bluuebunny/crossref_metadata_2025_split huggingface dataset:
The use of soxhletation method and microwave-assisted extraction in extracting tannin from jengkol peel (Pithecellobium jiringa)
Authors: Tambun R , Husna R , Fitri M D , Ginting Y , Alexander V 
Published: April 2021

AbstractThis study aims to compare the ability of the Soxhletation method and Microwave-Assisted Extraction in extracting tannin from Jengkol peel. The solvent used in both extraction methods is ethanol. In the Soxhletation method, the operating conditions performed are heating at a temperature of 70 °C for 6 hours, while the operating conditions at Microwave-Assisted Extraction are using a microwave power of 100 W with extraction time of 180 seconds. The ratio of samples and solvents in both methods is 1: 6 and 1:10. Based on the results of the study, the highest tannin content obtained from Jengkol peel extract using ethanol solvent is by using Microwave-Assisted Extraction, which is equal to 11.94% in the ratio of sample and solvent is 1:10. In the Soxhletation method, the highest tannin content obtained in the Jengkol peel extract is 10.72%, which is achieved in a sample and solvent ratio of 1:10.
Utilization of fatty acid from papaya seed waste oil (carica papaya l) as a raw material in the making of epoxy compound
Authors: Sinaga Mersi Suriani , Tambun Rondang , Mardhiyani Fina Dina Putri , Rahmadani Dea 
Published: April 2021

AbstractEpoxy is a compound that is produced from the reaction between double bond inside the fatty acid and active oxygen. This compound could be applied as a stabilizer, plasticizer on PVC (Polyvinyl Chloride) and could be used an antioxidant in processing natural rubber, surfactant, anti-corrosive-additive agent on lubricant, and as raw material for pesticide. The raw material in this study was papaya seed oil. The aim of this research to get the effect of catalyst concentration, amount of H2O2(ml) and stirring rate (rpm) on the characteristics of epoxy compounds. In this study, fatty acid, which was contained in raw material, was reacted to hexane, glacial acetic acid, H2O2with the variation of 40ml, 50ml, 60ml, and 70ml, sulfuric acid as a catalyst with variation, stirring velocity with variation of 400 rpm, 500 rpm and 600 rpm for 180 minutes. The result of this study showed that the best epoxy compound result was acquired at 2.5% of catalyst concentration, 70ml H2O2and 600 rpm of stirring speed, where the oxirane oxygen value was reached 3.52, iodine number was 10,4058 and oxygen conversion was 73, 76471%.
The influence of the amount of catalyst on the degree of sulfonation in the sulfonation process on waste-based Styrofoam (polystyrene) into Poly-(Styrene Sulfonic Acid)
Authors: Manurung R , Hasibuan R , Inarto H , Saputra A 
Published: April 2021

Abstract
This study aims to determine the influence of the amount of Ag2SO4 silver sulfate catalyst and amount of time on the degree of sulfonation in waste-based Styrofoam (polystyrene) into Poly-Styrene Sulfonic Acid (PSSA). The method used is sulfonation with sulfuric acid H2SO4 as a sulfonating agent. Based on the research, the sulfonation reaction was successfully carried out, which was shown by the functional group in the FTIR test and the highest degree of sulfonation achieved was 67.6%, which come from variation amount of 2% Ag2SO4 catalyst and 25 minutes of reaction time.
Improving the quality of liquid smoke from pyrolysis of oil palm fronds with the adsorption–distillation purification process
Authors: Maulina Seri , Karo Eka Oktaviani br 
Published: April 2021

