Reviewerly/exHarmony huggingface dataset:
Implementasi Clustering K-Medoids dalam Pengelompokan Kabupaten di Provinsi Aceh Berdasarkan Faktor yang Mempengaruhi Kemiskinan

&lt;p&gt;&lt;em&gt;The economy is one of the parameters to see how the development of a country. Ending poverty anywhere and in any form is goal 01 of the Sustainable Development Goals (SDGs) program. Until now, poverty has become one of the main problems in Indonesia, so poverty must be a concern of the government. Based on data from the Central Statistics Agency (BPS) shows that as of September 2020 the percentage of poor people in Aceh Province is still the highest on the island of Sumatra, which is 15.43%. The purpose of this study is to classify districts based on factors that affect poverty in Aceh Province. The method used in this study is the K-Medoids Cluster Analysis algorithm. The optimal number of clusters is 2 clusters with cluster 1 consisting of 11 districts and cluster 2 consisting of 12 districts. Cluster 1 has a higher percentage of poor population and poverty depth index than cluster 2, while cluster 2 has higher Gini Ratio, AHH, and RLS values than cluster 1.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;&lt;/em&gt;&lt;strong&gt;&lt;em&gt;Keywords : &lt;/em&gt;&lt;/strong&gt;&lt;em&gt;Clusters, Economy, Poverty, SDGs&lt;/em&gt;&lt;/p&gt;
Pengelompokan Kabupaten/Kota di Provinsi Jawa Barat Berdasarkan Dampak Kerusakan Bencana Banjir Menggunakan K-Medoids

&lt;p&gt;&lt;em&gt;The territory of Indonesia is located in geographical, geological, hydrological, and demographic conditions that allow Indonesia to be prone to disasters. The most common natural disaster in Indonesia is flooding. If accumulated, there have been 682 flood events in the country since the beginning of 2022. In Indonesia, especially West Java Province, flooding is the most common disaster, especially during the rainy season. So a study will be conducted that aims to determine the grouping of districts / cities in West Java Province based on the occurrence of flood disasters. The data used in this study were obtained from the publication of the National Disaster Management Agency. In this study, there are 4 variables of the impact of flood disasters, namely total deaths, total submerged houses, total damaged houses and total injured. The clustering method used in this research is K-Medoids. K-Medoids is one of the clustering methods that uses the partition clustering method in grouping a set of n objects into a number of k clusters. From the results of the K-Medoids analysis, three clusters were obtained. The first cluster consists of 3 districts/cities with high impact of flood disasters, the second cluster consists of 23 districts/cities with moderate impact of flood disasters, and the third cluster consists of 1 district/city with low impact of flood disasters. Based on the results of the analysis, efforts can be made by the government to focus more on designing steps that must be taken in preventing or overcoming the impact of flood disasters.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Keywords: &lt;/em&gt;&lt;/strong&gt;&lt;em&gt;Cluster; K-Medoids; Floods West Java&lt;/em&gt;&lt;/p&gt;
Entity and Entity Type Composition Representation Learning for Knowledge Graph Completion

This paper proposes a simple knowledge graph embedding (KGE) framework that considers the entity type information without additional resources. The KGE is used to obtain vector representations of entities and relations by learning structured information in triples. The obtained vectors are used to predict the missing links in a knowledge graph (KG). Although many KGs contain entity type information, most of the existing methods ignored the potential of the entity type information for the link prediction task. The proposed framework, which is called entity and entity type composition representation learning (EETCRL), obtains vector representations of both entities and entity types, which are combined and used for link prediction. Experimental results on three datasets show that the EETCRL outperforms the baseline methods in most cases. Furthermore, the results obtained from tests with different model sizes show that the proposed framework can achieve high performance even with a small model size. This paper also discusses the effect of considering information about entity types on the link prediction task by analyzing the experimental results.
Collaborative Filtering with <i>q</i>-Divergence-Based Relational Fuzzy <i>c</i>-Means Clustering

This paper presents a collaborative filtering (CF) algorithm for a recommendation system motivated by the need for higher recommendation accuracy. Cluster analysis captures information from a group of users such that users within a given cluster are more similar to each other than to those in other clusters. Therefore, clustering helps to detect similar users. However, inconsistent similarity measures have been applied during the clustering and prediction stages in the literature. Hence, this study resolves such discrepancies through the proposed CF algorithm, which uses fuzzy clustering for relational data such that a common similarity measure is applied to both the clustering and prediction stages. Experiments were conducted with ten datasets based on an artificial dataset and 40 datasets based on eight real datasets to demonstrate that the proposed algorithm could achieve a higher CF accuracy than conventional methods.
Digital Transformation of Higher Education: Logic, Mechanism and Path

