Reviewerly/exHarmony huggingface dataset:
Academic inbreeding and mobility in higher education: problems, analysis and prospects

The problems of organizing interactive learning in higher education are discussed, taking into account the prospective introduction of new educational standards. It is noted that the emphasis on the use of professional standards in the existing conditions will lead to a decrease in the creative component of graduate training, and the lack of the possibility of real practice will lead to dogmatism and scholasticism. The high dynamics of technical and technological transformations and transformations of the economic sphere in the Russian Federation against the background of global challenges demonstrates the discrepancy between the paces of individual training of high-class professionals. According to the author, the problem is not the transition beyond the boundaries of habitual work; the main attention should be paid to the "smart" future. Complex technologies require significantly more time than before to master the profession. Domestic specialized education should certainly be linked to the spatial development of Russia, which has a huge territory and corresponding local-territorial specifics. Job security – as a tactical emphasis disappears irrevocably within the borders of the region and the industry, giving way for adaptation to the market of local labor and also rapidly and freely moving capital.
Teacher training in the state of Chihuahua: Between the health challenge and teacher resilience.

The article proposes to recover the response of the Teacher Training and Updating Institutions in the state of Chihuahua regarding the various challenges imposed by the Coronavirus Disease (COVID-19). The qualitative exercise analyzes the experience of 10 institutions based on the voice of their students, teachers, and principals regarding changes in academic, administrative, and organizational processes. It is concluded that the pandemic has affected each institution in different ways and with diverse intensity. Despite the achievements, the experience analyzed reveals the relative success of the using virtual platforms in the face of three basic conditions: connectivity, technological competencies, and socio-emotional skills of the teaching staff. It highlights the importance of implementing tutoring, resilience, or awareness actions of teachers and students' needs, feelings, and sufferings. It is opportune to recover the experiences of other institutions and to question especially students, thesis students and graduates. (English) [ABSTRACT FROM AUTHOR] El articulo propone recuperar la respuesta de las Instituciones Formadoras y Ac-tualizadoras de Docentes en el estado de Chihuahua ante los diversos desafios impuestos por la pandemia del coronavirus (COVID-19). El ejercicio cualitativo analiza la experiencia de 10 instituciones a partir de la voz de sus estudiantes, docentes y directivos en torno a los cambios en los procesos academicos, administrativos y organizativos. Se concluye que, la pandemia ha afectado de diferente manera y con distinta intensidad a cada institucion. Pese a los logros, la experiencia analizada devela el relativo exito del uso de las plataformas virtuales ante tres condiciones basicas: conectividad, competencias tecnologicas y habilidades socioemocionales del profesorado. Destaca la importancia de implementar acciones tutoriales, de resiliencia o de concienciacion de las necesidades, sentimientos y malestares de docentes y estudiantes. Resulta oportuno recuperar las experiencias de otras instituciones e interpelar especialmente a estudiantes, tesistas y egresados. (Spanish) [ABSTRACT FROM AUTHOR] Copyright of Noesis: Revista de Ciencias Sociales y Humanidades is the property of Revista Noesis and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
A Red-noise Eigenbasis for the Reconstruction of Blobby Images

Abstract We demonstrate the use of an eigenbasis that is derived from principal component analysis (PCA) applied on an ensemble of random-noise images that have a “red” power spectrum; i.e., a spectrum that decreases smoothly from large to small spatial scales. The pattern of the resulting eigenbasis allows for the reconstruction of images with a broad range of image morphologies. In particular, we show that this general eigenbasis can be used to efficiently reconstruct images that resemble possible astronomical sources for interferometric observations, even though the images in the original ensemble used to generate the PCA basis are significantly different from the astronomical images. We further show that the efficiency and fidelity of the image reconstructions depends only weakly on the particular parameters of the red-noise power spectrum used to generate the ensemble of images.
Acceleration in Distributed Optimization under Similarity

We study distributed (strongly convex) optimization problems over a network of agents, with no centralized nodes. The loss functions of the agents are assumed to be \textit{similar}, due to statistical data similarity or otherwise. In order to reduce the number of communications to reach a solution accuracy, we proposed a {\it preconditioned, accelerated} distributed method. An $\varepsilon$-solution is achieved in $\tilde{\mathcal{O}}\big(\sqrt{\frac{\beta/\mu}{1-\rho}}\log1/\varepsilon\big)$ number of communications steps, where $\beta/\mu$ is the relative condition number between the global and local loss functions, and $\rho$ characterizes the connectivity of the network. This rate matches (up to poly-log factors) lower complexity communication bounds of distributed gossip-algorithms applied to the class of problems of interest. Numerical results show significant communication savings with respect to existing accelerated distributed schemes, especially when solving ill-conditioned problems.
A STUDY ON TEACHERS’ FILLED-PAUSE IN TEACHING ENGLISH (A Case of English Teachers at MA DARUL MUTTAQIEN NW PERIAN)

