Miracle-dz/UniFAR-FTUs huggingface dataset:
ESSENCE: a portable methodology for building information extraction systems

One of the most important issues when constructing an Information Extraction System is how to obtain the knowledge needed for identifying relevant information in a document. A manual approach not only is an expensive solution but also has a negative effect on the portability of the system across domains. To automatize the knowledge acquisition process may partially solve this problem even if a human expert takes part in it only for specific tasks. This work presents a methodology ({sc Essence}) to automatically learn information extraction patterns from unrestricted text corpus representative of the domain. The methodology includes different steps from which we stress the specific pattern generalization process. Generalization reduces the pattern base and therefore reduces the amount of information to validate by an expert. As we will see, the use of the lexical knowledge along with the lexico-semantic relations from WordNet are our basis knowledge source, especially, for the generalization process.
Small-Scale and Mesoscale Variability of Scalars in Cloudy Boundary Layers: One-Dimensional Probability Density Functions

A key to parameterization of subgrid-scale processes is the probability density function (PDF) of conserved scalars. If the appropriate PDF is known, then grid box average cloud fraction, liquid water content, temperature, and autoconversion can be diagnosed. Despite the fundamental role of PDFs in parameterization, there have been few observational studies of conserved-scalar PDFs in clouds. The present work analyzes PDFs from boundary layers containing stratocumulus, cumulus, and cumulus-rising-into-stratocumulus clouds. Using observational aircraft data, the authors test eight different parameterizations of PDFs, including double delta function, gamma function, Gaussian, and double Gaussian shapes. The Gaussian parameterization, which depends on two parameters, fits most observed PDFs well but fails for large-scale PDFs of cumulus legs. In contrast, three-parameter parameterizations appear to be sufficiently general to model PDFs from a variety of cloudy boundary layers. If a numerical model ignores subgrid variability, the model has biases in diagnoses of grid box average liquid water content, temperature, and Kessler autoconversion, relative to the values it would obtain if subgrid variability were taken into account. The magnitude of such biases is assessed using observational data. The biases can be largely eliminated by three-parameter PDF parameterizations. Prior authors have suggested that boundary layer PDFs from short segments are approximately Gaussian. The present authors find that the hypothesis that PDFs of total specific water content are Gaussian can almost always be rejected for segments as small as 1 km.
A virtual environment for collaborative assembly

To allow geographical dispersed engineers to perform an assembly task together, a virtual environment for collaborative assembly (VECA) has been developed to build a typical collaborative virtual assembly system. This presents the key parts of VECA, such as system architecture, HLA-based (high level architecture) communication and collaboration, motion guidance based on collision detection and assembly constraints recognition, data translation from CAD to virtual environment, reference resolution in multimodal interaction.
Intertemporal substitution and recursive smooth ambiguity preferences

In this paper, we establish an axiomatically founded generalized recursive smooth ambiguity model that allows for a separation among intertemporal substitution, risk aversion, and ambiguity aversion. We axiomatize this model using two approaches: the second-order act approach a la Klibanoff et al. (2005) and the twostage randomization approach a la Seo (2009). We characterize risk attitude and ambiguity attitude within these two approaches. We then discuss our model’s application in asset pricing. Our recursive preference model nests some popular models in the literature as special cases.
The uncertainty of valuation

Valuation is often said to be Ian art not a scienceo but this relates to the techniques employed to calculate value not to the underlying concept itself. Valuation is the process of estimating price in the market place. Yet, such an estimation will be affected by uncertainties. Uncertainty in the comparable information available; uncertainty in the current and future market conditions and uncertainty in the specific inputs for the subject property. These input uncertainties will translate into an uncertainty with the output figure, the valuation. The degree of the uncertainties will vary according to the level of market activity; the more active a market, the more credence will be given to the input information. In the UK at the moment the Royal Institution of Chartered Surveyors (RICS) is considering ways in which the uncertainty of the output figure, the valuation, can be conveyed to the use of the valuation, but as yet no definitive view has been taken. One of the major problems is that Valuation models (in the UK) are based upon comparable information and rely upon single inputs. They are not probability based, yet uncertainty is probability driven. In this paper, we discuss the issues underlying uncertainty in valuations and suggest a probability-based model (using Crystal Ball) to address the shortcomings of the current model.
Intelligent fault diagnosis of train bearings acoustic signals with Doppler shift based on the EMD and BPN

