Reviewerly/exHarmony huggingface dataset:
Research on the Impact of Information Security Certification and Concealment onFinancial Performance

With the rapid development of information technology, information security has been gaining attention. The International Organization for Standardization (ISO) has issued international standards and technical reports related to information security, which are gradually being adopted by enterprises. This study analyzes the relationship between information security certification (ISO 27001) and corporate financial performance using data from Chinese publicly listed companies. The study focusses on the impact of corporate decisions such as whether to obtain certification, how long to hold certification, and whether to publicize information regarding certification. The results show that there is a positive correlation between ISO 27001 and financial performance. Moreover, the positive impact of ISO 27001 on financial performance gradually increases with time. In addition, choosing not to publicize ISO 27001 certification can negatively affect enterprise performance.
BUILDING OF THE INTEGRATED DISTRIBUTED INFORMATION SYSTEMS SUPPORTING SCIENTIFICALLY-EDUCATIONAL ACTIVITY

The article is devoted to the development of the fundamental foundations of the technology of creating models, methods for building information systems integrated into the open semantic space to support scientific activities, consistent with international standards and trends in the development of both national and international information infrastructure. Information systems that support scientific research operate with various types of information.
Emotional Expression of Weibo Users in China during the COVID-19

Emotion, as an essential element in communication, is becoming increasingly important and influential in the era of social media. The expression of social media users also has more and more emotional characteristics. Based on the framework of emotional expression, this study encodes the collected 49 microblogs published by China’s official media accounts and their comments during COVID-19, and discusses the relationship between account types, text forms, discussion intensity and emotional expression tendency. It is found that account types and discussion intensity have a correlation with the emotional expression of Weibo users, while the correlation between text forms and emotional expression is not obvious. This study analyzes the emotional expression of social media and reflects on how to correctly understand the phenomenon of emotional expression and avoid the occurrence of “post-truth” events.
Discontinuous Time-domain Video Oriented Traffic Accident Reconstruction Technology under Virtual Projection Scene

Many media playback software may fail to account for frame timing can result in inaccurate or incomplete results, due to wide variety of proprietary digital video recording devices and file formats, especially in the discontinuous time-domain video(DT video), including, skipped or dropped frames, variable frame rates, etc. DT video is disrupted the reliability and accuracy of traffic accident data severely, making it urgent to study the traffic accident reconstruction Technology for DT video. In this paper, virtual projection scene (VPS) method is developed to reconstruct vehicle dynamic state and obtain accurate crash speed to avoid the unpredictable temporal span of DT video. Finally, a real traffic accident case is employed to illustrate the precision and reliability of VPS method.
A Novel Hybrid Model for PV Power Forecasting Using Support Vector Machine and Grasshopper Optimization Algorithm: Case Study

Photovoltaic (PV) installations have the potential to deliver significant economic and environmental advantages to electric networks. On the other side, when PV penetration rates rise, the unpredictability of the solar source presents a particular problem in grid management. In this respect, PV power forecasting is an important tool for managing uncertainty and ensuring system stability. In the current work, we present a novel hybrid model for intra-hour forecasting of PV power output. The proposed hybridization mechanism performs on training the Least Squares-Support Vector Machine (LS-SVM) model through Grasshopper optimization Algorithm (GOA) using PV power measured from 01-01-2016 to 31-12-2017 in half-hourly scale. GOA is developed for hyper-parameters tuning for the LS-SVM model for improving its forecasting performance. The forecasting performance of the proposed GOA-LS-SVM is evaluated and validated on a database of two years for one half-hour forecasting ahead. The proposed forecasting model benefit only from previous PV power output, in particular, the last eight PV power are used as input to the GOA -LA-SVM model. To demonstrate the effectiveness of the proposed model we test its forecasting ability against Extreme Learning Machine (ELM) for different sizes of training data. The proposed GOA -LS-SVM predicts PV power output with acceptable performance compared to the ELM model.
Media formats of post-drama theater

The article is devoted to the study of the question of the existence of post-dramatic performances in the modern media environment, in particular, the media formats of site-specific performances are studied. The purpose of this study is to identify the mechanisms of interactivity, performativity and immersiveness in the media formats of post-drama theater. The article raises the question regarding the meaning of the media format concept used in media studies in its connection with theatrical practices. The basic components of the concept of media format are the technical characteristics and focus on the target public. The chosen methodology allows us to characterize the technical capabilities of modern media formats for creating the effects of performativity, interactivity and immersiveness. The empirical basis of the research is the podcast The Theater of Everyday Life. Site-Specific Performances for Everyday Places and Routes in the mobile application Yandex Music and performances in the application Mobile Art Theater. The article draws conclusions concerning the influence of technical and verbal means of interaction used in mobile applications and in VR performances on the emergence of the effects of performativity and immersiveness in the minds of the audience. It is pointed out that the mechanics of the performances under consideration are connected with the concepts of A. Artaud and H.-T. Lehman, in particular, draw a conclusion about the role of the audience in such performances.
IMPLEMENTING REFLECTION AS AN INTERACTIVE METHOD IN FORMING COMMUNICATIVE SKILLS OF STUDENTS

