Reviewerly/exHarmony huggingface dataset:
Archimedes Revisited and Beyond

Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Twitter Facebook Reddit LinkedIn Tools Icon Tools Reprints and Permissions Cite Icon Cite Search Site Citation Terrence Toepker; Archimedes Revisited and Beyond. Phys. Teach. 1 December 2023; 61 (9): 780–784. https://doi.org/10.1119/5.0107227 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAmerican Association of Physics TeachersThe Physics Teacher Search Advanced Search |Citation Search
Automated handwriting recognition using artificial intelligence algorithms: Russian and foreign experience

The review is devoted to software solutions and projects for automated recognition of handwritten texts of historical sources, made in the Russian Federation and abroad. The author considers the most famous OCR/HTR services presented online, focuses on Internet resources on European and Eastern (Japanese, Chinese) paleography, and describes the basic technological principles for their implementation.
PENGARUH PENGGUNAAN VIDEO EDUKASI MENSTRUASI DAN KESEHATAN REPRODUKSI WANITA TERHADAP PEMAHAMAN TENTANG MENSTRUASI PADA SISWI KELAS VI DI SLB NEGERI 1 GIANYAR

Adolescence is a period of transition from child to adult, not only psychologically but also physically, and for teenage girls they experience menstruation. No exception, deaf female students also experience this period, but deaf children experience problems with their sense of hearing, causing limitations in children's ability to obtain information. information, especially information about menstruation. As with the problem of class VI female students at SLB Negeri 1 Gianyar, deaf female students' understanding of menstruation is still very low. For this reason, researchers have high hopes of being able to solve the problems experienced by female students with reproductive health educational videos as a medium and learning model that focuses on understanding the menstrual process of female students. By knowing the problems that exist in deaf children, motivation and encouragement are needed in learning. So that it is easier for students to understand the learning given by the teacher. Like the deaf female students in class VI at SLB Negeri 1 Gianyar who had difficulty understanding the menstrual process. For this reason, learning models and media are needed that can help students' understanding. Existing problems can be tested through classroom action research, which is carried out classically, and uses a quantitative approach with a type of pre-experimental research.&#x0D; ABSTRAKMasa remaja adalah masa peralihan dari anak-anak ke dewasa bukan hanya dalam artian psikologis tetapi juga fisik, dan bagi remaja perempuan mengalami menstruasi Tidak terkecuali, siswi tunarungu juga mengalami masa tersebut, tetapi anak tunarungu mengalami gangguan pada indra pendengaranya sehingga menyebabkan keterbatasan anak dalam memperoleh informasi, terutama informasi tentang menstruasi. Seperti pada permasalahan siswi kelas VI di SLB Negeri 1 Gianyar, pemahaman menstruasi siswi tunarungu masih sangat rendah. Untuk itu peneliti mempunyai harapan besar untuk dapat memecahkan permasalahan yang di alami oleh siswi dengan video edukasi kesehatan reproduksi sebagai salah satu media dan model pembelajaran yang menitik beratkan pada pemahaman proses menstruasi siswi. Dengan mengetahui permasalahan yang ada pada anak tunarungu sangat diperlukan motivasi dan dorongan dalam pembelajaran. Supaya peserta didik tersebut lebih mudah dalam memahami pembelajaran yang diberikan oleh guru. Seperti pada siswi tunarungu kelas VI di SLB Negeri 1 Gianyar yang mengalami kesulitan dalam memahami proses menstruasi. Untuk itu diperlukan model dan media pembelajaran yang dapat membantu pemahaman peserta didik. Permasalahan yang ada dapat diuji melalui penelitian tindakan kelas, yang dilakukan secara klasikal, dan menggunakan pendekatan kuantitatif dengan jenis penelitian pra eksperimen.&#x0D;
USING VIDEOS AS A TEACHING MEDIA FOR READING COMPREHENSION: DOES IT WORK?

There are various strategies and techniques of teaching used by teachers to improve students' reading comprehension. The most widely used and challenging tasks for teachers are the implementation of the media. In this study, the researcher employed video of narrative text as a considerable media to enhance students' reading comprehension and as a way to get students attention to study. Moreover, few studies report on the of videos used in teaching learning process in which any result will actually be considered beneficial to the development of teaching. Video of narrative text is a sequence of narrative text which is visualize in form of video. In conducting this study, the researcher used quasi experimental research design. Following the idea, this study was designed to investigate the effect of using video of narrative text on the students' reading comprehension. The tenth-grade students of one of the private schools in Malang were used as the target population of this study. The required data were collected through achievement test. Due to the need to understand the effect, ttest was employed in this present study. The result of this study showed that the use of video of narrative text did not give a significant effect on the students' reading comprehension. It was proven from the calculation result of independent sample ttest. Half of them showed improvement in their but half of them did not. Therefore, there was no significant different between students who taught by using video of narrative text and original text.
THE ANALYSIS OF STUDENTS’ NEED IN LEARNING ENGLISH (A DESCRIPTIVE QUALITATIVE RESEARCH DESIGN TOWARD STUDENTS OF LAW AND BUSINESS ADMINISTRATION UNIVERSITY OF KAPUAS SINTANG)