AbstractOil palm fronds have the potential to be processed into liquid smoke. The main compounds contained in liquid smoke are acids, phenols and carbonyl produced from the decomposition of cellulose, hemicellulose and lignin. The aim of this research is to purify the liquid smoke from the oil palm frond pyrolysis through the adsorption process with activated zeolite and distillation. The pyrolysis process takes place at a pyrolysis temperature of 400°C for 120 minutes, and the distillation process was carried out at the temperature of 150°C, 175°C and 200°C with 30 minutes, 45 minutes and 60 minutes. The analysis of liquid smoke conducted using the GC-MS Shimadzu QP 2100 brans instrument. The results indicated the highest acetic acid in liquid smoke was 63,09% at a distillation temperature of 150°C for 45 minutes. The highest total phenol content was 12,44% at 200°C distillation temperature for 60 minutes, and the highest total carbonyl content was 21,56% at 200°C distillation temperature for 60 minutes.
Comparison of activated zeolite and activated carbon as adsorbent on liquid smoke purification
Authors: Maulina Seri , Kamny Ekanzha Rizqandy , Amalia Rizki 
Published: April 2021

Abstract
This study aims to compare the using of activated zeolite with activated carbon as an adsorbent in the process of adsorption of liquid smoke. Liquid smoke was obtained from condensation of vapour produced by the pyrolysis of oil palm fronds. Adsorption of liquid smoke was carried out at temperature of 60 °C for 60 minutes with a ratio of adsorbent to liquid smoke 1:10. The parameters observed in this study were acetic acid, phenol compounds and carbonyl compounds which were analyzed using GC-MS. The results showed that the most dominant compounds which reduced after the adsorption process were carbonyl. Carbonyl compounds played a role in producing smoke scents. Adsorption process reduced the stinging scent of liquid smoke. The adsorption using activated zeolite showed an increase in acetic acid levels in liquid smoke with an average percentage increase of 11,29%, while the levels of phenol and carbonyl compounds decreased with an average percentage reduction of 14.35% for phenol compounds and 81.19% for carbonyl compounds. While on the adsorption by using activated carbon, acetic acid levels also increased with an average percentage increase of 0,58%, while phenol and carbonyl compounds decreased with an average reduction percentage of 31.19% and 83,35%.
Anthocyanin as natural dye in DSSC fabrication: A review
Authors: Pramananda Viqry , Hadyan Fityay Teuku Aufar , Misran Erni 
Published: April 2021

Abstract
Nowadays, solar cell technology that dominates the market is a silicon-based solar cell with efficiency of 15-20%. Unfortunately, this type of solar cell has some weaknesses such as complex production process, utilize hazardous compounds and expensive production price. Therefore, the researchers developed organic solar cell namely dye-sensitized solar cell (DSSC). Nevertheless, the efficiency of DSSC still lower than that of conventional solar cell. Several studies have been carried out to increase the efficiency of DSSC like the use of anthocyanin dye. Anthocyanin is a flavonoid compound that has a wide absorption range and has conjugated π bond to catch photons from sunlight. The use of anthocyanin in DSSC has been applied in several methods, such as the use of single anthocyanin dye, adding copigment, and mixing them with other dyes. The purposes are to increase stability and widen light absorption area due to result in better efficiency. This article reviews the development of anthocyanin utilization as a natural dye in DSSC fabrication as well as some modifications that have been done. The use of anthocyanin as a natural dye in DSSC fabrication is feasible to be developed in industrial scale.
Pre-design plant of cellulose acetate from sugarcane bagasse using the Emil Heuser Method with a production capacity of 10,000 tons/year
Authors: Trisakti B , Irvan  , Manurung R , Surya I , Sidabutar R , Alfayed M J , Alfaizah N , Sitorus D K , Ardiansyah D 
Published: April 2021

Abstract
Cellulose acetate is a cellulose derivative product that has high commercial value because it is widely applied to textile fibers, cigarette filters, plastics, photographic films, paper and membrane coatings. The need for cellulose acetate in Indonesia is quite large because Indonesia is one of the largest textile producing countries in the world. However, Indonesia does not yet have a factory that produces cellulose acetate. Therefore, the establishment of a cellulose acetate factory has a large market opportunity for domestic and foreign needs. The pre-designed plant of cellulose acetate from sugarcane using the Emil Heuser method is planned to operate with a production capacity of 10,000 tons/year. The factory location will be on Raya Krembung road, Krembung region, Sidoarjo Regency, East Java, Indonesia. The land area required is 25,000 m2. The planned of business entity is a Limited Liability Company (Ltd). The pre-designed plant has a Profit Margin of 41.69%, Break Even Point 30.99%, Return on Investment 27.53%, Pay Out Time 3 years 6 months 3 days, Return on Network 44.88%, and Internal Rate of Return 35.99%. Based on the analysis of this economic aspect, it can be concluded that this factory is feasible to be established.
The effect of method, type of solvent and extraction time towards the yield of oil on essential oil extraction from lime peel (Citrus aurantifolia)
Authors: Hasibuan R , Gultom E 
Published: April 2021

