bluuebunny/crossref_metadata_2025 huggingface dataset:
Chemical Composition, Distribution and Morphology of Beranang Laterite and Granite Aggregate
Authors: Hasan Nasiha Muawiya , Ariffin Afiq , Wahida Kamaruzaman Norul
Published: March 2021

Imbalance ecosystem due to massive construction projects taken by the government and developers need to be tackled seriously. Replacement on the construction material nowadays become a trend in solving the part of the issue or as a whole. Investigation on the most popular concrete material, concrete need to be done properly in order to find potential replacements especially on the aggregate as it takes approximately 60 to 70 % of concrete constituents. Laterite aggregate seems to have the potential as it is abundantly available in most region in Malaysia. This paper presents the chemical composition, distribution and morphological study on the Beranang laterite aggregate as compared to granite aggregate. The size use in the study is 20 mm maximum. The aggregates were subjected to, chemical elements, chemical elements distribution and the morphology analyses. From the results, it can be discussed that the main compositions such as carbon, silica, and oxygen were detected on the surfaces of both aggregates with similar peaks trend. Furthermore, the structural and morphology of both aggregates were also similar. In conclusion, based on the experimental carried out, Malaysian laterite aggregate has the potential to be acted as coarse aggregate in concrete mix. However, further experiments must be conducted to investigate the physical properties of it.
Experimental and simulation of aerodynamic performance of the small-scale wind turbine blades for usage in Malaysia
Authors: Jamil T A M T , Roslan S A H , Rasid Z A , Hassan M Z
Published: March 2021

The enormous growth in manufacturing technology has contributed to the global climate change as well as the extinction of the conventional energies. The effort of replacing these energies with renewable energy found that the energy return of investment is high for wind energy. While the required minimum wind speed for operating efficient wind turbine is 3.5-7 m/s, certain locations in Malaysia meets the requirement for implementing the wind turbine. In this paper, a comparison is made between two wind turbines with equal blade length: the first turbine blade (TB1) does not use any airfoils while the second turbine blade (TB2) applies airfoils of SG6042, NACA4412, NACA5510 after undergoing shape optimization process. Both blades were fabricated using a 3D printing machine. Aerodynamic performances of the TB1 were studied through experimental work i.e. the turbine blade was given wind, flowing at several speeds in a wind tunnel. For the TB2, Q-blade software was used for conducting the shape optimization process and determining its aerodynamic performances. It was decided to use several airfoils throughout the blade length of the TB2. Experimental work was also conducted on the TB2 similar to the TB1. Analysis from Q-blade software showed that TB2 produces power efficiency of around 40%. It was found from the experiment that the TB2 gives twice amount of power compared to TB1.
Studying the possibility of algorithmic compensation of temperature instrumental errors of string accelerometers as a composition of a strapdown inertial unit
Authors: Dmitry Gennadievich Allenov , Lazarenko S.V. , Lazarenko O.I. , Ghorbani Siamak
Published: March 2021

The article is devoted to the study of temperature errors of the string accelerometer used as part of a strapdown inertial unit. One of the main tasks facing the development of string accelerometers is the problem of compensating temperature effects to eliminate the resulting errors. One of the methods to solve such problems is to provide compensation for changes in the parameters of the string accelerometer, to level the appearance of the instrumental error in measuring the acceleration in the output signal of the device. On the prepared bench base at Scientific and Production Association of Measuring Technology (AO NPO IT) for setting up and conducting experiments, a study of string accelerometers, which are part of the strapdown inertial unit, was carried out. The study consisted of collecting output information from the device during its temperature calibration. During the experiment, the strapdown inertial unit was oriented in space so that its measuring axes of the accelerometer channels were directed alternately vertically upward or vertically downward with a smooth temperature change. The data obtained were analyzed to determine the dependence of the change in the initial vibration frequency of the string accelerometer and the design parameter of the accelerometer on the temperature in the operating temperature range of the device. An assessment of the possible level of efficiency of algorithmic compensation for changes in the accelerometer parameters was also shown. The studies carried out have shown the possibility, due to the algorithmic compensation of the temperature instrumental errors of one-component string accelerometers, to provide the accuracy requirements for the linear acceleration sensor channel of the strapdown inertial unit device in the operating temperature range. In particular, the use of algorithmic compensation for the temperature error of the initial frequency of the accelerometer f
0 reduced the absolute value of the parameter change by more than two orders of magnitude, and the maximum value of the error in approximating the change in the design parameter k from temperature is an order of magnitude less than the value before algorithmic compensation.
Comparison between lignin extraction by alkaline and ultrasound-assisted alkaline treatment from oil palm empty fruit bunch
Authors: Sultana Toma Farhana , Jemaat Z , Beg M D H , Khan M R , Yunus R M
Published: March 2021

