Reviewerly/exHarmony huggingface dataset:
Pengelompokan Provinsi di Indonesia Menggunakan Time Series Clustering pada Sektor Ekspor Nonmigas

Authors:
raw_author_name: Neva Satyahadewi
raw_affiliation_string: Universitas Tanjungpura

Abstract: Indonesia's export activities are dominated by non-oil and gas exports consisting of four sectors, namely the processing industry, agriculture, mining, and others. The government must pay attention to non-oil and gas exports for each province because exports can play an essential role in a country's economic growth. This study was conducted to cluster provinces in Indonesia using time series clustering in the non-oil and gas export sector based on data patterns concerning Dynamic Time Warping (DTW) distance. The sectors used in this study are the manufacturing industry sector and the agricultural sector in 34 Indonesian provinces in the period 2017 - 2021. Time series clustering analysis uses the average linkage method with DTW distance and the selection of the optimum number of clusters using the silhouette coefficient method. The results of the analysis in the processing industry sector resulted in 3 optimum clusters, namely cluster 1 consisting of 1 province that has high processing industry exports, cluster 2 consisting of 8 provinces that have medium processing industry exports, and cluster 3 consisting of 25 provinces that have low processing industry exports. As for the agricultural sector, it produces 2 optimum clusters, namely cluster 1 consisting of 5 provinces that have high agricultural industry exports, and cluster 2 consisting of 29 provinces that have low agricultural industry exports. The clustering results in the processing industry sector and the agricultural sectors have a silhouette coefficient value of 0.778 and 0.798, so it is said to have a strong cluster structure.
End-to-end VVC encoding for energy-aware HDR rendering

Authors:
raw_author_name: Olivier Le Meur
raw_affiliation_string: InterDigital, Rennes, France
raw_author_name: Franck Aumont
raw_affiliation_string: InterDigital, Rennes, France
raw_author_name: Thomas Guionnet
raw_affiliation_string: ATEME, Rennes, France
raw_author_name: Frédéric Plissonneau
raw_affiliation_string: InterDigital, Rennes, France
raw_author_name: David Touze
raw_affiliation_string: InterDigital, Rennes, France
raw_author_name: Pierre-Loup Cabarat
raw_affiliation_string: IETR, Rennes, France
raw_author_name: Juan-Carlos Vargas
raw_affiliation_string: ENENSYS, Rennes, France
raw_author_name: Oussama Hammami
raw_affiliation_string: IETR, Rennes, France
raw_author_name: Bill Redmann
raw_affiliation_string: InterDigital, Rennes, France

Abstract: The production, transmission and display of video content requires significant amounts of energy. Whether broadcasting or streaming a video, its display on modern televisions is responsible for a significant proportion of the energy consumption. This paper proposes a framework for analyzing and processing High Dynamic Range (HDR) video frames that allows a modern screen to use less energy when displaying these frames. The content is analyzed prior to encoding and transmission, generating metadata that are attached to the content. After reception by a compatible display, the metadata is then used along with display parameters and user settings to adapt the peak brightness of the content. Picture quality is assessed objectively and subjectively, while in the meantime, we analyze the influence of the peak brightness over the power consumption of the screen. All these analysis provide us new insights to propose an energy-aware HDR rendering.
3D rooms map concept based augmented reality for green library

Authors:
raw_author_name: F S Bahtiar
raw_affiliation_string: Library and Information Science, Universitas Islam Negeri Maulana Malik Ibrahim Malang
raw_author_name: F Nugroho
raw_affiliation_string: Informatics Engineering, Universitas Islam Negeri Maulana Malik Ibrahim Malang
raw_author_name: A N Rifqi
raw_affiliation_string: Library and Information Science, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Abstract: Abstract Green libraries are an exciting topic for creating environmentally friendly buildings. Libraries are synonymous with book lending services and comfortable reading rooms. The green library concept will be in line with increasing the comfort of library visitors. Libraries with large buildings need room maps for visitors to find room information. This research aims to create a room map with the concept of Augmented Reality (AR). Room maps generally use 2D images that provide information or instructions for all rooms in a building. The Augmented Reality approach as a 3D-based room map will undoubtedly provide a different experience to library visitors. Creating an AR room map will apply the Multimedia Development Life Cycle (MDLC) method. This method is suitable for application in multimedia product development. However, the resulting product is not only used as room map information but can also be used as a library promotional tool.
An Analysis of the Arts Curriculum Framework in India According to the ‘National Curriculum Framework for School Education 2023’ Document

