bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Experimental Study on Polymer Impregnated Concrete with Fly Ash
Authors: Jaganathan Krithika , Ramesh Kumar G B 
Published: July 2021

Abstract
Fly ash can be used in research paper to partly substitute cement for three separate types of concrete, M20, M40, and M60. Until the curing process is finished, the samples are made to undergo partial polymer impregnation and dried for 8 hours. For performance criteria, compressive strength, flexural strength and break structural stress, the concrete samples are then tested. The values obtained are compared with 0 percent of fly ash concrete cast specimens. Also, referred to as a nominal mix in this paper. Fly ash is chosen to perform this experiment because it is an eco-friendly material. It is a waste product that contributes to sustainability and incorporation of it in concrete is possible due to its pozzolanic characteristic. For the impregnation process, the polymers used are polyester and styrene. The experimental is conducted to evaluate the effect of fly ash onto cement along with partial polymer impregnation and their effects on strength properties. The research is also an initiative to contribute to sustainability. After the completion of the experiment, it can be observed that the use of fly ash as a partial replacement of cement does not negatively affect the strength parameters, alternatively, in the long run, it can be used to obtain strength higher than the nominal mix. The impregnation of polymer does have a significant impact on the concrete samples in terms of strength quality. The use of cement in concrete accounts for about 40% carbon dioxide emission, causing a greenhouse effect. On the other hand, the partial substitution of fly ash reduces the amount of cement needed in the construction process without compromising the performance of concrete. Even, the treatment of fly ash takes care of that. Due to the clear existence of fly ash, this form of selective replacement of cement in concrete can be used extensively.
Normalised Difference Vegetation Index Based Drought Monitoring Using Remote Sensing and GIS
Authors: Sreekanthand S Vidhya Lakshmi B 
Published: July 2021

Abstract
The objective of this research is to analyse vegetation’s reactions to precipitation. Three Pinups sp. combinations and water tension conditions (pine) forests and NDVI’s assessment of the capacity to identify drought and water stress in this sort of ecosystem. For the purposes of this analysis, a 30-year time series of NDVI indices, derived from SPOT-Vegetation data, is built for all three study sites and compared with field measured precipitation data for the same time span. Results indicate a good relationship between the two indices suggesting a stronger capacity for investigating the vegetation water status. In general, fluctuations in high seasonal precipitation tend to have a strong influence on both NDVI ratios, while a smoother spread of precipitation results in a poorer relationship with the two indices.
Smart Liquid Mixing System
Authors: Gauni Sabitha , Vamsi Vuddagiri Krishna 
Published: July 2021

Abstract
Smart drink appliances with a wide area of different control specifications have become a popular research area. Most of these systems are expensive and takes a lot of time to replace the whole system. The proposed method below will help us upgrade the existing appliances that make liquid mixing possible and a feature where we can control it with the help of voice. This system will help the present technologies upgrade them for automation, which will be easy since this is done using simple methods while having an ease of access. The system runs on an android smart phone, connected with the help of Bluetooth to raspberry pi 3 nodes. The application analyses the commands given through voice and sends the data to the Raspberry Pi. Based on the motors connected to it, the application searches for keywords in the command and takes the required control action.
Ocean of Things: Marine Environment Monitoring using Discriminatory Model
Authors: Menaka D , Gauni Sabitha 
Published: July 2021

Abstract
It is generating complex Marine Environment monitoring models for the ocean-based on data from Discriminant Analysis. The Ocean of Things (OoT) is adopted in this paper to help interface multiple sensors to predict climate conditions for Aquatic life monitoring. This study, therefore, contemplates five years of climate observations in two oceans. An effort is made to study the temperature, salinity, current of water, how it varies with relation to the ocean, and the reasons for differences in the location parameters. The findings are based on Canonical correlation, Lambda of Wilks, and characterization in general. It is found that the generated model is useful for weather forecasting and aquatic life monitoring.
Systematic Evaluation and Analysis of Bituminous Road Pavement Failure
Authors: Shaikh Salim G , Wadekar Abhijeet P 
Published: July 2021

