Miracle-dz/UniFAR-FTUs huggingface dataset:
Conservation Properties of Unstructured Staggered Mesh Schemes

Classic Cartesian staggered mesh schemes have a number of attractive properties. They do not display spurious pressure modes and they have been shown to locally conserve, mass, momentum, kinetic energy, and circulation to machine precision. Recently, a number of generalizations of the staggered mesh approach have been proposed for unstructured (triangular or tetrahedral) meshes. These unstructured staggered mesh methods have been created to retain the attractive pressure aspects and mass conservation properties of the classic Cartesian mesh method. This work addresses the momentum, kinetic energy, and circulation conservation properties of unstructured staggered mesh methods. It is shown that with certain choices of the velocity interpolation, unstructured staggered mesh discretizations of the divergence form of the Navier? Stokes equations can conserve kinetic energy and momentum both locally and globally. In addition, it is shown that unstructured staggered mesh discretizations of the rotational form of the Navier? Stokes equations can conserve kinetic energy and circulation both locally and globally. The analysis includes viscous terms and a generalization of the concept of conservation in the presence of viscosity to include a negative definite dissipation term in the kinetic energy equation. These novel conserving unstructured staggered mesh schemes have not been previously analyzed. It is shown that they are first-order accurate on nonuniform two-dimensional unstructured meshes and second-order accurate on uniform unstructured meshes. Numerical confirmation of the conservation properties and the order of accuracy of these unstructured staggered mesh methods is presented.
A PROBABILISTIC-SPATIAL APPROACH TO THE QUALITY CONTROL OF CLIMATE OBSERVATIONS

Surface weather and climate observations are the backbone of a multitude of analyses, studies and assessments. Errors in the observations do occur; if left unidentified, they can have severe and adverse affects on analyses and the decisions that result from them. Rigorous quality control of climate data is probably the single most important thing an analyst can do to ensure a successful outcome. Traditionally, quality control (QC) systems have been designed to emphasize the identification of human errors in COOP-like (Cooperative Observer) observational records that occur while reading gauges and thermometers, recording the data on paper, and keypunching these data into electronic format. Traditional QC methods have employed a series of quality checks that an observation must pass if it is to be considered valid. The outcomes of these checks are typically of a “yes” or “no” nature, and the observation is flagged with notations based on these outcomes. Examples of such quality checks include range checks and internal and external consistency checks, some of which are operated manually. In general, this type of QC system can be termed categorical and deterministic; that is, they employ categorical validity checks, from which a determination of validity results. An ever-increasing number of climate observations are being made electronically at automated weather stations. The development of the ASOS (Automated Surface Observing System), SNOTEL (Snowpack Telemetry), RAWS (Remote Automated Weather Station), and Agrimet networks, and the prospect of a COOP modernization program, all reflect the increased importance of electronic sensors and automated data delivery systems now and in the future. These new measurement technologies are presenting a number of challenges for traditional QC systems that include the following:
Re-conceptualizing requirements engineering: findings from a large-scale, agile project

Agile development is a force that reshapes requirements engineering (RE). Agile RE processes are not constrained to pre-development phase like in traditional RE; they're evenly spread throughout development. High-level RE occurs at the project beginning, and then agile RE continues at each development cycle. Each development cycle starts with customer representatives discussing requirements with the development teams. To seek new understanding of the requirements engineering process in agile projects, we have applied the model of software development as a conversation. In this paper we describe this model and use it to explain a selection of findings from a case study in a large-scale agile project.
The state of DTN evaluation

The most common definition of a challenged network, or Delay-Tolerant Network, is one in which there is no guarantee of a contemporaneous end-to-end path from source to destination. Because of the breadth of of the field, a wide variety of evaluation techniques have been developed and utilized. The goal of this panel is to showcase and discuss an interesting and current selection of evaluation efforts. In this year’s CHANTS submissions over a third used the ONE simulator from Aalto University [1, 2]. Keeping in mind that not all papers were based on simulation, it is fair to say that the ONE is becoming the de-facto simulation tool for certain types of DTN research. This is beneficial in that it facilitates comparisons between routing protocols, and allows researchers to focus their efforts on a single accessible tool. However the growing body of work that compares protocols that exist only in simulation may indicate an over-reliance on simulation and could lead to overlooking important practical technical challenges in the field. Another approach to evaluation is to deploy trial nodes in a real environment. Masato Tsuru has been involved in such field tests in collaboration with Japan’s NIICT and will be able to discuss their reasons for carrying out their experiments and the challenges involved. In addition the DARPA DTN project involved a considerable amount of field testing, and BBN’s Armando Caro will be able to give his perspective on the value and importance of their tests.
Experiments in Unconstrained Offline Handwritten Text Recognition

