bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Novel Coplanar Based Adder Logic Design Using QCA
Authors: Navaneetha Velammal M , Hannah Blessy P , Friska J , Rajeshwari A 
Published: August 2021

Abstract
Now a days, VLSI is a one of the top most technology are used in the field of electronics communication. It is used to create an integrated circuit by merging million of MOS transistor into a single chip. In VLSI, most of the transistors are design in micro scale level. Now a days people will want all materials are in compact size. So, it is necessary to design a circuit in nanoscale level. In the field of VLSI, CMOS technologies are used for designing a integrated circuit (IC) chips. But in CMOS, size that are used to designing a circuit is in micro scale level. So researcher is introducing new nanotechnology that new technology is called QCA technology. Logic function gate is a one of the fundamental components to design an any circuit in electronics communication. In this paper, novel coplanar approach to designing an efficient QCA based 4-bit full adder using XOR/XNOR logic gate is proposed. QCA Designer Version 2.0.3 simulation tools are used in this proposed method. Performance is analysed and verified to determine the capabilities of proposed full adder.
Enhanced Deep Learning Approach For IoT Enabled Sensitive Clinical Data Analytics
Authors: Mohamed Aslam M A , Kalaimani Shanmugam E V R M , Dilip Kumar S 
Published: August 2021

Abstract
With the enormous upgrade of clinical sensors, it has acquired developing interest to investigate the Healthcare Internet of Things (H-IoT) because of its wide relevance for wellbeing of patient. Current medical services are providing only a limited significance with the emergence of a new strain Covid-19. People are dealing with an issue of unforeseen demise because of different ailment which is a direct result of absence of clinical consideration to the patients at perfect time. Hence in this situation, an IoT based smart healthcare checking framework is necessary during this pandemic. In this paper, an enhanced deep learning framework is proposed that efficiently deep belief network perform IoT-enabled clinical data analytics. The proposed framework is utilized to PIMA Indian physiological parameter dataset quantify to the actual boundaries like internal heat level, heart beat rate, and oxygen level checking with the assistance of sensors. The proposed framework involves the secured cloud infrastructure where the clinical sensor data are acquired and stored. For secured cloud storage and to provide an improved security, Improved Elliptic Curve Cryptography (IECC) algorithm utilized set up a transfer a medical records trust between the doctors and patients centralised repository trailed by enabling a typical session key for communication. The proposed solution automatically predicts any abnormalities exist in the patient and it is communicated to the medical experts for disease diagnosis and appropriate medical consultancy is provided for the patient through secured channel. The proposed framework is deployed in real-time environment for remote healthcare especially in rural area.
Random Forest (RF) based identification of rice powder mixture using terahertz spectroscopy
Authors: Friska J , Navaneetha Velammal M , Rajeshwari A , Hannah Blessy P 
Published: August 2021

Abstract
Adulteration is a severe problem in agriculture field. It may cause some dishonest traders in the marketing side. For their own wish, dishonest traders make adulteration products for higher profit. In consumer side, agro product adulterations provide some unhealthy situation. It may cause severe health problem and also some incurable disease. Its right time, need to find an adulteration various level of agro products. For detecting rice adulteration, to collect spectral data for mixed rice powder (low quality rice powder and high quality rice powder), and a Fast Independent Component Analysis (FICA) algorithm is used to extract valuable information. Then, apply Random Forest Classifier algorithm for classifying purpose, whether the mixture is low quality or high quality. It achieves high accuracy with a single model and also easy to implement.
Smart Urban Water Quality Prediction System Using Machine Learning
Authors: J Bharath Singh , S Nirmitha , S S Kaviya 
Published: August 2021

Abstract
The World Health Organization says that every year more than 3.4 million people die as a result of water-related diseases. Quality of water serves as a powerful environmental determinant and a foundation for the prevention and control of waterborne diseases. The project aims to design a water quality prediction system using Machine learning based on the water standards suggested by BIS to prevent deaths due to water related diseases. The quality is predicted based on parameters such as pH, Temperature, TDS, Turbidity and Conductivity value. The dataset is preprocessed and split into test and training data. The data is fed into regression algorithm and been evaluated. Sensors that can measure the water parameters are also been implemented. A webpage interfaced with the Machine Learning model is created to upload sensor values and the corresponding water quality is predicted. This project can be used in urban areas to predict the quality of the drinking water thereby preventing the spread of diseases such as dysentery, typhoid and cholera due to consumption of contaminated water.
Effective fault detection approach for cloud computing
Authors: Ashritha Pola , Banusri M , Namitha R , Shiny Duela J 
Published: August 2021

