bluuebunny/crossref_metadata_2025 huggingface dataset:
Harmonic Analysis of Multilevel H-Bridge Inverter with Reduced Switches for Solar Power Applications
Authors: Krishnan S. , Ravikumar N. , Thirumal P. , Balamurali R.
Published: January 2021

A multilevel H-bridge dc–ac converter is an electronic device, the multilevel converter enhanced stepped output with less switches. This paper deals with H-Bridge multilevel converter it requires only few switches when compared to traditional method. So in proposed method using
only few switches, and it requires less gate triggering circuit. Less switches will operates for certain period of time. The proposed circuit is simulated using MATLAB software in that fast Fourier transform test to find the total harmonic distortion. With the proposed method multilevel converter
can be used in solar power applications to convert dc supply into ac supply, it produces less harmonics it will enhance life span of the motor and efficiency of the motor will raise because in proposed multilevel converter there is a less switches are used.
Analysis of Electromagnetic Wave with Right Handed Meta-Material
Authors: Ezhilmaran M. , Vishnupriyan J. , Ettappan M. , Kirubasankar K.
Published: January 2021

In today’s modern world wireless and mobile devices have become almost indispensable. As a result human beings are constantly exposed to electromagnetic radiation emanating from these devices which can be harmful for the health. The effect of electromagnetic radiation is higher
when we are close to the radiating device, so it is important that a mechanism is developed that will reduce the effect of these radiations and analyze the electromagnetic waves. Finite Difference Time Domain (FDTD) is the effective method to simulate and analyze for positive refractive index
on Metamaterial. The simulation environment is Opti-wave used to design perfectly matched layer (PML) structure. The anisotropic and inhomogeneous electric permittivity and magnetic permeability of the right handed metamaterial are presented and transformed to fit the input requirements of
the applied finite element solver.
Artificial Intelligent Approach to Predict the Student Behavior and Performance
Authors: Srinivasulu Senduru , Saandeep Boppana , Yuva Vatikutti , Retna Raj R. Jeberson , Gowri S.
Published: January 2021

Presently a days Predicting understudy execution turns out to be progressively productive because the procedure enormous content of information in instructive databases. Numerous examinations are utilizing this idea and region of execution is as yet expanding bigger various models understudy
marks, participation, semester mark, grade focuses, situation, wellbeing, educational plan exercises, and so on. In late patterns the measure of information put away is growing quickly. The primary objective is to make an overview of “A savvy way to deal with foresee the understudy conduct
and execution” To build up a model to anticipate understudy Behavior and execution. The understudy execution in training is a significant job in instructive conditions. The put away database contains understudy data to improve understudy viewpoint and conduct. This paper show patterns
and sorts of dissect ought to be performed to improve the training process. We anticipated understudy subtleties and produce a report to the workforce and guardians. In light of the presentation, we offer answers to improve their exhibition. Foreseeing understudy execution turns out to be
all the more testing because of the enormous volume of information in instructive databases. This paper additionally centers around how the anticipated data can be utilized to recognize the most significant qualities of determination in understudy information. We could improve understudy accomplishment
and achievement more in an effective manner utilizing instructive information mining systems. It could carry the advantages and effects of understudy, teachers, and scholastic foundations.
Bio-Inspired Algorithms for Preserving the Privacy of Data
Authors: Menaga D. , Begum I. Humaira
Published: January 2021

Security of the data is also concerned with the privacy of the data since the data or the information can be easily disclosed. Data sharing also plays a key role in security. Recently, patterns are disclosed using associative rule mining and the sensitive information are one of the
imposing threats to the security aspects in data mining. Preserving the data as well as the privacy of the user using several PPDM approaches leads to provide authorized access for such sensitive information. The security threats for preserving privacy are provided by developing a sanitization
process. The sanitization process is considered to be one of the biggest challenges in the mining of data. In this paper, different approaches such as GA-based and PSO based algorithms are surveyed and analyzed for preserving the privacy of data. The purpose of data sanitization and the use
of Bio-Inspired algorithms such as Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are discussed.
Comparative Analysis Between Online and Offline Shopping Approach and Behavior of Consumers
Authors: Sharma Anmol , Sharma Avinash , Kaur Harpreet , Shafali
Published: January 2021

The intent of this study is to present a view of online shopping decision through compare the offline and online decision making. Shopper’s shop when and where they desire, where they are contented with the products and the preference of shopping. The present paper is highlights
the distinction among online and offline shopping approach and behavior of consumers of the study. Total 30 statements have been developed. Total 500 respondents have taken part in survey out of which 316 consumers preferred online shopping over offline shopping, whereas, 184 consumers preferred
offline shopping over online shopping. Descriptive statistics and t-test is used to examine if mean level of agreement or disagreement between online shoppers and offline shoppers is significant or not. As a result it has been found that response of online and offline shoppers varies
significantly for statements like online or offline Shopping saves time, online or offline shopping is convenient, It is safe to give out personal information, online or offline shopping provides overall adequate information, online or offline shopping provides the other required customer
services, online or offline shopping requires fewer efforts, online or offline shopping provides faster goods and services, online or offline Shopping avoids botheration, online or offline shopping offers prompt delivery of goods, online or offline shopping allows one to look for the best
price before purchasing, During online or offline shopping, one can touch the goods before I buy them, During online or offline shopping, once can try ortake demo of the product, online or offline shopping raises my prestige, I often buy things online or offline because it puts me in a better
mood.
()-Fuzzy Commutative Ideals in BCH-Algebras
Authors: Zulfiqar Muhammad , Azhar Fozia
Published: January 2021

