Reviewerly/exHarmony huggingface dataset:
The Impact of Social Media on Linguistic Practices and Cultural Norms

This study aimed to analyze the impact of social media on linguistic practices and cultural norms. The objectives were to examine the linguistic features found on social media, influence on language evolution, impacts on language ideologies and community norms, effects on sociocultural practices, and role in empowering marginalized voices. A quantitative survey was conducted with 69 regular WhatsApp users using a 14-item Likert scale questionnaire distributed online. Descriptive statistics analyzed the response patterns. Previous research highlighted linguistic conventions emerging on social media platforms, such as hashtags. Studies also explored how words and memes diffuse across platforms and how communication styles can vary. Research further examined the impacts on linguistic diversity and convergence with the consensus that shared practices cultivate tight-knit online groups. The findings corroborated social media's diverse sociolinguistic influences and added a new perspective while illuminating broad consensus. Recommendations included integrating emerging online forms into education, considering language changes facilitated by platforms and reviewing policies that impede diversity. It also suggested training on digital sociolinguistics to guide navigating online language issues and recognizing social media's role in contemporary youth language use. Overall, the study advanced the understanding of social media's complex relationship with language use, attitudes and sociocultural dynamics. The insights shed light on technology's transformative impacts and implications for communication, language evolution, policies, education, and linguistic diversity.
Closing the Feedback Loop with Mastery Tasks

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 Geoffrey Lee-Dadswell, Fraser Cunningham Turner; Closing the Feedback Loop with Mastery Tasks. Phys. Teach. 1 September 2023; 61 (6): 528–531. https://doi.org/10.1119/5.0069535 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
Beyond the Content: Considering the Network for Online Video Recommendation

Online recommendation systems play critical roles in enhancing user experience by helping them find the most interesting videos from a vast amount of content. However, the existing recommendation modules and video transmission modules in the industry often operate independently, resulting in the recommendation model providing some videos that cannot be transmitted within the specified deadlines successfully. This can lead to an inferior watching experience for users and resource waste for video providers. To address this, we propose a novel framework called NetRec, which for the first time optimizes the recommendation quality by jointly considering the network transmission. We accomplish this by re-ranking the top-N videos obtained from the recommendation system and selecting the top-M (M is approximately half of N) videos that provide the maximum overall revenue, e.g., video playing time while considering the network status. The entire system comprises network measurement, video quality estimation, and multi-objective optimization modules. Real-world Internet results show that our framework can increase users’ video playing time by 20% to 160%. Furthermore, we provide several promising directions for further improving the video recommendation quality under our NetRec framework, which jointly considers the network for the recommendation.
The Construction of Computer Mathematical Model Based on Artificial Neural Network

Mathematical modeling is a way of using mathematical knowledge to solve practical problems in social activities. According to the mathematical processing function, storage function, drawing function and search function of the computer itself, the organic combination of it and mathematical modeling can promote the effective solution of social activity problems and promote the continuous development of economy and society. Based on this, this paper explores the relationship between computer technology and mathematical modeling, and analyzes the specific application of computer technology in mathematical modeling. Human brain information processing has nonlinear characteristics, and artificial neural network is a nonlinear network model similar to brain intelligence. Artificial neural network model is a nonlinear network model that simulates the neural system of human brain. Therefore, firstly, the artificial neural network is summarized; Then the BP network model is described, and the BP network based on elastic BP algorithm is designed and implemented; Finally, the training and testing of the network are simply analyzed.
A Renewed Sense of Dynamism

This year's Embedded World brought together developers, system architects, product managers and technologists. NEIL TYLER looks back at some of the key announcements
Research on Optimization Methods for Industrial Model Retrieval

In the retrieval process of industrial models, the traditional database retrieval can no longer meet their needs in terms of efficiency and precision because of their multi-source heterogeneous, complex types and large information scale. This paper optimizes the Elasticsearch search engine in three aspects: the underlying index of the search engine, keyword search and sorting algorithm; and verifies the feasibility of the method through experiments.
Criminal responsibility for spreading electronic rumours- A descriptive and analytical study in Jordanian law and judiciary

