Reviewerly/exHarmony huggingface dataset:
1. Nature-inspired optimization algorithm and benchmark functions: a literature survey

In the evolution process of humans, nature has played an important role in the transformation of mathematical investigation knowledge to modern human technological advancement. Nature optimizes the work based on biological, physical and chemical principles integrated with numerous mathematical models. People have learned the different principle and structure to design optimization algorithm that has been widely used in theoretical analysis and practical applications. In this chapter, we try to review several common nature-inspired algorithms with analysis systematically. Also, we try to incorporate the standard benchmark functions that are needed to evaluate the optimization algorithm. Through the chapter, we will discuss the original principle and the diversity of the algorithm in different practical applications.
Thematic Overview: Charting the Evolution of Knowledge Flows

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Respite for Customer’s Privacy Issues using Privacy Preserving Data Mining

Privacy preserving data mining has turned out to be progressively well known on the grounds that it permits sharing of security delicate information for study purposes. Nowadays, individuals have turned out to be progressively reluctant to share their information, over and over again people are either declining to share their information or giving erroneous information. As of late, protection safeguarding information mining has been considered broadly, in light of the wide multiplication of touchy data on the web. We examine strategy for randomization, k-anonymization, and other security safeguarding information mining strategies. Learning is matchless quality, and the more people are educated about data break-in, less inclined they will be to fall prey to the underhanded programmer sharks of data innovation. In this paper, we give a review of Privacy preserving data mining techniques.
The ordering of interface mapping rules in German object fronting

This paper discusses a data set on object-initial sentences in German. It is shown that it can be accounted for under the assumption that prosody-IS mapping rules come into play at different levels of the grammaticalmodel: Some, for example focus-related rules, apply at high levels, where they have access to prosodic and syntactic structure (and potentially even underlying structural representations). Others, in particular givenness-related rules, apply at lower levels, where they can affect phonetic realization, but not prosodic structure.
Attendance Capturing and Consolidation Mechanism Using Image Processing and Machine Learning Technique

Reorganization of hand written text needs natural intelligence. The proposed method recognizes the handwritten characters and classifies them from other characters for the attendance calculation system. The manual procedure for totaling students' attendance from the attendance register is difficult and time-consuming. The existing manual process for counting students' attendance contains a laborious effort for the number of students present or absent in a class. We propose an automated, digitized method for calculating the total number of presents or absent for a student in a class. The proposed system uses features extraction from a character, using feature extraction techniques. Support vector machine is one of the machine learning techniques used to classify a handwritten character. Support vector machine is trained using a large number of the training data set that needs to be fed into the database for accurate output. SVM is suitable and provides all the most desired levels of output. One Graphical User Interface(GUI) guides a user for stepwise visualization of the operations. Our objective is to minimize manual efforts and automate attendance counting more structured way.
Corrigendum to: Application of Two New Feature Fusion Networks to Improve Realtime Prostate Capsula Detection

We apologize for the error that occurred in the online version of the article. Table 3 was missing in the article entitled "Application of Two New Feature Fusion Networks to Improve Real-time Prostate Capsula Detection" in "Current Medical Imaging", 2021; 17(9): 1128-36 [1]. The original article can be found online at https://www.eurekaselect.com/article/113786 Original: Table 3 was missing. Corrected: Table 3 has been added.
Comparison of Different Models of Voiceprint Recognition used in Automatic Door Lock System (August 2021)

For any system, its reliability and the cost of construction have always been two major determinants of whether it can be used daily. In the field of voiceprint recognition, people are often forced to choose between accuracy and convenience. This paper discusses the performance of two speaker verification models in different environment and whether it is possible to balance between the cost and the result. The Gaussian Mixture Model with universal background model (GMM-UBM) and deep-learning method are selected to represent two common approaches in speaker verification. Through comparison between the two models, we find that the deep-learning method is in greater need of large training datasets to function since it performs poorer than the GMM-UBM model while trained with the same dataset containing only a few samples, while both of these two methods reach nearly 100% accuracy if provided a large enough dataset to train the model. Meanwhile, despite the attempt to yield higher accuracy by configuring the setting of both models, it appears that excellent performance only occurs when large amounts of training data are given, and little noise is present.
Identification of flood prone areas based on Geographic Information System (GIS): a case study of Buntulia District, Pohuwato Regency, Gorontalo Province

