bluuebunny/crossref_metadata_2025_split huggingface dataset:
Equal Access to the Vaccination of Covid-19 in Southeast Asia: Can ASEAN be a Catalyst?
Authors: Tarigan Muhammad Insan , Hafandi Raisha 
Published: July 2021

Since the time Covid-19 was discovered in Southeast Asia, around 2.5 million people have been infected and more than 54 thousand have died by early March 2021. Even though ASEAN members have followed most of the WHO recommendations to deal with Covid-19, cases are still liable to increase. Therefore, vaccine utilization is the best chance which people believe in to fight the pandemic for now. However, the vaccine’s availability and distribution are a dilemma for the ASEAN member countries. Therefore, this article aims to determine the possibility of ASEAN’s role in creating equal access to the Covid-19 vaccine for everyone. According to the juridical normative research, ASEAN is committed to protect and promote human rights and to realize the Sustainable Development Goals (SDGs). On that basis, the organization tends to play an important role in Covid-19 vaccination in Southeast Asia by cooperating with its partners to research and create the required vaccine.
Development of Puzzel Learning Media by Crossword Puzzel
Authors: Titisari Prima Wahyu , Pratiwi Febi Acitika 
Published: July 2021

<p><strong>Abstract.</strong> Learning media is a teaching and learning process that tends to be interpreted as graphical, photographic, or electronic tools to capture, process, and reconstruct visual or verbal information. Crosswords are a kind of word play. The learning media developed to facilitate teachers and students in the process of learning and teaching at Junior High School grade VIII. The purpose of this study was to prodice <em>puzzle </em>learning media by crossword <em>puzzle</em> and feasible to be developed as rearning media on human eireulatory system material. Based on the results of the observations that have been carried out, the teacher only uses descourse and less varied learning which makes students bored in learning. The method used in this study is the research and development (R &amp; D), by ADDIE method, the researcher produced a crossword puzzle and its feasibility will be tested. The results of the study after the media were tested on the validator of media experts and material experts got a very decent category. The results of the research from the science teacher, get a very feasible assessment to be developed. The results of research on peer review get a very feasible category to be tested. And the results obtained during the trial of students with trials of small groups, middle groups and large groups led to a very decent category. To we it can be concluded that, puzzle learning media by crossword puzzles is very feasible to develop.</p><p><strong>Keywords:</strong> Puzzle learning media, crossword puzzles</p>
PEMBELAJARAN FISIKA MELALUI INKUIRI TERBIMBING DENGAN MENGGUNAKAN MEDIA KIT LISTRIK PAKET DAN SWAKARYA DITINJAU DARI KREATIVITAS DAN KECERDASAN KINESTETIK SISWA
Authors: Purnami Wahyuni , Sarwanto Sarwanto , Masykuri Muhammad 
Published: July 2021

<p>Penelitian ini bertujuan untuk mengetahui perbedaan hasil belajar antara pembelajaran dengan inkuiri terbimbing dengan menggunakan media kit listrik paket dan swakarya, kreativitas, kecerdasan kinestetik, dan interaksinya. Penelitian ini dilaksanakan pada bulan Februari–November 2012 dengan menggunakan metode kuasi eksperimen. Populasi penelitian adalah seluruh siswa kelas IX SMPN 5 Klaten, Jawa Tengah. Penentuan sampel menggunakan teknik <em>c</em><em>luster random sampling</em>, yang terdiri dari kelas IX A dan kelas IX C. Kelas IX A diberi pembelajaran dengan menggunakan kit listrik paket dan kelas IX C menggunakan kit listrik swakarya. Instrumen tes digunakan untuk mengukur data hasil belajar kognitif. Observasi unjuk kerja dan angket digunakan untuk mengukur kreativitas dan kecerdasan kinestetik. Analisis data menggunakan anava tiga jalan dengan desain faktorial 2 x 2 x 2 dan dilanjutkan dengan uji<em> </em><em>Scheffe</em>. Dari penelitian ini disimpulkan bahwa: 1) ada perbedaan hasil belajar yang signifikan antara siswa yang diberi pembelajaran dengan menggunakan metode inkuiri terbimbing dengan menggunakan media kit listrik paket dan swakarya; 2) ada perbedaan hasil belajar yang signifikan antara siswa yang mempunyai kreativitas tinggi dan rendah; 3) ada perbedaan hasil belajar yang signifikan antara siswa yang mempunyai kecerdasan kinestetik tinggi dan rendah; 4) tidak ada interaksi antara media dan kreativitas terhadap hasil belajar; 5) tidak ada interaksi antara media dan kecerdasan kinestetik terhadap hasil belajar siswa; 6) ada interaksi antara kreativitas dan kecerdasan kinestetik terhadap hasil belajar siswa; 7) tidak ada interaksi antara media, kreativitas, dan kecerdasan kinestetik terhadap hasil belajar siswa.</p><p> </p><p><strong>Kata Kunci: </strong><strong> </strong><strong>Metode inkuiri terbimbing</strong><strong>, </strong><strong>kit listrik</strong><strong>, </strong><strong>kreativitas siswa, kecerdasan kinestetik</strong></p>
PENGEMBANGAN MODUL FISIKA BERBASIS MASALAH PADA MATERI LISTRIK DINAMIS UNTUK MENINGKATKAN KEMAMPUAN BERPIKIR KREATIF SISWA KELAS X SMA/MA
Authors: Sudaryati Asri , Suparmi Suparmi , Sarwanto Sarwanto 
Published: July 2021

