bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characterization of Biopolymer Blend-based on Alginate and Poly (vinyl Alcohol) as an Application for Polymer Host in Polymer Electrolyte
Authors: Ghazali N M , Mazuki N F , Samsudin A S 
Published: March 2021

Abstract
In the present work, alginate (Alg) blend with polyvinyl alcohol (PVA) with various compositions were prepared by using solution casting method. The intermolecular interaction occurred in the polymer blends were investigated via Fourier Transform Infrared (FTIR) spectroscopy. Electrical impedance spectroscopy was used to determine the conductivity values of the blends. The conductivity value of Alg-PVA polymer blend was found to be optimum at 7.52 x 10−8 S/cm for composition with 70:30 of Alg:PVA. Based on the findings, it is believed that the Alg-PVA blend is a promising candidate to be act as polymer host materials for application in polymer electrolyte system.
Eco-Ontology for supporting Interoperability in Product Life Cycle within Product Sustainability
Authors: Mohammed M , Romli A , Mohamed R , Noormazlinah A 
Published: March 2021

Abstract
Ontology originated in a branch of artificial intelligence and widely used in various fields such as semantic web, engineering systems, software engineering, biomedical informatics, library science, information engineering, knowledge management, decision-making system, and the industry sector. Ontology supports the knowledge management system and helps get significant features of product design. The lack of using knowledge is the critical challenge in information interoperability of the manufacture, especially, in the early stage of design. This information must be gathered, stored, shared, reused, and managed in a consistent and standardized way. The aim of this study is to use the ontology for reducing the complexity of information and increasing its organization, facilitating sharing and reusing of information, and improving its accuracy. The use of ontology has shown optimistic results to support comprehensive decisions in the industrial field. The researchers have confirmed the importance of using the ontology to improve interoperability over the product life cycle and address the impacts of products through the outputs of the product life cycle assessment tool. This study is expected to contribute to develop an efficient and practicable sustainability tool during product design with a complete view to solve the lack of sharing information in the product life cycle, provide high quality and comprehensive recommendations to support the manufacturing processes for product sustainability.
M-Learning in Promoting Green Building Awareness in Palestine
Authors: Mouzaneh M , Harun Z , Jamil N 
Published: March 2021

Abstract
Most Palestinians have yet to have the urge to participate in green building practices. To enhance green building education in Palestine, we built a mobile application named “Let’s Go Green” to deliver awareness and incorporate green building technologies. In order to validate the mobile learning (m-learning) effect, we have conducted separate measurements by using ARCS motivation model and paper-based quiz among 80 engineering and architecture students in Hebron, Palestine. The students were split into two groups; group A (experimental; applied m-learning method) and group B (control; adopted conventional lecture note method). This study has three important findings (1) m-learning users found to have stronger learning motivation than those who used the conventional lecture note; (2) m-learning users generally exhibited better learning effectiveness than non-users; (3) the m-learning was found to be attractive to the students, implying that it can be an important content for educational and leisure for green building education. The findings demonstrated that the Let’s Go Green Application is an effective instructional material to improve students’ knowledge on green building. This application can be downloaded for both smartphones; Android, and iPhone. These functions have not been implemented yet, therefore this is the first attempt of such an approach.
Moisture content and mechanical properties reduction of hard capsules upon prolong drying process
Authors: Aiman Hamdan Mohd , Hikmah Sulaiman Nur , Najwa Mohd Amin Khairatun , Adam Fatmawati 
Published: March 2021

