Reviewerly/exHarmony huggingface dataset:
Sociological measurement of the happiness index in Central Asian Countries

The relevance of scientific work in the field of studying the measurement of the happiness index in the countries of Central Asia is due to the fact that the assessment of the psychological state of society is a significant problem in the social sciences and humanities. The purpose of the study is to analyse the happiness index, the mechanism of its social measurement, which will be based on a comparative analysis of this indicator in Central Asian countries, in particular, on the example of such countries as Kazakhstan, Tajikistan, Turkmenistan, Uzbekistan, and Kyrgyzstan. The key objectives and directions of this study can be achieved through the use of different methodological approaches, which can reveal both the theoretical and practical components of the research. Such methodological approaches include theoretical and methodological approach, dialectical methodological approach, method of deduction, method of induction, method of synthesis, method of logical analysis, and others. In the course of the research work social and psychological aspects of the concept of the “happiness index” were identified, an assessment of international indices that are designed to conduct sociological change in the index of happiness as a level of quality of life was provided, and a comparative analysis of sociological measurement of the happiness index in Central Asian countries, which was based on an analysis of this index in such countries as Kazakhstan, Tajikistan, Turkmenistan, Uzbekistan, and Kyrgyzstan was conducted. The results of the study demonstrated that the quantitative assessment based on the index of happiness in the countries of Central Asia has a fairly low level of public satisfaction with the quality of life, therefore, an important aspect of the research work is also to identify the problems that impede this and to define the methods to solve them.
The Story Telling as a Solution of Student’s Difficulties in English Speaking at Islamic of Senior High School Sirojut Tholibin

Speaking is one of the most important of the four skills namely listening skills, speaking skills, reading skills and writing skills. Talking is one action to convey information and express ideas and feelings. This research is conducted to describe students' difficulties in speaking English lessons, factors that make it difficult for students to speak English, and students strategies to overcome their difficulties in speaking English lessons in twelfth grade MA Islam Sirojut Tholibin 2022/2023. This study uses a qualitative method. MA Sirojut Tholibin class XII IPA selected by the researcher as a sample consisting of 32 students. In collecting data, researchers used observation, interviews, and questionnaires. Data collected analyzed by reducing data, presenting data, drawing conclusions and verification. Researchers use the results of the pretest and posttest, to show reliability data. From the data analysis, the researcher found that each student was different difficulty in speaking, there is lack of vocabulary, poor pronunciation, nothing to say, lack of motivation, fear of being wrong, shy, using mother tongue. There are factors that cause difficulties in speaking English in English lessons. Other factors are internal factors, students do not have an interest in learning to speak, classroom conditions, student environment. Students have strategies for coping their difficulty in speaking. Students join English clubs or English courses for improve their speaking, so they can practice speaking English and ask them friend or teacher to improve their English. Students memorize vocabulary and write short stories to improve their speaking skills.
Audiovisual Media Influence on Skills Writing Job Application Letter Class XII Students at SMAN 1 Pangkalan Lesung

The emergence of problems of decreased learning activities and interest in students' writing skills is still low. This study discusses the influence of audiovisual media on the job application letter writing skills of grade XII students at SMAN 1 Pangkalan Lesung. The purpose of this study was to determine the influence of audiovisual media on job application letter writing skills in grade XII students at SMAN 1 Pangkalan Lesung. The benefits of research to develop learning media through appropriate educational methods so that they can influence student learning with potential and character. Research methods are obtained with pre-experimental designs, research instruments in the form of pretests and postes job application letter writing skills. Research data analysis techniques use descriptive statistical test techniques, normality tests, and homogeneity tests. The results of the study are audiovisual media affect the learning outcomes of job application letter writing skills for grade XII students at SMAN 1 Pangkalan Lesung, by giving the impression of a pleasant student learning experience, so that students become more motivated, learning becomes less boring, and makes communication easier to achieve effective and efficient learning goals.
Students’ Experience in Learning English Vocabulary Using Video on Youtube at The Eleven Grade of SMA Al-Washliyah 3 Medan in 2022-2023 Academic Year