Abstract
Presence of good quality roads and better connectivity to all habitants is counted one of the tool to see the development and development index of any country. In the past 30-40 years, roads were constructed rapidly; hence road length has increased to a greater extent in India. This paper will provide a systematic way of investigation and collection of field data about different types of bituminous pavement failure and their nature. This sample research, quantitative data is collected for the10 km road stretch of Mumbai-Goa NH-66. This study site is a typical representation of the condition of bituminous pavements in India and most of the parts of the world. However, their nature and magnitude change depends upon their meteorological, geographical parameters, type of road, traffic load etc. The research methodology is framed in four phases. Data is collected by trained engineers and staff working at the field level responsible for the construction and maintenance of bituminous road under the guidance of an experienced highway engineer. Detailed analysis of bituminous pavement distress is carried out systematically. It is also interpreted and represented by the statistical tools to understand it more broadly. The seriousness about type of distress and its effect on the overall failure of asphalt pavement is worked out. Results/findings worked out under this research paper is effective and concentrated the eyes of the researcher towards the root causes of asphalt pavement failure. This will definitely help the present and new researchers to further study and work on these root causes to find out the best possible solutions.
Risk assessment for earthquakes, debris flow and flooding in the ah 03 de octubre, in chosica, district of luringancho, Lima
Authors: Castillo Edwar Miguel Pagaza 
Published: July 2021

Abstract
In the district of Lurigancho, in spite of being a district that presents many natural hazards, there are no risk evaluations in all its sectors of high and multiple exposure, which would lead to the impossibility of proposing control measures for such risks in these sectors, which would result in future damages and losses. The present study allows to deepen the knowledge of the risks associated with the AH 03 de Octubre (flood, debris flow and earthquake), so it will allow to generate semi-quantitative data on its vulnerability; and from the risk assessment to support the labor of decision makers at the local or regional government level. The methodology considered was based on the structure of the manual for the evaluation of risks originated by natural phenomena of the National Center for the Estimation, Prevention and Reduction of Disaster Risks (CENEPRED). The risk levels obtained for the hazards present were generally high, with some slight variations in the percentage of blocks, which shows that the AH 03 de Octubre has a highly vulnerable population.
Fuzzy Interference System based Link Failure prediction in MANET
Authors: Durai Senthil Kumar Swami , Duraisamy Balaganesh , Thirukrishna J T 
Published: July 2021

Abstract
Mobile Ad-Hoc Network (MANET) contains wireless mobile nodes establishing a short-term network lacking the assistance of individual structure. Owing to the nodes mobility, such mobile nodes are auto-configuring also auto-organizing. In MANETs, approaches are essential to discover definite routes among the sender to receiver. One important concern for routing in MANET is how to choose a quality link route that can last longer because mobility may reason links to break regularly. To solve this issue, in this approach, a Fuzzy Interference System based Link quality prediction (FLQP) in MANET is proposed. In this approach, select the intermediate CH using Fuzzy Interference System (FIS) is predicting the sensor link quality by Received Signal Strength (RSS), Communication range (CR), Remaining Energy (RE), packet transmission rate (PTR) parameters. This FIS can be utilized to extend a metric for path selection in terms of link quality that can improve the network performance as to be exposed by the simulation results.
Synthesis and characterization of Schiff’s base-based chemosensor and its detection potential of Fluoride ions
Authors: Kurniawan C , Wati R R , Prasetya A T , Priatmoko S , Kasmui K , Bahron H 
Published: July 2021

Abstract
The development of selective and sensitive chemical sensors to overcome fluoride ions is needed, especially for applications in chemical and biological processes. One of the chemical compounds that can act as sensors is the Schiff base compound group. This study aims to synthesis a Schiff base based on salicylaldehyde and as a fluoride ion sensor. The one-pot synthesis approach was carried out in room terms by mixing salicylaldehyde with hydrazine hydrate or phenylenediamine with a molar ratio of 2: 1 in ethanol solvent under stirring for 24 hours. The bright yellow crystal was obtained with a yield of 80% for salicylaldazine (SB). The compounds in the dimethyl sulfoxide (DMSO) solvent tend to be colorless, but in the presence of F-ions, the solution turns orange. The results indicate an interaction between SB1 with F-ions in solution.
The effect of the REACT CBA strategy on the material of reaction rate on student achievement at SMA Kristen 1 Tomohon
Authors: Papia M , Rombang W A R , Karundeng M 
Published: July 2021

Abstract
The purpose of this study was to determine whether there was an effect of the REACT CBA strategy on the material reaction rate on student achievement at SMA Kristen 1 Tomohon. The REACT CBA strategy was applied in the experimental class with 33 student’s in number, and conventinal learning in the control class with 33 student’s. Studen achievement scores are obtained from the pretest and posttest scores. The results showed that there was no significant difference in the pretest scores of the experimental and control class, namely U = 543,5; p = 0,990 (p > 0,05). While for the posttest scores there is a significant difference between the experimental and control classes where U = 151,0; p = 0,000 (p = < 0,05). So that the conclusion is that H0 is rejected and H1 is accepted, it means that there is an effect of the material reaction rate on student achievement.
The influence of the learning approach of Science Technology Engineering and Mathematics (STEM) on attitudes and learning outcomes in class XI students of SMA Negeri 5 Halmahera Utara for material reaction rate
Authors: Manis A S , Tani D , Rombang W A R 
Published: July 2021

