Reviewerly/exHarmony huggingface dataset:
Exploring the Factors that affect Education Branding and Image Creation in B-School: Using Factor Analysis

Over the last decade, business education has been a popular topic of study for those pursuing higher education. Because the IIMs/IITs and top B-schools are unable to meet this demand, private firms have been allowed to enter the market. This has resulted in severe competition among B-schools, and the education business has never been more competitive. Due to the intense competition among B-Schools (especially private institutions/universities), they have decided to trademark their education. This research is being carried out with the primary goal of determining the most influential aspects in the development of the business school as a brand from the student's perspective. A structured questionnaire was used to elicit responses from respondents about the concept of educational branding. The statistical tool of factorial analysis is used to study the factors of educational branding. The exhibits of Educational Brand image construction model by private institutions and the articulation seen by future managers are explored in this study. This also allows institutions to place a greater emphasis on elements that have a high ranking among students rather of examining all of them.
Application of Block-Chain Technology in Healthcare Industry to Pursue COVID 19 Challenges

In the year of 2019 coronavirus (COVID-19) start spreading in China, but at the starting of 2020 the pandemic of COVID-19 disease has uncontrolled spread and adversely affected the whole world. The rapid explosion and worldwide spread shows the constraints of our healthcare systems to handle public healthcare emergencies. an outsized amount of our healthcare system is centralized, so it can’t provide important information about patients contact tracing, frauds in vaccination certificates, testing related data and medical supply related data. In such contexts innovative and newest technologies like blockchain have initiate as promising solutions for fighting with such situations like pandemic. By using blockchain technology we will combat pandemics by enabling early detection of patients, ensuring the orders of medical data and maintain reliable medical supply chain during pandemic. This study proposes a narrative innovative approach for handling challenges of (COVID-19) pandemic and contagion. This study proposes a Blockchain-based framework which investigate the chance of utilizing peer-to peer, time stamping, and decentralized storage advantages of blockchain to create a brand new system to verify and detect the unknown infected cases of COVID-19 (SARS COV-2) virus. The framework will enable to make sure citizens in addition as government to predict the infection risk of virus, to provide an efficient system able to support governments, healthcare experts, health related authorities and citizens to require critical decisions regarding infection and infection avoidance. this method consists of Blockchain Platform, Mobile application, closed-circuit television these components works together for detecting unknown infected patients and predict the infection risk of corona virus. to create decisions on vaccination and medical supply.
EVALUATION OF MACHINE LEARNING HYPERPARAMETERS PERFORMANCE FOR MICE PROTEIN EXPRESSION DATA IN DIFFERENT SITUATIONS

In this study, the aim was to assess the effect and significance of hyperparameters in four different datasets containing different values for observation numbers and variable counts with the machine-learning methods of support vector machines and artificial neural networks.With this aim, a dataset comprising 15 repeats of 77 protein levels from 38 healthy and 34 down syndrome mice was used.A total of 138 different models and model classification performance criteria were obtained from the datasets in the study comprising combinations of hyperparameters in machine-learning methods.Comparison of the models used criteria like accurate classification percentage, kappa statistic, mean absolute error and square root of mean error squares.According to performance criteria, the first dataset with 1080 observations x 77 variables had 71.30% accurate classification percentage for assumed parameters with the support vector machines polynomial kernel function, while changing the hyperparameter variables increased this rate to 99.44%.Similarly, the second dataset had 50.65% accurate classification percentage with the artificial neural network single hidden layer 2 neuron model, while changing the hyperparameter values increased this rate to 90.46%.In conclusion, in situations with low variable and observation numbers, the machine learning methods were determined to display lower performance.However, in datasets, it is very important for classification performance in artificial neural networks and support vector machines, especially polynomial and radial basis function kernel functions, to set hyperparameters according to the dataset.In situations with low variable numbers, especially, the effect of hyperparameters was determined to gain importance.
Exhibit 8: ADEA Competency Documents

Journal of Dental EducationVolume 85, Issue S2 p. S77-S98 EXHIBITS Exhibit 8: ADEA Competency Documents First published: 15 July 2021 https://doi.org/10.1002/jdd.12721Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat Volume85, IssueS2Supplement: ADEA ANNUAL PROCEEDINGSJuly 2021Pages S77-S98 RelatedInformation
Analysis of Trends and Management Pattern of Educational Aid in Nepal

