Reviewerly/exHarmony huggingface dataset:
The role of mobile media in journalism education

Journalism education is seen as laying the foundation for the attitudes and knowledge of future journalists and mobile media are one of the areas predicted to have an impact on future journalism. Departing from the assumptions that the curriculum can tell us something about what journalism schools highlight as important skills and knowledge for the future students to acquire, this chapter examines the role of mobile media in ten journalism schools across Europe. Inspired by approaches from the field of curriculum studies this exploratory study seeks to do an analysis of distinctive variables: (a) mobile media syllabus; (b) the practical or theoretical nature of mobile media subjects; and (c) the differences between mandatory, core, and basic training. Analysis shows that although many institutions have built mobile media perspectives in their course syllabus, it is not given an important role in the core of journalism education. Further, it seems like they mostly treat mobile media as a technology tool requiring practical skills to produce conventional and emerging storytelling formats. This corresponds with the understanding of MOJO—the mobile journalist with the phone as her tool.
Effects of Self-directed Learning Ability, Teaching Presence, and Learning Presence on University Students’ Learning Flow in Untact Online Class Environments

Objectives This study investigated university students’ self-directed learning ability, teaching presence, learning presence, learning flow, their correlations, and the effects of self-directed learning ability, teaching presence, and learning presence on the students’ learning flow.&#x0D; Methods 255 university students taking general courses at a four-year university participated in the study and were tested on their levels of self-directed learning ability, teaching presence, learning presence, and learning flow. Their test responses were analyzed through SPSS 25.0. Descriptive statistics, Pearson correlation analyses, and stepwise multiple regression analyses were administered.&#x0D; Results Descriptive statistical analyses found that their teaching presence was the highest among the four. Pearson correlation analyses revealed that their learning presence and learning flow, and their teaching presence and learning presence showed highest correlations. The results of the stepwise multiple regression analyses presented that the greatest variable affecting learning flow was learning presence. Among the subcomponents, cognitive presence in learning presence showed the greatest effect on learning flow.&#x0D; Conclusions It is important for universities and instructors to provide students with better learning environments by developing various teaching-learning resources and strategies that can facilitate the students’ cognitive presence and thus promote their learning flow.
Comparing Some Methods of Kernel Discriminant Analysis Under Fuzzy Environment

One of the most widely used statistical methods in the field of data analysis is the method of discriminant analysis, and the use of discriminant analysis requires the availability of a number of assumptions, the most important of which is that the data of explanatory variables have a multivariate normal distribution. The discriminant analysis often suffers from the problem of small sample size, especially when it is applied to classify several dimensions; we deal with this problem through the use of the Kernel Discriminant Analysis method (KDAM). But in many situations in real world suffuref from inaccuracy in measurements that is leads to inaccuracy in conducting the required statistical analyzes, so it is necessary to get out of the traditional pattern of data to that fuzzy pattern by finding a fuzzy information system based on the principle of cutting in the fuzzy group to find measurements of data that represent the phenomenon with certainty and which represent the group of important elements that represent those phenomenon. In this paper, we form the estimation function of the kernel density with an application in discriminant analysis to be a comparison in estimation density function depends on the choice of bandwidth, which controls the smoothing of the estimate and on the choice of the kernel function., some methods were used to estimate the bandwidth parameter, which is least square Cross validation, Biased cross validation and Bayes discriminant rule Method under fuzzy measurements. The estimation of Kernel density is important in multivariate data analysis, and it depends heavily on the appropriate selection of the bandwidth matrix (H) that reduces the mean integration square error (MISE) and the error rate (𝑀𝑅̂) through the common rule of sets which is KDR kernel discrimination. Finally, it was based on real data from the disease (general leukemia) and the 6 factors (variables) that affect the disease. We note that (KDA-Bay) method is better than (KDA-SCV) and (KDA-BCV) because it gives the lowest classification error rate from the results, and we note that all methods under fuzzy data better than the methods under traditional data.
Impact of cryptocurrencies on international markets

Cryptocurrencies, which have gained a lot of popularity owing to their decentralisation ideas, aswell as the possibility for largereturns, are still very volatile, and their losses are more likely. The price of Bitcoin, for example, climbed from $1,000 to a peak of almost $19,000 in 2017, before falling to roughly $3,000 in 2018. 1 Then, in the summer of 2021, Bitcoin fell to roughly $30,000 before rising again until the fall of 2020, reaching new highs of over $60,000. Digital orvirtual currency known as "cryptocurrency" is meant to be used as a form of payment. Prefixing"crypto" refers to the fact that cryptocurrencies rely on cryptography to protect transactions andcreate new currencies (coins). For example, encoding something that can be deciphered with akey but impossible to read without a key implies that coins can be difficult to manufacture buttransactions can be easily verifiable.
RT-DNAS: Real-Time Constrained Differentiable Neural Architecture Search for 3D Cardiac Cine MRI Segmentation

