Miracle-dz/UniFAR-FTUs huggingface dataset:
1 TH / P 6-24 Numerical analyses of baseline JT-60 SA design concepts with the COREDIV code

JT-60SA reference design scenarios at high (#3) and low (#2) density have been analyzed with the help of the self-consistent COREDIV code. Simulations results for standard carbon wall and the full W have been compared in terms of the influence of impurities, both intrinsic (C, W) and seeded (N, Ar, Ne, Kr) on the radiation losses and plasma parameters. For the scenario #3 in carbon environment the regime of detachment on divertor plates can be achieved with N or Ne seeding, whereas for the low density and high power scenario (#2), the carbon and seeding impurity radiation does not effectively reduce power to the targets. In this case only increase of neither average density or edge density together with Kr seeding might help to develop conditions with strong radiation losses and semi-detached conditions in the divertor. The calculations show that in case of tungsten divertor the power load to the plate is mitigated by seeding and the central plasma dilution is smaller compared to the carbon divertor. For the high density case with neon seeding operation in full detachment mode is observed. Ar seems to be an optimal choice for the low density high power scenario #2, showing wide operating window, whereas Ne leads to high plasma dilution at high seeding levels albeit not achieving semidetached conditions in the divertor.
Iterative Coupling of Boundary and Discrete Element Method Using an Overlapping FEM Zone

Abstract. One of the characteristics of the numerical simulation in geotechnical engineering is that non-linear/discontinuous behaviour is concentrated on small portions of the total domain. A representative example is tunnel excavation, where high stress concentration is observed only near the excavation area and not over the whole rock mass. The Discrete Element Method (DEM) is ideal for handling discontinuous behaviour. However, employing DEM over the whole domain would be prohibitive, due to the large computational effort it requires. On the other hand, the Boundary Element Method (BEM) can effectively treat infinite and semi-infinite domains. The aim of the current work is to develop a simulation methodology that can iteratively couple Boundary Element and Discrete Element Methods in order to treat discontinuous behavior that arises in small portions of the total domain. To simplify the meshing procedure, an overlapping FEM zone is introduced on the DEM side of the common boundary.
Quality Bad Poor Fair Good Excellent I c I Reference Module No-Reference Module " Perfect "

Full-reference and reduced-reference image quality assessment (IQA) models assume a high quality reference against which to measure perceptual quality. However, this assumption may be violated when the source image is upscaled, poorly exposed, or otherwise distorted before being compressed. Reference IQA models on a compressed but previously distorted “reference” may produce unpredictable results. Hence we propose 2stepQA, which integrates no-reference (NR) and reference (R) measurements into the quality prediction process. The NR module accounts for imperfect quality of the reference image, while the R component measures further quality from compression. A simple, efficient multiplication step fuses these into a single score. We deploy MS-SSIM as the R component and NIQE as the NR component and combine them using multiplication. We chose MS-SSIM, since it is efficient and correlates well with subjective scores. Likewise, NIQE is simple, efficient, and generic, and does not require training on subjective data. The 2stepQA approach can be generalized by combining other R and NR models. We also built a new data resource: LIVE Wild Compressed Picture Database, where authentically distorted reference images were JPEG compressed at four levels. 2stepQA is shown to achieve standout performance compared to other IQA models. The proposed approach is made publicly available at https://github.com/xiangxuyu/2stepQA .
Efficient description of shape perturbations Problem presented

Airbus wish to have efficient ways of describing perturbations of a manufactured aerofoil from its design shape. The typical kind of perturbations expected are waves, steps, and bumps, and automatic classification into the classes is desired. Various possible methods of analysis were proposed and studied in some detail, including projection onto suitable basis functions, wavelets, and radial basis functions. Other methods were studied in less detail, but with the aim of giving a digital signature of defects that could be used to classify them.
New tools for wheat genetics and breeding : Genome-wide analysis of SNP variation *

