Miracle-dz/UniFAR-FTUs huggingface dataset:
EXTERNAL HEAT TRANSFER PREDICTIONS IN SUPERSONIC TURBINES USING THE REYNOLDS AVERAGED NAVIER-STOKES EQUATIONS

External heat transfer predictions are performed for two-dimensional turbine blade cascades. The Reynolds averaged Navier-Stokes equations with algebraic (Baldwin-Lomax) and two-equation (low-Re k ? ) turbulence closures are solved with an explicit Runge-Kutta time-marching nite volume method. Comparisons with measurement for subsonic and transonic cascades show good agreement in some cases, but also reveals problems with transition prediction and turbulence modeling. Stability, grid independence and problems in the stagnation point region are investigated. Blind simulations of a supersonic cascade are included to demonstrate the methods capability in handling this type of ows. Nomenclature cp Speciic heat J=kgK] C 1 , C 2 , C, k , Turbulence model constants ] D Turbulence model term J=kgs] E Turbulence model term J=kgs 2 ] e0 Total energy J=kg] f1, f2, f Damping functions ] k Turbulent kinetic energy J=kg] le Local equilibrium length scale m] p Static pressure Pa] P Production of k W=m 3 ] Pr Prandtl number ] qi Heat ux W=m 2 ] S Strain parameter ] T Static temperature K] ui Velocity m=s] yn Normal distance from the wall m] Dissipation of k J=kgs] ij Kronecker's delta function ] Speciic heat ratio ] Dynamic viscosity Ns=m 2 ] Density kg=m 3 ] S Extra Source Term, equation J=m 3 s 2 ] ij Shear stress tensor N=m 2 ] Vorticity parameter ] Subscript: t Turbulent contribution Superscript: lam Laminar part turb Turbulent part 0 Not an averaged quantity
Digital Computation of Linear Canonical Transforms

We deal with the problem of efficient and accurate digital computation of the samples of the linear canonical transform (LCT) of a function, from the samples of the original function. Two approaches are presented and compared. The first is based on decomposition of the LCT into chirp multiplication, Fourier transformation, and scaling operations. The second is based on decomposition of the LCT into a fractional Fourier transform followed by scaling and chirp multiplication. Both algorithms take ~ N log N time, where N is the time-bandwidth product of the signals. The only essential deviation from exactness arises from the approximation of a continuous Fourier transform with the discrete Fourier transform. Thus, the algorithms compute LCTs with a performance similar to that of the fast Fourier transform algorithm in computing the Fourier transform, both in terms of speed and accuracy.
Validation of Machine Learning and Visualization based Static Code Analysis Technique

Software security has always been an afterthought in software development which results into insecure software. Companies rely on penetration testing for detecting security vulnerabilities in their software. However, incorporating security at early stage of development reduces cost and overhead. Static code analysis can be applied at implementation phase of software development life cycle. Applying machine learning and visualization for static code analysis is a novel idea. Technique can learn patterns by normalized compression distance NCD and classify source code into correct or faulty usage on the basis of training instances. Visualization also helps to classify code fragments according to their associated colors. A prototype was developed to implement this technique called Code Distance Visualizer CDV. In order test the efficiency of this technique empirical validation is required. In this research we conduct series of experiments to test its efficiency. We use real life open source software as our test subjects. We also collected bugs from their corresponding bug reporting repositories as well as faulty and correct version of source code. We train CDV by marking correct and faulty version of code fragments. On the basis of these trainings CDV classifies other code fragments as correct or faulty. We measured its fault detection ratio, false negative and false positive ratio. The outcome shows that this technique is efficient in defect detection and has low number of false alarms.
Learning Bayesian network structures by estimation of distribution algorithms: An experimental analysis

Learning the structure of a Bayesian network (BN)from a data set is NP-hard. In this paper, we discuss a novel heuristic based on estimation of distribution algorithms (EDA), a new paradigm for evolutionary computation that is used as a search engine in the BN structure learning problem. The purpose of this work is to study the parameter setting of the EDA and to fix a "good" set of parameters. For this purpose, the EDA-based procedure is applied on several benchmarks to recover the original structure from data. The quality of the learned structure is assessed using several performance indexes.
Genetic inference of population dynamics in the American pika: Identifying appropriate scales of inference within a region of declining survival

