Miracle-dz/UniFAR-FTUs huggingface dataset:
Sandwiching the marginal likelihood using bidirectional Monte Carlo

Computing the marginal likelihood (ML) of a model requires marginalizing out all of the parameters and latent variables, a difficult high-dimensional summation or integration problem. To make matters worse, it is often hard to measure the accuracy of one's ML estimates. We present bidirectional Monte Carlo, a technique for obtaining accurate log-ML estimates on data simulated from a model. This method obtains stochastic lower bounds on the log-ML using annealed importance sampling or sequential Monte Carlo, and obtains stochastic upper bounds by running these same algorithms in reverse starting from an exact posterior sample. The true value can be sandwiched between these two stochastic bounds with high probability. Using the ground truth log-ML estimates obtained from our method, we quantitatively evaluate a wide variety of existing ML estimators on several latent variable models: clustering, a low rank approximation, and a binary attributes model. These experiments yield insights into how to accurately estimate marginal likelihoods.
Nonlinear Analysis of Heart Rate Variability and Plethysmogram in Subjects with Normal and Abnormal Cardiovascular Function

We used nonlinear methods of Detrended Fluctuation Analysis (DFA) and Recurrence Quantification Analysis (RQA) to analysis of plethysmograms and their peak intervals in subjects with normal and pathological cardiovascular functions. Our results on HRV using DFA showed that scaling exponent indicated quantitatively differentiations among normal and pathologies. The measures of RQA were found to provide an unambiguous and quantitatively characterization of the plethysmogram time series in different cases. Accordingly, the integrations of these two analyses had the ability to identify and quantify normal and pathological cases, implying a possible clinical application.
Comparison of Short-term Outcomes of Thrombolysis for In-Hospital Stroke and Out-of-Hospital Stroke in United States

Background and Purpose— In-hospital stroke (IHS) differs from out-of-hospital stroke (OHS) in risk factors and outcomes. We compared IHS and OHS treated with thrombolysis from a large national cohort in a cross-sectional study to further clarify these differences. Methods— The Nationwide Inpatient Sample for the years 2005–2010 was searched for adult acute ischemic stroke cases treated with intravenous or intra-arterial thrombolysis. Patients treated on the day of admission were classified as OHS. We compared the demographic and hospital characteristics, comorbidities, and short-term outcomes of thrombolysed IHS and OHS. Results— IHS included 8.7% of 11 750 thrombolysed stroke cases in this study. IHS was associated with a higher comorbidity profile and higher rates of acute medical conditions compared with OHS. IHS had higher inpatient mortality (15.7% versus 9.6%; P<0.001) and lower rate of discharge to home/self-care (22.8% versus 30.0%; P<0.001). IHS was also associated with higher mortality among endovascular treatment group (19.3% versus 13.8%; P=0.010). The difference in the rate of all intracerebral hemorrhage was not significant (5.3% versus 4.7%; P=0.361). In the multivariate analysis, inpatient mortality (adjusted odds ratio, 1.59; 95% confidence interval, 1.32–1.92; P<0.001) and favorable discharge outcome (adjusted odds ratio, 0.79; 95% confidence interval, 0.67–0.93; P=0.005) remained significantly worse in IHS. Conclusions— Thrombolysed IHS is associated with worse discharge outcomes compared with thrombolysed OHS, likely because of their higher comorbidities and additional medical reasons for the index admission. Thrombolysis is not associated with a higher rate of intracerebral hemorrhage among IHS.
Web on the Wall Reloaded: Implementation, Replication and Refinement of User-Defined Interaction Sets

System design using novel forms of interaction is commonly argued to be best driven by user-driven elicitation studies. This paper describes the challenges faced, and the lessons learned, in replicating Morris's Web on the Wall guessability study which used Wizard of Oz to elicit multimodal interactions around Kinect. Our replication involved three steps. First, based on Morris's study, we developed a system, Kinect Browser, that supports 10 common browser functions using popular gestures and speech commands. Second, we developed custom experiment software for recording and analysing multimodal interactions using Kinect. Third, we conducted a study based on Morris's design. However, after first using Wizard of Oz, Kinect Browser was used in a second elicitation task, allowing us to analyse and compare the differences between the two methods.Our study demonstrates the effects of using mixed-initiative elicitation with significant differences to user-driven elicitation without system dialogue. Given the recent proliferation of guessability studies, our work extends the methodology to obtain reproducible and implementable user-defined interaction sets.
Resonance-averaged Photoionization Cross Sections for Astrophysical Models