Single nucleotide polymorphism (SNP) is one of the most broadly distributed types of molecular variation in a genome which, along with the availability of costand labor-effective genotyping platforms, make it the marker of choice for many crops. Our work is aimed at the development of a dense set of genetically mapped SNP markers for low-cost high-throughput genotyping of wheat germplasm. Next generation sequencing of normalized cDNA libraries was used for developing gene-associated SNPs in polyploid wheat. A total of 7.5 million 454 reads were generated from cDNA libraries of 10 wheat cultivars from US and Australia and processed for discovering SNPs using a bioinformatical pipeline specifically designed for variant discovery in polyploid transcriptomes. A total of 25,000 high-quality SNPs distributed among 14,500 EST contigs were identified. All these SNPs were validated by comparison with RNAseq data generated from an additional set of 17 U.S. and Australian cultivars. A total of 9,000 genome-wide common SNPs were selected for designing an Illumina iSelect assay. Preliminary testing showed that more than 95% of SNPs produce high-quality genotype calls with up to 70% being polymorphic in a diverse sample of U.S. and Australian cultivars with a minor allele frequency >0.05. The assay is currently being used for studying patterns of genetic diversity in a worldwide collection of wheat cultivars and for developing a high-density SNP map. A long term goal of this initiative is to advance wheat research and breeding by developing genetic and genomic tools for efficient analysis of agronomic traits using high-resolution linkage and association mapping and deploying SNP markers in breeding programs. 1Department of Plant Pathology, Kansas State University, Manhattan, KS 66506, U.S.A. ; 2USDA-ARS Biosciences Research Laboratory, Fargo, ND, U.S.A. ; 3USDA Western Regional Small Grains Genotyping Lab, Johnson Hall, WSU, Pullman, WA, U.S.A. ; 4USDA-ARS Eastern Regional Small Grains Genotyping Lab. , 4114 Williams Hall, NCSU, Raleigh, NC, U.S.A. ; 5Integrated Genomics Facility, Kansas State University, Manhattan, KS, U.S.A. ; 6Department of. Plant Sciences, University of California, Davis, CA, U.S.A. ; 7CSIRO, Food Futures National Research Flagship, Canberra, ACT 2601, Australia; 8Department of Primary Industries Victoria, Victorian AgriBiosciences Center, 1 Park Drive, Bundoora, VIC 3083, Australia. E-mail: eakhunov@ksu.edu
Planejamento da operação de sistemas hidrotérmicos de grande porte.

This paper presents the development of a Decision Support System (DSS) for the operational planning of large-scale hydrothermal systems formed by a series of hydroelectric and thermoelectric power plants, operated for the production and service demands for energy. Other sources of energy production, the expansion of the system, water transfers, multiple uses of water and environmental constraints are also considered. The DSS integrates a database with information of the hydrothermal system, a graphical interface to facilitate the editing of the data and display the results and the simulation and optimization models. The models of the called DSS HIDROTERM are based on the non-linear programming (NLP). In several applications made with the DSS with data for the Brazilian Hydrothermal System, formed by 4 subsystems and 128 active hydroelectric plants, very satisfactory results were obtained demonstrating various advances in relation to the model SISOPT from Barros et al. (2003), with emphasis on the processing speed, the size of systems to which the model can be applied and in a much more complete representation of the hydrothermal system. In addition to the planning of the operation of the hydrothermal system, the DSS can be applied also to the existing system diagnoses, analyses the impact of changes in operating rules and of multiple uses of water, planning and evaluation of expansion alternatives. Palavras-chave: Sistemas Hidroenergeticos, Reservatorios (Operacao), Programacao Nao Linear. 1) Pesquisador e Doutorando, EPUSP, Av. Prof. Almeida Prado, 271, 05508-900, Sao Paulo-SP. E-mail rczambon@usp.br 2) Professor Titular, EPUSP, Av. Prof. Almeida Prado, 271, 05508-900, Sao Paulo-SP. E-mail mtbarros@usp.br
GREEDY SUBSET SELECTION FOR SPEECH ENHANCEMENT IN WIRELESS ACOUSTIC SENSOR NETWORKS