Abstract This study aims to identify flood-prone areas in the Buntulia district. The types of data used in this study are primary data and secondary data. Data analysis techniques used to determine flood-prone areas are scoring and overlaying of three parameters, namely, slope maps, rainfall maps, and land use maps. The results of this study are to determine flood-prone areas based on Geographic information systems (GIS) in Buntulia District, Pohuwato Regency, Gorontalo Provinsi. To find out the number of flood-affected areas, it is carried out using a mapping of flood-prone areas, so that it is divided into four levels of flood vulnerability, namely the very vulnerable level of 1275 hectares (2.93%), the vulnerable level of 4493 hectares (10.35%), moderate level vulnerable area of 21406 hectares (49.31%), and the level of the non-vulnerable area of 16221 hectares (37.37%).
Strategies to Combat the COVID-19 Pandemic in the UAE

The COVID-19 pandemic has disrupted the playing field and overall operations for organizations in the United Arab Emirates (UAE) and the world at large. In this chapter, the authors explore the biggest human resource (HR)-related challenges that firms in the UAE have faced as a result of COVID-19. The chapter outlines the skills and competencies required by professionals to overcome the challenges they have experienced. This groundbreaking chapter also undertakes an analysis of the extent to which COVID-19 and the lockdown have influenced the ability of human resource departments to achieve their key strategic objectives. It has been found that skills are among the most important competencies that professionals must possess today to keep pace with recent developments and in order to navigate the “new normal.” The chapter concludes with a review of the competitive survival strategies that UAE organizations are applying in order to remain sustainable during and post COVID-19.
Lossy Compression of Remote Sensing and Dental Images Corrupted by Spatially Correlated Noise

Remote sensing and medical imaging are very important in human’s life. The former deals with many applications from weather monitoring to military purposes and is performed by sensors mounted onboard of satellite and aerospace carriers. Medical imaging assists in disease detection and diagnostics. Images acquired by synthetic aperture radar or ultrasound medical imagers, alongside with well-known advantages have several drawbacks, particularly, spatially correlated speckle which corrupts images and, simultaneously, restricts possibilities of lossless image compression of remote needed due to a large size typical for modern applications. Therefore, a very important task is lossy compression of such images with acceptable quality that can be described in different ways including visual quality metrics. Three lossy coders are considered in our study: AGU, BPG, and JPEG2000. Three quality metrics are used: PSNR, PSNR-HVS-M, and MSSIM where two latter ones are visual quality metrics. Performance comparisons are performed. Recommendations are given for remote sensing as well as medical imaging applications.
Pornhub and the Value of Bitcoin

In December 2020, Visa, Mastercard, and Discover stopped processing payments for Pornhub, a website based in Canada that allows users around the world to upload and view pornographic videos. Cut off from traditional payment processors, Pornhub had to rely on cryptocurrencies. I consider the extent to which deplatforming Pornhub increased the value of bitcoin and other cryptocurrencies accepted on the site.
Using Windows and Android Apps

When you think of installing apps, then there are probably two things that come to mind. The first is having to visit a website to download Windows software, being uncertain if it might be genuine or if it might have malware in it and installing it on your PC using an installer that dates all the way back to the early days of Windows. Indeed, many installers still ask if you want to add an icon to the Quick Launch bar which was retired with Windows XP in 2009.
Development of Train-Boarding Assistance Device for Wheelchair

Wheelchair users require the assistance of station staff when boarding trains due to step differences and the gap between the platform and train. Therefore, they feel stressed in the movement with the train. In addition, the burden on station employees is increasing with the increasing number of wheelchair users at railway stations. In this study, an assistance device is proposed to address these challenges. This device can be used with any existing wheelchair, platform, and train and does not require external power sources, such as electricity. Using this device, a wheelchair user can board a train independently without assistance.
Generalized zero-inated Poisson regression mixture model for fitting health-related data

In many bioscience studies, it is common to encounter count data with a large number of zeros that Poisson regression model or standard zero-inflated Poisson (ZIP) regression model do not fit well. Generalized zero-inflated Poisson (GZIP) regression mixture model can handle the data with excess zeros and overdispersion caused by unobserved heterogeneity. For the parameter estimation, expectation-maximization (EM) algorithm with iteratively reweighted least sqaures (IRLS) method is used. We applied GZIP regression mixture model into two health-related data, Behavioral Risk Factor Surveillance System (BRFSS) data and Integrated Public Use Microdata Series (IPUMS) census data, and compared the performance of the models using AIC and BIC to find the best mixture model.
A Study on Korean Liaison in Prosodic Units of Vietnamese Learners

