Reviewerly/exHarmony huggingface dataset:
Computational linguistics in Sanskrit Grammar

The grammar of the Sanskrit language has a complex verbal system, rich nominal declension, and extensive use of compound nouns.It was studied and codified by Sanskrit grammarians from the later Vedic period.The study of language in the Indian tradition began with the desire to maintain the purity of the dominant language and also to maintain the authenticity of scripture and ascertain the authenticity of its transmission.The Vedas were the primary scriptures and they were originally transferred orally.The Vedas also contained hymns that were part of rituals, methods to maintain accuracy of speech were necessary, and a sophisticated system of phonetics was employed to codify the language of ritual to keep it free from change.The earliest attempts of this are seen in 'Padapatha', in around 1000-700 BCE, which extracted individual words from the continuous recitation of the hymns-'Samhitapatha'-and also morphologically analyzed the words into roots and affixes.Vyakarana, which is grammar; and Nirukta, which is etymology and lexicography.The 'vedangas' were developed to help the student to correctly interpret the scriptures.This includes creating teaching aids, learning tools, online resources, along with lectures and textbooks.These tools include language teaching for sanskrit and Indian languages.The educational tools make use of the vast amount of research done by scholars in various fields of linguistics and computational linguistics.While the study of phonetics and metrics helped in the development of language science, the major impetus came from the study of vyakrana and nirukta (Deshpande 2016).Nirukta is a treatise by Yasaka on the etymology of rare and ambiguous Vedic words, and the morphological analysis of words in terms of roots and suffixes, and grammatical description of a set of words in terms of parts of speech was already available in the Padapathas.Panini's 'Ashtadhyayi' is a treatise in the vyakarana domain that contains 4000 sutras that provide an intricate system of rules that interpret a confounding array of linguistic matters, like the composition of nouns and case relations, the transformation of roots and nouns using suffixes, accent changes in wordformation and sentence construction.Patanjali's 'Mahabhashya' discusses Panini's grammar and other commentaries on it like Katyayana's Vrittikas, and deals with technical as well as philosophical issues of Panini's grammar.'Siddhanta-Kaumudi' is a commentary by Bhattoji Dikshit, who reordered the sutras in a way that makes them easy to follow for a student but distorts the architecture of the system designed by Panini. Panini's AshtadhyayiPanini was a Sanskrit grammarian who gave a comprehensive and scientific theory of phonetics, phonology, and morphology.Sanskrit was the classical literary language.Panini is considered the founder of the language and literature.Panini wrote Sanskrit Grammar.Pāṇini is known for his text Aṣṭādhyāyī, a sutra-style treatise on Sanskrit grammar, 3,996 verses or rules on linguistics, syntax and semantics in "eight chapters" which is the foundational text of the Vyākaraṇa branch of the Vedanga.
New Instances in IOT Technology

Abstract: Future of the Internet of Things with enabled Artificial Intelligence, block chain technology, Big data technology, cloud AWS - Azure endpoints with little coding or no coding to manager enamors powerful device management. Few of the application of Internet of Things like B2C sector of summers like smart homes, smart appliances and elderly care. In infrastructure area in internet of things like smart city, smart energy &amp; utilities and environmental monitoring. In the Commerce area in the Internet of Things like Medical &amp; healthcare, transportation and building accommodations. Coming to Industry and farming area in the Internet of Things like smart manufacturing and smart agricultures and more. Coming to IT Datacenters need to use Internet of Things and IoT enabled ship, airplanes and trains exceptional application going use in multiple manners. IoT application development services enables on all IoT devices / machines connect virtually with global wireless standard using fifth generation 5G mobile network (ultra low latency internet via embedded IoT devices). In Asia-Pacific zone, 5G adoption is going to hit 4 billion in 2025 as per Ericson mobility report.
Pengaruh Pemanfaatan Perpustakaan Sekolah Terhadap Hasil Belajar Siswa

The present study aimed to determine the effect of the utilization of the school library on students’ learning outcomes in the economics subjectin class X of social sciences at SMA Negeri 1 Suwawa Timur. This study employed a quantitative approach with a survey research method. The data used were primary data obtained from distributing questionnaires to students at SMA Negeri 1 Suwawa Timur, with a total sample of 41 respondens. At the same time, the data analysis technique used simple linear regression. The analysis results of the coefficient of determination in the table denoted that the adjusted coefficient of determination or the R-Squared value was 0,215 or 21,5%. This value signified that 21,5% of the variability of students’ learning outcomes could be explained by the variable of the utilization of the school library. In comparison, the remaining 78,5% was explained by other variables that were not examined in this study.
Sistem Informasi Penentuan Harga Pokok Produksi Pada Nirwana Collection Dengan Metode Job Order Costing