This study is intended to analyze students’ need in learning English for specific purposes. This descriptive qualitative research design is engaged 50 students as participants. There are 25 of Law students and 25 of business students are chosen as participants of this study. This study is provided 9 items of questionnaire as the tool for data collecting. SPSS as the medium for helping the researcher in analyzing data collection. The result of this study revealed that the most difficulties aspect in learning English is aspect of speaking. Meanwhile, the main purpose of students to learn English is to be able to speak English fluently. This result as important feedback for the instructors or lecturer to decide what should be done in providing an appropriate material in English class based on students’ needs.
Computational scaling in inverse photonic design through factorization caching

Inverse design coupled with adjoint optimization is a powerful method to design on-chip nanophotonic devices with multi-wavelength and multi-mode optical functionalities. Although only two simulations are required in each iteration of this optimization process, these simulations still make up the vast majority of the necessary computations and render the design of complex devices with large footprints computationally infeasible. Here, we introduce a multi-faceted factorization caching approach to drastically simplify the underlying computations in finite-difference frequency-domain (FDFD) simulations and significantly reduce the time required for device optimization. Specifically, we cache the numerical and symbolic factorizations for the solution of the corresponding system of linear equations in discretized FDFD simulations and re-use them throughout the device design process. As proof-of-concept demonstrations of the resulting computational advantage, we present simulation speedups reaching as high as 9.2× in the design of broadband wavelength and mode multiplexers compared to conventional FDFD methods. We also show that factorization caching scales well over a broad range of footprints independent of the device geometry, from as small as 16μm2 to over 7000μm2. Our results present significant enhancements in the computational efficiency of inverse photonic design and can greatly accelerate the use of machine-optimized devices in future photonic systems.
Cost Reduction of Kafka Clusters

This chapter zeroes in on the pivotal aspect of reducing hardware costs in Apache Kafka clusters. By carefully examining the choices between deploying Kafka on the cloud and on-premises, you'll delve into strategies that can lead to significant cost reduction.
RAM Allocation in Kafka Clusters: Performance, Stability, and Optimization Strategies

This chapter explores the significance of RAM for the performance and stability of Kafka clusters, as well as its impact on consumers and producers. While a Kafka cluster relies on various hardware resources such as CPU, disks, and NIC, RAM holds a distinct position due to its influence on cluster stability and performance.
A Deep Dive Into Producer Monitoring

This chapter delves into the art of monitoring producers in your Kafka cluster. Producers play a pivotal role in the Kafka ecosystem, where their efficiency directly influences throughput, latency, and overall resource consumption. A well-tuned producer not only ensures rapid message generation but also sends message in a manner that harmoniously coexists with brokers, avoiding unnecessary disruptions or delays.
Scientific Article Writing Mentoring for the English Subject Teacher Association in Palangka Raya

This community service aimed to address the professional development needs of teachers to enhance their career prospects. Teachers must compile portfolios to accumulate credit points for career advancement, thus necessitating their proficiency as teacher-writers. Hence, this sustainable community service sought to assist English as a Foreign Language (EFL) teachers in secondary high schools throughout Palangka Raya in comprehending the fundamentals of scientific writing, producing scientific articles, conducting research, and drafting research reports. The Participatory Action Research (PAR) methodology, which focuses on community empowerment, was employed for this endeavor. The activities were carried out over 12 workshop sessions involving 30 EFL teachers from the English Subject Teachers Association (MGMP) for junior and senior high schools in Palangka Raya. Before and after the workshops, KWL worksheets and WhatsApp Group discussions were utilized to facilitate the teachers' learning process. The results demonstrated that: (1) mentoring activities were executed effectively, with 80% of the planned materials successfully delivered to the participants; (2) participants expressed a positive perception of the activities, including satisfaction, relevance to their needs, comprehension, and overall significance.
Modelling Taylor's Table Method for Numerical Differentiation in Python

In this article, an attempt has been made to explain and model the Taylor table method in Python. A step-by-step algorithm has been developed, and the methodology has been presented for programming. The developed TT_method() function has been tested with the help of four problems, and accurate results have been obtained. The developed function can handle any number of stencils and is capable of producing the results instantaneously. This will eliminate the task of hand calculations and the use can directly focus on the problem solving rather than working hours to descretize the problem.
A Decision-Making Technique for Software Architecture Design

