Reviewerly/exHarmony huggingface dataset:
An Improved Adaptive Background Mixture Model for Realtime Tracking with Lightning Detection

Typical models of lightning detection are based on the acoustic, optical, and electromagnetic field properties of lightning, All of these lightning detection models require specialized instrumentation to implement. The image-based lightning detection model is more generalizable and scalable than traditional lightning detection models. The image-based lightning detection model just by Camera captures pictures to detect lightning. The images in a video can be divided into foreground and background, and lightning can be understood as the foreground of the video. The lightning images are separated from the video by judging the lightning foreground in the video with time index positioning. In order to quickly identify lightning from video, it is necessary to analyze lightning in terms of its physical properties and its digital image properties. Through the connection between physical properties and image properties, we propose the Adaptive Lightning detection for the task of background subtraction (ALD) algorithm by combining the properties of Background subtraction method and Mixture Gaussian method and adding Gaussian filter to remove noise. We used this method to analyze a total of ten hours of lightning video and compared it with the previously proposed algorithms.
New blog from the colleagues

The colleagues from the other side of the library also started blogging, but more of the book- and collection related library topics. For hosting the blog, the platform hypotheses.org was chosen. Hypotheses.org mainly focuses on academic content. Check it out at https://sub.hypotheses.org/ or subscribe to the RSS Feed.
WebP

I tried to improve the downlad-time and size of the assets used in this blog. This is mainly about optimizing the images for web. Not only that all JavaScript from this site has been removed previously, the images were a huge factor in the traffic of this page.. The images used in this blog are of different types. We use PNG, JPEG and SVG. Some of these files are huge and not optimized for web use. When I noticed that, I had a quick look at the size of our home page. It was about 2.5 Megabye,...
MICROCREDENTIALS: KNOWLEDGE, TIME, CONVENIENCE

In the modern world, along with the requirements of the labor market, employers and students, the need for flexible and inclusive learning paths is growing. The article presents information about microcredentials, which is a relatively new phenomenon for higher education and the labor market in general.Examples are given of how micro-credentials are implemented at universities, educational platforms and global companies.
UPDATED EDUCATIONAL PROGRAM - THE NEED OF THE TIME

The updated content of education is being introduced in accordance with the requirements of society for the modern education system. In accordance with this, changes are being made to the content of the educational program, a revision of the very model of secondary education, its structure, approaches and methods of teaching and education, the introduction of a fundamentally new system for assessing student achievement, increasing competitiveness, and functional literacy. The article discusses the problems faced by teachers and students themselves, suggests ways to solve these problems and recommendations for the implementation of this program.
APPLICATION OF EUROPEAN STANDARDS FOR EXTERNAL QUALITY ASSURANCE IN A STRUCTURAL CONTEXT (ON THE EXAMPLE OF THE KAZAKH NATIONAL ACADEMY OF CHOREOGRAPHY)

The article describes the context of external quality assessment of education in which the accreditation procedure of the Kazakh National Academy of Choreography, which is a multi-leveled educational institution, was conducted. An attempt was made to describe the structural application of widely known standards and recommendations for quality assurance in higher education (ESG) in assessing the quality of the multi-leveled educational process
ORGANIZATION OF CAREER GUIDANCE ACTIVITIES AT THE UNIVERSITY

This article describes the methods of organizing career guidance activities at the university. Setting goals and objectives, planning, organizing the main activities for effective career guidance at the university.
FEATURES OF THE IMPLEMENTATION OF RESEARCH WORK OF STUDENTS IN UNIVERSITIES OF THE REPUBLIC OF KAZAKHSTAN

The article describes the results of the study related to obtaining information on improving the state of research work of students in universities of the Republic of Kazakhstan. Priority patterns obtained as a result of a survey of students over a number of years are highlighted. Hypothetical assumptions are put forward and their preliminary justifications are described. Recommendations on improving the functioning and effectiveness of research work in universities of the Republic of Kazakhstan are proposed.
Darkmode in CSS

You may know the dark mode from your mobile phone or elsewhere. It’s basically a theme that can be activated, but also can be a system-wide default. Most browsers do also support this setting - and we as web developers can read these preferences (Firefox) and use media queries to apply a dark theme for our website. Note that this is not togglable, as some JavaScript solutions offer this feature, but only reacting to the browser preference. By the way - I removed all JavaScript from this blog....
Spam-Protect a Symfony5 Contact-Form with CAPTCHA

On many of our Websites we have contact forms. And recently there seems to be an elevated number of bots filling out these forms with spam data. That’s especially a problem, when a contact form is directly connected to an Issue Tracker, that automatically generates an issue when a mail to a specified address arrives. A possible solution for avoiding automated form-fills is using CAPTCHAs. So, as our Symfony Websites are using contact forms built with the form builder, and I was looking for a...
The Role of Human Resources Competence, Internal Control System, And Financial Accountability in Enhancing Organizational Performance: The Moderator Role of Human Resource Managers

