Reviewerly/exHarmony huggingface dataset:
Research on Community Risk Prediction Model and Management Based on Deep Learning

The influencing factors of community risk are complex. For the low accuracy of traditional prediction model, a multichannel convolutional neural network community risk prediction model is proposed by improving convolutional neural network of deep learning. First of all, in the community risk prediction model, the structure of multichannel input convolutional neural network is selected. Then, add it into the full connection layer. Subsequently, the DenseNet layer is added to establish connections between different network layers. Finally, the receptive field is improved, and the gradient disappearance is solved. Thus, the prediction accuracy of model is improved. Compared with the traditional model, the proposed multichannel convolutional neural network model has better prediction accuracy. In addition, it performs better on the three indicators, namely, correlation coefficient <math xmlns="http://www.w3.org/1998/Math/MathML" id="M1"> <mi>R</mi> </math> , coefficient of determination <math xmlns="http://www.w3.org/1998/Math/MathML" id="M2"> <msup> <mrow> <mi>R</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msup> </math> , and mean square root error RMSE. Compared with the commonly used LSTM model and logic regression model, the proposed model also has certain advantages, which is more suitable for community risk prediction.
Rising Again in Phoenix!

The 2022 CSE Annual Meeting will take place May 1–3 in Phoenix, AZ, and we have the honor of serving as this year’s Program Committee Co-Chairs. Along with our dedicated Committee members, we are working diligently to carry on CSE’s tradition of outstanding educational content and networking opportunities. We’re thrilled to announce that the theme for this year’s meeting is “Phoenix Rising: Adapting, Collaborating, and Learning in Scholarly Publishing.” As the first in-person CSE Annual Meeting since 2019, this year’s conference will offer attendees the opportunity to meet new industry colleagues on site. As we have all learned during the past few years, both professionally and personally we must be willing to adapt to changing circumstances, imagine new ways to collaborate, and consider each other as vital sources for new learning. Breakout sessions presented by expert speakers at this year’s annual meeting will be a mix of tried-and-true topics with universal interest to editorial offices, journals, authors, and reviewers, and will include lessons learned during the pandemic. We are looking forward to 2 keynotes this year. First, undoubtedly, you’ve noticed a lot of activity in the mergers and acquisitions space, with publishers buying services companies and long-time service providers buying platforms and technology startups. The Program Committee was curious about how all of these developments would affect publishers, especially society publishers. Lisa Janicke Hinchliffe, Professor and Coordinator for Information Literacy Services at the University of Illinois at Urbana-Champaign, and Roger Schonfeld, Director, Libraries, Scholarly Communication and Museums at Ithaka, have […]
Applying Scientific Approach to Improve the Recommended Competencies of English Junior High School Teachers in Palu City

The objective of the study is to investigate the effect of applying a scientific approach to improve recommended competencies of English junior high school teachers. A quasi-experimental design was employed with the use of convenience sampling techniques to select research subjects for control and experimental groups. The 30 items test was developed and used in pre-test and post-test for collecting data. The data were analyzed using t-test analysis to measure mean differences of the data sets from control and experimental groups. The result of data analysis indicates that the mean score of the experimental group, 77.19 is greater than the control group 61.15. This result shows the use of the scientific approach to teach research subjects in an experimental group has an effect in improving their competence on the recommended competencies mandated by the Law and regulations.
COVID-19’s Implications for Accounting Courses’ Competence Development: The Case of Portugal

Over the past few decades, higher education in accounting has been criticized for its focus on developing technical competences at the expense of general competences. The objective of this study is to analyze the general competences developed by the final-year students of accounting courses at Portuguese public polytechnics and to compare them with the most evident ones identified through a literature review for the current accounting profession. The study adopts a quantitative approach, carried out through a survey of 137 final-year students in the 2019/2020 academic year and using the techniques of descriptive and multivariate statistics. Among the main results, it was found that the ability to use information and communication technologies and lifelong learning were the most developed general competences. The results obtained allow us to conclude that the new practices developed through distance learning facilitated the development of technological competences, producing new reflections for improving the training of accountants.
Suitability of the Carbonate Successions for Different Industrial Uses, Pira Magroon Anticline, Northern Part of Iraq, Kurdistan Region

