Reviewerly/exHarmony huggingface dataset:
Kesalahan dan Interferensi Bahasa Pada Buku Ajar Bahasa Arab Madrasah Tsanawiyah

Mistakes will often be found in using Arabic both orally and in writing. This phenomenon is not uncommon. However, it has become commonplace due to the lack of ability of language users, especially Indonesian learners, to understand the structure of a second language, namely Arabic. Including elements of the first language into the second language has led to language deviations. Therefore, this study aims to examine errors and language interference found in Arabic textbooks for class VIII MTs (KEMENAG) in 2020. This research is qualitative research using error analysis methods. The data sources used are Arabic phrases and clauses, which have been identified based on the form of the error. The result of this study is that there are language errors in Arabic writing which are classified into several errors based on syntactic, phonological, morphological, and cultural aspects. Meanwhile, language interference was found based on morphological and cultural aspects.
A novel multidimensional uncalibration method applied to six-axis manipulators

This study proposes a multidimensional uncalibrated technique for tracking and grasping dynamic targets by a robotic arm in the eye-in-hand mode. This method avoids complex and cumbersome calibration processes, enabling machine vision tasks to be adaptively applied in a variety of complex environments, which solved the problem of traditional calibration methods being unstable in complex environments. The specific method used in this study is first, in the eye-in-hand mode, the robotic arm moves along the x, y , and z axes in sequence, and images are taken before and after each movement. Thereafter, the image Jacobian matrix is calculated from the three (or more) sets of images collected. Finally, the robotic arm converts the target coordinates in the real-time captured images by the camera into coordinates in the robotic arm coordinate system through the image Jacobian matrix and performs real-time tracking. This study tests the dynamic quasi-Newton method for estimating the Jacobian matrix and optimizes the initialization coupling problem using the orthogonal moving method. This optimization scheme significantly shortens the iteration process, making the uncalibrated technology more fully applied in the field of dynamic object tracking. In addition, this study proposes a servo control algorithm with predictive compensation to mitigate or even eliminate the systematic error caused by time delay in dynamic target tracking in robot visual servo systems.
Central Submonads and Notions of Computation: Soundness, Completeness and Internal Languages

Monads in category theory are algebraic structures that can be used to model computational effects in programming languages. We show how the notion of "centre", and more generally "centrality", i.e., the property for an effect to commute with all other effects, may be formulated for strong monads acting on symmetric monoidal categories. We identify three equivalent conditions which characterise the existence of the centre of a strong monad (some of which relate it to the premonoidal centre of Power and Robinson) and we show that every strong monad on many well-known naturally occurring categories does admit a centre, thereby showing that this new notion is ubiquitous. More generally, we study central submonads, which are necessarily commutative, just like the centre of a strong monad. We provide a computational interpretation by formulating equational theories of lambda calculi equipped with central submonads, we describe categorical models for these theories and prove soundness, completeness and internal language results for our semantics.
Determining the Irrigation Performance of Solar Panels Operating with a Sun Tracking System

In the study, utilizing the relationship established between plant water consumption and solar radiation, an irrigation system was attempted to be automated through a Programmable Logic Control (PLC) controlled program for tomato plants grown in an open field. The system has obtained its required energy through solar panels, utilizing solar energy as its power source. The performance of the system has been attempted to be evaluated through the yield and quality parameters of the cultivated plants by yield, mean fruit weight and width, titratable acidity, total solids, pH, leaves (fresh+dry) weights, stem (fresh+dry) weights, leaf area, plant height. The PV panels used in the system were equipped with a solar tracking system to pump more water at a lower cost. This has led to an increase in the efficiency of the panels.&#x0D; The solar radiation values obtained with a pyranometer sensor during irrigation were processed through the software written in the PLC's memory. The amount of water consumed by the plant the next day was calculated, and it was attempted to be automatically supplied to the plant's root zone at 10:00 am. The system has been made continuous by being controlled with automation and SCADA. The development of the plants, temperature, humidity, and radiation levels were measured, and the system's irrigation performance was determined according to the moisture level change in the soil.
Study Survey of Increasing Arabic Learning Due to Smartphones