Abstract
Drying is a traditional preservation method to control the properties and quality of pharmaceutical product such as hard capsule. In this study, carrageenan and nanocellulose (NC) solution were mixed with crosslinker and toughening agents in the formulation solution and dipped for hard capsule formation. The dipping bar was dried at different drying times from 40-60 minutes in an oven. The properties of carrageenan hard capsule were compared with commercial hard capsule materials which were gelatine and hydroxypropyl methylcellulose (HPMC). Prolong drying time decreased the moisture content and hydroxyl group absorbance of carrageenan hard capsule up to 20 % and 2%, respectively. The mechanical properties of the hard capsule sample reduced about 19.2 % due to reduction of intermolecular interaction between carrageenan, crosslinker and NC. Increment drying time leads to tissue shrinkage in carrageenan hard capsule thus collapse the biocomposite structure and mechanical properties. Gelatine and HPMC hard capsules had lower moisture content and higher mechanical strength and thermal properties as compared to carrageenan hard capsule. As the drying time increase, case hardening phenomena collapses the structure and change the structure chain in the biocomposite.
Effect of Different Treatment Methods on the Purification of Bacterial Cellulose Produced from OPF Juice by Acetobacter Xylinum
Authors: Athirah Raihana Nor Aziz Hashim Nurul , Zakaria Junaidi , Mohamad Shahril , Fathiyah Sy Mohamad Sharifah , Ab. Rahim Mohd Hairul 
Published: March 2021

Abstract
Bacterial cellulose (BC) is a form of cellulose produced by Acetobacter xylinum via fermentation process. BC contains impurities such as medium broth or the cell biomass. This study aims to determine the effect of purification method on the BC produced from oil palm frond (OPF) juice. Three purification method was presented in this study; first, BC was treated with different NaOH concentration at constant temperature of 70°C. Second, the BC was treated with different temperature while the NaOH concentration was fixed at 0.1M. Lastly, the BC was further purified in distilled water at different temperature. Fourier transform infrared spectroscopy (FTIR) and field emission scanning electron microscope (FESEM) analysis revealed that chemical composition of BC is similar to the natural cellulose without the present of biomass impurities as no peak at 1800 – 1500 cm−1 can be detected. Higher percentage for loss of biomass, 22.03 % can be obtained when the BC was treated with 1.0 M NaOH at 90°C and further purified in distilled water at 90°C. As conclusion, pure BC which are free from any impurities can be obtained by using proposed method.
Biosynthesis of SnO2nanoparticles by aqueous leaves extract of Aquilaria malaccensis (agarwood)
Authors: Buniyamin Irmaizatussyehdany , Md Akhir Rabiatuladawiyah , Asnida Asli Noor , Khusaimi Zuraida , Rusop Mahmood Mohamad 
Published: March 2021

AbstractBiosynthesis of tin oxide nanoparticles (SnO2NPs) was cost-effectively carried out in non-toxic aqueous mixture ofAquilaria malaccensis(agarwood) leaves extract and tin (IV) chloride pentahydrate solution at room temperature. The synthesized SnO2NPs were characterized by using Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), energy dispersive X-ray analysis (EDX) and UV-visible diffuse reflectance spectroscopy (DRS). The results from FT-IR spectra ofA. malaccensisleaves shows the presence of functional groups of polyphenolic from bioactive compounds which act as the template for reducing and capping agents during the synthesis activity. The structural properties of the obtained nanoparticles are studied using X-ray diffraction, which indicates that the crystallite size are 6.3 and 3.4 nm for sample synthesized from extract of fresh and old leaves respectively. The morphology of the nanoparticles shows uniform distribution of agglomerated spherical nanoparticles. DRS absorption spectrum indicates the band-gap for both samples 3.23 and 3.35 eV respectively. The green synthesized SnO2NPs is suggested may play forthcoming significant roles in catalysis and optoelectronic devices.
Optimization of Pomelo juice Citrus maxima (Burm.Merr.) Vacuum Concentration by Response Surface Methodology in Pilot scale
Authors: Tran T Y N , Dao T P , Nguyen P T N , Pham T N , Huynh B L , Mai, H C , Huynh X P , Tran T T 
Published: March 2021

Abstract
Because of its healthful nutritional properties, pomelo is gaining traction in the food and beverage industry. Pomelo juice concentration as a beverage provides vitamins, antioxidants, and energy. The Design Expert 11 calculation software is used to optimize the concentration process parameters, the temperature range is determined to include ± a values converted as axial. The results showed a positive correlation between the two factor variables and the obtained target function (TPC), the optimal value for the selected procedure was based on 79 °C with a time of more than 1.78 hours. At this point, TPC retention is 71.121%.
Activated Carbon based Rice Husk for Highly Efficient Adsorption of Methylene Blue: Kinetic and Isotherm
Authors: Tan T V , Nguyen H T T 
Published: March 2021