We present ground-state photoionization cross sections of atoms and ions averaged over resonance structures for photoionization modeling of astrophysical sources. The detailed cross sections calculated in the close-coupling approximation using the R-matrix method, with resonances delineated at thousands of energies, are taken from the Opacity Project database TOPbase and the Iron Project, including new data for the low ionization stages of iron Fe I-Fe V. The resonance-averaged cross sections are obtained by convolving the detailed cross sections with a Gaussian distribution over the autoionizing resonances. This procedure is expected to minimize errors in the derived ionization rates that could result from small uncertainties in computed positions of resonances while preserving the overall resonant contribution to the cross sections in the important near-threshold regions. The detailed photoionization cross sections at low photon energies are complemented by new relativistic distorted-wave calculations for Z ≤ 12 and from central-field calculations for Z > 12 at high energies, including inner shell ionization. The effective cross sections are then represented by a small number of points that can be readily interpolated linearly for practical applications; a FORTRAN subroutine and data are available. The present numerically averaged cross sections are compared with analytic fits that do not accurately represent the effective cross sections in regions dominated by resonances.
The key dimensions of knowledge-intensive business services (KIBS) analysis: a decade of evolution

The importance of knowledge and innovation in modern economies justifies the in-creasing interest that scholars are taking in studying knowledge-intensive business services (KIBS). The objective of this paper is to track the evolution of the key dimen-sions on which scholars have based their analyses through a literature review. More specifically, three main issues are addressed: (1) how KIBS are defined in the litera-ture; (2) how KIBS have been investigated empirically by researchers; and (3) how the analysis of KIBS has evolved over time. As a major assumption, the analysis catego-rises the research topic into three key conceptual dimensions: (i) knowledge; (ii) inno-vation and (iii) spatial proximity. The major hypothesis is that the way KIBS are seen, studied and perceived by the research community resolutely changed over time and that this evolution can be tracked by observing modifications in the key dimensions associated with the analysis of KIBS.
Impact of mobility prediction on the performance of Cognitive Radio networks

Wireless technology has enabled the development of increasingly diverse applications and devices resulting in an exponential growth in usage and services. These advancements made the radio frequency spectrum a scarce resource, and consequently, its efficient use is of the ultimate importance. To cope with the growing demand, network design focused on increasing the spectral efficiency by making use of advancement in Cognitive Radio technology. Cognitive Radio can reduce the spectrum shortage problem by enabling unlicensed users equipped with Cognitive Radios to reuse and share the licensed spectrum bands. Using the fact that a Cognitive Radio is capable of sensing the environmental conditions and automatically adapting its operating parameters in order to enhance network performance, we would like to make use of its knowledge to predict the mobility of Cognitive Radio users to improve the overall performance of the Cognitive Radio network. This study makes novel use of mobility prediction techniques to enhance reliability, bandwidth efficiency and scalability of the cognitive radio networks. Firstly, prediction techniques are evaluated and compared for prediction accuracy. Secondly, routing protocol reliability, efficiency and scalability performances are evaluated under different prediction techniques. Simulation results verify the performance improvements even with moderate accuracy predictors. Results clearly show that hybrid Markov CDF prediction performs the best. When compared with no prediction it significantly improves average reliability and efficiency by 11% and 8%, respectively.
A Bayesian modeling approach to multi-dimensional sentiment distributions prediction

Sentiment analysis has long focused on binary classification of text as either positive or negative. There has been few work on mapping sentiments or emotions into multiple dimensions. This paper studies a Bayesian modeling approach to multi-class sentiment classification and multidimensional sentiment distributions prediction. It proposes effective mechanisms to incorporate supervised information such as labeled feature constraints and document-level sentiment distributions derived from the training data into model learning. We have evaluated our approach on the datasets collected from the confession section of the Experience Project website where people share their life experiences and personal stories. Our results show that using the latent representation of the training documents derived from our approach as features to build a maximum entropy classifier outperforms other approaches on multi-class sentiment classification. In the more difficult task of multi-dimensional sentiment distributions prediction, our approach gives superior performance compared to a few competitive baselines.
Affect analysis of text using fuzzy semantic typing

We propose a convenient fusion of natural-language processing and fuzzy logic techniques for analyzing affect content in free text; our main goals are fast analysis and visualization of affect content for decision-making. The primary linguistic resource for fuzzy semantic typing is the fuzzy affect lexicon, from which other important resources are generated, notably the fuzzy thesaurus and affect category groups. Free text is tagged with affect categories from the lexicon, and the affect categories' centralities and intensities are combined using techniques from fuzzy logic to produce affect sets fuzzy sets that represent the affect quality of a document. We show different aspects of affect analysis using news stories and movie reviews. Our experiments show a very good correspondence of affect sets with human judgments of affect content. We ascribe this to the effective representation of ambiguity in our fuzzy affect lexicon, and the ability of fuzzy logic to deal successfully with the ambiguity of words in natural language. Planned extensions of the system include personalized profiles for Web-based content dissemination, fuzzy retrieval, clustering and classification.
Overloaded array processing with spatially reduced search joint detection

