Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling the ICN on optimal energy consumption

Information Centric Network (ICN) architecture as a deemed potential solution of network has attracted more and more attentions. Both routing and caching are the fundamental components of ICN. This work studies on the energy efficiency in access network of ICN, which jointly optimizes the routing scheme and caching capacity from the perspective of ISP. The energy consumption model of content distribution for the ICN is formulated with the bandwidth limit. Then the optimization problem is divided into two sub-problems: 1) RSWC, determine the routing paths for objects without considering the cache deployed and 2) RSC, take the cache into consideration to get the final resolution. The corresponding meta-heuristic algorithms are proposed. Simulation results show that our algorithm can get a better result for energy consumption with time complexity O(|Traf|). Meanwhile, the cache capacity and Zipf parameter are important factors affecting the total cost. Key-Words: ICN (Information-Centric Network); energy consumption; routing scheme; cache placement
A Study on Taiwanese Bei Guan Automated Composition Based on Rhythm Complexity and Markov Chain Analysis

In traditional Taiwanese music, not much information is recorded for percussion instruments. There is a very small amount of research for gongs and drums in Taiwanese music. This research tries to analyze rhythm of Bei Guan music by using rhythm complexity measure, to find out its attributes and similarities, and then to perform the similar and automated composition of Bei Guan music. The result of the research shows the possibility to preserve and promote Taiwanese Bei Guan Music with automated composition techniques.
589 Reconstruction of 3 D Geometry of General Curved Surfaces from a Single Image

Construction of 3D model from 2D images is important in reverse engineering and inspection applications. This work presents a new method to construct the 3D model of a free-form surface from a single image of the surface. The method combines the technique of recovering affine scene structure without requiring camera calibration, and the cubic corner method to extract 3D geometry. Recovering affine structure for images with free-form surfaces has been addressed for the first time. A novel modification of the cubic corner method is a construction scheme to determine a third point that forms an orthogonal triad. This approach is therefore able to handle cases where the three points being considered do not form orthogonal vectors. Results of implementation are promising. Future developments are discussed.
P o S ( P S T P 2 0 1 5 ) 0 4 0 COMPASS polarized Drell-Yan experiment

The COMPASS II started at 2012 that includes polarized Drell-Yan program with a polarized solid target. The availability of pion beam provides an access to the Drell-Yan physics throughout the process where quark(target)-antiquark(beam) pair annihilates electromagnetically with a production of dilepton pair. Study of angular dependencies of the Drell-Yan process cross-section allows us to access to parton distribution functions (PDFs) or, more precisely, a convolutions of various PDFs. The transversely polarized target together with negative pion beam is an important feature of the COMPASS Drell-Yan experiment, that provides us with unique data on transverse momentum dependent (TMD) PDFs. After a plot run in 2014, the experiment has just started in 2015. The role of the Drell-Yan experiment at COMPASS in TMD PDFs study, with a comparison to semi-inclusive deep inelastic scattering experiment, is described. The experimental set-up, the status of the data taking in 2015 and preliminary analysis results in the 2014 run are presented.
Analytical sociology for sociotechnical transition research : Bridging case study and system dynamics

This paper is motivated by the development in analytical sociology and sociotechnical transition research. This paper explores the potential for cross fertilization between the two that can improve current, transition research methodological practice, and provide a response to a number of criticisms on the Multi-Level Perspective on transition research. The paper proposes a retroductive transition research methodology to identify and test social mechanisms for their explanatory power in transition case studies. The methodology consists in the joint use of transition case study and system dynamics modeling and simulation. The paper discusses how the two methods are used iteratively, and how each one complements the strengths and counters the weaknesses of the other. The methodology has particular strengths and implications for the agenda of issues that research on future transitions to sustainability faces currently. It highlights the central role system dynamics can potentially play in sociotechnical transition research and community.
Two and Three Dimensional Investigation of Bubble Rising in High Density Ratio

