bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tibetan text classification based on RNN
Authors: Yan Wei , Cao Hui , Cui Zeyu 
Published: April 2021

Abstract
In this paper, a deep learning RNN model is used to classify Tibetan texts. The core idea is to first preprocess the Tibetan news corpus, and then use Tibetan syllables to construct a Tibetan syllable table based on the lexical and grammatical structure of Tibetan, embed the syllables in the sentence, and represent each syllable as a fixed Numerical vector. Secondly, the RNN cyclic neural network model is constructed. First, the text of different lengths is filled or truncated into a sequence length of uniform length. For each input text, the vector representation of text syllables is input on each time step of RNN to train the RNN model. The test samples were then used to evaluate the accuracy of model classification by introducing recall rate, precision rate and F-test. Finally, compared with traditional machine learning Logistic algorithm, polynomial naive Bayes algorithm and KNN algorithm, the results show that RNN model has better classification effect.
MQSD: A Scheduling Mechanism of Mixed Queue in the Integrated Intelligent Network
Authors: Zheng Jiangshan , Yang Li , Pan Chengsheng , Shi Huaifeng 
Published: April 2021

Abstract
In the integrative intelligent network, the burst and heterogeneous characteristics of the aggregation node traffic lead to increased queuing delay and frame loss rate of the business flow. It is difficult to meet the quality of service (QoS) requirements of the differentiated business flow. In response to the above problems, a mixed queue scheduling based on demand service (MQSD) is proposed for the integrated intelligent network of heaven and earth. Different scheduling algorithms are used to schedule different business flows, which distinguishes the different needs of the business. The weight of business flow is calculated using the construction judgment matrix method, and is determined to be acceptable through a consistency test. By comparing the available service volume with the demanded service volume, the available service volume to the business flow will be dynamically adjusted. Establish a simulation experiment platform to schedule different types of randomly generated data streams. Simulation results show that the MQSD mechanism reduces queuing delay and frame loss rate caused by burstiness while meeting QoS requirements.
Simulation Analysis of Harmonic Suppression for AC Charging Pile of Electric Vehicle
Authors: Zhou Z W , Yan X H 
Published: April 2021

Abstract
The nonlinear load of electric vehicle AC charging pile brings harmonic pollution to the power system, which seriously affects the safe and stable operation of the power system. In this paper, the AC charging pile of an electric vehicle is taken as the research object, and the system simulation and harmonic analysis are carried out. And APF is used to compensate and suppress the harmonic of the simulation model of electric vehicle charging. The simulation results show that the charger mainly increases the 5th and 7th harmonics to the power grid. After adding APF to the power grid side, the harmonics of the power grid side are suppressed, and the influence of the charging pile on the DC power grid is greatly reduced.
RETRACTED: Research on oil painting creation mode based on multimedia technology in big data Era
Authors: Wang Lin 
Published: April 2021

Abstract
With the continuous development of social economy, people’s living standards have been significantly improved. Under the impact of the information age, it has caused an indelible impact on the industry. In today’s era, with the continuous promotion of the development of the field, the art industry also has a lot of innovation and improvement. Due to the continuous expansion and simplicity of multimedia technology, we have a better experience of the visual effect experience of daily life, and promote the development of the art industry. In today’s information society, data-based situation, now the painting creation is also welcome to its brand-new side, it is moving towards the direction of diversified development and constantly forward exploration. The diversified forms shown in the era of big data have turned the visual art of painting into a kind of data symbolization, which meets the requirements of the development of multimedia in today’s society and has an impact on today’s social painting art to a certain extent. In the era background of today’s big data society, it also has some significant impact on the thoughts of many artists, and then has an impact on the social art development.
RETRACTED: Innovation of Cross-border E-commerce Practice Teaching Based on Big Data
Authors: Deng Jianghua , Qing Haohua 
Published: April 2021

