Reviewerly/exHarmony huggingface dataset:
Turbulence video simulation using the spatiotemporal cross correlation of distortion fields

Previous simulations of atmospheric turbulence in videos are computationally complex. The purpose of this study is to develop an efficient algorithm for simulating spatiotemporal videos affected by atmospheric turbulence, given a static image. We extend an existing method for the simulation of atmospheric turbulence in a single image by incorporating turbulence properties in the time domain and the blurring effect. We accomplish this through analysis of the correlation between turbulence image distortions in time and in space. The significance of this method is the ease with which it will be possible to produce a simulation, given properties of the turbulence (including turbulence strength, object distance, and height). We apply the simulation to low and high frame rate videos, and we show that the spatiotemporal cross correlation of the distortion fields in the simulated video matches the physical spatiotemporal cross correlation function. Such a simulation can be useful when developing algorithms that apply to videos degraded by atmospheric turbulence and require a large amount of imaging data for training.
EUROPEAN EXPERIENCE OF TEACHERS TRAINING OF GENERAL EDUCATION INSTITUTIONS (ON THE EXAMPLE OF GERMANY, FRANCE AND ITALY)

Relevance: the integration processes in the relations between Europe and Ukraine on the organization of education and public life actualize the need to analyse the European experience in training future teachers, but the process of reforming the education system today has many problems in training highly qualified specialists in the field of education. Aim: determining the specifics of vocational teacher education in the leading countries of the European Community. Methods: analysis to determine the state of professional and pedagogical training of future teachers in Germany, France and Italy; generalization to formulate conclusions about the state of training of future teachers. Results: it is established that the ultimate goal of introducing inquiry-based learning in German teacher education is to increase the professionalization of future teachers, which can be described by two internationally known concepts: "teacher as a reflexive practitioner" and "teacher as a researcher"; it is determined that in France there are uniform standards of teacher education throughout the country, integration of theoretical, practical and research components of professional training; passing a competitive exam to fill a vacant position in educational institutions of various types due to the fact that teaching staff belong to the category of civil servants, a competency-based approach to the expected learning outcomes; the article reveals that the Italian teacher education system is based on a "sequential model" for secondary school teachers, which requires a strong disciplinary competence, followed by a one- or two-year training program. Conclusions: Germany has announced significant investments in the digitalization of education. The country is preparing for fundamental changes in the skills of its workforce by implementing digital initiatives and reorienting the adult education system. The teaching staff is aging, and Germany faces the challenge of replacing a large number of teachers. In France, efforts continue to improve educational outcomes and reduce inequality, with support for teaching staff and increased funding measures. Authorities face the challenge of balancing the rapid pace of reform with the need to consult with stakeholders to ensure optimal impact. The proportion of Italian teachers satisfied with their jobs is among the highest in the EU, but only a small proportion feel that their profession is valued. The level of higher education is low, and the transition from education to work remains difficult even for highly qualified people.
Metode Kopertif Tipe Jigsaw Terhadap Hasil Belajar Siswa Pada Bidang Studi Fiqih Kelas VIII DI MTS HJ. Siti Julia Secanggang Tahun Ajaran 2021-2022

Learning at MTs Hj . Siti Julia Secanggang this part big still use old method ie lecture , memorization and sometimes ask answer , if Thing this going on continously so can make participant educate bored in learn , if no there is variation method so participant educate will feel fed up accept lessons and _ Thing this is what causes participant educate no concentration , drowsiness and even sleep in in class moment lesson still going on , conditions thereby must quick overcome with change in teach , if before participant educate only come , sit down and shut up , then moment here it is participant educate must truly involved in process learning . Method jigsaw learning is wrong one method where participant educate in place to in team study heterogeneous up to five members six people . Various Theory academic served to participant educate in form text , and every participant educate responsible answer for learn one portion the material .With apply method learning this expected participant educate have experience new in learn , as well could reach destination the learning in expect , because destination from learning that on the main thing is is reach competencies that have set , by because that various type method and strategy need used for participants educate no feel fed up with learning the . The method used in this study is a quantitative method, with the aim of knowingHow InfluenceMethod Cooperative Jigsaw Type Against Results Study Student on Field Studies Jurisprudence Class VIII at MTs Hj . Siti Julia Secanggang Year 2021-2022.
Artificial Intelligence Driven Chatbot