Lignin is the second most abundant terrestrial biopolymer after cellulose and is the largest renewable source of aromatic groups in nature. In this work, the study was carried out on the selective extraction of lignin from oil palm empty fruit bunch (OPEFB) using alkaline and ultrasound-assisted alkaline methods. OPEFB is available in high amounts as solid waste of palm oil industries, which is considered as lignocellulosic and has fairly high lignin content. The pretreatment of OPEFB for lignin production depends on the effect of particle size, liquid to solid ratio, the concentration of NaOH, reaction temperature, type of solvent, and sonication time. OPEFB was treated with 7.5%, 10%, and 15% NaOH at 900C for 1.5h without ultrasound irradiation and with ultrasonic time for 10, 20, 30, and 40 min. Extracted lignin was characterized by FT-IR, UV-Vis, TGA, and elemental analysis. Considerably improved results were obtained by using the ultrasound-assisted time for 30 min. The percentage yield and purity of lignin extracted by the ultrasound-assisted alkali method was higher than that lignin fraction which was achieved by the alkali method, and their purity was improved with the addition of sonication time from 10 to 30 min.
Evaluation of Improved Mode Shape Curvature-Based Damage Detection using Robust Regression Method
Authors: Man M H C , Amiruddin M A , Fawazi N
Published: March 2021

Structural Health Monitoring (SHM) is an important tool to maintain structures integrity and safety. Gapped Smoothing Method (GSM) is a high sensitivity algorithm for damage detection using mode shape curvature (MSC) to identify small size of damage. However, it has limited capability to localize wide size of damage with decent accuracy. The objective of this study is to improve GSM algorithm using Robust Regression i.e., Iteratively Re-weighted Least Square (IRLS) methods. Subsequently, evaluate the proposed algorithm’s capability to localize damage with different size and number of measurements of an aluminum beam numerically. Damage Estimate Reliability (DER) was used to evaluate effectiveness of the improved GSM algorithm. The obtained result shows inclusion of robust regression in the original GSM algorithm increase Damage Estimate Reliability (DER) for 50mm damage size with damage level 20% by 11.6%. IRLS reduces influence of an outlier towards estimation of undamaged MSC that cause noise around damage area (in damage index plot) therefore produce more accurate estimation of damage size. Improvement of GSM allows this method to localize different level of damage in structures.
Vibration Response Analysis of a Structural Metal Mild Steel under the Effect of Crack
Authors: Ahmed N , Mamun M , Ahmed A
Published: March 2021

When a crack is present in a structure then the probability of failure of that structure is higher. Failure occurs when the natural frequency of the periodic force and the natural frequency of the structure are in a state of superposition. To avoid this phenomenon, it is essential to calculate the natural frequency. The aim of this study is to analyze the behavior of natural frequency for different parameters such as crack position, crack depth, crack opening and mesh sensitivity. In this study, the first five modes of vibration of both cracked and uncracked I beam has been extracted. A further analysis of resonance for a fixed vertical load has also been done. An amalgamation of hexahedral and wedge elements has been used to study the behavior of the cracked structure. As this is a problem of discontinuity, thus it is very troublesome to make a solution analytically. Therefore, ‘ABAQUS CAE’, one of the most popular finite element analysis software, was used for the analysis of cracked structure. The discoveries of this examination are that the presence of crack decreases the natural frequency of the beam, this decrease is identified with the position of the crack, its opening and its depth. Another finding of this examination is that the impact of vibration is huge for I beam when the break arrives at its web segment. It was also discovered that resonance happens before if the crack profundity is bigger or the existence of the crack is nearer to the fixed end.
Experimental analysis the effect of end mill flutes on delamination in milling of synthetic FRP composite
Authors: Ling M C H , Haliah N H , Tan C L , Azmi A
Published: March 2021