With the rapid development and wide application of new generation digital technologies such as big data, machine learning and artificial intelligence, digital transformation of higher education has become a global issue. On the basis of clarifying the inner value logic, target logic and practice logic of digital transformation of higher education, we find out the mechanism of its role in practice through research, and propose targeted implementation paths to promote its high-quality development.
A Zero-Cost Darts Base on Multi-Step Optimization

DARTS has achieved great result in Image classification field, the accuracy predictor and computation costs are the key of DNAS algorithm. Searching for a high-performance architecture always costs Large amount of computation. With a gradient-based bi-level optimization, DARTS using one-step optimization which makes the process available within a few GPU day, because of the one-step optimization , there exists a great gap between the architectures in search and evaluation. In this paper, we propose a zero-cost DARTS method which using multi-step optimization to address the above issues. To further reduce the computational requirements, we use the zen-score to estimate architectures in evaluation stage. Experiments on CIFAR-10 and our private data sets show that our algorithm play a certain role in solving the above problems.
Meningkatkan Kemampuan Berbicara Siswa Kelas XI PM 1 dengan Strategi Pembelajaran Berdiferensiasi

It is common knowledge that graduates of vocational schools (SMK) are oriented toward the working world. Undoubtedly, English is highly essential to support the competence of these graduates. However, regrettably, English remains a daunting challenge, especially when it comes to speaking skills. Therefore, differentiated learning is of great importance to be implemented. Differentiated learning is a teaching strategy oriented toward the learning needs of students. In this research, the researcher employed differentiated learning, focusing on differentiating content, processes, and environments, with reference to addressing various learning styles. The aim of this research was to enhance the speaking skills of the 11th-grade PM 1 class using differentiated learning. The study utilized the Class Action Research (CAR) method, consisting of two cycles. Each cycle encompassed four stages: planning, acting, observing, and reflecting. Collaborative action research was conducted, involving the collaboration of the researcher and an English teacher serving as a mentor. Data collection involved tests, observations, and presentation assessments. The data analysis employed quantitative descriptive analysis, which presented the results in a descriptive form for quantitative data. Based on the research conducted, it was found that students' speaking skills were very low. In the pretest stage, their average score was 60. In the first cycle, there was an improvement to 70, and in the second cycle, there was a further increase to 85. From these results, it can be concluded that the use of differentiated learning is highly effective in improving the speaking skills of SMK Negeri 1 Banyuwangi 11th-grade PM 1 students.
Volleyball Action Recognition based on Skeleton Data

This research explores the intricacies of volleyball action recognition using skeleton data through the lens of the Long Short-Term Memory (LSTM) model. With the objective of accurately identifying distinct volleyball actions—Serve, Spike, Block, Dig, and Set—the study implemented a structured LSTM network, achieving a commendable 95% accuracy rate consistently across all actions. The findings underscore the transformative potential of deep learning, particularly the LSTM network, in sports analytics, suggesting a paradigm shift in understanding and analyzing sports actions. The research serves as a foundation for future studies, offering insights into the blend of artificial intelligence in sports, with applications extending to coaching support and enhanced sports broadcasts.
FPGA Hardware Acceleration Research and Implementation of Deep Learning Algorithms

The convolutional neural network model is an important algorithm for deep learning, and YOLOv3-tiny based on this model has excellent object detection ability. However, the computational power required by the model is still large, and it is difficult to realize the application in the embedded field. This paper proposes a hardware acceleration method for YOLOv3-tiny and implements it on FPGA platform. Firstly, the fixed-point quantitative processing was carried out for the network, and an appropriate fixed-point strategy was designed with the data accuracy as the index. Secondly, the parallel computing design and pipeline optimization principle were carried out, and the FIFO structure was introduced to shorten the running time. Finally, the experiment was carried out on the Xilinx PYNQ-Z2 platform, and the data were compared with the previous related work.
Expert System for Diagnosing Diseases in Children Aged One to Six Years Using the Forward Chaining Method

Expert systems are stems that try to integrate human knowledge into computer systems so that computers can solve problems as usually done by professional. This expert system aims to provide early information or symptoms to parents about children's diseases so that parents can find out the diseases experienced by children. This system works by entering all symptom data into the system to be traced so as to get a diagnosis of the detected results. This system was developed with PHP and MySQL programming languages as database servers. The creation of an expert system uses the Waterfall development methodology and the reasoning method used is the forward chaining method. The author hopes that this expert system can ease parents to find early solutions to treat diseases in children.
An Analysis of Achievement Standards for Integrated Social Studies Curriculum