A wireless acoustic sensor network is envisaged that relies on a collection of spatially distributed microphones, which observe a speech signal together with additive background noise. The microphone signals are sent to a fusion center where they are filtered and combined to produce an estimate of the speech signal. In order to save energy and extend network lifetime, it is desired to only have a subset of the microphones active at any one moment. This subset selection unfortunately comes with the adverse effect of decreasing the accuracy of the signal estimation. Since the network now has two competing objectives a trade-off develops that balances the energy consumption to estimation accuracy. We propose a network model that is cast similarly to a 0-1 knapsack problem that uses a greedy method to balance the output signal-to-noise ratio to total transmission energy expended by the wireless microphones. Simulations show that although a greedy approach is used, a relatively small decrease in output signal-to-noise ratio is achieved while there is a marked decrease in energy usage of the system.
Effects of Myrtle ( Myrtus communis ) essential oil on growth performance , carcass characteristics , intestinal morphology , immune response and blood parameters in broiler chickens

An experiment was conducted to determine the effects of Myrtle Essential Oil (MEO) on growth performance, carcass characteristics, intestinal morphology, immune response and blood parameters of broiler chickens. A total of 360 Ross 308 broiler chickens were allocated to five dietary treatments with five replicates of 15 birds each. Dietary treatments were prepared by formulating a corn-soybean meal-based diet free of antibiotics (Control) and supplementing the basal diet with three levels of MEO at 150, 300, 450 mg/Kg and antibiotic Virginiamycin (VGN) at 200 mg/Kg. The results showed that diets supplemented with MEO and VGN increased the feed intake, body weight gain and improved the feed conversion ratio compared to the control treatment (P<0.05). The relative carcass weight was significantly increased, whereas the weight of duodenum, jejunum and ilium and liver were decreased in broilers fed MEO (P<0.05). Dietary myrtle essential oil and antibiotic supplementations consistently resulted in significantly longer villus height, lower epithelial thickness of the small intestinal at 42 day of age compared with the control treatment (P<0.05). Supplementing the basal diet with MEO increased the antibody titers against sheep red blood cell (SRBC), although supplementing diet with 300 mg/kg of MEO was more effective (P<0.05). Broilers fed MEO diets especially at the level of 450 mg/Kg had a lower white blood cells count and heterophil, heterophil to lymphocyte ratio, but a higher lymphocyte and red blood cells count (P<0.05). In conclusion, data showed that diet supplemented with MEO improved the growth performance and increased antibody titers against SRBC, especially at the level of 300 mg/Kg, in broiler chickens. Myrtle oil supplementation may be considered a potential natural growth promoter. However, more studies are needed to define the effect of myrtle oil supplementation on the performance of poultry with regard to environmental conditions, effective dosage, active oil substances, dietary ingredients and nutrient density.
LAMINAR-TURBULENT TRANSITION CONTROL BY DIELECTRIC BARRIER DISCHARGE . THEORY AND EXPERIMENT

Recent results of investigations of laminarturbulent transition control by dielectric barrier discharge (DBD) in TsAGI are presented. Delay of natural transition in the flat-plate boundary layer by means of flow acceleration by discharge on one or three normal to flow direction electrodes was studied experimentally in quiet wind tunnel. Optimal electrodes locations and regime of discharge provided maximal downstream shift of transition were found. Phenomenological model of force induced by DBD actuator was developed and verified experimentally. This model was applied to numerical modeling of cross-flow dominated transition control by multi-electrode DBD actuator.
Physically based facial expression synthesizer with performance analysis and GPU-aided simulation