In present paper three-dimensional isothermal Lattice Boltzmann Method have been used to simulate the motion of bubble. The above model is unified with another two dimensional non-isothermal model in order to reduce computational cost. Firstly, it is ensured that the surface tension effect and Laplace law are properly implemented. Secondly, effect of governing dimensionless numbers on terminal Reynolds number and terminal shape of bubble are investigated in 3D and 2D simulations. Different flow patterns in various dimensionless numbers are obtained and by changing the dimensionless number, terminal change of bubble’s shape are seen. The error of 2D solution is calculated. The results show that with increasing terminal Reynolds number increase the difference between 2D and 3D solutions and in high Reynolds number, 2D simulation for this phenomenon is not acceptable.
Effects of Rapid Reduction of Body Mass Weight Cut ing on Performance Indices and Proneness to Injury in jūdōka . A Critical Appraisal from a Historical , Gender-Comparative and Coaching Perspective

In contrast with the vast amount of literature on rapid reduction of body mass in male wrestlers there is a particular lack of studies on the effects of “weight cutting” in female athletes who compete in weight class events such as jūdō. The advantages of competing in a lower weight category include increased leverage, relative power, and strength. A competitively active jūdōka attempts to build a longterm career in a single weight class to avoid having to overhaul tactical preparations due to having to face many new opponents. The most influential person on the jūdōka’s weight management behavior appears to be their jūdō coach and training partners. Significant gender differences in the type or magnitude of physiological effects of “weight cutting” are caused by female jūdōka typically relying on different methods (chiefly nutritional restriction and dehydration) when compared to their male counterparts (mostly increased energy expenditure and excessive exercise). Elite jūdōka engage in these unhealthy practices at an increasingly young age (<15 yrs) and are not commonly submitted to any preventive assessment of menstrual function, bone health, and markers of muscle and bone breakdown hence their high frequency and sustained history of musculo-tendinous injuries. While the effects of weight cutting on relative aerobic, anaerobic capacity and strength are limited, it is mainly dehydration, loss of muscle, tendon elasticity, catabolism, and premature osteopenia that contribute to their overall increased risk of injury. Protein and amino acid supplementation may be useful in avoiding severe catabolism and may potentiate lipolysis.
Speaker and Emotion Recognition of TV-Series Data Using Multimodal and Multitask Deep Learning

In our daily lives, the interaction between humans involves both linguistic and paralinguistic aspect to make a better understanding of the interaction. Several studies previously were conducted to enable recognition of the nonverbal aspect by machine, for the example are the recognition of speech emotion [2] and speaker [6], which are the important nonverbal aspects in the conversation. In recent time, study on multimodal and multitask recognition in human-machine communication field have gained attention. Emotion [8] or speaker [9] recognition using multi-modality had also been done by incorporating features from various aspects of video and resulted in the improvement. Studies on the multitask recognition also have been conducted, for the examples are recognition on speech and emotion [7]. In spite of these achievements, the study on multitask recognition that utilize multimodal features is still limited. In this work, we conducted a study on both multimodal and multitask recognition by using deep learning to recognize the speaker and emotion of a speech from TV-series. The utilized multimodal features consist of acoustic, lexical, and facial features, which can be extracted from TV-series data. We explored two methods to combine the multimodal features to see the better choice for utilizing multimodal features. The applied methods include features concatenation and hierarchical fusion. 2 Model Architectures
Draft 1 Comparison of ant-associated beetle communities inhabiting mounds of forest-1 dwelling ants in forests and forest clearings 2

Journal: Canadian Journal of Forest Research Manuscript ID cjfr-2018-0083.R1 Manuscript Type: Article Date Submitted by the Author: 30-Apr-2018 Complete List of Authors: Härkönen, Salla; Turun Yliopisto, Biology Sorvari, Jouni; Ita-Suomen yliopisto Kuopion kampus Keyword: Formicidae, myrmecophiles, humidity, species richness, clear felling Is the invited manuscript for consideration in a Special Issue? : N/A
Water wave kinematics of steep irregular waves — systematic perturbation approach, empirical law, PIV measurements and engineering practice