Abstract
The purpose of the study was to determine the effect of the Science Technology Engineering and mathematics (STEM) learning approach on attitudes and learning outcomes on the reaction rate material. This research was conducted at SMA Negeri 5 North Halmahera in the 2019/2020 school year. The research method used is descriptive research design with a pre-test and post-test control design. 30 students of Class XI MIA 1 were randomly selected to be assigned as research sample. Data on student attitudes towards learning chemistry were obtained through a questionnaire of initial test and final test of 20 items and data learning outcomes were obtained through the pre-test and post-test of 15 objective items. The results of the study obtained an average score of student attitudes towards chemistry after using the STEM learning approach of 93, 73 higher than before using the STEM approach 49.73 while the average score of learning outcomes after using the STEM learning approach was 78.33 higher than learning outcomes before using the STEM approach of 37.83. Based on the research findings, this show that there is an effect of the STEM learning approach on students’ attitudes and learning outcomes on the reaction rate material.
Convolutional neural network for classification of skin cancer based on image data using google colab
Authors: Kharisudin I , Hidayati A , Agoestanto A , Mashuri M 
Published: July 2021

Abstract
Climate change causes the world’s weather to become hotter and has an impact on human health. The direct impact that can be seen is the increase in skin cancer cases due to rising temperatures. This study aims to perform digital image data classification modeling by implementing the Convolutional Neural Network (CNN) method in skin cancer cases using Google Colab software. Research on deep learning applications for identifying and classification image data has been carried out in many recent articles. We used secondary skin cancer image data obtained by a dermoscopy consisting of malignant and benign skin cancer. From 3297, there are 1,800 images of benign skin cancer and 1,497 images of malignant skin cancer. For modeling purposes, it was divided into 2967 training data and 330 testing data. The training process uses variations of the epoch and learning rate to determine the best results. The accuracy value obtained is 99.60% and the validation accuracy value is 92.12%. These results were obtained using 100 epochs and a learning rate of 0.00001. Based on the prediction results using a confusion matrix for testing data, the accuracy value is 90%.
Increased accuracy of prediction hepatitis disease using the application of principal component analysis on a support vector machine
Authors: Alamsyah A , Fadila T 
Published: July 2021

Abstract
Data mining has been widely used to diagnose diseases from medical data. Classification is a data mining technique that can be used to predict disease. In previous studies, a support vector machine was widely used to obtain high accuracy in predicting hepatitis. In this study, the principal component analysis was applied to the support vector machine. A principal component analysis is used to extract features and reduce the number of features or attributes. Principal component analysis can reduce data dimensions without removing important information from the dataset. The extracted and reduced data are then used to classify the support vector machine. Classification performance measurement is done by using a confusion matrix. Hepatitis prediction accuracy achieved was 93.55%. This result is better than the support vector machine classification results without the application of principal component analysis.
Analysis of student’s expectation on science virtual class models during the covid-19 pandemic era in science education study program
Authors: Taufiq M , Dewi N R , Savitri E N , Parmin P , Darmawan M S 
Published: July 2021

Abstract
The period of the COVID-19 pandemic has forced all activities in educational institutions to maintain distance and all material delivery through unusual media and methods. To get around this unfavourable situation, online methods are one of the most effective options to overcome it. This research aims to analyse the most expected virtual class model on science learning based on student’s perspective. This research is a case study conducted through a survey method using an online questionnaire using google form. The subjects of this research were all students of basic science courses in the Science Education Study Program Faculty of Mathematics and Natural Sciences Universitas Negeri Semarang on odd semester of 2020. The results of this research indicate that the types of virtual classes implemented in basic science courses consist of LMS, LCMS, SLNs, combination of LMS-SLNs and LCMS-SLNs. The virtual classroom model implemented in science learning is in accordance with the objectives that include connectivity, flexibility, interaction, collaboration, development opportunities and motivation. The most expected virtual classroom model in science learning during the Covid-19 pandemic based on student perspectives is a combination of LMS-SLNs of 66.23%, LMS of 23.38%, LCMS-SLNs of 6.49%, and LCMS of 3.90%. The conclusion of this research indicates that the combination Virtual Class model of LMS (Learning Management System) and SLNs (Social Learning Networks) is the most expected according to student perspectives.
Analysis of student error in solving story problems in linear program materials
Authors: Kaeng F F , Mangobi J U L , Regar V E 
Published: July 2021

