Miracle-dz/UniFAR-FTUs huggingface dataset:
AN EXPERIMENTAL ANALYSIS AND IMPLEMENTATION OF ONTOLOGY BASED QUERY EXPANSION

Search engines history goes back to the field of Information Retrieval, that has gone through a tremendous change over the period of time. Though search Engines have experienced many enhancements in the last few years, the query processing Techniques that the Information Retrieval (IR) Technology relies on are still based on Keywords. It is difficult to formulate queries which are well designed for retrieval purpose. Query Expansion can solve this problem. Query Expansion is normally aimed to form a query into one that is more responsive for Information Retrieval. Though there are many approaches aimed at query expansion, ontology based query expansion has been found to have more advantages compared to the traditional ones. This paper compares the performance of the Traditional query processing methodology with the Domain Independent Ontology based query expansion Methodology.
From lidar scans to roughness maps for wind resource modelling in forested areas

Abstract. Applying erroneous roughness lengths can have a large impact on the estimated performance of wind turbines, particularly in forested areas. In this study, a new method called the objective roughness approach (ORA), which converts tree height maps created using airborne lidar scans to roughness maps suitable for wind modelling, is evaluated via cross predictions among different anemometers at a complex forested site with seven tall meteorological masts using the Wind Atlas Analysis and Application Program (WAsP). The cross predictions were made using ORA maps created at four spatial resolutions and from four freely available roughness maps based on land use classifications. The validation showed that the use of ORA maps resulted in a closer agreement with observational data for all investigated resolutions compared to the land use maps. Further, when using the ORA maps, the risk of making large errors (> 25 %) in predicted power density was reduced by 40–50 % compared to satellite-based products with the same resolution. The results could be further improved for high-resolution ORA maps by adding the displacement height. The improvements when using the ORA maps were both due to a higher roughness length and due to the higher resolution.
Aircraft Inspection Using Unmanned Aerial Vehicles

—In this paper, we propose a coverage planning algorithm for inspecting an aircraft, using an Unmanned Ariel Vehicle (UAV). Inspecting structures (e.g. bridges, buildings, ships, wind turbines, aircrafts) is considered a hard task for humans to perform, and of critical nature since missing any detail could affect the structure’s performance and integrity. Additionally, structure inspection is a time and resource intensive task that should be performed as efﬁciently and accurately as possible. In this paper we introduce a search space coverage path planner (SSCPP) with a heuristic reward function that exploits our knowledge of the structure model, and the UAV’s onboard sensors’ models to generate resolution optimal paths that maximizes coverage. The proposed method follows a model based coverage path planning approach to generate an optimized path that passes through a set of admissible waypoints to fully cover a complex structure. The algorithm predicts the coverage percentage by using an existing model of the complex structure as a reference. A set of experiments were conducted in a simulated environment to test the validity of the proposed algorithm.
First order Galilean superfluid dynamics.

We study dynamics of an (anomalous) Galilean superfluid up to first order in derivative expansion, both in parity-even and parity-odd sectors. We construct a relativistic system—null superfluid, which is a null fluid (introduced in N. Banerjee, S. Dutta, and A. Jain Akash, [Phys. Rev. D 93, 105020 (2016). ]) with a spontaneously broken global U(1) symmetry. A null superfluid is in one-to-one correspondence with a Galilean superfluid in one lower dimension; i.e., they have the same symmetries, thermodynamics, constitutive relations and are related to each other by a mere choice of basis. The correspondence is based on null reduction, which is known to reduce the Poincare symmetry of a theory to Galilean symmetry in one lower dimension. To perform this analysis, we use off-shell formalism of (super)fluid dynamics, adopting it appropriately to null (super)fluids. We also verify these results via c → ∞ limit of a parent relativistic system.
Traffic Danger Recognition With Surveillance Cameras Without Training Data

We propose a traffic danger recognition model that works with arbitrary traffic surveillance cameras to identify and predict car crashes. There are too many cameras to monitor manually. Therefore, we developed a model to predict and identify car crashes from surveillance cameras based on a 3D reconstruction of the road plane and prediction of trajectories. For normal traffic, it supports real-time proactive safety checks of speeds and distances between vehicles to provide insights about possible high-risk areas. We achieve good prediction and recognition of car crashes without using any labeled training data of crashes. Experiments on the BrnoCompSpeed dataset show that our model can accurately monitor the road, with mean errors of 1.80% for distance measurement, 2.77 km/h for speed measurement, 0.24 m for car position prediction, and 2.53 km/h for speed prediction.
Rough Set Theory Based Fuzzy TOPSIS on Serious Game Design Evaluation Framework