Today, most large-scale conversational AI agents (e.g. Alexa, Siri, or Google Assistant) are built using manually annotated data to train the different components of the system. Typically, the accuracy of the ML models in these components are improved by manually transcribing and annotating data. As the scope of these systems increase to cover more scenarios and domains, manual annotation to improve the accuracy of these components becomes prohibitively costly and time- consuming. In this paper, a group of Amazon researchers propose a system that leverages user-system interaction feedback signals to automate learning without any manual annotation. Users here tend to modify a previous query in hopes of fixing an error in the previous turn to get the right results. These reformulations, which are often preceded by defective experiences caused by errors in ASR, NLU, ER or the application. In some cases, users may not properly formulate their requests (e.g. providing partial title of a song), but gleaning across a wider pool of users and sessions reveals the underlying recurrent patterns. The proposed self-learning system automatically detects the errors, generate reformulations and deploys fixes to the runtime system to correct different types of errors occurring in different components of the system. The results show that the approach is highly scalable, and able to learn reformulations that reduce Alexa-user errors by pooling anonymized data across millions of customers.
Penerapan Sistem Informasi Akuntansi Terhadap Transaksi Bisnis Perusahaan

This study aims to determine the application of accounting information systems to business transactions at a motorcycle sales and service company. The method used in this research is qualitative where the data collection is obtained through interviews, documentations, and observations. Based on research conducted, the use of this information system is very helpful for companies in carrying out business transactions so that they are more effective and efficient. In addition, an unstable internet network is one of the obstacles that hinder the process of recording transactions.
Quality Improvement Strategies of Mobile Phone Product Based on Text and Sentiment Analysis

The development of the Internet has brought people the opportunity to communicate online, and user reviews have appeared under the review interface of various brands of hot products, and these reviews containing emotions have also intensified the competition among products.This paper takes cell phone background as an example, through data mining cell phone user reviews, using word frequency and word cloud methods for text analysis of user reviews, extracting two types of hot review words-[service features] and [cell phone features], exploring whether each hot review word behind can significantly affect the favorable rating of cell phones by establishing a random forest regression model, and calculating the corresponding sentiment score of each hot review word according to the sentiment tendency calculation method.Finally, this paper analyzes each hot review term in depth and designs a specific evaluation system, which can be used to paint an overall and detailed portrait of the cell phone, thus helping merchants to quickly find the shortcomings of the product and determine the direction of improvement.
Restarting virtual reality in journalism? A quantitative analysis of problems and potentials of selected immersive apps as perceived by their users

Since its emergence in the 1960s, virtual reality (VR) has generated significant enthusiasm among researchers and practitioners, as well as technology and media companies. In journalistic practice, however, VR has so far only been able to compete to a limited extent. This paper first establishes the status quo of VR apps in the journalistic field as found in the Oculus Store, and then analyses the user comments (N = 770) of 15 VR apps produced by journalistic media outlets to evaluate their perceptions in terms of the constructs of immersion, emotion, usability, and utility. Results show that users positively highlight VR’s capacities to elicit immersion and emotion, while technological aspects of usability and utility are often assessed negatively. Additionally, positive emotional and immersive reactions in VR are possible despite flaws in technology, and a positive immersion is also associated with a positive emotional VR experience. Derivations for a potential restart of VR apps in journalism are drawn.
Layout-based Smart Manufacturing Assessment Method and System

4차 산업혁명의 도래로 스마트 제조 환경 구현은 선택이 아닌 필수가 되었다. 글로벌 대기업은 막대한 투자와 경험을 기반으로 베스트 프랙티스를 발표하고 있다. 일반적으로 스마트 제조는 중소기업에서도 충분히 구현할 수 있는 개념이다. 그러나 중소기업은 스마트 제조를 실현할 투자, 시간 및 기술을 보유하고 있지 못하다. 각 중소기업들은 현재 상태에서 스마트 제조 환경을 구현할 수 있는 상태로 전환하기 위한 개선 계획이 필요하다. 따라서 현재 상태를 진단하는 것은 개선 계획을 개발하는 데 중요하다. 이 논문에서는 중소기업들이 스마트 제조 진단을 수행하는 데 도움이 될 수 있는 자가 진단 방법과 시스템에 대해 설명한다. 베트남 중소제조기업에 적용된 사례도 소개한다. With the advent of the fourth industrial revolution, implementing smart manufacturing (SM) technologies has become essential, not optional. Large, global companies are publishing best practices based on huge investment and time-consuming experiences. The general view is that smart manufacturing system (SMS) is a concept that can also be implemented by small and medium-sized manufacturers (SMMs) with similar benefits. SMMs, however, do not have the investment, time, or skills to realize those benefits. Each SMM will require an improvement plan for transition from their current state to a state where they can implement SMS. Therefore, assessing that current state is critical to develop such a plan. This paper describes a self-assessment method and system that can help SMMs to perform that assessment. It also introduces the application cases of the assessments of Vietnamese SMMs.
An Analysis of the Listening and Reading Sections of the Newly Published Japanese English Textbooks for Primary School