The purpose of this paper is to introduce the concept of ()-fuzzy commutative ideal in BCH-algebra and investigate some of their related properties.
A New-Flexible Generated Family of Distributions Based on Half-Logistic Distribution
Authors: Al-Marzouki Sanaa , Alrajhi Sharifah
Published: January 2021

We proposed a new family of distributions from a half logistic model called the generalized odd half logistic family. We expressed its density function as a linear combination of exponentiated densities. We calculate some statistical properties as the moments, probability weighted moment,
quantile and order statistics. Two new special models are mentioned. We study the estimation of the parameters for the odd generalized half logistic exponential and the odd generalized half logistic Rayleigh models by using maximum likelihood method. One real data set is assesed to illustrate
the usefulness of the subject family.
QoS Enabled Task Scheduling Approach in Cloud Computing as Per Service Level Agreement
Authors: Banga Puneet , Rana Sanjeev
Published: January 2021

Due to constraints along with profit margins in background, service provider’s sometime neglect to feed essential services to their respective clients. Such compulsion raises the demand for efficient task scheduling that can meet multiple objectives. But without any prior agreement,
again makes a casual approach. So this dispute can be addressed when competent scheduling executes right over the Service Level Agreement. It acts as hotspots to define set of rules to assure quality of service. At this time, there is a huge demand of SLA opted scheduling that can produce
profitable results from provider’s and client’s as well. This article presents a fundamental approach that can be applied to existing scheduling techniques on the fly. Result shows drastic improvement in terms of average waiting time, average turnaround time without comprising
provider’s cost margin at all along with fairness.
A Topical Survey: Applications of Machine Learning in Medical Issues
Authors: Maharana Chapala , Mishra Bijan Bihari , Dash Ch. Sanjeev Kumar
Published: January 2021

Computational Intelligence methods have replaced almost all real world applications with high accuracy within the given time period. Machine Learning approaches like classification, feature selection, feature extraction have solved many problems of different domain. They use different
ML models implemented with suitable ML tool or combination of tools from NN (Neural Network), SVM (Support Vector Machine), DL (Deep Learning), ELM (Extreme Learning Machine). The model is used for training with known data along with ML algorithms (fuzzy logic, genetic algorithm) to optimize
the accuracy for different medical issues for example gene expression and image segmentation for information extraction and disease diagnosis, health monitoring, disease treatment. Most of the medical problems are solved using recent advances in AI (Artificial Intelligence) technologies with
the biomedical systems development (e.g., Knowledge based Decision Support Systems) and AI technologies with medical informatics science. AI based methods like machine learning algorithms implemented models are increasingly found in real life applications ex. healthcare, natural calamity detection
and forecasting. There are the expert systems handled by experts for knowledge gain which is used in decision making applications. The ML models are found in different medical applications like disease diagnosis (ex. cancer prediction, diabetics disease prediction) and for treatment of diseases
(ex. in diabetics disease the reduction in mean glucose concentration following intermittent gastric feeds). The feature selection ML method is used for EEG classification for detection of the severity of the disease in heart related diseases and for identification of genes in different disorder
like autism disorder. The ML models are found in health record systems. There are other applications of ML approaches found in image segmentation, tissue extraction, image fragmentation for disease diagnosis (ex. lesion detection in breast cancer for malignancy) and then treatment of those
diseases. ML models are found in mobile health treatment, treatment of psychology patients, treatment of dumb patients etc. Medical data handling is the vital part of health care systems for the development of AI systems which can again be solved by machine learning approaches. The ML approaches
for medical issues have used ensemble methods or combinations of machine learning tools and machine learning algorithms to optimize the result with good accuracy value at a faster rate.
Online Assessment System in Improving Programming Student Learning
Authors: Petrlik Iván , Rodriguez Ciro , Lezama Pedro , Inquilla Ricardo , Hilario Manuel , Vásquez Enma
Published: January 2021

In this work, research aimed to determine the influence of the design and implementation of an online evaluation system for student learning at a university in Lima. An online evaluation system with web technology was designed and implemented that is comprised of supervised and exercise
qualification exams, where students answer questions with the optional use of aids that allowed them to improve their results. It was worked with a population of 30 students of the Programming Language I subject to the Systems Engineering degree. The type of research was applied, and the design
was quasi-experimental, and an entry test (pre-test) and exit test (post-test) were also applied. Likewise, instruments such as questionnaires, evaluation form, and validity and reliability tests were used in each case that allowed to know the information of the respective work. The results
of the hypotheses indicate that there are significant differences in general learning, learning of conceptual, procedural and attitudinal content after applying the Online Evaluation System in the results of the input and output evaluation (p<0.05) the average of the Post Test being
higher (p = 0.000); therefore, it is concluded that the system improves the evaluation of declarative, procedural and attitudinal learning.
Analysis of Steady State Behaviour of Biserial and Parallel Queue Network Model with Batch Arrival
Authors: Gupta Renu , Gupta Deepak
Published: January 2021