Accurately segmenting temporal frames of cine magnetic resonance imaging (MRI) is a crucial step in various real-time MRI guided cardiac interventions. To achieve fast and accurate visual assistance, there are strict requirements on the maximum latency and minimum throughput of the segmentation framework. State-of-the-art neural networks on this task are mostly hand-crafted to satisfy these constraints while achieving high accuracy. On the other hand, existing literature has demonstrated the power of neural architecture search (NAS) in automatically identifying the best neural architectures for various medical applications, within which differentiable NAS is a prevailing and efficient approach. However, they are mostly guided by accuracy, sometimes with computation complexity, but the importance of real-time constraints are overlooked. A major challenge is that such constraints are non-differentiable and thus are not compatible with the widely used differentiable NAS frameworks. In this paper, we present a strategy that can directly handle real-time constraints in differentiable NAS frameworks, named RT-DNAS. Experiments on extended 2017 MICCAI ACDC dataset show that compared with state-of-the-art manually and automatically designed architectures, RT-DNAS is able to identify neural architectures that can achieve better accuracy while satisfying the real-time constraints.
Private Capital Flows, Domestic Financial Markets and Energy Use in Africa

This study examines the relationship between private capital flows and energy use in Africa, considering the moderating role of domestic financial markets during the period, 1990–2019. To do this, we use the modified fixed effect model based on the feasible Generalised Least Squares estimator to fit a multiple regression that corrects for serial correlation using the Durbin-Watson serial correction approach. Our empirical results revealed that domestic financial markets play a significant role in establishing the connection between private capital flow and energy use. Specifically, the study showed that private capital inflows conditioned on a favourable financial market environment enhance energy use in Africa. In other words, the presence of these financial market indicators provides a conduit for private capital flows to improve energy use in Africa. Therefore, policy makers in Africa must provide the means to strengthen and further develop the domestic financial markets to attract the necessary private capital capable of enhancing energy use.
Artificial Intelligence (A.I) Application in Foreign Language Teaching and Learning

In this article, the author will analyze specifically the problem of using artificial intelligence (AI) technology in teaching Foreign Language at the higher education. From there, the author will propose some solutions to further improve the effectiveness of using AI technology in teaching and learning English in particular and foreign languages ​​in general in Vietnam in the next period.
Polarities Inconsistency of MOOC Courses Reviews Based on Users and Sentiment Analysis Methods

Sentiment classification has been perceived as an important feature in today's scenario, as it provides strategies for repeatedly assessing popular assessments to excerpt meaningful information about a product or amenity. The most important source of information about the social interactions taking place in Massive Open Online Courses (MOOCs) is forum messages. Patterns and learner behaviors can be discovered by analyzing forum messages. In our review, we contended that this number, which we alluded to as user polarity, may not precisely reflect the sentiment communicated in all of the lines that make up the assessment. We check out conclusions from six MOOC course audits and track down the sentiment analysis methods that naturally infer polarities have irregularities. Users tend to review their courses positively, although negative language and elements do arise from time to time, which these algorithms discover. To beat these issues, we present a polarity aggregation model that thinks about the two polarities while following the mathematical mean. We research its exhibition by removing components from MOOC audits and doling out added extremity to them. The benefit is that it combines the context's sentiment with the sentiment collected by a pre-trained algorithm.
Classification and Feature Extraction for Document Forgery Images

Hyperspectral images (HSIs) are captured over continuous wavebands. It includes the object's spatial as well as spectral information. Different materials have different reflection and absorption properties, which allows obtaining the underlying sample's physical structure and chemical composition. Therefore, hyperspectral imaging technology gives comprehensive information about the sample. This paper uses a hyperspectral imaging approach to detect document forgery in the documents through ink mismatch detection. The proposed approach utilizes PCA to handle multiple dimensions in HSIs. It captures the spectral features which act as an input to a convolutional neural network for image classification. The method is applied to the UWA Writing Ink HSI (WIHSI) database. The results are compared with the state-of-art results that prove the proposed approach's potential.
High Dimensional Datasets Optimization handling by Wrapper Sequential Feature Selection in Forward Mode - A Comparative Survey