Non-native speaker who speaks English as habit in occupation or daily activity is not certain yet to fill the pause as the native speaker’s habit. Some of the English teachers in Indonesia who speak English in giving lesson are predictedable to use filled-pause as hesitation. This study belongs to descriptive study, in which the purpose was to investigate the speech production by non-native speakers whether or not to use filled-pause hesitation as native speakers. The method used in this study was descriptive qualitative method. The technique used was analysing filled-pause based on types and its indications, positions, and the reasons of using filled-pause done by the English teachers at MA DARUL MUTTAQIEN NW PERIAN. The data were gained through the result of observation and interview. The result pointed out that the most type of filled-pause produced by the respondents were ‘er’. Meanwhile, the most position used by the respondents were the boundary of one constituent to another constituent (P2). Moreover, there were the reasons of doing filled-pause hesitation while the respondents did the speech, they were; to memorize vocabulary or sometimes if the speakers forget with the concept, to face the next speech, as the way of the speakers’ control in conveying speech, to search and to think new idea about what the speakers will say next.
Mining the technical skills of open source developers

Software is eating the world as we witness the rise of companies whose business model is totally centered on software. The successful implementation of these systems heavily depends on the quality and expertise of their software development teams. Indeed, IT-based companies are making an increasing effort to hire new professionals to fulfill their open positions. At the same time, the emergence of Social Coding Platforms (SCPs)---e.g., GitHub, Stack Overflow, etc---is contributing to nurturing a new generation of software developers. On one hand, these platforms favor technical recruiters by providing interesting information about software developers when prospecting a new workforce to their companies. On the other, the large volume of data available limits recruiters to only assess superficial information of their candidates. In order to contribute to this problem, we describe in this thesis an extensive investigation of methods and techniques that effectively identify the technical skills of software developers based on their activity in SCPs. We organize the research in three major working units. We start by studying in more detail the most demanded technical and soft skills of software developers under the eyes of IT companies. Next, we analyze the effectiveness of data-driven methods to assess developers' technical skills from two perspectives: (a) deep, where we evaluate supervised and unsupervised methods to identify the expertise level of software developers in three popular JavaScript libraries; and (b) broad, where we apply supervised methods to detect developers' proficiency in six widely mentioned technical roles. Overall, we obtained promising results in using an unsupervised technique to classify developers' expertise level. For example, we were able to produce clusters where the number of experts ranges from 65% to 75%. With respect to technical roles, the proposed model reported higher outcomes for precision (88%) and AUC (89%).
Improving Learning Outcomes of Students in Junior High School Number 1 Bengkulu City with Online Learning Model through Cloud X Application

The research aims to determine how to implement an online learning model to increase learning outcomes of learners. This type of research is class action research (PTK). The subject in this study was a student of class IX.7 Junior High School Number 1 Bengkulu City school year 2020/2021 amounting to 33 learners. The data was collected by using the final cycle concept comprehension test form using the google form feature. The results showed that the application of online learning models during the Covid-19 pandemic through the Cloud X application and using power point media and learning videos could improve student learning outcomes. The increase in student learning outcomes can be seen from the average scores of students from cycle I to cycle II is: 76.90; 81.12 and classical learning completeness of students is 36.36%; 78.79%.
jurnal Penerapan model pembelajaran RCCDE menggunakan audio visual untuk meningkatkan hasil belajar siswa MTs Nuruzzaman: Penerapan model pembelajaran RCCDE menggunakan audio visual untuk meningkatkan hasil belajar siswa MTs Nuruzzaman

Application of the Reading Concept Connection Discussion Evaluation (RCCDE) learning model to improve student learning outcomes on global warming material for the even semester of the 2019/2020 school year. The type of research used was classroom action assessment and the research subjects were grade VII students with 27 students consisting of 20 female students and 7 male students. Not all grade VII students have completed the KKM but 50% have completed the KKM. The results obtained showed that the student's average score reached 79.9% with a total classical completeness of 85.2%. So it can be concluded that the application of the RCCDE learning model can improve student learning outcomes.Keywords: Audio Visual Media, Learning Outcomes, RCCDE Model
DEVELOPING “SPEAK IT UP” BOARD GAME IN SPEAKING SKILL FOR UNDERGRADUATE EFL STUDENTS

