Reviewerly/exHarmony huggingface dataset:
A new simulation method for moiré control of LED background screen in film and television shooting

In contemporary film and television production, LED screens are commonly used as dynamic backgrounds, but moiré problems are often encountered. Existing studies on moiré control predominantly employ pre- or post-production removal methods, which exhibit limitations when applied to high technical specification images. To avoid moiré during the on-set shooting, cameramen often resort to techniques such as defocusing, the effect of which relies much on experience and expertise, and cannot entirely exclude the persistent occurrence of moiré phenomena in defocused scenarios. To address these issues, a more quantitative comprehension of the factors governing moiré formation is imperative. Previous explanations such as interference superposition of gratings or undersampling have proven inadequate in accurately simulating moiré on LED screens and therefore cannot effectively guide practice. We propose a convolutional imaging calculation-based approach for simulating the moiré pattern observed in screen shots. The simulated results exhibit consistent global patterns of moiré and their variation trends with shooting parameters, as compared to live results. We compare the moiré images generated through simulation methods with those obtained from live shooting experiments, while investigating the influential factors of moiré control during the live shooting. For various focusing scenarios, we present a constraint inequality for the shooting parameters, and demonstrate its efficacy in accurately predicting moiré reduction during defocused screen shooting. Furthermore, we apply this method to quantify the impact of camera roll rotation, LED screen dot pitch, opening ratio and pixel arrangement on moiré formation.
Machine Learning Approaches for Entity Extraction from Citation Strings

As the technological evolution is on the rise, so is the amount of research literature. It becomes important for the listing websites to easily parse the citation to store the metadata and to enable easier classification and database management. Citation parsing is an open research problem floating from decades. The Extraction and parsing of reference strings from the articles is a challenging task. State-of-the-art tools like GROBID, ParsCit and Cermine use simple machine learning models such as conditional random fields (CRF). There have been many attempts to solve this problem efficiently. Every work has tried to solve the problem in a different way. Based on relevant metrics, we have analyzed a variety of methods which have been applied to get through the task of citation parsing. We have comprehensively written the comparison among different approaches on several metrics. We concluded that Machine Learning based approaches performed much better than non-ML based approaches. One of the top performing Machine learning tools utilized conditional Random fields (CRF), which yielded an F1 score of 0.82 on an average.
Using Reference Points for Detection of Calcifications in Mammograms for Medical Active Systems

Context-awareness is one of the main features of any AmI system, particularly related to healthcare systems. To develop this kind of active systems it is necessary to create methodologies where it can be observed how the experts solve specific problems or situations. This paper focuses on the problem of breast cancer detection and classification, and presents a methodology based on a case study where radiologists and medical doctors were involved and their knowledge was extracted in order to define a model that could be used to develop a breast cancer automatic interpretation system, with the goal of helping the medical personnel in their decision-making process. As a first step towards the development of such active system, this paper presents the detection of calcifications, a type of finding in the breasts that could be benign or malign, depending on certain features. The detection is made by applying composite correlation filters, and even though the calcifications used for testing cover all the categories defined by a medical taxonomy (BI-RADS system), the accuracy of such detection is promising, where most categories have a detection accuracy of 80% or above.
Identifying Amharic-Tigrigna Shared Features: Towards Optimizing Implementation of Under Resourced Languages

In this article, exploratory research is conducted to analyze statistical overlap across Amharic and Tigrigna at different level of abstraction, namely, word level, CV syllable level, and at phoneme level. Amharic and Tigrigna are among the most widely spoken Ethiosemitic languages in Ethiopia, yet under resourced to be fully integrated into TTS applications that assist oral society in their day-to-day activities. Text to speech research requires linguistic resources involving intensive text analysis and acoustic resources that involve digital signal analysis. TTS researches for Ethiosemitic languages have been explored on monolingual basis which require fragmented research activities towards the resource intensive task. Investigating the level of overlap for Amharic and Tigrigna gives an insight to reuse shared acoustic and linguistic resources across these languages and reduce duplication of effort in the process of designing higher level applications such as TTS. According to our statistical analysis, Amharic and Tigrigna share 86.36% at phonemic level, 85.93% at CV syllable level, and encouraging level of overlap at the word level. The extent to which these languages overlap at different level of abstraction implies the opportunity to reduce duplication of effort in the design and development of bilingual and multilingual TTS for Ethiosemitic polyglots.
Popularisation of Bibliographic Products as an Important Component of Advertising and Information Activities of Libraries