Abstract
Essential oil is a volatile substance and has a distinctive scent that can be found on plants. Lime peel oil is one part of the plant which can be processed to make an essential oil so that it can be used as a natural fragrance in soap making. The purpose of this study is to produce essential oil from lime peel, which can be used as a substitute for synthetic fragrance ingredients in soap making. The other purpose is to obtain the optimum method, type of solvent, and the optimum extraction time to produce essential oil. The raw material used in this study is lime peel powder sized 50 mesh. The water content of raw material on lime peel powder is 76,5 %. The extraction method used in the research is maceration with stirring equal to 150 rpm and Soxhlet with extraction time for 6, 9, and 12 hours. In this study, the ratio of raw material to the solvent is 1:10, and the type of solvent used is hexane, ethanol, and distilled water. The result in this study shows that Soxhlet is the optimum method, which obtains yield equal to 6,15% for 12 using hexane as solvent.
Oil fuel production through pyrolysis of reject plastic from paper industry using coal fly ash as catalyst
Authors: Misran Erni , Bratajaya Bimanyu Yoga , Dina Sari Farah 
Published: April 2021

Abstract
This study aims to obtain the best operating conditions including pyrolysis time and amount of catalyst in oil fuel production from reject plastic as raw material with coal fly ash as catalyst based on its yield and characteristics. Both reject plastic and coal fly ash are waste originating from a paper industry in Medan. This research was carried out in three steps: preparation of reject plastic and coal fly ash, oil fuel production and characterization (composition of coal fly ash and density, viscosity and heating value of oil fuel). The main components in the coal fly ash are SiO2, C and Al2O3 that are 30.36%, 27.11% and 24.04% respectively. The yields of oil fuel are in the range of 14.18% - 26.58%. From 12 samples, 10 samples meet the standard density whereas 8 samples meet the standard viscosity for diesel fuel based on ASTM D-975. The best operating condition is achieved when using 15% catalyst with 2 h pyrolysis time that produce oil fuel with the highest heating value.
Analytical Study of Blockchain Enabled Security Enhancement Methods for Healthcare Data
Authors: Roy Moumita , Singh Monisha 
Published: April 2021

Abstract
Healthcare data protection is very much required in the present time due to the rate of growth in data volume and sensitivity of the data. The data is collected through EHR, diagnostic image like scan or x-ray or IoT wearable devices which has sensors and shared with stakeholders who can analyse the data and use it for betterment of the processes. Benefits of medical data sharing among the entities makes it even more vulnerable. In this paper we have studied and analysed few blockchain based methods of securing healthcare data which is stored in cloud. The methods studied is successful in keeping the data safe from unauthorized access.
A Comparative Study of Various Human Activity Recognition Approaches
Authors: Goel Dhruv , Pradhan Rahul 
Published: April 2021

AbstractHuman Activity Recognition (HAR) is a vast and exciting topic for researchers and students. HAR aims to recognize activities by observing the actions of subjects and surrounding conditions. This topic also has many significant and futuristic applications and a basis of many automated tasks like 24*7 security surveillance, healthcare, laws regulations, automatic vehicle controls, game controls by human motion detection, basically human-computer interaction. This survey paper focuses on reviewing other research papers on sensing technologies used in HAR. This paper has covered distinct research in which researchers collect data from smartphones; some use a surveillance camera system to get video clips. Most of the researchers used videos to train their systems to recognize human activities collected from YouTubes and other video sources. Several sensor-based approaches have also covered in this survey paper to study and predict human activities, such as accelerometer, gyroscope, and many more. Some of the papers also used technologies like a Convolutional neural network (CNN) with spatiotemporal three-dimensional (3D) kernels for model development and then using to integrate it with OpenCV. There are also work done for Alzheimer’s patient in the Healthcare sector, used for their better performance in day-to-day tasks. We will analyze the research using both classic and less commonly known classifiers on distinct datasets available on the UCI Machine Learning Repository. We describe each researcher’s approaches, compare the technologies used, and conclude the adequate technology for Human Activity Recognition. Every research will be discussed in detail in this survey paper to get a brief knowledge of activity recognition.
Bitcoin Price Alert and Prediction System using various Models
Authors: Shankhdhar Ashutosh , Singh Akhilesh Kumar , Naugraiya Suryansh , Saini Prathmesh Kumar 
Published: April 2021