A system for off-line handwritten text recognition is presented. It is characterized by a segmentation-free approach, i.e. whole lines of text are processed by the recognition module. The methods used for pre-processing, feature extraction, and statistical modelling are described, and several experiments on writer-independent, multiple writer, and single writer handwriting recognition tasks are conducted. Particularly, the incorporation of linear discriminant analysis, allograph character models, and statistical language knowledge is investigated. The evaluation results for lexicon-free handwriting recognition demonstrate the effectiveness of the proposed methods.
Pair-Aware Interference Alignment in Multi-User Two-Way Relay Networks

In this paper, K bidirectionally communicating node pairs with each node having N antennas and one amplify and forward relay having R antennas are considered. Each node wants to transmit d data streams to its communication partner. Taking into account that each node can perform self interference cancellation, a new scheme called Pair-Aware Interference Alignment is proposed. In this scheme, the transmit precoding matrices and the relay processing matrix are chosen in such a way that at any given receiver all the interfering signals except the self interference are within the interference subspace and the useful signal is in a subspace linearly independent of the interference subspace. If the number of variables is larger than or equal to the number of constraints in the system, the system is classified as proper, else as improper. Through simulations it is shown that for a proper system (2Kd≤2N+R-d), interferences can be perfectly aligned and the useful signals can be decoded interference-free at the receivers. An iterative algorithm to achieve the interference alignment solution is proposed. Also for the proper system fulfilling a certain additional condition, which will be derived in this paper, a closed form solution is proposed.
Basin Clustering of Turkey by Use of Monthly Stream-Flow Data

Security of the energy supply is an important topic in energy field. It has two parts which are supply and demand. To ensure that demand is met, the supply at the specific time points has to be known or predicted. Supply is predicted by use of seasonal, yearly and regional information. The stream-flow dataset resolution is monthly and it supplies the yearly and seasonal information. The only missing part for supply prediction is the regional information. The aim of this study to find the basin based regional clustering of the streams and correspondingly hydroelectric power plants. In this paper, 14 out of 26 basins of Turkey, which contain over 80% of the hydroelectric power plants of Turkey in Dispatcher Information System, are clustered by use of different clustering techniques. Results are visualized on Turkey basin map.
ARRANGEMENTS: ISSUES AND EXPERIENCES FROM THE CARIBBEAN ECONOMIES

Although a Currency Board is a simple monetary arrangement, there is a range of important policy issues that must be addressed by the domestic monetary authorities. If one defines policy misalignment as deviation from such policy rule then such mistakes have been associated with either external deficit or contradictory effects on GDP. This paper seeks to evaluate the exchange rate and interest rate misalignment in six Caribbean economies that have adopted Currency Board Arrangements. JEL classification: F33, F41
Effective Exchange Rates of the Bulgarian Lev 1879-1939

The paper constructs the first series of nominal and real effective exchange rates of the Bulgarian Lev from its establishment in 1879 until 1939. The dynamics of both indicators during the Classical Gold Standard fits the general picture of exchange rate development of other European countries while their movements in the Interwar years reflects the exchange rate policy of the monetary authority and the price effects of the Great Depression. The study also provides econometric estimation of the impact of the real effective exchange rates and foreign demand on Bulgaria’s real export performance allowing for some policy implications.
Experimental characterization of the nonlinear behavior of RF amplifiers

Using specifically designed broadband periodic random excitation signals, the best linear approximation of RF amplifiers is measured. The proposed technique: 1) takes into account the measurement uncertainty and the nonlinear distortions and 2) detects, quantifies, and classifies the nonlinear distortions with confidence bounds. The approach is suitable for the experimental characterization of existing amplifiers
2005 7 th International Conference on Information Fusion ( FUSION ) Sequential Auxiliary Particle Belief Propagation

This paper discloses a novel algorithm for efficient inference in undirected graphical models using Sequential Monte Carlo (SMC) based numerical approximation techniques. The methodology developed, titled "Auxiliary Particle Belief Propagation ", extends the applicability of the much celebrated (Loopy) Belief Propagation (LBP) algorithm to non-linear; non-Gaussian models, whilst retaining a computational cost that is linear in the number ofsample points (or particles). Furthennore, we provide an additional extension to this technique by analysing temporally evolving graphical models, a problem which remains largely unexplored in the scientific literature. The work presented is thus a general framework that can be applied to a plethora of novel distributedfusion problems. In this paper; we apply our inference algorithm to the (sequential problem of) articulated object tracking.
Safety Evacuation Measures in Urban Subway Fire

