Reviewerly/exHarmony huggingface dataset:
The [Dissipative] Joy of Accounting: Desiring, Imagining, and Talking about NFTs While the Planet Burns

Promoters of art-oriented non-fungible tokens (NFTs) and online NFT auction houses like Foundation, OpenSea, and SuperRare claim to be “revolutionizing” and “democratizing” the worlds of art and art collecting by deploying blockchain technology to track sales and purchases and thereby eliminating the threats of transactional opacity and fraud that have long plagued art markets. This article complicates such claims by arguing that with NFTs, the usual clamoring for authenticity in art becomes so abstract that only code remains, as the aesthetic object becomes effectively indistinct from the account of its provenance and transaction history. An NFT, like a financial derivative, has no necessary or representational relationship with any actual underlying object. The artwork associated with the token is, rather, prised apart from its existence as property and finds its use not in being seen or felt, but in the truth of its copyability. Looking beyond the NFTs themselves, this article interrogates the discourses promulgating this trend. Comment threads in Reddit and Discord groups, for example, do much to channel the libidinal energy elicited by an artwork, while the digital token itself generates an acquisitive enthusiasm wholly apart from the sensation of seeing or hearing the associated work. Despite fronting radical social change, NFTs ultimately reinforce traditional forms of property and ownership, exhibit reactionary aesthetic and cultural values, and anticipate increasingly authoritarian modes of social control. Taking a wider view, I consider ours an age of post-information, wherein, contrary to Bateson’s classic definition of information in terms of a doubled difference, we find data-based artifacts like NFTs (following cryptocurrency) to be increasingly productive of widespread social and political indifference, a perpetuation of sameness, and an augmentation of the narcissistic ego. In this case: data as the afterlife of art.
Students’ Strategies In Coping With Anxiety In Speaking English

The present research aims to analyse Students' Strategies in Coping with Anxiety in Speaking English. The research question of this research is what are the students’ strategies in coping with anxiety in speaking English. The aim of this research is to investigate the kinds of students’ strategies in coping with anxiety in speaking English. In this research the writer used a qualitative method with a case study approach. The data was collected from the students of second semester English Education Study Program Faculty of Teacher Training and Education Pakuan University. The instrument used were observation, questionnaire and interview. The result shows that the students of the second semester English Education Study Program Faculty of Teacher Training and Education Pakuan University carried out the five strategies, namely preparation, relaxation, positive thinking, peer seeking and resignation. It is in line with a theory proposed by Kondo &amp; Ling (2004). The students apply these strategies with various activities. By doing these strategies the students can reduce the anxiety they feel when speaking English, feel more prepared to speak English, and calmer when speaking English. In addition, they can be more confident in speaking English and their ability to speak English can increase. Therefore, it is very good for students to do these strategies.
Design of wind power equipment monitoring system based on Huawei AI chip

Abstract With the gradual development of wind power, developing a wind power equipment monitoring system for wind farms is of great significance for ensuring the normal operation of wind farms and subsequent data analysis and processing. This paper develops a wind farm equipment monitoring system based on Huawei AI chips. The frame structure, R&amp;D process, system construction process, and corresponding electronic circuits of the power vision edge computing system design based on Huawei AI chips are introduced in detail. The system can realize the intelligent processing of the data of the main electrical equipment of the wind farm and has functions such as the perception and acquisition of wind power resource data, the monitoring of the operating status of wind power equipment, and the advanced functions and intelligent processing of data.
ANALISIS PENDAMPINGAN ORANG TUA TERHADAP SISWA DALAM BELAJAR DI MASA PANDEMI COVID-19 DI SDN 2 NGABUL JEPARA

This study aims to determine the condition of parents/guardians of students who are not yet technology and information literate in helping children learn during the COVID-19 pandemic. The second goal is for parents to understand their role in assisting their children's learning during the COVID-19 pandemic. Researchers used quantitative methods. While the subject of this research is the parents of students at SDN 2 Ngabul Jepara. In collecting data, researchers used interviews, observations, and documentation. Then the data were analyzed, with two procedures, namely: a) data presentation b) drawing conclusions. The results of this study are a) Parents who do not really understand the development of technology and information find it difficult when accompanying and helping children in learning during the COVID-19 pandemic, so that the assistance is less than optimal. b) The role of parents in accompanying children when studying at home, namely, acting as a companion, motivating, facilitating, and helping to solve problems and being able to create a conducive situation for learning.
Analyses of Software Data and Their Interpretations: A Framework of Information Granules

