Reviewerly/exHarmony huggingface dataset:
Archiving for Extinction

Anjali Arondekar, Wendy H. K. Chun, Verne Harris, N. Katherine Hayles, Shannon Mattern, Saidiya Hartman, and Kate Eichhorn, among other scholars of the archives, have questioned the presumption of the archive as complete, whole, legitimate, authoritative, and ultimately in any way “total,” by looking beyond the contents that the physical repository hosts and guards, as well as how, what, and who goes under-, mis- and altogether unrepresented. In their tradition, we find that the contemporary moment provides exemplars of where an archival (re)making is being uncritically taken up, increasingly envisioned, and subsequently reliant upon present-day technological capacities and the technological imaginaries of the future near and far. Under the guise of scientifically vetted global betterment, and drawing on a long legacy of publicly funded innovation that is then recaptured and taken up by private industry, Big Tech takes profit and credit for these particular future-oriented deployments, but takes on little to none of the social, political, and environmental responsibility. In this article we explore specifically what users can do when their abstracted data production or consumption is based not only on deeply flawed science and technology that is pervasive, powerful, and compelling, but also invariably presented as the only solution to climate catastrophe and the end of human existence. The three archival projects explored in this article—ordered by scale—are Alphabet’s “The Selfish Ledger,” Big Tech’s “Genomics in the Cloud,” and Arch Mission’s launch of a “Solar, Earth, Lunar, and Mars Library.” By exploring the sociotechnological imaginaries of Big Tech, we reposition the archive in terms of its legitimation and framing of humanity’s past, present, and future. We demonstrate that the ledger is a political frame, cloud-based genomics is a biological and terrestrial fix, and the space library is a speculative implementation of the total—and final—archive for extinction.
Hoverboards in the Metaverse: A Conversation with Asad J. Malik

This interview, which took place in September 2021, explores the history of projects carried out by Jadu and the possibilities of Web3, NFTs, and the futures of data in the metaverse.
PENERAPAN STRATEGI RAFT (ROLE-AUDIENCE-FORMAT-TOPIC) UNTUK MENINGKATKAN KEMAMPUAN MENULIS PROCEDURE TEXT PADA SISWA KELAS IX DI MTs.NEGERI SINGKAWANG

This research aims to: 1). Improving students' writing skills through the application of the RAFT Strategy (Role-Audience-format-Topic) in class IX students of MTs Negeri Singkawang in 2023. 2) Strategies carried out by the teacher in improving students' writing skills through the application of the RAFT Strategy (Role-Audience-format- Topic) in class IX students of MTs Negeri Singkawang in 2023. Learning English with the Application of the RAFT Strategy (Role-Audience-format-Topic) is carried out so that learning is more varied so that it attracts student interest in learning, it is necessary to prepare learning strategies that can be adjusted to the rhythm of learning them, the learning strategy used must attract their interest in learning. Data collection techniques in this study are: measurement techniques (test techniques) and Direct Observation techniques. While the data collection tools in this study include tests, observations, and interviews. The results showed that the application of the RAFT Strategy (Role-Audience-format-Topic) could improve the ability to write Procedur Texts in class IX students of MTs Negeri Singkawang in 2023. Of the 32 students, almost all 30 students or the equivalent of 93.75% achieved learning mastery the minimum set for learning English is 2 people or equivalent to 6.25% obtaining learning outcomes under the KKM, which is 70. ABSTRAKPenelitian ini bertujuan untuk: 1). Meningkatkan kemampuan menulis Siswa melalui Penerapan Strategi RAFT (Role-Audience-format-Topic) pada siswa kelas IX MTs Negeri Singkawang Tahun 2023. 2) Stategi yang dilakukan oleh guru dalam meningkatkan kemampuan menulis Siswa melalui Penerapan Strategi RAFT (Role-Audience-format-Topic) pada siswa kelas IX MTs Negeri Singkawang Tahun 2023. Pembelajaran Bahasa Inggris dengan Penerapan Strategi RAFT (Role-Audience-format-Topic) dilakukan agar pembelajaran lebih variatif sehingga menarik minat belajar siswa, maka perlu dipersiapkan strategi pembelajaran yang dapat disesuaikan dengan irama belajar mereka, strategi pembelajaran yang digunakan harus menarik minatnya untuk belajar. Teknik pengumpulan data dalam penelitian ini adalah: teknik pengukuran (teknik tes) dan teknik Observasi Langsung. Sedangkan Alat pengumpul data dalam Penelitian ini meliputi tes, observasi, dan wawancara. Hasil penelitian menunjukan bahwa Penerapan Strategi RAFT (Role-Audience-format-Topic) dapat meningkatkan kemampuan menulis Procedur Teks pada siswa kelas IX MTs Negeri Singkawang Tahun 2023. Dari 32 siswa hampir seluruh siswa 30 orang atau setara dengan 93,75% mencapai ketuntasan belajar minimum yang ditetapkan pada pembelajaran Bahasa Inggris sedangkan 2 orang atau setara dengan 6,25% memperoleh hasil belajar di bawah KKM yaitu 70.
A New Technique for Programmable Very Low Frequency Filtering