Abstract
With the development of the times, cross-border e-commerce has gradually become an important course, but the current teaching methods are difficult to provide students with good teaching. Based on the background of big data, this article hopes to practice cross-border e-commerce in schools The teaching finds a practical form with good feasibility, and summarizes from it that can reflect the universally applicable internal laws, so that the school’s e-commerce teaching can make more students realize the role of big data. Studies have shown that cross-border e-commerce practice teaching under the background of big data is more popular among students than the current traditional teaching model, with a favorable rate of over 90%. And in terms of teaching efficiency, the efficiency of teaching based on big data reaches 0.835, which is much higher than traditional teaching methods. This shows that practical teaching of cross-border e-commerce based on big data can play an important role.
Design and Analysis of Enterprise Management System Framework Based on Blockchain Technology
Authors: Jiang Leilei , Dong Ke 
Published: April 2021

Abstract
With the advent of the data age and the rapid development of Internet of things technology, blockchain technology has been proposed. Since the advent of blockchain, it has been widely concerned. Its tamper proof, traceability, anonymity and openness have attracted more and more people’s interest. Many researchers and practitioners have stepped into this field. In this paper, the related technical concepts of blockchain are described, and the blockchain technology is integrated into enterprise management innovation to provide new ideas for enterprise management. This paper designs an enterprise management system based on blockchain technology according to the requirements, and carries out bug monitoring and pressure test on the system, and the results show that the system can be used well.
Application of Artificial Intelligence Technology in Traffic Flow Forecast
Authors: Li Yunxiang , Liu Guochang , Cheng Yingying , Wu Jifei , Xiong Yongyi , Ma Ruosen , Wang Yuhang 
Published: April 2021

Abstract
In recent years, China’s urbanization process has been accelerating, the number of motor vehicles has been increasing, and the problems of traffic congestion, traffic noise and environmental pollution have become increasingly prominent. The application of artificial intelligence system in the field of transportation provides a good idea to solve the above problems. Traffic flow prediction is to estimate the traffic flow in a period of time according to historical traffic data. This technology can provide decision-making basis for traffic guidance and path planning. In this paper, the deep learning theory of artificial intelligence technology is used to predict the short-term traffic flow, and the LSTM prediction model is constructed. On the basis of preprocessing the original data, through correlation analysis, compression matrix construction and other steps, a more accurate short-term traffic flow prediction is realized. According to the model, this paper also discriminates the actual road congestion, and the prediction results are basically consistent with the actual situation.
Thoughts on the Reform of Higher Vocational Dance Teaching Based on Big Data
Authors: Shang Meiling 
Published: April 2021

Abstract
In the fast-developing information age, the current teaching level can no longer meet the current students’ demand for knowledge. Based on the current teaching system and platform, this paper uses modern programming and big data information database as the basis, and combines some shortcomings of current college education methods and levels to design a set of remote dance information teaching system. On the basis of the B/S network structure, a new online and offline interactive teaching model for the three roles of teachers, students and administrators established by using big data has successfully enriched the diversity of higher vocational education methods.
Clove leaf ethanol extract (Syzygium aromaticum L. Merr. and Perr) is formulated as antiseptic liquid soap
Authors: Maryam S , Hartono K , Widiyawati I E 
Published: April 2021

Abstract
Secondary metabolite compound is compound that have medicinal properties, cosmetics, dyes, fragrances. Secondary metabolite compound can be modified into one form of pharmaceutical dosage, namely cosmetic products. One of the cosmetic products is liquid soap preparation. Soap that can kill bacteria is known as antiseptic soap. Clove leaves (Syzygium aromaticum L. Merr. And Perr) contain eugenol compounds which have antiseptic properties. This study aims to determine the effectiveness of the ethanol extract of clove leaves as an antiseptic liquid soap preparation. The formulation of clove leaf extract with concentrations of 5%, 10% and 15% with HPMC concentrations of 1 gr, 2 gr and 3 gr. The liquid soap formulation of clove leaf ethanol extract was tested for organoleptic, pH, specific gravity, high foam and viscosity. The results of testing the quality of all liquid soap formulations meet the requirements according to the standards set by SNI. Based on the evaluation of this liquid soap preparation, the ethanol extraction preparation can be formulated into liquid soap preparations. After being tested for its antibacterial activity, Sedian Liquid Soap from Ethanol Extract of Clove Leaves has effectiveness as an antiseptic.
Targeted discovery of glycoside hydrolases from enzymes reservoir of digestive gland Achatina fulica through functional metagenomic strategies
Authors: Kurniawati M , Yunus A , Ayu H D , Subandi S , Suharti S 
Published: April 2021

