Reviewerly/exHarmony huggingface dataset:
The Level of Application of Excellence Management According to the European Model EFQM Standards from the Female Teachers’ Point of View in Al-Batina North Governorate

The current study aimed to investigate the level of application of excellence management according to the European model standards from the point of view of female teachers in North Al Batinah Governorate and to enquire significant differences between the averages of female teachers with respect to the standards according to the cycle. To achieve the objectives of the study, the descriptive approach was used. The sample was selected randomly and consisted of (150) female teachers from the schools of the cycle 1 (4-1) and cycle 2 (10-5) in North Al Batinah Governorate. The study tool (questionnaire) consisted of (41) items distributed on six dimensions: (policies and strategies, employee satisfaction (individuals), partnerships and resources, operations, community interaction, school performance results), It was applied to the sample after verifying its psychometric characteristics. Findings showed that the level of application of excellence management according to the European model of excellence from the point of view of female teachers in North Al Batinah Governorate was high, as the results indicated that there were no statistically significant differences at the level of significance (α ≤ 0.05 between the arithmetic means of the level of excellence management application according to the European model from the point of view of the parameters attributed to the episode variable (first/ second), In the light of the results obtained, the researcher recommended the necessity of developing a national model for the management of excellence in the Sultanate, or working on adopting one of the international models for managing excellence; This is to support excellence and its application in all public schools, and to train school administrations on modern systems and trends in school management, to enhance their distinguished skills, and to work on refining the research skills of school principals, to practice scientific research to apply its results in the service of the educational institution, and to activate school administrations for several methods Effective measure of employee satisfaction with the services provided to them by the school Among the recommendations are also the provision of developed programs for property management, and the involvement of local community members in setting the annual school plan, in addition to designing an educational guide to spread the culture of managing excellence in public schools, the initiative of school administrations to form a team for school excellence, which monitors the extent to which excellence practices are applied and strengthened among all employees.
Diagnostic Test Accuracy of AI-Assisted Mammography for Breast Imaging: A Narrative Review

&lt;p&gt;This narrative review delves into the diagnostic test accuracy of AI-assisted mammography for breast imaging, examining its potential, challenges, and future implications. AI's integration into medical imaging has promised to revolutionize breast cancer diagnosis, prompting an evaluation of its performance and impact. A comprehensive literature search was conducted, resulting in the identification of key articles. These studies encompassed diverse AI techniques, training datasets, and geographical contexts. The review synthesizes findings on sensitivity, specificity, interpretability, ethical considerations, and global implications. The studies collectively demonstrate AI's potential in enhancing diagnostic accuracy, with deep learning algorithms exhibiting commendable sensitivity and specificity levels. However, challenges arise in data diversity, algorithmic bias, and interpretability. Ethical and regulatory considerations underscore the need for responsible AI deployment. The concept of augmented intelligence, wherein AI collaborates with radiologists, holds promise for future clinical practice. AI-assisted mammography holds transformative potential in breast cancer diagnosis, accuracy and efficiency. While challenges exist, collaborative efforts between stakeholders are essential to navigate complexities and realize AI's benefits. The review concludes that while AI holds promise in breast cancer diagnosis, ethical, global, and research considerations are imperative for its responsible and effective deployment.&lt;/p&gt;
Automated Measures of Sentiment via Transformer- and Lexicon-Based Sentiment Analysis (TLSA)

&lt;p&gt;The last decade witnessed the proliferation of automated content analysis in communication research. However, existing computational tools have been taken up unevenly, with powerful deep learning algorithms such as transformers rarely applied as compared to lexicon-based dictionaries. To enable social scientists to adopt modern computational methods for valid and reliable sentiment analysis of English text, we propose an open and free web service named transformer- and lexicon-based sentiment analysis (TLSA). TLSA integrates diverse tools and offers validation metrics, empowering users with limited computational knowledge and resources to reap the benefit of state-of-the-art computational methods. Two cases demonstrate the functionality and usability of TLSA. The performance of different tools varied to a large extent based on the dataset, supporting the importance of validating various sentiment tools in a specific context.&lt;/p&gt;
Hephaestus: Modelling, Analysis, and Performance Evaluation of Cross-Chain Transactions

