addition to the helical antenna itself. Measurements both of return loss and radiation patterns are made too to have a comparison with the results of simulation and to prove the design thoughts given by this paper. As a final evaluation, a PCMCIA carrier with the present design is installed into a Tablet PC to have a complete measurement.
College-Related Question Answering based on Knowledge Graph

An effective conversational agent can facilitate student advising. Many question-answering (QA) systems have been developed, but college-related QA has yet to be explored. It is a challenging task since questions from college students are domain-specific, while related training data is not available. The topics of the college-related questions are diverse, including the university, the department, undergraduate/graduate programs, and course content. To bridge this gap, we propose an effective question-answering framework for The Hong Kong Polytechnic University and Computer Science. It integrates a rule-based module, a knowledge-graph-based module, and a content-based module. The rule-based module can answer simple questions actually based on pre-defined rules. Then, we manually construct a college-related knowledge graph (KG) from related websites, Wikipedia, and textbooks. We embed the KG and employ the entity/relation representations to predict the answers. Moreover, we utilize a pre-trained language model to answer difficult questions based on college-related corpora. We evaluate the proposed QA framework by employing fourteen postgraduate students. The results show that it can answer most real-world questions.
On application of asymptotic generalized discrepancy principle to the analysis of epidemiology models

Various implementations of the discrepancy principle (DP) for linear ill-posed problems are given in a large number of papers. In all of these papers, the DP has been justified for special types of regularization strategies. In our paper, a unified approach to the construction of the DP is presented that does not require any special structure of the regularizing operator. In that respect, the new method generalizes all prior results on the DP principle for linear irregular operator equations with noisy data. The efficiency of the proposed scheme is demonstrated for a parameter identification problem in avian influenza. In solving this particular inverse problem, it turned out to be beneficial to use some regularization strategies, for which the earlier (structure-based) discrepancy principles were not applicable. This motivated the development of a novel DP put forth in the current paper.
A parametric estimation method for dynamic factor models of large dimensions

Abstract. The estimation of dynamic factor models for large sets of variables has attracted considerable attention recently, because of the increased availability of large data sets. In this article we propose a new parametric methodology for estimating factors from large data sets based on state–space models and discuss its theoretical properties. In particular, we show that it is possible to estimate consistently the factor space. We also conduct a set of simulation experiments that show that our approach compares well with existing alternatives.
Saliency maps and attention selection in scale and spatial coordinates: an information theoretic approach

Information measures with respect to spatial locations and scales of objects in an image are important to image processing and interpretation. It allows us to focus attention on relevant data, saving effort and reducing false positives. In particular, the information content of a man-made scene is typically confined to a small set of scales. We devise a scale space based measure of image information. Kullback contrasts between successive resolution lengths gives the differential information gain. Experiments show that this measure gives a clear indication of characteristic lengths in a variety of real world images and is superior to power spectrum based measurements. Decomposing the expected information gain into spatial coordinates gives us a saliency map for use by an attention selector. We combine the scale and spatial decompositions into a single information measure, giving both the spatial extent and scale range of interest. The information measure has an efficient implementation, and thus can be used routinely in early vision processing. <<ETX>>
Adaptive iterative learning control of uncertain robotic systems

A distinct feature of the proposed AILC scheme is that uncertain parameters are estimated in the time domain whereas repetitive disturbances are identified and compensated in the iteration domain. The bounds of the parameters are not required to be known a priori, and the learning control gain can be adjusted independently of the parameter adaptation gain. The overall closed-loop stability and uniform error convergence in the iteration domain are established without any acceleration measurements or their estimated values. The proposed AILC scheme is a balanced combination of the conventional adaptive control and the iterative learning control, where the shortcomings of each scheme are complemented. The validity of the scheme is confirmed through a simulation example.
Triple-Doppler Analysis of a Discretely Propagating, Long-Lived, High Plains Squall Line

Abstract A nonsevere squall line that developed on 21 June 1993 along the northern foothills of the Colorado Rocky Mountains is analyzed using a series of triple-Doppler analyses. This squall line developed in a relatively dry environment characterized by weak low-level but strong upper-level vertical shear of the horizontal winds. The drier thermodynamic profile, as characterized by a higher lifting condensation level, and weak low-level shear resulted in convection forming not along, but rather 7–10 km behind the leading edge of the shallow cold pool. The strong upper-level shear established a predominantly leading anvil. This led to a suppression zone immediately ahead of the leading line, which in turn resulted in a discrete mode of propagation of the squall line. Three different cycles were observed: each cycle had a distinct line of convective cells that initiate, intensify, and then decay. In each case the new cells developed 20–40 km out ahead of the decaying line of the previous cycle. Many studi.