This research is find out the students’ experiences and meaning of experiences in learning English using video on YouTube notably as extra resources for people learning English at home. The study attempt to answer research question, that is why do students’ experiences matter when learning English vocabulary using video on YouTube? That question were answered through a series of observation and interviews. All of the students were asked to reflect on their experiences and what those events meant to them. This research was conducted in SMA AlWashliyah 3 Medan. There were five students’ participants. The phenomenological investigation was applied to the research. Data has a narrative structure. After that, it was triple checked using member checking. The result of the analysis reveals that students’ experience some feelings, thought, and activities in learning. Before learning activities, learners bring the background of knowledge and learning style in their learning English using video on YouTube. During learning activities, the students experience some feelings such as lazy, happy, comfortable and motivated to learn. The students also think about the vocabularies which increase during the process of learning. The results are that video on YouTube offer a new strategy of learning English which is interesting and that video on YouTube provide audiovisual materials in which the students learn English vocabulary.
Logic-based similarity

This paper develops a {\em qualitative} and logic-based notion of similarity from the ground up using only elementary concepts of first-order logic centered around the fundamental model-theoretic notion of type.
Online Platt Scaling with Calibeating

We present an online post-hoc calibration method, called Online Platt Scaling (OPS), which combines the Platt scaling technique with online logistic regression. We demonstrate that OPS smoothly adapts between i.i.d. and non-i.i.d. settings with distribution drift. Further, in scenarios where the best Platt scaling model is itself miscalibrated, we enhance OPS by incorporating a recently developed technique called calibeating to make it more robust. Theoretically, our resulting OPS+calibeating method is guaranteed to be calibrated for adversarial outcome sequences. Empirically, it is effective on a range of synthetic and real-world datasets, with and without distribution drifts, achieving superior performance without hyperparameter tuning. Finally, we extend all OPS ideas to the beta scaling method.
LAVA: Data Valuation without Pre-Specified Learning Algorithms

Traditionally, data valuation (DV) is posed as a problem of equitably splitting the validation performance of a learning algorithm among the training data. As a result, the calculated data values depend on many design choices of the underlying learning algorithm. However, this dependence is undesirable for many DV use cases, such as setting priorities over different data sources in a data acquisition process and informing pricing mechanisms in a data marketplace. In these scenarios, data needs to be valued before the actual analysis and the choice of the learning algorithm is still undetermined then. Another side-effect of the dependence is that to assess the value of individual points, one needs to re-run the learning algorithm with and without a point, which incurs a large computation burden. This work leapfrogs over the current limits of data valuation methods by introducing a new framework that can value training data in a way that is oblivious to the downstream learning algorithm. Our main results are as follows. (1) We develop a proxy for the validation performance associated with a training set based on a non-conventional class-wise Wasserstein distance between training and validation sets. We show that the distance characterizes the upper bound of the validation performance for any given model under certain Lipschitz conditions. (2) We develop a novel method to value individual data based on the sensitivity analysis of the class-wise Wasserstein distance. Importantly, these values can be directly obtained for free from the output of off-the-shelf optimization solvers when computing the distance. (3) We evaluate our new data valuation framework over various use cases related to detecting low-quality data and show that, surprisingly, the learning-agnostic feature of our framework enables a significant improvement over SOTA performance while being orders of magnitude faster.
On the existence of solutions to adversarial training in multiclass classification

We study three models of the problem of adversarial training in multiclass classification designed to construct robust classifiers against adversarial perturbations of data in the agnostic-classifier setting. We prove the existence of Borel measurable robust classifiers in each model and provide a unified perspective of the adversarial training problem, expanding the connections with optimal transport initiated by the authors in previous work and developing new connections between adversarial training in the multiclass setting and total variation regularization. As a corollary of our results, we prove the existence of Borel measurable solutions to the agnostic adversarial training problem in the binary classification setting, a result that improves results in the literature of adversarial training, where robust classifiers were only known to exist within the enlarged universal $\sigma$-algebra of the feature space.
The Importance of Learning English Literacy for Accounting in Higher Education: Benefit and Drawbacks

This qualitative research aims to explore the importance of learning English literacy skills for English as a Foreign Language (EFL) accounting students in higher education. The data were collected through in-depth interviews, focus group discussions, and document analysis, and analyzed thematically. The findings indicate that developing English literacy skills offers numerous benefits for EFL accounting students, such as building literacy competence, enhancing employability, improving communication skills, facing globalization, understanding accounting terms and subjects, and identifying errors in accounting. However, the study also identified some drawbacks, time and effort including, Balancing Language Learning with Technical Accounting Skills Development and linguistic difficulties and frustration. The study suggests that educational institutions and policy makers should develop comprehensive strategies that support EFL accounting students in acquiring English literacy skills while addressing the potential challenges they may encounter. These findings have important implications for accounting education, highlighting the need to provide adequate resources and support to EFL accounting students to help them develop their English literacy skills and succeed in their academic and professional pursuits
Text, Image and Audio Steganography

