Reviewerly/exHarmony huggingface dataset:
A keyword extraction method for Chinese professional field text based on improved RAKE

An improved RAKE (Rapid Automatic Keyword Extraction) algorithm is proposed to solve the problems of phrase conglutination and inability to obtain professional words in the process of extracting keywords from Chinese professional texts. Through the TTF-IDF (Total Term Frequency-Inverse Document Frequency) method, professional field stop words are extracted and added to the general stop word dictionary for phrase segmentation. Professional domain entity words are introduced into the general word segmentation dictionary, and appropriate weight is given to them in the degree calculation to ensure that professional entity words get higher scores and are effectively extracted as keywords, because in professional field texts, professional entity words contain more core information. The experiments show that this algorithm is better than the basic RAKE and other algorithms in keyword extraction for Chinese professional field texts.
CURRENT ISSUES OF LEGAL REGULATION OF PUBLIC DISCUSSIONS IN UZBEKISTAN

The article studies the problems of ensuring the openness and publicity of public discussions, taking into account the proposals and opinions of their participants and other issues of legal regulation of this area. In the study, legislative acts and practices of their application, foreign practice and scientific views in this area were studied, and sociological surveys were conducted. The author investigated the practice of holding public discussions by non-governmental organizations, citizens’ self-government bodies and the media, as well as state bodies, and sought to clarify the concept of “public discussions”. The article proves that the nationwide discussion of bills is a kind of public discussion, and the effectiveness of using online technologies in this process. The regularity of public discussion of draft legal acts in the study is associated with a detailed regulation of this process. With this in mind, recommendations were developed on the legal regulation of public discussions on other issues of social importance. Based on the results of the study, the author put forward practical proposals for the development of general rules for conducting public discussions, including the provision by state bodies of replies to the proposals of the participants in the discussion.
ReEDNet-An Encoder–Decoder Framework for Single Image Dehazing

Single image dehazing based on deep learning techniques has made significant progress. Most existing approaches retrieve haze-free images by estimating the transmission map and global atmospheric light, which are difficult to compute. In this paper, an encoder–decoder-based deep network ReEDNet is designed for single image dehazing. Further, a Cross Feature Aggregation (CrFeAt) block is introduced that utilizes skip connections to preserve the spatial feature to the last layer. ReEDNet is a light network that can be deployed in a resource-constrained environment. A quantitative analysis of the proposed network is performed on the RESIDE dataset. Extensive experiments show that the proposed ReEDNet achieves better performance compared to the state-of-the-art approaches.
The Ticket Price Matters in Sharding Blockchain

Sharding technology has been recognized to be a promising solution for blockchain scalability problems in recent years. For safety guarantees in each shard, mainly to prevent the single-shard takeover attack, sharding requires an identity establishment protocol in which participants have to pay a certain amount of resources (i.e., ticket price) to get a node and participate in the network. However, state-of-the-art sharding protocols overlook a non-democratic state of the real-world where every participant has a different amount of resources, termed a non-democratic environment. This oversight raises combined problems of security and scalability due to the design of the identity establishment protocol. In this paper, we examine the effects of the non-democracy of blockchain networks in terms of the security and scalability of blockchain sharding and suggest formulae to quantitatively analyze the trade-off between security and scalability. Moreover, we conduct a numerical analysis by capturing four real-world resource distributions from renowned permissionless cryptocurrency networks. We re-evaluate the well-known sharding protocols through this numerical analysis and present the changed fault tolerance bounds and damage to scalability. The results show that the ticket price plays a leading role in tuning the effect of non-democracy. The main contribution of this paper is the proposal of new metrics for accessing the degree of security and scalability with regard to the ticket price in the identity establishment phase. Our discussion suggests further research on a more delicate ticket price control algorithm when designing a new sharding model for blockchain.
Privacy-Preserving Link Prediction

Consider two data holders, ABC and XYZ, with graph data (e.g., social networks, e-commerce, telecommunication, and bio-informatics). ABC can see that node A is linked to node B, and XYZ can see node B is linked to node C. Node B is the common neighbour of A and C but neither network can discover this fact on their own. In this paper, we provide a two party computation that ABC and XYZ can run to discover the common neighbours in the union of their graph data, however neither party has to reveal their plaintext graph to the other. Based on private set intersection, we implement our solution, provide measurements, and quantify partial leaks of privacy. We also propose a heavyweight solution that leaks zero information based on additively homomorphic encryption.
An Edge Based Framework for Risk Assessment of Communicable Disease