An antenna array is overloaded when the number of cochannel signals in its operating environment exceeds the number of elements. This paper proposes an iterative joint detection technique, spatially reduced search joint detection (SRSJD), that well approximates the joint maximum likelihood (JML) receiver, while reducing its computational complexity by several orders of magnitude. This complexity reduction is achieved by first exploiting the spatial separation between interfering signals with a linear preprocessing stage, and second, performing iterative joint detection with a reduced-state trellis formed over space instead of time. These novel joint detection trellises are possibly tail-biting and vary in structure from stage to stage. Through simulation, SRSJD is shown to demodulate over 2M synchronous quaternary phase-shift keying signals of zero excess bandwidth with an M element circular array. The channels of all users are assumed known.
On Implicitly Discovered OLAP Schema-Specific Preferences in Reporting Tool

On Implicitly Discovered OLAP Schema-Specific Preferences in Reporting Tool We propose content-based methods for construction of recommendations for reports in the OLAP reporting tool. Recommendations are generated based on preference information in user profile, which is updated implicitly by collecting and analyzing user activity in the reporting tool. Taking advantage of data about user preferences for data warehouse schema elements, existing reports that potentially may be interesting to the user are distinguished and recommended. The approach used for recommending reports is composed of two methods - cold-start and hot-start.
ALGORITHM FOR ONE MACHINE JOB SEQUENCING WITH PRECEDENCE CONSTRAINTS

Consider the problem of sequencing n jobs with general precedence constraints on a single machine to minimize total weighted completion time, which is NP-complete. However some class of problems can be solved in polynomial time, i.e . the problems whose precedence constraints are trees or series parallel. This paper proposes an O(n4) algorithm for implementing a decomposition procedure due to Sidney. It also shows that if each decomposed sub graph is series parallel, then the problem is solved in 0(n 5 ) running time, even if the whole graph is not series parallel.
Interval methods for multi-point collisions between time-dependent curved surfaces

We present an efficient and robust algorithm for finding points of collision between time-dependent parametric and implicit surfaces. The algorithm detects simultaneous collisions at multiple points of contact. When the regions of contact form curves or surfaces, it returns a finite set of points uniformly distributed over each contact region. Collisions can be computed for a very general class of surfaces: those for which inclusion functions can be constructed. Included in this set are the familiar kinds of surfaces and time behaviors encountered in computer graphics. We use a new interval approach for constrained minimization to detect collisions, and a tangency condition to reduce the dimensionality of the search space. These approaches make interval methods practical for multi-point collisions between complex surfaces. An interval Newton method based on the solution of the interval linear equation is used to speed convergence to the collision time and location. This method is more efficient than the Krawczyk‐Moore iteration used previously in computer graphics.
The Degrees of Freedom of the $K$-pair-user Full-Duplex Two-way Interference Channel with and without a MIMO Relay

In a K-pair-user two-way interference channel (TWIC), 2K messages and 2K transmitters/receivers form a K-user IC in the forward direction (K messages) and another K-user IC in the backward direction which operate in full-duplex mode. All nodes may interact, or adapt inputs to past received signals. We derive a new outer bound to demonstrate that the optimal degrees of freedom (DoF, also known as the multiplexing gain) is K: full-duplex operation doubles the DoF, but interaction does not further increase the DoF. We next characterize the DoF of the K-pair-user TWIC with a MIMO, full-duplex relay. If the relay is non-causal/instantaneous (at time k forwards a function of its received signals up to time k) and has 2K antennas, we demonstrate a one-shot scheme where the relay mitigates all interference to achieve the interference-free 2K DoF. In contrast, if the relay is causal (at time k forwards a function of its received signals up to time k 1), we show that a full-duplex MIMO relay cannot increase the DoF of the K-pair-user TWIC beyond K, as if no relay or interaction is present. We comment on reducing the number of antennas at the instantaneous relay.
Modelling and Performance Evaluation of Optical Burst Switched Node with Deflection Routing and Dynamic Wavelength Allocation

In this paper the effect of dynamic wavelength allocation (DWA) scheme implementation to the OBS node performance is investigated. We have developed the mathematical model of an OBS node in order to evaluate the burst blocking prob- ability. It is proposed to allocate a part of total wavelengt h capacity to be used by deflected bursts only. The results obtained from the model sh ow that if the number of allocated wavelengths is dynamicaly adapted to the deflec ted burst traffic intensity, the total blocking probability and deflected burst blocking probability significantly decrease. Concerning to the hardware requirements the implementation of deflection routing needs the limitted optical FDL buffer incorporatio n, to provide the deflected burst with the extra offset time. Also, control logic for bur st scheduler needs to be upgraded to perform the dynamic wavelength allocation for deflected bursts.
Lazy Classication with Interval Pattern Structures: Application to Credit Scoring