The performance analysis of a physically-based facial expression synthesizer with a novel algorithm for designing parametric muscle model is described. The facial expression synthesizer is partitioned into four general activities: construction of volumetric soft tissue layer, design of underlying volumetric facial musculature, ensemble of muscles to synthesize the facial expression and an efficient and stable numerical integration for dynamic skin deformation. We present techniques for analyzing the performance of facial expression systems in general and in particular the performance for various stages in our system. We also highlight potential improvements in performance that is possible using the powerful GPUs.
An Engineering Model for Healthcare Devices to Control , Detect , and Diagnose Medical Errors

Accurate diagnosis of diseases and their level of intensity is a key aspect of health. A minor error in medical diagnosis, besides diverting the course of treatment and increasing the duration of therapy, raises the cost of services, leads to psychological trauma, and most importantly jeopardizes patient safety. The shorter the time of diagnosis, the easier it is to prevent, fight, treat and control the disease at lower intensity levels. Thus, it is essential to provide a model to deal with the possible errors of diagnosis in healthcare system. The present article introduces an engineering method for detecting and diagnosing faults in patient treatment. In the first phase, the factors affecting the emergence of the disease are predicted using Perceptron neural network. In the second stage residual values are produced; and in the third stage, in case there is a fault, the sources and causes of the fault are examined with the help of statistical quality control charts. Validation of the proposed model is evaluated by providing a numerical example.
Efficient response time bound analysis of real-time rule-based systems

It is required not only to verify the logical correctness of a real-time expert system but also to determine whether the computation time required to compute a logically correct decision in each monitor-decide cycle is within the imposed timing constraint. A principal concept in the analysis methodology is that of a special form of rules. A set of rules satisfying all behavioral constraint assertions of a special form is guaranteed to have bounded response time. The authors present efficient algorithms for computing tight response time bounds for rule sets with bounded response time. These algorithms use techniques which do not involve checking the state-space graph corresponding to the rule sets. <<ETX>>
Language identification using noisy speech

This paper describes experiments in automatic identification of spoken languages using recordings of noisy radio signals as a data base. Prior efforts used uncorrupted speech; we selected techniques that we believed would be robust in noise. One technique attempted to distinguish languages by applying a classical quadratic classifier to prosodic features extracted from pitch and energy contours. Another was designed to exploit the frequency of occurrence of characteristic sounds using formant locations to represent the sounds, and using a vector-quantization distortion measure as the basis for language decisions. The techniques were required to make decisions based on speech segments of a few seconds duration. Our final tests were conducted on over 4 hours of previously unprocessed speech. Three languages, each from a different major language group, were used for development and testing. Allowing 11% false rejection (no decision), we achieved 64% correct identification with short speech segments. Our plans include the application of Markov modeling techniques to language identification.
Studium przypadku

: Early childhood bilingualism, natural bilingualism, and multilingualism, which occurs more often than ever before, are widely discussed in the secondary literature. Bilingualism entails acquiring a new identity and induces a change in linguistic thinking. This article contributes to the studies concerning the methods and strategies that are undertaken by such families that either raise or aim at raising a bilingual child; moreover, it puts forward a case study of a boy who is 2 years and 9 months old. In the introduction, the essential issues of raising a bilingual child are presented with a special emphasis put on the parents’ attitude towards bilingual education and their conviction of its underlying benefits for the boy. The empirical part of this article focuses on language proficiency and communication competences, and their assessment.
Proactive Channel Allocation for Ad-Hoc Networks

In this work we consider the problem of creating multi-edge channels in ad-hoc networks wherein each node can use multiple frequencies for sending and receiving packets by filling the slots of an OFDMA matrix. We consider the problem of how to fill-up the slots of a frequency×time matrix (FTM) at each node such that maximal collision free k > 1 path cover (CFkPC) of the communication graph is obtained. This problem is a variant of edge and node disjoint path cover in graphs extended to include collisions caused by the hidden terminal problem where two nodes A and B which are not in transmission range collide by transmitting at the same frequency and time to an intermediate node C. The proposed solution for filling the FTM is based on using maximum independent set in a suitable conflict graph. Our simulations compare between the proposed CFkPC approach and a version of the DCA protocol [12] that was extended to use multiple send/receive slots. The results show significant advantage of using CFkPC versus the adaptive approach of the extended DCA. We assume that GPS coordinate and GPS time synchronization is available.
Poster 272 QUANTIFYING THE OSCILLATORY EVOLUTION OF SIMULATED BOUNDARY-LAYER CLOUD FIELDS USING GAUSSIAN PROCESSES