This research article, “Analysis of Trends and Management Pattern of Educational Aid in Nepal: An Empirical Analysis” aims to analyze the trends and management pattern of education aid in Nepal. Aid is the essential means to remove the bottleneck of development in Nepal. Since 1952 AD international donors have been supporting education sector reforms in Nepal with individual basis. Aid program Education for All (EFA), (2004-2009 AD) was established with donors and Nepal Government Joint Financing Agreement (JFA) for the school education reform. Then after, EFA (2001-2015) established education aid for the reform of primary education in Nepal. This research used the secondary data from the different sources of information and used the descriptive research design for data analysis. The researchers concluded that the educational aid trend is in increasing way in each year, only effective management will fulfill the target and increase the effectiveness of the educational aid in the context of Nepal.
Simulation of quantum jump in three-level atoms using photons

We simulate experimentally a three-level system (cascade, Λ , V ) under quan-tum jump using a three-mode photonic system. A spatial light modulator is programmed for implementing the Kraus operators for quantum jumps.
A value-based approach to online entrepreneurship education in college and undergraduate programs in Russia

The article reveals the features of teaching courses on entrepreneurship, in accordance with the regulatory and methodological support of the Russian educational system, where entrepreneurship is not recognized as a separate area of professional activity. The author offers a possible explanation for this situation, focusing on the principles of modeling vocational education programs. The article reveals the difference between management and entrepreneurship, as well as training programs for "Management" and "Entrepreneurship". The author recommends to approve "Entrepreneurship" as a separate and independent direction of professional training. The key approach to teacher behavior in the educational process is revealed in the article using the concept of value used in entrepreneurship. The teacher's value-based learning approach is to provide the learner with more value in the learning experience than the cost of the learning to the learner. This concept is the opposite of cost- cutting business tactics Separately, the article reveals the problems of education transformation associated with the development of the digital environment. There is a decrease in the value of knowledge and an increase in the value of skills and abilities. For the implementation of entrepreneurship teaching programs in the educational process, more attention should be paid to practical exercises. Author shares his own experience in teaching entrepreneurship courses for bachelor and college programs in the Russian Federation. Separate practical tips for organizing and conducting online classes will help teachers, who face the same types of tasks, that is, for example, teachers, who implement disciplines through online means in accordance with the regulatory and methodological support of the Russian educational system.
Integrating Textual Data into Heterogeneous Data Ingestion Processing

In this abstract, two methods for integrating textual data and textual features into ingestion processing are summarized. The first method involves integrating all features, including textual features, into dedicated frameworks, such as by using machine learning techniques. In the second method, text and textual features, such as keywords, are used to explain results returned by heterogeneous data mining. In this context, it is necessary to link data (e.g., databases, images, etc.) and/or obtained results with textual data (e.g., documents and keywords).
PERANCANGAN BRAND CAMPAIGN DAN MEDIA PROMOSI UNTUK MENINGKATKAN AWARENESS VALUE BRAND ONY POTTERY

This study aims to introduce Ony Pottery to consumers with a brand campaign and the use of social media as a promotional media. Ony Pottery is a ceramic brand based in Surabaya. The research method used in this research is descriptive qualitative. The subjects of this study were consumers and followers of Ony Pottery on social media. The use of social media as a promotional medium is the right thing in this Covid19 pandemic. Ony Pottery's brand value is still conveyed to consumers through social media. Modernism is a design style raised by Ony Pottery in terms of products, social media to promotional strategies. It is hoped that by using the increased awareness, the public will get to know the ceramic brand Ony Pottery.&#x0D; &#x0D; Keywords: Authentic, Selfmade, Clay, Pottery, Brand Campaign
KESALAHAN PENGGUNAAN KONJUNGSI PADA MAKALAH MAHASISWA PROGRAM STUDI PENDIDIKAN BAHASA DAN SASTRA INDONESIA STKIP PGRI SUMATERA BARAT

The backgroundof this research is because are still many errors of using conjunctions in the papers of student of the Indonesia Language and Literature education study program STKIP PGRI West Sumatera. This study aims to describe the misuse of conjunctions found in the papers of students of the Indonesian Language and Literature education study program STKIP PGRI West Sumatera. This type of research is a qualitative study using descriptive methods. The data source of this research is a paper writing scientific papers and discourse analysis of studens of Indonesian Language and Literature education study programs STKIP PGRI West Sumatera. The data in this study are errors using conjunctions in student papers. The results of data analisysis showed that in the papers written by students there were still many errors in their use. Errors of use of conjunctions obtained as many as four errors of use of conjunctions namely Pertema. Misuse of conjunctions and those placed at the beginning of sentences and excessive use of conjunctions and expressions are found in sentences. Secondly, errors in the use of conjunctions and those used at the beginning of a sentence and are not used to connect two languages in a sentence. Third, the use of conjunction errors students put the conjunction at the beginning of a sentence and is not used to connect the power between sentences. Fourth, mistakes in the use of conjunctions while those used at the beginning of a sentence, whereas this conjunction is used precisily in the middle of asentence and used to combine contradictory sentences. The most common use of conjunction errors in student papers is the use of conjunctions whereas, because many students use conjunctions while not in place ther efore the use of conjunctions used by students is declared wrong.
Implications of Revenue Models and Technology for Content Moderation Strategies

