Reviewerly/exHarmony huggingface dataset:
The dual pillars of academic excellence: Transformational leadership and organizational commitment

This research delves into the connection between transformational leadership, organizational commitment, and lecturer performance within the realm of higher education. Its primary objective is to comprehend how transformational leadership and organizational commitment influence lecturers and their overall effectiveness. The study encompassed 178 lecturers from Kadiri University. Data collection involved the administration of a well-structured questionnaire, and subsequent analysis was conducted using multiple linear regression techniques. The results underscore a robust and positive association between transformational leadership and lecturer performance. Furthermore, the role of organizational commitment in lecturer performance is noteworthy. These findings hold pragmatic significance for educational institutions, highlighting the imperative of cultivating transformational leadership and organizational commitment to augment faculty performance and cultivate dynamic learning environments.
Blockchain Technology Applications and Cybersecurity Techniques: A Literature Review

Blockchain is a relatively novice technology rapidly increasing as a next-generation solution for maintaining digital transactions and record-keeping issues. Blockchain technology can be used in financial services, healthcare facilities, social services, the governmental sector, the Internet of Things (IoT), etc. Regularly any new technologies have some challenges like security risks (threats and vulnerabilities). Among these blockchain challenges is managing the large-scale digital transactional system, which is potentially exposed to a multitude of threats. Thus, this paper introduces the categories of blockchain technologies’ cybersecurity vulnerabilities and some aspects of cybersecurity risk assessment.
Activities and Practices of Requirements Engineering in Agile Software Environments

Requirements are one of the important factors for software success. However, Requirements Engineering (RE) activities, in the Waterfall process model, are done sequentially in the analysis phase, which makes it difficult when RE practitioners think and reason about them in Agile Software Development (ASD) process model. RE practitioners need to find the established RE activities conventions in the ASD process model, especially with an increase of software companies, which transform to the ASD process model, in order to foster their transition to the new model. The objective of this study is to provide RE activities in ASD to allow RE practitioners to utilize the appropriate activity for specific ASD methodology. RE activities in ASD are handled repetitively and on a small scale, which makes them embedded in the development life cycle. This paper focuses on highlighting them in different ASD methodologies and discusses the practices that resolve the traditional Waterfall model issues. Although the ASD model has resolved some traditional RE issues, it introduced other issues, such as a consequence of trying to achieve an adequate balance between agility and stability. In addition, there is a lack of practices that target non-functional requirements.
Weighted Linear Dynamic Logic

We introduce a weighted linear dynamic logic (weighted LDL for short) and show the expressive equivalence of its formulas to weighted rational expressions. This adds a new characterization for recognizable series to the fundamental Schützenberger theorem. Surprisingly, the equivalence does not require any restriction to our weighted LDL. Our results hold over arbitrary (resp. totally complete) semirings for finite (resp. infinite) words. As a consequence, the equivalence problem for weighted LDL formulas over fields is decidable in doubly exponential time. In contrast to classical logics, we show that our weighted LDL is expressively incomparable to weighted LTL for finite words. We determine a fragment of the weighted LTL such that series over finite and infinite words definable by LTL formulas in this fragment are definable also by weighted LDL formulas. This is an extended version of [17].
ANALISIS KEBUTUHAN PENGEMBANGAN KOMPETENSI GURU DALAM MENULIS GUNA MENINGKATKAN MOTIVASI DAN KEBERHASILAN MENULIS BUKU

This study aims to analyze the initial needs of developing the competence of elementary school teachers as an effort to increase motivation and success in writing books. The target of this study was a teacher at SD Hang Tuah Cluster, Pemalang District, Pemalang Regency. The method used in this research activity is descriptive qualitative with research instruments in the form of questionnaires and interviews. The use of data analysis techniques includes three stages, namely data reduction, data presentation, and drawing conclusions. Based on the analysis of the instrument, data was produced that the motivation and success of teachers in writing books is very low. The total number of teachers targeted for the study was 36 people. The percentage of teacher motivation in writing books is only 31% and success in writing books is at 3%. The low motivation and success of teachers in writing books is caused by internal conditions that are not conducive (limited knowledge about authorship) and inadequate facilities and infrastructure (time and capital). The results of this study are useful as an initial analysis of the need for teacher competency development in writing in order to have a strong motivation to start work so that teachers who are skilled in writing and productive in creating books as one of the published works.
METHODS OF MASS MEDIA TERMINOLOGY CREATION FROM ENGLISH TO ARABIC

