Reviewerly/exHarmony huggingface dataset:
Asymptotic Analysis of Statistical Estimators related to MultiGraphex Processes under Misspecification

This article studies the asymptotic properties of Bayesian or frequentist estimators of a vector of parameters related to structural properties of sequences of graphs. The estimators studied originate from a particular class of graphex model introduced by Caron and Fox. The analysis is however performed here under very weak assumptions on the underlying data generating process, which may be different from the model of Caron and Fox or from a graphex model. In particular, we consider generic sparse graph models, with unbounded degree, whose degree distribution satisfies some assumptions. We show that one can relate the limit of the estimator of one of the parameters to the sparsity constant of the true graph generating process. When taking a Bayesian approach, we also show that the posterior distribution is asymptotically normal. We discuss situations where classical random graphs models such as configuration models, sparse graphon models, edge exchangeable models or graphon processes satisfy our assumptions.
Retrospective Review of the Works of Science: Yesterday and Today as a Start for the Future

The article is devoted to statistical processing and analysis of works of science, accumulated in the joint collection of electronic resources “Science and Education” (SFERN&amp;E) for the period from 2005 to the present. The analyzed works of science, in their totality, are considered as the foundation of future science, characterized by interaction, convergence and synchronization of data from different fields of science. The article answers the questions: At the junction of which fields of science are works of science most often produced? What is the frequency of interaction between the various fields of science? Which fields of science are the leaders in interaction with each other? Answers to these questions will reveal the synergy between past and present science as the foundation for the science of the future.
Eyeball Identification and Tracking using Digital Image Processing

Real-time eyeball recognition and tracking using digital image processing techniques can give a way of communication. This paper presents the algorithm for tracking the position of eyes in real-time. The following method consists of two steps: face detection and eye-tracking. In vision-based human-computer interaction, skin color for face detection provides a useful cue. Firstly, face detection is done by combining RGB pixel color, HSI (Hue Saturation Intensity) and YCbCr (Luminance Chrome Blue Chrome Red) color based techniques. Then crop the colored face image from the image and divide cropped image into horizontal sections. As eyes are on the upper part of the face so we have used the speeded up robust features (SURF) key points based method on that section and select the strongest point which is located on the eye region. The eye region is segmented by pixel color techniques. Based on the proposed algorithm possibility of false eye detection is reduced. Experimental results show satisfactory performance in a real-time video stream with average accuracy of 97.2%.
Herramientas informáticas para contribuir al desarrollo de la lectoescritura en escolares sordos

In teacher training from the first grades there is a need to favor the literacy process in deaf schoolchildren. The objective is to propose educational software based on an Android application for the development of literacy in deaf schoolchildren in the first grade. The results obtained in the diagnosis carried out allowed the realization of educational software from developing an Android application for mobile devices which offers interactivity activities through the levels of text construction: denominative, predicative and discursive, also works the freehand tracing of the alphabet with the support of the dactyl.
Calibration and Validation of the Angstrom-Prescott Model in Solar Radiation Estimation using Optimization Algorithms

Earth and Space Science Open Archive This work has been accepted for publication in Earth and Space Science. Version of RecordESSOAr is a venue for early communication or feedback before peer review. Data may be preliminary. Learn more about preprints. preprintOpen AccessYou are viewing an older version [v1]Go to new versionCalibration and Validation of the Angstrom-Prescott Model in Solar Radiation Estimation using Optimization AlgorithmsAuthorsSeyedeh NafisehBanihashemi DehkordiBahramBakhtiariKouroshQaderiiDMohammad MehdiAhmadiSee all authors Seyedeh Nafiseh Banihashemi DehkordiShahid Bahonar University of Kermanview email addressThe email was not providedcopy email addressBahram BakhtiariShahid Bahonar University of Kermanview email addressThe email was not providedcopy email addressKourosh QaderiiDCorresponding Author• Submitting AuthorShahid Bahonar University of KermaniDhttps://orcid.org/0000-0001-8976-7272view email addressThe email was not providedcopy email addressMohammad Mehdi AhmadiShahid Bahonar University of Kermanview email addressThe email was not providedcopy email address
Announcement of Journal of Nanomaterial and Molecular Nanotechnology

Journal of Nanomaterial and Molecular Nanotechnology aims to make your online publishing process as simple and straightforward as possible. To do this, our team is constantly designing tools and features to improve the user experience. When the number of research papers grows, so does the need for large scale analysis and collaboration. Journal Selector, a new function that tests similarity in academic contexts is now available. The author can see a list of the most related scientific journals published is simply entering the title and/or abstract into our Journal Selector. This approach aids writers in choosing the best journals for their articles by emphasising the publication date and citability. Words are interpreted as vectors in hyperspace in this form, which is known as representation learning. Representation aids in the differentiation of various ideas within papers and, as a result, aids in the identification of similarities between them. In order to better capture the semantic meanings of terms, we used an advanced machine learning model. By using scientific text representation, the algorithm is able to make more accurate predictions.
Divide-and-Learn: A Random Indexing Approach to Attribute Inference Attacks in Online Social Networks