Data collected from software applications such as issue management systems or version control systems are abstract and require their thorough and comprehensive analysis. Automated issue generation is an understudied area in automated software development despite its effectiveness, safety, and satisfaction which increases developer productivity. Analysis of software data from automated issue generation provides information which could be used by relevant tools or monitored as any other feature in the development process. In this paper, we systematically apply a suite of methods, including clustering algorithms, cluster validity indexes, and information granularity, to generate explainable prototypes using software data from generated GitHub Issues. Among other approaches of data analytics, we employ the principle of justifiable granularity and a method of optimal information allocation. These methods are applied to two dimensional synthetic Gaussian data to illustrate the performance of the methods. The study provides the experimental results using the methods applied to real industrial data coming from the 0pdd software. The resultant groups provide some insights into structure for organising puzzles with similar characteristics.
Development of a Website-Based Education Management Information System in Inclusive Schools

One of problems in inclusive schools is caused by there is no inclusive school management information system. Based on these problems, it is necessary to have a management information system in inclusive schools that can help schools, the government and the community to create inclusive schools that can be accessed by everyone. This study aims to produce a product from the development of a website-based education management information system in inclusive schools. The research method used in this research is Research and Development (RnD) with the Borg and Gall model at stages four to ten. The process starting from the stages of data collection, planning, development, stage I expert validation, stage I expert revision, stage II expert validation, stage II expert revision. Product trials in inclusive schools, revisions to product trials in inclusive schools, and the final product of an education management information system in inclusive schools. The subject of this study involving inclusive schools parties such as teachers, and school committees from parents and some expert. The results of this study can be concluded that the development of a website-based education management information system in this inclusive school has been successfully carried out based on the Borg and Gall development model. The development of a website-based education management information system in this inclusive school has also obtained a very good eligibility level. So that it can be used by inclusive schools in managing education to provide the information needed by the community, government, and the school.
Knowledge Management Practices in the Public University Libraries: Librarian's Perspective

Some libraries play an essential role in teaching and learning but there are some constraints. It causes universities to be able to identify various factors and overcome the challenges of implementing KM in libraries. This study aims to explore current Knowledge Management (KM) practices in Public University Libraries (PUL). This type of research is qualitative. The methods used in collecting qualitative data are observation, interviews, and questionnaires. The instrument used is the interview sheet. The sample of this research is 11 people using purposive sampling. The collected data were analyzed using content analysis. The findings reveal no formal KM program in any of the selected universities. This study found that a prudent strategy for KM implementation, recruiting skilled personnel, ongoing training programs for staff and users, leadership, ICT infrastructure, higher authority decisions, budgets, and lack of qualified personnel are critical success factors for KM implementation in PUL. This research identified many challenges that PUL usually faces in their efforts to implement KM: lack of budget, lack of user awareness, lack of trained staff, and outdated technology.
Resource Repositories and linking resources: An exploratory study

In this article the existence, use and importance of repositories are explored. An introduction into language resources (LRs) is given as well as a discussion of two platforms for the distribution of language resources, namely, the repository of the South African Centre for Digital Language Resources (SADiLaR) and Lanfrica, a site that links resources. In this article, types of repositories, such as institutional and language resource repositories, will be distinguished and compared. Language preservation is proposed as an important aspect which can be strengthened by the presence and use of repositories. The view expressed in this article is that the availability of language resources and repositories are pivotal for the development, preservation and advancement of languages. Having a host site that links available resources and a repository where resources could be uploaded is a positive attribute of the mentioned online platforms, however as it will be discussed, the fact that information is available online is not a guarantee that the resources are or will be used by researchers or other interested persons, especially if they are not aware of their existence. The article is concluded with suggestions for future work, for example measuring the influence of inaccurate metadata of language resources on linguistic research.
Bahasa Bugis: Inflectional Morphology in the Verb

In this paper, I discuss some morphological processes of inflection in Bahasa Bugis particularly verb, in order to scrutinize some problems that appear in the analysis under a morphemic framework. To have a better understanding towards the analysis of the inflectional case, I will employ an approach of Paradigm Function Morphology by Stump (2001). As a result, inflectional occur depends on the aspect and the person. There are three main aspects found; durative, perfective, and conditional. Of which, durative has four subcategories; durative (repeated), durative (feature &amp; repeated), durative (similar), and durative (repeated &amp; similar). Moreover, perfective aspect is also found to have one subcategory called perfective (past &amp; similar). On the other hand, an interesting phenomenon found in person where the second person differentiated by the pragmatic meaning; more polite and less polite. Finally, through PFM, we can capture the mappings, block by block, show how morphosyntactic features are realized by the exponents in the language.
Shared syntactic representations in non-native languages