Along with the development of edge computing and Artificial Intelligence (AI), there has been an explosion of health-care system. As COVID-19 spread globally, the pandemic created significant challenges for the global health system. Therefore, we proposed an edge-based framework for risk assessment of communicable disease called CDM-FL. The CDM-FL consists of two modules, the common data model (CDM) and federated learning (FL). The CDM can process and store multi-source heterogeneous data with standardized semantics and schema. This provides more data for model training using medical data globally. The model is deployed on edge nodes that can measure patients' status locally and with low latency. It also keeps patient privacy from being disclosed that patient are more likely to share their medical data. The results based on real-world data show that CDM-FL can help physicians to evaluate the risk of communicable disease as well as save lives during severe epidemic situations.
Maritime video ship detection and tracking based on improved YOLOX and DeepSORT

Object detection and tracking in maritime videos are crucial for marine management today. Nevertheless, due to the small size of ships in maritime video, current state-of-the-art algorithms are incapable of producing satisfactory results. We design an improved YOLOX (iYOLOX) and DeepSORT-based method to detect and track small objects in maritime videos to improve detection accuracy. Initially, the primary feature extraction capability of YOLOX’s backbone network is improved by adding the convolutional block attention mechanism. Second, we employ the context enhancement module to enlarge the receptive field while preserving the specific features. Finally, a parallel deformable convolution bifusion feature pyramid network is utilized for bidirectional feature extraction for small objects. iYOLOX is additionally combined with the DeepSORT algorithm to track targets. The experimental results show iYOLOX performed better when compared with the original YOLOX such that iYOLOX improves 3% average precision (AP) on the COCO2017 dataset, 4.7% APs for small-size objects, and 3.41% AP50 on the LMD-TShip maritime video dataset. Furthermore, it indicates that the proposed algorithm effectively alleviates some object occlusion and camera shaking issues and improves the model’s utility and robustness.
ANALYSIS OF THE EXPERIENCE OF CREATING GLOBAL DIGITAL GOODS MARKETS BASED ON OUR OWN PLATFORMS

The presented work summarizes the arguments and counter-arguments within the scientific discussion on analyzing world experience in creating digital goods markets based on its platforms. Pricing policy on the Internet has many nuances, particularly geographic location, dynamic pricing, and price discrimination depending on belonging to a specific social category. The main goal of the conducted research is to identify the main directions of influence on the price policy, which are relevant for the digital goods market, particularly in the gaming industry. The systematization of literary sources and approaches to solving the problem of analyzing the peculiarities of conducting the pricing policy of digital goods proved that this problem is quite relevant among scientists worldwide and needs further elaboration. The research was carried out in the following logical sequence: 1) analysis of literary sources and popular methods of price discrimination; 2) consideration of the concept of a game platform as the basis of the distribution of power between various market subjects; 3) comparison of activities of popular gaming platforms; 4) consideration of game products as certain economic microsystems, and "skins" as currency in these systems; 5) analyzing specific games that use atypical methods of earning profit as for the non-digital world; 6) consideration of tools for expanding markets to a vast network using the example of web API interfaces. The global digital goods market was chosen as the object of the study. The research paper presents the results of a theoretical analysis of pricing strategies for the gaming industry as one of the essential branches of the digital sector. The digital services market began to form relatively recently, based on the stock market's pricing principles. However, everything related to digitalization is developing more rapidly, so the time has come when you can adopt various existing practices of the digital services market for the physical market, namely the use of digital platforms, differentiated pricing policies, the use of additional market research tools such as Telegram bots, online stores, applications, etc.
THE POSSIBILITY OF DEVELOPING AN E-LEARNING PLATFORM USING CLOUD ERP SOFTWARE: A CASE STUDY ON ODOO

E-Learning portals are large data warehouses that allow the interconnection of various types of activities in order to automate and streamline of the decision-making process. Distributed learning allows the realization of an educational process of the best quality, based on a modern education and a very high perspective, customized according to the increasingly demanding and complex individual needs. In the paper we studied the possibility of using the Odoo ERP program, implemented in the Cloud environment for the development of an e-learning platform. For a company that offers paid qualification courses, we have implemented the whole e-learning process, starting from the moment a student enrolls in a certain course and until the issuance of the participation certificate. All activities are carried out automatically, via email. The payment of the courses can be done with the card or bank transfer and is automatically registered in the accounting, the invoice being issued automatically, reaching to the recipient by email. Technology has changed the way we live our lives, the way we communicate and the way we learn. The continuous evolution of technology allows humanity to communicate and learn in a virtual environment similar to that of real world interaction. These changes at the educational level, where eLearning is becoming more dynamic and socially interactive, there are still some weaknesses regarding the successful implementation of these platforms among educational institutions. Schools with a traditional education system find it difficult to adapt or embrace these much-needed changes without resisting the new trends and preferences of society. There is a growing trend for educational institutions to successfully implement eLearning efficiently.
Secure Consistency of COMS/MI and GK-2A/AMI Shortwave Radiation product based on machine learning