Abstract
From last many years it has been a trend to invest in cryptocurrency especially (Bitcoin) because it is one of the most popular and decentralized digital currency. However, its prices keep on fluctuating very much that makes it difficult to predict. So, our research aim is to find the less time consuming and accurate model for the prediction of Bitcoin price from different machine learning models like (Multivariate Linear Regression, Theil-Sen Regression, Huber Regression) and deep learning algorithms like (LSTM, GRU). The dataset that we will use for our prediction purpose will be stored in MongoDB (Big-Data Tool) because it consists of huge data points. We have also implemented IOT in our system to create an alert system, which alerts user when the value of bitcoin price reaches a threshold value.
Performance evaluation of health recommendation system based on deep neural network
Authors: Sood Gauri , Raheja Neeraj 
Published: April 2021

Abstract
Deep learning has developed as an innovative zone of machine learning and data mining exploration part. Controlled or unconfirmed methodologies which contain of a number of layers of handling which form a hierarchy are castoff for preparation in deep learning. Every succeeding layer mines an ever more intellectual depiction of the input data and shapes upon the depiction from the preceding layer, usually by calculating a nonlinear alteration of its input. The constraints of these alterations are adjusted by preparation of the prototypical on a dataset. A deep learning prototypical studies better depiction as it is delivered with more volumes of data. Key objective of using deep learning methods in recommender schemes is to lower time complexity and to increase the accurateness of formed expectations. In this paper, performance of planned HRS is evaluated by Arbitration Time, Latency Time, Jitter, Execution Time, Network Bandwidth Consumption, Power Consumption, Training Accuracy and Testing Accuracy.
Comparative Study of Recent CMFD Techniques: A Review
Authors: Parashar N 
Published: April 2021

Abstract
Due to the ease in manipulation of digital images with various existing photo editing tools and softwares the task of authentication and identifying the reliability of digital image has become a major concern. Copy-move forgery detection (CMFD) is therefore known to be one of the key-domains in the latest digital image authentication study. Copy-move forgery is a passive approach in which a portion of an image is copied and then pasted onto the same image, resulting in a tampered image. In this paper, current developments in CMFD have been surveyed and a comparative evaluation of recent CMFD techniques has been done along with its advantages and limitations. Also, a detailed description of relevant copy-move forgery detection datasets is provided which will help the researchers to decide which dataset to choose for a given CMFD approach.
Impact of Driving Factors on Cloud Computing Adoption in the Higher Education
Authors: Hiran Kamal Kant 
Published: April 2021

Abstract
The aim of this research is to explore the sociocultural and economic factors involved in the adoption of emerging technology, i.e., the cloud at the University in Ethiopia. Organizations’ growth and development depend on the various factors that influence productivity and efficiency to improve the work culture. The data collected from the relevant key actors or stakeholders from the higher education system i.e., University of Gondar, Ethiopia, and complied in a purposive way. The researcher identified the most inducing factors under the sociocultural categories are societal belief with regression weight SoCF_1=0.821, followed by ideologies or value of individual towards CC, language barrier, and awareness towards the cloud. Similarly, the most inducing economic factors were high investment cost with regression weight EcoF_1=1.096, followed by per capita income, government grants and infrastructure development. The framework from the full-scale analysis will theoretically lead to the creation of a discussion model that can be used to examine cloud adoption in higher education.
Automation of discussion board evaluation through keyword extraction techniques: a comparative study
Authors: Thiyagarajan Gomathi , Prasanna S , Uma B 
Published: April 2021