Fibre reinforced polymer (FRP) composites often employed the milling process to achieve the final geometrical shapes and dimensional tolerances. However, the random variations material properties and abrasiveness of FRP composite make the milling process become a challenge. An experimental approach has been committed in this study to analysis the effect of tool geometry in end-milling on unidirectional FRP composites with its machinability indices. The experiment methodology was conducted by altering the cutting tool geometry (number of flutes) and types of reinforcement fibres. Overall, the milling experiments induced various damages on FRP composite such as fibre pull-out, delamination and epoxy matrix interfacial de-bonding are associated to the rapid deterioration of tool sharpness. Besides that, the performance of four flutes end mill tool is distinguished with better surface finish when machining across carbon fibre orientation under same spindle speed and feed rate. This is likely due to the tool engagement during cutting process and nature properties of carbon FRP composite.
Effect of Annealing Temperature on the Crystal and Morphological sizes of Fe2O3/SiO2 Nanocomposites
Authors: Hassan Y M , Zaid H M , Guan B H , Hamza M F , Adam A A
Published: March 2021

Annealing the synthesized materials at different temperatures is very significant in ensuring the complete removal of the impurities during the particle formation process. Recently, nanocomposites material has shown reasonable outcomes and performed exclusively over bare single nanoparticles (NPs) in various fields of studies. In this paper, the composite of Fe2O3/SiO2 nanomaterial was synthesized via a Sol-gel auto-combustion method with aid of organic precursors. The material was synthesized at various concentrations and annealed at different temperatures. Characterization of the composite material was done by analyzing crystal structures, elemental composite distributions, morphologies, and chemical compositions via X-Ray Diffraction (XRD), Energy dispersed X-ray (EDX), Field Emission Scanning Electron Microscopy (FESEM), and Fourier-Transform Infrared Spectroscopy (FTIR), respectively. The chemical interaction between amorphous silica and iron oxide nanoparticles has been established due to the manifestation of the characteristic wavelengths corresponding to the linkage bond between the amorphous silica and iron oxide nanoparticles. The FESEM imaging revealed that the morphological size increased significantly with an increase in temperature. Furthermore, in the XRD experiment, it was found that increasing the temperature has significantly improved the crystal properties of the composite material. Hence, annealing temperature can serve as a reliable method that can control the morphological size and crystal structure of the materials
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

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

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

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

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

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

Biosynthesis 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

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

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

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

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

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

Microbial 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

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

With 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

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

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

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

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

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.
Survey Paper on Visibility Restoration of Underwater Optical Images and Enhancement Techniques
Authors: Saxena Khushboo , Gupta Yogesh Kumar
Published: March 2021

We have investigated the problem of underwater hazy image enhancement and restoration in this paper studied. Underwater image processing has several applications in the field of oceanic research work and scientific applications such as archaeology, geology, underwater environmental assessment, laying of long distance gas pipelines and communication links across the continents which demand geo-referential surveying of the oceanic bed and prospection of ancient shipwreck. There are many difficulties for undersea optical imaging. To submerging a camera in underwater enough space is required. The maneuvering of the camera with the help from remote place or in person at the site is likewise a complex task. However, the major challenge is imposed by underwater medium properties. Underwater haze image enhancement has gained widespread importance with the rapid development of modern imaging equipment. Though, the contrast enhancement of single underwater hazy image is a cumbersome task for scientific exploration and computational application. At extreme depth, because of attenuation in light propagation, the underwater images are susceptible to inferior visibility.
Survey on Smartphone Securities
Authors: Vaishnav Pragya , Kaushik Manju , Raja Linesh
Published: March 2021