The emergency incidents in urban subway system were analyzed. The main incident of emergency incidents was gained, then the reason of main emergency incident was analyzed. The different smoke control and evacuation modes were discussed, then the best smoke control and evacuation mode were obtained. Smoke spread at platform was simulated by FDS+EVAC. The relation of soot density, extinction coefficient and evacuation speed have liner relationship. The main influence factors of evacuation time were analyzed. The simulation results indicate that the existence of automatic fare gates of metro reduces the efficiency of evacuation. The evacuation time of no automatic fare gate is longer than evacuation time of automatic fare gate around 40%.
A Hierarchical Domain Model-Based Multi-Domain Selection Framework for Multi-Domain Dialog Systems

We proposed a hierarchical domain model (HDM)-based multi-domain selection framework (MDSF) for multi-domain dialog systems. The HDM-based MDSF statistically detects one or more candidate domains and heuristically determines one or more final domains from among the candidate domains. The HDM is used in both the candidate domain detection and final domain determination components. Multi-domain dialog systems that employ the HDM-based MDSF provide service to one or more domains at the same time, whereas traditional multi -domain dialog systems provide service to only one domain at a time. To validate the HDM-based MDSF, we developed a multi-domain dialog system for TV program, video-on-demand, and TV device domains. The experimental results show that the HDM-based MDSF correctly selects one or more domains and enables multi-domain dialog systems to provide more accurate and rapid dialog service than traditional multi-domain dialog systems.
Data Extraction Based on Index Path in Web

Data extraction in Web is to obtain the desired information to users in Web pages. For a more accurately valuable data extraction, this paper proposes a new method called data extraction based on index path in Web (DEIP) . This approach establishes the index path for each text node using XML DOM; defines the prefix of data-rich by keywords in the index path; generate extraction rule and obtain a wrapper according. The wrapper can extract data automatically in the same domain from a Website. It does relevant to the continuity, the structural similarity, and the location relations of the useful information in Web pages, but not the HTML tag, Experiments indicate that this method is efficient in the recall and the precision of data extraction.
Hoarders Only Discount Consumables and Are More Patient for Money

Individuals with hoarding disorder (HD) excessively acquire and retain goods while also exhibiting characteristics of impulsivity and addiction. However, HD individuals do not always perform impulsively in experiments, they do not appear interested in money, and they exhibit many features of risk-aversion and future-planning. To examine impulsivity in HD, we compared validated community participants high and low in hoarding tendencies on questionnaire measures of hoarding and impulsivity as well as a standard experimental measure of impulsivity (intertemporal discounting) that was modified to compare decisions about money, pens, and snacks. Common discounting effects were replicated. Compared to the low hoarding group, the high hoarding group was more impatient for consumables (pens and snacks) but they were more patient for money. This increased patience for money in high hoarding individuals is in contrast to all other studies on discounting in disordered populations, but consistent with the phenomenology of HD. HD does not appear to be driven by a fundamental inability to wait, but rather a specific, potent desire for consumable rewards.
A Zoomable Mapping of a Musical Parameter Space Using Hilbert Curves

Abstract This article presents an interface for navigating a musical parameter space. The entire combinatorial space of a ten-parameter synthesizer is laid out as a two-dimensional surface on a multi-touch screen. The surface can be scrolled and zoomed using touch-screen swipe and pinch gestures, reminiscent of a map application. The user can place markers on the surface to flag favorites and to explore regions of different sizes around these points. The mapping from the two-dimensional surface to the higher-dimensional parameter space uses a space-filling curve. Hilbert curves constructed from Gray codes with long bit runs can be used to preserve locality as much as is possible, while still maintaining access to all possibilities. A user study was performed to compare this parameter mapping with a more traditional one-slider-per-parameter interface. Questionnaire responses indicate that different mapping strategies suit different stages of the creative process. The combination of the two interfaces was deemed more useful than either individually, reinforcing the notion that a combination of divergent and convergent processes is important for creative tasks.
Faraday effect based optical fiber current sensor for tokamaks

Fiber optical current sensor (FOCS) is a technique considered to be compatible with the ITER nuclear environment. FOCS principle is based on the magneto-optic Faraday effect that produces non-reciprocal circular birefringence when a magnetic field is applied in the propagation direction of the light beam. The magnetic field or the electrical current is deduced from the modification of the state of polarization of light. The linear birefringence of the fiber related with non-perfect manufacturing, temperature changes or stress constitute a parasitic effect that reduces the precision and sensitivity of FOCS. A two-pass optical scheme with a Faraday mirror at the end has been proposed to compensate the influence of linear birefringence. In this paper we perform a Stokes analysis of the two-pass optical scheme to highlight the fact that the linear birefringence is not compensated perfectly by the Faraday mirror when non-reciprocal birefringence such as Faraday effect is also present.
Collapsed Variational Bayesian Inference for PCFGs

This paper presents a collapsed variational Bayesian inference algorithm for PCFGs that has the advantages of two dominant Bayesian training algorithms for PCFGs, namely variational Bayesian inference and Markov chain Monte Carlo. In three kinds of experiments, we illustrate that our algorithm achieves close performance to the Hastings sampling algorithm while using an order of magnitude less training time; and outperforms the standard variational Bayesian inference and the EM algorithms with similar training time.
Structural lubricity: Role of dimension and symmetry