How do speakers represent and process syntactic information in their second and third language?We investigated this question with cross-linguistic syntactic priming of passives from Spanish (L3) to English (L2).We found that cross-linguistic structural priming occurs between two non-native languages in intermediate to advanced speakers of English as an L2 and Spanish as an L3.We take these results to show that multilingual speakers have one integrated shared abstract representation of passives.The findings are compatible with the extension of the bilingual shared-syntax model to multilingual syntactic processing.
Sentiment Analysis Tweet KTT G-20 di Media Sosial Twitter Menggunakan Metode Naïve Bayes

The G-20 or The Group of Twenty is a group consisting of 19 countries with major economies plus 1 European Union. This group was formed in 1999 as a systematic forum with the aim of discussing important issues or problems related to the world economy. The countries included in the G-20 include Australia, Canada, Saudi Arabia, United States, India, Russia, South Africa, Turkey, Argentina, Brazil, Mexico, France, Germany, Italy, United Kingdom, China, India, Japan, and South Korea. From these data it can be concluded that the G-20 Summit is a forum capable of improving the standard of living of many people because of its ability to produce international policies, laws and regulations. Indonesia was once in the world's spotlight because in November 2022, Indonesia will host the G-20 Summit in Nusa Dua, Bali, to be precise. Ordinary people use Twitter to express emotions related to something, both negative and positive emotions. With the implementation of sentiment analysis data from tweets from 500 data tweets using the Naive Bayes algorithm, the result is an accuracy of 69%. The accuracy value with class precision for positive predictions is 78%, while the class precision accuracy value for negative predictions is 36%. The positive class recall accuracy value is 81%, while the negative class recall accuracy value is 32%.
Introduction to a Systemic Functional Grammar of Korean

This chapter introduces the appliable linguistics theory, Systemic Functional Linguistics (SFL), informing this grammar of Korean. The three basic theoretical dimensions of SFL are outlined – stratification (levels of language), rank (constituency) and metafunction (kinds of meaning). The approach to the distinctive relation of system to structure in SFL is then explained, including the formalisation of paradigmatic relations in system networks. The chapter closes with an outline of the book as a whole.
SPEECH EMOTION RECOGNITION USING CNN-LSTM

-Speech emotion recognition is a rapidly growing field of research that aims to automatically identify emotions from speech signals. This paper presents a speech emotion recognition using machine learning techniques. The study begins by providing an overview of the various approaches used in speech emotion recognition, including feature extraction, feature selection, and classification. These selected features like pitch, MFCC are compared with the existing datasets in databases. and baased on the features the audios are classified using CNN LSTM algorithm. This model is trained in the free environments like collab using Python, and for User interface and HTML, CSS is used. Key Words: Speech Emotion, MelFrequency Cepstral Coefficient, CNN, LSTM
Dynamic three-dimensional imaging with cubic-meter-level measurement volume using multi-scale band-limited illumination profilometry

Dynamic three-dimensional (3D) surface imaging using phase-shifting fringe projection profilometry is currently driven by industrial manufacturing, archaeological inspection, and entertainment. However, existing techniques cannot simultaneously provide the robustness in solving spatially isolated 3D objects, the tolerance of large variation in surface reflectance, and the flexibility of tunable working distances with a cubic meter (m<sup>3</sup>)-level measurement volume at video rate. To overcome these limitations, we have developed multi-scale band-limited illumination profilometry (MS-BLIP). MS-BLIP implements multi-frequency fringe projection with the associated phase unwrapping, which enables robust 3D imaging of spatially isolated objects. Meanwhile, MS-BLIP adopts dual-level intensity projection to enhance its dynamic range, which allows recovering 3D information from surfaces with large reflectance variation. Moreover, MS-BLIP applies a newly developed iterative method for distortion compensation, which improves the 3D reconstruction quality over a cubic-meter-level measurement volume. Finally, a dove prism is used to adjust the orientation of the field of view, which helps MS-BLIP fit different experimental scenarios. With a measurement volume of up to 1.5 m<sup>3</sup> and a working distance of up to 2.8 m, MS-BLIP showcases the video-rate 3D surface imaging of full human-body movements.
Experimental Full-Domain Mapping of Quantum Correlation in Clauser-Horne-Shimony-Holt Scenarios