&lt;p&gt;A new technique for obtaining a very large time-constant integrated filter is proposed. The time-constant of the filter is made proportional to r0C, where r0 is the output impedance of a transistor. Since 1/r0 is proportional to the bias current, the filter cut-off frequency is linearly programmable. The technique is demonstrated ex- perimentally using a simple circuit.&lt;/p&gt;
A simple neural model for unlabelled data

Abstract Neural networks are powerful tools for modelling big unstructured data. Advanced architectures and learning methods are used in applications. Nevertheless simpler models which use less data could be helpful. We propose a very simple learning algorithm in order to model the data distribution. Experiments show how effective and data-efficient our method is. Code is available at https://github.com/unverciftci/toUniform.
HSAM: Hybrid Sentiment Analysis Model for COVID-19 Contact Tracing Applications

&lt;p&gt;To understand the public’s perception of COVID-19 tracing applications, previous studies were primarily based on exploratory research, surveys or machine learning methods, which are semantically weak and time-consuming. To increase the reliability of this analytical methodology, hybrid-based Twitter sentiment analysis can be applied. In this paper, we propose a hybrid model for sentiment analysis by using Valence Aware Dictionary for Sentiment Reasoning (VADER) + Support Vector Machine (SVM). We demonstrate from the numerical analysis that a VADER and SVM-based hybrid model provides the best performance with 82.3% accuracy, 0.84 precision, 0.83 recall and 0.82 F1-score. The use of hybrid-based methods is shown to be effective in analysing the public’s perception towards COVID-19 contact tracing applications using tweets collected from the UK, USA and India. Positive responses clearly outweighed negatives responses towards contact tracing, but this was contradicted by the low uptake of apps in all three nations. Our analysis, however, showed that neutral responses were 52% of the collected tweets; these tweets did not express positive or negative opinions, and subsequent tweets from the same users could not be verified, thus limiting the number of analyzed tweets available.&lt;/p&gt;
QBithm: towards the coherent control of robust spin qubits in quantum algorithms

Many efforts have succeeded over the last decade at lengthening the timescale in which spin qubits loss quantum information under free evolution. With these design principles, it is now timely to zoom out and take the whole picture: concerning applications that require user-driven evolutions, qubits should be assessed within the desired algorithm. This means to test qubits under external control while relaxation is active, and to maximize the algorithm fidelity as the actual figure of merit. Herein, we pose and analytically solve a master equation devised to run one-spin-qubit algorithms subject to relaxation. It is handled via a code, QBithm, which inputs gate sequences and relaxation rates thus connecting with the longstanding work devoted to their ab initio computation. We calculate fidelities against relaxation and imperfections, and implement well-known pulse sequences quantitatively agreeing with experimental data. Hopefully, this work will stimulate the study of many-qubit systems driven under relaxation and imperfections in quantum algorithms.
A Study of Image Hiding Techniques in The Spatial Domain