An approach to intelligent fault diagnosis of train bearings acoustic signals with Doppler shift is proposed in this paper, which based on the EMD and BPN without eliminating the Doppler shift effect, by extracting the fault characteristic information from train bearing acoustic signals. First, decompose the acoustic signals with Doppler shift into IMFs by EMD. Then, calculate the 8 VFs of IMFs and 10 TFs of original signals, take the 18 features as the input of BPN. After training the BPN, the result of test samples shows the proposed approach can discriminate different fault conditions of train bearing reliably and accurately.
A novel approach to find out QRS complex for ECG signal

The objective of this paper is to develop a microcontroller based QRS detection technique for ECG signal. The work is performed in two stages. Synthetic ECG data is used for validation of the technique from Physionet database. At first MATLAB simulation is performed on single lead ECG data with 8-bit digital format. In the next stage, this is implemented in an 8051 based standalone embedded system. The digitized data stored in PC is serially sent to 8051 microcontroller and stored in an on board SRAM. The program is developed to analyze the data sequentially in SRAM and detect the R-peaks. Whenever an R-peak is obtained, the corresponding indexes are sent back to PC using serial port for storing it in another data file.
Queuing Theory-based Latency/Power Tradeoff Models for Replicated Search Engines

Large-scale search engines are built upon huge infrastructures involving thousands of computers in order to achieve fast response times. In contrast, the energy consumed (and hence the financial cost) is also high, leading to environmental damage. This paper proposes new approaches to increase energy and financial savings in large-scale search engines, while maintaining good query response times. We aim to improve current state-of-the-art models used for balancing power and latency, by integrating new advanced features. On one hand, we propose to improve the power savings by completely powering down the query servers that are not necessary when the load of the system is low. Besides, we consider energy rates into the model formulation. On the other hand, we focus on how to accurately estimate the latency of the whole system by means of Queueing Theory. Experiments using actual query logs attest the high energy (and financial) savings regarding current baselines. To the best of our knowledge, this is the first paper in successfully applying stationary Queueing Theory models to estimate the latency in a large-scale search engine.
Perioperative Implementation of Continuous Positive Airway Pressure: A Review of the Considerations

OSA patients present unique challenges in the peri-operative period. They routinely require more monitoring, oxygen therapy, unplanned ICU admissions, longer hospital stays, and have more adverse events than healthy counter- parts. Some data suggest that perioperative CPAP use is associated with reduced morbidity and mortality of patients with OSA, and yet its application remains inconsistent. This review aims to summarize existing literature on the peri-operative use of CPAP, identify barriers to its implementation, and begin defining an algorithm for the practical application of peri-operative CPAP.
A Browser Scanner: Collecting Intranet Information

At present, using with HTML5 and new browser technologies, many information, such as a hostname or a server application name, can be collected by a Web server. Even if the visitors are protected by a firewall, their intranet information can be collected. Then, currently people should also focus on the intranet information where he or she belongs to. In this paper, we propose a network scanning tool that allows a Web browser to collect information about active hosts or the existence of a proxy over a channel to the Web server.
The nanomechanical NOSE

We present a novel chemical sensor based on a microfabricated array of silicon cantilevers. Individual cantilevers are sensitized for the detection of analytes using metal coatings. Analyte molecules chemisorbing or physisorbing on the cantilever coating and chemical reactions produce a change in interfacial stress between analyte molecules and cantilever. This leads to a nanomechanical response of the cantilever, i.e. bending. The bending is read out using a time-multiplexed optical beam-deflection technique. From magnitude and temporal evolution of the bending, quantitative information on analyte species and concentration is derived. Here, we demonstrate the detection of ethene and water vapor with such a nanomechanical nose.
19 Selection of Best Alternative Process Plan in Automated Manufacturing Environment : An Approach Based on Particle Swarm Optimization

In the present flexible and automated manufacturing environment, selection of optimal process plan is a crucial decision making problem. The systematic determination of processing steps for the transformation of raw material to its finished product is identified as process planning. The real world dynamic shop floor is characterized by the availability of several machines, tools, fixtures/jigs etc., and demands the completion of several design tasks before the commencement of manufacturing actual manufacturing of a part type. Different geometrical and tolerance relationships among several features of the part types necessitate the arrangement of different setups to carry out various and hence, diverse alternative process plans to manufacture a part come into existence. Any of these feasible process plans can be used to produce the particular part type from its raw material [1], [2]. Due to the incorporation of dynamic shop floor situations such as bottleneck machines, non availability of tools, machine breakdown, etc., the process plan selection problem becomes non linear and NP hard in nature. The proliferation of Computer Aided Process Planning (CAPP) systems has made it easy and more efficient to tackle these types of non linear process planning systems. The scheduling complexity in the manufacturing systems was discussed in [2] and it was proposed that this can be reduced with the limited number of tools and auxiliary devices. The three reasons given by [2] to solve the process plan selection problem are: production cost, tool magazine capacity limitation, and reduction of auxiliary devices. Later, the process plan selection problem was attempted in [1] considering three objectives such as to minimize total time, minimize number of setups and to minimize dissimilarity among process plans. Reference [3] contributed in solving process plan selection problem using fuzzy approach to deal with the imprecise information. Reference [4] incorporated the factors such as similarity index within a process plan and degree of similarity among various process plans. They used fuzzy approach to take care of the part type processing sequence. PPS problem has also been attempted using Hybrid Hopfield Neural network and Genetic Algorithm Approach [13].
Mind-Body Parallelism Revisited