본 연구에서는 베트남인 한국어 학습자의 운율단위에 따른 연음 규칙 실현 양상을 파악하고자 하였다. 이를 위해 운율단위인 음운단어와 음운구에서의 연음 환경을 만들어 발화 실험을 진행하였다. 실험 결과, 음운구 내에서의 연음 규칙 실현율은 극히 낮았으며 오류 양상에 있어서는 대부분이 띄어쓰기 단위인 어절 단위로 끊어 읽는 절음 오류를 보였다. 이는 베트남인 학습자의 운율단위에 대한 인식 부족과 교수, 학습의 필요성을 보여주는 것이다. 이에 반해 음운단어 내에서는 동일 자음 첨가 오류가 과반을 넘게 차지하였으며, 베트남어에 존재하는 초성 자음 유무가 연음 실현율 차이에 영향을 주었다. 이는 학습자 모어가 한국어 발음에 영향을 미친 것으로 모어의 특징을 반영한 발음교육이 이루어져야 함을 시사한다. 또한 모어의 음운 체계에 없는 발음이라 할지라도 학습 초기부터 자주 노출되어 사용빈도가 높은 어휘는 높은 연음 실현율을 보였으며 음운단어에서의 연음 규칙 실현율 최상위인 학습자들이 음운구 내에서의 연음 실현에 성공하였다. 이를 통해 학습 초기부터 정확하고 명시적인 발음교육을 한다면 모어의 간섭 현상도 개선될 수 있음을 확인할 수 있었으며 이는 발음교육의 중요성을 보여주는 일례라 할 수 있을 것이다.This paper discusses the liaison of Vietnamese learners according to prosodic units. To this end, the experiment is conducted in phonological words and phrases with liaison. As experimental results, the rate of liaison in phonological phrases is very low. Most of Vietnamese learners produce errors in the pronunciation of liaison and pronounce one word by one word without linking a consonant between two words. It means they have little or no understanding of prosodic units. It is necessary to teach Vietnamese learners to pronounce prosodic units correctly. On the other hand, the error in adding the same consonant as the coda of the preceding syllable to the onset of the following syllable holds a majority in phonological words. It is interesting to note that onset consonants in Vietnamese affect liaison. It seems that the mother tongue of Vietnamese learners has an influence on their Korean pronunciation. We suggest the pronunciation education considering characteristics of the mother language of learners. In addition, words that have been used most frequently from the beginning of learning show a high rate of liaison. Moreover, learners who have the highest rate of liaison in phonological words pronounce liaison also in phonological phrases. Therefore, We think that the adequate pronunciation education at the beginning of learning Korean is very important and makes Vietnamese learners overcome interferences of their mother tongue.
Electronic voting machine security issues and solution protocol by physical unclonable function

The Electronic Voting Machine (EVM) has been introduced for minimizing the charges of election conduction. Even though the EVM system has saved millions of trees from cutting down and reduce the cost of election conduction (reduced the use of pen and paper method and the counting time and charges) so many numbers of cases have been filed against the misuse of EVMs. Hackers may set the EVM machines to vote for the particular party to whom they wish to win. In cryptographical words, the hackers find a way to malfunction the EVM machine. The common issue centered in EVM machines is software running in it. The public and members of any political party do not have full trust in it. Hence it is time to improve security with technology that is not hackable. This chapter provides a way to secure the EVM machine votes and save democracy by theway of uniquely authenticating every person aswell asmachines using unclonable technology in each voter ID chip and EVM machines. Hence, it blocks the ways of casting multiple votes and modifying the EVM machines.
Motivating monitoring as an element of the education quality management system

The article considers the main aspects of the formation of a methodology for motivating monitoring of the constituent entities of the Russian Federation, focused on obtaining complete and reliable information, which is the basis for making adequate management decisions in the education quality management system. A system of indicators and motivations is present. The areas of evaluation of data of Motivating monitoring of the constituent entities of the Russian Federation are divided into 3 blocks: 1) creating conditions for achieving results - assessing the quality of work of the constituent entities of the Russian Federation in a direction that provides educational and educational results; 2) achievement of educational and educational results - assessment of the contribution of the constituent entities of the Russian Federation to the achievement of strategic educational and educational results of the country&amp;apos;s education system; 3) organization of work processes - assessment of the quality of administrative work and executive discipline of the constituent entities of the Russian Federation. The article also provides a calculation formula for the formation of ratings of subjects of the Russian Federation. The authors propose a discussion on the prospects for the development of the education quality management system and the feasibility of expanding the scope of monitoring to the municipal and institutional levels.
An assessment and grading method of ultra-HD TVs based on subjective and objective evaluation

The new breakthroughs of high dynamic range (HDR) technology have boosted the development of ultra-high-definition televisions (Ultra-HD TVs), and the evaluation standard of HDR video plays a significant role. But owing to the imperfect technique and standards, the current high-end products can hardly reach the requirements of Ultra-HD TVs. To improve the HDR assessment technique, a grading method for consumer-oriented products which balances the subjective and objective assessment is proposed to evaluate the HDR performance of Ultra-HD TVs. The subjective assessment is based on existing HDR standards, and the peak brightness, dynamic range, color gamut coverage and the absolute deviation of the electro-optical transfer function (EOTF) constitute the objective evaluation. With the proposed method, the videos which quality between the SDR and HDR standards can be divided into 3 or 4 grades by 4 metrics. The statistical results expound that many Ultra-HD TVs in the consumer-oriented market performs better than the HDR access standard, but still far from the professional-level, and the experiment results certify that the proposed method is an effective standard and can facilitate the standardized development on HDR performance of Ultra-HD TVs.
Extracting Multilingual Relations with Joint Learning of Language Models