The primary objective of the paper is to analyse a network queue model with two queuing subsystems commonly allied to a single server. The first queue subsystem consists of two biserial servers while the other subsystem consists of three non serial parallel servers. At biserial queueing
subsystem, the customers arrive in batches of fixed size from outside the system and individual arrival takes place at parallel subsystem. The input process is poisson and the service time distribution is exponential. Time independent solution and various queue characteristics have been calculated
using generating function technique and laws of calculus. Numerical illustration is provided to have clear understanding of the model.
Integration of PRESENT Cipher Model Using Bit Permutation in Wireless Sensor Network for Data Security
Authors: Tripathy Alakananda , Pradhan Sateesh Kumar , Nayak Ajit Kumar , Rath Smita , Tripathy Alok Ranjan
Published: January 2021

Security of data has become the biggest concern in recent years, due to the growing number of wireless networks. Accordingly, cryptography is becoming essential in improving data security. Encryption schemes that transforms the data into an incomprehensible shape. It plays an important
role in applications such as wireless sensor networks, as most of the data is transmitted through an unsafe channel. Ultra-lightweight cryptography is one the most preferable research areas which having significant contribution towards the security aspects. There is a low power block cipher
PRESENT. In this proposed work a PRESENT as reference block cipher is implemented. Here a method called PRESENT block cipher is used with key shuffling and S-Box. This method produces a 64 bits cipher text as result on input text of size 64 bits and key having of 128 bit. This developed method
gives better results in comparison to other existing cipher on performance on different hardware and software platforms. With less memory requirement it produces a higher accuracy and confidentiality of the message is maintained. The proposed cipher have the better encryption time, decryption
time, throughput. This proposed cipher has better resistance to crypt analysis according to avalanche effect. This proposed cipher can well be applicable for application where small traced area and low power decadence are vital design metrics.
Iterative Parametric Approach for Quadratically Constrained Bi-Level Multiobjective Quadratic Fractional Programming
Authors: Goyal Vandana , Rani Namrata , Gupta Deepak
Published: January 2021

The paper proposed an iterative parametric approach procedure for solving Bi-level Multiobjective Quadratic Fractional Programming model. The Model is divided into two levels-upper and lower. In the first stage of the approach, a set of pareto optimal solutions of upper Level is obtained
by converting the problem into equivalent single non-fractional parametric objective optimization problem by using parametric vector and ε-constraint method. Then for the second stage, the solution of upper level is followed by the lower level decision maker while finding solution with
the proposed algorithm to obtain the best preferred solution. A numerical example is solved in the last to validate the feasibility of the approach.
A Pragmatic Analytics of Covid Data Patterns for Predictive Mining of Patients
Authors: Walia Rubika , Oberoi Neelam , Sachdeva Sakshi
Published: January 2021

The year 2020 has emerged as a menace and threat for the human being whereby the social as well as professional livings getting affected. In the global perspectives, the human lives are affecting and huge demise occurring. In this research work, the effectual implementation towards
the usage of Artificial Intelligence is done with the machine learning so that the overall outcomes and predictive mining can be done with higher degree of performance. The work is having the integration pattern of COVID datasets of patients with benchmark characteristics and thereby to have
the predictions for the upcoming tests and by this way overall prediction can be done.
Multiclass Severity Classification for Software Bugs Using Support Vector Machine, K-Nearest Neighbor, Decision Tree and Naïve Bayes
Authors: Kumar Raj , Singla Sanjay
Published: January 2021

During the software development, all most 30–35 present cost is due to the testing. This means that if a bug travels from one phase to succeeding phases without detection, it will definitely increase the cost of the software development and due to this software quality may be
compromised. So use of the data mining algorithm for the software bug classification is highly appreciable. Bug severity may be categorised into S1, S2, S3, S4 and S5 categories, depending on the impact of the severity. In this paper, multiclass of bug severity is done using SVM, KNN, Decision
Tree and Naïve Bayes. Comparative analysis of these algorithms is done with respect to accuracy, precision, recall and execution time.
Energy Efficient Design on 16 nm Ultrascale Plus Architecture Using Static Probability and Toggle Rate
Authors: Pandey Bishwajeet , Tomar Geetam S. , Mohamed Rajina R. , Hussain D. M. Akbar , Pandit Amit Kant
Published: January 2021