Nowadays, steganography has become a useful technology and the interest in it has increased due to the rapid growth in the use of the internet, and it is applied to transmit information secretly using various techniques. Hiding is one of the main important techniques in steganography, which is the science of hiding secure information inside the carrier body to provide secure communication via the internet, so that only the sender and receiver can identify and reveal it. In stealth, many different forms of carrier can be used such as image, video, protocol, and audio. The digital image is most commonly used as a vector file because of its frequency on the internet. There are many changing techniques of steganography, and each has strengths and weaknesses. In this study, we conducted a review of techniques used for hiding in the spatial domain to explore the term hiding by reviewing and collecting different studies related to this field published from 2015 to 2021. This study evaluated nine proposed approaches to address this problem. Three metrics - image quality, message capacity, and security - were used to evaluate each method. Finally, the results are presented and summarized, since the capacity and quality of the hiding image are important for a good approach. There is a trade-off between the amount of confidential data that can be included, image distortion, and the security of image hiding. The disadvantages of each method are also identified, which serve as the basis for future research. Along with a complete review of the basic concepts of steganography additionally, types of steganography and interest in image steganography based on spatial domain are presented. Furthermore, the criteria most commonly used to evaluate steganography performance in terms of non-perception, payload capacity, and robustness are addressed. Each spatial domain technology attempts to meet the most important steganographic design requirements of (1) maintaining non-perception at a good level, (2) high capacity payload, and (3) robustness against intruder attacks. But in truth, the perfect steganography system does not exist, and it may be another lacking in robustness. for example ,It has a high ability but suffers from lack of resistance to statistical attacks. Therefore, when designing an LSB hiding scheme file a balance must be struck between the requirements for hiding information. A good recommendation from the techniques reviewed is that the combination of steganography and encryption techniques increases the confidentiality of the hidden message.
Zero-Shot Transfer Learning using Affix and Correlated Cross-Lingual Embeddings.

Learning morphologically supplemented embedding spaces using cross-lingual models has become an active area of research and facilitated many research breakthroughs in various applications such as machine translation, named entity recognition, document classification, and natural language inference. However, the field has not become customary for Southern African low-resourced languages. In this paper, we present, evaluate and benchmark a cohort of cross-lingual embeddings for the English-Southern African languages on two classification tasks: News Headlines Classification (NHC) and Named Entity Recognition (NER). Our methodology considers four agglutinative languages from the eleven official South African languages: Isixhosa, Sepedi, Sesotho, and Setswana. Canonical correlation analyses and VecMap are the two cross-lingual alignment strategies adopted for this study. Monolingual embeddings used in this work are Glove (source), and FastText (source and target) embeddings. Our results indicate that with enough comparable corpora, we can develop strong inter-joined representations between English and the considered Southern African languages. More specifically, the best zero-shot transfer results on the available Setswana NHC dataset were achieved using canonically correlated embeddings with Multi-layered perceptron as the training model (54.5% accuracy). Furthermore, our NER best performance was achieved using canonically correlated cross-lingual embeddings with Conditional Random Fields as the training model (96.4% F1 score). Collectively, this study’s results were competitive with the benchmarks of the explored NHC and NER datasets, on both zero-short NHC and NER tasks with our advantage being the use of very minimal resources.
A New Centralized Detection-Based Process for Evaluating Anomalies and Analyzing the First Causes Using Machine Learning and Web Semantic

In the last decades, many works have been done to enhance data performances in the computer field. Data performance consists to describe all improvements which can be added to data traffic. More precisely, we are talking about techniques allowing improving the evaluation of big data using machine learning. Data evaluation is composed of several variables such as security, quality of service, data synchronization, scalability, and data structuring. In this work, we complete our proceedings done to supervise the continuity of technological evolution in terms of big data and safety. In other words, we aim to add brick to our previous processes to take into consideration the enhancement of the analysis of the causes generating frauds and intrusions preventing data traffic. To achieve this end, we increase current machine learning techniques with prior knowledge based on data thresholds set by experts in the first place. We also aim to integrate knowledge facilitating the interpretation of the causes causing all kinds of anomalies in the second place. Finally, our process will be endowed with the requirements to improve the rate of detection of anomalies and reduce human involvement operation.
NLP and Graph embeddings: TextGraphs.jl