Many geological formations are exposed in the Pira Magroon anticline (Mountain); in the northeastern part of the Kurdistan Region, Iraq. The components of the exposed formations are carbonate rocks, especially limestone, which might be utilized for different industrial uses. To have an industrial assessment for the exposed limestone beds in the Pira Magroon anticline, Zewe Gorge has been chosen for sampling, where the Shiranish and Kometan formations are exposed in the outlet of the gorge. Eleven samples have been collected within the Shiranish and Kometan Formations starting from the bottom of the Kometan Formation, with different sampling intervals. Thereafter, the samples were prepared to be tested by XRF machine; in order to show the concentrations of the main oxides in the collected samples. The weighted averages were calculated from the concentrations of the oxides, and then the averages were indicated. Accordingly, the data was compared with the Iraqi and other industrial standards, to know the usage of the tested rocks for different industries. The acquired data showed that the carbonate successions of the Kometan and Shiranish Formations of the Zewe Gorge in the Pira Magroon Anticline, can be used in cement production.
Desktop Virtual Assistant

Abstract: Changes in technology have impacted human life in a variety of ways. Because of technology improvements, the way we lived in the past and how we live now are vastly different. Previously, computers could only perform a limited number of jobs, but advances in machine learning, artificial intelligence, and other technologies have advanced computers significantly. As a result, various voice assistants such as Alexa, Siri, and Cortana, which function on speech recognition, have been developed to make computers more advanced and to eliminate the use of input devices. Keywords: Virtual assistant, Speech recognition, python, text to speech.
Nepalese Society is Becoming More Attracted to English: Just as Iron is Attracted to Magnets

Just as globalization has affected Nepal's various political, social, and economic sectors, so has its impact on education. Over the last 50-60 years, the influence of English as a foreign language in the Nepalese education system has been increasing. The attraction of English has increased in such a way that it has become like a tradition to learn English before own's mother tongue. Not only in school, but parents are also eager to teach English to their children from home. Parents are constantly trying to improve their child's English. The psychology that a child becomes omniscient if he knows English is affecting everyone. Nepalese society is being influenced by the fact that foreign culture and English are more civilized than their mother tongue and culture. Globalization is currently adversely affecting the Nepalese education system. The English-only education system has not been able to explain the importance of their own language and local knowledge. With the development of the mentality that language is only for a good job and a prosperous life, the mentality that English should be learned anyway has taken root in Nepalese society. This paper has also tried to present the growing attraction of English education in Nepalese society from different perspectives. Textbooks, medium of examination, question papers, giving a lot of opportunities to students who know English have drawn everyone towards English. This paper presents the problems, solutions, and suggestions in four different sections. In the first section, the early stages of English education in Nepal are discussed. In the second section, the influence of foreign languages ​​on the original language and culture is discussed. Third, the fact that English influence has increased in emotional expression and daily life is presented in graphs and bars. The final section includes research findings, solutions, and suggestions.
Nowcasting of Solar Power Production by a Deep Learning &amp;#160;Methodology: Improving Forecasts for Solar Energy Sites during Sahara Dust Events using Highly Resoved Historic Time Series, Remote Sensing and Numeric Weather Prediction Models

&amp;lt;p&amp;gt;With the rapidly increasing use of solar power accurate predictions of the site-specific power production are needed to ensure grid stability, energy trading, (re)scheduling of maintenance, and energy transfer. Particularly in systems relying on many factors such as solar energy, extreme events can be a threat to the power grid stability and accurate nowcasts. Thus, warnings within a reasonable amount of time ahead for preparation are essential. In the MEDEA project, funded by the Austrian Climate Research Program, we aim at improving the definition and detection of extreme events relevant for renewable energies and using these findings to improve both weather and climate predictions of such extreme events.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;In the presented case study, we investigate selected (extremes) cases of Sahara dust events in 2021 where various weather prediction models were unable to properly reproduce the amount of aerosols in Central Europe resulting in a discrepancy between actual solar power production compared to predictions being off by more than 5 GW.&amp;amp;#160; Here, several solar production forecasts gave impaired results based on raw NWP model output. To tackle such events and improve the predictability, a deep learning framework including an LSTM (long short-term memory; type of an artificial neural network) and random forest will be adopted for nowcasting with multiple heterogeneous data sources available. Relevant features include 3D-fields from different NWP models (AROME, WRF), satellite data and products (CAMS), point-interpolated radiation time series from remote sensing, and observation time-series (site observations, close meteorological sites). We investigate up to 6 hours ahead nowcasts at several Austrian solar power farms with an update frequency of 15 minutes.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Results obtained by the developed method yield, in general, high forecast-skills, where we elaborate on interesting cases studies from a meteorological point of view. Different combinations of inputs and processing-steps are part of the analysis. We compare obtained forecast results to available forecast methods, e.g., an analogs-based method, pvlib forecasts driven with AROME and AROME RUC.&amp;amp;#160;&amp;lt;/p&amp;gt;
SISTEM INFORMASI MANAJEMEN PENDIDIKAN DI SEKOLAH