This article addresses the links and interactions between the neuroscience parallel line of theories and the paral- lel line of mental activity and thinking. An argument is made that the most fundamental biological entity, the human ge- nome, provides a pathway of mind-body functional coordination via a double helix metaphor. Brief selections of neuro- science and psychological theories associated with the characteristics of higher thinking are presented. Advantages of trac- ing the double-helix/genome pathway to mind -body issues are discussed. A modification is proposed to reflect the unique development of speech and language in human beings. Their effects on thinking and communication warrant a unique avenue of investigation.
THE CONJUGACY THEOREMS

We use the theory of differential forms, orientation, and mapping degree to prove that all maximal tori in a compact connected Lie group are conjugate. We also prove that all Lie groups are orientable, and that if G is a compact connected Lie group and T a maximal torus of G, then dim G/T is even.
Silent grief : narratives of bereaved adult siblings.

This qualitative research project is a narrative inquiry into the lives of four bereaved siblings; one is myself. The purpose of the project was to explore our mutual experiences of loss, look for patterns, and create a forum for continuing our stories in a new way. Identified as a disenfranchised loss (Wray, 2003) adult siblings are often seen as the least impacted family member when a sibling dies. After such a death, the concern is first directed toward the grieving spouse and children and then the deceased’s parents. Adult siblings are often expected to be a source of strength and support for others. Through in-depth interviews and story telling, three participants shared their reflections of, first, living with and, then, living without beloved siblings. Their stories of loss and love are captured both with words and visually through photographs. My stories are woven throughout the text as I reflect upon my grief journey and ongoing search for meaning.
An efficient Bayesian inference approach to inverse problems based on an adaptive sparse grid collocation method

A new approach to modeling inverse problems using a Bayesian inference method is introduced. The Bayesian approach considers the unknown parameters as random variables and seeks the probabilistic distribution of the unknowns. By introducing the concept of the stochastic prior state space to the Bayesian formulation, we reformulate the deterministic forward problem as a stochastic one. The adaptive hierarchical sparse grid collocation (ASGC) method is used for constructing an interpolant to the solution of the forward model in this prior space which is large enough to capture all the variability/uncertainty in the posterior distribution of the unknown parameters. This solution can be considered as a function of the random unknowns and serves as a stochastic surrogate model for the likelihood calculation. Hierarchical Bayesian formulation is used to derive the posterior probability density function (PPDF). The spatial model is represented as a convolution of a smooth kernel and a Markov random field. The state space of the PPDF is explored using Markov chain Monte Carlo algorithms to obtain statistics of the unknowns. The likelihood calculation is performed by directly sampling the approximate stochastic solution obtained through the ASGC method. The technique is assessed on two nonlinear inverse problems: source inversion and permeability estimation in flow through porous media.
A state searching method for model-based diagnosis

Model-based diagnosis has a great advantage compared to other diagnostic methods. However, there are some problems existed in model-based method like large complexity, inefficient. This paper studies a state searching method using system conflicts to exclude large invalid state space and speed up the search procedure. All the tested candidate states are generated in best first order and expanded to find best solutions of the system. The simulation results prove the proposed searching method is more effective than the general method.
Reconstitution of high-level micafungin resistance detected in a clinical isolate of Candida glabrata identifies functional homozygosity in glucan synthase gene expression.