How species will respond to the changing climate is poorly understood, but will become increasingly important to understand as the climate changes further. One way to predict the eventual effects of climate change on many species is to study early effects of contemporary climate change on a model species that is known to be climate-sensitive. The American Pika (Ochotona princeps) typically occurs in alpine habitats and has a thermally sensitive physiology, making it an ideal model that is already being widely studied for these effects. This study used SNPs (Single Nucleotide Polymorphisms) from RADseq (Restriction site Associated DNA sequencing), a novel genetic analysis technique, to analyze the genetic composition of a regional pika population in the Colorado Rocky Mountains predicted to have three subpopulations. Using this method of analysis, the pika in this region were found to be genetically similar with little differentiation between subpopulations. For this population heterozygosity was generally low, but there were differences in levels of inbreeding between individuals and some subpopulations. These results show high levels connectivity under current conditions, and variable dispersal at the local level. This study also highlights the differences between data from SNPs and microsatellites used in previous studies, and provides a baseline for the comparison of future studies using SNPs from RADseq.
A peer-to-peer zone-based two-level link state routing for mobile ad hoc networks

A new global positioning system (GPS)-based routing protocol for ad hoc networks, called zone-based hierarchical link state (ZHLS) routing protocol, is proposed. In this protocol, the network is divided into nonoverlapping zones. Each node only knows the node connectivity within its zone and the zone connectivity of the whole network. The link state routing is performed on two levels: focal node and global zone levels. Unlike other hierarchical protocols, there is no cluster head in this protocol. The zone level topological information is distributed to all nodes. This "peer-to-peer" manner mitigates traffic bottleneck, avoids single point of failure, and simplifies mobility management. Since only zone ID and node ID of a destination are needed for routing, the route from a source to a destination is adaptable to changing topology. The zone ID of the destination is found by sending one location request to every zone. Simulation results show that our location search scheme generates less overhead than the schemes based on flooding. The results also confirm that the communication overhead for creating and maintaining the topology in the proposed protocol is smaller than that in the flat LSR protocol. This new routing protocol provides a flexible, efficient, and effective approach to accommodate the changing topology in a wireless network environment.
Overview of micro-grid energy management system research status

Micro-grid has gradually become a new method for developed countries to solve many problems in the traditional power system. In this paper, the concept of micro-grid and energy management system is introduced firstly, and then the important roles of the application of energy management technology in micro-grid system are described. Combined the literature, a summary is made on the development status of micro-grid energy management system at home and abroad, then the corresponding feasible solutions to the problem of key technical problems was proposed. Finally, the outlook of the development trend of micro-grid energy management system in the future is made.
Organogenesis of the Caenorhabditis elegans intestine.

The intestine of Caenorhabditis elegans is an epithelial tube consisting of only 20 cells and is derived clonally from a single embryonic blastomere called E. We describe the cellular events that shape the intestine. These events include cytoplasmic polarization of cells in the intestinal primordium, the intercalation of specific sets of cells, the generation of an extracellular cavity within the primordium, and adherens junction formation. The polarization of the intestinal primordium is associated with the generation of an asymmetric microtubule cytoskeleton, and microtubule function plays a role in subsequent cell polarity. We show that an isolated E blastomere is capable of generating polarized intestinal cells, indicating that some of the major events in intestinal organogenesis do not depend upon interactions with surrounding tissues. We compare and contrast intestinal organogenesis with some of the basic steps in development of a second epithelial organ, the pharynx, and suggest how these differences lead to organs with distinct shapes.
Generic Management Challenges of Adopting IT-Shared Services

This study empirically explores generic management challenges in the early phase of adopting IT-shared services, which are organizational independent units for delivering organization-wide IT services. Data has been collected by the means of twenty case studies, conducted between 2002 and 2010. Seven themes are general, reoccurring management challenges for the whole organization that includes business units as well as IT units. The challenges are as follows: (i) ability to deliver IT services, (ii) communication, (iii) IT service portfolios, (iv) nature of IT services, (v) power and control, (vi) pricing, and (vii) service level agreements. Better understanding these challenges is essential for further research on how to manage the transition towards shared-services arrangements. This study, therefore, is an elementary step in this complex endeavor, providing valuable insights into which management challenges need consideration.
Predictive Windows for Delay Compensation in Applications * Telepresence

Predictive Kalman filters can be used to predict positions of a mouse when it is operated under some basic assumptions. This prediction can be used to estimate what portions of a larger image an operator wants to view. This paper discusses theory and experimentation being done at the University of Alberta using predictive Kalman filters to provide predictive windows for low bandwidth telepresence applications. We compare several state models used in prediction with each other and also with having no prediction, both with numerical measures, and on human subjects. We show that the constant velocity model provides the best prediction results.
Accurate approximation method for prediction of class I MHC affinities for peptides of length 8, 10 and 11 using prediction tools trained on 9mers