This study presents a hybrid methodology for solving the serious game design evaluation in which evaluation criteria are based on meaningful learning, ARCS motivation, cognitive load, and flow theory (MACF) by rough set theory (RST) and experts’ selection. The purpose of this study tends to develop an evaluation model with RST based fuzzy Delphi-AHP-TOPSIS for MACF characteristics. Fuzzy Delphi method is utilized for selecting the evaluation criteria, Fuzzy AHP is used for analyzing the criteria structure and determining the evaluation weight of criteria, and Fuzzy TOPSIS is applied to determine the sequence of the evaluations. A real case is also used for evaluating the selection of MACF criteria design for four serious games, and both the practice and evaluation of the case could be explained. The results show that the playfulness (C24), skills (C22), attention (C11), and personalized (C35) are determined as the four most important criteria in the MACF selection process. And evaluation results of case study point out that Game 1 has the best score overall (Game 1 > Game 3 > Game 2 > Game 4). Finally, proposed evaluation framework tends to evaluate the effectiveness and the feasibility of the evaluation model and provide design criteria for relevant multimedia game design educators.
The contribution of ontologies to the creation of knowledge bases for the management of legal compliance in occupational health and safety

Occupational health and safety (OHS) is at the heart of corporate policies and the increasing trend towards litigation has contributed to the inflated number of regulatory texts published each year. OHS professionals are therefore faced with the need to process a growing amount of data in order to remain in compliance. They train themselves in law, draw upon internal expertise (the company's legal department) or external consultants (advisory and enforcement agencies) and equip themselves with information systems. These systems are mainly 'judicial monitoring' databases that contain regulatory texts and associated comments. For the most part, this data is complex to interpret and difficult to exploit given the growing number of texts, the expertise needed to understand them and the difficulty in being sure that they are relevant to the activities of the company. This need for clarity may be met by models and methods from artificial intelligence. Amongst these, we have selected the concepts of the ontology and the knowledge base. An ontology is a model of a particular domain of knowledge created for a specific purpose. Mainly used for the formalization of knowledge, it can also be used to define a common language between an information system and a community of actors (i.e. OHS professionals). A knowledge base is a set of knowledge that is specific to a given domain that can be exploited by a technology. The coupling between the ontology and the knowledge base makes it possible to automate certain tasks, such as monitoring, auditing, ensuring compliance, etc. This three-part article describes a methodology and an associated software tool that can ensure compliance. The first part identifies elements used in the definition and the proven benefits of ontologies and knowledge bases. The second describes the approach taken in the design of the ontology and its implementation as a rule base using a bespoke knowledge base editor. Finally, a concrete example of the formalization of regulatory knowledge (using the theme of harassment and violence at work) is presented to demonstrate the contributions and the limitations of the tool.
Pharmacological inhibition of s phingosine kinase isoforms alters estrogen receptor signaling in human breast cancer

Recently, crosstalk between sphingolipid signaling pathways and steroid hormones has been illuminated as a possible therapeutic target. Sphingosine kinase (SK), the key enzyme metabolizing pro-apoptotic ceramide to pro-survival sphingosine-1-phosphate (S1P), is a promising therapeutic target for solid tumor cancers. In this study, we examined the ability of pharmacological inhibition of S1P formation to block estrogen signaling as a targeted breast cancer therapy. We found that the Sphk1/2 selective inhibitor (SK inhibitor (SKI))-II, blocked breast cancer viability, clonogenic survival and proliferation. Furthermore, SKI-II dose-dependently decreased estrogen-stimulated estrogen response element transcriptional activity and diminished mRNA levels of the estrogen receptor (ER)-regulated genes progesterone receptor and steroid derived factor-1. This inhibitor binds the ER directly in the antagonist ligand-binding domain. Taken together, our results suggest that SKIs have the ability to act as novel ER signaling inhibitors in breast carcinoma. Journal of Molecular Endocrinology (2011) 46, 205–216
A Novel Method for Surface Defect Detection of Photovoltaic Module Based on Independent Component Analysis

This paper proposed a new method for surface defect detection of photovoltaic module based on independent component analysis (ICA) reconstruction algorithm. Firstly, a faultless image is used as the training image. The demixing matrix and corresponding ICs are obtained by applying the ICA in the training image. Then we reorder the ICs according to the range values and reform the de-mixing matrix. Then the reformed de-mixing matrix is used to reconstruct the defect image. The resulting image can remove the background structures and enhance the local anomalies. Experimental results have shown that the proposed method can effectively detect the presence of defects in periodically patterned surfaces.
Review of Flexure Bearing

Conventional type of bearing having disadvantage of backlash, higher friction and wear, in order to overcome this limitations new concept was developed i.e. linear bearing. Linear Bearing are nothing but deformable bodies having spiral cut. They offers various advantages over conventional bearing. Now a day’s technology of linear compressor uses linear motor which has very less friction. Piston motor, motor shaft is vertically supported by linear bearing. Present paper focuses on study of such linear bearing named as flexure bearing. FEA tool is used for analysis and design of bearing.
ON THE FOUR-PARAMETER BOND PRICING MODEL