High-quality data might be difficult to be produced when there is a large quantity of information in a single educational dataset. Researchers in the field of educational data mining have recently begun to rely more and more on data mining methodologies in their investigations. However, instead of undertaking feature selection methods, many research investigations have focused on picking appropriate learning algorithms. Since these datasets are computationally complicated, they need a lot of computing time for categorization. This article examines the use of wrapper approaches for the purpose of managing high-dimensional datasets in order to pick appropriate features for a machine learning approach. This study then suggests a strategy for improving the quality of student or educational datasets. For future investigations, the suggested framework that utilizes filter and wrapper-based approaches may be used for many medical and industrial datasets.
Modeling and application of marketing and distribution data based on graph computing

Integrating marketing and distribution businesses is crucial for improving the coordination of equipment and the efficient management of multi-energy systems. New energy sources are continuously being connected to distribution grids; this, however, increases the complexity of the information structure of marketing and distribution businesses. The existing unified data model and the coordinated application of marketing and distribution suffer from various drawbacks. As a solution, this paper presents a data model of “one graph of marketing and distribution” and a framework for graph computing, by analyzing the current trends of business and data in the marketing and distribution fields and using graph data theory. Specifically, this work aims to determine the correlation between distribution transformers and marketing users, which is crucial for elucidating the connection between marketing and distribution. In this manner, a novel identification algorithm is proposed based on the collected data for marketing and distribution. Lastly, a forecasting application is developed based on the proposed algorithm to realize the coordinated prediction and consumption of distributed photovoltaic power generation and distribution loads. Furthermore, an operation and maintenance (O&M) knowledge graph reasoning application is developed to improve the intelligent O&M ability of marketing and distribution equipment.
Retraction: Research on the Cultivation and Improvement Strategies of University Teachers’ Innovative Consciousness and Ability Based on Network Technology (J. Phys.: Conf. Ser. 1648 022075)

This article has been retracted by IOP Publishing following an allegation that raises concerns this article may have been created, manipulated, and/or sold by a commercial entity. In addition, IOP Publishing has seen no evidence that reliable peer review was conducted on this article, despite the clear standards expected of and communicated to conference organisers. The authors of the article have been given opportunity to present evidence that they were the original and genuine creators of the work, however at the time of publication of this notice, IOP Publishing has not received any response. IOP Publishing has analysed the article and agrees there are enough indicators to cause serious doubts over the legitimacy of the work and agree this article should be retracted. The authors are encouraged to contact IOP Publishing Limited if they have any comments on this retraction. Retraction published: 16 September 2022
Retraction: Analysis of the Status Quo, Problems and Suggestions of the Development of Combined Heat and Power Central Heating in China Based on Big Data Technology (J. Phys.: Conf. Ser. 1648 022150)

This article has been retracted by IOP Publishing following an allegation that raises concerns this article may have been created, manipulated, and/or sold by a commercial entity. In addition, IOP Publishing has seen no evidence that reliable peer review was conducted on this article, despite the clear standards expected of and communicated to conference organisers. The authors of the article have been given opportunity to present evidence that they were the original and genuine creators of the work, however at the time of publication of this notice, IOP Publishing has not received any response. IOP Publishing has analysed the article and agrees there are enough indicators to cause serious doubts over the legitimacy of the work and agree this article should be retracted. The authors are encouraged to contact IOP Publishing Limited if they have any comments on this retraction. Retraction published: 16 September 2022
Retraction: Research on Innovation and Entrepreneurship of Business Education in Colleges and Universities Based on Computer Big Data Mining Technology (J. Phys.: Conf. Ser. 1744 032053)

This article has been retracted by IOP Publishing following an allegation that raises concerns this article may have been created, manipulated, and/or sold by a commercial entity. In addition, IOP Publishing has seen no evidence that reliable peer review was conducted on this article, despite the clear standards expected of and communicated to conference organisers. The authors of the article have been given opportunity to present evidence that they were the original and genuine creators of the work, however at the time of publication of this notice, IOP Publishing has not received any response. IOP Publishing has analysed the article and agrees there are enough indicators to cause serious doubts over the legitimacy of the work and agree this article should be retracted. The authors are encouraged to contact IOP Publishing Limited if they have any comments on this retraction. Retraction published: 16 September 2022
Retraction: Research on The Construction of Japanese Curriculum System for Foreign-Related Secretarial Major in Technology-Based Universities Based on Computer Multimedia Technology and Multicultural Background (J. Phys.: Conf. Ser. 1744 032084)