Scientists in 2010 were using a 40 nanometer Process based FPGA called Virtex-6 and 45 nm Process Technology based FPGA called Spartan-6. After 2010, researchers shifted their focus towards 28 nm technology based 7 series FPGA (Artix-7, Kintex-7, and Virtex-7) due to their intrinsic
capability of low power consumption than both 40 nm and 45 nm technology based FPGA. In December, 2013, Xilinx introduced the 20 nm process technology based UltraScale series: Virtex UltraScale and Kintex UltraScale families. But now in 2020, researchers are using 16 nm technology based UltraScale+
FPGA. In our work, we are also using 16 nm technology based UltraScale+ FPGA for implementing our memory using VIVADO 2018.3 hardware programming tool and Verilog Hardware Description Language. There is 49.42%, 25.28% saving in design power on UltraScale+ FPGA when we minimize static probabilities
to 0.1 and 0.2 respectively.
Assistive Technology for People with Special Needs and Its Role in Enriching Arabic Grammar and Quranic Studies-Abd Allah Ibn Al-Husayn Ukbari as a Model
Authors: Sayed Mohamed Aziz Abdelmaksoud , Taher Rusdee , Madroh Muhammadmansour , Manzo Ousmane , Binmong Sorhibulbahree , El-Ebiary Yousef A. Baker
Published: January 2021

Assistive technology has an important role in helping people with disabilities, so what this technology can offer goes beyond simple help limits, is that it opens up broad prospects for a new lifestyle. Those with special needs have high concerns, strong wills, solid intentions and
creative minds, which Allah Almighty blessed them to encourage and satisfy their hearts. In the context of preface of the book “Nakt al-Humyān fī Nukat al-Umyān, (biographies of notable blind people, with a section on the causes of blindness).” Its writer Khalīl
ibn Aybak al-afadī (1296–1363) pointed out a saying, which has high value, deep impact, and significance tribute to people with special needs, where he said: “it's rare to see a blind man being a dull, inefficient, inactive but blind person only can be found as an intelligent,
smart and genius. “This research's title is “Assistive Technology for People with Special Needs and its Role in enriching Arabic Grammar and Qur'anic Studies (Abd All āh ibn al-usayn ‘Ukbarī as a model).” We will address issues of people with special needs
specially Abd Allāh ibn al-Husayn ‘Ukbarī as a model as he was blinded in his youth as he was hit by chickenpox. The research seeks to discuss the saying: “Although Al-‘Ukbarī was a handicapped person, but he had outstanding efforts and contributions in
enriching Arabic grammar and Quranic studies.” It (research) aims to explain the concept of assistive technology and people with special needs, also to know our duty towards them and to mention the most important and preferred effects of Al-‘Ukbarī. As well as clarifying
the most prominent features of Al-‘Ukbarī's curriculum in his grammatical works and highlighting his efforts in enriching Arabic grammar and Quranic studies.
Evaluating Drone Tension Release-Mechanisms for Consistency
Authors: Hertzog Pierre E. , Swart Arthur James
Published: January 2021

Monitoring of any kind requires consistency. Reliable and repeatable data must be obtained so as to ensure that any decision making process is well informed so as to prevent serious damage, loss or injury. Monitoring may also be used for quality assurance, where a specific technology
is tested repeatedly to determine if its performance remains consistent. The purpose of this paper builds on previous work by an innovative jig to evaluate a number of tension release-mechanisms from a variety of manufacturers in order to determine their operating limits and their subsequent
degree of consistency in performance. These tension release mechanisms are primarily used in fishing, where fishing bait attached to a fish line needs to be dropped at a specific location in the sea. An experimental study is conducted where quantitative data is collected of seven such mechanisms
obtained from different manufacturers. Each mechanism was tested 10 times with a given weight. Averages values are then calculated that relates to the required weight needed to activate the tension release-mechanism. A maximum deviation percentage from this average value is then calculated.
The Gannet range of mechanism performed the best, with accuracy levels above 95%. The worst performing mechanisms ranged in accuracy levels from 13.9% to 42%. Results do seem to indicate that a thicker fishing line with a heavier weight brings out the best performance in all the release-mechanisms,
as the level of accuracy increases for each increase in weight class. Consumers, or end-users, can make use of this information to select an appropriate release-mechanism that will satisfy their requirements for such a mechanism, be it casual or professional fishing.
Indian Engineering, Procurement, and Construction Companies: Which Non-Price Attributes Impact Their Willingness to Pay When Buying Switchgear?
Authors: Subramaniyan Anantharaman , Mittal Amit , Aggarwal Arun
Published: January 2021

This paper on industrial marketing, attempts to identify the non-price attributes (desired values) affecting the willingness to pay (WTP) of the Indian engineering, procurement, and construction (EPC) companies when buying medium- and high-voltage switchgears from manufacturers. A review
of literature until 2018, covering theoretical framework and empirical results in varied market environments was conducted. An initial experiential survey with 22 manufacturers was conducted to understand their business pain points with EPCs. To obtain a comprehensive list of the desired values
affecting EPC’s WTP, another experiential survey was conducted with both manufacturers and EPCs. The study revealed that insufficient price realization or low WTP was among the top three pain points. Further, in conjunction with literature reviews, the study revealed 10 major desired
values affecting WTP, offering manufacturers a reliable EPC value driver guide. A theoretical model on WTP was proposed by authors, setting out that WTP is impacted by customer satisfaction, and in turn by the perceived value, thereby contributing to the academic knowledge pool. As a scope
for further study, data may be collected from EPCs and statistically analyzed to understand the relative importance of these desired values and to verify if a higher perceived value translates to satisfaction and WTP.
A Novel Approach for Dimensionality Reduction and Classification of Big Data Using Meta-Heuristic Approach
Authors: Kaur Amrinder , Kumar Rakesh
Published: January 2021