This article examines reflection as one of the interactive methods, which in turn allows students and teachers to interact during class work, thereby developing their communication skills. A feature of the article is the description of communicative reflective methods, as well as the ways and methods of its implementation. The article describes the most common and effective communicative methods of reflection, which were used in the process of practical training in English lessons. The use of these methods has shown high results in the development of communication skills, as well as the impact on the interest and activity of students. The study was carried out in two stages by using a special expert commission, which assessed the results of students in the classroom without reflection and using reflection. The results of the study can serve as a theoretical basis for further research on the use of reflective methods to improve speaking in English lessons, and the development of communication skills.
Security

Establishing an API Marketplace can be like setting up an embassy for your organization in a foreign and hostile territory. Although your intention is noble and your aim is to help third-party providers leverage your products and services, it exposes the enterprise to a range of new attack vectors every day. The stakes are incredibly high when precious customer and other sensitive data are at risk. The mantra that everyone is responsible for ensuring the safety and integrity of the platform is not to be taken lightly. Any breaches across any of the API products could lead to negative public sentiment, impacting other products, the Marketplace, and the greater organization.
Edge Loss for Remote Sensing Image Super-Resolution

Remote sensing image super-resolution (SR) plays an essential role in many remote sensing applications. Recently, remote sensing image super-resolution methods based on deep learning have shown remarkable performance. However, directly utilizing the deep learning methods becomes helpless to recover the remote sensing images with a large number of complex objectives or scene. So we propose an edge-based dense connection generative adversarial network (SREDGAN), which minimizes the edge differences between the generated image and its corresponding ground truth. Experimental results on NWPU-VHR-10 and UCAS-AOD datasets demonstrate that our method improves 1.92 and 0.045 in PSNR and SSIM compared with SRGAN, respectively.
Multi‐label based view learning for vehicle re‐identification

Due to the high similarity of different vehicles with similar appearances and the great diversity of camera viewpoints, vehicle re-identification (ReID) is still a challenging task. It commonly maps query set image into a high dimensional embedding space and then retrieve gallery vehicle images according to the distance. In this letter, a multi-label based view learning (MLVL) model to enhance the distinguishability of intra-class and inter-class through multiple labels learning, and decrease the distance of intra-class features caused by multi-view appearances of vehicles. Specifically, the model includes two main parts. First, the vehicle orientation estimation module is responsible for detecting key-points of the vehicle and predicting its orientation, which provides the orientation label for the multi-label based learning network to enhance view-invariant representation. Second, a novel dual-triplet and quadruplet loss function is designed to optimise intra-class and inter-class distance with the help of multi-label information, i.e. vehicle colour, type and orientation. In particular, a multi-label based sampler is proposed to generate training mini-batches instead of random sampler. Extensive experiments results show that the proposed MLVL model achieves 5.6 % $\%$ mAP improvement on VeRi-776 and 1.9 % $\%$ on VERI-Wild datasets compared with baseline model.
Characteristics of Phishing Websites

A web page is a document created with Hypertext Markup Language (HTML) and Cascading Style Sheets (CSS) that is displayed in a web browser. The address bar of a browser specifies the URL of the website. A website is a single domain name that consists of a collection of interlinked web pages. The characteristics of a phishing website were examined in this chapter. A web page is made up of three parts: HTML, CSS, and JavaScript. Attackers use these sections of code to carry out a wide range of phishing schemes.
Impact of Tropical Convective conditions on Solar Irradiance Forecasting based on Cloud Motion Vectors