One of the goals of teaching English is that how students use the target language orally. Yet, many problems are still found in English speaking class to EFL students. Lack of vocabularies and some psychological factors are really believed as major problems in speaking class. This study focuses on developing an instructional medium in the form of a board game namely “Speak it up!” to be used as the teaching medium to teach speaking for undergraduate EFL students. This board game is designed for the undergraduate EFL students to practice English. Considering one of benefits of instructional medium is believed to be a strong way to facilitate students to speak English. Moreover, this media will be one of solutions as instructional medium to teach speaking especially in language function theme. That is why,this research is going to develop a medium which based on the needs of instructional medium to make the learning process of speaking become active, effective and enjoyable. This research is developed based on the Design and Development (D&D) model. The data are gained from the experts’ judgment evaluation result, which is available of the expert judgment checklist. Then, all data are both analyzed qualitatively and quantitatively using mean score. The study categorized as a succeed study as the developed material met the criteria of a suitable learning material.
STUDENTSâ€™ RESPONSE THROUGH SELF-MONITORING ATTENTION TECHNIQUE IN WRITING SKIL

In writing process the students have to compose their writing by using their own choice of sentence structure and organize their own ideas in such a way that the reader can understand them. The aim of this study is to describe the studentsâ€™ response after having been taught by using self-monitoring attention technique. The data in this study is use descriptive data. The results of this study were 57.10% students strongly agree, 35.05% students agree, 6.35% students quite agree, 0.30% students disagree, and 1.30% students strongly disagree. Most of the students were more active and enthusiastic during the process of teaching and learning through self-monitoring attention technique
Sistem Pendeteksi Gejala Stunting pada Anak dengan Metode Certainty factor Berbasis Website

The purpose of this study is to design and develop a stunting symptom detection system in children using the Website-based certainty factor method which aims to create a stunting symptom detection system in children from an early age and help parents in maintaining nutrition in their children, indirectly said to be computerized to detect stunting means that when applied, it makes it easier for parents to monitor nutrition quickly and precisely. This study uses a system development method where the model used is Waterfall. The results of this study are in the form of an application that provides several symptoms of stunting in children then the user can conduct consultations to determine the calculation of the results of stunting symptoms correctly. The use of this certainty factor method is implemented in an expert system that is used to look for symptoms caused by stunting and in solving the case, the certainty factor obtains an accuracy of 80%.
Projected Model Counting: Beyond Independent Support

The past decade has witnessed a surge of interest in practical techniques for projected model counting. Despite significant advancements, however, performance scaling remains the Achilles' heel of this field. A key idea used in modern counters is to count models projected on an \emph{independent support} that is often a small subset of the projection set, i.e. original set of variables on which we wanted to project. While this idea has been effective in scaling performance, the question of whether it can benefit to count models projected on variables beyond the projection set, has not been explored. In this paper, we study this question and show that contrary to intuition, it can be beneficial to project on variables beyond the projection set. In applications such as verification of binarized neural networks, quantification of information flow, reliability of power grids etc., a good upper bound of the projected model count often suffices. We show that in several such cases, we can identify a set of variables, called upper bound support (UBS), that is not necessarily a subset of the projection set, and yet counting models projected on UBS guarantees an upper bound of the true projected model count. Theoretically, a UBS can be exponentially smaller than the smallest independent support. Our experiments show that even otherwise, UBS-based projected counting can be more efficient than independent support-based projected counting, while yielding bounds of very high quality. Based on extensive experiments, we find that UBS-based projected counting can solve many problem instances that are beyond the reach of a state-of-the-art independent support-based projected model counter.
Temporal-attentive Covariance Pooling Networks for Video Recognition

For video recognition task, a global representation summarizing the whole contents of the video snippets plays an important role for the final performance. However, existing video architectures usually generate it by using a simple, global average pooling (GAP) method, which has limited ability to capture complex dynamics of videos. For image recognition task, there exist evidences showing that covariance pooling has stronger representation ability than GAP. Unfortunately, such plain covariance pooling used in image recognition is an orderless representative, which cannot model spatio-temporal structure inherent in videos. Therefore, this paper proposes a Temporal-attentive Covariance Pooling(TCP), inserted at the end of deep architectures, to produce powerful video representations. Specifically, our TCP first develops a temporal attention module to adaptively calibrate spatio-temporal features for the succeeding covariance pooling, approximatively producing attentive covariance representations. Then, a temporal covariance pooling performs temporal pooling of the attentive covariance representations to characterize both intra-frame correlations and inter-frame cross-correlations of the calibrated features. As such, the proposed TCP can capture complex temporal dynamics. Finally, a fast matrix power normalization is introduced to exploit geometry of covariance representations. Note that our TCP is model-agnostic and can be flexibly integrated into any video architectures, resulting in TCPNet for effective video recognition. The extensive experiments on six benchmarks (e.g., Kinetics, Something-Something V1 and Charades) using various video architectures show our TCPNet is clearly superior to its counterparts, while having strong generalization ability. The source code is publicly available.
Meme Sentiment Analysis Classification With Optical Character Recognitin (OCR) Method And Naïve Bayes Algorithm