<p>Penelitian ini bertujuan untuk: (1) mengetahui karakteristik modul fisika berbasis masalah pada materi listrik dinamis, (2) mengetahui kelayakan modul fisika berbasis masalah pada materi listrik dinamis, (3) mengetahui efektivitas modul fisika berbasis masalah pada materi listrik dinamis untuk meningkatkan kemampuan berpikir kreatif siswa. Jenis penelitian ini adalah penelitian dan pengembangan (<em>Research and Development</em>) menggunakan model Borg and Gall (1983) dengan 10 tahapan, yaitu: 1) penelitian dan pengumpulan informasi, instrument yang digunakan berupa pedoman wawancara dan lembar angket kebutuhan, 2) perencanaan, instrument yang digunakan berupa matrik keterkaiatan PBM dengan berpikir kreatif, 3) pengembangan produk awal, instrument yang digunakan berupa draf modul, silabus, RPP, kisi angket validasi, kisi angket keterbacaan, kisi angket respon, kisi soal tes berpikir kreatif, dan kisi angket penyebaran, 4) uji coba produk awal, instrument yang digunakan berupa lembar validasi, 5) revisi produk pertama, instrument yang digunakan berupa draf modul, 6) uji coba lapangan terbatas, instrument yang digunakan berupa lembar angket keterbacaan, 7) revisi produk kedua, instrument yang digunakan berupa LKS siswa, 8) uji lapangan operasional, instrument yang digunakan berupa soal tes uraian, lembar observasi, dan lembar angket respon siswa, 9) revisi produk akhir, instrument yang digunakan berupa LKS siswa, 10) diseminasi dan implementasi, instrument yang digunakan berupa lembar angket respon guru. Teknik analisis data yang digunakan yaitu analisis deskriptif, analisis kelayakan modul berdasarkan skor kriteria, dan analisis tes kemampuan berpikir kreatif melalui uji <em>Paired T-Test</em> dan dihitung menggunakan <em>N-Gain </em>ternormalisasi. Sampel penelitian dan pengembangan meliputi: 1) validator ahli (materi, media, dan bahasa) dan praktisi pendidikan (2 guru fisika), 2) sampel uji coba lapangan terbatas sejumlah 12 siswa kelas XD, 3) sampel uji coba lapangan operasional sejumlah 24 siswa kelas XA. Hasil penelitian ini adalah: 1) karakteristik modul fisika, dikembangkan dengan berbasis masalah pada materi listrik dinamis untuk meningkatkan kemampuan berpikir kreatif. Tahapan pembelajaran berbasis masalah yang dimunculkan sebagai kerangka dalam modul meliputi: (1) mengorientasi siswa kepada masalah, (2) mengorganisasikan siswa untuk belajar, (3) membimbing penyelidikan individual maupun kelompok, (4) mengembangkan dan menyajikan hasil karya, (5) menganalisis dan mengevaluasi proses pemecahan masalah, 2) modul dikategorikan layak dengan skor rata-rata 3,62, 3) modul fisika berbasis masalah pada materi listrik dinamis efektif untuk meningkatkan kemampuan berpikir kreatif siswa pada kategori sedang dengan<em> N-Gain </em>sebesar 0,52.</p>
The relationship between the normalized difference vegetation index, rainfall, and potential evapotranspiration in a banana plantation of Venezuela
Authors: Olivares Campos Barlin Orlando , Paredes Franklin , Rey Juan Carlos , Lobo Deyanira , Galvis-Causil Stephanie 
Published: July 2021