&lt;p&gt;Ecosystems of multiple blockchains are now a reality. Multi-chain applications and protocols are perceived as necessary to enable scalability, privacy, and composability. Despite being a promising emerging area, we have been witnessing devastating attacks on cross-chain bridges that have caused billions of dollars in losses, and no apparent solution seems to emerge from the ongoing chaos. In this paper, we present our contribution to minimizing bridge attacks, by monitoring a &lt;em&gt;cross-chain model&lt;/em&gt;. In particular, we aggregate &lt;em&gt;cross-chain events&lt;/em&gt; into &lt;em&gt;cross-chain transactions&lt;/em&gt;, and verify if they follow a set of &lt;em&gt;cross-chain rules&lt;/em&gt;, which then generate a model.&lt;/p&gt; &lt;p&gt;We propose &lt;strong&gt;Hephaestus&lt;/strong&gt;, the first cross-chain model generator that captures the operational complexity of cross-chain applications. &lt;strong&gt;Hephaestus&lt;/strong&gt; can generate cross-chain models from local transactions in different ledgers, realizing arbitrary cross-chain use cases and allowing operators to monitor their applications. Monitoring helps identify outliers and malicious behavior, which can enable programmatically stopping attacks (``a circuit breaker''), including bridge hacks. &lt;/p&gt; &lt;p&gt;We conduct a detailed evaluation of our system, where we implement a cross-chain bridge use case. Our experimental results show that &lt;strong&gt;Hephaestus&lt;/strong&gt; can process 600 cross-chain transactions in less than 5.5 seconds in an environment with two blockchains using sublinear storage, paving the way for more resilient bridge designs.&lt;/p&gt;
IMPROVING STUDENTS’ SPEAKING ABILITY BY SHORT DILAOGUES MEMORIZATION

This research aimed at improving students’ speaking ability using short dialogue. It was a classroom action research (CAR). The study was conducted in a cyclic process starting from planning, acting, observing, and reflecting. What technique? Technique was implemented in two cycles. The subjects of this research were elementary level students from SMAS Panca Setya Sintang. The study found out that the implementation of short dialogue memorization technique has improved the students' speaking ability. The students also improved their active involvement in class. In the first cycle, only some students participated in class actively, but most of them were very active in the second cycle. Based on the students’ score data, more than half of the students got higher in each aspect. Compared with the data from Cycle I, Cycle II was dominated by the students who got a score of 6 in each aspect, while Cycle I was dominated by the students who got score 2 and 1. Almost all students passed the criteria of success, 70. Therefore, the teachers were recommended to improve the students’ speaking ability using short dialogue memorization technique.
The Use of ICT as a Resource and Media for Modern 21st Century Learning in Primary Schools

The advancement of technology and information makes human life easier, but at the same time it makes some humans lack morals and behave badly due to lack of socialization. Behind all the bad impacts on the development of technology, there are also positive impacts in it, such as in the field of education. One of the positive impacts is ICT (Information and Communication Technology) learning media. The purpose of this study is to determine the use of ICT (Information and Communication Technology) as a Source and Media for Modern 21st Century Learning in Elementary Schools. This research uses quantitative methods, data obtained from distributing questionnaires and through interviews. The results of the study explain that the usefulness of ICT (Information and Communication Technology) as a source and modern learning media in elementary school children is very useful and helps students in carrying out learning. The conclusion of this study explains the usefulness of ICT (Information and Communication Technology) as a source and modern learning media in elementary school children is very helpful in the learning process. The researcher realizes the limitations of this study were only conducted in elementary schools in one of the districts in West Sumatra province, the researcher hopes that future researchers can conduct the same research with a wider range in order to continue this research. Researchers also recommend to researchers who will continue to be a benchmark in conducting research related to the use of ICT (Information and Communication Technology) as a modern learning resource and media in elementary schools.
Students’ Experience in Using Natural Reader Application to Ensure the Accuracy of Their English Pronunciation

Since 1960, speech synthesis technology has existed and its applications are now widely available, one of which is the Natural Reader application. Natural Reader is an application that can be used in knowing how to pronounce words in English. This study aims to describe students' experiences with using the Natural Reader application and examine the effect of utilizing the use of the Natural Reader application as a tool to test the accuracy of pronunciation of Mahmud Yunus Batusangkar State Islamic University students, by using the Natural Reader application students can more easily test their English accuracy. The method used by researchers is quantitative method, quantitative research can show data containing numbers that can be obtained by utilizing google form as a means of making a questionnaire. This research shows that the Natural Reader application has the potential to ensure the accuracy of pronunciation in English. So it can be concluded that the Natural Reader device can ensure the accuracy of student pronunciation in English.&#x0D;
A Novel Deep Learning Approach to Malaria Disease Detection on Two Malaria Datasets