This study was conducted to evaluate whether the integrated social curriculum achievement standards were integrated with the real-world phenomena faced by learners and knowledge, skills, values, and attitudes in their lives to function as the basis for composing textbooks or teaching and learning. The KDB(Know, Do, Be) framework was used to analyze the degree of integration. As a result of the analysis, the 2022 revised integrated social studies curriculum achievement standards sufficiently dealt with knowledge and function elements, but the value and attitude elements were insufficient. Elements K, D, and B are presented together in the content system table, but only some of the B elements presented in the content system table were included in the achievement criteria. In 10% of cases where element B was directly organized on the achievement standard, but element B could be organized up to 90% based on the contents of the curriculum document. The reason for organizing element B in this way is that if the class, which is a situation in which the learner directly learns, is clearly equipped with elements K, D, and B, the integration of learning and life, the essence of the integrated social studies, can be effective. To this end, first of all, element B is presented in a balanced way with elements K and D in the achievement standard, so knowledge, skills, values, and attitudes need to appear in life. Second, in subjects that aim for integration throughout the curriculum, such as the substances, goals, and content system of the subject, such as an integrated social studies, the achievement standards should be described so that knowledge, skills, values, and attitudes, which are the content of the subject, are clearly revealed. Finally, it is necessary to use element D in a variety of ways so that element D can include or aim for element B in the achievement standard.
Interactional Coherence in Twitter Messages on the Anglophone Crisis in Cameroon

This paper examines the coherent indicators in 269 Twitter messages on the Anglophone crisis in Cameroon. The data was collected through screenshots from Anglophone Cameroonians from 2016 to 2020. Insights were got from Oshima and Hogue (2006) who give four elements of coherence devices that writers can use in order to achieve coherence. These include the repetition of key nouns, the use of consistent pronouns, transition signals to link ideas and ordering of information in logical order. After quantitative and qualitative analyses, the findings indicated the repetition of key nouns, pronouns, transitional words and logical ordering of ideas. It was equaly discovered that the coherent devices help in the smooth flow of ideas, and context displays an important role in the realisation of coherence.
Study on Regulating Cyberbullying from the Perspective of Criminal Law

As the advance of the times and the popularization of the internet, a large number of netizens have entered cyberspace. Along with this, the phenomenon of cyber bullying has become rampant and a pressing social issue, but the criminal legislation of our country seems to lack sufficient measures to regulate such dangerous behavior. Currently, scholars have two main viewpoints regarding regulating cyber bullying. One revolves around existing legal frameworks or regulations and aims to address cyber bullying through an interpretive approach. Another argues that the existing criminal charges have numerous flaws and fail to adequately meet the regulatory demands, thus advocating for the creation of specific charges. Therefore, it is crucial to study the current situation and deficiencies in Chinas criminal regulation of cyber bullying and explore practical solutions to address these shortcomings.
Trend Analysis of Research Papers Related to Child Care Teacher Education

This study analyzed trends in 79 research papers related to child care teacher educationpublished in domestic academic journals from the 1990s until June 2023. The data were dividedinto general research trends and research methods and research results research trends and thenanalyzed by frequency and percentage, respectively. As a result of the study, research papersrelated to child care teacher education were studied the most in the 4th period (2010-2019), andthe research topic was the in-service child care teacher system and system (child care practice,retraining) that was relatively studied the most. Futhermore, the study found that surveyresearch and qualitative research methods were frequently employed, Prospective child careteachers were the primary subjects of these studies, with questionnaire-based data collection andqualitative analysis methods being prevalent. The results of this analysis highlight the focus onimproving the quality of child care teacher education through the current analysis andimprovement of the current child care teacher education.
Instructions for the Creative Activity of 'Making Class Bell' Using Traditional Korean Instrument Tones from the National Gugak Center's Gugak Digital Source

This study devises a method for instructing the creative activity of 'Making Class&#x0D; Bells' using the tone of Korean traditional instruments from the gugak (Korean&#x0D; traditional music) digital sound source provided by the National Gugak Center.&#x0D; First, as a result of reviewing the aspects of gugak creation content included in&#x0D; the 2015 revised middle school music textbook, there were no creative activities&#x0D; utilizing the tones of gugak instruments. Based on the reviewed contents, an&#x0D; instruction plan of the creative activity using the tone of gugak instruments&#x0D; consists of four steps: the step of exploring gugak instruments, the step of&#x0D; distinguishing the tones of gugak instruments, the step of utilizing the tones of&#x0D; gugak instruments, and the step of submitting what they created. Following these&#x0D; steps, the creative activity of 'Making Class Bell', made up of eight classes, was&#x0D; applied to the first-year middle school students in Seocho-gu, Seoul. The first&#x0D; result is that students were able to experience the tone of gugak instruments and&#x0D; further the harmony of sound. Second, they were able to practice gugak in their&#x0D; life. Third, this activity shows that the gugak creative education using digital&#x0D; media can become active. Fourth, they can enjoy various gugak instruments. Fifth,&#x0D; they can develop their creativity through the composition activity.
The Influence of Pre-Service Early Childhood Teachers’ ICT Efficacy and Digital Competency on Intention to use digital in Education