This study examines the role of internal control systems, human resource competencies, and financial accountability in organizational performance as viewed by human resource managers. The research was carried out in Jordanian business organizations. The sample included executives from 130 companies listed on the Amman Stock Exchange. A questionnaire was created and distributed to collect data, which was then analyzed using SPSS version 25. According to the study, financial accountability, internal control systems, and human resource competencies all contribute to the improvement and enhancement of organizational performance, and human resource managers play an important role in this. According to the study, organizations should strive to include such components at all levels to achieve effectiveness and gain a competitive advantage.
THE RELEVANCE OF THE DEVELOPMENT OF THE EDUCATIONAL PROGRAM «ASSESSMENT» IN THE MODERN ECONOMY OF KAZAKHSTAN

The article considers the relevance of the profession «appraiser». The necessity of qualified specialists in the field of evaluation activity is substantiated. Attention is paid to the process of training appraisers and the main objectives of the implementation of the educational program «Evaluation» at the Karaganda University of Kazpotrebsoyuz. The analysis of the sufficiency of professional appraisers at the present stage of economic development of our country is carried out.
Using Natural Language Processing and Machine Learning to Identify Opioids in Electronic Health Record Data

This study evaluates the utility of machine learning (ML) and natural language processing (NLP) in the processing and initial analysis of data within the electronic health record (EHR). We present and evaluate a method to classify medication names as either opioids or non-opioids using ML and NLP.A total of 4216 distinct medication entries were obtained from the EHR and were initially labeled by human reviewers as opioid or non-opioid medications. An approach incorporating bag-of-words NLP and supervised ML classification was implemented in MATLAB and used to automatically classify medications. The automated method was trained on 60% of the input data, evaluated on the remaining 40%, and compared to manual classification results.A total of 3991 medication strings were classified as non-opioid medications (94.7%), and 225 were classified as opioid medications by the human reviewers (5.3%). The algorithm achieved a 99.6% accuracy, 97.8% sensitivity, 94.6% positive predictive value, F1 value of 0.96, and a receiver operating characteristic (ROC) curve with 0.998 area under the curve (AUC). A secondary analysis indicated that approximately 15-20 opioids (and 80-100 non-opioids) were needed to achieve accuracy, sensitivity, and AUC values of above 90-95%.The automated approach achieved excellent performance in classifying opioids or non-opioids, even with a practical number of human reviewed training examples. This will allow a significant reduction in manual chart review and improve data structuring for retrospective analyses in pain studies. The approach may also be adapted to further analysis and predictive analytics of EHR and other "big data" studies.
DEVLOPMENT OF ROBOTICS,MAZE SOLVING ROBOT AND APPLICATIONS

Robotics and artificial intelligence are two of the computer science topics that are expanding quickly. Robotics focuses on creating machines that can independently sense their surroundings and communicate with one another in the physical world, whereas artificial intelligence (AI) focuses on creating machines that reason similarly to humans.The primary focus of robotics is on designing systems that would affect human social life. The self-monitoring robots can follow instructions and execute complicated maze-solving algorithms on their CPU cores. This paper provides an overview of robots and their practical applications.
Association Rule

Businesses are increasingly seeking to understand consumer behavior and purchasing habits in order to analyze the relationship between different products purchased by customers. By leveraging the association rule mining technique, businesses can identify complementary products and bundle them together to increase sales. This chapter provides an overview of association rule mining, a form of unsupervised learning that enables data scientists to analyze the relationship between data items in a dataset. The chapter explains the Apriori algorithm, a feature of association rule mining, and highlights how data scientists can collaborate with domain experts to achieve business objectives such as product matching and testing the efficiency of association rule results. Readers can follow a step-by-step guide to experience the association rule mining technique using RapidMiner, enabling them to develop their understanding of this valuable analytical tool.
Recommendation System

Recommendation systems are critical tools used by marketing departments to provide customers with product recommendations. Data scientists also use recommendation system analysis to assess the effectiveness of product and service suggestions. There are two types of recommendation systems: content-based and collaborative filtering. Content-based recommendations are based on the customer's purchase history, while collaborative filtering suggests a product based on purchasing behavior. Collaborative filtering can be divided into content-based filtering, which suggests products based on similar purchasing behavior, and item-based filtering, which suggests products based on their attributes. User-based and item-based nearest-neighbor collaborative filtering and probabilistic methods are used to analyze data and provide product suggestions. Businesses rely on recommendation systems to achieve various objectives such as customer retention and increased ROI. RapidMiner can analyze data following the principles of the recommendation system, as demonstrated in this chapter, step-by-step.
Players are not Ready 101: A Tutorial on Organising Mixed-mode Events in the Metaverse