Authors:
raw_author_name: Eunjin Ko

Abstract: The purpose of this study is to explore and analyze the arts curriculum framework, including music subjects, in India's newly announced 'National Curriculum Framework for School Education 2023', in order to examine various implications for Korea's music curriculum. For this purpose, this paper utilizes a literature research method to examine India’s curriculum documents, focusing on items such as 'document structure', 'competency', 'rationale and aims', 'content system and achievement standards' and ‘teaching &amp; learning and assessment’ according to the components of Korea's 2022 revised music curriculum. As a result of the analysis, the characteristics of each item and the differences with Korea's 2022 revised music curriculum were presented, and based on this, implications related to the design method and content of Korea's music curriculum were derived.
The Analysis of Word Formation Process in Song Album “Traumazine” by Megan Thee Stallion

Authors:
raw_author_name: Muhammad Iqbal Ramdhani

Abstract: Songs can be used to express ideas or emotions, or even as a way for people to communicate with one another. One area of linguistics, morphology, deals with how language structure might be used to analyze meanings or feelings in song lyrics. In this study, the word formation process for the song Megan Thee Stallion from the album “Traumazine” will be analyze. Descriptive research is the qualitative method employed in this study. The word formation hypothesis of George Yule (2019) is used by the researcher. The 18 songs on Megan Thee Stallion’s album “Traumazine” provided the source of the data used in this research. The “traumazine” album by Megan Thee Stallion contains 8 of the 14 different kinds of word formation process that were examined in this study. This study discovered 34 data on word formation process. There are three data from borrowing, seven from ccompounding, three from blending, ten from clipping, one each from hypocorisms and backformation, eight from acronyms, and one from multiple processes. Based on the findings, Megan Thee Stallion’s song albu ‘Traumazine” most dominantly uses the clipping process to create words
A Comparative Study on Hadoop MapReduce and Apache Spark Framework for Big Data Analytics

Authors:
raw_author_name: Dr. Vandana Vijay
raw_affiliation_string: College, Jaipur, India
raw_author_name: Dr. Vaibhav Sharma
raw_affiliation_string: College, Jaipur, India
raw_author_name: Dr. Vandana Srivastava
raw_affiliation_string: College, Jaipur, India

Abstract: In today internet world, due to the current advent of new technologies, mobile devices, and communication media like social networking sites, the amount of data generated every year is growing at a very high rate.The growth of this generated data is beyond our imagination.It is impossible to store these huge data sets in RDMBSs like MySQL, as there are no specific formats of the data and that can be in either text or image formats.It requires the need of technologies which can easily manage and process huge volumes of structured and unstructured data in real-time and can protect data privacy and security.Big data technologies like MapReduce, Apache Flume, and Apache Spark can capture, store, and analyze this huge amount of data in very efficient and less costly manner.Spark and MapReduce programming frameworks provide an effective open-source solution for managing and analyzing the Big Data.MapReduce is a high-performance distributed Big Data programming framework.It processes the data in batch processing environment.On the other hand, Apache Spark is a scalable distributed inmemory data processing engine.It processes the data in both batch and real time environment.It uses Resilient Distributed Datasets (RDD) and Directed Acyclic Graph (DAG) for data processing.In this paper, a review on Hadoop MapReduce and Apache Spark have been made by comparing them on various parameters like performance, streaming, fault tolerance, storage, language support, and reliability.
Deep Gaussian Covariance Network with Trajectory Sampling for Data-Efficient Policy Search

Authors:
raw_author_name: Kevin Cremanns
raw_affiliation_string: Niederrhein University of Applied Sciences,Institute for Modelling and High Performance Computing,Krefeld,Germany