This paper develops a theoretical model to study the economic incentives for a social media platform to moderate user-generated content. We show that a self-interested platform can use content moderation as an effective marketing tool to expand its installed user base, to increase the utility of its users, and to achieve its positioning as a moderate or extreme content platform. For the purpose of maximizing its own profit, a platform will balance pruning some extreme content, thus losing some users, with gaining new users because of a more moderate content on the platform. This balancing act will play out differently depending on whether users will have to pay to join (subscription vs advertising revenue models) and on whether the technology for content moderation is perfect.We show that when conducting content moderation optimally, a platform under advertising is more likely to moderate its content than one under subscription, but does it less aggressively compared to the latter when it does. This is because a platform under advertising is more concerned about expanding its user base, while a platform under subscription is also concerned with users’ willingness-to-pay. We also show a platform’s optimal content moderation strategy depends on its technical sophistication. Because of imperfect technology, a platform may optimally throw away the moderate content more than the extreme content. Therefore, one cannot judge how extreme a platform is by just looking at its content moderation strategy. Furthermore, we show that a platform under advertising does not necessarily benefit from a better technology for content moderation, but one under subscription does, as the latter can always internalize the benefits of a better technology. This means that platforms under different revenue models can have different incentives to improve their content moderation technology. Finally, we draw managerial and policy implications from our insights.
Crust, mantle and core structure of Mars from InSight seismic data

&amp;lt;p&amp;gt;With the deployment of a seismometer on the surface of Mars as part of NASA&amp;amp;#8217;s InSight mission,&amp;lt;br /&amp;gt;the Seismic Experiment for Interior Structure (SEIS) has been collecting continuous data since early 2019.&amp;lt;br /&amp;gt;The primary goal of InSight is to improve our understanding of the internal structure and dynamics of Mars, in&amp;lt;br /&amp;gt;particular crust, mantle, and core. Here we describe constraints on the structure of the mantle of Mars based&amp;lt;br /&amp;gt;on inversion of seismic body wave arrivals from a number of low-frequency marsquakes.&amp;lt;/p&amp;gt; &amp;lt;p&amp;gt;We consider 8 of the largest (moment magnitude is estimated to be between 3 and 4) low-frequency events with&amp;lt;br /&amp;gt;dominant energy below 1 Hz for which P- and S-waves are identifiable, enabling epicentral distance estimation.&amp;lt;br /&amp;gt;The 8 events occur in the distance range 25-75 degrees. Body wave arrivals that include the main P- and S-waves,&amp;lt;br /&amp;gt;surface reflections (PP, PPP, SS, SSS), and core reflections (ScS) are picked using a set of complimentary methods&amp;lt;br /&amp;gt;that allows to check for consistency. The resultant set of differential travel times (PP-P, PPP-P, SS-S,...) are&amp;lt;br /&amp;gt;subsequently inverted for radial profiles of seismic P- and S-wave velocity, core size and mean density, and epicentral&amp;lt;br /&amp;gt;location of the events. To determine interior structure, we rely on independent methods as a means of assessing the&amp;lt;br /&amp;gt;robustness of the results.&amp;lt;/p&amp;gt; &amp;lt;p&amp;gt;We present a radial velocity model for the upper mantle of Mars, with implications for the thermo-chemical evolution&amp;lt;br /&amp;gt;of the planet that match a cooling, differentiated body, and a thick lithosphere. Based on the location of the events,&amp;lt;br /&amp;gt;we are able to constrain structure to the core-mantle-boundary, including the size of the core and its mean&amp;lt;br /&amp;gt;density that point to large liquid and relatively light core, implying a significant complement of light alloying&amp;lt;br /&amp;gt;elements. Our estimate of the average crustal thickness as seen by all events is compatible with the local crustal&amp;lt;br /&amp;gt;thickness at the InSight landing determined from observations of converted phases.&amp;lt;/p&amp;gt;
DIAGNOSIS OF BLADE ICING CONDITION OF WIND TURBINES BASED ON RANDOM FOREST