Abstract
In cloud computing, accessibility to data anytime is crucial, acquiring data and maintaining that data without any loss or incursion is an essential task. A cloud service must have the potential to recognize unexpected faults and respond effectively. Hence, a system to identify faults is developed which recognizes anomalies using various techniques and algorithms. Several different types of faults occur in cloud computing which causes the poor performance of cloud computing. The various types of faults occurred are collected and classified using a fuzzy one class support vector machine and long short term memory(LSTM) algorithm. Comparative analysis of accuracy and precision is done with various algorithms like Naive Baye Algorithm, Decision Tree Algorithm, K-Neighbors Algorithm, and Logistic Regression Algorithm. Experimental results show that Logistic regression gives the best accuracy, precision and performance for detecting faults among the aforementioned algorithms. The efficacy of our model is illustrated in experimental results.
BAT algorithm based MPPT technique for bidirectional converter in photovoltaic system under partial shading condition
Authors: Ishwarya S , Janani D , Shadika R , Sureka M 
Published: August 2021

Abstract
A photovoltaic cell is related in nursing device. It converts energy of sunbeams directly into electricity by electrical process impact. Electrical phenomenon system could be a device that converts alternative energy into current. Partial shading has high affect on photovoltaic system. Photovoltaic system generates electrical power which relies on solar irradiance. The photovoltaic system is always affected by the partial shaded system. So that, the maximum power cannot be obtained easily. Some effects on photovoltaic system by partial shading are air, trees shadow, thunders. However, some techniques to find maximum power are PSO, P&L, FL and ANN. Maximum power point is tracked by BAT algorithm. Because, it is swarm intelligence based method. In the global optimization BAT algorithm has high accuracy, and good dynamic performance. It has quick convergence rate. In addition to BAT algorithm, bidirectional converter is used. A bidirectional converter allows power in both reverse and forward direction. It is capable of performing both step-up and step-down functions and it also performs continuous power flow in the circuit. By using BAT algorithm and bidirectional converter, maximum power can be tracked and output can be improved.
Plagiarism Detection through Data Mining Techniques
Authors: Nennuri Rajashekar , Geetha Yadav M , Samhitha M , Sandeep Kumar S , Roshini G 
Published: August 2021

Abstract
Plagiarism is a problem that is becoming more prevalent as technology advances and the use of computer systems grows in comparison to previous generations. Plagiarism is the unauthorized use of another person’s work. Since manual plagiarism detection is difficult, this method should be automated. Plagiarism detection can be done using a variety of methods. Some of the research focuses on intrinsic plagiarism, while others focus on extrinsic plagiarism. Data mining is an area that can assist in both detecting plagiarism and improving the reliability of the operation. Plagiarism can be detected using a variety of data mining techniques. Text mining, clustering, bi-grams, tri-grams, and n-grams are some of the techniques that can assist with this. In this paper we will use the data mining techniques to increase the efficiency of detection of plagiarism.
Preface
Authors: Vergel-Ortega M , Rincón Leal O L , Dueñas Ramírez L M 
Published: August 2021

V International Meeting of Mathematical Education

The objective of the V International Meeting on Mathematics Education (V IMME) is to create and maintain a space that privileges and promotes the culture of mathematics, reflection and discussion on the education and application of mathematics, statistics, its history, evolution and didactics, and its interrelation with the sciences. At the meeting, researchers, scientists, and mathematics teachers socialize the results of research, consolidate networks for the exchange of successful experiences, to strengthen mathematics education at different educational levels, promote innovation and encourage the creation of policies, models, educational strategies, tools, and techniques in various areas of mathematics. They also promote innovation and encourage the creation of policies, models, educational strategies, tools and techniques in different areas of knowledge, and foster students' interest in research.
V International Meeting of Mathematical Education, Organizing Committee, International Scientist Committee, International Scientific Committee, Invited Speakers are available in this pdf.
Applications of linear algebra to the study of mathematical modelling of the physical phenomena of heat conduction by electricity
Authors: Nolasco Serna C , Afanador Garcia N , Guerrero Gómez G 
Published: August 2021

AbstractThe study of the phenomenon of electrical conduction has its origin in two historical antecedents, Fourier’s law and Maxwell’s equations. The mathematical formulation of electrical conduction has been extensively studied and the differential equations describing the phenomenon are known. The mathematical solution of the physical model of electrical conduction employs different techniques, the best known of which are the Fourier series, Grenn functions and Bessel equations. The purpose of this research is to present a model of heat conduction with the use of electric current that dissipates heat by convection. The research proposes a method for solving the mathematical model associated with the conduction phenomenon using linear algebra. The advantage of using linear algebra will allow to establish a step-by-step procedure that could be used to study phenomena related to heat conduction, in addition to allowing its implementation through programming. In order to establish the fit of the method derived from linear algebra, the analytical solution and the solution proposed in the research were compared to verify that the proposed method fits with a small error.
Detection of water leaks with Dowsing technique and Reynold’s transport theorem
Authors: Pérez-Carrascal K , García-Guarín J 
Published: August 2021