Abstract
With the current trend in lieu of the ongoing pandemic, online learning and technology-based pedagogy receive worldwide attention. There are several pedagogical practices one can use to evaluate students mindful and the method will vary based on the learning objective. In this paper, our goal is to dive deeper into identifying the best keyword extraction technique which can be closely mapped with human evaluation. We report the results of three popular keyword extraction techniques specifically RAKE, TF-IDF, and Semantic Fingerprinting on the dataset generated from the discussion board post of a Learning Management System. The results illustrate that the TF-IDF algorithm shows the highest correlation with a human evaluation with 0.76 correlations, RAKE with 0.36, and Semantic Fingerprinting with 0.58. It was also identified Semantic Fingerprinting had a lowest mean square error of 18.26.
Comprehensive Analysis of Cloud based Databases
Authors: Kumar E. Saravana , Kesavan Selvaraj , Naidu R. Ch. A , Kumar R Senthil , Latha  
Published: April 2021

Abstract
With standard change in the computing architecture and distributed, wide range processing approach leverage the large data to be analyzed and extract the content. The recent advancement in Web technology enables the user to produce process and ingest content of any structure. Cloud computing helps to provide computing infrastructure, centralized storage and seamless services for organizations and users. In a digital world, data is core aspect of the economy, become part of government, enterprise, social sectors and every individual in a day to day life. Data analysis is gathering of strength in both research and production communities. There are many social networking sites, web, enterprise and IoT data require being stored in secured, centralized data store. It also demands data to be stored without any predefined schema and able to retrieve in near real time. When demand goes up application needs to be scaled to sustain for the demand. Similarly, data store should support scalability to support applications demand. Cloud providers and third-party organization offers numerous data storage, database options. This article highlights various available data storage options, suitability and limitations.
All-optical logic gates based on anomalous Floquet photonic topological insulator structures
Authors: Merlo Juan M , Wu Xueyuan , Kempa Krzysztof , Naughton Michael J 
Published: April 2021

Abstract
Topological photonics is an incipient research area where the well-developed theory and applications of so-called topological insulators is applied to photonic systems. In that vein, specially-designed ring waveguides, arranged in a periodic structure and evanescently coupled, have shown the ability to propagate edge states that are robust against defects in the lattice. Here, we propose the application of photonic topologically-protected edge states (TPES) in the anomalous Floquet photonic topological insulator structures to develop a device that is able to behave as OR, AND, and XOR logic gates, depending on the characteristics of the excitation field. Materials and dimensions of the device are amenable to conventional fabrication methods, opening the possibility for implementation in on-chip photonic communication technology. We conclude by applying our results to the implementation of an all-optical two bit calculator based on TPES, a potential building block for future computational technology.
Near singular-phase optical biosensing with strongly coupled modes of a plasmonic–photonic trimer
Authors: Gupta Nitish Kumar , Tiwari Anjani Kumar , Wanare Harshawardhan , Ramakrishna S Anantha 
Published: April 2021

Abstract
A lithography-free plasmonic–photonic hybrid nanostructure exhibiting an interesting phenomenon of cavity-mediated normal-mode splitting among doubly-degenerate Tamm plasmon polariton modes has been designed and optimized to manifest three strongly coupled modes. The exotic dispersion of these supermodes is used to design a self-referenced spectroscopic refractive index sensor at optical frequencies with a substantial sensitivity value of 1410 nm RIU−1. The same structure is also shown to function as a singular-phase-based refractometric biosensing platform with multiple near-singular points, exhibiting a maximum sensitivity of around 27 000∘ RIU−1 with a sufficiently broad dynamic range of operation. Furthermore, the presence of three near-singular points provides the necessary flexibility in striking an appropriate balance between sensitivity and dynamic range of operation. The concomitant existence of the mentioned functionalities is an outcome of the strong coupling between the modes, which enables us to exhibit exquisite control over the dispersion of the supermodes. These distinctions enable our proposal to be of direct utility in highly demanding point-of-care biosensing applications.