Abstract
Digestive gland Achatina fulica is source of bioprospecting of glycoside hydrolases enzymes for many biotechnological and industrial processes. Nevertheless, there is limitation to discover novel enzymes. The functional-based approach analyzes the metagenomic library based on the genomic function of an organism used to look for new enzyme-producing genes. The aim of this study was to determine the chances of obtaining the novel genes for glycoside hydrolases from enzymes reservoir of digestive gland A. fulica through functional metagenomic method. The results showed that the total RNA concentration isolated from the digestive gland of A. fulica was 2,343.2 ng/uL. A total of 2 uL of total RNA has been used to construct the metagenomic library, so there are 4.69. 1010 - 1.87. 1011 transcribed molecules from 1.17. 109 - 4.68. 109 genes. This is a great number of chances to acquire the novel glycoside hydrolase genes.
Variation in recombinant protein production volume of Fim-C-salmonella typhi as a raw material for typhoid detection kit at laboratory scale
Authors: Nurjayadi M , Jinan S F , Setiyoto T , Hardianto D , Sulfianti A , Agustini K , Sukmawati D , El-Enshasy H A 
Published: April 2021

Abstract

Salmonella typhi is gram-negative bacteria that caused typhoid fever in humans; prevention of the disease is currently through vaccination. The development of disease detection tools is also being carried out so that the detection process is faster and more accurate. In line with the development of typhoid detection devices, prior studies have managed to find factors that influence the production of Fim-C S. typhi protein on a small scale as raw material for typhoid detection kits. The purpose of this research is to apply the results of previous studies in the production of recombinant Fim-C-S. typhi proteins with volume variations of 50mL-300mL, as a foundation for large-scale production. The results of protein production were characterized by Sodium Dodecyl Sulfate Polyacrilamide Gel Electrophoresis (SDS-PAGE) and protein concentration measurements using the Bicinchoninic Acid (BCA) Assay at a wavelength of 562 nm. The results showed an amount of that protein increase along with gradually production volumes, mainly the protein in the form of inclusion bodies. According to the results obtained can be concluded production of the recombinant protein Fim-C-S. typhi at 50-300 mL volume variation on a laboratory scale has been successfully performed with consistent results, which is expected to be basic in production at pilot scale and large scale.
Chemical analysis of commercial quail laying ration with substitution of fermentation waste bean sprouts
Authors: Mardewi N K , S Rejeki I G A D , Rukmini N K S 
Published: April 2021

Abstract
Japanese quail (Coturnix-coturnix japonica) has great potential to be developed as an alternative source of cheap animal protein. Generally, quail breeders use commercial rations. The problem is that commercial rations are expensive. From an economic perspective, the cost of the ration is very high, reaching 70% of the total cost of production. To reduce the cost of ration and to maintain the nutritional quality, it is tried to substitute commercial rations using feed ingredients that have good nutritional content and the price is cheap by using waste bean sprouts. The purpose of this study was to determine the chemical quality of commercial quail laying rations substituted with fermented waste bean sprouts. The study used a completely randomized design (CRD). The treatment consisted of substituting 0%, 5%, 10% and 15% waste bean sprouts in the commercial quail laying ration. From the research results obtained that the substitution of fermented waste bean sprouts in commercial quail laying rations has a very significant effect (P<0.01) on dry matter, water content, ash content and organic matter. Substitution of waste bean sprouts in quail laying rations up to the level of 10% produces the lowest ash content and water content and meets the SNI standard, as well as the highest organic matter content of the ration
Application of yeasts isolated from fermented cocoa beans for biocontrol of pathogenic mold in chocolate fruit
Authors: Sukmawati D , Arman Z , Hasanah R , Balqis M , Setiawan A , Tafrijiyyah F , Sari R , Supiyani A , Prihantini N B , Husna S N A , El Enshasy H A , Dailin D J 
Published: April 2021