The study discusses the issue of rumors from the perspective of criminal responsibility due to the importance of controlling technical practices through the information network, and despite the importance of this issue and its seriousness to society, the legal organization of it still suffers from problems, such as the absence of explicit texts that directly condemn these practices, the legislative overlap between the texts of criminalization, which called on the researcher to regulate the penal responsibility for spreading rumors Starting with its definition, and mentioning its characteristics and clarifying its penal provisions, and in conclusion the researcher summarized that there is a legislative confusion in the penal texts governing this issue in addition to the lack of provisions of the Jordanian Cybercrime Act condemning such practices explicitly, it is necessary to amend the law of cybercrime and include it explicitly and directly in the crime of rumors and stay away from expansion in comparison on the basis of the content of the widespread news.
Virtual success

Purpose This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies. Design/methodology/approach This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context. Findings Metaverse and virtual reality technologies are opening new doors to innovation and development for firms looking to boost revenues and gain competitive advantage. Originality/value The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.
Solutions of the Schrödinger Equation in Three Dimensions

Many physics textbooks take a traditional approach to the demonstration of mathematical relationships and derivations, presenting them in linear order. However, many physical derivations follow a tree-shaped structure with interconnected steps running in parallel, where numerous individual equations are manipulated and combined to reach a final result. Thus, conventional presentation often leads to derivations being spread over several book pages and linked by formula numbering. This title takes a novel and intuitive approach to introductory quantum mechanics by utilising concept maps to address non-linear structures in key mathematical relationships. Concept maps are structures in a form similar to flowcharts where derivations, concepts, and relations are visualised on one page, supported by concise accompanying text on the opposite page. Perfect as a supporting and guiding tool for undergraduates, this book is designed to aid in the understanding and memorisation of key derivations and mathematical concepts in quantum mechanics.
Engaging with Researchers and Raising Awareness of FAIR and Open Science through the FAIR+ Implementation Survey Tool (FAIRIST)

Seven years after the seminal paper on FAIR was published, that introduced the concept of making research outputs Findable, Accessible, Interoperable, and Reusable, researchers still struggle to understand how to implement the principles. For many researchers, FAIR promises long-term benefits for near-term effort, requires skills not yet acquired, and is one more thing in a long list of unfunded mandates and onerous requirements for scientists. Even for those required to, or who are convinced that they must make time for FAIR research practices, their preference is for just-in-time advice properly sized to the scientific artifacts and process. Because of the generality of most FAIR implementation guidance, it is difficult for a researcher to adjust to the advice according to their situation. Technological advances, especially in the area of artificial intelligence (AI) and machine learning (ML), complicate FAIR adoption, as researchers and data stewards ponder how to make software, workflows, and models FAIR and reproducible. The FAIR+ Implementation Survey Tool (FAIRIST) mitigates the problem by integrating research requirements with research proposals in a systematic way. FAIRIST factors in new scholarly outputs, such as nanopublications and notebooks, and the various research artifacts related to AI research (data, models, workflows, and benchmarks). Researchers step through a self-serve survey process and receive a table ready for use in their data management plan (DMP) and/or work plan. while gaining awareness of the FAIR Principles and Open Science concepts. FAIRIST is a model that uses part of the proposal process as a way to do outreach, raise awareness of FAIR dimensions and considerations, while providing timely assistance for competitive proposals.
Parking curve optimization for oblique slots in multi-obstacle environment

For parking path generation, Reeds-Shepp curve is commonly adopted in algorithms such as Hybrid A*. However, path planning for underground parking with pillars and lanes occupancy cases is difficult due to the narrow space constraints. In narrow environment, RS curve might cause frequent turning and generate large radian arc that are not suitable for parking. In addition, the last segment of RS curve is an arc that occupies large area when parking into slots and is easy to collide with obstacles like pillars. Therefore, we proposed AP-RS curve to promote performance of path searching and obstacle avoidance by taking driver’s parking habits into consideration. For oblique parking lots, CCS curve is designed to ensure the last segment of curve parallel to the slot, which have less occupancy and straighten the car up in movement to reduce tire wear. The proposed method is tested under different oblique slot with 30, 60, 90, 120, 150 degrees and its performance is compared with RS curve and KKL-RS curve. The results show that AP-RS curve for oblique slot have fewer search iterations, higher adaptability to different kinds of slots, higher success rate of path planning in multipleobstacles environment.
Development and preliminary validation of an open access, open data and open outreach indicator