Quantum correlation between two parties serves as a useful resource in the surging applications of quantum information. The Bell nonlocality and quantum steering have been proposed to describe nonclassical correlations against local-hidden-variable and local-hidden-state theories, respectively. To characterize the two types of nonclassical correlations, various nonlocality and steering inequalities have been established, and the amount of inequality violation serves as a helpful indicator for many entanglement-based tasks. Quantum state tomography has been employed for measuring quantum states, while the method requires intensive computation and does not directly verify either nonlocality or steering over the full domain independent of established theories. Here, we experimentally map the full-domain correlation with bipartite states for nonlocality and quantum steering in Clauser-Horne-Shimony-Holt scenarios. The measurement of the maps automatically accounts for detection imperfections. Furthermore, we demonstrate the application of the correlation maps in the entanglement-based quantum key distribution protocol with arbitrary bipartite states. The correlation maps show direct measurements and simple interpretations that can answer fundamental questions about nonlocality and quantum steering as well as contribute to quantum information applications in a straightforward manner.
Analysis of Yamaha Scorpio Engine Performance with Variation of Ethanol Fuel and Shell V Power

The number of motorized vehicles used will also be as much as the use of fossil fuels, as well as the increasing growth of vehicles that increases year by year, which does not affect fuel consumption but population growth. Fuel quality is measured by RON, where the higher the octane value, the better the fuel quality. RON simply describes how much pressure can be exerted before gasoline spontaneously ignites in the combustion chamber of the vehicle. This study aimed to determine the effect of Power, torque and fuel consumption with a mixture of Petalite, Shell V-Power and Ethanol with a test object, namely the Yamaha Scorpio motor. The research method used is a quantitative approach with a type of development research. The result of this study is that Shell V Power fuel, when mixed with ethanol will produce better engine performance, the greater the percentage of methanol introduced into the fuel, the better the performance produced, both torque, power, and fuel consumption, namely at rpm 1000,1500,2000,2500 methanol 8% the most optimal where the time is 174 Sec, Sec 105, Sec 86, Sec 51 Sec. And the force on the Load Cell is 0.535, 0.875, 1.102, 1.421 kgf.&#x0D;
Efficient inference in the transverse field Ising model

Abstract In this paper we introduce an approximate method to solve the quantum cavity equations for transverse field Ising models. The method relies on a projective approximation of the exact cavity distributions of imaginary time trajectories (paths). A key feature, novel in the context of similar algorithms, is the explicit separation of the classical and quantum parts of the distributions. Numerical simulations show accurate results in comparison with the sampled solution of the cavity equations, the exact diagonalization of the Hamiltonian (when possible) and other approximate inference methods in the literature. The computational complexity of this new algorithm scales linearly with the connectivity of the underlying lattice, enabling the study of highly connected networks, as the ones often encountered in quantum machine learning problems.
Data Selection for Training the Neural Fuser Applied to Autonomous UAV Navigation

Over the past few years, there has been a steady increase in the use of aircraft vehicles, in particular unmanned aerial vehicles (UAV). UAV navigation is generally controlled by a human pilot. But the challenge for the scientific community is to carry out autonomous navigation. Some solutions have been proposed for the UAV autonomous navigation. Studies indicate as a solution to use data fusion and/or image processing navigation. Kalman Filter (KF) can be employed as a data fuser, but the KF has disadvantages. An alternative to the KF is based on artificial intelligence. Here, the KF is replaced by a self-configured neural network. This work investigates a way to select data for training the neural fuser, based on crossvalidation techniques. The results are compared to the data fusion done by a KF.
TKGQA Dataset: Using Question Answering to Guide and Validate the Evolution of Temporal Knowledge Graph

Temporal knowledge graphs can be used to represent the current state of the world and, as daily events happen, the need to update the temporal knowledge graph, in order to stay consistent with the state of the world, becomes very important. However, there is currently no reliable method to accurately validate the update and evolution of knowledge graphs. There has been a recent development in text summarisation, whereby question answering is used to both guide and fact-check summarisation quality. The exact process can be applied to the temporal knowledge graph update process. To the best of our knowledge, there is currently no dataset that connects temporal knowledge graphs with documents with question–answer pairs. In this paper, we proposed the TKGQA dataset, consisting of over 5000 financial news documents related to M&amp;A. Each document has extracted facts, question–answer pairs, and before and after temporal knowledge graphs, to highlight the state of temporal knowledge and any changes caused by the facts extracted from the document. As we parse through each document, we use question–answering to check and guide the update process of the temporal knowledge graph.