In the era of rapid digital technological advancements, there is an escalating demand fordigital education within early childhood education. Therefore, in order to improve pre-serviceearly childhood teachers' intention to use digital technology in education, we examined thestructural relationship between digital competency and technology self-efficacy, which arerelated variables. The study involved 247 pre-service early childhood teachers from A Universityin Gyeonggi-do and K University in Daejeon. Collected data were analyzed using structuralequations. The results of this study are as follows. First, digital competency had a significantand positive impact on technology self-efficacy and intention to use digital in education. Second, technology self-efficacy exhibited a significant and positive influence on intention to usedigital in education. Third, technology self-efficacy played a mediating role in the relationshipbetween digital competency and intention to use digital in education. These findings suggestthat technology self-efficacy and digital competency should be improved to increase pre-serviceearly childhood teachers' intention to use digital in education.
Analysis bibliometrics driving distraction

The driving process is a very complex activity like awareness, retrieval decision, and execution. Introduction Circumstances distracting the driver are significant for ensuring the driver's safety. Therefore, research This study trends article about distracted driving. Data from the Scopus database is collected, published between 2013 and December 2022, and processed using Vosviewer. The combination of words used to find an article related to distracted driving is "driving distraction" and "behavior." Studying this endeavor answers the formulation problem: " What just trend main, topics key, and the sources that contributed most in the research domain? How development study scientific related distraction driving, especially in context security Then cross section and the factors that influence it, are reflected in literature scientific?". The result of the study This is as follows: Disruption trends driving from year to year experience enhancement so that matter the show that study regarding “Driving Distraction” and “Behavior” are still exciting For researched more further, factors the resulting distraction in study various things, including factor internal and external distraction. Internal factors are existing factors _ from self-drivers and external factors like the use of the telephone, side billboards road, navigation while driving, and listening to music at the moment driving.
Nullius in Verba

Ad LibitumNovember 2023Nullius in VerbaDaniel BoschDaniel BoschAtlanta, GeorgiaSearch for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/M23-1733 Audio Reading - “Nullius in Verba” Supplement. Audio. Virginia L. Hood, MD, a physician from the University of Vermont, reads “Nullius in Verba” by Daniel Bosch Your browser does not support the audio element. Audio player progress bar Step backward in current audio track Play current audio trackPause current audio track Step forward in current audio track Mute current audio trackUnmute current audio track 00:00/ SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail —Motto of the Royal SocietyWhen she was a child She was misled aboutWhen she was a child.She weighed just over three stone. The first time her father was on top of herShe weighed just over three stone.The slats of a twin bed can flex. This is not a question of language.The slats of a twin bed can flex.Every clock’s face seemed to say The same thingEvery clock’s face seemed to say.The twist always came Just after. AndThe twist always came.What’s worse Is that she came to knowWhat’s worse.We had nothing ... Author, Article, and Disclosure InformationAuthors: Daniel BoschAffiliations: Atlanta, GeorgiaCorresponding Author: Daniel Bosch; e-mail, danielhbosch@gmail.com. PreviousarticleNextarticle Advertisement Audio Reading - “Nullius in Verba” Supplement. Audio. Virginia L. Hood, MD, a physician from the University of Vermont, reads “Nullius in Verba” by Daniel Bosch Your browser does not support the audio element. Audio player progress bar Step backward in current audio track Play current audio trackPause current audio track Step forward in current audio track Mute current audio trackUnmute current audio track 00:00/ FiguresReferencesRelatedDetails Metrics Current IssueNovember 2023Volume 176, Issue 11Page: 1566 ePublished: 21 November 2023 Issue Published: November 2023 Copyright & PermissionsCopyright © 2023 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...
Big Data, Behavioral Genetics and Risk of Future Offending

A convergence of trends in assessing the future risk of reoffending could result in morally questionable inputs into the criminal process. Advances in the analysis of DNA and increases in the availability of information about people gleaned from social media might allow for new inferences to be drawn against offenders during the sentencing process. We explore how developments in forensic DNA analysis methods and law enforcement DNA databases in conjunction with information about an offender’s developmental environment could lead the prosecution to postulate a high risk of recidivism and thus argue for a longer sentence. We then consider some reasons why such a prosecution strategy might be troubling. In doing so, we focus on issues related to the inferential process, discrimination, privacy and constitutive luck.