We present the development and preliminary validation of a new person-centered indicator that we propose is named “OADO” after its target concepts: Open Access (OA), Open Data (OD) and Open Outreach (OO). The indicator is comprised of two factors: the research factor indicating the degree of OA articles and OD in research; and the communication factor indicating the degree of OO in communication activities in which a researcher has participated. We stipulate that the weighted version of this new indicator, the Weighted-OADO, can be used to assess the openness of researchers in relation to their peers from their own discipline, department, or even group/center. The OADO is developed and customized to the needs of Elsevier's Research Information Management System (RIMS) environment, Pure. This offers the advantage of more accurate interpretations and recommendations for action, as well as the possibility to be implemented (and further validated) by multiple institutions, allowing disciplinary comparisons of the open practices across multiple institutes. Therefore, the OADO provides recommendations for action, and enables institutes to make informed decisions based on the indicator's outcome. To test the validity of the OADO, we retrieved the Pure publication records from two departments for each of the five faculties of the University of Southern Denmark and calculated the OADO of 995 researchers in total. We checked for definition validity, actionability, transferability, possibility of unexpected discontinuities of the indicator, factor independence, normality of the indicator's distributions across the departments, and indicator reliability. Our findings reveal that the OADO is a reliable indicator for departments with normally distributed values with regards to their Weighted-OADO. Unfortunately, only two departments displayed normal distributions, one from the health sciences and one from engineering. For departments where the normality assumption is not satisfied, the OADO can still be useful as it can indicate the need for making a greater effort toward openness, and/or act as an incentive for detailed registration of research outputs and datasets.
The concept of a “free school” by K.V. Ventzel and V.N. Chekhov: on the use of pre-revolutionary and Soviet experience in modern Russian realities

Based on the analysis of the creative heritage of outstanding representatives of prerevolutionary and Soviet pedagogy, the article reveals the principles of building a “free school” based on taking into account the interests of each student and creating individual conditions for achieving the highest results. The concept of free education of the individual was adopted after the October Revolution, practically used in the practice of creating a “new school” in the first third of the 20th century, proving its effectiveness in the education and formation of the Soviet man. It is established that the theoretical postulates of a new type of pedagogy by V.N. Chekhov and K.N. Ventzel were the forerunner of the Western theory of a personality-oriented approach to education, the so-called transformative model of pedagogy, which became widespread in the late 20th - early 21st centuries. The authors substantiate the necessity and possibility of using the experience of prerevolutionary and Soviet pedagogy in modern realities.
Diagnostics of Evaluative Competencies of Teachers at the Level of a General Education Organization

The article presents the results of diagnostics of evaluative competencies of teachers organized in the gymnasium No. 55 of Tomsk on the basis of the author’s methodology. The purpose of the article is to present the experience of designing and applying a diagnostic technique that allows to identify deficiencies in the evaluative competencies of teachers at the institutional level of quality management of general education. Empirical data on the deficits of evaluative competencies of teachers are presented and commented on. The organizational model of diagnostics is characterized, the structure of processing of diagnostic results is proposed. It is shown that even at the level of a general education organization, without resorting to regional structures for the diagnosis of professional competencies, it is possible to identify such deficiencies in evaluation activities as the integration of diagnostics of metasubject results into the current thematic control, assessment of functional literacy of students, the use of a criterion approach and the objectivity of marking. The institutional level of diagnostics of evaluative competencies is the most informative and convenient from the position of subsequent construction of individual educational routes of the teacher to fill the identified deficits. The results of the study are applicable in the mass practice of ensuring the functioning of internal systems for assessing the quality of education.
Cad Systems for Automatic Detection and Classification of Covid19 Using Image Processing and Machine Learning

Counting of platelets in blood cells assumes to be a significant role in the health sector. In any case, the procedure of the manual tallying of platelets in blood cells is incredibly tedious, which prompts erroneous outcomes. So as to overcome these difficulties, this research presents a fully auto
Peningkatan Prestasi Belajar Matematika melalui Penerapan Model Pembelajaran Kooperatif Tipe STAD (Student Teams Achievement Divisions) pada Siswa Kelas VII.C SMPN 3 Masbagik Semester II