– When two chemically passivated solids are brought into contact, interfacial interactions between the solids compete with intrabulk elastic forces. The relative importance of these interactions, which are length-scale dependent, will be estimated using scaling arguments. If elastic interactions dominate on all length scales, solids will move as essentially rigid objects. This would imply superlow kinetic friction in UHV, provided wear was absent. The results of the scaling study depend on the symmetry of the surfaces and the dimensionalities of interface and solids. Some examples are discussed explicitly such as contacts between disordered three-dimensional solids and linear bearings realized from multiwall carbon nanotubes.
Dagstuhl Workshop on Scenario Management Contents Introduction and Overview Agenda Subgroup Mission Statements Participant Abstracts Scenario Management: an Interdisciplinary Approach Editorial, Special Issue of Ieee Transactions on Software Engineering Editorial, Special Issue of Requirements Engin

ion helps us to manage complexity when we deal with large sets of scenarios. Type abstraction leads from the extensional to the intensional level. Content abstraction allows us to use boxes with names instead of full descriptions. Composition abstraction consolidates a set of scenarios into a common higher-level scenario. Generalization abstraction factors out common properties. Usage abstraction lets one scenario make use of other scenarios that provide lower-level services. Aspect abstraction focuses scenarios on one particular aspect of the problem. To what extent we need these kinds of abstraction in which situations is still a research topic. Scenarios Support the Acquisition and Impact Analysis of Business Rules Sol J. Greenspan, GTE Labs, Waltham, USA Business Rules (BRs) are decisions made to achieve the goals of an enterprise, and comprise an important set of requirements on the (human and automated) systems that support the running of the enterprise. For example, a bank with the goal of „reducing fraud“ might impose the rule that checks over $ 5000 require a second signature, besides the bank tellers before being cashed. There may be a large set of BRs involving many goals, activities and agents. When a statement is made such as „in context C use rule R to achieve goal G,“ there is typically uncertainty about the degree of effectiveness if the rule is followed, the consequences of not following it, and the accuracy of the context in which it is considered applicable. Scenarios of enterprise operation help in several ways; to explore and decide on BRs; to discover conflicts; and, if specified sufficiently formally, to support rapid deployment/evolution of the BRs. Because BRs are usually heuristic and speculative, their effectiveness, risks and correctness of context can often only be confirmed or measured by observing the actual running of the enterprise. Scenarios are, again, the proposed tools for providing feedback to check the BRs. In our work at GTE Labs, we base BRs on a conceptual enterprise model and a decision support system, and we simulate business scenarios to develop and validate the rules. Requirements Elicitation and Validation with Real World Scenes
Classification of EEG signals based on AR model and approximate entropy

The analysis of electroencephalogram (EEG) signal is a low-cost and effective technique to examine electrical activity of the brain and diagnose brain diseases in the Brain Computer Interface (BCI) applications. Classification of EEG signals is an important task in BCI applications. This paper investigates two common methods of feature extraction on EEG signals, autoregressive (AR) model and approximate entropy. AR coefficients of each segment of each channel are calculated by AR model and entropies of each channel are also calculated by approximate entropy. A combination strategy of feature extraction, where each feature vector consists of AR coefficients and approximate entropies, is proposed in this paper. Extreme learning machine is employed as a classifier for evaluating the classification performance. The classification of five different mental tasks is evaluated by the proposed method. It can be observed from experimental results that the proposed method can effectively improve the classification performance, and achieve a good compromise between classification accuracy and computational cost.
SPECTROSCOPIC REDSHIFTS FOR SEVEN LENS GALAXIES

We report Very Large Telescope observations of 11 lensed qua sars, designed to measure the redshifts of their lens galaxies. We successfully determined the redshi fts for seven systems, five of which were previously unknown. The securely measured redshifts for the lens ing galaxies are: HE0047 −1756 z = 0.408; PMNJ0134−0931z = 0.766; HE0230−2130z = 0.522; HE0435−1223z = 0.455; SDSS0924 +021z = 0.393; LBQS1009−025 z = 0.871; and WFIJ2033 −472 z = 0.658. For four additional systems (BRI0952 −0115, Q1017−207, Q1355−2257 and PMNJ1632 −003) we estimate tentative redshifts based on some features in their spectra. Subject headings: cosmology: gravitational lensing — Quasars: general — Quas ars: individual: HE0047−1756, PMNJ0134 −0931, HE0230−2130, HE0435−1223, SDSS0924 +021, BRI0952−0115, LBQS1009 −025, Q1017−207, Q1355−2257, PMNJ1632 −003, WFIJ2033−472