Miracle-dz/UniFAR-FTUs huggingface dataset:
A Visual Attention Model Using Depth Information from the Point of Gaze

We propose a visual attention model in which a novel feature map called the “depth-of-field map” is introduced. The depth-of-field map functions similar to the depth of field effect of human vision by enhancing the saliency of the regions near the point of gaze in the direction of depth and reducing the gaze movements between regions widely separated from each other. In this study, we first counted the relative frequency of three types of human gaze movements (movement to adjacent objects at a similar depth, movement to adjacent objects in the same twodimensional direction, and movement to other objects) in three situations (matching, memorizing, and no assigned task). The result shows that the percentage of gaze movement to adjacent objects at the same depth is more than chance and the proportions of these three types of gaze movements vary according to the task. We then implement the proposed model using Microsoft Kinect for Windows and input the scenes from the human experiment into the model. The result shows an occurrence distribution similar to that of human gaze movement according to a given task. It indicates that the proposed model could bring robotic gaze movement closer to that of a human. Keywords—visual attention, depth information, human-robotinteraction.
The complete transformation methodology for sequential runtime checking of an ANNA subset

We present in this report a complete description of a methodology for transformation of Anna (Annotated Ada) programs to executable self-checking Ada programs. The methodology covers a subset of Anna which allows annotation of scalar types and objects. The allowed annotations include subtype annotations, subprogram annotations, result annotations, object annotations, out annotations and statement annotations. Except for package state expressions and quantified expressions, the full expression language of Anna is allowed in the subset. The transformation of annotations to executable checking functions is thoroughly illustrated through informal textual description, universal checking function templates and several transformation examples. We also describe the transformer and related software tools used to transform Anna programs. In conclusion, we describe validation of the transformer and some methods of making the transformation and runtime checking processes more efficient.
UVM RAL : Registers on demand Elimination of the Unnecessary

This paper puts forward a novel approach of deploying UVM Register data base in verification environment. The supreme edge in utilizing this approach is that it improves the performance of the test on the whole (which is from compilation to simulation). This approach is perused, with examples, from idea to adoption in this paper. Keywords—UVM RAL, Register model, dynamic database creation.
Rapid Identification of Enhanced Drought and Salt Tolerances in Arabidopsis Conferred by BnBADH 1 Gene

Identifying and applying salt or drought tolerant genes is a quick method of enhancing crop tolerance to environmental stresses. In this study, a full-length new betaine aldehyde dehydrogenase gene from Brassica napus (BnBADH1) was isolated by homologous cloning method according to the sequence of Arabidopsis BADH1 gene. BnBADH1 was 1506 bp in length and it theoretically encoded a hypothetical protein with 501 aa; sharing 90.2% identity with its ortholog in Arabidopsis (GenBank: ALDH10A8) in nucleotide sequence and 93.4% identity in amino acid sequence. The mRNA expression levels of BnBADH1 under drought or salt stress was investigated by quantitative real-time PCR. Under drought stress, the expression level of BnBADH1 mRNA began to decrease slightly from 12 h to 72 h; but it suddenly increased at 96 h and reached a peak at 120 h; after that, its expression reduced drastically from 144 h to 192 h. While under salt stress, there was no obvious difference in expression level at the first 8 h (2 -8 h); but mRNA increased sharply at 20 h. Moreover, the BnBADH1 gene was induced into Arabidopsis and overexpressed. Drought and salt stress tolerance was enhanced in Arabidopsis as was expressed by higher root length of transgenic plants compared with its wild plants. It is the first report which highlighted the expressions of newly isolated gene BnBADH1 from rapeseed in transgenic Arabidopsis to enhance drought and salt stresses tolerance. © 2019 Friends Science Publishers
ON THE SPAWNING SEASON AND EARLY LIFE HISTORY OF OIL SARDINE SARDINELLA LONGICEPS

Spawning and spent-recovering oil sardines Sardinella longiceps (Cuvier and Valenciennes) unusually occurred in May 1976 at Vizhinjam, far south of the limit of the traditional fishery for the species. It was also possible to collect the egg, though a single one, from the same locality coinciding with this occurrence. That there was considerable spawning activity of the species around this place was indicated by the occurrence of postlarvae and juveniles in sufficient abundance to form a minor fishery, during the immediately following period. Illustrated descriptions of some important stages of early life history based on the collections are given.
Reducing the Risk of Developing Diabetes Diabetes Canada Clinical Practice Guidelines Expert Committee