We present a Divide-and-Learn machine learning methodology to investigate a new class of attribute inference attacks against Online Social Networks (OSN) users. Our methodology analyzes commenters’ preferences related to some user publications (e.g., posts or pictures) to infer sensitive attributes of that user. For classification performance, we tune Random Indexing (RI) to compute several embeddings for textual units (e.g., word, emoji), each one depending on a specific attribute value. RI guarantees the comparability of the generated vectors for the different values. To validate the approach, we consider three Facebook attributes: gender, age category and relationship status, which are highly relevant for targeted advertising or privacy threatening applications. By using an XGBoost classifier, we show that we can infer Facebook users’ attributes from commenters’ reactions to their publications with AUC from 94% to 98%, depending on the traits.
Measuring and visualizing social distancing using deep learning and 3D computer vision

Social Distancing has proved a necessary measure in controlling the spread of Coronavirus. The CDC (Center for disease control and prevention) in the United States recommends 6 feet as a safe distance between individuals. Therefore, a surveillance system capable of measuring distances between individuals can prove beneficial in limiting the spread. Video surveillance systems have already been introduced in various fields of our daily life to enhance security and protect individuals and sensitive infrastructure. In this work we present a way to use the existing video surveillance infrastructure to measure and monitor social distancing. We present a practical approach to monitor this distance using artificial intelligence and projective geometry techniques. Our approach, after initial setup, works in real-time requiring only a monocular surveillance camera feed. The proposed approach utilizes YOLO v4 neural network object detector for detecting pedestrians in the camera’s view. Projective transformation is used to localize the pedestrians on the ground. Finally, the real world distances between pedestrians is calculated and visualized with the right perspective and occlusion relations as if the distance marks are actually on the ground. All the implementation is in real-time, and is performed on python using the OPENCV libraries and the YOLO v4 neural net with pretrained weights. Experimental results are provided to validate our approach. The code of this work will be made publicly available at GitHub upon acceptance. Copyright © 2020 for this paper by its authors.
Effects of Automation on Sustainability of Immunohistochemistry Laboratory

The COVID-19 pandemic that hit the world recently caused numerous changes affecting the health system in every department. Reduced staff numbers, mostly due to illness, led to an increase in automation at every stage of laboratory work. The immunohistochemistry (IHC) laboratory conducts a high volume of slide staining every day. Therefore, we analyzed time and total costs required to obtain IHC slides in both the manual and automated way, comparing their efficiency by processing the same sample volume (48 microscope slides—the maximum capacity that an automated immunostainer—DAKO, Autostainer Link 48, Part No AS48030—can process over a single cycle). The total IHC procedure time to run 48 slides manually by one technician was 460 min, while the automated process finished a cycle within 390 min (15.22% less time). The final cost of a single manual IHC slide was 12.26 EUR and 7.69 EUR for slides labeled in the automated immunostainer, which reduced final costs by 37.27%. Thus, automation of the IHC procedure reduces the time and costs of the IHC process, contributing significantly to the sustainability of the healthcare system during the COVID-19 pandemic, overcoming insufficient human resources.
INOVASI PENDIDIKAN BERBASIS DIGITAL: PENGGUNAAN FORUM DISKUSIONLINE DALAM PENGAJARAN BAHASA INGGRIS DI INDONESIA

The main issue in ELT is the lack of students’ participation during the teaching learning process.Beside the conventional method that has been done by the lecturer, there are apparently some otherfactors such as the lack of students’ confidence of using English, students’ anxiety of making mistakesespecially in English grammatical structure and pronunciation, less-interactive class, inadequatetime, and the size of the class. Unfortunately, the lack of student participation can impede theaccomplishment of learning objectives, which in this case related to the students' English proficiency.This study is a literature review which focuses on the advantages of using online discussion forum asone of the alternative platforms for lecturer to facilitate learning outside the classroom. This studyfound that the use of online discussion forum in ELT can improve students’ participation, promotesocial interaction and foster students’ achievement in English classroom. Keywords : online discussion forum, ELT, students’ participation
An Analysis of Students’ Difficulties in Writing Recount Text: A Case Study at The Eleventh Grade Students of MA Putra Al-Ishlahuddiny Kediri Academic Year 2016/2017