<p>The water supply for rainfed crops such as bananas in the Aragua state of Venezuela is often uncertain, particularly towards the beginning of the rainy season (April-May). Where climatic conditions are seasonal, the temporal evolution of the NDVI (Normalized Difference Vegetation Index) closely accompanies the interannual variation of vegetation growth in response to thermal and hydric factors. The aim of the study is to assess the relationship between NDVI, rainfall and potential evapotranspiration during the period of January/2016 to December/2017 in a Venezuelan banana plantation. In this study, the NDVI derived from the GIMMS MODIS Terra product, the daily accumulated precipitation data (mm) and the daily mean air temperature (°C) were used as the only way to estimate the potential evapotranspiration. The results showed that the GMOD09Q1-based NDVI reflects reasonably well the spatiotemporal variation in biomass accumulation. Besides, this provides information on the water stress conditions in banana plants at the plot level. The influence of Precipitation and potential evapotranspiration on the NDVI was more evident when a lag of 1 month was considered in terms of the Spearman r, implying that there is a delay in the banana phonological response to rainfall changes and dryness conditions. However, due to its low spatial resolution (i.e. 250 m), it is not adequate for the identiﬁcation of banana wilt disease. Therefore, future studies are needed to assess other satellite-derived spectral indices for monitoring the health of banana plants over different sites in Venezuela.</p>
DECISION SUPPORT SYSTEM FOR DETERMINING THE OPTIMAL COMPOSITION OF THE TEAM OF PERFORMERS ON THE EXAMPLE OF THE SPORTS VERSION OF THE GAME “WHAT? WHERE? WHEN?"
Authors: Melnykov Oleksandr 
Published: July 2021

The paper describes the task to create a decision support system that allows you to determine the optimal composition of the team of performers. The sports version of the game “What? Where? When?" is chosen. The principles of holding tournaments on the intellectual game “What? Where? When?" and the rules for the formation of teams to participate in such competitions. It is concluded that to predict the impact of changes in the team composition on the result, it is advisable to use modern mathematical and intellectual methods, including the method of artificial neural networks. The available data on the results of synchronous tournaments LUK (ST) since 2011 and city tournaments (GT) since 2017 are presented, the main indicators for each competition are characterized. The introduction of the output factors is substantiated: the ratio of the team’s result to the average result and the ratio of the team’s result to the winner’s result. The forecasting problem is formulated as a prediction of the relative result of a team on a specific game based on the available list of team players for this game. It is proposed to take into account the location of a particular game, and fix the participation of players in the form of a “share” of the contribution to the team’s result, while the sum of the “shares” of all players should be equal to one. A method of artificial neural networks with a two-layer perceptron architecture, a sigmoid activation function and an error propagation algorithm for training a network is proposed. Examples of calculation in the Deductor Studio Lite environment are given. It is concluded that for the practical application of the model, the constant use of standard packages is inapplicable. In addition, it is also necessary to solve the problem of automating the selection of the team composition. Described is an application developed in a visual programming environment – a decision support system that allows you to import source data from an XLS file, configure input and output factors, change the architecture of the neural network (the number of hidden layers and the number of neurons in each layer), train the neural network using the backpropagation of errors, save the trained network on disk and load it again, calculate values for the input data, search for options for the composition of the team. The developed decision support system makes it possible to give recommendations on the formation of a team for a specific tournament by enumerating options.
Keywords: intellectual games, questions package, team building, forecasting, artificial neural network, perceptron, sigmoid, network training.
MODELLING SEMANTIC KERNEL OF WEB RESOURCE
Authors: Orekhov Sergey , Malyhon Hennadiy 
Published: July 2021