• As safe and effective preventive therapies for type 1 diabetes have not yet been identified, any attempts to prevent type 1 diabetes should be undertaken only within the confines of formal research protocols. • Intensive and structured healthy behaviour interventions, ideally resulting in loss of approximately 5% of initial body weight, can reduce the risk of progression from impaired fasting glucose or impaired glucose tolerance to type 2 diabetes by almost 60%. When initiated early, the effects of healthy behaviour interventions are long lasting (more than 20 years). • Progression from prediabetes to type 2 diabetes can also be reduced by pharmacologic therapy with metformin (~30% reduction), with persistent benefits observed after more than 10 years of stopping treatment in the Diabetes Prevention Program.
IP header compression in the SGSN

This paper discusses how protocol header compression schemes can be implemented in the Serving GPRS Support Node (SGSN) as part of the GSM recommendations. We briefly describe details of the two compression algorithms currently selected for implementation by the recommendations committee, followed by an explanation of how these schemes can be implemented in the SGSN.
Smooth mixed models for balanced longitudinal data

Centring is a familiar device much used in the analysis of fixed effects models, but rarely seen in the context of mixed models, since the distribution of the random effects usually brings about the required centring. However there are mixed models, notably in the analysis of longitudinal data, where the distribution of the random effects does not bring about the necessary centring. In such models we use a conditional argument to centre the distribution of the random effects directly: the resulting estimates are of necessity unbiased. In general, we define a new class of mixed models, centred mixed models. We give some examples of models in this class and discuss efficient estimation of the fixed and random effects, and the variance parameters. We illustrate our method with the analysis of some Canadian weather data.
The Validity of the Kirchhoff Approximation for Rough Surface Scattering Using a Gaussian Roughness Spectrum

The validity of the Kirchhoff approximation for rough surface scattering is examined by comparison with exact results obtained by solving an integral equation. The pressure release boundary condition is assumed. The field quantity calculated is the bistatic scattering cross section, which is obtained with a Monte Carlo technique. The accuracy of correcting the Kirchhoff scattering cross section for shadowing is also addressed. The surface realizations used are randomly rough with a Gaussian roughness spectrum and have height variations in only one direction. The surface correlation length is found to be the most important parameter in defining the valid region of the Kirchhoff approximation away from the low grazing angle region. A procedure is given that provides a quantitative measure of the accuracy of the shadow-corrected approximation when the root-mean-square (rms) slope angle of the surface y is •< 20* and when the incident grazing angle 0 is >• 2y. Examples with 0 •< 2), are also discussed.
Impact of exomoons in flux and polarization phase curves of starlight reflected by exoplanets

While the search for exoplanets harvests an increasing interest, the times of exomoon detection and characterization are still to come. As those found in our Solar System, exomoons are potential candidates for hosting extraterrestrial life and/or granting their parent exoplanet with the required habitability conditions. Moreover, seizing and characterizing the orbit and properties of these companions is the keystone of a more exhaustive exoplanet characterization and a comprehensive understanding of planetary system formation mechanisms. We show that measuring the flux and polarization of starlight reflected by a planet–moon system could potentially lead to the characterization of the lunar albedo, size and orbital parameters of its orbit around the planet.
Lisp-Stat to Java to R

This paper will describe my experiences in moving on from Lisp-Stat to Java to R. I was introduced to Lisp-Stat in'89 and used it actively for teaching and research over the next 10 years. My use of Lisp-Stat culminated in a joint project with Hani Doss on Bayesian Sensitivity Analysis and it remains the largest piece of software I wrote using Lisp-Stat. At the time the project was completed, the only open statistical system that could deliver the goods was Lisp-Stat. In this article, I will describe how the power of Lisp, underlying statistical components and dynamic graphics were exploited in the project. When development on Lisp-Stat slowed down, Java was coming into its own as an important language and R became an open source collaborative project. Of course, I have moved on and I use R for most of my work today. I will touch upon my experience with Java and R briefly.
SPARSE SAMPLING FOR MAGNETIC RESONANCE IMAGING

Functional Magnetic Resonance Imaging (MRI) and other dynamic MRI applications, require rapid acquisition to measure dynamic processes changes. Experimental data are collected in the k-space by following different trajectories to cover the whole space. Complete data acquisition needs several minutes: the reduction of the number of collected trajectories allows proportional acquisition time reduction but undersampling occurs, producing artefacts. In what follows, MRI sparse sampling acquisition and reconstruction methods are overviewed. In particular, sparse methods are grouped in two classes: the first contains methods in which the sampling scheme is independent of the sample shape, the most important is Compressed Sensing (CS); the other contains methods that adapt their sampling pattern, by modifying the acquisition trajectories (both in number and directions) during the acquisition, to the sample internal structure. In this second class, an emerging set of methods, hybrid forms of adaptive CS, are included and discussed. The current paper clarify the importance of using adaptive CS strategies in MRI to reduce acquisition time and undersampling artefacts and to improve the signal to noise ratio (SNR) of the resulting image.
2 Semantic Web technologies and news classification