This thesis entitled “An Analysis of Students’ Difficulties in Writing Recount Text: A Case Study at the Eleventh Grade Student of MA Putra Al-Ishlahuiddiny Kediri Academic Year 2016/2017”. It was aimed to know students’ difficulties and the factors contributing to those difficulties in writing recount text. There were 36 out of 135 students who were taken by using purposive sampling as samples (XI IPA 2). In data collection, three kinds of instruments were used: test, questionnaire and interview. The test was used to know students’ difficulties in writing recount text. The questionnaire was divided into open and close ended questions to obtain information about the factors contributing to the students’ difficulties in writing recount text. The Interview was used as an additional input to complete the data. This study used quantitative and qualitative descriptive method to analyze the data. From the analysis it was found that students were generally categorized as mean score with the percentage is (50.69%) by seeing students’ difficulties in content, organization, vocabulary and sentence structure in term of the test conducted. In terms of the questionnaires, the result showed that the most dominant difficulties were the making of past tense sentences and distinguishing regular from irregular verbs with percentage (81%). Whereas the interview result found that most of students did not understand how to write a recount text and how to use proper words and that they had lack of vocabulary
INOVASI PEMBELAJARAN MENULIS PUISI MELALUI METODE BERBASIS PENGALAMAN DI KELAS X TKRO 1 SMK KB PUSDIKPAL

Writing skills as a part that is considered important, namely writing poetry skills. However, the conditions that occur are in fact many who experience difficulties. Learning strategies are needed in creating a pleasant atmosphere. Experience-based learning model is an approach where students as the center start with the premise that people learn based on experience. The purpose of this study is to describe the effect of using experience-based methods on learning to write poetry in class X TKRO 1 SMK KB Pusdikpal. The research method used in this research is PTK. The instruments used were test and non-test. Data collection techniques include observation, interviews and documentation. Aspects to be assessed include: Accuracy of themes and meanings, diction, rhymes, power of imagination, mandate. The pre-cycle result, the average score of writing poetry was still low, namely 61.1, in the first cycle the class average score increased to 69.5, while in the second cycle, the average score reached 78.4. The increase obtained is if the average value of learning to write poetry in the pre-cycle compared to the first cycle has increased by 8.4, while in the second cycle it is 8.9. With the results obtained in cycle II, it can be seen that the innovation of learning to write poetry in class X TKRO 1 SMK KB Pusdikpal using experience-based learning methods is considered to be able to improve learning outcomes in writing poetry.
RANCANG BANGUN SISTEM MONITORING JUMLAH AYAM DI KANDANG PADA PETERNAKAN BERBASIS IMAGE PROCESSING UNTUK OTOMATISASI PEMBERIAN PAKAN

Currently in Indonesia there are many large or small scale chicken breeders. However, sometimes there are still breeders who feed their animals inefficiently, for example, the amount of feed given is not measured and there is no checking of the number of chickens in the cage. With the development of Image Processing, it can help chicken breeders to be able to monitor the number of chickens. Therefore, in this final project, designed an automatic chicken feeding system that uses a proximity sensor to find out the remaining feed in the container and also uses a camera to monitor the number of chickens in the cage. The prototype to be designed is 50x50x50 cm in size, the system being designed consists of a camera, Arduino Uno controller, servo, measurement sensor using ultrasonic and weight sensor. In this prototype has the haar cascade classifer method, where this method is for reading moving objects and the working principle of feeding chickens will be scheduled at a predetermined time, then the amount of feed given to chickens is based on the results of the number of chickens in the cage. The existence of a prototype monitoring system for the number of chickens in the cage on image processing based farms for automation of chicken feeders, the results of the automatic chicken feeding design get a scheduled feeding time, can monitor the number of chickens in the cage and feed according to the number of chickens who are in the cage.
La presencia social del facilitador en la educación en línea. Buenas prácticas

Online, virtual or Distance Education refers to that model of teaching which consists in a didactic, Information and Communication technology-mediated dialog, that favors greater flexibility and personalization of learning. Teaching English in a virtual context implies necessarily creating a sense of teacher social presence. This concept refers to the state or attitude of being aware of the participants, available, supportive and keeping emotionally connected and committed, truly interested in learning and personality growth. The purpose of this article is to share some good practices that have worked in the Open University for Adults, a leading Distance Education institution in the Dominican Republic. A Google forms survey was applied to a sample of eight facilitators. The survey consisted of a list of strategies, resulting from an extensive Literature review, which referred to teacher social presence and popular procedures to promote collaboration and interactivity in synchronous meetups. The results indicated the generalized use of the strategies that favor the previous-to-course preparation, communication, collaboration, interactivity and effective formative assessment. Complementary relations were identified between the teacher social presence strategies and the procedures used in the online synchronous meetups. Having identified these good practices could help other online facilitators to promote a facilitator-participant emotional connection.
УДК 378:7.012(045) КОМПЕТЕНТНІСНИЙ ПІДХІД ДО ПРОЄКТУВАННЯ ОСВІТНЬО-ПРОФЕСІЙНОЇ ПРОГРАМИ З МЕДІАДИЗАЙНУ :