The Covid-19 pandemic has grown and spread in various countries, changing various areas of people's lives, especially in Indonesia, some time back. The purpose of this observation is to find out the use of smartphones for students of Junior High School madrasahwhen studying online. This observation is through a quantitative approach through the survey study method and selecting a random sample by establishing10 speakers who live in dormitories, namely Junior High School grade 7 students who have obtained questionnaire answers using google from. The research tool is adapted from several writings. The tool is made from 5 questions. The observation results found that there were seven people who had their own smartphones and three students used the smartphones of their parents, siblings and other people in online learning, while the time used to study through smartphones was between 5 to 6 hours. The students of Junior High School use smartphones are classified as a good category in learning because they can do and collect tasks well. So students discussed it with their friends, and all felt satisfied with using smartphones in online learning activities. Saran for the next researcher to use the variables of attitude and the impact of using smartphones for Junior High School students who have their own smartphones
Central Bank Digital Currencies Analyzed in a Banking School versus Currency School Framework

Abstract This article analyses the justifications for the creation of central bank digital currencies – CBDCs – and their anticipated features with the aim of looking at them from two different and somewhat opposing perspectives. These perspectives define the two broad historical and logical currents that emerged in the Banking School versus the Currency School debates. We are going to investigate to which extent can the concept of CBDC be embedded into the Banking School’s body of thought and to which extent can it be criticized with the arguments of the Currency School.
NAVIGATION STRATEGY FOR MOBILE ROBOT BASED ON COMPUTER VISION AND YOLOV5 NETWORK IN THE UNKNOWN ENVIRONMENT

Intelligent mobile robots must possess the ability to navigate in complex environments. The field of mobile robot navigation is continuously evolving, with various technologies being developed. Deep learning has gained attention from researchers, and numerous navigation models utilizing deep learning have been proposed. In this study, the YOLOv5 model is utilized to identify objects to aid the mobile robot in determining movement conditions. However, the limitation of deep learning models being trained on insufficient data, leading to inaccurate recognition in unforeseen scenarios, is addressed by introducing an innovative computer vision technology that detects lanes in real-time. Combining the deep learning model with computer vision technology, the robot can identify different types of objects, allowing it to estimate distance and adjust speed accordingly. Additionally, the paper investigates the recognition reliability in varying light intensities. The findings of this study offer promising directions for future breakthroughs in mobile robot navigation
The Improvement of The Students' Vocabulary by Using Crossword Puzzle

This study aims to help overcome the problems that exist in class VII B students of SMPN 1 Jabiren Raya, Pulang Pisau Regency, Jabiren Raya District. A total of 30 students were the subjects in this study. After conducting a pre-observation, a problem was found, namely related to the vocabulary that students still have a little. Therefore, to overcome this problem, the researcher used Crossword Puzzle printed on HVS paper as a method to help improve students' vocabulary. This research uses Classroom Action Research (CAR) method. This research design uses collaborative classroom action research. This study collaborated with the English teacher of SMPN 1 Jabiren Raya as a collaborator and observer. The model in this study uses the Kurt Lewin Model where the stages in each cycle begin with the stages of Planning, Action, Observation, and Reflection. This study consisted of two cycles in which in each cycle there was 1 meeting with a duration of 3 subject hours. To collect data, researchers used research instruments: Vocabulary Test, Interview, and Questioner. After the implementation of this research, there was an increase in students’ vocabulary. It can be seen from the increase in each cycle, namely in cycle 1 students got 53.3% classical completeness and increased in cycle 2 to 90% after conducting vocabulary tests through multiple choice. Therefore, based on the research that has been conducted, the Crossword Puzzle method can improve students' vocabulary.
A Novel Approach for Quaternion Algebra Based JSEG Color Texture Segmentation

In this work, a novel colour quantization approach has been applied to the JSEG colour texture segmentation using quaternion algebra. As a rule, the fundamental vectors of the colour space are derived by inverting the three RGB colour directions in the complex hyperplanes. In the proposed system, colour is represented as a quaternion because quaternion algebra provides a very intuitive means of working with homogeneous coordinates. This representation views a colour pixel as a point in the three-dimensional space. A novel quantization approach that makes use of projective geometry and level set methods has been produced as a consequence of the suggested model. The JSEG colour texture segmentation will use this technique. The new colour quantization approach utilises the binary quaternion moment preserving thresholding methodology, and is therefore a splintering clustering method. This method is used to segment the colour clusters found inside the RGB cube and the colour consistency throughout the spectrum and in the space are both considered. The results of the segmentation are compared with JSEG as well as with the most recent standard segmentation techniques. These comparisons show that the suggested quantization technique makes JSEG segmentation more robust.
ANALISIS SENTIMEN TWITTER TERHADAP PERLINDUNGAN DATA PRIBADI DENGAN PENDEKATAN MACHINE LEARNING

