Reviewerly/exHarmony huggingface dataset:
Upaya Guru dalam Meningkatkan Kemampuan Membaca Kitab Kuning Santri Tingkat Wustho Madrasah Diniyah

Success in reading the yellow book requires a teacher's strategy / efforts carried out by the asatidz / teacher council. This study has the aim of knowing the teacher's efforts in improving the ability to read the yellow book. This type of research is a qualitative research that collects data using interview and documentation methods. Based on the theory, the results of observations and interviews can be concluded 1. The teacher's efforts in improving the ability to read the yellow book are the teacher providing daily nahwu material, increasing class hours, using the sorogan method, giving mufrodat (vocabulary) doing questions and answers during madrasah, getting used to reading the mabadiul fiqhiyah book, accuracy in reading the yellow book, understanding in exploring the contents of the yellow book reading, and the ability to express the contents of the yellow book reading. 2. supporting factors and inhibiting the ability to read the yellow book. The teacher gives motivation to read often, uses an interesting learning process, and has low interest.
Color Image Encryption with a Novel Technique and Chaotic Singer Map

One of the extreme efficient, important, and necessary means used to preserve the information and contents of the image through sending it over the Internet or network communication is image encryption. In this paper, a novel technology for images encryption has been proposed by using different methods. The proposed method consists of five stages. In the first stage, the original color image is divided into eight parts and shuffles it. The second stage separates the R, G, B matrix of the original image and then converts them into a binary code. Third stage generates secret keys by using singer map, where it can generate high pseudorandom sequences with high-speed performance. In the fourth stage, the logical XOR operator is applied to encrypt the image based on the three matrix and secret keys. Fifth stage is the process of decrypting which is the opposite of the encryption process. The suggested approach efficiency is validated via entropy, correlation, UACI and NPCR tests. Likewise, empirical outcomes and security test displayed that the proposed technology achieved secrecy and was capable of facing attacks and challenges.
An Intelligent and Data-Driven Mobile Platform for Youth Volunteer Management using Machine Learning and Data Analytics

In Lewis and Clark High School’s Key Club, meetings are always held in a crowded classroom. The system of eventsign up is inefficient and hinders members from joining events. This has led to students becoming discouraged fromjoining Key Club and often resulted in a lack of volunteers for important events. The club needed a more efficientway of connecting volunteers with volunteering opportunities. To solve this problem, we developed a Volunteer Match Mobile application using Dart and Flutter framework for Key Club to use. The next steps will be toadd a volunteer event recommendation and matching feature, utilizing the results from the research on machine learning models and algorithms in this paper.
Practice in the system of training the future educator

A cross-cutting program is an educational document that regulates the purpose, content, the chain of practices. Teachers of the university departments develop the work programs on the basis of a cross-cutting program since it contains recommendations on the types and forms of control over the level of knowledge, skills, and abilities that students should acquire. The authors studied training of the future teachers in the course of educational-productive practice in secondary schools and estimated its effectiveness. During the study, research and empirical methods were used, as well as methods of mathematical statistics. The link between the educational process of higher educational institutions and pedagogical practice in general secondary educational institutions was analyzed. The peculiarities of pedagogical practice and its influence on the formation of general and professional competences were revealed. It was concluded that practical training is an important component in teachers’ preparation and their self-affirmation.
I Dream of Siri: Magic and Female Voice Assistants

Recent advances in science and engineering have facilitated the development of artificial intelligence voice assistants. While this is true from a technical aspect, smart speakers and voice assistants did not develop in isolation from the rest of human society. The devices may be new, but the practices and patterns in their development and use are not. Using Lévi-Strauss’s structural anthropology, I map homologous practices of smart speaker interaction onto historical conceptions of supernatural magic use. This structural comparison suggests that practices and patterns that were essential to magic use have re-emerged in smart speaker utilization in similar forms. Some of these practices are noteworthy for their homology alone. However, other homologous behaviors revive patterns of inequity that, in Western magical traditions, had privileged the traditionally educated man. The goal of this paper is to elucidate the ghost in the machine: the prejudiced social practices of supernatural magic that were asserted to be eradicated yet which are now, nevertheless, newly instantiated within our most cutting-edge devices.
Opportunities and Challenges of Public Finance Management in Sierra Leone