A four-parameter random walk model for the short rate of interest is described in Wilmott et al. (15). For pricing zero-coupon bonds from the resulting partial differential equation based on this short rate model, a certain form of solution requires the solution of two first-order nonlinear ordinary dif- ferential equations. In the present paper we show the interesting result that, for obtaining solutions of the bond pricing equation, neither of these two equa- tions requires any differential equation solving techniques; in fact, both these first-order nonlinear differential equations can be solved simply by elementary integration. We include the corresponding yield curve and its asymptotic be- havior. We identify our results obtained here for the general four-parameter model in the two special cases of Vasicek (14) and Cox, Ingersoll and Ross (4) with those given by these authors.
2004 Insider Trading and Voluntary Disclosure

I investigate the incentives of insiders from publicly traded companies to voluntarily disclose their private information. This is done in a multi-asset Kyle-type trading framework where disclosure serves to attract discretionary liquidity trades. Equilibria where some insiders completely disclose their private information only exist when at least two assets are not traded by non-discretionary liquidity traders, referred to as noise traders. When at most one asset has no noise trading, then all insiders retain some information and trade upon it. The amount of information retained by insiders in this case increases with noise trading volume and equilibria where insiders do not reveal any information at all are more likely to exist as the number of assets increases.
WIYN OPEN CLUSTER STUDY. LXIII. ABUNDANCES IN THE SUPER-METAL-RICH OPEN CLUSTER NGC 6253 FROM HYDRA SPECTROSCOPY OF THE 7774 Å OXYGEN TRIPLET REGION

We present a spectroscopic abundance analysis of the old, super-metal-rich open cluster NGC 6253, with emphasis on its O abundance. High-dispersion, 7774 Å O i triplet region spectra of 47 stars were obtained using Hydra II on the CTIO Blanco 4 m. Radial velocity analysis confirms 39 stars consistent with single star membership, primarily at the turnoff. Thirty-six of these are included in our abundance analysis. Our differential analysis relative to the Sun yields primarily scaled-solar values, with weighted cluster averages of [O/H] = +0.440 ± 0.020, [Fe/H] = +0.445 ± 0.014, [Al/H] = +0.487 ± 0.020, [Si/H] = +0.504 ± 0.018, and [Ni/H] = +0.702 ± 0.018 (where the errors are &sgr; &mgr; ? > ). We discuss possible origins for the three known super-metal-rich clusters based upon their abundance patterns, Galactic locations, and space motions. The abundance patterns of NGC 6253 are very similar to those of NGC 6791 and NGC 6583. With the possible exception of oxygen, the abundances of these clusters are all close to scaled-solar, and they are similar to patterns seen in metal-rich disk dwarfs and giants. However, they also seem to differ from those of metal-rich bulge stars. We demonstrate that NGC 6253 is unusually oxygen rich (in [O/H]) for its 3.3 Gyr age. While we find [O/Fe] to be scaled-solar for NGC 6253, the more recently reported values for NGC 6791 show a large variation, from values close to scaled-solar down to values at least a factor of two below scaled-solar. We discuss the possibility that the scaled-solar [O/Fe] abundances of NGC 6253 and NGC 6791 might reflect a flattening of the Galactic [O/Fe] versus [Fe/H] relationship. This possibility may be consistent with disk star abundance data, which show an apparent “floor” at [O/Fe] ∼ − 0.1 ? > for [Fe/H] > 0 ? > , and with chemical evolution model results, which may predict such a flattening due to a decrease in supernova Fe yields at super-solar-metallicities. Orbit solutions for NGC 6791 allow that it may have formed in the inner disk and was then kicked out, but the origins of the other two much younger clusters remain mysterious. We re-evaluate the age of NGC 6583 in view of the evidence that the cluster is super-metal-rich, and confirm a probable age less than 1 Gyr (best range: 500–900 Myr). We also argue that it is unlikely the cluster is more than 3 kpc away (best range: 2–3 kpc) if the apparent turnoff, main sequence, and giants are all cluster members.
User Segmentation Based on Twitter Data Using Fuzzy Clustering

Social Networking Sites, which create platform for social interactions and sharing are the mostly used internet websites, thus are very important in today’s world. The vast usage of social networking sites (SNSs) has effected the business world, new business models are proposed, business process are renewed and companies try to create benefit form these sites. Besides the functional usage of SNSs such as marketing and customer relations, companies can create value by analyzing and mining the data on SNSs. In this paper, a new segmentation approach, using Text Mining and Fuzzy Clustering techniques. Text mining is process of extracting knowledge from large amounts of unstructured data source such as content generated by the SNSs users. Fuzzy clustering is an algorithm for cluster analysis in which the allocation of data points to clusters is fuzzy. In the proposed approach, users self description text are used as an input to the Text Mining process, and Fuzzy Clustering is used to extract knowledge from data. Using the proposed approach, companies can segment their customers based on their comments, ideas or any kind of other unstructered data on SNSs. DOI: 10.4018/978-1-4666-4213-3.ch014
A decision support system for application migration to the Cloud