The purpose of the research is to analyse effective methods and tools for promoting bibliographic products by leveraging the Internet capabilities within the context of libraries, particularly by examining existing practices and innovative strategies in the online space to enhance the accessibility of bibliographic resources. Research methodology. To study this problem, general scientific methods (analysis, synthesis, deduction, and induction) were used in relation to the use of marketing tools, social communications, Internet opportunities for the exchange and distribution of the resources bibliographic products in the modern library space of Ukraine. As a result of applying these methods, we have gained a deep understanding and analysis of the problems and opportunities in using marketing tools, social communications, and Internet capabilities for the exchange and dissemination of bibliographic production in modern libraries in Ukraine. The scientific novelty of the study arises from the fact that the subject of bibliographic production popularisation in Ukrainian libraries remains insufficiently developed, particularly in terms of promoting publications by means of the Internet, necessitating a comprehensive approach to studying all possibilities and identifying pathways for the development of library activity. Such a comprehensive approach will allow us to identify optimal pathways and development strategies for libraries in the digital age, which, in turn, will contribute to improving access to cultural heritage and information for the public, increasing information literacy, and supporting libraries as crucial agents of education and cultural development in society. Conclusions. The research examines the effectiveness of libraries’ promotional and informational activities in popularising bibliographic production through extensive Internet resources. Special attention is paid to primary tools for promoting bibliographic production in social media and incorporating crowdfunding instruments. &#x0D; Keywords: bibliographic products, advertising and information activities, library marketing, popularisation, Internet marketing, blog, book trailer, social media, SMM (Social Media Marketing), digital marketing, reputation marketing, event marketing, guerrilla marketing, crowdfunding.&#x0D;
iMAGING: a novel automated system for malaria diagnosis by using artificial intelligence tools and a universal low-cost robotized microscope

Introduction Malaria is one of the most prevalent infectious diseases in sub-Saharan Africa, with 247 million cases reported worldwide in 2021 according to the World Health Organization. Optical microscopy remains the gold standard technique for malaria diagnosis, however, it requires expertise, is time-consuming and difficult to reproduce. Therefore, new diagnostic techniques based on digital image analysis using artificial intelligence tools can improve diagnosis and help automate it. Methods In this study, a dataset of 2571 labeled thick blood smear images were created. YOLOv5x, Faster R-CNN, SSD, and RetinaNet object detection neural networks were trained on the same dataset to evaluate their performance in Plasmodium parasite detection. Attention modules were applied and compared with YOLOv5x results. To automate the entire diagnostic process, a prototype of 3D-printed pieces was designed for the robotization of conventional optical microscopy, capable of auto-focusing the sample and tracking the entire slide. Results Comparative analysis yielded a performance for YOLOv5x on a test set of 92.10% precision, 93.50% recall, 92.79% F-score, and 94.40% mAP0.5 for leukocyte, early and mature Plasmodium trophozoites overall detection. F-score values of each category were 99.0% for leukocytes, 88.6% for early trophozoites and 87.3% for mature trophozoites detection. Attention modules performance show non-significant statistical differences when compared to YOLOv5x original trained model. The predictive models were integrated into a smartphone-computer application for the purpose of image-based diagnostics in the laboratory. The system can perform a fully automated diagnosis by the auto-focus and X-Y movements of the robotized microscope, the CNN models trained for digital image analysis, and the smartphone device. The new prototype would determine whether a Giemsa-stained thick blood smear sample is positive/negative for Plasmodium infection and its parasite levels. The whole system was integrated into the iMAGING smartphone application. Conclusion The coalescence of the fully-automated system via auto-focus and slide movements and the autonomous detection of Plasmodium parasites in digital images with a smartphone software and AI algorithms confers the prototype the optimal features to join the global effort against malaria, neglected tropical diseases and other infectious diseases.
Wigner function analysis of finite matter-radiation systems

We show that the behaviour in phase space of the Wigner function associated to the electromagnetic modes carries the information of both, the entanglement properties between matter and field, and the regions in parameter space where quantum phase transitions take place. A finer classification for the continuous phase transitions is obtained through the computation of the surface of minimum fidelity.
Integrated Intermodal Model of Online Teaching-Learning: A Proposal Focusing on Edu-Communication and Online Interactions