Abstract: Steganography refers to the concealment of confidential data within a common medium, like a text, image, or audio file, without altering its original appearance, to evade detection. This method is used for several purposes, including protecting data privacy, preventing unauthorized access to data, and ensuring safe information transmission over insecure networks. While steganography can be used for legitimate purposes such as by military, law enforcement, and journalism, it can also be employed for malicious activities like cybercrime and terrorism. The least significant bit (LSB) of each letter in text &amp; audio and the LSB of each pixel in images are altered in steganography to make the alterations invisible. Advanced steganography algorithms like Masking &amp; Filtering and Encrypt &amp; Scatter have improved security against steganalysis assaults while producing higher-quality stego images. The method’s capability for concealing text with an unlimited hidden text size in text, audio, and images will be employed in the outcome.
Blockchain Solution for Public Distribution System

The Public Distribution System (PDS) in India is essential to supply food grains produced by farmers to the people who are below poverty line. It is a system for distribution of food grains at affordable prices. However, the current PDS system is plagued by various issues, delayed payments and mismanagement of stock being the primary one. This work aims to use blockchain technology, one of the cutting edge technologies, to overcome these issues and make the PDS a digital, secure, transparent and scalable system. Blockchain provides transparency such that the user can track food grains and all the key data would be recorded throughout the supply chain. The system requires minimal human intervention. To facilitate payments to the farmers and millers business logic through smart contract is implemented. The proposed PDS blockchain system was implemented in public blockchain and was tested for different use cases.
Healthcare Data Management System Using Blockchain

The healthcare industry generates vast amounts of data that must be managed and stored securely. Blockchain technology has the potential to revolutionize healthcare data management by providing a secure, decentralized, and tamper-proof way to store and share data. Today's medical data management systems require data transparency, traceability, Immutability, auditing, lineage, flexible access, trust, privacy, and security. Also, most of the existing Healthcare systems used to manage data are centralized and pose potential risks in the event of a single point of failure Natural disaster. Blockchain is an emerging and disruptive decentralized technology that has the potential to become an important technology. This research will show you the use of blockchain for medical data management systems can stimulate innovation and make great strides in improvement. It also describes the key benefits of hiring Opportunities in blockchain technology and the healthcare industry. The purpose of this research is to explore the implementation of blockchain technology in health data management and identify related challenges.
Normal proofs and tableaux for the Font-Rius tetravalent modal logic

Tetravalent modal logic (T ML) was introduced by Font and Rius in 2000; and it is an expansion of the Belnap-Dunn four{valued logic FOUR, a logical system that is well{known for the many applications it has been found in several fields. Besides, T ML is the logic that preserve degrees of truth with respect to Monteiro's tetravalent modal algebras. Among other things, Font and Rius showed that T ML has a strongly adequate sequent system, but unfortunately this system does not enjoy the cut-elimination property. However, in [16], it was presented a sequent system for T ML with the cut{elimination property. Besides, in this same work, it was also presented a sound and complete natural deduction system for this logic. In the present work, we continue with the study of T ML under a proof-theoretic perspective. In first place, we show that the natural deduction system given in [16] admits a normalization theorem. In second place, taking advantage of the contrapositive implication for the tetravalent modal algebras introduced in [17], we define a decidable tableau system adequate to check validity in the logic T ML. Finally, we provide a sound and complete tableau system for T ML in the original language.These two tableau systems constitute new (proof-theoretic) decision procedures for checking validity in the variety of tetravalent modal algebras.
Smart School Application : Enhancing Administrative Efficiency, Communication, and Personalized Learning in Education

In recent years, there has been an increasing demand for digital technologies in education, and smart school applications are becoming increasingly popular. Smart school applications offer a range of features, including e-library, attendance, leader board, quizzes, event calendar, fees management with online payment, and news or circular sections. This review paper aims to provide an overview of the features and benefits of smart school applications. The paper discusses the potential advantages of using these applications, including improved efficiency and communication, increased student engagement, and enhanced learning outcomes. The paper also explores the challenges associated with the implementation of smart school applications and suggests strategies for successful deployment. Finally, the paper highlights some of the key considerations for schools and educational institutions considering the adoption of smart school applications.
The Use of Digital Technologies in the Professional Socialisation of Future Social Workers in Higher Education