OBJECTIVES A mechanism for the acquisition of high-level echinocandin resistance in Candida glabrata was investigated. FKS mutants were constructed to: determine whether clinically significant micafungin resistance requires a hot-spot mutation in FKS1 and a premature stop codon in FKS2, as was observed in a clinical isolate; select for variants with reduced susceptibility and locate mutations in FKS genes; and assess the roles of FKS1 and FKS2. METHODS A panel of FKS mutants was constructed using micafungin-susceptible parents by site-directed mutagenesis. Drug susceptibility, gene expression and glucan synthase activities were compared between mutants. Mutations acquired by selection were identified by DNA sequence analysis of FKS genes from selected variants. Single FKS deletants were constructed and their phenotypes examined. RESULTS Introduction of the hot-spot mutation in FKS1 alone conferred an intermediate reduction in susceptibility, and the premature stop codon in FKS2 alone had no effect on susceptibility, while severely reduced susceptibility equivalent to that of the clinical isolate required both mutations. Exposure of susceptible strains to micafungin yielded variants with an intermediate reduction in susceptibility that possessed a hot-spot mutation in FKS1. Further exposure to micafungin yielded variants with severely reduced susceptibility that acquired various single mutations in FKS2. The phenotypes of Δfks1 and Δfks2 mutants indicate that the two FKS genes are functionally redundant, while deletion of both FKS1 and FKS2 conferred synthetic lethality. CONCLUSIONS In the laboratory mutants of C. glabrata, clinically significant reduced susceptibility to micafungin required single nucleotide changes in both FKS1 and FKS2, and both genes encoded β-1,3-glucan synthase catalytic subunits.
A manufacturable 0.35 /spl mu/m 150 GHz f/sub T/ SiGe:C bipolar RF technology

Intensive world wide development work in high-speed bipolar RF technologies leads to a rapid increase in transistor performance. This paper describes a manufacturable leading-edge 0.35 /spl mu/m bipolar SiGe:C technology offering balanced transistor parameter sets with more than 150 GHz f/sub T/ and 180 GHz f/sub max/ as well as further integrated active and passive devices to serve a broad spectrum of applications.
Impacts of Keyword Frequency and Ranking Scope on Relevance of Web Search Results

In the past few decades, The World Wide Web has expanded vigorously and so has the information accessible on The Internet. In today’s world, it would be impossible to navigate through this gigantic network without the help of a modern Web Search Engine to find the relevant information. Since introduction of PageRank, many variations of it have been proposed which mainly focus on link structure of web and query context. In this work, a generalized PageRank is proposed to incorporate two important factors for quality search results; keyword frequency and ranking scope. Different variations of the proposed ranking algorithm are analyzed to establish importance of proposed factors in influencing relevance of search results with respect to keywords of interest. The experimental results show that the proposed algorithm significantly outperforms PageRank algorithm.
VideoSnapping

Aligning video is a fundamental task in computer graphics and vision, required for a wide range of applications. We present an interactive method for computing optimal nonlinear temporal video alignments of an arbitrary number of videos. We first derive a robust approximation of alignment quality between pairs of clips, computed as a weighted histogram of feature matches. We then find optimal temporal mappings (constituting frame correspondences) using a graph-based approach that allows for very efficient evaluation with artist constraints. This enables an enhancement to the "snapping" interface in video editing tools, where videos in a time-line are now able snap to one another when dragged by an artist based on their content, rather than simply start-and-end times. The pairwise snapping is then generalized to multiple clips, achieving a globally optimal temporal synchronization that automatically arranges a series of clips filmed at different times into a single consistent time frame. When followed by a simple spatial registration, we achieve high quality spatiotemporal video alignments at a fraction of the computational complexity compared to previous methods. Assisted temporal alignment is a degree of freedom that has been largely unexplored, but is an important task in video editing. Our approach is simple to implement, highly efficient, and very robust to differences in video content, allowing for interactive exploration of the temporal alignment space for multiple real world HD videos.
A HYBRID SOFTWARE DEVELOPMENT METHOD FOR LARGE-SCALE PROJECTS: RATIONAL UNIFIED PROCESS WITH SCRUM

Conventional software development methods have gradually been replaced by lightweight agile software development methods since the mid-1990s. This phenomenon is mainly due to the conventional methods’ shortcomings, including a slow adaptation to rapidly changing business requirements, and a tendency to be over budget and behind schedule. This paper analyzes characteristics, strengths, and weaknesses of both conventional and agile methods. This paper also explains the four major phases and nine disciplines of the Unified Process, and the common elements of the Scrum process. Finally, this paper suggests a new hybrid software development method that combines the Rational Unified Process with the Scrum process to accommodate the strengths of both methods while suppressing their weaknesses. The hybrid method can be utilized in the software industry, particularly, in the business sectors that deal with large-scale projects.
Towards Better Search and Sharing : the Growing Role of Relevance Feedback for Personalized Web Search

We are living in the era of fast information growth when we are hardly able to selforientate in the volume of information surrounding us and manage it. In the situation of huge information overflow that we are experiencing already now and will be experiencing sharply in the future we are trying to better understand how to treat information around us looking for new methods of organizing new information pieces or retrieving slices of information best matching our current needs. In this paper we are examining the growing role of relevance feedback to improve information retrieval in Web search systems and representing a shift to its active use in BESS (BEtter Search and Sharing) collaborative search system.