This Classroom Action Research was conducted by applying the STAD type cooperative learning model (Student Teams Achievement Divisions) in order to improve the quality of the learning process and is a concept of learning activities that assist teachers in carrying out Mathematics learning activities taught by trying to maximize the active role of students, especially their knowledge. and how to apply it in everyday life. With this concept, learning outcomes are expected to be more meaningful for students. The learning process takes place naturally in the form of student activities working and experiencing, not transferring knowledge from teacher to student. The quality of learning is more important than the results. This Classroom Action Research (CAR) was conducted with the aim of knowing the improvement of mathematics learning achievement through the application of the STAD Type Cooperative learning model (Student Teams Achievement Divisions) in class VII-C students of SMPN 3 Masbagik in the 2020/2021 school year. This Classroom Action Research (CAR) was carried out in stages 2 cycles, and from the results of the actions that have been carried out it has been proven to improve student learning achievement both in terms of classical student learning completeness, namely in the first cycle of 72%, it can increase to 92% in the second cycle. it means that there is an increase of 20% and in terms of the average value of the evaluation results, namely in the first cycle of 72 to 87 in the second cycle, this means that there is an increase of 15. In terms of student activity in this classroom action research also shows an increase in the level of learning activity students from the Moderately Active category in cycle I became the Active category, meaning there was an increase as well.
Pruned-F1DCN: A lightweight network model for traffic classification

With the continuous development of deep learning, deep neural networks are gradually applied to traffic classification problems. However, the large network structure and parameter number of deep neural networks hinder the application on edge computing devices. Reducing network scale helps relieve computational pressure, this paper proposes a lightweight traffic classification model to provide reliable accuracy and reduce the consumption of computing resources. In this work, we design an F1DCN network, which takes full advantage of the convolution layer parameters and the convolution kernel field of view. The lightweight approach effectively improves the classification performance and saves massive parameters. The model pruning method is applied to find the optimal structure of the network. Experiments on two public datasets show that the proposed model reduce more than 80 % parameters and 45 % FLOPS compared with traditional traffic classification methods, and maintaining more than 95 % classification accuracy.
The Construction and Influence of Celebrity Personas

In modern society, the rapid development of technology and media is gradually making the act of "star-making" more efficient and convenient, while the prevalence of consumerism, the strong involvement of capital and the changing concept of social groups also make such a significant part of "star-making" which means the construction of the "Public Persona" has become an important part of today's media in an era that cannot be ignored. Therefore, this paper analyzes the construction and influence of the celebrity's "persona" through the preexisting example and theories. Previous research shows that the "persona" of celebrities is inseparable from the injection of capital and the promotion of fan groups, and it is also connected with the characteristics of individual celebrities. Due to the complexity of its construction, the "persona" of celebrities will have an impact on themselves, their fan base, and the larger society; these impacts are often long-term and heterogeneous.
FIRST LANGUAGE ACQUISITION FOR CHILDREN AGED 3-4 YEARS IN SEBERANG ULU 1 KERTAPATI PALEMBANG

This study aims to describe the acquisition of first language in children aged 3-4 years at Seberang Ulu 1 Kertapati Palembang with a total of 4 children who have different ages in the phonology and morphology study level. The research method used is descriptive qualitative method. Data collection techniques used in this study were observation techniques, recording techniques, listening techniques, interview techniques and note taking techniques. The data analysis technique used is descriptive analysis technique. Therefore, the difficulty that often arises in analyzing novels is having to read &#x0D; Keywords : First language acquisition, phonology, morphology, Palembang, and language acquisition studies
METODE REGRESI GULUD UNTUK MENGATASI MASALAH MULTIKOLINEARITAS PADA KASUS INDEKS KUALITAS LINGKUNGAN HIDUP DI INDONESIA TAHUN 2021

The environmental quality index is an indicator of environmental quality in Indonesia. EQI shows an increasing trend from 2018 to 2022, although Indonesia's environmental quality is ranked 116 out of 180 countries in the world. Therefore, the purpose of this study is to describe the characteristics of the EQI and the factors that can affect EQI, estimate the parameters of the ridge regression model and test the significance of the ridge regression model parameters to overcome the multicollinearity problem in the EQI case. This study uses 4 independent variables, namely population density, traffic, waste, and sanitation in Indonesia in 2021 as secondary data. In this study, ridge regression analysis is used because there is an almost linear relationship between the factors that are thought to affect the EQI. Ridge Regression is a technique that imposes limits (penalties) on parameter estimates in the regression model so that a reduction in the estimated coefficient value can overcome the multicollinearity problem. The results show that the optimal lambda value is 4.737078 when using the 5-fold cross-validation method. Variables that partially affect EQI are population density, waste, and environmental sanitation. The independent variables in this study that can explain the variability of EQI in Indonesia in 2021 is 59.52%, while 40.48% is explained by other variables that are not included in the model. Indonesia's EQI score in 2021 is 71.45 with the predicate "Good". Keywords: Environmental Quality Index, Ridge Regression, Cross Validation.