bluuebunny/crossref_metadata_2025_split huggingface dataset:
Patient health monitoring using soft computing techniques
Authors: Pawan YVR Naga , Prakash Kolla Bhanu , Kumar Vadla Pradeep 
Published: June 2020

Abstract
Due to exponential growth and rapid modernization in urban areas, there is a disparity in the socio-economic urban and rural populace. The wellbeing of these population is peril change in lifestyle affecting the health of an individual or their families. Moreover, the many countries has health issues in Communicable and Non-Communicable Diseases and malnutrition. As per World Health Organization (WHO), the Doctor to Patient Ratio (DPR) is 1:1000. It is an apprehensive task for a Doctor to monitor health concerns of the patients. The time to spent by a doctor to a patient is an average of 7-10 min, where most of the time, the doctorsare busy in taking notes symptoms or feeding the data to the Health Care System. The smart devices and Computational Intelligence (CI)and Soft Computing Techniques (SCT) may help the doctors to monitor the data of their patients suffering with various health care issues and also to diagnose and to provide state-of-the-art treatment. The collected data may be used by theconglomeration of doctors for their superfluous analysis and predictions, local government authorities may use the data to improve sanitation and controlling the outbreak of epidemics and also for other health care predictions. Applying SCT, identification of correlated features, feature ranking or importance and feature selection are performed on UCI Machine learning Datasets and also classification and prediction are performed on the Datasets to examine the accuracy of the predictions for the classification algorithms - rpart, knn and svm.
Bayesian networks applied to climate conditions inside a naturally ventilated greenhouse
Authors: Silva Jesús , Navarro Evaristo , Varela Noel , Pineda Lezama Omar Bonerge 
Published: June 2020

Abstract
The prediction of gradients in a naturally ventilated greenhouse is difficult to achieve, due to the inherently stochastic nature of the airflow. Bayesian networks are numerical uncertainty techniques that can be used to study this problem. A set of experimental data was obtained: air temperature, air humidity, wind speed, and CO2 concentration at one and three meters above the ground in the growing space. The data set was discretized and used to develop a Bayesian Network model that describes the relationships between the studied variables. The model shows the differences that allow to identify the degree of dependence of the variables, as well as to quantify their inference.
Solving the problem of optimizing wind farm design using genetic algorithms
Authors: Viloria Amelec , Lobo Hugo Nuñez , Pineda Lezama Omar Bonerge 
Published: June 2020

Abstract
Renewable energies have become a topic of great interest in recent years because the natural sources used for the generation of these energies are inexhaustible and non-polluting. In fact, environmental sustainability requires a considerable reduction in the use of fossil fuels, which are highly polluting and unsustainable [1]. In addition, serious environmental pollution is threatening human health, and many public concerns have been raised [2]. As a result, many countries have proposed ambitious plans for the production of green energy, including wind power, and consequently, the market for wind energy is expanding rapidly worldwide [3]. In this research, an evolutionary metaheuristic is implemented, specifically genetic algorithms.
Influence of lighting and noise on visual color assessment in textiles
Authors: Silva Jesús , Rondon Carlos , Cabrera Danelys , Pineda Lezama Omar Bonerge 
Published: June 2020

Abstract
Color is a human perception of the light reflected by an object. It is an appreciation that depends on the way the human’s eyes detect the reflected light and the way the brain processes it. However, for industry, it is an attribute of product appearance and its observation allows the detection of certain anomalies and defects [1]. Therefore, color is a characteristic that allows to judge an object by creating conditions for its acceptance or rejection [2]. In this research, a laboratory experiment was carried out to analyze different factors involved in visual color evaluations in textiles. A complete factorial experiment design was carried out in which the analyzed factors were lighting, noise, color and participants.
Thermographic imaging for use in artificial intelligence and vision algorithms
Authors: Silva Jesús , Echeverría Ana María , Varela Noel , Pineda Lezama Omar Bonerge 
Published: June 2020