While the academic community tries to define and experiment with the metaverse, businesses and institutions seek to build their representation in the metaverse. Many educational institutions build meta-campuses and move online classes into virtual environments beyond simple videoconferencing. This paper describes our experience building a university metaverse, highlighting the technical, human, and organisational challenges we have encountered through two major events. Considering the issue of real-time communication and scalability in the web-based metaverse, we also present an analysis of video streaming in virtual reality (VR) platforms: Meta's Workroom, Spatial, and Mozilla Hubs.
Analysis of the Effects of Teachers’ Scaffolding on Project-Based Learning of BS-English Students of University of Sindh, Jamshoro, Sindh, Pakistan

The present study investigates the effects of scaffolding on project-based learning (PjBL) of BS-English students at the University of Sindh. The objectives of the study were to disclose students' behaviour and the impacts of scaffolding during project work. This study adopts the mixed research methods under the explanatory research design to obtain the answers to the research questions. This study used questionnaires and reflection accounts for data collection. The statistical packages for social sciences (IBM SPSS Statistics version 23) were used for questionnaire data analysis and reflection accounts' data were analysed through content analysis. Considering data analysis distinct major themes emerged that were associated with the benefits and challenges of scaffolding and PjBL. Moreover, in the Pakistani context rarely teachers and students are familiar with modern ELT methods and their implementation is quite challenging. It is therefore recommended that mainly in PjBL teachers focused on the outcomes of the project but it is important to consider whether students acquire various skills during project work which is also the integral aim of PjBL. Hence, teacher's scaffolding is not confined to the completion and outcomes of the project but the teacher must observe whether the student develops the language and soft skills during project work.
Next-LSTM: a novel LSTM-based image captioning technique

Recently, image captioning has evolved into an immensely popular area in the field of Computer Vision. Research in this area is active and various Machine learning-based image captioning models have been proposed in the literature. It strives to generate natural language sentences in order to describe the salient parts of a given image. The main challenge with the existing approaches is effectively extracting image features to generate adequate image captions. Further, there is a need to improve the generalizability of the results on large and diverse datasets. In the current paper, a novel method, namely Next-LSTM is proposed for image captioning. It first extracts the image features using ResNeXt. It is a powerful convolution neural network based model that is adopted for the first time in the image captioning domain. Later, it applies a Long-short term memory network on the extracted features to generate accurate captions for the images. The proposed framework is then evaluated on the benchmark Flickr-8k dataset on Accuracy and BLEU Score. The performance of the proposed framework is also compared to the state-of-the-art approaches, and it outperforms the existing approaches.
Consummate Change Agent

Women in Higher EducationVolume 32, Issue 6 p. 1-2 Profile Consummate Change Agent Lois Elfman, Lois ElfmanSearch for more papers by this author Lois Elfman, Lois ElfmanSearch for more papers by this author First published: 21 June 2023 https://doi.org/10.1002/whe.21281Read 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 No abstract is available for this article. Volume32, Issue6June 2023Pages 1-2 RelatedInformation
THE READING PERFORMANCE OF LEARNERS IN MOTEHR-TONGUE IN THE COUNTRYSIDE AREA OF THE PHILIPPINES

With the implementation of Mother-Tongue Based Multilingual Education (MTB-MLE) under the Enhanced Basic Education Act of 2013 and the lack of contextualized and localized teachers guide and learners materials has motivated the researcher to pursue this study which aimed to determine the reading performance of learners in mother-tongue. The respondents of the study were comprised of 312 grade 3 pupils from all the central schools in the Schools Division of Eastern Samar during the First Grading Period of the School Year 2021-2022. This study used descriptive design. Results of the study revealed that the reading performance of learners in mother-tongue showed that the learners are advanced in terms of segmental sounds compared to supra-segmental sounds. This means that the lack of system of writing for the Waray language, lack of vocabulary lists, lack of assessment and validation tools for reading materials, lack of grammar materials/explanation, and lack of proper contextualized and localized learners materials affected the learners reading performance when dealing with complicated supra-segmental sounds. This study proved that even if teachers had a very satisfactory performance indicator, but there is a lack of development in contextualized and localized strategic intervention materials in MTB-MLE for local Waray language, particularly the Waray language used in Eastern Samar, there is still a language barrier between the teachers and pupils in understanding lessons taught in their respective school.
Tilburg University supports ResearchEquals

Tilburg University is now an inaugural supporting member of ResearchEquals, sustaining and governing the development of modular publishing.Tilburg University already included open science in its strategy in 2018 and has since vitalized local efforts through the Open Access Lab and the local Open Science Community. Other efforts like the
KU Leuven supports ResearchEquals