The article presents an attempt to describe mathematically the effect of the semantic kernel of a web resource on the Internet. In accordance with the theory of marketing, the product that we want to sell on the network is characterized by the following basic properties: price, time and place. In other words, a potential buyer wants to receive a given product in the right place at a given time. To satisfy this need, it is necessary to use the classic component of marketing, product promotion. However, this component is now becoming a fully virtual instrument. This tool functions in a hypertext, video and image environment. Therefore, the user analyzes the meaning of these elements in order to get the desired product. The results of web projects carried out in this area indicate the emergence of a new phenomenon, which reflects the main meaning of virtual promotion – this is the semantic core. The core is a short annotation of the main properties of the product, its location and time of appearance. Therefore, the purpose of this article is both a presentation of a new object of research and a mathematical description. It is assumed that the semantic core is formed on the basis of natural language terms. In other words, the semantic core is a set of keywords that are grouped by meaning. We propose to use data mining approaches for clustering to group terms. The classic clustering method at the moment is k-means. The article presents a model of the semantic core based on this method. This method and its distance function are considered as the second stage of web content processing. At the first stage, web content is converted into a semantic web. However, the k-means technique has significant drawbacks when modeling the semantic core. Therefore, in the development of this idea, the work shows an alternative way to modeling the kernel. As an alternative approach, the construction of clusters based on the concept of maximum flow is considered. This approach has the significant advantage that the type of links in the semantic network overlaps with the type of distance function in this method. As a result, on a real web project, the effect of the connection between the semantic core model and the level of new users of the web resource was demonstrated over the past five years.
Keywords: semantic kernel, keyword, k-means, max flow.
SIMULATION OF THERMAL PROCESSES OF A NPP STEAM GENERETOR FOR INFORMATION TECHNOLOGY OPTIMIZED CONTROL
Authors: Nikulina Olena , Severyn Valerii , Kotsiuba Nina , Bubnov Anton 
Published: July 2021

Mathematical models of thermal processes in the form of Cauchy in the state space with relative variables of the steam generator PGV-1000 of the power unit of a nuclear power plant with a nuclear reactor VVER-1000 have been developed for the using of models in information technology for optimizing the control of a steam generator. The working thermal processes in the PGV-1000 steam generator associated with the supply of feed water to it from the water treatment system and the coolant from the nuclear reactor and the removal of vapors to the main steam header are considered. The design diagram of the steam generator is presented, which reflects the working processes in it under the evaporation mirror and above it. On the basis of differential equations of the heat balance of the heat carrier in the steam generator and in the metal heat exchange tubes, the simulation of heat transfer from the heat carrier to the feed water in the steam generator is carried out. The heat transfer model in the form of a linear system of differential equations in relative state variables is developed. The processes of vaporization during heating of feed water by the heat transfer surface are considered. Differential equations of material and heat balances of dynamic processes of vaporization in a steam generator are compiled, which are not equations in the Cauchy form. Transformations of the differential equations of material and heat balances in the steam generator to the Cauchy form are carried out. A nonlinear system of differential equations for the balance of vaporization in relative state variables is obtained. The values of the constant parameters of the models for the steam generator PGV-1000 are calculated. The mathematical model of thermal processes in the PGV-1000 steam generator, which is presented in the form of a system of differential equations and includes the processes of heat transfer and steam generation, will make it possible to identify and optimize the steam generator control system with the help of information optimization technology.
Keywords: nuclear power plant, steam generator, thermal processes, mathematical model, differential equations, optimization, control, information technology.
Fenomena Natural Resource Curse dalam Pembangunan Wilayah di Indonesia
Authors: Rahma Hania , Fauzi Akhmad , Juanda Bambang , Widjojanto Bambang 
Published: July 2021