The advent of the pandemic in the years 2020-2021 further deepened the discussion about educational design that was guided by educational communicative practices. The objective of this work was to develop an online teaching-learning model focused on interaction and edu-communication. The study followed the Integrated Mixed Research Strategy in five stages. Firstly, the problem and objectives of the research were identified, by surveying the theoretical framework. Next, a qualitative field study was conducted with qualitative meta-synthesis and content analysis. The information collected revealed a correlation between the content of the articles and the main approaches in the theoretical foundation, pointing to a collaborative learning model in online teaching, with a focus on learning communities, modularization of objectives and content, and emphasis on interaction, being observed a lack in the methodological area of ​​edu-communication and interrelations with interaction. To develop the Integrated Intermodal Model of online teaching-learning, concepts from convergent approaches and theories from the meta-synthesis sample were added. This resulted in a prototype of online educational design for flexible, digital environments, supported by ICTs, promoting reflection, interaction, autonomy, and dialogue. It is important to highlight that the model requires additional replication, review, testing, and validation.
The Comparison Of Student’s Ability In Understanding The English Reading Text By Using Skimming And Scanning Technique

The aim of this research was to find out the effectiveness of using skimming and scanning technique and find out which technique is better skimming or scanning on students’ ability in understanding the English reading text of the tenth grade students at MAS Al Washliyah Serbalawan in the academic year 2021/2022. This research used quantitative approach with pre - experimental design. The data were obtained by using post-test only. The data of post-test was analyzed by using descriptive and inferential statistics. (SPSS 23.0). The result of the research shows that the testing hypothesis of post-test scores was found that tcount = 2.668 ˃ ttable = 1.684 at the significance level α=0,05 with the degrees of freedom (df)=39, So, Ho is rejected and Ha is accepted. It means that the implementation of Scanning and skimming effect on students reading ability at tenth grade of MAS Al Washliyah Serbelawan in academic year 2021/2022
Learning Syllables in Malay Language through Augmented Reality Content for Preschool Children

The rapid growth and widespread adoption of augmented reality (AR) opened new possibilities for seamless integration into various aspects of human life. In this context, educators increasingly explored the potential of AR to enhance learning experiences. This research focused on leveraging AR technology to address a specific problem encountered by preschoolers in their language learning journey. The problem at hand was that preschoolers often encountered difficulties in blending consonant-vowel and consonant-vowel (CV+CV) sounds to form words in the Malay language. While they could easily sound out individual consonants and vowels, they struggled with combining these sounds to create new words, hindering their reading and language development. To tackle this challenge, the proposed solution involved the development of an AR prototype aimed at making learning Malay language syllables engaging and enjoyable for preschoolers. The research’s output allowed children to practice forming syllables and improved their pronunciation through interactive AR experiences. Moreover, it offered quizzes to test their knowledge of Malay language syllables, providing instant feedback for a positive and effective learning experience. The survey presented the results of system testing, which revealed that a significant number of respondents had prior exposure to AR and found the research output's instructions clear and understandable. The integration of AR elements, such as 3D objects and marker detection, received positive feedback from most participants. However, some users expressed a desire for additional training, and there was potential to further enhance the app's level of excitement. In conclusion, this research demonstrated the promising role of AR in addressing preschoolers' challenges with language learning. By leveraging AR technology to create interactive and captivating learning tools, educators could better equip young learners with the necessary language skills, fostering a solid foundation for their reading and communication abilities in the Malay language.
How Much Is Blockchain Related News Worth?

In the blockchain frenzy, some companies announce to initiate or increase blockchain-related business and/or change their names to include “blockchain” or “bitcoin.” The US market reacts with an average cumulative abnormal return of 80.96% for the 2-day window encompassing the announcement day and the very next day. The effect is an average of 9.37% cumulative abnormal return for Mainland China and Hong Kong. After a year, all the US companies remained above pre-announcement levels, yet quite some companies in Mainland China and Hong Kong revert to pre-announcement levels and sometimes even lower; such reversal indicates that previous valuation increase is temporary.
The Implications of School Unrest on Students’ Academic Performance in Secondary Schools in Bondo Sub-County, Kenya

Schools are called to effectively assess and monitor school climate given its potential ability to enhance positive student outcomes and mitigate risk behaviors. When a positive school climate exists, students, staff members and parents feel safe, included and accepted. The school community demonstrates respect, fairness and kindness in their interactions and builds healthy relationships that are free from discrimination and harassment. This study sought to examine the Implications of school unrest on students' academic performance in secondary schools in Bondo sub-County Kenya. The study was guided by the System Theory of biologist Ludwig Von Bertalanffy. A descriptive research design was used in this study. The study adopted the mixed method of study. This study population comprised 3159 Form 3 students, 49 principals, 49 teachers of Guidance and Counseling and 1 sub-county Quality Assurance and Standards Officer in Bondo sub-county. Stratified sampling, purposive sampling and simple random sampling were used to arrive at a sample size of 300 of Form three students from sampled schools. Besides, all Principals and Guidance and Counseling Teachers of the selected schools were also brought on board. Data were collected using a questionnaire, interview schedule and document analysis. After collection, quantitative data were sorted, edited, coded, classified and tabulated for analysis. Data were analyzed using descriptive and inferential statistics. Descriptive statistics results were presented as counts/tables, percentages, bar graphs, column graphs and pie charts. Further, chi-square tests and Spearman correlation tests were run between school climate and students' unrest. This study established that unrest in secondary schools is a consequence of a negative climate, necessitating students' indiscipline and that it has the potential to affect students' overall academic performance. HO2 stated that the association between unrest in schools and students' overall academic performance factor was statistically significant. The study suggested that there is a need to increase students' feeling of safety at school, for example, by reducing victimization, improving overall school and neighborhood safety and promoting classroom engagement.
Data-to-Text