The LinkedTV project News scenario aims at improving the experience of watching news on TV. It envisages that potential users of the system watch news broadcasts, express a need for additional information and that the system provides resources from the web that are potentially relevant to them. Our goal was to investigate user information needs for a given news topic, based on news video fragments. Furthermore, we aimed at representing the news video fragment and related information needs in a form compatible with the system knowledge representation model. Our contribution consisted of a method to formally represent fragments and requirements using a controlled vocabulary, which was applied to information needs collected through a user study. The analysis resulted in lists of concepts and schemas of the content structure. This contribution supports semantic linking between news, related information needs and additional resources to be retrieved from the web to satisfy those needs.
Improved multi-step forecasting using a new statistical test

We propose a general test of whether a time series model, with parameters estimated by minimising the single-step forecast error sum of squares, is robust with respect to multi-step prediction, for some specified lead-time. The test may be applied to a, possibly seasonal, ARIMA model using the parameters and residuals following maximum likelihood estimation. It is based on a score statistic, evaluated at these estimated parameters, that measures the sensitivity of the multi-step forecast error variance with respect to the parameters. We show that the test has acceptable size properties for higher lead times, when applied to the exponentially weighted moving average predictor, and investigate how its power varies with the lead time, under the simple ARMA(1,1) alternative. We also demonstrate the high power of the test when it is applied to a process generated as the sum of a stochastic trend and cycle plus noise, which has been modelled by an autoregression. We use frequency domain methods for the derivation and sampling properties of the test, and to give insight into its application. The test is illustrated on two real series, and a function for its general application is available from the authors.
Improving Co-occurrence Matrix Feature Discrimination

This paper discusses a method of improving the discrimination power of a certain class of GLCM features. We investigate where co-occurrence matrix features derive their discriminatory power, and provide a theoretical basis for improving this method. Finally, we present examples of discrimination improvement using a real-world data. Cross-validation results have indicated remarkable increases in feature discriminatory power for almost all features trailed. The co-occurrence feature Variance was a good example, with an average 70% decrease in misclassification after implementing the improvements detailed in this paper.
Screening of Key Species Involved in Baiyaojian Fermentation Based on Gallic Acid Content

The present study aimed to screen for dominant species involved in Baiyaojian fermentation based on the appearance and gallic acid content of Baiyaojian. The species were added via two routes: Jiuqu (dried fermentation starter) or distiller’s grains. Baiyaojian was fermented with each individual species under the same fermentation conditions, and the dominant species was screened, isolated, and purified. Then, the dominant species from the two methods were compared to determine the optimal species for fermentation. One dominant species, each was isolated from Baiyaojian fermented with Jiuqu and distiller’s grains. These species were subsequently identified as Rhizopus oryzae BYJ.G-1 and Aspergillus niger BYJ.H-1, respectively. The gallic acid content in the fermentation products of R. oryzae BYJ.G-1 was higher than that of A. niger BYJ.H-1, and the surface of R. oryzae BYJ.G-1 was covered with white hyphae. Both R. oryzae BYJ.G-1 and A. niger BYJ.H-1 were dominant species involved in the fermentation of Baiyaojian. R. oryzae BYJ.G-1 appeared to be more effective than A. niger BYJ.H-1. These findings suggested that single-species fermentation could be used to optimize the fermentation process of Baiyaojian and to improve its fermentation efficiency, thereby improving the quality of Baiyaojian as well as its safety for clinical use. © 2019 Friends Science Publishers
Assessment rubrics can give music teachers and their students a clear and fair measure of progress and mastery in the classroom , studio , or rehearsal

A primary difficulty with music performance assessment is managing its subjective nature. To help improve objectivity, rubrics can be used to develop a set of guidelines for clearly assessing student performance. Moreover, rubrics serve as documentation for student achievement that provides music teachers with a written form of accountability. This article examines the complexities of music performance assessment and provides an argument for the benefit of rubrics in the assessment process. In addition, discussion includes an overview of the various types of rubrics as well as suggestions for choosing and writing rubrics to assess musical performances.
Customizable Content Based Filtering Method to Filter Texts and Images from Social Network User Wall