KU Leuven is now an inaugural supporting member of ResearchEquals, sustaining and governing the development of modular publishing.As part of their commitment to Open Science, KU Leuven supports sustainable implementations of Open Access and Open Science through the KU Leuven Fund for Fair OA. The fund is usually only
Report of 16th International Conference on Webometrics, Informetrics and Scientometrics (WIS) &amp; 21th COLLNET Meeting

The 16th International Conference on Webometrics, Informetrics, and Scientometrics (WIS) and the 21st COLLNET Meeting, 2022 which was scheduled to be held from 10 to 12 November 2022 at Chulalongkorn University, Bangkok, Thailand was organized after a two-year break, due to the Corona restrictions, by COLLNET in association with the Society for Library Professionals (SLP) and Asian Chapter, Special Libraries Association (SLA) and Chulalongkorn University, Bangkok, Thailand for the professional growth of the library and Information Science professionals. The broad focus of the conference was on collaboration and communication in science and technology; scientometric research on Covid19; techniques for collaboration studies; informatics law and distributions; mathematical models of communication and collaboration; quantitative analysis of s&amp;t innovations; evaluation indicators; collaboration in science and technology from both quantitative and qualitative points of view; bibliographic control bibliometric research data analysis and data mining; technology &amp; innovations in libraries and their impact on measurement on learning, research and users technology transfer and innovation in library management through metrics. The aim of the conference was therefore to contribute to evidence-based knowledge on scientific research and practices, which in turn can contribute to institutional, regional, national and international policy-making in the field of research and innovation. This event was part of the successful COLLNET conference series (www.collnet.de). Previous COLLNET conferences were held in Berlin (Germany) in 2000, New Delhi (India) in 2001, Sydney (Australia) in 2001, Beijing (China) in 2003, Roorkee (India) in 2004, Stockholm (Sweden) in 2005, Nancy (France) in 2006, New Delhi (India) in 2007, Berlin (Germany) in 2008, Dalian (China) in 2009, Mysore (India) in 2010, Istanbul (Turkey) in 2011, Seoul (South Korea) in 2012, Tartu (Estonia) in 2013, Ilmenau (Germany) in 2014, Delhi (India) in 2015, Nancy (France) in 2016, Kent (UK) in 2017, Macau 2018 and Dalian (China) 2019.
Mapping global research on expert systems

Purpose: The purpose of the study is to conduct a scientometric analysis of expert systems literature indexed in the Science Citation Index Expanded (SCIE) of the Web of Science database for a period of ten years (2011-2020). Design/Methodology: The study collected data from the Science Citation Index Expanded (SCIE) of the Web of Science (WoS) database from 2011-2020. The synonymous, broader and related terms of Expert Systems were selected from the Dewey Decimal Classification Scheme and Sears List of Subject Headings. A string of these terms was employed to retrieve data in the advanced search mode of the database. The harvested data was analyzed using scientometric techniques. Besides, the Microsoft Excel and VOSviewer software were used to represent and map the research productivity on expert systems. Findings: The results indicated inconsistent fluctuations in the annual number of publications from 396 in 2011 to 463 in 2020 and a decline in the number of citations from 8344 in 2011 to 520 in 2020. Further, it is divulged that China, the USA, and Spain are the three top countries contributing to expert system research published 16.36%, 14.96%, and 8.95% of literature respectively. While analysing institutional performance, the results revealed that most of the institutions are from China (6), followed by Iran (4), Spain (3) and India (2) /Malaysia (2) respectively. Further, by clustering the network map for keywords co-occurrence, it was found that expert systems, fuzzy logic, knowledge-based systems, machine learning, and artificial intelligence are the most common keywords and hence the hot topics of research in the area. Practical implications: The findings of the study may help researchers, information scientists and technologists to identify the research progress in the field of expert systems. Besides, it will help librarians to know the hot topics of research, prominent publications and prolific authors in expert systems. This will be helpful in the collection development of expert systems and artificial intelligence in libraries and information centres. Research limitations: The database studied for the work does not represent the total literary output available on expert systems as data in other databases like Scopus, Compendex, IEEE Xplore, arXiv, etc. haven’t been harvested. Originality/Value: The study is based on current literature on expert systems and will highlight new research trends in the said field.
Homomorphic Encryption

Homomorphic encryption is a form of encryption that enables computation on encrypted input without first decrypting it. This is significant because it enables calculations that protect the privacy of sensitive data, allowing sensitive data to be handled safely without the danger of exposure. This can be advantageous when privacy is an issue, such as cloud computing and big data analysis.
Floating-Point Arithmetic

Working with large numbers can be seen as abstract art, as covered in Chapter 4 . If the encryption schemes are not implemented correctly, the entire cryptographic method might result in a serious fatality.