Abstract
Agricultural waste is a resource that is renewable and readily available and is used as a precursor to coal synthesis in industry. In this study, agricultural waste from rice husk was used as precursors to prepare activated carbon, which was activated by KOH. The effectivity factors including time contact, concentration, pH solution, and sorbent dosage play an important role in removing MB in water media. Moreover, the MB adsorption efficiency reached over 80 % at a concentration of 50 mg/L, pH 8 within 180 minutes. The kinetic analysis via pseudo-first-order, pseudo-second-order, Bangham, and Temkin model showed that MB adsorption followed pseudo-second-order (R2 = 0.99934). The fitness of equilibrium data to popular isotherm equations such as the Langmuir, Freundlich, Elovich, Temkin and Dubinin-Radushkevich were carried out. Among all tested isotherm models, Langmuir model is the best fitted to equilibrium data (R2 = 0.99924). The results of this study show that activated carbon made from rice husk has the potential to be used to remove the dye in wastewater treatment.
Biochemical Characteristics of small shrimp (Acetes japonicus) of varied sizes collected in Ben Tre Province, Vietnam
Authors: Ung T D , Tran T Y N , Nguyen N L , Phan D A , Tan L V 
Published: March 2021

Abstract
Small shrimp (Acetes japonicus) is a common ingredient in various dried and fermented dishes on Asian countries. In this study, we explored the nutritional qualities of small shrimps with respect to their body length. The shrimp materials were harvested from near-shore waters of Ben Tre province, Vietnam. Various measures including mineral, lipid, salt and astaxanthin content of small shrimps of three size groups including small, medium, and large were evaluated. Current results indicate high salt content of small, medium, and large shrimp, at 23.74 ± 0.01, 24.09 ± 0.01, and 27.97 ± 1.38 mg/g dry basis, respectively. The mineral content seemed to be irrelevant to body size. Large and medium shrimps showed higher lipid content than the small counterpart. However, small shrimps are advantageous in terms of astaxanthin content. Further studies should contemplate nutritional quality with respect to harvest area and dietary scheme.
Carboxymethyl Jackfruit Seed Starch: synthesis, characterization, and influence of reaction parameters
Authors: Van C K , Nguyen P N T , Tran T Y N , Mai H C , Tran T L , Nguyen T Q 
Published: March 2021

Abstract
Carboxymethyl jackfruit seed starch (CMS) was synthesized under different reaction conditions. The influence of sodium hydroxide concentration, monochloroacetic acid (MCA) concentration, IPA-water ratio, solvent-starch ratio, reaction time, and temperature were evaluated for degree of substitution (DS). Results have shown that the optimal DS of 0.68 was obtained at 50 °C, 90 minutes in solvent-starch ratio and isopropanol-water were 8:1 and 10:0. The ratio of sodium hydroxide and monochloroacetate acid moles to anhydroglucose unit (AGU) moles for the optimal DS were 1 and 1. Scanning electron microscope (SEM) of CMS particles showed the starch grain structure remains the same but the surface appeared many alveolar holes and no longer smooth as MS. Fourier transform infrared spectra (FTIR) of CMS and MS confirmed that carboxymethylation takes place on native starch molecules when the absorption band appears at a wavenumber of 1643 cm−1 corresponding to the vibrations of featured functional C=O group in CMS structure.
The major and minor components of Kaffir Lime (Citrus hystrix DC) essential oil in the steam distillation process
Authors: An T N T , Ngan T T K , Van C K , Anh H L T , Minh L V , Ay N V 
Published: March 2021