Abstract: Probabilistic world models increase data efficiency of model-based reinforcement learning (MBRL) by guiding the policy with their epistemic uncertainty to improve exploration and acquire new samples. Moreover, the uncertainty-aware learning procedures in probabilistic approaches lead to robust policies that are less sensitive to noisy observations compared to uncertainty unaware solutions. We propose to combine trajectory sampling and deep Gaussian covariance network (DGCN) for a data-efficient solution to MBRL problems in an optimal control setting. We compare trajectory sampling with density-based approximation for uncertainty propagation using three different probabilistic world models; Gaussian processes, Bayesian neural networks, and DGCNs. We provide empirical evidence using four different well-known test environments, that our method improves the sample-efficiency over other combinations of uncertainty propagation methods and probabilistic models. During our tests, we place particular emphasis on the robustness of the learned policies with respect to noisy initial states.
Improving Line Search Methods for Large Scale Neural Network Training

Authors:
raw_author_name: Philip Kenneweg
raw_affiliation_string: Technical Faculty University Bielefeld,Bielefeld,Germany
raw_author_name: Tristan Kenneweg
raw_affiliation_string: Technical Faculty University Bielefeld,Bielefeld,Germany
raw_author_name: Barbara Hammer
raw_affiliation_string: Technical Faculty University Bielefeld,Bielefeld,Germany

Abstract: In recent studies, line search methods have shown significant improvements in the performance of traditional stochastic gradient descent techniques, eliminating the need for a specific learning rate schedule. In this paper, we identify existing issues in state-of-the-art line search methods, propose enhancements, and rigorously evaluate their effectiveness. We test these methods on larger datasets and more complex data domains than before. Specifically, we improve the Armijo line search by integrating the momentum term from ADAM in its search direction, enabling efficient large-scale training, a task that was previously prone to failure using Armijo line search methods. Our optimization approach outperforms both the previous Armijo implementation and tuned learning rate schedules for Adam. Our evaluation focuses on Transformers and CNNs in the domains of NLP and image data. Our work is publicly available as a Python package, which provides a hyperparameter free Pytorch optimizer.
Pengaruh Subtitle pada Motion Graphics "Affordable" terhadap Pemahaman Siswa Kelas VII SMPN 7 Bogor

Authors:
raw_author_name: None Amata Fami
raw_affiliation_string: Institut Pertanian Bogor

Abstract: The aim of this study is to assess the influence of subtitles in the "Affordable" motion graphics on the comprehension of 7th-grade students at SMPN 7 Bogor. This research utilizes a quantitative descriptive approach. In this study, samples are obtained through non-probability sampling, and respondents are selected using purposive sampling. Simple linear regression is employed as the data analysis technique. The results of the simple linear regression analysis reveal that the "Affordable" motion graphics have a positive and significant impact on the comprehension of 7th-grade students at SMPN 7 Bogor, accounting for 24.46%, while the remaining 75.54% is influenced by other variables.
Towards Industry 4.0: Innovation of Digital-Based Academic Administration System in Islamic Religious Universities

Authors:
raw_author_name: Hijrawati Usman
raw_author_name: Sahraini Sahraini
raw_author_name: Munir Yusuf

Abstract: The Industry 4.0 era demands digitalization in all fields, including public services in the higher education sector. This research aims to develop a digital-based academic administration service system. The research was conducted at the Faculty of Tarbiyah and Keguruan Sciences, Institut Agama Islam Negeri Palopo. The development method used was Rapid Application Development (RAD), with stages of requirements planning, system design, development and feedback collection, and product implementation. This research involved staff or education personnel and web developer experts. Data were collected through observation and validation questionnaires and analyzed descriptively using percentage techniques to determine validity. Product validity was tested by expert web developers through analysis using the Aiken V formula. This research provides an important understanding of the importance of digitalization in improving the efficiency and quality of academic administration services in the digital era. The results of this study provide a significant contribution to developing a digital-based academic administration service system and can be a foundation for further research and development in the future. This research significantly impacts academic administration practice by contributing to a digital-based service system. These findings can be the basis for further research and development on optimizing academic administration services in the digital era.
OPPORTUNITIES FOR THE DEVELOPMENT OF EDUCATIONAL SERVICES BASED ON CREATIVITY PEDAGOGY