The kinematics of steep irregular waves is an important topic of continuing interest for the offshore industry. One of the challenges is how to deal with continuous design spectra with decay ω or ω, for which secondor higher-order terms in traditional engineering approaches may diverge near the equilibrium water surface unless an (arbitrary) high-frequency cutoff is employed. In these cases, common practice is often to employ the method of Wheeler stretching, which is not based on rigorous hydrodynamic theory. A systematic perturbation approach, called the nonlinear Schrödinger method, has been derived using the strategy that the peak of the spectrum is accounted for as mainly free waves, and that all bound waves arising from the free waves near the peak are accounted for as well. The method was reported by Trulsen (1999) for second-order nonlinear waves on deep water, and by Trulsen, Gudmestad & Velarde (2001) for second-order nonlinear waves on finite depth. The method is now being expanded to third-order nonlinear waves. Second-order nonlinear Schrödinger kinematics corresponds to the cubic nonlinear Schrödinger equation for spatiotemporal evolution, while third-order Schödinger kinematics corresponds to the modified nonlinear Schrödinger equation of Dysthe (1979). For the first time, this method is now validated with the precise measurements of Grue et al. (2003) obtained by Particle Image Velocimetry (PIV) near the peaks of steep irregular waves. Third-order kinematics gives excellent comparisons with the experiments, and it turns out that non-local contributions at the third order are important for the successful computation of the fluid velocity field. The kinematics of extreme waves in deep water was recently analyzed by Grue et al. (2003). They discovered that after proper normalization, the kinematics profiles under a variety of extreme wave crests fitted surprisingly well with a universal exponential profile e, where z is the vertical coordinate and k is a local wavenumber. The key to the successful collapse of data demonstrated by Grue et al. (2003) was to use the local trough-to-trough “wave period” as basis for normalization at the crest to be considered. Furthermore, the local wavenumber and steepness had to be determined by careful use of third-order nonlinear formulas for Stokes waves. We show that the method of Grue et al. (2003) may be considered as a limiting case of the nonlinear Schrödinger kinematics method for deep water (Trulsen 1999) in the limit that the length of the computational domain is exactly one local trough-to-trough wave period, and provided the perturbation expansion of Trulsen (1999) is extended to the next order of nonlinearity with respect to local nonlinear effects only, excluding non-local effects and finite bandwidth effects.
Analysis of Crime data using data mining

Frequent pattern (itemset) mining plays a key role in rule mining. The Apriori and FP-development calculations are the most renowned calculations which can be utilized for Frequent Pattern mining. his paper shows the study of different Frequent Pattern Mining and Rule Mining calculation which can be applied to crime crime pattern mining. The analysis of survey would provide the data about what has been done already in a same area, what is the present trend and what are the other related areas. Frequent Pattern mining having three important approaches that is candidate generation approach, without candidate generation approach and vertical layout approach. It also explains different frequent pattern calculations and how it can be connected to various zones especially in wrongdoing design identification. This paper helps the researchers to get clear thought towards the application of frequent pattern mining algorithm in various areas.
Forecasting Stocks with Multivariate Time Series Models . 1

This work seeks to forecast stocks of the Nigerian banking sector using probability multivariate time series models. The study involved the stocks from six different banks that were found to be analytically interrelated. Stationarity of the six series were obtained by differencing. Model selection criteria were employed and the best fitted model was selected to be a vector autoregressive model of order 1. The model was subjected to diagnostic checks and was found to be adequate. Consequently, forecasts of stocks were generated for the next two years.
Reduction of heat losses on the skid pipe system of a pusher type furnace