Nirwana Collection is a shell craftsman in Kendal Regency. Nirwana Collection does not yet have a system for calculating the cost of production. In accounting records done manually, the data is not well organized and has not produced information as expected.&#x0D; Nirwana Collection produces goods based on orders, the calculation of the cost of production is still not correct, because it does not calculate other costs incurred and only focuses on raw materials. This of course results in an inaccurate selling price and results in a profit that is not as expected.&#x0D; The Accounting Information System for the Cost of Production at the Nirwana Collection with the Job Order Costing method can process recordings and transactions at the Nirwana Collection more effectively, as well as making it easier to produce production cost reports quickly and accurately.
Analisis Latensi Video Streaming Antara Jaringan Berbasis Local Area Network dan Web

The current era is growing Live streaming which includes audio and video data. This research method collects data through the results of measuring Video Streaming latency (delay time) on variations of Local Area Network and Web-based computer networks. Based on the analysis of measurement results, the latency value (delay time) of Video Streaming on Local Area Network-based devices using Quality of Service (QoS) obtained a value of 8.58 ms and is smaller (optimal) compared to Web-based networks.&#x0D; Keywords : Quality of Service, latency, LAN, Web
HWCD: A hybrid approach for image compression using wavelet, encryption using confusion, and decryption using diffusion scheme

Abstract Image data play important role in various real-time online and offline applications. Biomedical field has adopted the imaging system to detect, diagnose, and prevent several types of diseases and abnormalities. The biomedical imaging data contain huge information which requires huge storage space. Moreover, currently telemedicine and IoT based remote health monitoring systems are widely developed where data is transmitted from one place to another. Transmission of this type of huge data consumes more bandwidth. Along with this, during this transmission, the attackers can attack the communication channel and obtain the important and secret information. Hence, biomedical image compression and encryption are considered the solution to deal with these issues. Several techniques have been presented but achieving desired performance for combined module is a challenging task. Hence, in this work, a novel combined approach for image compression and encryption is developed. First, image compression scheme using wavelet transform is presented and later a cryptography scheme is presented using confusion and diffusion schemes. The outcome of the proposed approach is compared with various existing techniques. The experimental analysis shows that the proposed approach achieves better performance in terms of autocorrelation, histogram, information entropy, PSNR, MSE, and SSIM.
Postgraduate Science Students’ Impressions and Experiences of Online Pedagogical Practices: Implications for Technology-Enhanced Pedagogy

This study explores the postgraduate science teachers’ conceptions and experiences of online pedagogical practices in diverse school contexts. Embracing technology-enhanced pedagogy remains a key strategic imperative within the context of evolving pedagogical benefits associated with the advent of the Fourth Industrial Revolution (4IR). As key agents of educational change, science teachers face the key imperative to harness the pedagogical affordances of online platforms with a view to realizing the achievement of envisaged educational outcomes. Furthermore, research studies on online teaching have predominantly focused on technological aspects and very little on their impact on humans. The empirical investigation adopted a qualitative case study design and involved 20 purposively selected postgraduate science students from diverse school contexts in South Africa. Data were collected through the administration of an open-ended survey questionnaire and semi-structured interviews. Key findings emanating from the empirical investigation indicated that postgraduate science teachers’ coherent adoption of appropriate online pedagogical strategies was largely hampered by a lack of technological resources and inadequate professional capacity to implement online teaching and learning in diverse school contexts. Sustainable teacher professional development opportunities on the utilization of virtual digital platforms ought to be provided with a view to enabling postgraduate science teachers to harness the pedagogical affordances of online teaching and learning.
METHODOLOGICAL FEATURES OF GENERALIZING KNOWLEDGE OF SCHOOL STUDENTS ABOUT FUNDAMENTAL PHYSICAL PRINCIPLES