Abstract
Contamination by pathogenic mold in postharvest cocoa beans becomes a significant concern by most Indonesian farmers. Pathogenic mold can cause damage to cocoa beans by such as rotting diseases in fruit. One alternative that can be used to control pathogenic mold is using biological agents such as yeasts. Some group of yeasts can produce cellulase enzyme that can degrade cellulose, and it can possibly break the cell wall with of mold which composed of semi-crystalline chitin, p-need, and cellulose. This study aims to determine the yeast originated from fermented cocoa beans which can produce cellulase enzymes and their potential ability as a biocontrol for pathogenic molds in chocolate fruit. This study includes yeast isolation from fermented beans, screening of yeast isolates that produce cellulase enzymes, and in-vitro antagonistic testing against pathogenic molds on chocolate fruit. The results showed that there were 21 yeast isolates from fermented cocoa beans, and among all, there were five isolates which can produce cellulase enzymes, namely isolate C4.-3.3, C4.-3.13, C4.-4.9, C4.-4.10, and C4.-5.9. Yeast isolate C4.-4.10 can produce cellulase enzymes with an index of 0.32 U/mL. This research showed that the 5 yeast isolates have the low category of cellulase enzyme, and further study is needed to be done to confirm their ability to act as a biocontrol agent.
The effect of brewing time on pH values, polyphenols content, and antioxidant activities of coffee husk tea (cascara tea)
Authors: Maharani S , Mustikawati I , Nailufhar L , Istiqomah S 
Published: April 2021

Abstract
Coffee husk tea, well-known as cascara tea, is a by-product of coffee processing. It contains phenol compound that has antioxidant activity. Total phenol compound is extracted by brewing process. It is commonly called polyphenol compounds. Polyphenols extraction process is deeply connected to brewing method, especially the time. The purpose of this study was to determine the effect of brewing time on pH, polyphenols content, and antioxidants activity of cascara tea. This study was carried out in Completely Randomized Design with variations of brewing time in 5 levels from 5 minutes, 7 minutes, 10 minutes, 12 minutes, and 15 minutes. The results showed that the variation of brewing time significantly affected the levels of pH values, polyphenols content, and antioxidant activity of cascara tea. The brewing time of cascara tea for 10 minutes has the highest level of polyphenols content and antioxidant activity. Meanwhile pH values was decreased during brewing process.
Code-mixed sentiment analysis of Indonesian language and Javanese language using Lexicon based approach
Authors: Tho C , Heryadi Y , Lukas L , Wibowo A 
Published: April 2021

Abstract
Nowadays mixing one language with another language either in spoken or written communication has become a common practice for bilingual speakers in daily conversation as well as in social media. Lexicon based approach is one of the approaches in extracting the sentiment analysis. This study is aimed to compare two lexicon models which are SentiNetWord and VADER in extracting the polarity of the code-mixed sentences in Indonesian language and Javanese language. 3,963 tweets were gathered from two accounts that provide code-mixed tweets. Pre-processing such as removing duplicates, translating to English, filter special characters, transform lower case and filter stop words were conducted on the tweets. Positive and negative word score from lexicon model was then calculated using simple mathematic formula in order to classify the polarity. By comparing with the manual labelling, the result showed that SentiNetWord perform better than VADER in negative sentiments. However, both of the lexicon model did not perform well in neutral and positive sentiments. On overall performance, VADER showed better performance than SentiNetWord. This study showed that the reason for the misclassified was that most of Indonesian language and Javanese language consist of words that were considered as positive in both Lexicon model.
Predicting tuberculosis drug resistance using machine learning based on DNA sequencing data
Authors: Hadikurniawati W , Anwar M T , Marlina D , Kusumo H 
Published: April 2021