In 2020, Japan started a new English curriculum in which English classes began from grade 5, based on the latest edition of the Course of Study (the guideline produced by the Ministry of Education, Culture, Sports, Science, and Technology (MEXT). The objectives of this research paper are to examine seven sets of newly published English textbooks’ reading and listening sections to learn about their specific features, as well as their difficulty levels. The result demonstrates that in all seven sets of textbooks, the listening sections have far more volume of content than the reading sections. The readability tests indicate that the reading sections contain higher levels of sentences, which contradicts the authors’ initial impression. However, a careful study of the use of past tense verbs and prepositions in each section demonstrates that there are more prepositions in all seven sets of textbooks in the listening sections. The results indicate that past tense verbs and prepositions can be effective benchmarks to measure the readability level of these newly published English textbooks.
IMPROVING STUDENTS’ SPEAKING SKILL THROUGH VISUAL AIDS IN THE SECOND YEAR STUDENTS OF ENGLISH EDUCATION DEPARTMENT STATE ISLAMIC UNIVERSITY OF ALAUDDIN MAKASSAR

This research was an experimental research. This research aimed to find out the improvement of students’ speaking skills with a research objective; to find out the improvement of Students’ Speaking Skills by using visual aids in the Second Year Students of the English Education Department State Islamic University of Alauddin Makassar. The visual aids that the researcher used in this research were pictures and videos. This research was conducted at English Education Department State Islamic University of Alauddin Makassar the second-year students. In this research, the population was 101 students in the second year of EED. The sample was 50 students. There were 25 students in EED A as an experimental group and 25 students in EED B as a control group. The instrument that the researcher used in this research to collect data were speaking tests. The data were analyzed quantitatively using SPSS 23.0 version. The findings of the research showed that the use of visual aids was able to improve students’ speaking skill in the Second Year Students of English Education Department State Islamic University of Alauddin Makassar.
PENGARUH PENAMBAHAN SISTEM IOT RASPBERRY PI TERHADAP KECEPATAN CETAK DAN TINGKAT PRODUKTIVITAS OPERATOR 3D PRINTER REPRAP

Most of desktop-scale 3D printers are based on the open-source design of the ReplicatingRapid Prototyper (REPRAP) community. One aspect that can be developed in REPRAP 3Dprinters is the addition of Internet of Things (IoT) technology. Therefore, a Raspberry Pi-based IoTsystem that can be implemented on a REPRAP 3D printer is developed. The IoT system allowsthe 3D Printer to connect into internet network and has a website-based interface. This study aimsto compare the impact of Raspberry Pi based IoT systems implementation on the 3D printingspeed and to measure productivity level of 3D printer operator. Testing is done by printing fourobjects when the IoT system has not been added to the 3D printer and printing four objects whenthe IoT system has been added to the 3D printer. In testing, the data on the printing time of eachobject is obtained, this data is used to compare the print speed between before and after the 3Dprinter was added to the IoT system. Furthermore from testing, the data of time required byoperators to prepare and monitor the performance of 3D printers is also obtained, this data is usedto compare the productivity levels of 3D printer operators before and after adding the IoT system.Based on the test results, it was found that 3D printers with IoT systems have faster printpreparation times than 3D printers without IoT systems. However, 3D printers with IoT systemshave a longer machine time than 3D printers without IoT systems. The operator productivity levelfor 3D printers with IoT systems is higher than 3D printers without IoT systems.
Towards Practical Explainability with Cluster Descriptors

With the rapid development of machine learning, improving its explainability has become a crucial research goal. We study the problem of making the clusters more explainable by investigating the cluster descriptors. Given a set of objects <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$S$</tex> , a clustering of these objects <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\pi$</tex> , and a set of tags <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$T$</tex> that have not participated in the clustering algorithm. Each object in <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$S$</tex> is associated with a subset of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$T$</tex> . The goal is to find a representative set of tags for each cluster, referred to as the cluster descriptors, with the constraint that these descriptors we find are pairwise disjoint, and the total size of all the descriptors is minimized. In general, this problem is NP-hard. We propose a novel explainability model that reinforces the previous models in such a way that tags that do not contribute to explainability and do not sufficiently distinguish between clusters are not added to the optimal descriptors. The proposed model is formulated as a quadratic unconstrained binary optimization problem which makes it suitable for solving on modern optimization hardware accelerators. We experimentally demonstrate how a proposed explainability model can be solved on specialized hardware for accelerating combinatorial optimization, the Fujitsu Digital Annealer, and use real-life Twitter and PubMed datasets for use cases. Reproducibility materials: Link
Inventory Purchase Recommendation for Merchants in Traditional FMCG Retail Business