The article is devoted to solving the urgent, complex and multifaceted problem of increasing of the level and quality of fundamental training of schoolchildren in physics in modern educational conditions. The author notes that the solution of this problem requires the implementation of methodical approaches and learning technologies that will provide students with a purposeful and consistent mastery of a system of organically interconnected subject, worldview and methodological knowledge, followed by their generalization with the help of relevant physical principles at the level of modern physical pictures of the world. In this regard, the author determined the sequence of studying the material and highlighted the theoretical and methodological aspects of generalizing students' knowledge about the fundamental physical principles of relativity, conservation and atomism, which should be the focus of teachers' attention both during the educational process and at the final classes on the relevant topics. Schoolchildren's awareness of the physical essence of the principle of relativity contributes not only to the understanding of the general laws of mechanical motion and the interaction of bodies in different reference systems, but also expands and deepens knowledge of two basic scientific concepts (mass, energy) and forms an idea of a single four-dimensional space-time continuum that encompasses. Students' understanding of the fundamental importance of the principle of conservation is connected not only with the unity of space-time, but also with the symmetry of space, symmetry of interactions, and symmetry of laws. Elucidation by students of the physical essence of the fundamental principle of atomism involves a consistent awareness of the discrete structure of matter, electromagnetic radiation, the discreteness of the physical characteristics of micro-objects. It is noted that students' understanding of the physical essence and methodological significance of the latter will not only correspond to the development trends of modern physical science, but will also contribute to increasing the level of subject competence, the formation of a scientific worldview, and will be a guarantee of the success of further education and future professional growth. Key words: fundamental physical principles, systematization and generalization of schoolchildren's knowledge, scientific outlook, subject competence of students in physics.
The Impact of KaniMani Storytelling Mobile Application (KM-SMA) on Tamil Students’ Speaking Skills and Motivation in Learning Tamil

The research aims to delve into the KaniMani Storytelling Mobile Application (KM-SMA)’s impact on Tamil students’ speaking skills and motivation to learn Tamil through the use of mobile applications. Thirty-six Tamil students aged between 7 and 8 years old were chosen based on their performance on a Classroom Assessment (CA) and randomly assigned to one of two groups (one experimental and one control) of 18 participants each. All the students were from three national primary schools, in the Pasir Gudang district, Johor, Malaysia. Two instruments were employed to examine the speaking skills of the participants before and after the experiment: speaking tests as pre-post tests and a motivation questionnaire. In addition, paired t-test was employed to examine the data. We found that following treatment, KM-SMA participants performed better than the control group regarding motivation and speaking skills. The results showed the importance of language instruction through mobile applications; it is a crucial element and we advised that it be considered in the Tamil language curriculum.
Rec-GNN: Research on Social Recommendation based on Graph Neural Networks

Solve the problem that the accuracy of scoring prediction is not high due to insufficient learning of the features of two graph data (user social graph and user item graph) in the social recommendation system (GraphRec), and improve the accuracy of the social recommendation system.In this paper, the user associated with item and the user evaluation of items are improved, and the commodity category attribute is added; And use users as a bridge to connect user-user social graph and user-item graph; Analyze the heterogeneous advantages between nodes, and make full use of the two graph data contained in the social recommendation system to generate the feature vectors that are sufficiently differentiated and representative for users and goods.Compared with the GraphRec basic model without commodity category attribute, the experimental results show that the improved (Rec-GNN) based social recommendation model has a higher accuracy rate in scoring prediction.In this method, RMSE indicators have been improved by 2.5% and 1.5%, respectively, on Ciao and Epinions' two real data sets, and MAE indicators have been improved by 1.3% and 1.3%, respectively.The experimental performance of the model after adding a deeper potential relationship between users and commodities was not tested.This paper analyzes the complex interaction between nodes and adds rich feature information, such as user social information, user ratings on items, and item category attributes, to obtain a more differentiated feature vector representation of users and goods, which has higher accuracy in the social recommendation system score prediction.
Research on intelligent learning platform system based on Spring Boot

With the popularity of the Internet, people's way to explore knowledge began to go to the Internet, digital intelligent learning platform emerged at the historic moment.As for the traditional teaching method, it is taught at a fixed time and place, and the form of education and learning is not free enough.Compared with traditional teaching methods, students can freely access more diverse teaching resources through intelligent learning platform, and they can repeatedly learn the required course knowledge according to actual needs.At the same time, they can also ask questions and communicate on intelligent learning platform.This paper mainly studies the design and implementation of intelligent learning platform based on Spring Boot.The main function of this platform is to seek a convenient means of intelligent teaching and management for teachers and students, so that students can easily study independently and watch the teaching videos uploaded by teachers.Obviously, intelligent learning platform can improve students' enthusiasm for self-study.Technically, the platform uses the front-end and back-end separation architecture to deploy, develop and debug the front-end and back-end projects separately.The front end selects the progressive framework vue.js to complete the complex interaction logic and two-way binding of the front end, and selects ElementUI to design simple pages.Back end selection of Spring Boot, as the overall framework of intelligent learning platform backend, with Java to achieve interface function design, Redis in the Laragon environment to achieve cache optimization, MyBatis to achieve persistent layer development, and MySQL to achieve data storage.This platform provides an intelligent learning and management solution for teachers and students, and is committed to improving the efficiency of learning.After testing, the intelligent learning platform achieved in this paper meets the expected results and achieves good performance.
Decentralized Maintenance Supply Chain System for Highly Sensitive Assets: ‘Blockchain of Things’ (BCoT)-based Solution