The public sector of the economy, as a rule, established itself as a leading choice in the economy of Sierra Leone. The effective functioning of this sector depends on qualified management, to make management decisions with respect to such organizations.&#x0D; &#x0D; It should be noted that the most modern management technologies in the field of finance developed and proved to be successful in practice for commercial organizations. Commercial organizations are aimed at profit and welfare of its shareholders. These goals are easily measurable and formalized in enough indicators showing the achievement of the organization's business objectives.&#x0D; &#x0D; The entities of the public sector are significantly different from commercial organizations. The purpose of entity of public sector is to provide public goods, such as services in the field of law enforcement, health, education and others, rather than increasing shareholder wealth. The economic effect of such services is difficult to measure. The effect of the provision of those services cannot be measured by referring to the cost benefits, because the benefits of such services are impossible to calculate in monetary terms. For example, benefits from the provision of health services, is to increase the public health of the nation. The complexity in measuring of the effectiveness of public sector entities requires the&#x0D; use of appropriate tools by management in the field of public finance management.
Structure of the Gokana Verb Phrase: A Principles and Parameters Analysis

This paper described the structure of the verb phrase in Gokana within the framework of Principles and Parameters Theory. The study examined the structure, types and linear order of constituents within the Gokana verb phrase. The study found that the Gokana VP has an abstract SPEC V-bar which serves as a landing site for moved adjuncts from post verbal position to pre verbal position of the Gokana clause. The paper identified the specifier, complement and adjunct as the basic constituents of the verb phrase in Gokana. The paper noted that while complements are obligatory and tightly woven into the structure of the verb with respect to sub-categorization facts of the verb, adjuncts and specifiers are non-obligatory in the canonical structure of the Gokana verb phrase. Thus, the Gokana VP can sometimes occur without specifiers, adjuncts and complements in surface syntax. The study noted that the verb is the head of the Gokana verb phrase. The study identified five subtypes of complements and six subtypes of adjuncts in the Gokana VP. The paper claimed that there is a severe semantic constraint on the linear sequence of adjuncts and recommended a detailed investigation of the order of adjuncts in the Gokana verb phrase.
Conical Classification For Efficient One-Class Topic Determination

As the Internet grows in size, so does the amount of text based information that exists.For many application spaces it is paramount to isolate and identify texts that relate to a particular topic.While one-class classification would be ideal for such analysis, there is a relative lack of research regarding efficient approaches with high predictive power.By noting that the range of documents we wish to identify can be represented as positive linear combinations of the Vector Space Model representing our text, we propose Conical classification, an approach that allows us to identify if a document is of a particular topic in a computationally efficient manner.We also propose Normal Exclusion, a modified version of Bi-Normal Separation that makes it more suitable within the one-class classification context.We show in our analysis that our approach not only has higher predictive power on our datasets, but is also faster to compute.
A DECENTRALIZED CRYPTOGRAPHIC BLOCKCHAIN APPROACH FOR HEALTH INFORMATION SYSTEM

Blockchain had been an exciting studies vicinity for a long term and the advantages it gives had been utilized by some of diverse industries. Similarly, the healthcare zone stands to advantage immensely from the blockchain generation because of protection, privacy, confidentiality and decentralization. Nevertheless, the Electronic Health Record (EHR) structures face issues concerning records protection, integrity and management. In this paper, we speak how the blockchain generation may be used to convert the EHR structures and might be an answer of those issues. We gift a framework that would be used for the implementation of blockchain generation in healthcare zone for EHR. The goal of our proposed framework is first off to put into effect blockchain generation for EHR and secondly to offer stable garage of digital facts via way of means of defining granular get entry to guidelines for the customers of the proposed framework. Moreover, this framework additionally discusses the scalability trouble confronted via way of means of the blockchain generation in preferred through use of off-chain garage of the facts. This framework gives the EHR device with the advantages of getting a scalable, stable and imperative blockchain-primarily based totally answer with use of sha256 hashing algorithm.
ADAPTIVE FUZZY CONTROL CONCEPTS AND SURVEY

In this paper an adaptive fuzzy control concepts and survey are introduced. Starting with the global adaptive control towered the adaptive fuzzy control, the required concepts are explained. Some of the adaptive fuzzy control subjects are viewed as sequential steps with simplifying their views to enable the reader to get a fast and global idea with some details if it is necessary. Most of the stability considerations in the corresponding references are proved by using the lyapunov criteria, where the derivation is a mathematical concept with long steps. Therefore, it is mentioned without details, and for more information, the corresponding reference must be studied. It can be seen from this topic, that the main role of the fuzzy system in adaptive control is the system identification, controller construction and output predictor. The adaptive fuzzy control survey is presented at the end, so the reader can go along with the topics after he reviewed the necessary concepts.
Qu-ANTI-zation: Exploiting Quantization Artifacts for Achieving Adversarial Outcomes