Recently Mobile data security has become a serious subject for everyone, who save their private and confidential data on mobile and perform financial transactions on the daily basis through their mobile. Mobile users are aware that their mobile data is no more secure after stealing their smartphone. 84% person wants advance mechanism for smartphone security so even after login the application, monitoring user can be possible throughout the session. Author conducted a survey on mobile security for 105 participants. This survey responses gave a clear out motive to do research on advance authentication method which is keystroke dynamics on smartphone.
Software Defined Networking: A review on Architecture, Security and Applications
Authors: Gaur Kuntal , Choudhary Pranjal , Yadav Priya , Jain Ayush , Kumar Pradeep
Published: March 2021

Throughout the development of the network, the Software Defined Networking(SDN) paradigm introduced the transition of conventional networks by decoupling the forwarding hardware from the network’s control logic. The SDN architecture enables networks to track traffic actively and detect threats to promote network forensics, alteration of security policy, and insertion of security services. We discuss SDN-related technologies in this paper. In particular, we are attempting to cover the key components of SDN: architecture, security, and its implementations hoping that our efforts will help researchers set relevant and practical directions for future SDN research. In a nutshell, this paper highlights the current and future directions for secured SDN.

This paper examines the architecture of SDN where we discuss the network-building methods that arise in the case of the network control being removed from the continuity with the purpose of planning. We further explore the need of guarding access, veracity, and confidentiality of the resources and data, coupled with the myriad security options available for SDN. Lastly, we discuss the diversity bestowed by SDN in different sectors.
Arbitrage-Type Trade Using Correlation Analysis
Authors: Dhyani Bijesh , Nigam Pushkar , Kumar Ankit , Kumar Abhishek , Venkatesan K , Ambeth Kumar V D
Published: March 2021

The prediction of the stock market was one of the greatest obstacles. Since there are many reserves whose values are extremely unpredictable, good returns from investment must be calculated and determined. We tried our best to address these challenges by picking an index (a collection of stocks in the same sector) and developed an arbitration style trading mechanism in which the leading stock of that index could be chosen by correlation analyzes and technical analyses. When people hear the trade in similarities, they will wonder of arbitration. And that’s why we’re dreaming about investing in arbitrage. Although this is not true: arbitrariness is when two entities that are similar or rather connected are out of whack. So, we will look at a stock and its index and they are not identical, so they’re never out of whack. There are rules to define the entries and exits in a chosen stock in the trading system. The additional advantage of this method is to forecast the movement of one stock using its relationship with another stock of the same index. Established method is split into two phases: stock correlation and technological analysis. Experiments between July 2017 and June 2020 indicate that the know-how could include an index and its entries and exits.
Second- and third-order optical susceptibilities across excitons states in 2D monolayer transition metal dichalcogenides
Authors: Lafeta Lucas , Corradi Aurea , Zhang Tianyi , Kahn Ethan , Bilgin Ismail , Carvalho Bruno R , Kar Swastik , Terrones Mauricio , Malard Leandro M
Published: March 2021

Semiconducting transition metal dichalcogenides have significant nonlinear optical effects. In this work we have used second-harmonic generation and the four-wave mixing spectroscopy in resonance with the excitons in MoS2, MoSe2, and WS2 monolayers to characterize the nonlinear optical properties of these materials. We show that trions and excitons are responsible for enhancing the nonlinear optical response and determine the exciton and trion energies by comparing with the photoluminescence spectra. Moreover, we extract the second- and third-order optical sheet susceptibility (χ
(2) and χ
(3)) across exciton energies and compare with values found in the literature. We also demonstrate the ability to generate different nonlinear effects in a wide spectral range in the visible region for monolayer MoS2, opening the possibility of using two-dimensional materials for nonlinear optoelectronic and photonic applications.
Magnetic diagnostics for magnetohydrodynamic instability research and the detection of locked modes in J-TEXT
Authors: HAN Dongliang , SHEN Chengshuo , WANG Nengchao , LI Da , MAO Feiyue , REN Zhengkang , DING Yonghua
Published: March 2021