INTRODUCTION In the iron and steel making process, hot rolling only accounts for approximately 10% of the energy consumption. Yet 1.5 to 2 GJ/t steel are consumed for hot rolling, and 80% of this energy is utilised for reheating of the slab. The rolling itself requires only 0.3 to 0.4 GJ/t [1]. Increasing energy costs and targets for the reduction of CO2 emissions provide a constant challenge for all high temperature process users to optimise their processes. In addition to raw material and labour costs, the costs for energy and environmental requirements play an increasingly important role. New technical solutions are required to improve the energy efficiency and reduce the energy consumption, and consequently the CO2 emissions. The target of voestalpine Grobblech GmbH and FBB Engineering GmbH is to optimise the hot rolling process from an energy point of view, reduce CO2 emissions, and reduce the operational cost of the reheating furnaces. Another important aspect is the increase in productivity by reducing the shutdown time of the furnace. Cooperation in partnership between the operator of the kiln and the supplier of refractory materials is an essential requirement for achieving these goals. This paper discusses how energy consumption and energy loss can be reduced in reheating furnaces of hot rolling mills by new lightweight refractory materials and a new lining concept for the skid pipe insulation.
Speckle Tracking Echocardiography in Diabetic Patients with STEMI

Background: Noninvasive assessment of MI based on strain is of growing interest because of its clinical value in the detection of early myocardial dysfunction and stratifying patient prognosis. Cardiovascular MR imaging techniques are considered reference techniques, especially MR tagging, which remains the most widely available and validated cardiovascular MR modality for myocardial strain quantification. Diabetes not only increases the risk of MI but also increases the mortality associated with the acute event. DM is a strong independent predictor of short and long-term recurrent ischemic events, including mortality, in patients with ACS. Correlation between the GLPSS by speckle tracking echocardiography with traditional echocardiographic indices in diabetic patients with STEMI in 24hrs after primary PCI. Methods: 30 patients with STEMI (58 ±8, 9 diabetic, 21 non diabetic) all patients underwent 1ry PCI. Conventional 2D echocardiography to asses LVEF, WMSI, EDV and ESVI and speckle tracking echocardiography to asses LV GLPSS was done within 24hr of 1ry PCI. Results: All patients with STEMI had low LV avge GLPSS (–10.57±2.67%) with significant between diabetic (–9.00 ± 2.3%) and non diabetec (–11.2 ±2.6%) with significant p :0.03, at Avge GLPSS –9.5% all dibetic patients uncontrolled diabetis with HbA1C ≥ 10 with sensitevity 66% and specificity 72% and AUC 0.7, no significant between diabetic and non diabetic patients as regarding LVEDV with p :0.7, LVESV with p :0.4, LVESVI p :0.2 , EF with p :0.6, or WMSI with p :0.7. Significant proportional correlation found between Avg GLS and EF with p :0.01 and significant inverse correlation between Avg GLS and WMSI was found with p :0.04 no significant between Avg GLS and ESVI with p :0.08. Conclusion: Assessment of myocardial strain in diabetic patients by speckle tracking echocardiography may efficiently detect early contractile changes which may precede functional alterations observed with conventional M-mode echocardiography.
WebAPI rdfs : subClassOf msm : Service , prov : Entity ; rdfs : label

Web APIs enjoy significant increase in popularity and usage in the last decade. They have become the core technology for exposing functionalities and data. Nevertheless, due to the lack of semantic Web API descriptions their discovery, sharing, integration, and assessment of their quality and consumption is limited. In this paper, we present the Linked Web APIs dataset, an RDF dataset with semantic descriptions about Web APIs. It provides semantic descriptions for 11,339 Web APIs, 7,415 mashups and 7,717 developers profiles, which makes it the largest available dataset from the Web APIs domain. It captures the provenance, temporal, technical, functional, and non-functional aspects. We describe the Linked Web APIs Ontology, a minimal model which builds on top of several well-known ontologies. The dataset has been interlinked and published according to the Linked Data principles. We describe several possible usage scenarios for the dataset and show its potential.
Algorithm of Building Regression Decision Tree Using Complementary Features