People who live before the arrival of the information age, handling information is donemanually or mechanically by using machines that are not computers. However, inentering a new era, the world community is now also in an era of knowledge-basedsociety. In addition, the world is in an era of information and communication. Which atthe moment we are in the information age, this means that information has touched allaspects of life, both individuals, groups and organizations. At the individual level variouskinds of information are needed such as the need for education, health, employment, andother types of products or services.
Evaluation of a system that the reading of sentences by a voice synthesizer and the highlighting sentences

It is generally known that there are individual differences in human cognitive function.We made a hypothesis; giving both visual and audio stimuli may make it easier for people to catch information.In this study, we set three indicators consists of memory, understanding and concentration for an experiment.The difference in learning effect due to the reading situation was measured.We concluded voice synthesizer and highlighting system can help reading in some cases.
Cystic Region Detection Using Hybrid Fuzzybased Multi-Region Normalization

One of the main purposes of this approach is to automatically extract the cystic border.Several of the semiautomatic segmentation strategies that have already been used may result in incomplete categorization, which is likely to fail as well as causes solitary pixel in noise dentistry x-rays images due to sampling artifact.As such, cyst boundaries are not removed appropriately.It focuses on the elimination of solitary pixels caused by artefacts.This suggested technique uses both the fuzzy memberships function of every pixel as well as localized spatially information of the neighbor pixels to accomplish the maximum feasible levels of automated processes for computers-aided diagnostics or identification of illnesses.That fuzzy-based multi-region normalization is implemented in five phases.To begin, FCM techniques are used to determine the numbers of centroids.This fuzzified function is constructed as well as provides memberships degree numbers to any and every pixel within every class based on the number of cluster centers as well as the shape of the histogram.It generates an intermediary segmentation output by fuzzy memberships degrees at about this step.This fuzzy localized aggregating of the neighborhood pixels will be the fourth phase, with the greatest responsiveness of the memberships degree generating pixels being kept in mind only for ultimate cystic area retrieved outputs.
Autonomous security assessment model using genetic algorithm in cyber-security domain for healthcare documents

In this article, an organization data security appraisal model dependent on abreast hypothesis was considered and advanced. Based on completely considering the data security issues evaluation interaction and components, the degree and mischief of the assault were broke down, and information sources and the particular techniques for incorporating circumstance factors and key hubs were applied to plan the general model, in this way guaranteeing the precision of healthcare documents through cyber-security approaches. The use of hereditary calculation in the dependability investigation of PC correspondence networks is of extraordinary importance. In this paper, the dependability examination and utilization of PC correspondence network dependent on hereditary calculation were considered. The primary substances of hereditary calculation were presented. Simultaneously, the primary substance and exploration techniques for the unwavering quality investigation of PC correspondence network were talked about. Finally, the exploration results were examined and talked about. The outcomes show that the use of hereditary calculation in PC correspondence network dependability investigation is acceptable, which gives a positive evaluation to attain better efficiency of PC correspondence network.
Type-errors and Token-errors in Grammar Evaluation

Evaluation forms an integral part of the teaching-learning process and therefore needs to be judiciously conducted.When it comes to languages, there is a danger of evaluation being subjective or, at least, onedimensional.Two teachers may, for example, evaluate the same essay differently, with one teacher focusing on every error therein (token-based evaluation of errors), while the other focuses on just the types of errors committed (type-based evaluation).Depending on the kind of evaluation adopted, therefore, a learner's grades may differ significantly.With a view to address such discrepancies, this paper proposes a mode of evaluation where tokenerrors and type-errors are both considered, but in different grammatical areas.The proposed mode of evaluation is expected, among other things, to save teachers some amount of 'correction time' and promote independent learning among learners.
Contemporary Conditions of Efficient Implementation of Inclusive Education at the University