This article has been retracted by IOP Publishing following an allegation that raises concerns this article may have been created, manipulated, and/or sold by a commercial entity. In addition, IOP Publishing has seen no evidence that reliable peer review was conducted on this article, despite the clear standards expected of and communicated to conference organisers. The authors of the article have been given opportunity to present evidence that they were the original and genuine creators of the work, however at the time of publication of this notice, IOP Publishing has not received any response. IOP Publishing has analysed the article and agrees there are enough indicators to cause serious doubts over the legitimacy of the work and agree this article should be retracted. The authors are encouraged to contact IOP Publishing Limited if they have any comments on this retraction. Retraction published: 16 September 2022
Retraction: Research on College Students’ Innovation and Entrepreneurship Education Based on Computer Multimedia Technology (J. Phys.: Conf. Ser. 1648 032023)

This article has been retracted by IOP Publishing following an allegation that raises concerns this article may have been created, manipulated, and/or sold by a commercial entity. In addition, IOP Publishing has seen no evidence that reliable peer review was conducted on this article, despite the clear standards expected of and communicated to conference organisers. The authors of the article have been given opportunity to present evidence that they were the original and genuine creators of the work, however at the time of publication of this notice, IOP Publishing has not received any response. IOP Publishing has analysed the article and agrees there are enough indicators to cause serious doubts over the legitimacy of the work and agree this article should be retracted. The authors are encouraged to contact IOP Publishing Limited if they have any comments on this retraction. Retraction published: 16 September 2022
Retraction: A Study of the Role and Approach of China English in the Spread of Chinese Culture Based on the Analysis of Big Data (J. Phys.: Conf. Ser. 1744 042131)

This article has been retracted by IOP Publishing following an allegation that raises concerns this article may have been created, manipulated, and/or sold by a commercial entity. In addition, IOP Publishing has seen no evidence that reliable peer review was conducted on this article, despite the clear standards expected of and communicated to conference organisers. The authors of the article have been given opportunity to present evidence that they were the original and genuine creators of the work, however at the time of publication of this notice, IOP Publishing has not received any response. IOP Publishing has analysed the article and agrees there are enough indicators to cause serious doubts over the legitimacy of the work and agree this article should be retracted. The authors are encouraged to contact IOP Publishing Limited if they have any comments on this retraction. Retraction published: 16 September 2022
Retraction: Research on College English Online Learning Platform Model Based on Big Data Technology (J. Phys.: Conf. Ser. 1648 042090)

This article has been retracted by IOP Publishing following an allegation that raises concerns this article may have been created, manipulated, and/or sold by a commercial entity. In addition, IOP Publishing has seen no evidence that reliable peer review was conducted on this article, despite the clear standards expected of and communicated to conference organisers. The authors of the article have been given opportunity to present evidence that they were the original and genuine creators of the work, however at the time of publication of this notice, IOP Publishing has not received any response. IOP Publishing has analysed the article and agrees there are enough indicators to cause serious doubts over the legitimacy of the work and agree this article should be retracted. The authors are encouraged to contact IOP Publishing Limited if they have any comments on this retraction. Retraction published: 16 September 2022
Retraction: The Influence of the Theory of Subject Description on American Modern Literature Based on Big Data Analysis (J. Phys.: Conf. Ser. 1744 032194)

This article has been retracted by IOP Publishing following an allegation that raises concerns this article may have been created, manipulated, and/or sold by a commercial entity. In addition, IOP Publishing has seen no evidence that reliable peer review was conducted on this article, despite the clear standards expected of and communicated to conference organisers. The authors of the article have been given opportunity to present evidence that they were the original and genuine creators of the work, however at the time of publication of this notice, IOP Publishing has not received any response. IOP Publishing has analysed the article and agrees there are enough indicators to cause serious doubts over the legitimacy of the work and agree this article should be retracted. The authors are encouraged to contact IOP Publishing Limited if they have any comments on this retraction. Retraction published: 16 September 2022
Retraction: Exploration of Multi-modal English and American Literature Teaching Based on Computer Network (J. Phys.: Conf. Ser. 1648 032036)

This article has been retracted by IOP Publishing following an allegation that raises concerns this article may have been created, manipulated, and/or sold by a commercial entity. In addition, IOP Publishing has seen no evidence that reliable peer review was conducted on this article, despite the clear standards expected of and communicated to conference organisers. The authors of the article have been given opportunity to present evidence that they were the original and genuine creators of the work, however at the time of publication of this notice, IOP Publishing has not received any response. IOP Publishing has analysed the article and agrees there are enough indicators to cause serious doubts over the legitimacy of the work and agree this article should be retracted. The authors are encouraged to contact IOP Publishing Limited if they have any comments on this retraction. Retraction published: 16 September 2022