Malaria is a contagious febrile disease transmitted to humans by the bite of female mosquitoes. It is important to diagnose this disease in a short period of time. Finding the mathematically best numerical solution to a particular problem is the most important issue for most departments. In deep learning-based systems developed, the difference between the real data and the predicted result of the model is measured using loss functions. To minimize the error rate in the predictions during the training process of deep learning models, the weight values used in the model should be updated. This update process has a significant effect on the model prediction result. This article presents a new deep learning-based malaria detection method that will help diagnose malaria in a short time. A new 21-layer Convolutional Neural Network (CNN) model is designed and proposed to describe infected and uninfected thin red blood cell images. By using thin red blood cell sample images, 95% accuracy was achieved with Nadam and RMSprop optimization techniques. The results obtained show the efficiency of the proposed method according to each optimization algorithm.
Development of the Edpuzzle Platform as an Audio Visual Learning Media for Arabic Language Learning at Madrasah Aliyah

The development of technology is currently growing so rapidly, various applications and online media are becoming increasingly popular to be used as learning media, including Youtube and Edpuzzle which can be used as learning support platforms with interactive, effective and fun video media for students. Arabic language learning with audio visual is needed by madrasah Aliyah students, so that learning is not boring and more interesting. This research aims to develop the Edupuzzle platform as an audio-visual learning media for Arabic language learning in madrasah Aliyah. The method used in this research is research and development with the Kemp model. Kemp's model is a learning design model designed in the early part of education aims to provide guidance to learners to think about general problems and learning objectives. The results of this study explain that the Edpuzzle platform can be used as audio-visual learning media in learning Arabic with audio visuals that can facilitate students in learning Arabic online. The conclusion of this research is that the Edpudzzle platform can be used as a learning medium for teachers, especially in Arabic language learning. the limitation of this research is that researchers only conduct research on the Edpudzzle platform for Arabic language learning, for that researchers hope that future researchers can conduct research with the same platform but more explained to support the teaching and learning process in other subjects.
CURRENT PROBLEMS OF TRAINING SCIENTIFIC AND PEDAGOGICAL PERSONNEL AT UNIVERSITIES

Modern Russian higher education is undergoing qualitatively new transformations in the context of globalization and turbulence in the external environment. However, the basis for good professional training for students is the didactic training of university teachers. The article analyzes the key problems of modern training of scientific and pedagogical personnel for teaching at a university, regardless of specialty, reveals ways and prospects for the development of problems and develops recommendations for solving them.
UNIVERSITY AS A DRIVER FOR REGIONAL ECONOMY DEVELOPMENT

One of the key characteristics of the knowledge economy is the increasing role of knowledge- intensive industries and innovative businesses in the state with corresponding changes in the structure of employment and qualitative redistribution of budget expenditure items. Knowledge becomes the main source of economic growth and a priority production resource [1]. Consequently, the needs for new professionals, investments, learning technologies, the creation and development of university infrastructure, changes in ethics and institutional norms are the challenges that universities face in the conditions of the sanctioned reality of Russia.
Penanganan Masalah Kesulitan Belajar Akademik

This research aims to find out the types or obstacles that occur to students in carrying out the learning process and show how to overcome them. In this study we used the library research method. Learning difficulties are one of the conditions in which learners cannot achieve the expected learning objectives. This is caused by a gap between intelligence and academic abilities such as dyslexia, dyscalculia and dysgraphia. Dyslexia is a condition where children experience obstacles in processing writing into spoken language in the form of a combination of abilities and difficulties that affect the learning process in one or more skills such as reading, spelling, and writing. Dyscalculia is a condition where children have difficulty in the most basic mathematical calculations in mathematical arithmetic operations. While Dysgraphia is a condition where children experience obstacles or difficulties in the process of expressing thoughts in written composition in terms of grammar (syntax), word meaning, and the ability to decompose words into their sound components or unite sounds into words (phonology). Identifying forms of learning difficulties needs to be done early if we already see something that is not in accordance with the child's development. With this, it is hoped that these difficulties can be overcome properly by experts.
Method for Adaptive Wavelet Filtering of Speech Signals Based on Daubechies Filters with Minimization of Errors in Finding Optimal Thresholds