Magnetohydrodynamic (MHD) instabilities are widely observed during tokamak plasma operation. Magnetic diagnostics provide important information which supports the understanding and control of MHD instabilities. This paper presents the current status of the magnetic diagnostics dedicated to measuring MHD instabilities at the J-TEXT tokamak; the diagnostics consist of five Mirnov probe arrays for measuring high-frequency magnetic perturbations and two saddle-loop arrays for low-frequency magnetic perturbations, such as the locked mode. In recent years, several changes have been made to these arrays. The structure of the probes in the poloidal Mirnov arrays has been optimized to improve their mechanical strength, and the number of in-vessel saddle loops has also been improved to support better spatial resolution. Due to the installation of high-field-side (HFS) divertor targets in early 2019, some of the probes were removed, but an HFS Mirnov array was designed and installed behind the targets. Owing to its excellent toroidal symmetry, the HFS Mirnov array has, for the first time at J-TEXT, provided valuable new information about the locked mode and the quasi-static mode (QSM) in the HFS. Besides, various groups of magnetic diagnostics at different poloidal locations have been systematically used to measure the QSM, which confirmed the poloidal mode number m and the helical structure of the QSM. By including the HFS information, the 2/1 resonant magnetic perturbation (RMP)-induced locked mode was measured to have a poloidal mode number m of ∼2.
Intra-annual Spatiotemporal Dynamics of the Monarch Butterfly (Lepidoptera: Danaidae), Regal Fritillary (Lepidoptera: Heliconiinae), and Their Floral Resources in North Dakota, United States
Authors: Antonsen Adrienne K , Kral-O’Brien Katherine C , Hovick Torre J , Limb Ryan F , Geaumont Benjamin A , Harmon Jason P
Published: March 2021

Many butterflies in the United States, along with their nectar resources, are declining. Large-scale conservation planning can be challenging, however, when butterflies and their nectar sources exhibit disparate spatiotemporal dynamics. We initiated a multi-year survey on monarchs (Danaus plexippus), regal fritillaries (Speyeria idalia), and floral resources across North Dakota from 2017 to 2019 to understand resource use through space and time. We surveyed three sites in each county in North Dakota, twice a year for 3 yr, for a total of 954 site visits. Our objectives were to 1) identify important floral resources for monarchs and regal fritillaries, 2) determine intra-annual spatial and temporal distributions of the butterflies and their nectar sources, and 3) quantify how floral resources influenced butterfly abundance and interacted with spatiotemporal factors (latitude, longitude, and flight season). Milkweeds (Asclepias spp.), native thistles (Cirsium spp.), and blazing stars (Liatris spp.) were identified as particularly important nectar resources for monarchs and regal fritillaries; all plant and butterfly species exhibited unique spatiotemporal distributions. Monarch abundance at a site was positively related to the availability of flowering milkweeds, and regal fritillary abundance was positively related to the floral availability of native thistles and coneflowers (Echinacea spp.). These relationships were consistent across the spatial and temporal extent of our study, indicating that the butterfly–flower relationships we detected are maintained and relatively consistent across our study region and years. By accounting for spatiotemporal dynamics, we can help elucidate the persistence of butterfly-flower species interactions at large scales and inform conservation efforts for these threatened species.
Novel Assertions: A Reply to Mahon
Authors: Dixon Daisy
Published: March 2021

In a recent paper, James Edwin Mahon (2019) argues that literary artworks—novels in particular—never lie because they do not assert. In this discussion note, I reject Mahon’s conclusion that novels never lie. I argue that a central premiss in his argument—that novels do not contain assertions—is false. Mahon’s account underdetermines the content of literary works; novels have rich layers of content and can contain what I call ‘profound’ assertions, and ‘background’ assertions. I submit that Mahon therefore fails to establish that novels never lie.
Invited Commentary: Toward Better Bias Analysis
Authors: Gustafson Paul
Published: March 2021

In this issue of the Journal, Lash et al. (Am J Epidemiol. 2021;190(8):1604–1612) show how some previously published bias analyses could have been better. In investigation of one of their examples, we add some thoughts about routes to better bias analysis, particularly via exploration of a joint distribution of bias parameters and target parameters.