Cloud computing enables the computing resources to be available for purchase on demand. The benefits like elasticity, exibility and expenditure reduction attract many enterprises to consider the migration of their applications to the Cloud. By the rapid expansion of Cloud computing market and the maturation of the offered solutions, the consumers have more and more choices in selecting Cloud offerings. However, when they face a large number of Cloud offerings which have similar features, an appropriate choice will be the key to guarantee a comparatively low operational cost. In this thesis, we propose a decision support system for application migration to the Cloud, by which consumers are able to obtain recommendations on selecting suitable Cloud services. We have evaluated this system with appropriate test cases and compared it with the existing tools and frameworks.
Ultralow equivalent magnetic noise in a magnetoelectric Metglas/Mn-doped Pb(Mg1/3Nb2/3)O3-PbTiO3 heterostructure

An ultralow equivalent magnetic noise of 6.2 pT/√Hz at 1 Hz was obtained in a bimorph heterostructure sensor unit consisting of longitudinal-magnetized Metglas layers and a transverse-poled 1 mol. % Mn-doped Pb(Mg1/3Nb2/3)O3-29PbTiO3 (PMN-PT) single crystal. Furthermore, the equivalent magnetic noise was ≤1 pT/√Hz at 10 Hz. Compared with previously reported multi-push-pull configuration Metglas/PMN-PT sensor units, the current heterostructure exhibits a higher magnetoelectric coefficient of 61.5 V/(cm × Oe), a similar equivalent magnetic noise at 1 Hz and a lower noise floor at several hertz range. The ultralow equivalent magnetic noise in this sensor unit is due to the low tangent loss and ultrahigh piezoelectric properties of Mn-doped PMN-PT single crystals.
Imaging in Compressed domain using Dreamlets

Summary The objective of this paper is to further investigate the theory and algorithm of wave propagation and imaging in the dreamlet domain for direct application of compressed seismic data. In our former work, dreamlet shows great application potential in efficient representation of seismic data. Based on the combination of dreamlet compression and wave propagation theory, we discuss one-way dreamlet wave propagation and imaging in terms of data processing in the compressed domain, that allows us to process only a few percentage of the decomposition coefficients of the whole data set to get the accurate imaging result. By using a 5-layer velocity model as numerical example, we show that the dreamlet coefficients of the seismic data is also decreasing with the depth of migration in the receiver side, meanwhile the imaging quality using the compressed data remains in a similar accuracy.
Analysing Amazonian forest productivity using a new individual and trait-based model (TFS v.1)

Abstract. Repeated long-term censuses have revealed large-scale spatial patterns in Amazon basin forest structure and dynamism, with some forests in the west of the basin having up to a twice as high rate of aboveground biomass production and tree recruitment as forests in the east. Possible causes for this variation could be the climatic and edaphic gradients across the basin and/or the spatial distribution of tree species composition. To help understand causes of this variation a new individual-based model of tropical forest growth, designed to take full advantage of the forest census data available from the Amazonian Forest Inventory Network (RAINFOR), has been developed. The model allows for within-stand variations in tree size distribution and key functional traits and between-stand differences in climate and soil physical and chemical properties. It runs at the stand level with four functional traits – leaf dry mass per area (Ma), leaf nitrogen (NL) and phosphorus (PL) content and wood density (DW) varying from tree to tree – in a way that replicates the observed continua found within each stand. We first applied the model to validate canopy-level water fluxes at three eddy covariance flux measurement sites. For all three sites the canopy-level water fluxes were adequately simulated. We then applied the model at seven plots, where intensive measurements of carbon allocation are available. Tree-by-tree multi-annual growth rates generally agreed well with observations for small trees, but with deviations identified for larger trees. At the stand level, simulations at 40 plots were used to explore the influence of climate and soil nutrient availability on the gross (ΠG) and net (ΠN) primary production rates as well as the carbon use efficiency (CU). Simulated ΠG, ΠN and CU were not associated with temperature. On the other hand, all three measures of stand level productivity were positively related to both mean annual precipitation and soil nutrient status. Sensitivity studies showed a clear importance of an accurate parameterisation of within- and between-stand trait variability on the fidelity of model predictions. For example, when functional tree diversity was not included in the model (i.e. with just a single plant functional type with mean basin-wide trait values) the predictive ability of the model was reduced. This was also the case when basin-wide (as opposed to site-specific) trait distributions were applied within each stand. We conclude that models of tropical forest carbon, energy and water cycling should strive to accurately represent observed variations in functionally important traits across the range of relevant scales.