Abstract
The constant technological innovation in devices for the acquisition of digital images such as: energy-efficient and high-pixel sensors, memories with greater storage capacity and processors capable of sampling digital signals more quickly, have made it possible to digitize with greater reliability real life scenes in an instant of time, making it possible to analyze and interpret different physical phenomena [1][2][3] such as fractures in materials, evasion of obstacles, weather conditions, injury detection, among others, giving rise to a new line of research called Artificial Vision (AV) focused on generating algorithms to improve image quality, segment characteristics of interest and eventually recognize patterns, in order to make more efficient image processing for the solution of problems in robotics, automation, security, medicine, veterinary, and others. The research aims to develop a database of thermographic images of pregnant and non-pregnant sheep, providing a tool for specialists in the area of computer intelligence and artificial vision.
Self-charging Peripherals with inbuilt Power Harvesting System
Authors: Azman Mohamed , Babu Sahil , Reddy Thalla Harish 
Published: June 2020

Abstract
Most of the computer peripherals around us require an active power source; they are either wired while some are wireless and are powered by DC batteries. The majority of these devices consume significantly less power when compared to the main device’s power consumption patterns. One may observe that we perform physical activities on the input devices in specific, and since these devices anyway just sip on power, we might as well consider harvesting some energy from the actions performed on the device to power the device itself. In this paper, we explore and discuss the mechanisms that could be potentially used in order to design and produce computer (input) peripherals that would practically last forever without the need to recharge, or swap batteries. We have designed and made prototypes of harvesting mechanisms based on electromagnetic induction, as well as the piezoelectric effect. The work presents a potentially exhaustive system for the next generation of self-powered devices over which any physical human input is expected, and not necessarily confined to the application discussed here.
A survey of digital down converter architecture for next generation wireless applications
Authors: Abinaya A , Maheswari M 
Published: June 2020

Abstract
This article presents a brief survey of Digital down Converter (DDC) architecture and its extensive applications. The distinctive feature of the DDC architecture is its frequency translation from real data signal at an intermediate frequency to a complex baseband signal at zero frequency. The architecture of DDC comprises of Numerically Controlled Oscillator (NCO) and decimation filters. The components of ultra efficient DDC architecture have been implemented in Field Programmable Gate Array (FPGA) device. This down converter provides high malleability, customizability and bearable cost. Due to its amenities, digital down converter was utterly studied and applied in many wireless communication technologies.
Design, simulation, and analysis of a 6-axis robot using robot visualization software
Authors: Talli Amit , V Meti Vinod Kumar 
Published: June 2020

Abstract
In this advanced technological world, robots play an important role in achieving the tasks of a human. Robots have become an essential aspect of the industry, need well-trained engineers to optimize the robot manipulator. To obtain the optimum elements of the work to be carried, a systematic approach required to design, simulate, and analysis of customized robots. This paper presents the design, simulation, and analysis of a 6-axis robot for n-number of applications using solid works simulation and RoboAnalyzer visualization software. The SolidWorks software is used to design the robot and analyzed using the SolidWorks Simulation Xpress and motion study. The robot visualization software: RoboAnalyzer used to analyze the robot kinematics and dynamics. This 3-dimensional software’s help to improve the skills and knowledge of industrial robots. Robot design, simulation, and analysis require the use of 3-dimensional software in the event of an invention needed to develop the high-quality design and improved speed where the industry needs.
Automatic forecasting of student’s province towards Information and communication technology awareness
Authors: Verma Chaman , Kumar Deepak , Illés Zoltán , Stoffová Veronika 
Published: June 2020