Abstract
Essential oils are natural products used in many fields, including perfumes, cosmetics, aromas, spices and nutrition. Kaffir Lime (Citrus hystrix DC), which belongs to the Rutaceae family, is a prominent tree in the southwest region, particularly in An Giang province (Vietnam). Moreover, Kaffir Lime is known as a potential candidate for aromatherapy and cosmetics, a natural alternative for insect repellents, an antioxidant and spice for food. Therefore, the purpose of this study is analyze the phytochemical content of Kaffir Lime essential oil using the steam distillation method. The process of steam distillation was conducted by continuously applying heat onto 500 g of imported Kaffir Lime peels. After 15 min of condensation, the yield of essential oil extraction achieved 1.6%. The essential oil was primarily composed of monoterpene hydrocarbon, aldehyde and ester with sabinene (22.875%), (3-pinene (33.939%), D-limonene (15.847%) and P-citronellal (14.791%) being the main components. Other ingredients included a-pinene (3.099%), (3-myrcene (0.836%), eucalyptol (0.354%), y-terpinene (0.476%), 4-terpineol (2.246%), a-terpineol (1.426%and linalool (1.139%). The presented extraction process as well as phytochemical profiles of Kaffir Lime suggested further studies on potential bioactivities of these constituents.
Utilization of Central Composite Design in Optimization of Microbial Growth Inhibition using Ananas Comosus Leaves Juice
Authors: Ya’acob A , Zainol N 
Published: March 2021

AbstractMicrobial growth inhibitors have been very effective for the prevention of disease transmission and infection. For this study, pineapple (Ananas comosus) leaves juice (PLJ) was use as microbial growth inhibitor (MGI) because of its higher phenolic content. Microbe from contaminated pineapple leaves was use as tested microbe. The selected operating conditions in this study were temperature and microbial inhibition time with the range between 35 to 39 °C and 10 to 50 min respectively. Microbial growth inhibition experimental design set-up was constructed using Design Expert software (Version 7.1.6) to analyze the condition required. The experiments was conducted according to the central composite design (CCD) in two variables of the surface response methodology (RSM) to determine the optimum conditions for inhibiting microbial growth. Quadratic polynomial model was constructed to predict the microbial growth inhibition. A quadratic polynomial model was generated to predict microbial growth inhibition. Microbial growth inhibition was measured using the method of colony formation unit (CFU) counting. The RSM result showed that microbial inhibition time had a major impact on inhibition of microbial development. The optimum conditions were 37 °C and 34.25 min with a 94.73% microbial growth inhibition. In this condition, microbe growth was predicted to be at a minimum rate due to inhibition of the phenolic compound in PLJ. The optimum state of this study will be useful for the use of PLJ in pineapple plantation.
A New Tool to Solve Machine Learning Problems under Intuitionistic Fuzzy Sets
Authors: Saraswat R. N. , Gahlot Sapna 
Published: March 2021

Abstract
The focus of this manuscript is to develop fuzzy new information measure for IFSs, and we proved the reliability and validity of the introduced measure. There are many applications of divergence measures in machine learning are discussed by various well-known authors and researchers in the literature of Information Theory, Mathematics, Computer Science other branches of engineering. Here, proposed a new information and fuzzy divergence measure along AIFSs. Properties and their validity, we proved of the established fuzzy information and divergence measure in terms of fuzzy. Using similarity information measure under AIFSs, we shown the applications to deal the machine learning cases for real life problems or case study and justify by numerical illustrations and we also shown the comparisons along with other measures.
SRGM using Testing-Effort Function with Uncertainty in Operating Environment
Authors: Dhaka Ramgopal , Pachauri Bhoopendra , Jain Anamika 
Published: March 2021

AbstractWith increasing pace of technological advancement and new tech introduction in today’s word, reliability of the software has become vital. For software reliability assessment, many software reliability growth models (SRGMs) have been discussed. In literature, many of the existing SRGMs have considered uncertainty of the operating environment but very little work has included testing effort function (TEF) with uncertainty in operating environment. In this research, an SRGM incorporating Gompertz TEF has been investigated with the uncertainty of operating environment. Software testing environment is usually a controlled one with variables known to the developer, but operating environment may introduce uncontrolled and unknown variables. This model has considered a constant fault detection rate in perfect debugging environment. Further, sensitivity analysis has been done. The numerical results have been compared with existing SRGMs.
Text Summarization Techniques and Applications
Authors: Dehru Virender , Tiwari Pradeep Kumar , Aggarwal Gaurav , Joshi Bhavya , Kartik Pawan 
Published: March 2021

