Reviewerly/exHarmony huggingface dataset:
Factors Affecting Companys Profile on Web Page

The objective of this paper is to determine the availability of descriptive factors in the companys web page. Descriptive factors are the type of top-level domain name, information on authorship, availability of keyword, availability of description and currency of the website which are derived from the last date of modification.
Use of Unmanned Aerial Vehicles in the Creation of a Topographic Plan of a Chalk Pit

Creating topographic plans of terrain sections in the classical way takes a lot of time. It is proposed to use modern equipment and software products to solve the task, which should lead to a reduction in time during the production of work, as well as reduce the cost of the final product. This paper describes the process of drawing up a topographic plan of the chalk pit area for the purposes of landscaping with the use of an unmanned aerial vehicle, followed by processing the data obtained in a specialized software product. The basic preparations for the shooting of unmanned aircraft, also the process of shooting and processing photos in a specialized software product “Agisoft Metashape” for receiving and decoding of the orthophotomap were analyzed. An approach to laying a network of identification marks on the ground with the use of GPS receivers and determining their spatial coordinates is considered in detail. Also, due to the large volume of work and some technical limitations of the work of the unmanned aerial vehicle, it became necessary to divide the terrain into survey areas, followed by combining the broken sections into a single orthophotomap. The principle of dividing the terrain into separate flight zones is also described in the paper.
Study of The Narrative Structure of Loram Kudus people as a means of Learning Literary Appreciation: Content Analysis based on Vladimir Propp

Abstract Kudus is one of the cities located in central Java province. The folklore of the Holy City is very diverse. In each sub-district has a very interesting folklore and it also charged with local wisdom values. Researchers analyzed the story of the founding of the famous Wali Mosque in Loram Kulon village. As part of the literary work, the folklore of Wali’s founding at Taqwa Mosque and Sultan Hadirin contains pragmatic values that are very interesting to review. The research paradigm is a qualitative description as a research design with the content analysis method. According to Vladimir Propp, the data provider is done using library studies using data in writings as much as possible about structuralism studies. Data collection techniques are carried out with data-log tinging techniques (interview), observation, and documentation. The results of the study obtained two analysis results and discussions namely (a) the narrative structure of the folklore of Masjid Wali At-Taqwa and Sultan Hadirin and (b) the plan of implementing literature appreciation learning using the learning model think talk write (TTW).
A probabilistic hammer for nailing complex neural data analyses

In this issue of <i>Neuron</i>, Młynarski et al. (2021) provide a maxent-based normative method for flexible neural data analysis by combining data-driven and theory-driven approaches. The next challenge is identifying the right frameworks to use this method at its best.
ropenblas: Download, Compile and Link OpenBLAS Library with R

The ropenblas package provides improved performance on GNU/Linux systems and allows for passing additional compilation flags for more technical users.Through the ropenblas() and rcompiler() functions, the user will be able to compile and link the GNU/Linux distribution R language with the OpenBLAS library, all within R and in a very simple fashion.It works for all GNU/Linux distributions.Linking the OpenBLAS library to R brings better computational performance to the language in the most diverse algebraic operations commonly used in areas such as statistics, data science, and machine learning.
A Unified Equation Characterizing a Monopulse Angle Tracking Unit

The engineering community is confident in its assessment of how an angle tracker will perform in a multi-target environment as the target-to-tracker range decreases, causing targets to leave the tracker antenna beam. When one target signal dominates due to the angular separation of the targets, the tracker will center on the dominating signal. It is not well understood how the tracker will behave when angle separation is not the limiting factor in signal strength. Past work demonstrated how angle error signal normalization impacts track loop dynamics in a dual target scenario [1]. That work postulated a unified equation combining the mathematical representation of dichotomous and centroid tracking. The original equations represented the limiting cases of a zero and infinite bandwidth Automatic Gain Control (AGC). It was postulated a unified equation could account for a finite, non-zero bandwidth AGC; however, a closed-form solution was not derived. This paper provides the closed-form solution for the unified equation and provides additional results via simulation.
A Light-weight Hand-waving Gesture Recognition Method Using Kinect V2 and Frequency Analysis