Pattern structures allow one to approach the knowledge extraction problem in case of arbitrary object descriptions. They provide the way to apply Formal Concept Analysis (FCA) techniques to non-binary contexts. However, in order to produce classification rules a concept lattice should be built. For non-binary contexts this procedure may take much time and resources. In order to tackle this problem, we introduce a modification of the lazy associative classification algorithm and apply it to credit scoring. The resulting quality of classification is compared to existing methods adopted in bank systems.
5th International Workshop on Constraints and Language Processing

Communication in general requires a process for (a) producing an optimal form given a certain meaning, and recovering that meaning given the optimal form, and (b) arriving at an optimal interpretation given a certain form, and reproducing that form given the optimal interpretation (Blutner et al. 2006). Hence, optimal communication involves more than the sum of two unidirectional processes of optimization. I will discuss this hypothesis for the case of object fronting in Dutch. Object fronting is rare but grammatical in Dutch. Usually, object fronting is considered to be a type of topicalisation. Therefore, we expect object fronting to occur when the object is the topic of the sentence, and since animate noun phrases are better topics than inanimate noun phrases, we can expect object fronting to happen more often when the object is animate. This would explain the speaker’s tendency to start a sentence with an animate noun phrase, irrespective of its grammatical function. But from the hearer’s perspective a fronted object is in fact more easily recognizable as an object when it is inanimate. I will argue that indeed both the speaker’s and the hearer’s perspectives constrain object fronting, and that not only does the speaker take into account the hearer’s perspective, but also the other way around.
Asymptotic behavior of Maxwell fields in higher dimensions

We study the fall-off behaviour of test electromagnetic fields in higher dimensions as one approaches infinity along a congruence of “expanding” null geodesics. The considered backgrounds are Einstein spacetimes including, in particular, (asymptotically) flat and (anti-)de Sitter spacetimes. Various possible boundary conditions result in different characteristic fall-offs, in which the leading component can be of any algebraic type (N, II or G). In particular, the peelingoff of radiative fields F = Nr 1 n/2 + Gr n/2 + . differs from the standard four-dimensional one (instead it qualitatively resembles the recently determined behaviour of the Weyl tensor in higher dimensions). General p-form fields are also briefly discussed. In even n dimensions, the special case p = n/2 displays unique properties and peels off in the “standard way” as F = Nr 1 n/2 + IIr n/2 + . A few explicit examples are mentioned.
A FAB Approach to E-Commerce Knowledge Accessibility Requirements

E-commerce sites currently provide poor access to information and knowledge. Accessibility is a key issue, both for selling individual products and services, and for selling the concept of e-commerce ahead of other modes of commerce. This report uses the concept of Features, Advantages and Benefits (FAB) to define knowledge-level accessibility requirements (KAR). The KAR criteria are applied in a survey of the largest 15 e-commerce sites to show that access to knowledge for on-line purchases is impaired by the lack of product benefit information. This conclusion is supported by other survey information indicating that experienced shoppers spend less time searching for information, are more successful in identifying relevant products, and make and pay for more purchases via the web. The paper discusses how the top 15 sites can succeed without knowledge of product benefits and whether other markets will be able to implement e-commerce using existing web business models, interfaces and technologies.
Nmf9 Encodes a Highly Conserved Protein Important to Neurological Function in Mice and Flies

Many protein-coding genes identified by genome sequencing remain without functional annotation or biological context. Here we define a novel protein-coding gene, Nmf9, based on a forward genetic screen for neurological function. ENU-induced and genome-edited null mutations in mice produce deficits in vestibular function, fear learning and circadian behavior, which correlated with Nmf9 expression in inner ear, amygdala, and suprachiasmatic nuclei. Homologous genes from unicellular organisms and invertebrate animals predict interactions with small GTPases, but the corresponding domains are absent in mammalian Nmf9. Intriguingly, homozygotes for null mutations in the Drosophila homolog, CG45058, show profound locomotor defects and premature death, while heterozygotes show striking effects on sleep and activity phenotypes. These results link a novel gene orthology group to discrete neurological functions, and show conserved requirement across wide phylogenetic distance and domain level structural changes.
A Scalable VLSI MIMD Routing Cell

It is a well known fact that full custom designed computer architectures can achieve much higher performance for specific applications than general purpose computers. Thisperjormance has to be paidfor: a long design trajectory results in a high cost-performance ratio. Current VLSI design and compilation tools however, make semi-custom designs feasible with greatly reduced costs and time to market. This paper presents a scalable andflexible communication processor for message passing MIMD systems. This communication processor is implemented as a parametrisized VLSI routing cell in a VLSI compilation system. This cell fits into the SCARCE RISC processor framework [ I ] , which is an architectural framework for automatic generation of application specific processors. By use of application analysis, the cell is tuned to the specijic requirements during silicon compilation time. This approach is new, in that it avoids the general performance penalty paid for requiredflexibility.