Abstract
An experimental study is conducted to forecast the residence state of the students based on their response provided in the ICT survey held during the academic year 2015-2016 at two universities of India. The dataset consists of 560 instances and 59 features. We considered the state as the response variable and 35 features as predictors after self-reduction. The dataset is trained and tested with k-fold cross validation using three popular supervised machine learning classifiers named Artificial Neural Network (ANN), Sequential Minimal Optimization (SMO) and random forest (RF) in the Weka 3.8.1 workbench. The outcomes of the study reveal that RF classifier outperformed with highest accuracy (83.39%) the ANN and SMO at 6-Fold of Cross-Validation (CV). Finally, the authors presented state forecast models which accurately forecasting the state of the student based on their answers during the survey with stabilizing the value of k=6 of CV. The maximum accurate forecasting count for Punjab student is found 239 out of 282 and for Haryana student is found 228 out of 278 with k=6. The findings of study prove a significant difference between the RF and the ANN, the SMO in accuracy and there is no significant difference between accuracy gained by SMO and ANN for state forecasting against student’s response during the survey.
A novel rescuebot for borehole accidents
Authors: Shakthi Murugan K H , Vijithra A Jasmine , Padmavathi B , Jacintha V , Sumathi K 
Published: June 2020

Abstract
Major reports are saying that many children were dead due to the unclosed bore wells. The rescue process cannot be handled smoothly because the environment inside the bore well cannot be predicted by easy means. A less expensive robot can be developed with simple mechanisms for controlling will simplify the rescue process. A movable robot capable of adjusting to the bore well dimensions is constructed. The robot has two arms that can be adjusted to rescue the child with the support of camera also aiding in the survival of the baby. Some additional features are also introduced to enhance and ease the comfort of the rescue operation. A compressor is used to fill an air bag that is implemented in this robot to make the rescue operation easy and be comfortable to lift the victim safely. The gas and temperature inside the bore well can be measured using gas sensor and temperature sensor respectively.
Finite Element Analysis on Multiple IGBT Switch Open-Circuit Fault in PWM Inverter Fed Induction Motor
Authors: Pyasi Kripanidhi , Praveen Kumar N 
Published: June 2020

Abstract
This study analyzes the single and multiple IGBT switch open circuit fault in an inverter fed induction motor (IM) using Finite Element Method. The finite element simulation is carried out in ANSYS Maxwell and Simplorer for various fault conditions such as single IGBT switch open in an inverter leg, two IGBT switch open in the inverter same leg and in different leg. A three-phase 7.5kW IM is modelled in ANSYS Maxwell which is fed through a three-phase voltage source inverter modelled in ANSYS Simplorer. Inverter switches are controlled using sinusoidal pulse width modulation technique. Several electromagnetic parameters such as torque, speed, line voltage, phase current, flux line & flux density distribution over the machine and radial air gap flux density are analysed.
Static Eccentricity Fault Analysis in Inverter Fed Induction Motor using Finite Element Method
Authors: Priya B Hema , Karthick R , Lokprakash B , Vasanth S , Praveen N Kumar 
Published: June 2020

Abstract
One of the common faults encountered in three phase induction motors (IM) is the eccentricity fault. In this work, a study on the electromagnetic characteristics of open-loop voltage source inverter fed IM is carried out for healthy and static eccentricity fault condition with the assistance of Finite Element Analysis. The importance of electromagnetic field analysis is it contains the data about the position of stator, rotor and mechanical parameters of IM. Thus the strategy of monitoring airgap magnetic fields and current are often used for the diagnosis of faults in IM. Detection of eccentricity fault at the incipient stage is difficult because the changes that the fault would introduce in the motor terminal quantities are negligible unless the severity is very high. A comparative study is carried out for healthy and eccentric fault motor with the help of ANSYS Maxwell Finite Element Analysis tool. Electromagnetic field parameters such as speed, current, flux distribution over the machine and in the air gap are analysed for healthy and faulty motor.
Distributed State Estimation of a Non-linear process system with interconnected subsystems
Authors: Elenchezhiyan M , Kumar E Govinda , Shijoh V 
Published: June 2020