Memes generally in the form of images that are the result of the production of people who are used to comment on an event followed by certain templates from popular online images. The spread of memes has become phenomenal and has become very popular in recent years, ranging from lightly charged memes such as memes about jokes, meme quotes to memes with heavy content such as memes about government, education, and the latest news. So that a system is made that can classify types of memes into negative or positive memes by applying the image process and OCR Tesseract combined with the Naive Bayes algorithm. OCR Tesseract is needed to recognize text contained in an image, while the Naive Bayes Algorithm is an algorithm used to find the highest probability value to classify the test data in the most appropriate category. In this study, the test data are meme documents. The results obtained from this application are the level of accuracy of meme classification analyzed is 73.3% from 15 test data and the average classification process time is 1.328 ms. Memes that have been classified for accuracy value depend on the results of OCR using the tesseract engine
Design and Analysis Methods for Trials with AI-Based Diagnostic Devices for Breast Cancer

Imaging is important in cancer diagnostics. It takes a long period of medical training and clinical experience for radiologists to be able to accurately interpret diagnostic images. With the advance of big data analysis, machine learning and AI-based devices are currently under development and taking a role in imaging diagnostics. If an AI-based imaging device can read the image as accurately as experienced radiologists, it may be able to help radiologists increase the accuracy of their reading and manage their workloads. In this paper, we consider two potential study objectives of a clinical trial to evaluate an AI-based device for breast cancer diagnosis by comparing its concordance with human radiologists. We propose statistical design and analysis methods for each study objective. Extensive numerical studies are conducted to show that the proposed statistical testing methods control the type I error rate accurately and the design methods provide required sample sizes with statistical powers close to pre-specified nominal levels. The proposed methods were successfully used to design and analyze a real device trial.
CYCLOPS: A Blockchain-Based Policy System and Formal Policy Model for Consumer Data Movement

We present Control Your CLoud OPerationS (CYCLOPS), a consumer policy smart contract system and a policy model language that allows a consumer to define their own data policies. Our focus is on consumer data mishandling which peaked in the news a few years ago, but is still a problem with no clear solution. We focus on the problem of unauthorized inter-domain consumer data movement and third-party access from a policy viewpoint. Third-parties are given access to consumer data without explicit permission. We use smart contracts to implement decentralized consumer policies. The policies themselves provide an authorization mechanism for companies to use and be aware of a consumer’s desires prior to allowing third party access or data movement across domains. Data from testing CYCLOPS showed there is low cost to the consumer to set up and change a policy (in most cases a fraction of a dollar).
STANDARDIZATION OF RECORDS MANAGEMENT SYSTEM IN LOCAL GOVERNMENT UNITS (PHASE 1: Assessment of the Records Management System of Local Government Units

The study, Assessment of the Records Management System (RMS) of Local Government Units in the Local Government of Laguna, aimed at the assessment of RMS that is being practiced by the province on its Phase 1.This will become a basis for the Standardization of the Records Management System in the Local Government Units in Laguna.It dealt with the parameters of RMS as to; (1) IRMS, (2) Record management program, (3) Regulatory Environment (4) Functionality and components of record system, (5) Record management processes and control, (6) ARMA, (7) Filing Methods, (8) Filing Procedures, and (9) Indexing Rules and as being practice currently by the Local Government of Laguna.The Administrative Professionals of the eight (8) Municipal Government or four (4) Districts of the Province of Laguna were the respondents of the study.From the 160 Administrative professionals in the Municipal Government, a result of "Very Satisfactory" the nine (9) RMS parameters was drawn.This can be inferred that the Province of Laguna strongly agreed on the given parameters and is currently practicing RMS across Municipalities.On the other hand, the seven (7) Municipalities has no significant difference on the RMS practices, except one (1) from the eight (8) having a significant difference on its RMS practices in all Municipalities that were assessed.This can be inferred that the Province of Laguna has its implementing RMS that is considered to be adhering to the standard measures.Nevertheless, the municipalities in Laguna have uncommon RMS practices which is needed to be standardized as to international standard and as to practice or implementation.