The open access to annotated text for supervised learning problems is currently an important topic in Machine Learning. For specialized domains, such as healthcare and pharmacological, public annotated documents are subject to restrictions to safeguard patients’ privacy. This issue is exacerbated for languages with scarce training data such as Japanese. To develop accurate solutions despite this situation, we propose a joint learning network of pre-trained Language Models for Natural Language Processing tasks, where each model focuses in one specific language. We present a preliminary evaluation that shows improved performance over baseline network.
Verb placement and verb movement

This chapter surveys and analyses the rich variation in verb placement and verb movement operations which is attested in the history of French. The analysis developed suggests than an original SOV grammar where the finite verb remains in-situ is reanalysed as one with optional verb movement to the left periphery during the Classical Latin period, with this movement itself reanalysed as systematic V-to-C movement in certain colloquial and late Latin texts. Until the Renaissance, French is also argued to feature systematic V-to-C movement, albeit to distinct heads within the left periphery. Novel data is presented to suggest that as part of an SVO grammar, French has featured verb movement to the high tense-aspect-mood field since the 16th century. A diachronic and synchronic analysis of verb–subject inversion in interrogatives and verb movement in imperatives is also presented. The chapter concludes with a formal parametric analysis of both unmarked and marked verb movement from Latin to Modern French.
Comparative Study of Marathi Text Classification Using Monolingual and Multilingual Embeddings

Text classification, a common task in Natural Language Processing, is used to classify sentiments, food reviews and many more. With the increased adaption of regional languages in the digital era, the necessity of text classification in regional languages has also increased. As one of the 22 constitutional languages, Marathi is spoken by approximately 83 million people. This widespread use of Marathi has led researchers to perform Marathi text classification; however, these research works pre-dominantly were based on language specific manual features based on grammar rules, morphological clues and syntactic dependencies between the words. This work compares and evaluates various pre-trained monolingual and multilingual embeddings with machine learning models to perform Marathi text classification. Our experiments show that the transformer based multilingual embeddings with Long Short Term Memory (LSTM) architecture outperform monolingual embeddings with better recall, precision, accuracy and F1-Score with lesser training time.
Un altro fantasma di meno: le lettere di Lorenzo Moschi a Francesco di Marco Datini

This article draws on two recent discoveries that shed light on a little known 14th century Florentine poet, Lorenzo Moschi. One is a signed document dated 1375 present in a Laurenziano manuscript, and the other includes five letters contained in the “Fondo Datini” collection of the Archivio di Stato in Prato, all addressed to the renowned merchant Francesco di Marco Datini in 1386 and signed ‘Lorenzo Moschi in Napoli’. After providing well-documented socio-historical background details and a palaeographical note (the latter indicating that the signature present in the 1375 codex and the letters from 1386 are all written in the same hand), the article offers a critical edition of the letters and includes an investigation into their contents by comparing them with coaeval texts from the same archive. This is followed by an extensive linguistic and stylistic analysis, together with a glossary, aimed at highlighting the structural, syntactical and lexical features typical of business correspondence.
The efficiency of multimedia technologies utilized in studying Mathematics course in the fields of Engineering

Abstract The learning model represented in the paper implies the use of specifically designed workbooks and dynamic presentations, original (self-developed) interactive computer games and training systems, LearningApps.org web service, mobile applications in Glide, Kahoot! in-game learning platform, Desmos graphing calculator and the Maple computer algebra system in learning. The applied educational tools give students an opportunity not only to get to know basic mathematical concepts, work out and test their computation skills individually but also to model processes that change over time, changing the process variables interactively. The article provides several examples of such assignments for students. In this model of arranging to learn, an educator is becoming free from a lot of routine work (manual check of tasks and tests). The educational experiment took place in the 2019-2020 and 2020-2021 academic years. 167 Engineering students from Sholom-Aleichem Priamursky State University, Moscow State University of Civil Engineering, and Osh State University participated in it. The conducted experiment proved the effectiveness of the learning model suggested: competent academic performance of students has increased by 15%. Therefore, supported multimedia technologies, involving most of the sensory experience of a student in understanding learning materials, make learning more productive.
Cybersecurity

Abstract Dr Deepthi Ratnayake explores the impact of dark patterns on web applications.