Although the phenomenon of natural resource curse is suspected to have occurred at the regional level in Indonesia, no measurement of such a phenomenon has been carried out yet. This research is aimed to provide an index of measuring the degree of natural resource curse at provincial level in Indonesia. Two indices, the natural resource dependence index and regional sustainable development index, were used to formulate index of regional resource curse (RRCI) using geometric mean of conditional weighted product method. The results found that provinces with richer in mining tend to have higher resource curse index compared with those with less extractive resources. ------------------------------------------ Meski fenomena natural resource curse diduga terjadi di tingkat daerah di Indonesia, pengukuran terhadap fenomena tersebut belum pernah dilakukan. Penelitian ini bertujuan untuk mengukur besaran natural resource curse di tingkat provinsi di Indonesia. Dua indikator, yakni indeks ketergantungan sumber daya alam dan indeks pembangunan daerah berkelanjutan digunakan untuk menghitung regional resource curse index (RRCI) menggunakan rerata geometrik conditional weighted product method. Hasilnya menunjukkan bahwa provinsi dengan sumber daya alam tambang yang lebih kaya cenderung menghadapi fenomena resource curse yang lebih tinggi dibandingkan provinsi dengan sumber daya ekstraktif yang lebih sedikit.
Training Image Optimization Method Based on Convolutional Neural Network and Its Application in Discrete Fracture Network Model Selection
Authors: Yu Siyu , Li Shaohua 
Published: July 2021

Abstract
Training image (TI) is important for multipoint statistics simulation method (MPS), since it captures the spatial geological pattern of target reservoir to be modeled. Generally, one optimal TI is selected before applying MPS by evaluating the similarities between many TIs and the well interpretations of target reservoir. In this paper, we propose a new training image optimization approach based on the convolutional neural network (CNN). First, candidate TIs were randomly sampled several times to obtain the sample dataset. Then, the CNN was used to conduct transfer learning for all samples, and finally, the optimal TI of the conditioning well data is selected through the trained CNN model. By taking advantage of the strong learning ability of CNN in image feature recognition, the proposed method can automatically identify differences in spatial features between the conditioning well data and the samples of the training image. Hence, it effectively resolves the difficulty of spatial matching between discrete datapoints and grid structures. We demonstrated the applicability of our model via 2D and 3D training image selection examples. The proposed methods effectively selected the appropriate TI, and then the pretreatment techniques for improving the accuracy of continuous TI selection were achieved. Moreover, the proposed method was successfully applied to training image selection of a discrete fracture network model. Finally, sensitivity analysis was carried out to show that sufficient conditioning data volume can reduce the uncertainty of the optimization results. By comparing with the improved MDevD method, the advantages of the new method are verified in terms of efficiency and reliability.
Artificial Intelligence Coreflooding Simulator for Special Core Data Analysis
Authors: Mathew Eric Sonny , Tembely Moussa , AlAmeri Waleed , Al-Shalabi Emad W. , Shaik Abdul Ravoof 
Published: July 2021

SummaryTwo of the most critical properties for multiphase flow in a reservoir are relative permeability (Kr) and capillary pressure (Pc). To determine these parameters, careful interpretation of coreflooding and centrifuge experiments is necessary. In this work, a machine learning (ML) technique was incorporated to assist in the determination of these parameters quickly and synchronously for steady-state drainage coreflooding experiments. A state-of-the-art framework was developed in which a large database of Kr and Pc curves was generated based on existing mathematical models. This database was used to perform thousands of coreflood simulation runs representing oil-water drainage steady-state experiments. The results obtained from the corefloods including pressure drop and water saturation profile, along with other conventional core analysis data, were fed as features into the ML model. The entire data set was split into 70% for training, 15% for validation, and the remaining 15% for the blind testing of the model. The 70% of the data set for training teaches the model to capture fluid flow behavior inside the core, and then 15% of the data set was used to validate the trained model and to optimize the hyperparameters of the ML algorithm. The remaining 15% of the data set was used for testing the model and assessing the model performance scores. In addition, K-fold split technique was used to split the 15% testing data set to provide an unbiased estimate of the final model performance. The trained/tested model was thereby used to estimate Kr and Pc curves based on available experimental results.The values of the coefficient of determination (R2) were used to assess the accuracy and efficiency of the developed model. The respective crossplots indicate that the model is capable of making accurate predictions with an error percentage of less than 2% on history matching experimental data. This implies that the artificial-intelligence- (AI-) based model is capable of determining Kr and Pc curves. The present work could be an alternative approach to existing methods for interpreting Kr and Pc curves. In addition, the ML model can be adapted to produce results that include multiple options for Kr and Pc curves from which the best solution can be determined using engineering judgment. This is unlike solutions from some of the existing commercial codes, which usually provide only a single solution. The model currently focuses on the prediction of Kr and Pc curves for drainage steady-state experiments; however, the work can be extended to capture the imbibition cycle as well.