UNLABELLED Several accurate prediction systems have been developed for prediction of class I major histocompatibility complex (MHC):peptide binding. Most of these are trained on binding affinity data of primarily 9mer peptides. Here, we show how prediction methods trained on 9mer data can be used for accurate binding affinity prediction of peptides of length 8, 10 and 11. The method gives the opportunity to predict peptides with a different length than nine for MHC alleles where no such peptides have been measured. As validation, the performance of this approach is compared to predictors trained on peptides of the peptide length in question. In this validation, the approximation method has an accuracy that is comparable to or better than methods trained on a peptide length identical to the predicted peptides. AVAILABILITY The algorithm has been implemented in the web-accessible servers NetMHC-3.0: http://www.cbs. dtu.dk/services/NetMHC-3.0, and NetMHCpan-1.1: http://www.cbs. dtu.dk/services/NetMHCpan-1.1
FAST DISINTEGRATING TABLET TECHNOLOGY: NEWLY PROSPECTS

Tablet that disintegrate rapidly in the mouth are convenient for patient who have difficulty in swallowing conventional dosages forms. Although various formulation technologies like Zydis Technology, Durasolve Technology, Orasolve Technology, Flash Dose Technology, Wow Tab Technology, Flash Tab Technology, Quicksolv Technology, Lyos Technology, Fast Melt Technology and Zip-lets Technology are used. This review highlights numerous techniques to explain the phenomenon of preparing mouth disintegration tablets like Freeze Drying, Moulding, Sublimation, Spray Drying, Direct compression, Wet granulation and Dry granulation.
Reading the Tea Leaves: Model Uncertainty, Robust Forecasts, and the Autocorrelation of Analysts' Forecast Errors

We put forward a model in which analysts are uncertain about a firm’s earnings process. Faced with the possibility of using a misspecified model, analysts issue forecasts that are robust to model misspecification. We estimate that this mechanism explains approximately 60% of the autocorrelation in analysts’ forecast errors. The remainder stems from the cross-sectional variation in mean forecast errors and in analysts’ estimation errors of the persistence of earnings growth shocks. Consistent with our model, we find that analysts learn about some features of the earnings process but not others, and this learning reduces, but does not eliminate, the autocorrelation of forecast errors as firms age. Other potential explanations for the autocorrelation of analyst forecast errors are rejected. Our model of robust forecasting applies not only to analysts’ forecasts but also to all model-based forecasts.
The Effect of the Addition of Tricalcium Phosphate to 5% Sodium Fluoride Varnishes on the Microhardness of Enamel of Primary Teeth

Aim. The aim of this study was to compare the effect of pH cycling on the microhardness of the enamel of primary human teeth treated with a conventional brown Sodium Fluoride (5% NaF) Varnish to those treated with a white Fluoride Varnish (5% NaF) enhanced with functionalized tricalcium phosphate (fTCP). Materials and Methods. Ninety extracted caries-free primary incisors were washed in a detergent and divided into three groups; group A received no treatment, teeth in group B were coated with Sodium Fluoride (5% NaF) Varnish, while teeth in group C were coated with 5% NaF varnish enhanced with functionalized tricalcium phosphate (fTCP). After ten days of pH cycling, the surface microhardness of the teeth was measured using a Knoop indenter. Results. The mean Knoop hardness number (KHN) of 5% NaF with fTCP was greater than that of 5% NaF alone while the control group had the lowest mean KHN. Conclusion. The results of this study suggest that the use of an additive such as fTCP to a fluoride varnish significantly improves the protective ability of the varnish on primary teeth in vitro.
Study on Segmentation of 3D Human Body Based on Point Cloud Data

The segmentation of 3D human body is the key technology for Digital clothing, digital body measurement, computer animation and so on, but there are some shortcomings. So the segmentation of 3D body based on point cloud data is studied, and the method that the entire body model is divided into six parts is proposed in this paper. In the proposed method, some techniques such as slice, curve fitting and other mathematical tools are used to segment 3D human body according to the surface feature points. Finally, experimental results show that the proposed method can improve the accuracy of segmentation.
Liquidity, Trends and the Great Recession

We study the impact that the liquidity crunch in 2008-2009 had on the U.S. economy’s growth trend. To this end, we propose a model featuring endogenous growth a la Romer and a liquidity friction a la Kiyotaki-Moore. A key ﬁnding in our study is that liquidity declined around the demise of Lehman Brothers, which lead to the severe contraction in the economy. This liquidity shock was a tail event. Improving conditions in ﬁnancial markets were crucial in the subsequent recovery. Had conditions remained at their worst level in 2008, output would have been 20 percent below its actual level in 2011.
Real-time update with joint optimization of route selection and update scheduling for SDNs