User interaction over the internet is growing day by day. The social network users send massive information to the network to share with others on the network. This increases the information on social media, hence needed a mechanism to handle or manage such high dimensional data termed
as Big Data. Big Data reduction can be performed by using a feature selection approach. But, the Classification of such massive data is a challenging task for all the researchers. To overcome this problem, a metaheuristic based Genetic Algorithm (GA) for the selection of most suitable rows
which can be provided for training. The selected rows undergo a feature extraction process, which is attained by Principle Component Analysis (PCA). The extracted principle components are optimized using another meta-heuristic algorithm termed as Whale Optimization. As the proposed algorithm
uses unlabelled data, clustering is done to label the data. Two different distribution indexes were calculated for data with GA selected rows and data with GA selected rows along with PCA and whale. The distribution index is the ratio of a total number of elements in one cluster to a total
number of elements in the second cluster. High distribution index leads to better accuracy when it comes to classifying the text data. The data is clustered using the K-Means algorithm to find the cluster indexes. The proposed algorithm presents a hybrid classification mechanism with
upper and lower boundaries of classified labels using Artificial Neural Network (ANN) and Support Vector Machine (SVM).
Efficient Framework for Fully Automatic Test Case Generation and Prioritization Using Genetic Algorithm in Software Testing
Authors: Rani Seema , Kaur Amandeep
Published: January 2021

Automation in software testing is significantly growing in recent situation. Most part of the system is automated with help of the software. Today every modern software developers are trying to automate the software development process as much as possible. Therefore to develop any software
more skills and expertise are needed. For the software development process, testing of software is the exceedingly significant and considerable phase. Automatic test data generation had an essential function in specific area regarding software testing. Test case creation is technique of gathering
the data which completes the testing standards, all criteria’s and conditions. During testing process, the software goes through frequent modifications. As a result, due to all of these modifications and repetitive retesting the cost of testing process increases. This is called regression
testing. Regression testing requires more expertise, more effort, more time and more cost. Here to reduce the time and expenditure, many type of techniques are proposed. The changes in one test case will affect all the others test cases. To triumph over this problem, when the changes occurred
in the software every the test case have to be retested repeatedly. And this problem leads to make the testing process time consuming with unnecessary increased cost. Here In this research paper, the work’s focal point on automatic test cases generation and prioritization with improved
evolutionary genetic algorithm.
The Influence of Magnetic Fields and Heat and Mass Transfer on Peristaltic Flow Through a Porous Channel
Authors: Gafel Hanan S.
Published: January 2021

This paper discusses the effects of both magnetic fields and heat and mass transfer on the flows of a peristaltic nature with incompressible Newtonian fluid mechanics in a channel. The study was conducted under the assumption of a low Reynolds number and a long wavelength. The analytical
solution was deduced from velocity and temperature. The outcomes for velocity and temperature, presented analytically, were evaluated in a numerical form and discussed briefly. Non-dimensional wave amplitude impact, the magnetic field, Grashof number, and the volume rate of flow in the waveform
were analyzed theoretically and computed numerically. The expressions for velocity, pressure gradient, pressure rise, temperature, fractional force of the internal and outer channels, and shear stress were sketched for various embedded parameters; afterward, they were accordingly interpreted.
Results of a numerical nature were given and illustrated graphically in every case. The results acquired in the presence and lack of magnetic field were compared against each other. The outcomes imply that the effects of the magnetic field and heat and mass transfer were evident in the phenomena.
The effects of various involved criteria manifesting in the solutions were meticulously assayed.
Majorana Field Effect Transistor. Majorana Fermion Detection and Transport Properties
Authors: Costa Miraci S. , Beirão Antônio T. M. , da Silva Carlos A. B. , da Silva Shirsley J. S. , Nero Jordan Del
Published: January 2021

In this work we obtain analytically the transport properties as current and conductance in a toy model system formed by a quantum dot with a single level connected to a Kitaev chain deposited on a s-wave superconductor to identify the signature of Majorana zero modes (MZMs) called Majorana
Fermions in solid state. For this, we use the Non-Equilibrium Green’s Functions (NEGF) also named as Keldysh formalism in the matrix form to obtain the current–voltage (I–V) and conductance– voltage (G–V) curves to which goes to characterize the
investigated system. Thus, it’s possible to verify the presence of the Majorana Fermions in three points: (i) Conductance peak in zero polarization; (ii) The current difference depends on the asymmetry of μL and μR. We find that only for μL
= μR, the source and drain currents are equal. (iii) The current difference depends on the asymmetry of ΓL and ΓR.
The Odd Generalized NH Inverse Exponential Model: Theory and Application
Authors: Al-Marzouki Sanaa , Alrajhi Sharifah
Published: January 2021