The process of making decisions on software architecture is the greatest significance for the achievement of a software system's success. Software architecture establishes the framework of the system, specifies its characteristics, and has significant and major effects across the whole life cycle of the system. The complicated characteristics of the software development context and the significance of the problem have caused the research community to build various methodologies focused on supporting software architects to improve their decision-making abilities. With these efforts, the implementation of such systematic methodologies looks to be somewhat constrained in practical application. Moreover, the decision-makers must overcome unexpected difficulties due to the varying software development processes that propose distinct approaches for architecture design. The understanding of these design approaches helps to develop the architectural design framework. In the area of software architecture, a significant change has occurred wherein the focus has shifted from primarily identifying the result of the architecting process, which was primarily expressed through the representation of components and connectors, to the documentation of architectural design decisions and the underlying reasoning behind them. This shift finally concludes in the creation of an architectural design framework. So, a correct decision- making approach is needed to design the software architecture. The present study analyzes the design decisions and proposes a new design decision model for the software architecture. This study introduces a new approach to the decision-making model, wherein software architecture design is viewed based on specific decisions.
Semi-supervised Learning Based on Graph Stochastic Co-Training

This article is devoted to the development of a new approach in semi-supervised machine learning. The goal of this article is to analyze the accuracy of the single-view co-training system, based on the use of a modified graph-based stochastic label propagation algorithm for a multiclass classification problem. Graph transformation of data is preceded by feature decomposition, with three algorithms being compared: Singular Value Decomposition, Truncated Singular Value Decomposition, Iterative Primary Component Analysis, Kernel Primary Component Analysis. To improve the accuracy of the proposed method, additional parameter was included in the label propagation algorithm, allowing for the usage of the algorithm in co-training systems. Further performance increases are achieved via optimization of data modification, which is achieved by applying feature decomposition methods and parallelizing the calculation-heavy processes. As examples of practical use were considered solutions to the problem of multiclass classification for standard datasets of the library sklearn and for the real dataset Traffic Signs Preprocessed. Analyses of the results of the implementation of the proposed approach showed improvements in accuracy and of performance solving the multiclass classification problem.
Lingkungan Positif dalam Mendukung Pembelajaran

A positive environment can greatly support individual learning and growth. Whether it is in the context of formal education, professional training, or lifelong learning, a supportive environment plays a very important role. Here are some elements that make up a positive environment to support learning: Teacher or Mentor Involvement; Available Resources; Comfortable Classroom; Diversity and Inclusion; Motivation and Social Support: Supportive peers, family support, and motivation from the social environment can greatly influence an individual's motivation to learn and achieve their academic or professional goals; Opportunities to Participate; Constructive Feedback; Clear Goals; Freedom and Autonomy; Fair Evaluation and Opportunities for Independent Reading and Learning.
Pengembangan Media Pembelajaran Berbasis Flip HTML 5 pada Mata Pelajaran Teknik Pemesinan Bubut di SMK Negeri 1 Padang

Flip HTML 5-based e-modules are a form of presenting material using smartphone and internet technology that can be used as an independent learning resource with a practical and easy-to-operate display. This study aims to analyze the development of learning media based on flip html 5 in lathe machining technique subjects at SMK Negeri 1 Padang. This type of research is development research or also known as R&amp;D (Research and Development). This research uses the ADDIE development procedure. The data collection technique used a questionnaire to obtain information about the quality of the E-Module product developed in the form of a validation sheet. The instrument used by researchers in this development research is a validation guideline. From the results of the validation and practicality questionnaire, it can be concluded that the product based on Project Based Learning in the subject of Lathe Machining class XI Vocational High School is very feasible to use.
Stability Issues in On-Premises Kafka Data Centers

Kafka clusters can be separated into two deployment categories—cloud-based and on-premises. This chapter discusses the potential stability issues that may arise from hardware failures in Kafka clusters that are deployed on-premises. Such clusters are heavily dependent on their hardware components and might experience stability issues due to failures in these components. This can impact the cluster stability.
Two Proposed Models for Securing Data Management for Enterprise Resource Planning Systems Using Blockchain Technology

An Enterprise Resource Planning (ERP) system is a software application that serves as a centralized platform to streamline and automate organizational functions and share real-time data, facilitating efficient communication and collaboration. It provides an all-inclusive approach to managing and optimizing business processes, boosting efficiency, fostering cooperation, and giving an overall picture of how the organization is operating. However, the traditional centralized databases in ERP systems pose security concerns. Blockchain Technology can be an appealing alternative as it comes with immutable and decentralized data as well as enhanced security. This study focuses on two methods of securing data management in ERP systems: Organizing the distributed information using The Ralph Kimball data model and optimizing an individual block using Database Sharding. This study does an extensive examination to determine the effectiveness of both suggested strategies, comprising a detailed evaluation that highlights the benefits and limitations of both techniques. This paper intends to patch the security holes in ERP systems to safeguard sensitive data and mitigate risks.
Correction and Analysis of Turbulence Effects in Time-Lapse Images Using Optical Flow Registration