This paper describes a light-weight method for hand-waving gesture detection. Gesture recognition is actively researched as a user interface of robots. Conventional gesture recognition methods need to employ complicated pattern matching algorithms, such as DTW, HMM, and DNN, which require a powerful computing platform such as fast CPU or GPU that consumes much energy. We propose a gesture recognition/detection method specially designed for the recognition of hand-waving gesture. This method uses Kinect V2 as the sensor and detects the waving gesture using only a simple signal processing. The recognition experiment suggested that the proposed method gave sufficiently high accuracy, and the processing speed was much faster than real-time.
Beyond Rationality Order and Purpose: A Step into the Dark Side of Global Educational Research

Previous articleNext article No AccessBook Essay ReviewBeyond Rationality Order and Purpose: A Step into the Dark Side of Global Educational Research Education in Radical Uncertainty: Baudrillard as Transgression in Theory and Method, by Stephen Carney and Ulla Ambrosius Madsen. London: Bloomsbury Academic, 2021. 272 pp. £81.00 (cloth). ISBN 978-1474298834.Jason BeechJason Beech Search for more articles by this author PDFPDF PLUSFull Text Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinkedInRedditEmail SectionsMoreDetailsFiguresReferencesCited by Comparative Education Review Volume 65, Number 1February 2021 Sponsored by the Comparative and International Education Society Article DOIhttps://doi.org/10.1086/712182 Views: 147Total views on this site HistoryReceived October 15, 2020Accepted October 15, 2020 © 2021 by the Comparative and International Education Society. All rights reserved.PDF download Crossref reports no articles citing this article.
The Knowledge Graph of Chinese Cadre Education and Training Research--Based on the Bibliometric Analysis of CSSCI Sources from 2001 to 2020

Abstract Cadre education and training is a leading, basic, and strategic project for the construction of the cadre team, providing strong leadership and cadre team guarantee for party building and national development in all periods. In the past 20 years, fruitful results have been achieved in research in related fields of education and training of Chinese cadre. This paper analyses 308 CSSCI papers with the help of Citespace software and found that the existing research focuses on three aspects: the history of cadre education, the improvement of the effect of cadre education and training, and the strategy of cadre education and training. It is found that the correlation between the research topics is insufficient, the research results are relatively independent, and the quantitative analysis results are insufficient. It is concluded that research on the theory of cadre education and training, research on policies of cadre education and training, and research on the construction of the cadre education and training system with Chinese characteristics in the new era should be the focus of the next cadre education and training research.
Cooking Actions Inference based on Ingredient’s Physical Features

Most of the cooking recipes available on the internet describe only major cooking steps, since the detailed actions are considered to be common knowledge. However, when we want a robot to cook a meal based on a recipe, we have to give to the robot a step by step plan of each of the tasks needed to execute one recipe step. In this paper, we developed a framework for inferring the executable cooking actions of ingredients, in order to compensate for the common knowledge of humans. We tuned the existing VGG16 Convolutional Neural Network (CNN) to learn the physical features of ingredients. Then, we built an inference model for six different cooking actions based on the learnt physical features of ingredients. The resultant inferred action(s) represents the next possible action(s) that can be executed. As there can be more than one executable action for the same ingredient state, we prioritize the cooking actions considering the previously executed action, for which kind of people the meal is being prepared for and the cooking time allowed. We show experimental results on five different types of ingredients that are not contained in the training dataset of the CNN.
Unusual Activity And Anomaly Detection In Surveillance Using GMM-KNN Model

The major purpose of surveillance is to keep track of a region for security enhancement. The traditional system is being accustomed so far, where it uses a lot of manpower and energy to manually monitor the anomalous events. It therefore results in a waste of time and resources. This paper is a part of intelligent security systems to detect any unwanted happenings or anomalies in a locale using surveillance. An approach to detect unusual activity in surveillance using GMM-KNN model has been proposed. The dataset is acquired from the industrial premises of NLC India Limited. The project proposal has the following stages. The elicitation of frames is performed from the obtained dataset. The initial foreground detection is accomplished by using the GMM. The post processing step to neglect unwanted noises and objects is done using filters and morphological operations. Statistical features are extracted for each object to detect anomaly. Feature based Detected foreground objects are classified into anomaly and background based on KNN classifier.
Survey of High Security and Compression Encryption through Discrete Shearlet Transform and Code Vector Quantization