&amp;lt;p&amp;gt;Cloud Motion Vector (CMV) estimation from consecutive satellite images is widely used commercially for providing hours-ahead intraday forecasts of solar irradiance and PV power production. The modelling assumptions in these methods are generally satisfied for advective motion which is common in mid-latitudes, but strained for tropical meteorological conditions dominated by convective clouds. The region under analysis in this study encompasses both tropical and sub-tropical climatic zones and is affected by seasonal strong convection, i.e., the South Asian Monsoon.&amp;lt;/p&amp;gt; &amp;lt;p&amp;gt;The purpose of this study is to benchmark the monthly forecast error of three commonly used CMV estimation techniques - Block-match, Farneb&amp;amp;#228;ck (Optical flow) and TV-L&amp;lt;sup&amp;gt;1&amp;lt;/sup&amp;gt; (Optical flow), for analysing their performance on a seasonal basis. The main focus of this work is the analysis of the limitations of image processing based Block-match and Optical flow techniques in predicting irradiance during the Monsoon period, which presents frequent convective formation and dissipation.&amp;lt;/p&amp;gt; &amp;lt;p&amp;gt;Forecasted Cloud Index (CI) maps are validated against reference analysis CI maps for the period 2018-2019 for forecast lead times from 0 to 5.5 hours ahead using the Peak Signal to Noise Ratio (PSNR) metric for estimating the accuracy. Persistence of analysis cloud index maps are used as the reference worst case scenario forecast. Site-level forecasts of irradiance for the same period are validated against ground measured irradiance from two BSRN stations - Gurgaon and Tiruvallur, located in Northern and Southern India respectively.&amp;lt;/p&amp;gt; &amp;lt;p&amp;gt;From the Winter period in March to the Monsoon period in August, there is a marked reduction of the 30 minutes ahead forecast accuracy by 3 dB in terms of Peak Signal to Noise Ratio at the image-wide level. This can be observed for all the three methods and the worst-case persistence scenario. Both optical flow methods outperform Block-match by 0.5 dB for the entire period of analysis. The Gurgaon BSRN site is affected by Summer Monsoon and shows an increase in nRMSE by a factor of 3 for all the methods. This station shows a seasonal pattern of forecast error closely matching the image-wide forecast accuracy. The forecast error for the Tiruvallur BSRN station on the other hand reaches its peak in December (Data for October and November are absent), due to its location in the Winter Monsoon climatic zone. Again, the nRMSE for all methods increase by a factor of almost 3 from March to December. The inter-method difference in accuracy is not significant and a seasonal difference (20% nRMSE) dominates. This highlights the shortcomings of image processing techniques in extrapolating future cloud locations under convective situations, where there is rapid change in cloud content between consecutive images.&amp;lt;/p&amp;gt;
A Generalization of Possibilistic Fuzzy C-Means Method for Statistical Clustering of Data

The Fuzzy C-means (FCM) algorithm has been widely used in the field of clustering and classification but has encountered difficulties with noisy data and outliers. Other versions of algorithms related to possibilistic theory have given good results, such as Fuzzy C- Means(FCM), possibilistic C-means (PCM), Fuzzy possibilistic C-means (FPCM) and possibilistic fuzzy C- Means algorithm (PFCM).This last algorithm works effectively in some environments but encountered more shortcomings with noisy databases. To solve this problem, we propose in this manuscript, a new algorithm named Improved Possibilistic Fuzzy C-Means (ImPFCM) by combining the PFCM algorithm with a very powerful statistical method. The properties of this new ImPFCM algorithm show that it is not only applicable on clusters of spherical shapes, but also on clusters of different sizes and densities. The results of the comparative study with very recent algorithms indicate the performance and the superiority of the proposed approach to easily group the datasets in a large-dimensional space and to use not only the Euclidean distance but more sophisticated standards norms, capable to deal with much more complicated problems. On the other hand, we have demonstrated that the ImPFCM algorithm is also capable of detecting the cluster center with high accuracy and performing satisfactorily in multiple environments with noisy data and outliers.
Role of Big Data Analytics in the Financial Service Sector

This paper attempt to be aware of that the big data revolution occurrence in and around the 21st century has found a significance with banking firms, taking into deliberation the valuable data they’ve been storing for several decades. To identify with the various scenarios in big data in banking, financial services, and insurance areas, where these analytics is turning out to be paramount and also highlights the possible benefits, of the new-age technologies. The fourth industrial revolution marks the next stage in this movement, and driving organizations have just started to adjust their business approach for the digital age. Still follow a line of investigation is going on in Big Data which the finance sector has attaining its peak stage in each and every second. In this point of view, this study will be important for financial data management to address technological challenge in order to understand the promised benefits of Big Data.
Data sparsity for twitter sentiment analysis in real-time from biased and noisy data

Specializing in the analysis of strong emotions expressed in text, sentiment analysis is a scientific field. You may convey your thoughts and feelings about anything by expressing your opinion about it. This work explains the origins of sentiment analysis and how to configure sentiment evaluators. This paper showed comprehensive assessment of emotions will still be required. Analysis includes non-textual material. The use of visual media in social research is also useful. Without a doubt, I see the value of these links. This research uses a domain-specific seed list to categorize tweets. As much information as possible is preserved during tweet categorization. The algorithm categorizes tweets precisely and sentimentally to build a user interest profile. To test the method, 1 million tweets were used and up to 96% of them were correctly classified.
Assessment of Gold Mining Impact on the Vegetation of Itagunmodi-Igun Drainage Basin, Southwestern Nigeria from 1972–2011: A Remote Sensing