Oscillatory motions in clouds have long been observed in cloud field simulations and observations at multiple scales. Cumulus clouds can be seen as a series of pulsating plumes with a period of 10-15 minutes (Heus et al., 2009; Malkus, 1952; Zhao and Austin, 2005a,b), which plays an important role in understanding moist convection. On a much larger scale, Feingold et al. (2017) have observed that the simulated cloud size distribution oscillates over time with spectral power at a period of approximately 80 minutes. Specifically, they found in their simulations that xthe cloud field alternates between a relative abundance of large clouds breaking up into smaller plumes which then reform into larger clouds. Gaussian process regression provides an alternate way to analyze periodic time variations of noisy processes. Here, we will apply Gaussian process regression to a large eddy simulation of marine boundary layer clouds similar to that modeled in Feingold et al. (2017). In Section 2 we define the time-series used to represent the changing cloud-size distribution and briefly discuss how Gaussian process (GP) regression is used to find periodic structure. In Section 3 we use GP regression and a more traditional spectral analysis to show that the large eddy simulation exhibits periodicity at both 45 minute and 78 minute timescales. The original poster and all the code used to produce both the poster and the figures in this abstract are available for download from github at https://github.com/phaustin/gaussian_ processes_ams_2018. git
5-15-2019 DESIGNING USER-ADAPTIVE INFORMATION DASHBOARDS : CONSIDERING LIMITED ATTENTION AND WORKING MEMORY

Business intelligence systems provide information dashboards that aim to assist decision-makers in understanding business situations and consequently support in decision-making. They typically include compressed visual information to raise data exploration from different perspectives. Although information visualization is known as a possible solution to overcome human cognitive limitations such as attention and working memory, we do not know much about existing cognitive challenges of users when performing data exploration tasks using information dashboards. In this paper, we present the results of an eye-tracking experiment to study the impact of attention and working memory limitations on the effectiveness of dashboards. For that, we explicitly considered visuospatial working memory capacity (WMC) as one critical individual difference and investigated how users with different visuospatial WMC allocate attentional resources while conducting data exploration task. We found that both users with high and low visuospatial WMC have difficulties to control their attentional resources. However, these difficulties are more for users with low visuospatial WMC in compare with high WMC. Our results highlighted the need for designing user-adaptive information dashboards. Therefore, we articulated meta-requirements for designing information dashboards that are sensitive to the attention and WMC of their users as two central components of information processing theory.
Mega-Systems-the issue of advanced systems development

A new class of software systems, the class of Mega-Systems, is discussed. The class of Mega-Systems includes the categories of Huge Systems, Package Systems, Systems of Systems and Generic Systems. The attributes and the characteristics of Mega-Systems are identified and related to traditional systems. Based on the discussion of these attributes, a new approach for the development of Mega-Systems is proposed. An adaptation of the GenSIF framework is suggested as a general model for the development of all categories of Mega-Systems. <<ETX>>
Semantic browsing of digital collections Conference or Workshop Item

Visiting museums is an increasingly popular pastime. Studies have shown that visitors can draw on their museum experience, long after their visit, to learn new things in practical situations. Rather than viewing a visit as a single learning event, we are interested in ways of extending the experience to allow visitors to access online resources tailored to their interests. Museums typically have extensive archives that can be made available online, the challenge is to match these resources to the visitor’s interests and present them in a manner that facilitates exploration and engages the visitor. We propose the use of knowledge level resource descriptions to identify relevant resources and create structured presentations. A system that embodies this approach, which is in use in a UK museum, is presented and the applicability of the approach to the broader semantic web is discussed.