Abstract
Zahorí techniques are traditionally used to detect water currents in land for subsequent extraction. On the other hand, water leaks represent economic losses in factories and residences. It is enough to survey a city and determine the exaggerated number of residential leaks. Once the leak appears, a corrective action must be taken, this action is founded in itself and in the problems derived from this failure; and it is that knowing the exact location of a leak is risky if strictly collateral damage appears in the property. This research proposes to complement two different techniques, the first detects the presence of water based on the Dowsing search, and the second uses the Reynolds Transport Theorem to detect the leak relying on numerical methods and computational simulation. The Dowsing search proved to be reliable to detect the presence of water, the Reynolds Transport Theorem, yields the location of the leak with an average relative error of 10.6727% and the computational simulation corroborates Darcy’s Law. Therefore, the method proposed in this investigation is sufficient for the corrective management of leaks.
Teaching physics through the implementation of a didactic strategy for the integration of knowledge in secondary school students
Authors: Prada Nuñez R , Hernández C A , Gamboa A A 
Published: August 2021

Abstract
The objective was to evaluate the implementation of the knowledge integration model in high school students studying physics in a public educational institution in the city of San José de Cúcuta, Colombia. A quasi-experimental model was applied. An intervention was implemented as a didactic strategy for the integration of knowledge based on the Pragmatic Pedagogical Principles, its operative criteria, and activities. Conceptual progress is reported by means of Hake’s normalized factor or gain, which was modified to the rating scales, and the results of partial exams are considered, implementing a continuous and formative evaluation system. The results were compared between the experimental and control groups. It was found that the experimental group showed better academic achievement and performance than the control group. This suggests that the results generated a continuous learning progress thanks to the application of the operative judgments of the corresponding principles.
Analysis of variables related to the mass flow of gaseous emissions in beehive ovens
Authors: Mendoza–Lizcano S M , Palacios–Alvarado W , Medina–Delgado B 
Published: August 2021

AbstractIn the combustion processes of the ceramic industry, large amounts of pollutant gas concentration are generated, so it is necessary to measure the system and the physical phenomenon, as well as the variables inherent to the process, for subsequent estimation in terms of physical magnitudes, and a dimensional analysis, this allows to generate approximations in the causal relationships of the variables. The objective of the research is to analyze the behavior of the variables involved in the process and the influence of the mass flows of polluting gases. An exploratory and experimental methodology was used, for this, the data were taken with the technique of direct measurement in the sources of gas emissions and subsequently subjected to simulation in software such as AMOS V24.0 and LISREL V8.8., on the other hand, the data were subjected to an exploratory and confirmatory factorial analysis, using SPSS software version 24.0. As a result, the variables capacity and production are practically identical, which leads to a high correlation and, consequently, an undesired multicollinearity between the variables, so the suggestion is to omit one of them. On the other hand, the sulfur percentage variable is inversely correlated with most of the variables and its saturation is not clear, so it is theoretically sustained as a latent variable of the SO2 indicator.
A mathematical model for the simulation of the Magdalena River in the city of Barrancabermeja, Colombia
Authors: Cely-Calixto N J , Bonilla-Granados C A , Carrillo Soto G A 
Published: August 2021

Abstract
The integration of mathematical models allows the simulation of the spatiotemporal behavior of water quality parameters of a river. The representation of reality and different scenarios through simulation makes it possible to know the variations in water quality of a receiving water source associated with liquid discharges. Therefore, for this study, the mathematical model QUAL2K was applied to simulate the water quality of the Magdalena River in the section that crosses the city of Barrancabermeja, Colombia. For this purpose, a database of hydro-climatological records from 1977 to 2020 was used. Among the analyses, dissolved oxygen and biochemical oxygen demand were considered as water quality parameters. As a result of the initial data processing of the distribution tests and Kolmogorov goodness of fit, the best fit with the normal distribution was obtained for the estimation of flow rates. The concentrations of the water quality parameters dissolved oxygen and biochemical oxygen demand were represented in the mathematical model, which shows the dilution capacity of the pollutant loads of the wastewater, due to the high flow of the Magdalena River in the study section.
Relevance of the use of measurement units and orders of magnitude in the training of civil engineers
Authors: Márquez Peñaranda J F , Cáceres Rubio J R , Pineda Rodríguez J R 
Published: August 2021