In this paper we introduce a new lifetime distribution derived from odd generalized NH-G (OGNH-G) family technique called OGNH-inverse exponential (OGNHIE) distribution. We establish various mathematical properties. The maximum likelihood (ML) estimates for the OGNHIE parameters are
derived. Finally the model is applied to a real dataset. We apply goodness of fit statistics and graphical tools to examine the adequacy of the OGNHIE distribution. The importance of this research lies in deriving a new distribution under the name OGNHIE, which is considered the best distributions
in analyzing data of life times at present if compared to many distribution in analysis real data.
A Prototype of Fiber Bragg Grating Dendrometric Sensor for Monitoring the Growth of the Diameter of Trees in the Amazon
Authors: Oliveira Lelis Araujo de , Oliveira Jackson Moreira , de Sousa Fabio Barros , de Sousa Fiterlinge Martins , de Oliveira Jorge Everaldo , Costa Marcos Benedito Caldas
Published: January 2021

In this work, we propose a fiber optic point dendrometer with two Fiber Bragg Grating (FBG) sensors capable of simultaneously measuring strain and temperature considered suitable for monitoring the growth of the diameter of trees in the Amazon compared to conventional electrical sensors
and we perform a simulation on the performance of the sensors for measuring the diameter using the Coupled Mode Theory (CMT) and the Transfer Matrix Method (TMM). A measure of the diameter variation was suggested and the sensitivity of the sensors were analyzed from the measurements of the
displacements of the Bragg wavelengths varying simultaneously the strain and the temperature. The results showed that the proposed configuration, thermally varied from 0 °C to 80 °C and deformed from 0 to 2400 μ could specifically detect minute variations in diameters with a resolution
of 0.5 μm (0.0005 mm) with good linearity staying with a variation of the Bragg wavelength 0.12 nm for each 10 °C and 0.24 nm for each 200 μ. The feasibility of using this type of configuration of FBG sensors for strain and temperature measurements in the monitoring of forest, forestry,
climate change and irrigation areas in the Amazon is very promising.
Aluminum-Doped Titanium Dioxide Thin Films: A Study of Different Concentrations on Poly(3-hexylthiophene): PhenylC61-Butyric Acid Metheyester-Based Organic Solar Cells
Authors: Al-Mosawi Buraq T. Sh. , Al-Hashimi Mohammed K. , Abdulameer Ameer F.
Published: January 2021

Sol–gel preparation method usually used to prepare the metal oxides. So, it is a rewarding process to prepare the electron selective film made of aluminum-doped titanium dioxide (Al-doped TiO2). The latter was used to fabricate the inverted organic solar cells P2HT:PCBM.
The doping content with Al impact on the optical and morphological characteristics of each film were examined. These characteristics were analyzed depending on the magnified images of the prepared samples by atomic force microscopy (AFM), scanning electron microscopy (SEM), X-ray diffraction
(XRD) in addition to the Uv-vis spectroscopic results. The outcomes revealed that the concentration of Al doping has potential influences on the optical properties, XRD results and surface morphology. The J–V curve characteristics of each solar cell utilizing Al–TiO2
film were analyzed and noticed that the most powerful conservation efficiency is 2.09% when using Al–TiO2 layer with 0.5 wt.% Al as a doping element.
Application of Chemometric Techniques for Validation of Computational Methods Applied in Molecular Modeling of 6α-Hidroxyvouacapan-7β, 17β-Lactone with Antiproliferative Activity in Leukemia Cells
Authors: Lobato Cleison C. , Silva Rai C. , Sanches Vitor H. S. , Santos Kelton L. B. dos , Santos Igor V. F. dos , Carvalho Adonay S. de , Costa Renato A. da , Ferreira Elenilze F. B. , Brasil Davi S. B. , Macêdo Williams J. C. , Borges Rosivaldo S. , Santos Cleydson B. R.
Published: January 2021

Hidroxyvouacapan-6α-7β, 17β-lactone (HVL) is a synthetic derivative of 6α, 7β-dihydroxyvouacapan-17β-oic acid (ADV) which was isolated from the fruits of Pterodon polygalaeflorus Benth. Both compounds showed anti-inflammatory and analgesic activities.
According to studies conducted by Euzébio et al. in 2009 and 2010, ADV, HVL and some derivatives showed antiproliferative activity in different line of cancer cells, including the K562 leukemia. In this paper, we propose a combination of quantum-chemical methods, multivariate analysis
and statistical to assess semi-empirical (AM1, PM3 and ZINDO), Hartree-Fock (HF) and DFT (B3LYP) methods in different basis set for determining which method better describes in sign and magnitude the geometric parameters of HVL compared to crystallographic data. PCA results were based on three
main components, explaining 88.79% of the total variance for the geometrical parameters O2C6, O4C17C14C, C16O1C12, C6C7O3C17 and O3C7C8C14. DFT (B3LYP) method corresponded well with experimental data in hierarchical cluster analysis (HCA). The experimental and theoretical angles were analyzed
by linear regression and statistical parameter (correlation coefficients, significance and predictability) were evaluated.
A Deterministic Model for Five Major Medical Health Insurance Companies in South Africa
Authors: Tong T. O. , Kekana M. C. , Shatalov M. Y. , Moshokoa S. P.
Published: January 2021