Natural language processing (NLP) techniques analyze formal properties of speechin humans. One way of analyzing language is through graph embeddings. Graphs are cunningly simple abstractions, which have vertices and nodes as basic elements. Nevertheless, graphs were revealed to be very useful abstractions to describe associations in real-world phenomena whenever there are coupled elements. Graph embeddings associate words with nodes and adjacency in a phrase with links (edges). When words are repeated, the respective node is linked twice. Some attributes of these “speech graphs” are correlated with mental states, such as connectivity (e.g. largest connected components).The first section of this article reviews theoretical basis for the analysis of text-based graph embedding (”Text Graphs” or ”Speech Graphs”). We present standard procedures of text embedding and discuss graph properties (e.g. connected components) in this context.Some features brought by TextGraphs.jl (e.g. density, centrality) were not used before in literature. The second section covers applications, including installation, basic features, and vignettes with example cases
ANALISIS KESULITAN KETERAMPILAN MENULIS PARAFRASE PUISI KE PROSA SISWA KELAS VI SEKOLAH DASAR

This research is motivated by the low learning outcomes of language skills, especially the skills of writing paraphrasing poetry into elementary school prose. This study aims to obtain the results of the analysis of students' difficulties in writing skills. Paraphrasing poetry to prose for sixth grade elementary school students. The causes are, among others, the teaching methods of teachers who are less diverse, boring, lack of teacher skills that are not suitable for anticipating the difficulties experienced by students, students' lack of understanding of the diction contained in poetry, and lack of writing skills and developing story sentences. The analysis of the difficulties experienced by students in Paraphrasing material converting poetry into prose has never been done, so this affects the score of students who do not meet the KKM set by the school, which is 70. This observation uses a qualitative approach with data collection techniques carried out through observation, interviews and work results. Student. The object of this observation is a grade VI student at SD Negeri 3 Menawan and a document Paraphrasing poetry into prose written by a grade VI student at SD Negeri 3 Menawan. The number of students observed was 23 students. The result of this observation is to find out the students' difficulties in writing paraphrasing poetry to prose. These difficulties include students' difficulties in converting poetry into stories, conveying their thoughts into prose, assembling sentences, and the lack of understanding of the meaning of words in the poetry presented due to the lack of students' vocabulary. Based on the results of the analysis of students' difficulties in paraphrasing poetry, the teacher can determine the steps to teach Indonesian, especially Paraphrasing poetry to prose in elementary schools well.
EFEKTIVITAS PENGGUNAAN MEDIA SCRAPBOOK PADA KETERAMPILAN MENULIS NARASI SISWA KELAS VI SEKOLAH DASAR

This research is motivated by the low skills of students in writing narratives. This study aimed to describe the effectiveness of using Scrapbook media on the narrative writing skills of sixth-grade elementary school students. This research uses a descriptive qualitative research method. This study’s subjects were sixth-grade elementary school students of SD 1 Jepang. The sampling technique used is purposive sampling, which uses the entire sixth grade, which consists of 32 students. Data collection techniques using observation, interviews, and documentation. Data analysis techniques in research take place before in the field and during the field. The results showed that it was easier for students to write narratives using Scrapbook media. Interest in learning also increases with the use of these media. In addition, students' narrative writing learning outcomes also increased to an average of 75. From the results of this study, it can be concluded that Scrapbook media is effectively used in the narrative writing skills of sixth-grade elementary school students.
Remarks on Fixed Point Assertions in Digital Topology, 5

We discuss published assertions concerning fixed points in digital metric spaces that are incorrect or incorrectly proven, or reduce to triviality.
Fuzzy Enhanced Artificial Potential Field-based Mobile Car Path Planning