This study discusses creation methods used by terminologists to translate mass media terminology from English to Arabic. In this era of globalisation, various forms of mass media such as the print media, radio, television, film, broadcasting and the internet have already become integrated with society all over the world, including in the Arab world. Thus, the appropriate translation of media terminologies which originate from foreign languages, especially English, is important to ensure that Arabic media remains relevant in the mainstream, in addition to guaranteeing the sustainability and dynamism of the Arabic language itself as the main language of communication in the modern world. However, the linguistic discrepancies between English and Arabic pose a unique challenge to terminologists to produce accurate translations of the terminologies. A total of 40 media terms were selected from entry B of the Mustalahat Ilamiyyah dictionaryas data for this study. Then, the Malay equivalent of each terminology is identified by referring to the official website of Pusat Rujukan Persuratan Melayu developed by Dewan Bahasa dan Pustaka. Next, the list of Arabic terminologies is classified according to the method of Arabic terminology formation and analysed descriptively based on the views of al-Qasimi (2019). This study found that ishtiqaq (derivation) is the most frequently used terminology creation method, followed by tarkib (phrase), prefix and suffix, and tarib (arabization). This study will benefit students and researchers in the field of Arabic linguistics as well as Arab media companies by providing clarification on the methods commonly used by Arab terminologists in constructing technical terms in Arabic, especially in the field of mass media.
Hyper chaos followed by DCT and gyrator transform for image encryption

Color images can be encrypted using a hyperchaotic system in the Discrete Cosine Transform (DCT) and gyrator transform domains. These encryption techniques provide an added layer of security to protect sensitive image data from unauthorized access or tampering. The Red, Green, And Blue (RGB) components of the original color image are encoded into two-dimensional streams, respectively. These two-dimensional streams, representing the RGB components, are then processed by the display or printing device to recreate the full-color image. This paper proposes a new image encryption scheme that integrates DCT and the gyrator transform simultaneously. This innovative approach enhances the security and robustness of image encryption, making it suitable for a wide range of applications in data protection and transmission. Specifically, four chaotic sequences generated by a hyperchaotic system are blended into streams to synthesize complex sequences. Subsequently, the two-dimensional complex streams are scrambled using the discrete cosine transform and encoded back into an image format. Finally, the parameters in the hyperchaotic system using DCT and the gyrator transform improve the security of the proposed scheme. Theoretical and experimental analyses both confirm the security and validity of the proposed work.
A mobile app for removing duplicate multimedia images

With the development of multimedia technology and the popularity of smartphones, the collection of multimedia information from various applications has rapidly grown. This information encompasses text, images, video, and audio compositions. This multimedia information has not only transformed the way we communicate and share content but has also posed new challenges and opportunities in fields such as data analysis, content creation, and information management. Consequently, multimedia education has become the focal point for research institutions and businesses. The modern solution faces two main challenges: expensive uptime and comparative speed. Therefore, this study first introduces a washing method called Permutation (OPH) to reduce expensive working time. Furthermore, the study explores innovative techniques to enhance the comparative speed of the modern solution, ultimately aiming to achieve a more efficient and cost-effective system. With the OPH, a permutation wash (GOPH) has been developed, along with several useful techniques to address pressure changes. This development is based on the fact that most multimedia files differ from one another. A new hashing method, known as Hierarchical Permutation Hash (HOPH), has been created to enhance productivity. Extensive testing with real multimedia files clearly demonstrates that HOPH is five to seven times faster than Minis' while maintaining the same level of accuracy. HOPH achieves this remarkable speed improvement by efficiently leveraging hierarchical structures in data, making it a promising solution for a wide range of multimedia applications.
Wide. Open. Science.