Due to existing challenges of operating supply chain for the highly sensitive assets (i.e., nuclear power plants) such as delays, disconnection between asset components' elements performance evaluation and supply chain process, lack of digitisation, etc.Therefore, The International Atomic Energy Agency (IAEA) as agency that manages highly-sensitive assets proposed the development of proactive management systems of operating supply chains in order to deal with mentioned challenges, as well as, enabling all parties to collaboratively interact in an integrated system nationally and internationally.Blockchain is a proven technology to enable (1) automating supply chain process in some leading industries (i.e., automotive industry); (2) minimising fragmentation in supply chain, (3) enhancing the trust among suppliers.Moreover, Industrial Internet of Things (IIoT) sensors can be used to track performances of power plants' elements to enable performing maintenance in the right time.As such, coupling blockchain and IIoT can enable developing the highly recommended proactive supply chain system by IAEA.In this research, A solution is developed to build the structure and the high-level architecture of the proposed proactive supply chainbased blockchain and IIoT.Moreover, a smart contract is developed to demonstrate the needed functions to manage the entire supply chain process for highly-sensitive assets such as nuclear power plants for energy production.
Sentiment Analysis of Microblog During the COVID-19 Pandemic Based on NEZHA Model

Microblog sentiment analysis aims at mining the opinions and views of Internet users on specific events, which is an important content of network public opinion monitoring.The current microblog sentiment analysis generally selects the BERT model proposed by Google, which has no targeted improvement for Chinese text.While there are many improved models based on Bert and the NEZHA (Neural Contextualized Representation for Chinese Language Understanding) model is one of them which is developed by Noah's Ark Lab.The whole word masking technique and functional position encoding mechanism are introduced in the model which can reach the advanced level in a series of Chinese natural language understanding tasks.At present, there are relatively few studies on the application of the NEZHA model to Microblog sentiment analysis during the epidemic, and the validity of the model in this field is still lacking.In response to this problem, the NEZHA model was used to import the 2020 Microblog dataset for sentiment analysis and prediction to verify its effectiveness.Through experimental verification, the NEZHA model has significantly improved the Macro F1 value for microblog sentiment analysis compared with the BERT model, which has greater practical value.
Multiple Similar Groups Based Information Technology for POI Recommendation in LBSNs

With the development of modern information technology, it becomes increasingly easier for users to obtain information through various type of services or applications.However, it also brings difficulty for users to search for really desired information among massive corresponding data.Thus, recommendation systems have become necessary for these services and applications to solve the information overload problem.Point-of-interest (POI) recommendation is famous in Location-based social networks (LBSN) for the ability of exploring users' preference and recommending interesting places.Most traditional POI recommendation algorithms are collaborative filtering (CF) based, and the key idea is to generate recommendation list for a target user by mining historical data of his similar users.We found that, different similarity measurement method may lead to different conclusions.Thus, we proposed a multiple similar group-based CF algorithm for POI recommendation in this paper.Given a target user, we first determined his similar users by using different similarity calculation methods and constructed corresponding groups.The recommended locations for the target user are determined by comprehensively considering the suggestions of our groups.We implemented our algorithm and compared with previous approaches by using the dataset.The experimental results show that, our algorithm performs best.
Seismic Risk Mitigation and Management for Critical Infrastructures using an RMIR Indicator

Recent earthquake events have highlighted the importance of critical infrastructures (CI) resilience, as a strong correlation was found between the economic loss and the severity of CIs damage.CIs are characterized by a complex structure composed of sub-components that are essential for the continuous performance of the system.CIs owners and governments allocate ample of their resources in retrofitting and upgrading CIs systems and components to increase the resilience of CIs and reduce the risk they are exposed to in case of seismic events.Governments and decision-makers must manage and optimize the retrofit efforts to meet the budget and time constraints.This research presents a probabilistic methodology for seismic risk mitigation and management in CIs.The risk expectancy is appraised according to an FTAbased simulation.The simulation includes the development of exclusive fragility curves for the CI and an examination of the expected damage distribution as a function of the earthquake intensity.Furthermore, this research proposes a novel RMIR (Risk Mitigation to Investment Ratio) indicator for priority setting of seismic mitigation alternatives.The RMIR is a quantitative indicator that evaluates each alternative's costeffectiveness in terms of risk expectancy mitigation.Following the alternative's RMIR value, it is possible to prioritize the alternatives meeting the budget and time constraints.This paper presents the implementation of the proposed methodology through a case study of a generic pumping station.The case study includes twelve mitigation alternatives examined and evaluated according to the RMIR indicator.