Abstract
The purpose of this research was to determine the percentage of student errors in solving story problems on the linear program material. The errors noted were misunderstandings of questions, errors in mathematical modeling, errors in calculating / solving, and errors in drawing conclusions. The research was conducted on class XI MIPA students of SMA Negeri 1 Langowan. The results showed that all students made mistakes solving story problems with the material of the linear program. There were 38 errors (23.89%) at the question understanding stage. There were 5 errors (3.14%) at the mathematical modeling stage. There are 90 errors (56.60%) at the computation / completion stage. There were 24 errors (15.09%) at the conclusion stage. There were 2 other errors (1.25%) made by students.
Identification of students’ conceptual understanding on electrolyte and non-electrolyte solution material using a three tier multiple choice test
Authors: Noho S S , Sihaloho M , Musa W J A 
Published: July 2021

Abstract
This study aims to identify the percentage of students’ conceptual understanding using the Three-Tier Multiple-Choice test on electrolyte and non-electrolyte solutions. The research method used is descriptive quantitative. The instrument used was a Three-Tier Multiple-Choice test. The research subjects were class X IPA MAN 1 Gorontalo City with a total sample of 20 students. The data were processed based on the students’ answer patterns which were grouped into categories of understanding the concept, not understanding the concept and misconceptions (misconceptions 1,2, and 3). The results showed that the category of understanding the concept of students was in the low category with a percentage of 28%, did not understand the concept in the high category with a percentage of 54%, and misconceptions were in the low category with a percentage of 18%. Of the 18% students who experienced misconception, the percentage was 8% misconception 1, misconception 2 was 2%, and misconception 3 was 8%.
Distance weight of GWR-Kriging model for stunting cases in East Java
Authors: Ardianti D , Pramoedyo H , Nurjannah N 
Published: July 2021

Abstract
The chosen of distance weights is needed to form an accurate Geographically Weighting Regression model. There are 3 types of distance weights namely Gaussian kernel, Bisquare kernel and Tricube kernel. The weighting in GWR describes the closeness relation between locations. For data that has spatial heterogeneity, GWR models are more suitable models than OLS models. This study was conducted to obtain the best distance weighting based on minimum cross-validation method. Using secondary data from the Health Department in East Java with 34 districts for observation, the dependent variable is stunting and five independent variables that influence stunting cases. Based on the result, GWR models with fixed gaussian models produces a better accuracy in higher R
2 values compared to OLS models. The predicted map of the spread stunting cases conducted by interpolation GWR Kriging using exponential semivariogram.
Development of PIMCA learning model on magnetic field
Authors: Patol R , Tulandi D A , Umboh I , Poluakan C , Komansilan A , Tumimomor F 
Published: July 2021

Abstract
Research on physics learning on magnetic field has been carried with the PIMCA Learning Model (Presentation, Idea Mapping, Conceptualization, Formative Assessment introduced by Cosmas Poluakan). The research objective was to develop a PIMCA learning model based on Multiple Representation-Semiotic Resources. This research and development with reference to the 10 steps of developing the Dick and Carey model. This research was conducted in the Physics Education department of Manado State University, with 30 student teachers candidate as respondents. The research procedure starts from the development step by doing the validity of the expert test and then doing trials in small groups and large groups with pre-test and post-test. The results showed that the validity of the expert test got an average value of 3. 28 so that the learning model was in the very good category and was worthy to be disseminated. In the small group trial results, the pre-test mean score was 0.2 and the post-test mean score was 2.2. Whereas for the large group the results of the pre-test and post-test trials were 0.7 and 2.5. In the student response, 46.6% chose very good, 40% chose were good, and 13.4% chose were quite good. The results of this research indicate that the PIMCA learning model is suitable for use as a learning model that can help students understand the concept of magnetic fields. 6% chose very good, 40% chose were good, and 13.4% chose were quite good. The results of this research indicate that the PIMCA learning model is suitable for use as a learning model that can help students understand the concept of magnetic fields. 6% chose very good, 40% chose were good, and 13.4% chose were quite good. The results of this research indicate that the PIMCA learning model is suitable for use as a learning model that can help students understand the concept of magnetic fields.
PIMCA learning models to improve student learning outcomes in optic magnifying glass tool
Authors: Hartati H , Mondolang A H , Silangen P M , Tulandi D A , Marianus M , Poluakan C 
Published: July 2021

Abstract
The research was carried out on the students of physics education Faculty mathematics and science Manado state university with a total of 28 students as respondents. The purpose of this study was to determine the increase in student learning outcomes on the autik lup material using the PIMCA learning model The research instrument used was a test. The research process started with the pre-test, continued with the implementation of physics learning according to the 4 steps of the PIMCA model and ended with a post-test. The results showed that the mean value before the test was 27,86 and the mean value after the test was 75 The results showed that the MR-SR-based PIMCA learning model can improve student learning outcomes to properly understand concepts of physics, especially in the subject of magnifying glass tool.