The icing of wind turbine blades will reduce the reliability of wind turbines, the safety of equipment and personnel, and the stability of power systems, thus the diagnosis of wind turbine blade icing condition is significant. In this paper, the supervisory control and data acquisition system (SCADA) data are used to build the icing diagnostic model based on random forest (RF). First, divide the SCADA data into icing data, non-icing data, and invalid data according to the labels for the data-icing and non-icing; then, use the down-sampling technology to extract a new sample set to avoid unbalanced distribution of sample; finally, the new sample set is applied to RF and compare with other machine learning algorithms such as support vector machine (SVM) and eXtreme Gradient Boosting (XGBoost). The results show that the diagnosis model based on the RF classifier has higher accuracy and precision, and it is more suitable for the practical application of icing diagnosis.
A Model-Guided Unfolding Network for Single Image Reflection Removal

Removing undesirable reflections from a single image captured through a glass surface is of broad application to various image processing and computer vision tasks, but it is an ill-posed and challenging problem. Existing traditional single image reflection removal(SIRR) methods are often less efficient to remove reflection due to the limited description ability of handcrafted priors. State-of-the-art learning based methods often cause instability problems because they are designed as unexplainable black boxes. In this paper, we present an explainable approach for SIRR named model-guided unfolding network(MoG-SIRR), which is unfolded from our proposed reflection removal model with non-local autoregressive prior and dereflection prior. In order to complement the transmission layer and the reflection layer in a single image, we construct a deep learning framework with two streams by integrating reflection removal and non-local regularization into trainable modules. Extensive experiments on public benchmark datasets demonstrate that our method achieves superior performance for single image reflection removal.
Network monitoring tools: enabling the management of network assets, ensuring high availability

With the advancement of technology and communication systems as monitoring tools used to manage the network essential to ensure the continuous functioning of systems and devices on a company's network. Through bibliographic research, with studies on computer network and its communication protocols, experimental, considering procedures and manuals of installation, configuration, descriptive, to verify the data collected by the tools. It presents a comparison between Zabbix and Nagios, two open source tools very popular in the market, to conclude which tool is best suited to media and large companies’ scenarios. In summary, Zabbix presents a more viable option for the growth and efficiency of network management in companies. Nagios, on the other hand, proved to be adaptable to different scenarios, with the availability of several plugins increased by the community.
Which way for information and knowledge management education and research?

This scholarly book focuses on the relationship between information knowledge and technology with regard to the Fourth Industrial Revolution.The latter is understood to be a set of highly disruptive technologies blurring the lines between the physical, digital and biological spheres, collectively referred to as cyber-physical systems.Technologies such as cognitive computing, cloud computing, the Internet of Things, big data, augmented or virtual reality, 3D systems, artificial intelligence and power supply are transforming social, economic and political systems.Ultimately, we need to transform, be more creative and innovative to develop and sustain existing and emerging capabilities in the 'new normal', which has been accidentally accelerated by COVID-19 requirements.Technologies for digital transformation create the opportunity for Africa to bypass traditional phases of industrial development as the continent has done successfully in the past.Challenges addressed in the book are inequality, social justice, ethics, access and success, policy, infrastructure and cybersecurity.The book contributes to the ongoing discourse among scholars in Africa.It consists of 10 chapters where conceptual and field research are combined.The first chapter, by Trywell Kalusopa from the University of Namibia, focuses on e-government, with an emphasis on digital government in the digital economy.The second chapter, by Kelvin J. Bwalya from the University of Johannesburg, focuses on e-government from an artificial intelligence perspective.The third chapter, by Tom Kwanya from the Technical University of Kenya, focuses on the perception of robots for information services.In the fourth chapter, Johannes Britz, from the University of Wisconsin, discusses information ethics in the digital economy.
How do Pedagogical Conversational Agents affect Learning Outcomes among High School Pupils: Insights from a Field Experiment

Pedagogical conversational agents (CA) support formal and informal learning to help students achieve better learning outcomes by providing information, guidance or fostering reflections.Even though the extant literature suggests that pedagogical CAs can improve learning outcomes, there exists little empirical evidence of what design features drive this effect.This study reports on an exploratory field experiment involving 31 pupils in commercial high schools and finds that students achieved better learning outcomes when preparing for their tests with a pedagogical CA than without.However, the drivers of this effect remain unclear.Neither the use frequency of the design features nor the pupils' expectations towards the CA could explain the improvement in marks.However, for the subjective perception of learning achievement, pupils' expectations was a significant predictor.These findings provide support for the use of pedagogical CAs in teaching but also highlight that the drivers of better learning outcomes still remain unknown.