The aim of the article is to analyse the application of digital technologies in the process of professional training and professional socialisation of future social workers in departmental, civil and confessional-oriented institutions of higher education. The results of the study allow determining the specific features of professional socialization in the context of digitalization of learning in different types of higher education institutions and draw conclusions about the digital competences formed in the process of learning. The digital competences of a future police officer encompass three basic areas: the skills needed to support everyday professional activities, the skills to handle digitally restricted information, and the special skills to fight crime. In civilian universities, the basic digital competences of future professionals include: competences in readiness to form a system of network society values; competences in the development of motivation for search activity and self-development; instrumental-operational competences, etc. Confessional-oriented universities have their own structured and justified opinion on digitalization of education and training, which is based primarily on the views of the Russian Orthodox Church as a social institution and its head of the Church– His Holiness Patriarch of Moscow and All Russia, which are based on the tenets of the Orthodoxy. In the conclusion we conclude that the problematic of digitalization of the modern learning process is relevant for scholars and practitioners of various branches of social and humanitarian knowledge, as well as for future specialists of the social sphere studying in different types of universities.
Universal Deep Network Steganalysis of Color Based on Channel Representation

Up to now, utmost being steganalytic styles are designed for grayscale images, and they aren't suitable for color images that are extensively used in current social networks. To begin with, we divide the input image based on the different embedding spaces of its colors, resulting in three separate channels.. The proposed system includes preprocessing, convolutional, and bracket modules. To save the steganographic vestiges in each color channel, in preprocessing module, we originally separate the input image into three channels according to the corresponding embedding spaces(i.e RGB for spatial steganography and YCbCr for JPEG steganography), and also prize the image residuals with 62 fixed high- pass pollutants, eventually concatenated all abbreviated residuals for posterior analysis analysis rather than adding them together with normal complication like being CNN- grounded steganalyzers. To accelerate the network confluence and effectively reduce the number of parameters, in convolutional module, we precisely design three types of layers with different roadway connections and group complication structures to further learn high- position steganalytic features. In bracket module, we employ a global normal pooling and completely connected subcaste for bracket
Sign Language Based Video Calling App

Deaf and hard of hearing people communicate with others and within their own communities by using sign language. Computer recognition of sign language begins with the learning of sign gestures and continues through the production of text and speech. There are two types of sign gestures: static and dynamic. Both gesture recognition systems are crucial to the human community, even if static gesture recognition is easier than dynamic gesture recognition. We have conducted research on the steps required to convert static American sign language (ASL) to readable text and selected the best available methods to do so. Examined general steps are the data collection, pre-processing, transformation, feature extraction, and classification. There are also some recommendations for further study in this field.
Structural Analysis of the Novel Dima'un fi Qasr al-Chamra by Ehab Farouk Hosny: Important Cultural Stories in the History of Islamic Civilization in Spain

This research aims to conduct a structural analysis of the novel Dima'un Fi Qasr al-Chamra by Ehab Farouk Hosny. This novel raises an important cultural story in the history of Islamic civilization in Spain. It tells the story of a beautiful woman from Egypt, named Sarah, an archaeologist who researches Islamic heritage buildings both in her own country and in other countries. It tells the history of Andalusia, now Spain, starting from discovering a map buried in one of the rooms in Sultan Hasan's mosque in Cairo. The map was a secret document of the Alhambra belonging to the great scientist Al Zahrawi (Albucasis), containing a chemical composition to treat cancer. This paper has two main objectives: the practical and theoretical objectives. The realistic goal is to reveal the intrinsic and coherent elements and the interrelationship between one part and another. Meanwhile, the academic goal is to discover a secret document belonging to el-Zahrawi, a scientist, containing a cancer drug's composition. To remind readers that the discovery of personal papers, in any case, should not be announced in public because it can be dangerous and will cause various problems in obtaining certain benefits and goals. The theory used is a structural theory, which focuses on literary works viewed as a unified and integrated structure. The technical method is the structural method, which works structurally by revealing and describing the intrinsic elements in "Dima'un Fi Qashril-Chamra" by Ehab Farouk Hosny and connecting the mutual relationships between the parts. This technique uses formalism representing literary works such as character, plot, motif, theme, and language. The method used in this research is library research. Library study is a technique of collecting data and information by examining written sources such as scientific journals, reference books, literature, etc., related to this discussion. Based on its nature, this research is classified as qualitative research using descriptive analysis techniques.