&amp;#160;Satellite-based solar radiation data is widely used to monitor global climate and environmental changes and is also actively used to analyze weather data and predict particulate matter. Korea can continuously retrieval solar radiation in the observation area due to the generational shift of COMS (Communication, Ocean and Meteorological Satellite)/MI (Meteorological Imager sensor) and GK-2A (GEO-KOMPSAT-2A)/AMI(Advanced Meteorological Imager sensor). However, The quality of each solar radiation output is different due to difference between the algorithms, input data and resolution. Therefore, it is possible to produce a climate resource map for the Korean Peninsula for continuous climate change monitoring by analyzing the error characteristics between the solar radiation of COMS/MI and GK-2A/AMI and expanding the retrieval period through correction between the two products. In this study. We analyzed the error characteristics of the two satellites compare to the meteorological observation data of Korea and the satellite CERES solar radiation data in overlapping periods. As a result of error analysis, the RMSE of COMS/MI was 85.6 (W/m2), lower than the RMSE of GK-2A/AMI, 95.6 (W/m2). Considering the solar radiation data error characteristics of these satellites, a correction model based on machine learning techniques was created to secure the consistency of solar radiation data. When this was verified with in situ data for a period of 10 years, RMSE was 89.21 (W/m2) and Bias was 17.39 (W/m2), which was stable in the temporal consistency test, and the annual increase in solar radiation on the Korean Peninsula was confirmed.&amp;#160;&amp;#8251; This work was supported by the "Graduate school of Particulate matter specialization." of Korea Environmental Industry &amp; Technology Institute grant funded by the Ministry of Environment, Republic of Korea.
For-profit versus non-profit cybersecurity posture: breach types and locations in healthcare organisations

Background The implementation of emerging technologies has resulted in an increase of data breaches in healthcare organisations, especially during the COVID-19 pandemic. Health information and cybersecurity managers need to understand if, and to what extent, breach types and locations are associated with their organisation’s business type. Objective To investigate if breach type and breach location are associated with business type, and if so, investigate how these factors affect information systems and protected health information in for-profit versus non-profit organisations. Method The quantitative study was performed using chi-square tests for association and post-hoc comparison of column proportions analysis on an archival data set of reported healthcare data breaches from 2020 to 2022. Data from the Department of Health and Human Services website was retrieved and each organisation classified as for-profit or non-profit. Results For-profit organisations experienced a significantly higher number of breaches due to theft, and non-profit organisations experienced a significantly higher number of breaches due to unauthorised access. Furthermore, the number of breaches that occurred on laptops and paper/films was significantly higher in for-profit organisations. Conclusion While the threat level of hacking techniques is the same in for-profit and non-profit organisations, certain breach types are more likely to occur within specific breach locations based on the organisation’s business type. To protect the privacy and security of medical information, health information and cybersecurity managers need to align with industry-leading frameworks and controls to prevent specific breach types that occur in specific locations within their environments.
Benefits of Life-Long Education

The influence of life-ling education on person’s cognitive functioning is considered in the article. Flexibility of cognitive control was used as a marker for cognitive integrity. 116 respondents aged 56-84 participated in the research. Participants have being learning from 8 to 36 years in their lives. Some of them have even four different educations. Statistically significant correlation between indices of cognitive flexibility and years of education has been obtained in the research. The conclusion that formal education with considerable years of education promotes cognitive well-being has been drawn. Life-long education makes it easy to adapt to challenges of modern world. It allows us to save mind’s clarity and flexibility thus ensuring successful aging and cognitive integrity.
Image Super-Resolution Reconstruction Based on Residual Convolution and Double Attention Mechanism