Suppose you ask a question that can be answered using data in a database, and you use a text-to-data model to map the question to a formal query in the database. The query evaluated on a database returns the answer in a structured representation, such as a table in a relational database or a graph in a graph database. The full cycle of natural language interfaces to databases is not complete without mapping this structured data to natural language, which is the topic of this chapter.
Building an NLIDB: The Basics

The main purpose of this chapter is to help readers to form a high-level understanding of NLIDBs and to better understand and leverage the techniques and approaches to be introduced in the rest of the book. We first describe an example database and example input questions against the database in Sect. 2.1. We then introduce the common architecture of a baseline NLIDB before introducing terminologies to be used throughout the rest of the book (Sect. 2.2). Finally, we describe a step-by-step basic process to construct such a baseline NLIDB for the example database to handle the example question in Sect. 2.3.
Study for a photovoltaic system to supply electricity to an isolated apiary

The paper presents, based on the study and the experience of the authors in the field, some considerations, especially from an application aspect, useful in building a photovoltaic system for supplying electricity to an isolated apiary, as well as simulations for such a system, made with the PVGIS program . The main high-performing electric machines of today with relatively high energy consumption from an isolated beehive are identified, as well as their specific mode of use, during a calendar year, an essential factor for establishing the installed power of such a photovoltaic system and a its effective technical-economic design.
Research on single-frame fringe phase unwrapping methods

Fringe projection 3D measurement technology, as a new type of modern measurement technology, is widely used in various fields, such as reverse engineering, information security, medical diagnosis and other fields due to the advantages of non-contact, high precision, and rapid measurement. The single fringe 3D measurement requires only one deformed fringe image to recover the phase distribution that containing the object information. The paper employs the Fourier transform fringe analysis technique for single-frame fringe phase demodulation. The wrapped phase of the object is recovered through Fourier transformation, frequency domain filtering, and Fourier inverse transformation. Then, the phase unwrapping algorithm is used to unwrap the discontinuous wrapped phase into a continuous phase with practical significance. The traditional phase unwrapping methods that scan line by line and column by column are only suitable for completely sampled wrapped phase fields. The branch-cut method used in this paper is a powerful noise-resistant path optimization phase unwrapping algorithm. This algorithm generates branch-cut lines that represent unreliable areas in the phase unwrapping process and selects paths that avoid these branch-cut lines, thereby constraining the spread of local errors.
FB Chat N SS Writing (Facebook Chat and Students’ Writing)

Social networking websites are not only famous in Malaysia but all around the world. Schill (2011) stated that social media sites only encourage negative effects. It became so serious that academicians are still researching how these social networking sites like Facebook are affecting students’ language performances. In line with those statements, this study focused to find out what were the characteristics of Facebook Chat, to examine the reasons for students to use those characteristics and to find out whether students used those characteristics in their academic writing tasks. The methodology revolved around questionnaires and written work whereby students were asked to answer questionnaires and write essays on three given topics. The respondents for this research were 40 TESL undergraduates from a local public university. Samples were those who had Facebook accounts and were active Facebookers. It was apparent that 42.5% of the samples spent more than 3 hours on Facebook in which 45% of them used Facebook specifically to chat. It was shocking as 50% of the samples agreed that they used Facebook Chat features like abbreviations in their academic writing. Besides that, 55% of them agreed that they were approached or scolded by their lecturers for using those features. As for the written work of the students, a staggering 74% of the essays had Facebook chat features in them. Frequent use of chat language may impact one's ability to communicate effectively in formal settings. Over time, individuals may struggle with proper grammar, spelling, and punctuation, as well as clarity and coherence in their writing. Furthermore, frequent use of chat language may impact one's ability to communicate effectively in formal settings. Over time, individuals may struggle with proper grammar, spelling, and punctuation, as well as clarity and coherence in their writing.