In this paper, A deterministic for top five medical insurance in South African market system is analyzed under important parameters such as emigration, immigration, personal interaction and advertisement. The critical outcome indicate all those medical insurance will remain relevant
to South African population as long the aforesaid parameters are positive and intensified.
Optical Properties and Structural Behavior of Antimony Borate Glass
Authors: Ahmed Azza El-Sayed , Guizani Ikram Hassouna , El-Deen Abeer Serag , Ahmed Salwa Said
Published: January 2021

Structural and optic consistent of the amorphous system of concentrations (65-x)B2O3-xSb2O3-10 ZnO-25 Na2O (x = 0, 5, 10, 15, 20 mol%) were carried out using X-ray diffraction (XRD) examination, optical absorption
spectrum (Ultra-violet) spectrophotometers UV and Fourier-transform infrared spectroscopy (FTIR) analysis. XRD pattern revealed the non-crystalline nature of investigated samples at different concentrations. Also, the optical band gap was evaluated at different concentrations. Results revealed
that band gap values increase by increasing antimony concentration from (3.1–3.45) eV. From optical measurement spectra, Urbach energy ΔE evaluated at different concentrations. The structural unit of BO4 transformed to BO3 due to the change of the molar volume,
density. The increase of density of any glassy system means that the average interatomic distance is reduced. This leads to the increase of the force constant leading to the blue shift of IR bands and the band edge, and N4 fraction with antimony oxides concentrations which leading to closing
up of amorphous structure.
Optimized Attachment to Achieve Different Buccolingual Movement of Maxillary Molars in Clear Aligner Orthodontic System: Biomechanical Analysis
Authors: Qin Long , Wang Qiao , Zhang Dongliang , He Xin , Wu Binbin
Published: January 2021

The different positions and angles of attachment affecting the buccolingual movement of the maxillary molars, especially lingual tipping and negative torque movements, were biomechanically analyzed in order to determine how to better control and prevent unwanted movement of clear aligners.
The aligner can be designed and placed appropriately to improve expected tooth movement. Based on mechanical principles, the force system of attachment was analyzed, and the optimum attachment position and angle for tipping and negative torque movement was determined. Attachment close to the
enamel-cementum junction (ECJ) was found to achieve the best F (M/L) during negative torque movement; however, the angle should also be adjusted. Attachment close to the occlusal surface achieved greater tipping force at specific angles. When more tipping movement is required, it is recommended
to place the attachment 3–5 mm from the ECJ. The angle of the attachment should be 110–120 degrees from the tooth surface. When place the attachment 4–5 mm from the ECJ, the angle of the attachment should be between 145 and 146.5 degrees.
The Effect of Immune-Related Genes on Colonic Adenocarcinoma Prognosis
Authors: Hou Mingyu , Ma Jiakang , Lin Xiaoyan , Ma Jun
Published: January 2021

Colorectal adenocarcinoma (COAD) is the most common type of colon cancer, and its occurrence is intimately associated with immune-related gene (IRG) expression. In this research, the IRG expression was analyzed and 484 were found significantly different between COAD and normal tissue.
To construct a COAD patient IRGs-prognosis model, 11 of the IRGs were selected by multivariate Cox analysis. IRGs in the model were closely related to tumor invasion depth, lymphoid involvement, distant metastasis, stage, and age. This work lays the foundation for future scientific research
and clinical work related to COAD.
Preparation of New Nano-MnO2 and Its Molybdenum Adsorption in Manganese Sulfate Solution
Authors: Haifeng Wang , Xiaoliang Chen , Pingyuan Zhao , Zhaowei Gao , Xiaoyu You , Jiayu Tian , Jiawei Wang
Published: January 2021

Manganese sulfate solution was in this study oxidized, using H2O2 as oxidant, to obtain new Nano-MnO2 in situ. The characterization of new MnO2 was carried out by XRD, SEM, FT-IR and BET. The effect of new manganese dioxide adsorpting
molybdenum ion in manganese sulfate solution was also studied. Results showed that the main crystal form of the new MnO2 was γ type, and there was agglomeration of nanospheres with 200∼300 nm diameter from the microscopic morphology, which had abundant surface
hydroxyl groups, and its specific surface area was as high as 146 m2/g. MnO2 addition was 1.0 g under optimal adsorption conditions when the pH was 2, and the reaction time was 30 min, with removal rate of 99.2% molybdenum and 0.26 ppm residual amount of molybdenum in
manganese sulfate solution, which met the quality standard for high purity manganese sulfate (HG/T4823-2015) with ≤5 ppm molybdenum content. Moreover, the thermodynamics and kinetics of molybdenum adsorption by new manganese dioxide were also studied. The experiments showed that the adsorption
process was in accordance with the Freundlich adsorption equation. The adsorption process of molybdenum on manganese dioxide could be described with pseudo second order kinetic model, and the internal diffusion was a controlling link of adsorption rate.
Targeting Mesoporous Silica for Synergistic TH-302 and Afatinib Delivery to Nasopharyngeal Carcinoma
Authors: Zhang Shengchi , Li Li , Wei Xianfeng , Mao Xiang , Zhang Xueqing , Liu Yao , Wei Mei , Wang Wei , Zhang Lun
Published: January 2021