As technology and information advances, the main defense and security aspects in the protection of personal data become very important. Protection of personal data is a human right that must be protected by the state. Data digitization is a demand and challenge in the advancement of information. Efforts in protecting personal data are basically carried out through legal certainty instruments in the form of regulations that regulate a system in order to realize a strong system in protecting cyber crime. Various regulations already exist in the legal system in Indonesia. Nevertheless, there are still cases of personal data leakage among Indonesians. The purpose of this study is to describe the condition of personal data protection in Indonesia and analyze cases of data leaks detected in Twitter tweets in the period July 1, 2021 to September 29, 2022. The study was conducted by using Twitter tweet scrapping techniques and classifying netizen responses based on positive, negative, and negative sentiments. neutral. Each sentiment is analyzed with wordcloud by finding what topics are often discussed by netizens on the protection of personal data. Furthermore, the classification evaluation is continued by looking at the accuracy of the machine learning classification algorithm, namely naive bayes and random forest. The results of the study stated that in the period from July 1, 2021 to September 29, 2022, the public's response to the protection of personal data was still negative. Which means that the data protection system in Indonesia is still not effective with the occurrence of various cases of data leakage. Based on the accuracy value, the Naive Bayes algorithm is very good at classifying tweets based on their sentiments, which is 99.84% compared to the random forest algorithm.
Information Literacy Through the Lubuklinggau Regional Fairy Tale Application Shaping the Character of Students

The development of modern technology greatly influences changes in several fields, including education.Due to the development of technology and information, it is possible to combine information systems with regional languages and cultures.Mobile technology is also growing rapidly, this can be seen from the number of applications or websites that run on mobile devices.The purpose of this study is to describe regional culture through literacy in regional fairy tales mobile application in order to shape the character of students in Lubuklinggau City.This media can be accessed via smartphone or tablet.Variety of media that can be used This application uses local culture.Using the waterfall method (system engineering, analysis, design, coding, testing, and maintenance).This application can produce cultural values that are almost abandoned by the younger generation or students.
Pengaruh Penerapan Sistem Absensi Fingerprint Dan Kompensasi Terhadap Tingkat Efektivitas Kinerja Di Kantor Bina Mandiri Syariah Bekasi

This study aims to determine the effect of the application of fingerprint attendance and compensation on the level of effectiveness of the performance of employees of the Bina Mandiri Syariah Cooperative in bekasi city. The population in this study was all employees at the Bina Mandiri Syariah office in Bekasi City. using total sampling technique, all 27 employees were used as research respondents. The analysis technique used is multiple regression analysis with t-test and F test. Based on the results of the study, the regression equation was obtained as follows: Y' = 10.027 + 0.395 X1 + 0.399 X2+ e. This regression equation shows that performance is affected by the use of fingerprint attendance and compensation. The results of another study concluded that the use of fingerprint attendance and compensation had a positive and significant influence on employee performance at the Bekasi Bina Mandiri Syariah Office so that all research hypotheses were accepted.
Pembelajaran Daring Melalui Whatsapp Dalam Capaian Kehadiran, Aktivitas Belajar Dan Hasil Belajar di Masa Pandemi

The purpose of this study was to determine learning, student learning experiences and learning activities and online learning outcomes through WhatsApp, This type of research uses qualitative research. data collection with the method of observation, interviews, and documentation. The results of the study show that online learning at the PAI Study Program, Muhammadiyah University of Palembang uses the WA application, Google meeting, zoom, and google classroom. lecturer in PAI Study Program Achievement of student attendance in online learning from 100 percent, 90 percent, even 80 percent. active in learning. Learning outcomes are said to be good by showing that students know, understand, like, and are satisfied during the learning process.
Employment of Audacity Application for Vocabulary Lessons

In this day and age, technology has explored every line, including the world of education. There are many technologies that can be used in education, one of which is Audacity. Audacity is an application that is used to edit sound or audio. This application can be downloaded via desktop or android. One of the Arabic language learning used in this application is Istima’. This research is a qualitative descriptive research. Descriptive research is research that can examine literature reviews or describe phenomena that occur in the world of education. The purpose of this study is to describe the use of the Audacity application as an effort to strengthen students' interest in learning, this study uses qualitative research methods that are literature studies, while the sources of literature in this study are journals and books in the form of e-modules. As for how to use the application using an audacity account by utilizing the audacity application.
Virtual reality: the gateway for non-professionals to solve complex design problems