Abstract
Worldwide, a typical civil engineering program focuses in formal, natural, and applied sciences within an environment of ethical and social responsibility. Mathematics and computer sciences are the main formal sciences. The most widely used natural sciences are physics, earth science, and chemistry. On the other hand, a student who begins the professional cycle of the program must develop skills in applied science to solve practical problems. Complex processes and concepts requiring skills related to mathematics and physics must be developed. Such processes and concepts demand an impeccable handling of operations which involve diverse precision degrees, measurement units and a high variety of basic and derived quantities. This work describes the identification and classification of the main errors made by students when solving written exams applied in a natural environment of structural design courses. Data were collected during four years at a university in Colombia. Report of errors was grouped into five categories named modelling, quantities, regulation, signs, and others. Collected errors were evaluated qualitatively and quantitatively. In addition, each error was assigned to a risk level (high, intermediate, low) according to its potentiality to generate catastrophic errors in professional practice. The quality and number of observed errors seem to be correlated with the time of year in which they occur. On the other hand, the high-risk errors resulted to outweigh the two lower risk levels. This finding is worrying and serves as the basis for making an urgent call to review the way of teaching and its relationship with practical results. In synthesis, this study presents a novel manner to study the formation errors in engineering civil programs. In the near future, it is expected to use the results of this research to propose a procedure for the design and feedback of teaching strategies consistent with the evaluation objectives of each course.
The rubric as an assessment tool for solving problem situations in the physics and mathematics teaching context
Authors: Salazar-Torres J , Rincón Leal O , Vergel Ortega M 
Published: August 2021

AbstractPolya propose the didactic problem-solving strategy to strengthen the teaching and learning processes in the mathematic field. Thus, this strategy can be applied in other fields such as physics teaching the article proposes an evaluation strategy based on the design of a rubric to assess the processes associated with solving mathematical problems, as a classroom research work based on Research, Pedagogical Action. As one of the results, an analytical rubric composed of criteria and indicators associated with the steps of Polya problem solving is proposed, as well as a reflection associated with the teaching of problem solving in the engineering area.
Climate change, riverine flood risk and adaptation for the conterminous United States
Authors: Wobus Cameron , Porter Jeremy , Lorie Mark , Martinich Jeremy , Bash Rachel 
Published: August 2021

Abstract
Riverine floods are among the most costly natural disasters in the United States, and floods are generally projected to increase in frequency and magnitude with climate change. Faced with these increasing risks, improved information is needed to direct limited resources toward the most cost-effective adaptation actions available. Here we leverage a newly available flood risk dataset for residential properties in the conterminous United States to calculate expected annual damages to residential structures from inland/riverine flooding at a property-level; the cost of property-level adaptations to protect against future flood risk; and the benefits of those adaptation investments assuming both static and changing climate conditions. Our modeling projects that in the absence of adaptation, nationwide damages from riverine flooding will increase by 20%–30% under high levels of warming. Floodproofing, elevation and property acquisition can each be cost-effective adaptations in certain situations, depending on the desired return on investment (i.e. benefit cost ratio), the discount rate, and the assumed rate of climate change. Incorporation of climate change into the benefit-cost calculation increases the number of properties meeting any specified benefit-cost threshold, as today’s investments protect against an increasing frequency of future floods. However, because future expected damages are discounted relative to present-day, the adaptation decisions made based on a static climate assumption are very similar to the decisions made when climate change is considered. If the goal is to optimize adaptation decision making, a focus on quantifying present-day flood risk is therefore at least as important as understanding how those risks might change under a warming climate.
Analysis of Air Pollutions’ Effects on Chinese Children, Adolescents, and Young Adults
Authors: Zhang Muqing 
Published: August 2021

Abstract
In recent years, air pollution in China is becoming more and more serious. Due to air pollution, people were forced to wear masks on streets and some schools even suspended their classes. Many researches had proved that air pollution will cause severe damages to human health. This research focused on reviewing the previous studies on the air pollution’s effects on Chinese children, adolescents, & young adults (the target population), and tried to provide suggestions for future research. The previous researches conducted on this topic were searched on cnki.net and Pubmed and collected. The obtained papers are selected and analyzed. It can be concluded that air pollution had huge effects on the target population’s respiratory system, cardiovascular system, and mental state.
Industry Chain and Technology Trends in China’s Solid-state Battery Industry
Authors: Zhang Lei , Liu Yingqi , Pang Beibei 
Published: August 2021

Abstract
Solid-state battery is different from traditional lithium-ion battery, which is a kind of battery using solid electrode and solid electrolyte, and it has the advantages of high safety, long life, high charging and discharging efficiency, good high temperature resistance, simple assembly and processing, and easy to scale up. This paper first analyzes the industrial chain of solid-state batteries in China and the stakeholders in the process of industrial development, and finally draws a technology roadmap for the development of China’s solid-state battery industry based on industrial characteristics. In the future, along with energy transformation and national policy support, the focus should be on solid state electrolytes for solid state batteries, and gradually realize the development path of solid state battery electrolytes from liquid state of traditional lithium-ion batteries to solid-liquid hybrid, gel, solid state, and all-solid state.