This month, we explore how researchers are advancing and expanding the reach of Earth and space sciences.
THE DEVELOPMENT OF DIGITAL COMPETENCIES AMONG TEACHERS IN THE CONTEXT OF TRANSITION TO THE «UNIVERSITY 4.0»

The article is devoted to describing the digital skills required of pedagogical employees to function in the contemporary educational environment. Also, the article discusses potential methods for developing prospective teachers’ digital capabilities in a university setting through the creation of contemporary, pertinent, and in-depth content as well as instructional, methodological, and informational assistance. The most popular methods for structuring the competency model of job candidates for Industry 4.0, including behavioral and digital skills, are covered in the article. On the basis of an analysis of the likelihood of achieving particular performance indicators in the sphere of vocational education, the limitations in the growth of graduates’ digital capabilities were demonstrated. Different interpretations of the traits of digital competences in Kazakhstan and other countries are offered to create a cohesive approach. The degree of digital literacy of contemporary future teachers was evaluated to examine the viability of developing a digital learning environment at universities. The influence of the digital economy on the development of a set of key abilities and the education of experts in demand in contemporary society is what gives this piece its relevance. The majority of models and frameworks are concerned with evaluating university teachers’ level of digital competences, which are a collection of knowledge, abilities, and attitudes required for a teacher to use technology effectively. The impact of the digital economy on the development of a set of core competences and the education of experts in demand in the contemporary world. Keywords: digital competencies, successful pedagogical activity, modern educational space, ICT competencies.
學部及び朝鮮総督府の敎科書國定化に関する一考察

&lt;JPN&gt; &#x0D; 本論文では1895年から1945年まで韓国の教科書国定化がどのような過程を経て展開されたのかを把握するために、教科書編纂および発行を「小学校令」時期(1895-1905)、「普通学校令」時期(1906-1910)、「朝鮮教育令」時期(1910-1945)に分けて考察した。さらに、日本での教科書の国定化過程と国定制を採択した意図にも注目した。本論文の結果をまとめると次のようになる。第一に、各時期の教科書の内容構成に関して、「小学校令」時期には近代国家の形成や民族の独自性、自主性を強調した教科書が発行されたのに対し、「普通学校令」時期には日本人官僚の積極的な関与により、日本精神や日本倫理が内容となっている教科書が大きな比重を占めた。これは「朝鮮教育令」時期の教科書編纂につながり、教科書には植民地主体として備えるべき徳目や内鮮一体、國体明徴などを強調する内容が含まれた。第二に、各時期の教科書編纂および発行は効率性の原則が適用された。特に、「普通学校令」時期と「朝鮮教育令」時期には日本で発行された教科書が翻訳や編集という過程を経て学部や朝鮮総督府から刊行された。このような関連性は第2次朝鮮教育令以後の学校規則にも現れた。すなわち、教科書発行主体として日本の＇文部大臣＇が登場したのは内地延長や一視同仁というスローガンの下で日本の国定教科書を植民地で使用できるための措置であった。第三に、各時期の教科書編纂および発行政策を通じて国民と国家の関係を見ると、「小学校令」時期には韓国国民の教育水準を向上させ、国民としての自覚を志向しようという意図が強かった。反面、「普通学校令」時期と「朝鮮教育令」時期には我が民族の自負心をなくすための思想統制やイデオロギー伝授という意味が強く内包されていた。第四に、これは日本で教科書国定制が採択された理由とも脈を同じくする。 1903年の日本における教科書の国定化には国民の自由な思想を統制･抑圧し、国家のイデオロギーを強制するための政府の意図が強く含まれていた。これはそのまま統監府や朝鮮総督府の植民地教育政策につながり、「朝鮮教育令」時期を通じて画一的で抑圧的な国家主義教育が強化されていった。&#x0D; &lt;ENG&gt;&#x0D; This paper examines the nationalization of textbooks in Korea from 1895-1945, dividing the timeline into three periods: the “Elementary School Ordinance” (1895-1905), “Ordinary School Ordinance” (1906-1910), and “Joseon Education Ordinance” (1910-1945). The study aimed to clarify the process of nationalization of textbooks and understand the nature of textbook compilation in Korea by reviewing Japan's intention. The results are summarized as follows; First, in terms of the textbook contents in each period, textbooks emphasizing the formation of a modern state, national independence, and independence were issued during the “Elementary School Ordinance” period, while textbooks containing Japanese ideology accounted for a large proportion due to the active involvement of Japanese officials during the “Ordinary School Ordinance” period. This can also be seen in the textbook contents from the “Joseon Education Ordinance” period, which included emphasizing the virtues, internal unity, and national emblem that students were expected to have as colonial subjects. Second, the principle of efficiency was applied in the compilation and publication of textbooks in each period, particularly during the “Ordinary School Ordinance” and “Joseon Education Ordinance” periods.
Optical Character Recognition (OCR) Application For Image To Braille Typeface Conversion