Leopoly is working on a 3D design software for VR called Shapelab with the aim to provide tools for professional and hobby 3D artists. During development, we have been approached by users coming from various professional backgrounds other than artistic 3D design, which made us want to explore the possibilities virtual reality has to offer for these use cases. We argue that VR could open doors for people with no background in 3D modeling to solve complex design problems needed to digitize their traditional workflows.
A benchmarking for public information by Machine Learning and Regular Language

Technologies such as Big Data and Transfer Learning have been attracting the interest of industry and academia over the last 15 years. The consequence of this is an almost unanimous preference for technological solutions that use statistical models. This technology is causing a revolution in the information extraction process. In this research, we question whether this technique is the best solution for extracting information from documents. We compare machine learning (ML) and rule-based approaches in the task of recognizing legal entities in the official gazette. We built an annotated dataset with 100 examples of legal documents and submitted this model to an evaluation in IBM Watson Knowledge Studio (WKS). We show that, in a scenario where documents follow a formal structure, rules-based information extraction systems still present themselves as low-cost, more uncomplicated, and more efficient solutions.
Politeness in Tiba Meka ritual in Manggaraian language and culture, Eastern Indonesia

Politeness is crucial to communicating among individuals or between groups in a speech community. This research mainly explores the politeness of welcoming guests in the Manggaraian speech community. Video recording and interviews were the techniques used to collect the data. Eight videos were recorded and transcribed in text. The data were interpreted in socio-pragmatics theory. The findings reveal that the Manggaraian speech community tend to apply positive and off-the-record politeness strategies. A positive politeness strategy was mainly employed to build a close relationship and friendliness and to show respect to a guest. The use of a positive politeness strategy was marked in honorifics such as ite, mori, ema, and downtoner yo. An off-the-record politeness strategy was utilised to designate generosity, modesty, and approbation to a guest. This politeness strategy was indicated in metaphorical expressions. The social factors that determine the use of those politeness strategies are related to the context of the event, age, relation, and guest status. In this study, the Manggaraian speech community employ politeness in the ritual of welcoming a guest to achieve three benefits: manifesting respect, maintaining a good relationship, and showing a positive attitude toward the guest.
Diagnostic Accuracy of Fine Needle Aspiration Cytology of Breast Masses, and Morphologic Patterns of Breast Lesions, Hawassa, Sidama Ethiopia: A Five-Year Review

Most breast diseases are presented as mass lesions that can be easily detected by the patients or during clinical examination and breast imaging.Fine needle aspiration biopsy of the breast is an unquestionably useful test in differentiating various benign and malignant breast lesions however its diagnostic accuracy is still poorly known.Therefore, this study was conducted to evaluate the validity and diagnostic performance of fine needle aspiration cytology (FNAC) in diagnoses of breast masses and describe morphologic patterns of breast pathology in Hawassa University Comprehensive Specialized Hospital.This is a five years retrospective cross-sectional study of all breast lumps that underwent fine needle aspiration cytology and subsequent histopathology evaluation in the Department of Pathology, Hawassa university comprehensive specialized hospital Sidama, Ethiopia from September 2015 to August 2019.Sensitivity, specificity, positive and negative predictive value, and diagnostic accuracy were calculated and morphologic patterns of breast pathology were described.Fibroadenoma and invasive ductal carcinoma were the most common benign and malignant breast lesions, respectively.The sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy of fine needle aspiration cytology of breast lumps were found to be 97.64%,95.89%, 96.5%, 97.2%, and 96.8% respectively.FNAC is a valid method with high sensitivity and specificity for preoperative diagnosis of breast lesions, and we recommend the popularization of FNAC in our practice to complement histological diagnosis of breast lesions for early diagnosis and optimum treatment of our patients.
Assessing Biases through Visual Contexts

Bias detection in the computer vision field is a necessary task, to achieve fair models. These biases are usually due to undesirable correlations present in the data and learned by the model. Although explainability can be a way to gain insights into model behavior, reviewing explanations is not straightforward. This work proposes a methodology to analyze the model biases without using explainability. By doing so, we reduce the potential noise arising from explainability methods, and we minimize human noise during the analysis of explanations. The proposed methodology combines images of the original distribution with images of potential context biases and analyzes the effect produced in the model’s output. For this work, we first presented and released three new datasets generated by diffusion models. Next, we used the proposed methodology to analyze the context impact on the model’s prediction. Finally, we verified the reliability of the proposed methodology and the consistency of its results. We hope this tool will help practitioners to detect and mitigate potential biases, allowing them to obtain more reliable models.