Optical flow processing is applied to time-lapse image sequences collected in the field for atmospheric refraction research. The pixel displacement estimates are used for turbulence mitigation and the investigation of spatial and temporal turbulence effects.
Konsep Inteligensi dan Peranan dalam Proses Pembelajaran di Sekolah

The aim of this research is to describe the participants' main ideas about intelligence and explain what roles influence the learning process for students. In this research, researchers used qualitative methods that are literary in nature. The results of this research state that intelligence is very influential in the students' learning process because it can be seen that students who have high intelligence can more easily participate in learning activities quickly and well compared to students who have low intelligence. Suggestions from this research enrich the study of intelligence and its role in the learning process.
Mitigation of Byzantine attack using LSP algorithm in CR Networks through Blockchain Technology

In the past couple of years, the research on the Byzantine attack and its defense strategies has gained the worldwide increasing attention. In this paper, we present a secure protocol to escape from the Byzantine attack in the cognitive radio networks. This protocol is implemented using the Lamport-Shostak-Pease algorithm and blockchain technology. A reliable distributed computing system must be able to handle the faulty components to deliver the error less performance. These faulty components send the conflicting information to the other parts of the system. As a result, it creates a problem which is similar to the Byzantine Generals Problem (BGP). In order to design a reliable system, it is necessary to identify and overlook such faulty components. In the cognitive radio networks, there are the two types of users i.e. primary and secondary users. The primary users hold the licensed spectrum whereas the secondary users hold the leased spectrum. In these CR networks, there can be a similar problem like BGP while allocating the spectrum to the secondary users. Also, it requires all the users to agree on a common value, even with some faulty users in the network. This is called as the Byzantine Agreement. Here we have addressed this Byzantine General problem to develop a reliable and secure spectrum allocation using the Lamport-Shostak-Pease algorithm. It can solve the BGP for n≥3m+1 users in the presence of ‘m’ faulters. In this implementation, the blockchain technology is used as the efficient decentralized database which records all the transactions of the users, like exchanging currency, mining, updating the blockchain and auctioning the spectrum for lease.
A Sphere Packing Approach to Design Multiplexed Multispectral Filter Arrays

We propose a method to design a multiplexed Multispectral Filter Array (MSFA) based on Optimal Sphere Packing (OSP) in a 4D-Euclidean space that promotes uniformity and improved signal-to-noise ratio in the measurement process of the 3D-datacube while delivering enhanced reconstructions.
Quadrature Transform Based Surface Profiling of Speaker’s Diaphragm Using Fringe Projection Profilometry

Quadrature transform-based fringe projection profilometry is proposed for surface profiling of the speaker’s diaphragm. Experimental and simulated results show that quadrature transform outperforms Fourier transform and four-step phase-shifting techniques for dynamic object analysis.
Analysing political opinions using machine learning

In the era of digital world, text is not confined to textbooks or newspapers anymore. People use platforms like Twitter, Facebook, Quora, and other social media platforms to express their opinions over certain products, movies, social, economic or political causes. Huge chunks of textual data are available on these platforms for analysis. This paper tries to leverage deep learning and natural language processing (NLP) to use the publicly available text data to predict outcomes of Indian general elections by analysing the tweets with hashtags for various parties, using opinion mining to define polarity in the opinions. It tries to adopt a hybrid approach using NLP. The results from the analysis help in highlighting the potential of machine learning in predicting the election results and identifying the political inclination of people towards specific policies thus, indicating the efficiency of using social media to predict real-world outcomes.
Extreme learning machine for solving paddy nutrient deficiencies in Davangere region

Soil nutrient is an important aspect that contributes to the soil fertility and environmental effects. Traditional evaluation approaches of soil nutrient are quite hard to operate and they are very slow, making great difficulties in practical applications. The proposed study, presents extreme learning machine (ELM) for analysing the soil fertility index values of boron, zinc, organic carbon and pH in Davangere District. Boron, zinc, organic carbon, and pH concentrations in soil play significant roles in paddy crop cultivation and growth. Proposed ELM-based approach helps in the prediction of boron, zinc, organic carbon and pH index values in soil by evaluating four linear and nonlinear activations functions. Performance of ELM model is analysed by increasing the number of hidden neurons in the hidden layer.