Abstract
Tuberculosis is a serious infectious disease caused by Mycobacterium tuberculosis (MTB) that primarily affects the lungs. It is known that several strains of MTB are resistant to drugs used in the treatment. This situation calls for the importance to detect and prevent further drug resistance and thus reducing the mortality rate. The conventional molecular diagnostic test is costly, requires a long time to conduct, and has low prediction ability. This research aims to explore the Machine Learning approach to accurately predict drug resistance which offers a much faster and cheaper solution than the conventional one. Experiments were carried out on 3393 isolates of MTB using several Machine Learning algorithms including C4.5, Random Forest, and Logitboost. Multiple drugs evaluated in this study include rifampicin (RIF), isoniazid (INH), pyrazinamide (PZA), and ethambutol (EMB). By using 10-fold cross-validation, the result had demonstrated that the model can accurately predict drug resistance with an accuracy of 99% and with Area Under Curve (AUC) reaching (near) 1. This result suggests that Machine Learning approach has a promising result in predicting Tuberculosis drug resistance.
K-Nearest Neighbor method for detecting egg quality conditions using Raspberry Pi
Authors: Ahsan M , Nugraha D A , Yunus A , Budianto A E , Setyaningsih W , Firniawan A , Susilowati M 
Published: April 2021

Abstract
Food production in Indonesia is very strong and constrained, such as rice, corn, eggs and so on. Eggs that are consumed every day by Indonesian citizens, many consumers of egg food are not alert to the condition or condition of the eggs, whether they are feasible or expired. There are many studies related to the nature of eggs, egg quality and others, in part there is no modeling tool for detecting egg quality conditions based on raspberry pi using the K-Nearest Neighbor method which can be used to see good or bad eggs. In this study, the Raspberry Pi was used as the main component with the aid of a camera as an image capture on eggs using training data of 100 egg samples consisting of 50 good eggs and 50 bad eggs in order to get maximum accuracy. With the help of 2 led as a light source and the software uses the Python language. The purpose of this study was to obtain the expected accuracy by collecting 20 eggs randomly to get a percentage (17/20) * 100 = 85%.
Geogebra application for quadratic functions
Authors: Sumartini T S , Maryati I 
Published: April 2021

Abstract
The purpose of this study is to analyze the use of geogebra applications in mathematics learning on quadratic function material. In addition, it needs to be seen how respondents’ conceptual and procedural understanding of the quadratic function material. This research uses quasi-experimental by taking a sample of 80 respondents. Samples were given treatment with the use of geogebra applications in mathematics learning with quadratic function material. Data analysis was performed using SPSS. The results showed that the use of geogebraic applications was effective in developing respondents’ conceptual and procedural understanding of quadratic function material.
Preliminary study as an exploration activity for estimating insitu coal density using the correlation of seismic downhole and geology drilling
Authors: Agustina R D , Pazha H , Rasyid F A 
Published: April 2021

Abstract
The need for coal is increasing every year so that coal exploration activities need to be done to maintain the availability of these materials. Exploration activities generally use the correlation of geological method (analysis) and direct measurement using the geophysical method. One of the geophysical methods used is the downhole seismic method, to determine the quality of coal hardness through several seismic parameters, namely variations in the value of the initial wave velocity (Vp & Vs) and the wave travel time (Tp & Ts). This study aims to avoid mining land clearing and environmental destruction that are misplaced. This exploration activity is carried out at six measurement points. The results showed that the density of coal in the range 1.42 - 2.05 g/cm3, while coal that is feasible to be mined has a density of 1.81 - 2.05 g/cm3 with very soft rock to very hard rock classification.