Quantization is a popular technique that $transforms$ the parameterrepresentation of a neural network from floating-point numbers intolower-precision ones ($e.g.$, 8-bit integers). It reduces the memory footprintand the computational cost at inference, facilitating the deployment ofresource-hungry models. However, the parameter perturbations caused by thistransformation result in $behavioral$ $disparities$ between the model beforeand after quantization. For example, a quantized model can misclassify sometest-time samples that are otherwise classified correctly. It is not knownwhether such differences lead to a new security vulnerability. We hypothesizethat an adversary may control this disparity to introduce specific behaviorsthat activate upon quantization. To study this hypothesis, we weaponizequantization-aware training and propose a new training framework to implementadversarial quantization outcomes. Following this framework, we present threeattacks we carry out with quantization: (i) an indiscriminate attack forsignificant accuracy loss; (ii) a targeted attack against specific samples; and(iii) a backdoor attack for controlling the model with an input trigger. Wefurther show that a single compromised model defeats multiple quantizationschemes, including robust quantization techniques. Moreover, in a federatedlearning scenario, we demonstrate that a set of malicious participants whoconspire can inject our quantization-activated backdoor. Lastly, we discusspotential counter-measures and show that only re-training consistently removesthe attack artifacts. Our code is available athttps://github.com/Secure-AI-Systems-Group/Qu-ANTI-zation
Counterfactual Matters: Intrinsic Probing For Dialogue State Tracking

A Dialogue State Tracker (DST) is a core component of modular task-oriented dialogue systems.Tremendous research progress has been made in past ten years to improve performance of DSTs especially on benchmark datasets.However, their generalization to novel and realistic scenarios beyond the held-out conversations is limited.In this paper, we design experimental studies to answer: 1) How does the distribution of dialogue data affect the performance of DSTs? 2) What are effective ways to probe counterfactual matter for DSTs?Our findings are: the performance variance of generative DSTs is not only due to the model structure itself, but can be attributed to the distribution of cross-domain values.Evaluating iconic generative DST models on MultiWOZ dataset with counterfactuals results in a significant performance drop of up to 34.64% (from 50.91% to 16.27%) in absolute joint goal accuracy.It is believed that our experimental results can guide the future work to better understand the intrinsic core of DST and rethink the suitable way for specific tasks given the application property.
TECHNIQUES IN CONDUCTING ENGLISH READING SKILLS TEST PERFORMED BY INDONESIAN TEACHERS ON ASSESSMENT OF LOCAL EDUCATION STANDARD 2021

One of the ways to measure the students' English reading comprehension skills is through testing. Despite its significant value, students frequently construct bad tests without considering the main rules in doing English reading comprehension tests. This research concerns to study of techniques in testing English comprehension reading skills performed by teachers in Indonesia on Assessment of Local Education Standard in the year 2021. Assessment of Local Education Standard abbreviated as ASPD in a provincial- standardized test to maintain the quality of learning. Four EFL teachers in Indonesia were chosen based on their teaching experience in high schools. The researcher used document observation and in depth- interview techniques to collect data which were transformed into observation notes and interview transcription. The data were then analyzed qualitatively. Findings from this study shown that there are three main themes regarding the most used techniques performed by the teachers, first, students must be able to analyze the bloom taxonomy theory, second, students must be able to identify the scope of material, and third determining the keywords of the question. From understanding and doing those three themes, teachers believe that these techniques could help and improve student's ability in facing English reading comprehension tests.
Investigation of a Novel Shape Sensor for Musical Expression

A novel, high-fidelity, shape-sensing technology, BendShape , is investigated as an expressive music controller for sound effects, direct sound manipulation, and voice synthesis. Various approaches are considered for developing mapping strategies that create transparent metaphors to facilitate expression for both the performer and the audience. We explore strategies in the input, intermediate, and output mapping layers using a two-step approach guided by Perryâs Principles Â . First, we use trial-and-error to establish simple mappings between single input parameter control and effects to identify promising directions for further study. Then, we compose a specific piece that supports different uses of the BendShape mappings in a performance context: this allows us to study a performer trying different types of expressive techniques, enabling us to analyse the role each mapping has in facilitating musical expression. We also investigate the effects these mapping strategies have on performer bandwidth. Our main finding is that the high fidelity of the novelÂ BendShape sensor facilitates creating interpretable input representations to control sound representations, and thereby match interpretations that provide better expressive mappings, such as with vocal shape to vocal sound and bumpiness control; however, direct mappings of individual, independent sensor mappings to effects does not provide obvious advantages over simpler controls. Furthermore, while the BendShape sensor enables rich explorations for sound, the ability to find expressive interpretable shape-to-sound representations while respecting the performerâs bandwidth limitations (caused by having many coupled input degrees of freedom) remains a challenge and an opportunity.
Sistem Informasi Persediaan Barang Dengan Metode Weight Moving Average Berbasis Android Di Toko Awd Mranggen