The paper deals with the problem of adaptive wavelet filtering of speech signals based on Daubechies filters with minimization of errors in finding optimal threshold values. This approach is similar to estimating a speech signal by averaging it using a kernel that is locally adapted to the smoothness of the signal. In this case, a set of coupled mirror filters decomposes the speech signal in a discrete domain according to the orthogonal Daubechies wavelet basis into several frequency bands. Noise removal of speech signals is performed as a complete cutoff of the wavelet transform coefficients based on the assumption that their small amplitude values are noise. Thus, in the Daubechies wavelet basis, where coefficients with large amplitude correspond to abrupt changes in the speech signal, such processing preserves only the intermittent components originating from the input speech signal without adding other components caused by noise. In general, by equating small coefficients to zero, we perform adaptive smoothing that depends on the smoothness of the input speech signal. By keeping the coefficients of large amplitude, we avoid smoothing out sharp drops and preserve local features. Performing this procedure on several scales leads to a gradual reduction of the noise effect on both piecewise smooth and discontinuous parts of the speech signal. In view of this, the main task of the study is to adaptively generate micro-local thresholds, which will reduce the impact of additive noise on the pure form of the speech signal, and preserve significant wavelet coefficients of large amplitude that characterize the local features of the speech signal. Thus, as a result of our work, we have proved the feasibility of developing the presented method of wavelet filtering of speech signals with adaptive thresholds based on Daubechies wavelet analysis, which minimizes the loss of speech intelligibility and allows for noise removal depending on the properties and physical nature of the processed data.
Spatial Light Modulator-Based LiDAR System for Extended Field-of-View Scanning with Computer-Generated Holography

The aim of this paper is to propose a new method of scanning the field of view (FOV) in light detection and ranging (LiDAR) systems by utilizing computer-generated holography (CGH) method with a spatial light modulator (SLM). Based on replacing the objective in the telescope with the SLM, we were able to successfully scan large FOVs in LiDAR systems, confirming the effectiveness of this approach. The proposed conceptual breakthrough of this approach will be presented as part of the preliminary studying project for the LiDAR system in the satellite payloads.
Digital Holographic Interferometry: Out-of-plane measurement over a large dynamic range

Digital Holographic Interferometry is limited by the dynamic range of the deformation to be measured. In this presentation, we re-visit a technique that address these issues and maximizes the output from DHI measurements.
Research on the Reform of ROS Robot Programming Experiment Course for Applied Undergraduate Artificial Intelligence Majors

Through artificial intelligence-oriented teaching and scientific research exploration, remarkable results have been achieved in consolidating professional basic education, promoting disciplinary innovation, and cultivating high-quality application-oriented talents. This major is a multidisciplinary
Cognitive Practice in Creativity Understanding

Creativity is a universal category for describing human capabilities. In the conditions of the information age, ideas about the complexity of the ontology of a person and his existence in a variety of realities, discourses and roles deepen. The non-classical ontology of man has changed the ideas about the work of the researcher. Evidence moves from rigid definitions of philosophical constructs to their disclosure in dis-course. Cognitive practice arises in the discourse of human creative possibilities in the unity of reason and feeling. Creativity is existential in nature due to the perception of terms as ways of organizing a discourse about the creative being of a person in thought. The term cogito is an image of reality. It helps to consider creativity in the aspect of its mental (cognitive) understanding. It contains the meaning of the practice of research. It contains formalizable and non-formalizable aspects, logic and inner feeling. Compound terms combine being and knowledge, existence and knowledge. That term is “mind”. Cognitive practice in development moves from understanding the concept of intelligence to understanding the concept of mind as a technology of enactive thinking. Cognition becomes body mind. Cognitive practice is not limited to the study of human cognitive abilities. It is due to the creative power of the human mind.
Age and Gender Prediction using Face Recognition

Abstract: This project focuses on the development and implementation of a robust system for age and gender prediction through facial recognition technology. The increasing demand for intelligent systems capable of analyzing demographic information from facial images has motivated the exploration of advanced machine learning techniques. The methodology involves collecting a diverse dataset of facial images, annotating them with accurate age and gender labels, and employing state-of-the-art deep learning models for feature extraction and prediction. The deep neural network architecture utilized is trained on a large dataset to learn complex patterns and relationships within facial features.