The paper analyzes the conditions of introducing inclusive education at universities. The suggested classification of necessary conditions may be applied in practice for efficient inclusion at higher educational institutions. We used the methods of descriptive analysis, observation, and Pearson’s chi￾squared test (χ2). The research findings include the identified efficient conditions of inclusive education, such as (1) creating a column about “Inspiring stories” on the website of the educational institution; (2) conducting group psychological training for students, joint activities, and the so-called “student hour”; (3) establishing a department of distance and inclusive education; (4) developing further education courses for teachers with a focus on communication with students with disabilities and health-related conditions; (5) designing courses for tutors and assisting students with disabilities and health-related conditions to provide them with comprehensive support within the entire period of study at universities; and (6) creating online and offline courses for teachers to develop their readiness to introduce inclusive education at universities by five criteria.
Private Face Image Generation Method Based on Deidentification in Low Light

The existing face image recognition algorithm can accurately identify underexposed facial images, but the abuse of face image recognition technology can associate face features with personally identifiable information, resulting in privacy disclosure of the users. The paper puts forward a method for private face image generation based on deidentification under low light. First of all, the light enhancement and attenuation networks are pretrained using the training set, and low-light face images in the test set are input into the light enhancement network for photo enhancement. Then the facial area is captured by the face interception network, and corresponding latent code will be created through the latent code generation network and feature disentanglement will be done. Tiny noise will be added to the latent code by the face generation network to create deidentified face images which will be input in a light attenuation network to generate private facial images in a low-lighting style. At last, experiments show that, compared with other state-of-the-art algorithms, this method is more successful in generating low-light private face images with the most similar structure to original photos. It protects users' privacy effectively by reducing the accuracy of the face recognition network, while also ensuring the practicability of the images.
Research on analysis of power and water consumption data for group tenant identification based on federated learning

The protection of user privacy is more and more important, which restricts the effective application of traditional methods in some fields. Federated learning is an effective method to solve such problems. The vertical federated learning method can be effectively applied to the joint analysis of multiple energy data. This paper discusses the application of this method in identifying group tenants in the research of urban energy big data, proposes an address based data matching method and corresponding coding rules, and implements an example based on SecureBoost. The results show that vertical federated learning has a good effect in the joint modeling of electricity and water data.
PERANCANGAN SISTEM INFORMASI KUNJUNGAN PASIEN RAWAT JALAN BERBASIS WEB

The design of an outpatient visit information system is a form of need for the hospital system which is believed to provide convenience for medical record officers in analyzing outpatient visit data. I hope that with the outpatient information system it can be easier to access data and store data. The outpatient visit system is not computerized and officers need to re-enter visit data to manage patient visit data and this is quite time-consuming which causes the information produced to be slow, less accurate and irrelevant. For this reason, researchers evaluate the existing work system at the hospital order to improve good system governance. Researchers use Microsoft Visual Studio 2010 determining the program. The results in this system are that initial introduction to prospective system users, a performance evaluation is carried out to anticipate changes information needs the future and is more thorough in lending and storing medical record files.
«Teacher-student» relationship: nonlinearity of interaction of individuals

The idea of considering the nonlinearity of interactions between personalities in «teacher-student» relationship is determined the transition of science from classical to non-classical and post-classical stages of its development. Paradigmatic shifts that require semantic explication of the «teacher-student» relationship in a certain discourse are associated with a synergetic research program and the formation of complex and nonlinear styles of scientific thinking. Since there are a number of approaches to the philosophical and methodological study of the «teacher-student» relationship, we can talk about a number of complications, because each of the components of this relationship shows the diversity of their interactions and so on. That is why there is no single understanding of the problem of the «teacher-student» relationship, which could be applied to different contexts. Based on a nonlinear approach to understanding the teacher-student relationship, the nonlinearity of each of the components of this relationship and their interaction with each other is revealed. Clarification of the problematic spectrum of the term «personality» in the article was based on the study of classical and modern research. The methodological perspective through which the study took place gave a holistic view of the understanding of the nonlinearity of the features of personality in both components of this relationship. It was found that a person can be interpreted as nonlinear only in his interaction with others, that is why any person involved in the educational process will acquire nonlinear characteristics. The importance of understanding the nonlinearity of personality characteristics in modern post-classical discourse is clarified and the methodological potential of the nonlinear approach to understanding personality is investigated. Based on the synergetic approach it is revealed the understanding of nonlinear characteristics of personalities as active subjects of the «teacher-student» relationship, who are capable to self-organization, self-development, self-regulation, self-analysis and self-realization, and are carriers of nonlinear thinking.