Tumor hypoxia is considered as an important factor for tumor metastasis and disease recurrence. Evofosfamide (TH-302) is a hypoxic prodrug, which can selectively target the hypoxic area of solid tumors, and has the potential to improve the efficacy of the commercial anticancer drug
afatinib (AFT). However, free hydrophobic AFT and hydrophilic TH-302 still have several unequivocal deficiencies, such as unsatisfactory tumor inhibition rate, serious side effects and being easy to induce multidrug resistance. Moreover, the operation process of co-administration is too complicated.
Therefore, this paper discussed the synergistic effects of AFT/TH-302 and developed a kind of co-loaded targeted mesoporous silica nanoparticles (MSNs) for the treatment of nasopharyngeal carcinoma (NPC). The calculated proportion of AFT and TH-302 were encapsulated by folic acid (FA) modified
MSNs (FA-MSNs). In vitro experiments showed that free AFT and TH-302 had synergistic effect, while MSNs nanocarrier could significantly reduce the half maximal inhibitory concentrations (IC50) of AFT and TH-302. AFT and TH-302 show significant synergistic on NPC cells, the application of MSN
carrier platform including fixed proportion of AFT and TH-302 improves the synergistic effect and provides a new idea for the treatment of NPC.
IL-17B Regulates Endothelial Cell Apoptosis in Venous Thrombosis
Authors: Li Yunyan , Yang Yuan , Chen Jianfu , Wang Yuxue , Zhang Yong , Zhou Yan , Wang Zilong , Lu Yongping
Published: January 2021

Venous thromboembolism (VTE) is the comorbidity of deep vein thrombosis (DVT) and pulmonary embolism (PE); it is an urgent public health problem. The primary cause of venous thrombosis is endothelial dysfunction caused by vascular injury and inflammation or overexpressed procoagulant
factors. Previous studies have shown that vascular endothelial cell apoptosis is involved in venous thrombosis, causing vascular wall damage. The pro-inflammatory cytokine interleukin-17 (Il-17A) induces endothelial cell apoptosis and promotes thrombosis. However, it remains unclear whether
other IL-17 family cytokines are involved in thrombus formation. Among the IL-17 family, IL-17B is less well-characterized. Several studies have reported that IL-17B could stimulate TNF-α, IL-1, and IL-6 expression in macrophages. Furthermore, IL-17B induced activation of the
ERK1/2 pathway, upregulating Bcl-2 family anti-apoptotic proteins in breast tumors. However, it is unclear whether IL-17B is involved in thrombus formation by regulating endothelial apoptosis. Therefore, this study aimed to examine whether IL-17B could affect endothelial apoptosis by promoting
thrombus formation.
The Researches and Applications of Reverse Engineering in the Protection and Inheritance of National Handcrafts
Authors: Zhang Dehai , Li Junheng , Zhu Huimin , Liu Shujun , Yu Kun , Guo Zhaocan , Fu Liang
Published: January 2021

National handcrafts are well-known at home and Abroad for their fine ingredients, exquisite blending of colors, and excellent skilled shaping and painting. What is more, they have great value and are deeply popular with people around the world. National handcrafts, as a cultural crystallization,
must be protected. In order to better realize the protection, we try to apply the technology of reverse engineering to the protection. This article mainly takes a handcraft, Yan Zi YU (meaning “swallow fish”), as an example to expound and demonstrate the process of reverse engineering
technology. During this process, by using scanning technology of reverse engineering, the collection and splicing of the point cloud data, the theoretical analysis of the NURBS surface in the reconstruction phase, and other practical operations in other stages, reverse engineering can be used
to regenerate 3D modal data of the swallow fish and to inspect and analyse the errors in it through Geomagic Quality to ensure that the new model meets the precision requirements. Therefore, the reverse engineering technology can be completely applied to the protection of national handcrafts
so that they can fully demonstrate their own value and function. If the precision of reverse engineering detection can reach nanometric level, a breakthrough will promote the protection of cultural relics.
Study on Chitosan-Based Nanocomposite Hydrogel in Soft Tissue Defect of Hand
Authors: Zhang Jian , Gao Zhaoyu , Zhang Yao , Tian Jinghai
Published: January 2021

Hand soft tissue defects are a common disease in surgical emergency, which seriously affects the limb function of patients and significantly reduces their quality of life. To effectively repair hand soft tissue defects, a difficult problem posed to surgeons, we report here the use of
a chitosan-based nanocomposite hydrogel (CS-GEL-PDRN). In vitro experiments showed that the nanocomposite hydrogel could promote the proliferation of human embryonic fibroblasts M-22 and human vascular endothelial cells EC-304. In addition, the hydrogel had excellent blood compatibility. In
the rabbit model of soft tissue defects, CS-GEL-PDRN effectively coordinated cytokine responses, accelerated wound healing and promoted tissue repair. Based on this, CS-GEL-PDRN is expected to play a clinical role in the repair of hand and other soft tissue defects in the future.