The advancement of the computerized time has changed the data obtaining, stockpiling and transmission to the advanced structure. The digitalization of data has made its securing, stockpiling and transmission measures to be help. The simplicity of these cycles has expanded the utilization of advanced data by more extensive scope of individuals. Likewise, the simple admittance to this data makes it shaky to be put away and communicated with no veil. The transmission of the computerized data ordinarily happens in the open organization where it very well may be altered or caught by snoops. Past the security issues, the computerized time likewise faces a test in dealing with the hole that emerge between the measure of computerized data that is being created and the capacity of putting away and handling the data created. Compressive detecting, another sign obtaining and pressure method cuts off as an answer to this issue by improving the securing cycle to acquire the picture in the packed structure at a rate considerably less than Nyquist rate. These issues that emerge due to the digitalisation of data accentuations the requirement for the encryption just as pressure encryption calculations, in which the investigation and plan of a few picture encryption and pressure encryption calculations are to be tended to in this theory.
New lower and upper bounds on Armstrong codes

An Armstrong(q, k, n) code is a q-ary code of length n of minimum distance n - k +1 such that for every (k -1)-subset of coordinates there exists a pair of codewords that agree exactly there. Let f(q, k) denote the largest n such that an Armstrong(q, k, n) code exists. Upper and lower bounds on f(q, k) were given earlier in general, and in the case when k > k <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> (q). In the present paper we propose a new construction to provide Armstrong((p+1)/2,2ℓ, p) for a prime p and give an upper bound in the case of fixed k and large enough q. Both results imply improvements on corresponding general known bounds for large enough q.
A Church Historical Meaning of the Year of 1919 and the Role of the Church Today in Korea

The year 1919 is regarded by the Seventh-day Adventist Seventh-day Adventist (SDA) Church especially in Korea as a very meaningful year both theologically and historically. The Bible conference, held in the United States in 1919, was a deep debate in on the Inspiration, Ellen White, and the role of the Spirit of Prophecy in the church. Since then , however, theological development of the church has been stagnant for some time due to the influence of fundamentalism that has entered the church. In the same year of 1919, the March 1 movement broke out in Korea seeking, yearning for independence from Japan''s colonial government. The movement was carried out under the influence of Christianity with, and the Seventh-day AdventistSDA Church also participated participating in the movement. This historical experience is Seventh-day Adventist Church to current and future provide an opportunity of redefining life. First, theFrom this the SDA learned that the right and clear understanding of God''s revelation helps to interpret the Bible properly, so the church should be able to have a deeper and more thorough foundation in theology. Secondly, the Church''s influence on society is not just by words, but by practical life, when each Christian practice for the public good of the community in the public square.
A new parallel adaptive clustering and its application to streaming data

This paper presents a parallel adaptive clustering (PAC) algorithm to automatically classify data while simultaneously choosing a suitable number of classes. Clustering is an important tool for data analysis and understanding in a broad set of areas including data reduction, pattern analysis, and classification. However, the requirement to specify the number of clusters in advance and the computational burden associated with clustering large sets of data persist as challenges in clustering. We propose a new parallel adaptive clustering (PAC) algorithm that addresses these challenges by adaptively computing the number of clusters and leveraging the power of parallel computing. The algorithm clusters disjoint subsets of the data on parallel computation threads. We develop regularized set k-means to efficiently cluster the results from the parallel threads. A refinement step further improves the clusters. The PAC algorithm offers the capability to adaptively cluster data sets which change over time by reusing the information from previous time steps to decrease computation. We provide theoretical analysis and numerical experiments to characterize the performance of the method, validate its properties, and demonstrate the computational efficiency of the method.
Design and Fabrication of Hybrid Land–Air Vehicle

Micro-aerial robotics is a rapidly developing and researched upon the field. However, the ‘Unmanned Aerial Vehicles’ (UAVs) or in this case quadcopters are becoming more advanced and popular day by day. They consume more power and are not maneuverable in natural terrains. Therefore, a hybrid robotic system is proposed which combines the best of an aerial vehicle and a terrestrial vehicle. It uses efficient utilization of power and overcomes obstacles.
The Adapted Program as the Main Tool of Modeling the Educational Environment of Students with Disabilities in the System of Secondary Vocational Education

Introduction. The problems of inclusive education in the system of secondary vocational education have recently become particularly relevant due to the increasing number of students with limited health opportunities and disabilities. Therefore, there is an urgent need to find the best ways to build an educational route for students of these categories. Such an educational trajectory should not only include special conditions that ensure the satisfaction of the special educational needs of such students, but also be aimed at mastering the professional competencies necessary for a modern competitive individual in the labor market. The main tool for implementing the inclusive model of education should be considered an adapted educational program of secondary vocational education. However, the implementation mechanism of this normative document still continues to raise many questions and difficulties. That is why this study was conducted, which involved teachers and masters of vocational training in the system of secondary vocational education, aimed at identifying the difficulties that arise in the implementation of adapted educational programs. The obtained results demonstrated the ambiguity of the current situation in the field of building and implementing an inclusive model in the system of secondary vocational education and allowed us to offer the authors possible solutions to these situations.
Fractal Geometry-Based Automatic Generation of Large-Scale Image Database for Pre-Training in 3D Object Recognition