In the so-called explained artificial intelligence, there is a need to build small models, but accurate and intuitive for the analyst. It is necessary to formalize, which models are perceived by analysts and decision-makers as intuitively understandable and plausible.It’s shown that the use of accumulated information about additional to each other in some sense, complementary features can improve the accuracy of the small regression decision trees, as well as make them more plausible. The formal definition of the complementarities of the feathers is proposed. Algorithm of building regression decision tree with complementary features is presented. Condition of plausibility of two-levels decision tree is described.
PREPARATION OF RED YEAST RICE USING VARIOUS THAI GLUTINOUS RICE AND Monascus purpureus CMU 001 ISOLATED FROM COMMERCIAL CHINESE RED YEAST RICE SAMPLE

A strain of Monascus purpureus CMU001 was isolated from locally available commercial Chinese red yeast rice (Ankak or Ang Khak) by surface sterile technique. The identity of the strain was then confirmed by conventional methods. Preparation of red yeast rice using isolated strain was carried out on various kinds of rice, and especially the most well known varieties of Thai glutinous rice such as Korkor 6 white glutinous rice (RD6), Kam black glutinous rice (Kam) and Sanpatong 1 white glutinous rice (SPT1). The red rice products obtained were studied for the intensity of red pigment by measuring the absorbance of red extracts at 500 nm. The results indicate the most intense red pigment when using RD6 with 3 week cultivation. In order to know the effect of nutrient variation, soybean milk was added during cultivation as amino acids source. The highest intensity was also expressed when RD6 was used with 2 week cultivation. The supplement of 1 ml of 0.25 g/ml soybean milk gave the product with more intense red color.
FACTORS AFFECT EXPORTING OF VIETNAM ' S FISHERY TO US AND EUROPE MARKET . REALITIES AND SOLUTIONS

The article employs gravity model to identify and assess the effects of the factors impact on exporting revenue of Viet Nam Seafood to European and American markets. The data consists of 26 national board of the American and European countries were analyzed using econometric methods: Fixed Effect and Random Effect. The results show that seafood exported from Vietnam to these markets can be affected by different elements such as GDP of importing nations; GDP of exporting countries, the population of the countries; exchange rate and geographical distances. Of which GDP of importing countries and exporting countries, the population and exchange rate have a correlation with exports while geographical distances have counter effects on exports. Otherwise, seafood import duty of these countries ultimately not affect exports of seafood from Vietnam to US and Europe. Based on the research findings, the article suggests solutions to develop and expand Vietnam seafood export to these potential markets.
Expression of CD38 on Macrophages Predicts Improved Prognosis in Hepatocellular Carcinoma

Background: CD38 is involved in the adenosine pathway, which represents one of the immunosuppressive mechanisms in cancer. CD38 is broadly expressed across immune cell subsets, including human macrophages differentiated in vitro from monocytes, but expression by tissue-resident macrophages remains to be demonstrated. Methods: Tissue samples were obtained from 66 patients with hepatocellular carcinoma (HCC) from Singapore and analyzed using immunohistochemistry. Tumor-infiltrating leukocytes (TILs) were further examined using DEPArray™, and the phenotype of freshly isolated TILs was determined using flow cytometry. Results: CD38 was frequently co-expressed with the macrophage-specific marker CD68. CD38+CD68+ macrophage density was associated with improved prognosis after surgery, while total CD68+ macrophage density was associated with poor prognosis. DEPArray™ analysis revealed the presence of large (>10 μm), irregularly shaped CD45+CD14+ cells that resembled macrophages, with concurrent CD38+ expression. Flow cytometry also revealed that majority of CD14+HLA-DR+ cells expressed CD38. Conclusion: CD38 expression was clearly demonstrated on human macrophages in an in vivo setting. The positive association identified between CD38+ macrophage density and prognosis may have implications for routine diagnostic work.