The Capstone Research entitled Optical Character Recognition (OCR) Application for Image To Braille Typeface Conversion is a type of quantitative research and the developers have focused on developing this application project that can convert text-containing images into a braille PDF document that is ready to print. The application is designed to benefit the educational environment for students with visual impairments by giving them access to a novel discovery for the processing of educational materials tailored to their specific needs. A total of 10 experts and 20 co-developers were invited to evaluate the application project according to its functionality, responsiveness, performance, and usability (user satisfaction). Data were gathered through Microsoft Forms and analyzed using one of the central tendencies, the mean score for each category. Results showed that Product Functionality has a mean score of 4.59, Product Responsiveness with 4.52 and Product Performance with 4.51 which all coincide with the mean description present in the interpretation table of Excellent. On the other hand, the Product Usability (User Satisfaction) has a mean score of 4.46, which coincides with the mean description of Good. After analyzing all categories, the overall mean score is 4.52 which has the corresponding description of Excellent. This means that the application project is highly acceptable, and thus, fulfilling the intended functions needed by the end users. Keywords: Optical Character Recognition (OCR), Braille, Typeface Conversion, Text Extraction, Applicati
Image Segmentation on Convolutional Neural Network (CNN) using Some New Activation Functions

Image segmentation means subdividing the image into different objects. We use different methods for the segmentation of images. For getting different objects from a single image, we generally apply old methods, such as Fuzzy C-means, and K-means clustering techniques. In the case of getting different objects from huge amounts of image datasets, we generally apply the CNN technique. The Activation Function (AF) plays a major role during the segmentation of images through CNN. We can increase the power of CNN using activation functions. Generally, the exponential activation function is used for very complex and non-separable types of problems. So, in this paper, we segment the triangle and CamVid datasets on CNN using NewSigmoid AF and root2Sigmoid AF. Both AFs are exponential activation functions. We made a 12-layer CNN for the triangle segment and a 13-layer CNN for the CamVid segment. After that, we compare four activation functions on both CNNs. These activation functions are NewSigmoid, Relu, root2sigmoid, and Tanh. On the triangle image dataset, we have achieved global accuracy of 96.29% through NewSigmoid AF, 95.77% through Relu AF, 97.02% through root2sigmoid AF, and 96.47% through Tanh AF. On the CamVid dataset, we have achieved global accuracy of 93.97% through NewSigmoid AF, 94.01% through Relu AF, 94.19% through root2sigmoid AF, and 94.13% through Tanh AF. We also check the validation accuracy of the CamVid dataset. We take 10% of images for validation purpose. For the same dataset and same CNN network, we found validation accuracy of relu is 96.04%, root2simgoid is 96.26%, tanh is 96.20% and NewSimgois is 96.26%. Therefore, we can say that the root2sigmoid AF gives a better result as compared with NewSigmoid, Relu, and Tanh AFs.
Eight Reasons Why You <i>Must</i> Go to the BIALL Conference

Abstract With another highly successful BIALL Annual Conference behind us, LIM co-editors Jas and Mike Breslin – the latter a first-time attendee this year, the former a veteran of 18 conferences – explain why this really is an unmissable event.
The Role of Media in the Preservation and Promotion of Archaeological Heritage