Currently, single-image super-resolution reconstruction based on deep learning has achieved good results. To address the problems that most networks will have long training time, weak image learning ability and not fully utilizing the high frequency information of images, an image super-resolution reconstruction method based on residual convolution and double attention mechanism is proposed. The model performs deep feature extraction of the image by cascading deep convolutional networks, introduces local residual blocks to solve the model degradation brought by too many network parameters, and embeds the dual attention mechanism module in the residual blocks for adaptive calibration to adjust the feature map weights of each channel and the spatial correlation between features, so as to obtain deep texture detail information and reconstruct the feature image by sub-pixel convolutional layers to up sampling to reconstruct the high-resolution image. In the test sets of Set5 and Set14, peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) are used as evaluation indexes, while comparing SRCNN, FSRCNN and VDSR methods all reconstructed images with better results. The experimental results show that the method can effectively improve the utilization of high-frequency feature information and can increase the reconstruction capability of the images to a certain extent.
EXPLORING THE EFFECTS OF TIKTOK ON THE ACADEMIC PERFORMANCE OF SARGODHA UNIVERSITY STUDENTS AT GRADUATE LEVEL

TikTok is a very popular application, introduced by China in September 2016.A good update formed by the company in 2018 is that they add music in TikTok application which became the reason of popularity among the youth all over the world. It is very easy to use application; you can easily use it in your mobile which is the most common reason of its popularity. TikTok is a very use full application but it is not being used in a positive way in our country. In regarding to this we did research and find out the impact of this app on the academic performance of Sargodha university at graduate level and the to which extent our youth is addicted with this application. It will also find out are they using this application in a positive way or not. In this regard, we did a survey form which has been filled by approximately 201 media Undergraduate students.
Using Video – Based Ebook in Teaching Writing for the Enhancement of Grammatical Competence among ESL Learners

The study generally focused on enhancing the grammatical competence of learners using video-based eBooks. Using a pre-experimental research design, the study assessed the pre-test, and post-test scores of the respondents and their significant difference using paired t-tests. Furthermore, the respondents’ assessment of the video-based eBook was analyzed using mean and standard deviation, while pearson r was used to test the correlation between the respondents’ assessment and their grammatical competence. The respondents were composed of 41 grade 10 students who were enrolled in modular distance learning. Results revealed that before the utilization of the video-based eBook, the majority of the students have very low and low grammatical competence. In contrast, the students’ grammatical competence improved to a high level, as indicated in the post-test results. Moreover, most of the respondents strongly agreed with the video-based eBook’s content, instructional, and technical quality indicators. The null hypothesis, which claims no significant difference between students’ grammatical proficiency before and after the test, is not sustained. Lastly, the findings supported the null hypothesis that no significant relationship exists between the assessed video-based eBook and the respondents’ grammatical competence. Based on the study’s findings and conclusions, the researcher suggested that the school and teachers consider using the video-based eBook as an e-module since it helps improve the grammar skills of the learners. Keywords: grammatical competence, video-based ebook
The world market of digital educational editions: Development prospects

The article discusses the changes in the educational publications market under the influence of digital transformation. Expansion of the diversity of digital devices, changes in the needs of the target audience, and the development of new educational practices contribute to the emergence and growth of new niches in the global market of educational publications. The study of the market of digital educational products in different countries shows that many factors influence the level of its development. These factors are the government policy, the level of IT technology in the country, and the competitive environment in this niche in the market of a particular country. Moreover, the quality of the competitive environment and the interest of technology companies have a greater impact than the government policy. Two strategies for the production of electronic educational products in the modern world market stand out and are illustrated by examples: publishing isolationism and production tandems with technology companies. A classification of three models of electronic textbooks is proposed based on the analysis of educational publications in the natural sciences representing countries with emerging markets for electronic textbooks: the United States, Russia, and Finland. The first model is the presentation of electronic textbooks in PDF format. Textbooks in this version are the original mockup of a printed textbook. The second model is based on the printed form of the textbook, distributed in EPUB 3 format through the publisher’s own publishing software or affiliate applications. Multimedia and interactive materials in such textbooks are not mandatory, but complementary, and they are included in the textbook via pop-ups. The third model is a publication that was originally created only in electronic format. Often, such textbooks are components of a digital educational environment that provides electronic exchange of tasks, collective performance of laboratory works, interdisciplinary connection of educational material in various disciplines, etc. The study of the most relevant and innovative offers on the market of such countries as the USA, the UK, Spain, Denmark, Russia, and Finland shows four promising areas in the preparation of textbooks in the EdTech field. These are (1) artificial intelligence manuals, (2) tools of virtual, augmented, and mixed reality, (3) computer games with educational potential, and (4) programming platforms. Contribution of the authors: the authors contributed equally to this article. The authors declare no conflicts of interests.