The AWD Mranggen store is a store that is engaged in the sale of bags, belts, shoes with sales developments increasing from year to year, with fairly tight business competition, the AWD Mranggen store must be able to calculate the estimated number of items to be purchased based on previous sales data, the prediction is very influential on the decision to determine the number of items to be provided by the AWD Mranggen Store for the next sales period data. Inventory of goods that are not right cause some losses in terms of time and also costs, it is necessary to have a forecasting system. Forecasting is a technique to identify a model that can be used to predict conditions in the future. By using the weight moving average method, it can be seen that the error value is more than smaller than other methods and the estimated results can be more precise so that it can help owners make decisions in carrying out inventory.
Problems and Solutions for Literacy Development of 5th Grade Elementary School Students Amidst Covid-19 Pandemic Era in Mandailing Natal Regency

Literacy is defined as the ability to listen, speak, read and write. The literacy development of 5th Grade Elementary School students amidst covid-19 pandemic era faces a myriad of problems. Those problems are urgently needed to be solved. The objective of this study is to identify problems and to discover solutions for literacy development of 5th grade elementary school students during covid-19 era pandemic. The data were collected through semi-structured interview involving 23 teachers of 5th elementary school in 23 districts located in Mandailing Natal Regency. The data were afterwards analyzed by thematic analysis with the results distributed into the most specific separated themes. The overall results revealed that 31 problems were found. They were consisting of 8 problems of listening, 8 problems of speaking, 7 problems of reading and 8 problems of writing. Moreover, this study also uncovered 32 solutions for literacy development problems. They were 10 solutions for listening, 6 solutions for speaking, 10 solutions for reading and 6 solutions for writing. These findings could function as significant sources for relevant problem solving in literacy development context amidst covid-19 pandemic era.
Application of 3D vision intelligent calibration and imaging technology for industrial robots

Abstract During modern flexible lean manufacturing, flexible operation of irregular and complex workpieces with different specifications and arbitrary placement is an essential ability of industrial robots, while it cannot be met by traditional clamping methods. Vision technology brings flexibility and convenience to industrial robots, but the common two-dimensional technology only involves three degrees of freedom (plane displacement and rotation), which hinders the positioning of arbitrarily placing workpieces (often six degrees of freedom) and disorderly sorting. In addition, for typical visual tasks in industrial environments like defect detection, accurate distinguishing of such defects as pits and scratches is challenging under two-dimensional plane imaging. The introduction of three-dimensional information provides an effective solution to this problem. Thus, in the face of increasingly complex, flexible, intelligent and personalized manufacturing needs, the acquisition and processing of 3D visual information are of much importance.
An optical processor for matrix-by-vector multiplication: an application to the distance geometry problem in 1D

Abstract We present the architecture of a new optical processor specialized in matrix-by-vector multiplication via the manipulation of the light wavefront. This processor can reach up to 1.2 Giga MAC (multiply-accumulate) operations per second using commercially available devices. Moreover, this architecture is compatible with a hardware upgrade with the potential to achieve a processing speed of above Tera MAC per second. We initially present the optical processor and then discuss the use of such a processor for tackling a special class of the one-dimensional distance geometry problem, which is a well-known NP-hard problem.
The Effect of Round-Trip Translation on Fairness in Sentiment Analysis

Sentiment analysis systems have been shown to exhibit sensitivity to protected attributes.Round-trip translation, on the other hand, has been shown to normalize text.We explore the impact of round-trip translation on the demographic parity of sentiment classifiers and show how round-trip translation consistently improves classification fairness at test time (reducing up to 47% of between-group gaps).We also explore the idea of retraining sentiment classifiers on round-trip-translated data.
ESTIMASI MODEL REGRESI SEMIPARAMETRIK SPLINE TRUNCATED MENGGUNAKAN METODE MAXIMUM LIKELIHOOD ESTIMATION (MLE)

Regression modeling with a semiparametric approach is a combination of two approaches, namely the parametric regression approach and the nonparametric regression approach. The semiparametric regression model can be used if the response variable has a known relationship pattern with one or more of the predictor variables used, but with the other predictor variables the relationship pattern cannot be known with certainty. The purpose of this research is to examine the estimation form of the semiparametric spline truncated regression model. Suppose that random error is assumed to be independent, identical, and normally distributed with zero mean and variance , then using this assumption, we can estimate the semiparametric spline truncated regression model using the Maximum Likelihood Estimation (MLE) method. Based on the results, the estimation results of the semiparametric spline truncated regression model were obtained p=(inv(M'M)) M'y