Abstract. A GIS-based Normalized Differential Vegetation Index (NDVI) was analyzed using space-based data between 1972 and 2011 as Input data. The result of the NDVI using Landsat 7 ETM+ shows clearly that the values range from 0.19 to −0.31. Mountains and highlands of the Itagunmodi-Igun area revealed stressed vegetation cover between 0.11 to −0.31. The NDVI was also performed on Landsat imageries of four different epoch: 1972, 1986, 2000, and 2010. Results showed that vegetation index ranged from −0.105 to 0.033, −0.25 to 0.480, −0.313 to 0.19 and −0.29 to 0.5 in 1972, 1986, 2000 and 2010 respectively. The analysis revealed that the study area experienced an increase in biomass between 1972 and 1986 but with some areas experiencing outright disappearance of vegetation as indicated by the lower bands of index values in 1972 (−0.105) and 1986 (−0.25). The result showed that the Basin experienced a rapid and significant increase in biomass between 2000 and 2010, as indicated by the lower bands of index values in 2000 (−0.291) and 2010 (0.5). The results of the NDVI in 1972 ranged from −0.105 to 0.033 while NDVI in 1986 ranged from −0.25 to 0.480 which indicated a significant increase in the vegetation index. The results of the NDVI in 2000 ranged from 0.291 to 0.5 also indicated a significant increase in the vegetation index. The study concluded that artisanal mining could cause land and vegetation degradation with consequent loss of biodiversity, ecological modification.
Bibliometric study of Research done in Modern European Languages Available in ETD – Shodhganga

Join us for ETD2021 (Electronic Theses and Dissertations) Conference in November 2021 in the United Arab Emirates. Our theme, ‘Open scholarship in a post-pandemic world’ addresses the enhanced need for discoverability of research findings in a virtual world. Since the global impact of the COVID-19 pandemic has constrained international travel and mobility, we have all come to rely on working in the virtual world. These developments have merely accelerated the existing trends towards more electronic and digital repositories. Since 1991, the Networked Digital Libraries of Theses and Dissertations (NDLTD) have contributed to research collaboration by identifying and aggregating digital repositories of theses and dissertations as a previously fugitive class of research resources.
Principles and patterns of formation of skills of economic safe behavior in schoolchildren

The article discusses the features of the formation of skills of economically safe behavior based on the study of basic concepts of financial literacy.
The influence of poetic and musical rhythm on the perception and comprehension of an educational text by an Ancient Greek student

The article presents the results of the historical and psychological reconstruction of educational reading in an Ancient Greek school. The purpose of this reconstruction was to identify the psychological mechanisms of influence of the musical and poetic rhythm on the student's personality, to determine the pedagogic potential of the poetic text as a means of raising, to reveal the psychological mechanisms of the activity of the text as a subject of educational reading. The educational effects of the rhythm of the mythological and poetic text in the context of the formation of the socio-cultural identity of an Ancient Greek student are revealed. The psychological mechanisms of the participation of poetic and musical rhythm in the organisation of the practice of reading in an Ancient Greek school are described. It is noted that the poetic rhythm of the text suggests a special way of participating in the teacher's educational reading. Based on the reconstruction, it is concluded that the rhythmically intense educational mythological and poetic text has the ability to evoke an emotional response in the student, influence his unconscious attitudes, and impose emotional and semantic dominants of perception and understanding of what is written. The most important task of modern education is found in the formation of student's sense of rhythm in the process of educational reading. It is noted that this sense of rhythm in a modern school can be formed by referring to educational texts and texts used in youth culture.
Study of the Preprocessing of Venous Images

Due to the design of intravenous imaging instruments and the rapid development of venipuncture robots, it is of great significe to study the high-quality venous image processing method. In this paper, a series of preprocessing of the venous image is carried out, and the development of venous image processing is briefly introduced. The process of vein image processing is mainly divided into three steps. The first step is to use the improved Otsu method for binarization. The second step is to use the selective median filter algorithm to filter. The third step is to refine the image with a fast parallel thinning algorithm. Experimental results show that the vein image processing effect is better.
INFORMATION SYSTEM DESIGN FOR FINAL PROJECT CONSULTATION

This Final Project is one of the graduation requirements for Industrial Engineering students at the Islamic University of Bandung. Currently. The final project consultation process is conducted manually using physical documents owned by each student as proof of consultation in the form of a consultation card. The problem faced was the difficulty in monitoring consultations and recording consultation discussions which were not well organized. The purpose of this study is to design a consulting information system using the prototyping method. The prototyping method is a system development method used to describe the system. The stages in this method consist of: (1) The planning stage is the identification of system requests. (2) the analysis phase analyzes the existing business processes in the final project section and identifies functional and non-functional requirements, (3) the design phase includes the interaction design of systems, processes, data and logical systems and physical interfaces. (4) Implementation phase of database and website development using PHP language and MySQL database. The results obtained from this study are business process consulting for the Final Project after the implementation of the proposed information system; final project consulting information system design which is expected to facilitate the consultation process in terms of time and consultation file documentation