Small and micro merchants in the traditional FastMoving Consumer Goods (FMCG) retail business play a vital role in developing economies. In Indonesia, 82% of the population gets their day-to-day groceries from traditional trade merchants. Our work aims to help these grocery merchants prosper by increasing their sales and improving their inventory turnover cycle. To this end, we conduct an in-depth analysis of merchants’ inventory-buying behaviors from a transaction record dataset and propose several item recommendation methods for merchants’ inventory based on insights gathered from the data. For analysis, we investigate the stock-keeping unit (SKU) coverage, the SKU selling speed, merchant repeat purchase patterns, the growth rate of monthly spending, as well as their correlations with total monetary spending by merchants. Our recommendation methods consider recency and utility of SKU selling speed, and are implemented using popular item-based recommendation and content-based filtering algorithms. The inventory recommendation system was deployed and tested in production. Initial results show a lift in click-through rate (CTR) and also show that merchants are accepting the recommendations of SKU items for their inventory that they had never bought before.
Penerapan Algoritma C4.5 Untuk Prediksi Keterlambatan Pembayaran Sumbangan Pembinaan Pendidikan (SPP) Santri

SPP is a mandatory fee for students used by Islamic boarding schools to facilitate all learning activities carried out by students, with a predetermined payment time. One of the problems in paying tuition fees is the case of students being late in paying tuition fees. The problem of late payment of tuition fees is something that must be considered because this can affect the implementation of education and fulfillment of needs and result in a decrease in the financial income of the pesantren. If the problem of late tuition payments can be predicted more quickly, then the management can prevent and anticipate earlier. To overcome this problem, the c4.5 algorithm is applied to predict late payment of tuition fees in order to produce a pattern based on the classification results. By using the variables of Parents' Income, Dependents, Father's Job, First Payment, Second Payment and Third Payment. This is done to see students who have the potential to be late in making tuition payments so that they can anticipate a decline in the financial income of the pesantren. In this study, the accuracy of the c.45 algorithm method has been tested for prediction of late tuition payments using the confusion matrix formula with an accuracy of 76.92%.
YFACC: A Yorùbá Speech–Image Dataset for Cross-Lingual Keyword Localisation Through Visual Grounding

Visually grounded speech (VGS) models are trained on images paired with unlabelled spoken captions. Such models could be used to build speech systems in settings where it is impossible to get labelled data, e.g. for documenting unwritten languages. However, most VGS studies are in English or other high-resource languages. This paper attempts to address this shortcoming. We collect and release a new single-speaker dataset of audio captions for 6k Flickr images in Yoruba=-a real low-resource language spoken in Nigeria. We train an attention-based VGS model where images are automatically tagged with English visual labels and paired with Yoruba utterances. This enables cross-lingual keyword localisation: a written English query is detected and located in Yoruba speech. To quantify the effect of the smaller dataset, we compare to English systems trained on similar and more data. We hope that this new dataset will stimulate research in the use of VGS models for real low-resource languages.
Tingkat Pemanfaatan Bahan Koleksi sebagai Pemenuhan Kebutuhan Informasi pada Anak di Rumah Literasi Ranggi Sumatera Utara

Reading books for children is very important for a child's growth and development, especially when entering a formal educational environment such as elementary school. This activity aims to explore the benefits of having a literacy house, especially to improve children's learning abilities. Using participatory rural appraisal methods or techniques and data collection techniques through interviews, observation, focus group discussions and literature review. The results of the study show that the Ranggi Literacy House at the PWI Complex, Percut Sei Tuan, Deli Serdang acts as a source of learning for children, especially underprivileged children, a place for character formation, and a source of information for parents. in child care, community recreation and training facilities, even facilities for mothers to express their talents. The results of the study indicate that the availability of children's literature in the mother and child library services is quite adequate. Judging from the suitability of literature for the age level and information needs of children, it is in accordance with the availability of 3D collections for children who cannot read, and the availability of fairy tales, comics, religious books, history books, and other textbooks. The use of children's literature at the Ranggi Literacy House is quite good. This is shown by the enthusiasm of users in reading literature and utilizing the available facilities. Obstacles faced by the Ranggi Literacy House in improving the reading culture of its users: they do not yet have an audio-visual collection, even though audio-visual collections can contribute to improving children's reading culture because in reality children tend to prefer using technology and prefer to see and hear. However, in fulfillment of this, the Ranggi Literacy House also often holds watching folklore or other stories together as a form of character education for children.&#x0D; Keywords: Reading garden, learning resources, educational-recreational information sources.