We propose the generation method of large-scale image database for pre-training in 3D object recognition. The method is inspired from the principles of nature law. We adopt fractal geometry to represent the principles and build the Fractal Data Base random search (FractalDBrs). In contrast to traditional image database such as ImageNet, Iterated Function System (IFS) automatically generates large amount of image data to build the proposed FractalDBrs in short time without menial labors such as collecting and annotating images. In the experiments, we utilized the FractalDBrs and traditional databases; ImageNet, CIFAR100, Caltech256, or Places365, for pre-training in 3D object recognition with ModelNet40. The model pre-trained with FractalDBrs achieved the highest discrimination accuracy of 97.12% against the second highest accuracy of 96.43% with ImageNet. For reference, the model trained from scratch achieved 91.53% discrimination accuracy. We have verified the effectiveness of the proposed fractal geometry-based image database for pre-training in 3D object recognition.
A Transparent Logical Framework for Aspect-Oriented Product Ranking Based on User Reviews

Customer reviews play a major role in online shopping, but there is hardly any support for aggregating the opinions of multiple reviewers, especially when the user is interested in certain aspects only. Current retrieval methods cannot handle the issues of limited credibility, contradictions and information omission when dealing with this type of documents. For addressing these problems, we investigate two multi-valued logic retrieval models. Subjective logic was specifically developed for considering uncertainty and subjective opinions. As an alternative, we regard a probabilistic version of a 4-valued logic addressing missing and inconsistent information. For an aspect-product pair, we get a probability distribution over the truth values and use them for ranking the search results. Our experimental results on a data set from the hotel domain show that our proposed approaches outperform the traditional keyword-based methods for the task of ranking items based on reviews. Moreover, the logic-based methods are more transparent than other approaches.
Bridge Target Detection in Remote Sensing Image Based on Improved YOLOv4 Algorithm

The automatic detection of bridge targets in remote sensing images is of great significance. By analyzing the YOLOv4 network structure and algorithm core ideas, according to the characteristics of remote sensing image bridge target detection, this paper adds 104×104 feature layer scale and combines the idea of attention mechanism to improve the algorithm network structure. At the same time, adjust the anchor point frame according to the characteristics of the bridge target scale to improve the performance of the YOLOv4 algorithm in the remote sensing image bridge target detection, and verify it through the design control experiment. The experimental results show that on the tailored DOTA bridge datasets, the bridge target precision and recall rate of the M-YOLO algorithm have been improved, and the average precision rate has increased by 5.6%, which proves the effectiveness of the improved algorithm.
Dynamic Cross-Sentential Context Representation for Event Detection

In this paper, which focuses on the supervised detection of event mentions in texts, we propose a method to exploit a large context through the representation of distant sentences selected based on coreference relations between entities. We show the benefits of extending a neural sentence-level model with this representation through evaluation carried out on the TAC Event 2015 reference corpus.
Comment on ‘Inference after covariate-adaptive randomisation: aspects of methodology and theory’

In the past decade, significant progress has been made regarding inference under covariate-adaptive randomisation. We thank Prof. Shao for a timely review of the growing literature about the topic....
Uso de herramientas digitales como estrategia para el desarrollo habilidades de análisis y razonamiento en los estudiantes de TIC

The generic competences that the career of Information and Communication Technologies require that the student can have the analysis and reasoning skills to be able to integrate and manage information and communications technologies, which contribute to productivity and the achievement of objectives Strategic organizations. So, through digital tools in the teaching-learning process, the teacher will contribute to develop those skills. Those that will contribute to the objective under the ADDIE model are analyzed and proposed (which represents a descriptive guide for the construction of training and support tools thanks to the development of its five phases that come from the initials of each of them) as first phase; to continue with the creation of different activities and strategies that will be applied with the students and then measure the impact towards their development. The analysis and reasoning skills contribute to analytical thinking, being important because it constitutes one of the bases for critical thinking, as well as helping to solve problems that arise in everyday life.