Authors:
raw_author_name: Fayzullaeva Nilufar

Abstract: The article explores new opportunities for the development of educational services based on the pedagogy of creativity. As the education sector undergoes transformational changes, there is growing recognition of the importance of developing students' creativity. This topic delves into the theoretical foundations of creativity pedagogy, explores its practical applications, and examines potential ways to expand educational services in which creativity is a cornerstone. The goal is to shed light on how using creativity ineducation can lead to more dynamic and effective learning environments.
Creation of MOPOKAR (Card Monopoly) to Enhance Learning Skills in Comparing the Social Conditions of Indonesia and Neighboring Countries in Grade 6

Authors:
raw_author_name: Nurdinah Hanifah
raw_affiliation_string: Universitas Pendidikan Indonesia
raw_author_name: Dadan Nugraha
raw_affiliation_string: Universitas Pendidikan Indonesia

Abstract: This research aims to create MPOKAR-based (Monopoly Card) learning media and determine its effectiveness in improving students' learning skills. The research employs the Research &amp; Development (R&amp;D) method with the ADDIE model (Analyze, Design, Development, Implementation, Evaluation). Data collection techniques include observation, questionnaires, and tests. The study population consists of sixth-grade students in SDN Pakubeureum 1, located in the Kertajati sub-district of Majalengka Regency, West Java. Random sampling is used to select ten respondents for the study. The collected data are then descriptively analyzed using the SPSS program. The resulting media is highly valid, with a material percentage of 82.5% and a media aspect percentage of 98%. The media's feasibility test yields a percentage of 95%, categorized as highly feasible. Subsequently, the test results (pre-test and post-test) using the one-group pretest-posttest design on ten sixth-grade students show an average pre-test score of 54.00 and a post-test score of 82.00. It is concluded that the post-test results are greater than the pre-test, indicating an improvement in students' learning outcomes. Based on the research findings, it can be stated that the MOPOKAR ASEAN (Monopoly Card) media can enhance learning skills and is thus deemed suitable for use as a learning tool in elementary schools.
The Relationship Between The Use Of Youtube Media And The Learning Outcomes Of Students At SMKN 6 Padang.

Authors:
raw_author_name: Asmar Yulastri
raw_affiliation_string: Universitas Negeri Padang

Abstract: This research aims to: 1) Analyzing how the use of Youtube media in SMKN 6 Padang, 2) Analyzing how the learning outcomes of students in class Xl Pasrty and Bakery subjects at SMKN 6 Padang, 3) Analyzing the relationship between the use of YouTube media on the learning outcomes of students in class Xl Pastry and Bakery subjects at SMKN 6 Padang. This type of research is quantitative research with a correlational approach. The population in this study were Xl culinary class students with 101 people. The research sample amounted to 50 people with the sampling technique was simple random sampling. The data collection technique was carried out using a questionnaire (questionnaire) using a Likert scale that had been tested for validity and reliability. Data analysis using descriptive analysis. The results showed that: 1) The use of Youtube media is in the moderate category (73.25%), 2) Student learning outcomes are in the moderate category (78.78%), 3) Based on the results of the research analysis, the correlation value rxy 0.603 was obtained and the tcount value (5.242)&gt; t table 1.667. So it can be said that there is a positive relationship between the use of YouTube media and student learning outcomes.
X-AMR Annotation Tool

Authors:
raw_author_name: Ahmed, Shafiuddin Rehan
raw_author_name: Cai, Jon Z.
raw_author_name: Palmer, Martha
raw_author_name: Martin, James H.