A significant area of study in the field of autonomous driving technology is path planning. Artificial potential field approach is a popular technique to analyze local path planning, however, its conventional algorithm suffers the flaws of local optimal and unachievable goals. In this study, the artificial potential field method's repulsive force field expression is enhanced, and the fuzzy control method is integrated with the artificial potential field method. Through the design of two fuzzy controllers, the driving deflection angle and driving speed are controlled in real time, which helps the mobile car to overcome the defects of the conventional artificial potential field method in some typical position relationships, travel more safely and smoothly to its destination, and create efficient path planning. The Matlab simulation results demonstrate the improved algorithm's ability to address the issues of an unreachable objective and a local optimum in a few common path planning places, and also shows advantages in obstacle avoidance safety.
The Strongest Array Beyond Halbach Array

In the Cartesian coordinate system, the direction of magnetization in which the magnetic field is strongest in one axis direction at the origin was derived using variables in the spherical coordinate system. In this direction, i.e., using the strongest field array, it is 3.51 % larger than the Halbach array (Halbach sphere) in the hollow sphere. In particular, an experiment using a sphere magnet to approximate the point where the difference is large revealed that the central magnetic field is stronger. We also found that the Halbach array (Halbach cylinder) has the strongest central magnetic field for infinite cylinders. Furthermore, we have shown that the segmentation of this direction into blocks can be optimized according to the strength of the magnetic field.
An Efficient Alternative to Subgraph Isomorphism and Its Advantages

Subgraph Isomorphism is a fundamental problem in graph theory. It has many applications in social network analysis, molecular investigations, knowledge graphs, etc. Given a Query Graph and a Data Graph, the target of Subgraph Isomorphism, i.e., Subgraph Matching, is to determine if this Query Graph is isomorphic to any subgraph of the Data Graph. This work proposes a new type of Query Graph, combined with multiple general Query Graphs. We call it Compulsory-Optional Query Graph (CO Query Graph). This new type of Query Graph contains all the vertices in the combined general Query Graph, and each vertex corresponds to a search priority. Based on CO Query Graph, the previous multiple match processes can be reduced to one. It tremendously improves search efficiency. The Subgraph Isomorphism based on this new kind of Query Graph is an extension and improvement of the previous Subgraph Isomorphism studies. We propose a backtracking-pruning-based CO solver (BPC). This algorithm builds on the backtracking-pruning framework. BPC modifies the output criterion and matching conditions to satisfy the CO query context. A case study of real-world graph data illustrates that BPC built on CO Query Graph is more efficient than conventional Query Graphs. To verify the effectiveness of our method, we conducted experiments on the synthetic graph and real-world data. The results show that the BPC can significantly reduce the search space and improve the search efficiency in the recursive calls and the response time. Experiments resulting from synthetic graph data analysis allow us to primarily identify the critical factor that affects the efficiency of the BPC primarily.
Conversational Analysis of Grice’s Maxim Theories on Cooperative Principles in Bahasa Indonesia Lecturers

As human always involve in social interaction; they are required to use language appropriately to avoid missed-understanding. They need to obey to what-so- called as ‘cooperative pinciples’ (Grice, 1975) and ‘politeness’ (Leech, 1993). However, it is unavoidable that failure of communication often occur especially in a community with different backgrounds (e.g. culture, economy, education, etc.). This study aims (1) to figure out the types of violation of Grice’s cooperative principle, and (2) to figure out the degree of politeness principle in daily conversation among lecturers in Musamus University majoring Pendidikan Bahasa dan Sastra Indonesia. The data of the present qualitative study were conversations among lecturers of PBSI of Musamus Univeristy which transcripted and analizyed descriptively based on the four maxims of cooperative priciple by Grice (1975)—maxim of quantity, quality, relevance, and manner and the degree of politeness by Brown and Levinson. The findings revealed that maxim violation was dominated by maxim of relevance (58) while other maxims were maxim of quantity (31), maxim of quality (23), and maxim of manner (20). Some factors triggering speech participants to violate the maxims were to create humor, to avoid being involved in further conversation, to show anger, to ask for confirmation, and to ask someone to do something. In addition, different cultural background also contributes to it. Meanwhile, speech participants tend to use positive politeness to show respect and honor since the conversation occurred at work field.