Due to flow dynamics, a software defined network (SDN) may need to frequently update its data plane so as to optimize various performance objectives, such as load balancing. Most previous solutions first determine a new route configuration based on the current flow status, and then update the forwarding paths of existing flows. However, due to slow update operations of Ternary Content Addressable Memory (TCAM) based flow tables, unacceptable update delays may occur, especially in a large or frequently changed network. According to recent studies, most flows have short duration and the workload of the entire network may vary after a long duration. As a result, the new route configuration may be no longer efficient for the workload after the update, if the update duration takes too long. In this paper, we address the real-time route update, which jointly considers the optimization of flow route selection in the control plane and update scheduling in the data plane. We formulate the delay-satisfied route update (DSRU) problem, and prove its NP-Hardness. Two algorithms with bounded approximation factors are designed to solve this problem. We implement the proposed methods on our SDN testbed. The experimental results and extensive simulation results show that our method can reduce the route update delay by about 60% compared with previous route update methods while preserving a similar routing performance (with link load ratio increased less than 3%).
Acm Sigir 2006 Workshop on "evaluating Exploratory Search Systems" Eess 2006 Preface from the Workshop Co-chairs Evaluating Exploratory Search Systems Building Models of Search Success with Experience Sampling and Event Logs

Exploratory search tasks stack additional challenges on the already difficult task of evaluating searching effectiveness. The experience sampling method has been used at MSN Search to assess the relationship between individual result and overall session satisfaction. Combining experience sampling with robust modeling of implicit variables has been shown to yield a productive model for general search. Methods for extending this approach to new systems designed to support exploratory search are proposed.
Modal Matching: An Approach to Natural Compliant Jumping Control

This letter derives the basic concept of modal matching-an approach to natural motion control. Modal matching exploits the nonlinearity of the rigid multi-body dynamics (and the variability of the elastic transmissions) as degree of freedom to fit the natural plant dynamics to the desired dynamics of the task. Modal matching achieves a desired intrinsic oscillation behavior, which is locally equivalent to the dynamics of the basic spring-loaded inverted pendulum or pogo-stick model (both implementing a linear inertia acting on a linear spring), well established in locomotion analysis and control. Using the concept of modal matching, an efficient and effective methodology to natural jumping control is introduced.
Meta‐analysis of clinical metabolic profiling studies in cancer: challenges and opportunities

Cancer cell metabolism has received increasing attention. Despite a boost in the application of clinical metabolic profiling (CMP) in cancer patients, a meta‐analysis has not been performed. The primary goal of this study was to assess whether public accessibility of metabolomics data and identification and reporting of metabolites were sufficient to assess which metabolites were consistently altered in cancer patients. We therefore retrospectively curated data from CMP studies in cancer patients published during 5 recent years and used an established vote‐counting method to perform a semiquantitative meta‐analysis of metabolites in tumor tissue and blood. This analysis confirmed well‐known increases in glycolytic metabolites, but also unveiled unprecedented changes in other metabolites such as ketone bodies and amino acids (histidine, tryptophan). However, this study also highlighted that insufficient public accessibility of metabolomics data, and inadequate metabolite identification and reporting hamper the discovery potential of meta‐analyses of CMP studies, calling for improved standardization of metabolomics studies.
A Comparison between IT governance research and concepts in COBIT 5

Information Technology Governance (ITG) concepts have continuously evolved over the years. Introductions of new concepts, standards, regulations and frameworks in ITG, such as COBIT 5, create greater diversions in ITG concepts. This paper aims to investigate and compare concepts in academic literatures to COBIT 5. This study reviews and analyzes Information Systems (IS) literatures that adhere to ITG. We identified 100 articles that published in accredited journals during 2002 to 2012. Then, we compare the finding from these articles to the concepts proposed in COBIT 5. This study found both similarities and differences and also suggested some interesting researches on several key areas that should be conducted for better understanding of ITG. Keywords-IT governance; IT management; IT decision making; COBIT 5; framework
SEMANTIC INTEGRITY CONSTRAINT VIOLATIONS CHECK FOR SPATIAL DATABASE UPDATING

An efficient spatial data structure in a GIS system for database updating is required in order to minimising of spatial constraint violations and timesaving. An automated constraint checking procedure has been introduced to perform constraint violations check at compiling time before updating the database. Formal definitions of spatial data types were used in attempt to formulate novel equations and architectures to detect constraint violations and framework for spatial repository. A data structure called Semantic Spatial Outlier R-Tree (SSR-Tree) was proposed for the Semantic Integrity Constraints Checking System to improve the functionality of the proposed method. The R-Tree or its variants have been widely-used data structures for this purpose and which are based on a heuristic optimization but unable to perform semantic spatial join queries at database updating. An experiment was conducted using actual spatial data and results revealed that the performance of SSR-Tree is notably superior to the R*-Tree and R-Tree for conducting semantic spatial join queries. * Corresponding author. Tel. :+86-451-86400863; fax: +86-451-86414093.