Abstract: This paper presents a novel Cross-document Abstract Meaning Representation (X-AMR) annotation tool designed for annotating key corpus-level event semantics. Leveraging machine assistance through the Prodigy Annotation Tool, we enhance the user experience, ensuring ease and efficiency in the annotation process. Through empirical analyses, we demonstrate the effectiveness of our tool in augmenting an existing event corpus, highlighting its advantages when integrated with GPT-4. Code and annotations: https://github.com/ahmeshaf/gpt_coref
I would love this to be like an assistant, not the teacher: a voice of  the customer perspective of what distance learning students want from an  Artificial Intelligence Digital Assistant

Authors:
raw_author_name: Rienties, Bart
raw_author_name: Domingue, John
raw_author_name: Herodotou, Christothea
raw_author_name: Whitelock, Denise

Abstract: With the release of Generative AI systems such as ChatGPT, an increasing interest in using Artificial Intelligence (AI) has been observed across domains, including higher education. While emerging statistics show the popularity of using AI amongst undergraduate students, little is yet known about students' perceptions regarding AI including self-reported benefits and concerns from their actual usage, in particular in distance learning contexts. Using a two-step, mixed-methods approach, we examined the perceptions of ten online and distance learning students from diverse disciplines regarding the design of a hypothetical AI Digital Assistant (AIDA). In the first step, we captured students' perceptions via interviews, while the second step supported the triangulation of data by enabling students to share, compare, and contrast perceptions with those of peers. All participants agreed on the usefulness of such an AI tool while studying and reported benefits from using it for real-time assistance and query resolution, support for academic tasks, personalisation and accessibility, together with emotional and social support. Students' concerns related to the ethical and social implications of implementing AIDA, data privacy and data use, operational challenges, academic integrity and misuse, and the future of education. Implications for the design of AI-tailored systems are also discussed.
Extracting Lexical Features from Dialects via Interpretable Dialect  Classifiers

Authors:
raw_author_name: Xie, Roy
raw_author_name: Ahia, Orevaoghene
raw_author_name: Tsvetkov, Yulia
raw_author_name: Anastasopoulos, Antonios

Abstract: Identifying linguistic differences between dialects of a language often requires expert knowledge and meticulous human analysis. This is largely due to the complexity and nuance involved in studying various dialects. We present a novel approach to extract distinguishing lexical features of dialects by utilizing interpretable dialect classifiers, even in the absence of human experts. We explore both post-hoc and intrinsic approaches to interpretability, conduct experiments on Mandarin, Italian, and Low Saxon, and experimentally demonstrate that our method successfully identifies key language-specific lexical features that contribute to dialectal variations.
Profile of Rainfall Patterns and Extreme Air Temperatures 1981-2020 in the Mosunal Region of Indonesia (Case Study: South Sumatra)

Authors:
raw_author_name: Melly Ariska
raw_author_name: Supari Supari
raw_author_name: Muhammad Irfan
raw_author_name: Iskhaq Iskandar

Abstract: Increasing concentrations of greenhouse gases have led to changes in extreme climate events. This study aims to describe the picture of climate change in the South Sumatra Region during the last 40 years, namely from 1981-2020. Rainfall and extreme temperature data were obtained from BMKG data for South Sumatra Province at the Palembang City Climatology Station (SK Palembang City) and the Sultan Mahmud Badaruddin II Meteorological Station (SM SMB II). Maximum temperature data, minimum temperature and rainfall were obtained based on parameter profiles obtained from BMKG data for South Sumatra Province based on the ETCCDMI provisions. Maximum temperature data, minimum temperature and rainfall are processed with RClimDex software so that temperature and extreme rain index data are obtained. These indices are extreme climate indices consisting of TN90p, TX90p, TNn, TNx,TXx, TXx, TMAXmean, TMINmean, RX1day, RX5day, SDII, CDD and CWD. The results of this study indicate that the trend of air temperature will increase significantly in South Sumatra Province, especially the minimum air temperature, then the precipitation pattern will also increase, especially the accumulation of rainfall for 5 consecutive days. There is an increase in the number of dry days and a decrease in the number of wet days, as well as the higher accumulation of daily rainfall but the wet days are decreasing day by day. This is also increasingly having an impact on climate change in South Sumatra Province which is getting hotter day by day and the smoke disaster due to land and peat fires in South Sumatra Province is increasingly worrying.