Today online social media are most valuable and essential member of human life. People can online communicate with their family, society and friends to exchange several type of information including text, images, audio & video data. Therefore, there is need of control of user over the contents which are published on his wall. Hence , user is able to avoid undesirable content that is displayed on his wall. But, currently social networks provide this service in very small extent. To provide this service, we plan a user defined filtering rules and machine learning categorization technique in this paper. Filtering rules grant users to personalize the filtering norms that are employed to the contents which are published on their walls. Automatic categorization based on content of messages into proposed categories is possible through machine learning technique. Also, proposed system can restrict the undesired images that are published on online social network (OSN) user private space by using content wise image filtering along with K-Nearest Neighbour (KNN) classifier. Keywords— Online Social Network (OSN), Machine Learning, KNearest Neighbour (KNN) Classifier, Information Filtering.
Matching potential in randomized complete block designs

A small sheep experiment (nobs=32) planned to use a randomized complete block design (RCBD) treatment assignment of two binary factors. Complications creating the RCBD blocks prompted the researchers to discard the original blocks from the initial analysis plan and to rearrange their experimental units into new groups using linear covariate adjustment. We compare the blocks from the experiment’s initial analysis plan and the groups from the researcher’s linear covariate adjustment to groups formed by potential matching methods. We evaluate these three analysis approaches on the original sheep dataset and on simulated sheep datasets. We find that the groups created using matching methods produce less precise estimates and that further, those estimates may be biased. Additionally, the matching methods may alter the experiment’s size and thus, its overall power. When small RCBD experiments have complications forming the desired blocks, we recommend the joint use of well-established preliminary testing and post-stratification procedures. This acts as a more formalized version of the sheep researchers’ use of linear covariate adjustment and implicit model selection.
Image Processing and Concentric Ellipse Fitting to Estimate the Ellipticity of Steel Coils

In this chapter a particular image processing problem existing in quality assurance for steel industry is addressed. Since the quality standards in steel industry are ever increasing, even steel industry starts to use machine vision systems to monitor their product quality. In case of steel coils a particular figure of merit in quality is the roundness (ellipticity) or lack thereof of the coil. The mathematical correct measure of the roundness is the eccentricity , with the major semi axis a and the minor semi axis b. But the fastest way for the
Religiosity Buffers and has a Quadratic Moderation Effect on the Relationship between Gender Inequality and Life Satisfaction around the World

This paper reports two studies that sought to examine whether religiosity moderates the relationship between gender inequality and subjective well-being. Using a multi-level and a national-level analysis on 84 and 127 nations, respectively, we found evidence in support of this hypothesis. We also examined whether religiosity is a quadratic moderator of the relationship between gender inequality and subjective well-being. In the 127-nation study, we found evidence that national-level religiosity is indeed a quadratic moderator of the
Investment in agricultural productivity vs rural commercialization: which way to rapid poverty reduction in Ethiopia?

Developing countries identify a set of strategic objectives to promote agricultural production, and assure food security and reduced level of poverty. Two of these objectives are (i) sustainable increase in agricultural productivity, and (ii) accelerated agricultural commercialization. Each of these objectives is backed-up by a long-list of priority investment areas. However, most of these countries cannot satisfy the financial and technical requirements to execute both of the strategic objectives and all of these investment areas. In light of this, taking the case of Ethiopia as an example, this study employs an economy-wide model and assesses the relative efficiency of alternative investment options on agricultural performance and poverty reduction. Results show that the policy instruments cause significantly different production and welfare responses. Productivity enhancing interventions such as input subsidy and irrigation provision have superior welfare consequences, while policies aimed at small holder commercialization have the least effect.
DataScience 4 NPA Data Science Service for Non-Programmers

With the emergence of Big Data, the scarcity of data scientists to analyse all the data being produced in different domains became evident. Moreover, the processing of such amounts of data also is challenging due to current technologies in use. With this in mind, the DataScience4NP aims to explore the use of visual programming paradigms to enable non-programmers to be part of the data science workforce at a faster pace and at the same time to provide a scalable data science service. By observing the common process employed by data scientists in the extraction of knowledge from data, which includes data insertion, preprocessing, transformation, data mining and interpretation/evaluation of results, we envisioned a system to perform all these steps without requiring users to program. Thus, our solution aims to provide an intuitive user interface where users can build personalized sequential data science workflows that are consequently processed by a back-end service. The back-end service translates the received workflows to a lower-level representation, enabling the execution of the translated tasks by separate scalable and distributed data science services in parallel. The entire system is composed of different services containerized with Docker and orchestrated with Kubernetes, allowing it to be easily deployed in different clusters. To evaluate our tool, and particularly to verify if the concept we envisioned for the creation and execution of data science tasks was intuitive, we conducted preliminary usability tests with two different groups of people, where we observed a high level of user satisfaction. Concluding, from the feedback obtained, it was clear that this concept of sequential workflows would bring added value to both novice and advanced data scientists.