Globally, information and communications technologies are opening new doors for experiencing and exploring ancient heritage through cross‐media interaction. This research paper is an attempt to understand and highlight the role of Pakistani media that it can play to save and preserve the historic legacies of our nation for future generations. We have witnessed that ever since the liberalization of media in Pakistan around 1990, it has been growing at a remarkable pace and has matured. It has experienced massive technological changes both in traditional and new media mores. We have also witnessed its positive role in highlighting some key issues, which our nation has and is currently facing.
The production and distribution of scientific knowledge: A global perspective

The educational enterprise is not omnipotent and is heavily constrained by natural, socioeconomic and pedagogical factors. The present research aims to study the state of the production and distribution of scientific and mathematics knowledge worldwide using the Programme for International Student Assessment (PISA) 2018 big data bank. The first finding is that the distribution of this knowledge shows that about two-third of the world's population belongs to quality groups one, two, and three, representing the low-achieving section of the proficiency scale. The second finding is that there is practically no sign of domain specificity. Thus, the learning problems do not reside in the curriculum but in some higher cognitive factors such as general intelligence or developmental stage. It is high time to adopt educational policies oriented toward the real world rather than an aspired one. Keywords: PISA 2018, scientific literacy, quality groups, proficiency distribution, educational efficiency, individual differences.
Impact of Feature engineering for Improved Sentiment Analysis in Amazon Product Reviews Using K-Nearest Neighbor

Online reviews are an important factor that encourages consumers to make purchases through e-commerce. However, it is challenging to objectively assess the sentiments expressed by actual consumers due to the prevalence of fraudulent reviews. This study focuses on sentiment analysis and seeks to uncover the best feature combinations based on review and reviewer centric approach. The results of the study show that the combination of feature Rating, VerifiedPurchase, ReviewLengths, and (CV+TF-IDF) = 1400 words with the application of KNN classification provides the best accuracy rate of 83%. The results of this study can assist consumers in making purchasing decisions and seller in increasing the value of their products and services based on the feedback provided by customers.
Machine learning approach to customer sentiment analysis in twitter airline reviews

Customers typically provide both online and physical services they use ratings and reviews. However, the volume of reviews might grow very quickly. The power of machine learning to recognize this kind of data is astounding. Numerous algorithms that could be employed for job of sentiment analysis have been developed to categorize tweets about airline sentiment into positive, neutral, or negative categories, this study compares the effectiveness algorithm for machine learning Naive Bayes (NB), Logistic Regression (LR), Decision Tree (DT), Support Vector Machine (SVM), Adaboost, Extreme Gradient Boosting (XGB), Light Gradient Boosting Machine (LGBM), and Random Forest (RF) dividing the Twitter airline sentiment data into positive, neutral, or negative categories using the TF IDF model. The experiment involved two phases of activity: a classification algorithm utilizing SMOTE and sans SMOTE with Stratified K-Fold CV algorithm. With the RF model, the greatest performance accuracy for SMOTE is 97.56%. Without SMOTE, the RF with a value of 92.21% provides the maximum performance accuracy. The findings demonstrate that SMOTE oversampling can improve sentiment analysis accuracy.
Survey on Distributed AI-Enhanced Deep Learning for Predicting Chemo Response in Non-Hormone Receptor Breast Cancer

This study offers a novel method for forecasting the response to chemotherapy in non-hormone receptor breast cancer, a difficult and complicated condition. TensorFlow-powered Spatial Temporal Integration (CNN-RNN) Architecture is used in the methods to integrate clinical data and histological images. Heuristic-driven deep learning techniques use domain-specific knowledge to build models and choose features. Using clinical knowledge, Hybrid Differential Evolution and Particle Swarm Optimization (DE-PSO) optimizes the model's parameters. Because Lime offers comprehensible justifications for the model's predictions, its adoption guarantees transparency and interpretability. Furthermore, federated learning is used in a distributed training approach to preserve scalability and safeguard patient data privacy. This method offers precision and empathy for better treatment decisions for non-hormone receptor breast cancer by fusing AI with clinical expertise.