The theoretical aspect is highlighted and practical ways of designing a professional educational program Mediadesign are presented. The features of professional training in the design direction have been investigated. Topical issues of ensuring the quality of the educational process of future media designers using the tools of the competence approach are considered. The article highlights the importance of modeling competencies and the peculiarities of introducing a competent approach into the process of professional training for applicants for higher education. The issues of the importance of modeling competencies and the peculiarities of introducing a competence-based approach into the process of professional training of future media designers in higher education are analyzed. It is proved that the quality of professional training of future media designers justifiably causes the need for the formation of the necessary competencies among students, which combine knowledge, skills, abilities; abilities and personality traits; general culture indicators; the ability to perform professional duties efficiently. The acquisition by future specialists of a system of design, creative, technological, communicative and interactive knowledge, skills and abilities is aimed at the formation of competencies, which should be considered as a result of high-quality professional training in the professional educational program Mediadesign. The specificity of a media designer's activity lies in the ability to carry out design developments in the context of modern world material and artistic culture, to creatively comprehend the national heritage and to master the skills of using advanced digital technologies as much as possible, provides ample opportunities for employment, professional growth and further scientific activities; the ability to perform complex specialized tasks and solve complex problems in the field of digital media, provides for the implementation of innovations in professional activities and is characterized by the uncertainty of conditions and requirements.Determining the competencies of a media designer makes it possible to determine a clear logical and consistent structure for the design of an educational and professional program Media design. The acquisition by future media designers of a system of knowledge, skills and abilities is aimed at the formation of integral, general and special competencies, which should be considered as a result of the educational process of professional training of Mediadesign.
Towards holistic scene understanding in autonomous driving

Holistic scene understanding is a vital component of the self-driving vehicles of the future. It is crucial that those vehicles are able to understand and interpret their environment in order to drive safely. This requires precise detection of surrounding objects (vehicles, humans, traffic objects, nature), discrimination between drivable and non-drivable surfaces (road, sidewalk, buildings) and segmentation of static and dynamic objects into high-level semantic classes. In the past, computer vision has tackled these problems separately due to their complexity and high computational needs. Nowadays, deep learning-based systems are trained on manually annotated datasets to solve these problems, however they face multiple challenges: 1) the number of the annotated semantic classes are limited by the available datasets to few dozen decreasing the variety of recognizable objects, 2) the density of annotations is inversely proportional to the size of the datasets, rendering huge dataset incompatible for precise segmentation, and 3) detection and segmentation are solved separately, that leads to higher memory and computational demands. Our research addresses the aforementioned challenges by proposing new methods to: 1) train a single network on multiple datasets with different semantic classes and different type of annotations, and 2) solve simultaneously with a single network the problems of detection and semantic segmentation. We have deployed those networks in our autonomous driving car with real-time performance. We demonstrate state-of-the-art results, together with a fivefold increase in the number of recognizable classes, and we integrate efficiently detection and segmentation into a joint panoptic segmentation system, taking important steps towards achieving holistic scene understanding.
THE EFFECT OF USING THINK PAIR SHARE TECHNIQUE TO DEVELOP STUDENTS’ READING SKILLS AT VIII GRADE OF SMP NEGERI 2 KOTA JAMBI

The objectives of the research are to how the effectiveness of Think Pair Share to teach reading comprehension. The method used in this research was Think Pair Share technique. The subject of the research is the eighth grade students of SMP Negeri 2 Kota Jambi. There are 36 students of the eighth class E, and 36 students of the eighth class F. The conclusion in this research is a significant difference of the effects on the students’ reading comprehension between those who were taught using Think Pair Share and those who were taught without using think Pair Share. It can be proved from the score result of Null hypothesis (Ho) is accepted if the value of t-test is the same or less than the value of t-table ( t-test = t-table or t-test 2.032). Alternative hypothesis (Ha) is accepted if the value of t-test is higher than the value of t-table (t-test > t-table). Thus, the alternative hypothesis is accepted, the value of t-test is higher than the value of t-table (5.437 > 2.028. Based on the calculation analysis, it was found that there is improvement score on the students who were taught by think pair share technique. This can be seen from pre test result treatment and post test result after treatment.