Abstract
A person does not need to go through pages of articles for a given topic to understand the gist; a mere summary is more than sufficient in many cases. This has given rise to many apps that crunch through hundreds of articles to generate a personalized feed of summaries that a user can go through. With more and more people having access to the internet, lots of information is being created and shared online. This gives us the luxury of having it just a click away from consumption. However, not all of this information is filtered and cleared from the noise. This work aims to explore different techniques of text summarization and evaluate them on different parameters such as the extent of compression/summarization, retention of meaning/gist, and grammatical errors.
A Study on Sentiment Analysis of Mental Illness Using Machine Learning Techniques
Authors: Tiwari Pradeep Kumar , Sharma Muskan , Garg Payal , Jain Tarun , Verma Vivek Kumar , Hussain Afzal 
Published: March 2021

Abstract
In the digital age, social media plays a crucial role in society. Social media provides a platform to youth for exchanging their views on public issues and express their personal issues. Hence online media can be used for studying the behavior of people. Applying sentiment analysis on the data obtained timely from social networking sites (here Twitter), depression, anorexia, and other similar mental illness can be predicted among youth. The importance of detecting depression is that it is the root cause of a plethora of diseases. Early prediction can also mitigate the number of suicides. This work is to detect depression and PTSD (Post Traumatic Stress Disorder) among the Twitter users. Analysing the tweets, how likely a person is to suffer from any of the aforementioned diseases can be discovered.
A Review on Recent Trends in Secure and Energy Efficient Routing Approaches in Wireless Sensor Networks
Authors: Sharma Vivek , Bhatt Devershi Pallavi 
Published: March 2021

Abstract
The development in technology has resulted in development of multifunctional, small, lower priced, lower power consuming and multifunctional sensor nodes in wireless sensor networks (WSNs). The factors considered in design of the nodes are scalability, energy consumption, transmission range, environment etc. These nodes carry out activities like sensing, processing, information transmission and communication. The most of battery consumption is done by transmission of signals during communication process. So, saving energy is a foremost factor in the WSN. The routing scheme is extremely important for appropriate delivery of packets. This paper presents a review on some energy efficient routing protocols which are considering security measures as well, to improve security of nodes in WSN and targets to design approaches that needs less energy consumption during communication.
Retinal Microaneurysm Detection by CNN
Authors: Deepa R , Narayanan N K 
Published: March 2021

Abstract
Diabetic Retinopathy (DR) is a fast-growing retinal disease happens as a result of exponential growth in sugar level in blood which diminishes eyesight. The severity level identification of this eye disorder is performed by ophthalmologists due to scarcity of good software for finding DR. The initial stage of diabetic retinopathy is identified by the presence of microaneurysm. This paper conducts the initial phase detection of the disease by using Convolutional Neural Network (CNN). For conducting experiment DIARETDB1 dataset used. The images from the database are resized as a preprocessing step then automatic feature extraction done by the simple CNN used. By performing training, the CNN network classifies images with and without disease. The Sensitivity, Specificity and Accuracy obtained by the technique explained is 97.62%, 100% and 97.75%.
Automatic Prediction of Road Angles using Deep Learning-Based Transfer Learning Models
Authors: Sharma Sparsh , Jhaketiya Vinit , Kaul Ajay , Raza Abrar Ahmed , Ahmed Suhaib , Naseem Mohd. 
Published: March 2021

Abstract
The construction of robust and complex roads requires a considerable amount of resources, time, and effort. These efforts get manifold, especially when a road is to be constructed on rugged terrains. The use of Artificial Intelligence (AI) can be seen in almost all the research sectors. The efforts and the cost involved in road construction can be reduced by the induction of AI-based techniques for the estimation of road construction-related parameters that are required to predict the tentative cost incurred in the whole road construction project. In this article, the angle, which is one of the crucial parameters that aids in estimating the total cost and time required for the whole road construction project is predicted using the variation of three transfer learning-based deep learning models viz. VGG-16, DenseNet-121, and DenseNet-169. The proposed VGG16 based CNN model performance is computed and compared in terms of the evaluation metrics like Mean Square Estimation (MSE), Mean Absolute Error (MAE), and Correlation Coefficient (R2). Based upon the simulation results conducted, it was observed that VGG-16 has yielded road angles with less difference error.