Abstract
In this paper authors propose a distributed state estimation scheme for the hybrid system with interconnected subsystems to estimate the states. The system considered in this work has different subsystems which can interact with each other via their states over a communication network. The objective is to implement the distributed state estimation scheme for interconnected subsystems in which each subsystem sensors are connected to the communication network, the estimator has been used for each subsystem to estimate the current states by utilizing the states of the neighboring subsystems over the communication network. The proposed state estimation framework utilizes unscented Kalman filter algorithm. Unscented Kalman filter has been designed for each subsystem to estimate the current state estimates which corrupted by state and measurement noise. The benchmark system taken to implement distributed state estimation is continuous stirred tank reactor units which are strongly interconnected via their neighboring states. The reactors temperature is maintained at unstable operating point by a decentralized proportional integral controller for each subsystem by utilizing the measurements of the sensors from the network. The estimation framework has been verified in the absence of the network failure to stabilize the plant at unstable operating point. The estimate of the corresponding subsystems is used to compute the controller output in the absence of the network failure with minimal sharing over the network.
Corrosion inhibition performance of celery, pomegranate and green tea extracts on mild steel in dilute sulphuric acid
Authors: Loto Roland T , Loto Cleophas , Oyedeko Fope 
Published: June 2020

Abstract
Extracts of celery, pomegranate and green tea were evaluated for their inhibition performance on mild steel corrosion in 0.5 M H2SO4 by weight loss measurement, potentiodynamic polarization and optical microscopy characterization. The plant extracts displayed effective inhibition performance from 60% to 90% volumetric content with highest inhibition performance values of 95.83%, 87.08% and 92.37% at 90% volumetric content in the acid media. Observation shows the inhibition efficiency values of the plant extracts are significantly dependent on volumetric content compared to exposure time. The plant extract demonstrated cathodic inhibition properties Optical images of mild steel without the extracts in the acid media in the absence of the extracts displayed general surface deterioration with large corrosion pits. The image significantly contrasts the observation for the inhibited steel.
Corrosion resistance study of UNS A93105 aluminum alloy in neutral chloride and acid chloride solution
Authors: Loto Roland T , Loto Cleophas 
Published: June 2020

Abstract
The corrosion resistance of UNS A93015 aluminum alloy (A93015) was studied in neutral chloride solution at specific chloride concentration and in 3.5% neutral chloride solution at specific sulphate concentration by potentiodynamic polarization technique, open circuit potential measurement (OCP) and optical microscopy characterization. The presence of sulphate ions in the neutral chloride solution significantly increased the corrosion rate of A93015 compared to the solutions with chloride ions. At 0.5% NaCl concentration, the lowest corrosion rate of 0.255 mm/y was obtained in the neutral chloride solution which corresponds to polarization resistance of 1121 Ω. The corrosion rate value increased to 0.295 mm/y at 3.5% NaCl with significant cathodic shift in corrosion potential. The presence of sulphate ion in the neutral chloride solution significantly increased the corrosion rate of A93015. At 0.00625M sulphate ion concentration the corrosion rate is 4.739 mm/y while at 0.1M concentration, the corrosion rate is 22.176. OCP curves of A93015 at 0.5% and 3.5% NaCl concentration transited anodically to -0.651 V and -0.703 V with relative thermodynamic stability. A93015 OCP plots from 3.5% NaCl solution at 0.00625 M and 0.1 M SO4
2- ion concentration shifted the OCP plots cathodically with absence of potential transients which signifies improved thermodynamic stability.
Effect of heat treatment on the corrosion resistance of S43035 ferritic stainless steel in dilute sulphate-chloride environment
Authors: Loto Roland T 
Published: June 2020

Abstract
The corrosion resistance of heat treated S43035 ferritic stainless (500°C and 1000°C) was studied in 3.5M H2SO4 solution at 0% to 6% NaCl concentration and compared with the results obtained for the non-treated steel by potentiodynamic polarization and open circuit potential measurement. Polarization data revealed that heat treatment improved the general corrosion resistance of the steel by percentage margins ranging from 10.36% to 83.44% depending on chloride concentration. Heat treated (500°C) S43035 steel displayed the lowest corrosion rate value followed by the heat treated steel at 1000°C. Open circuit potential measurement plot indicates that heat treatment increases the vulnerability of S43035 steel to corrosion.
Data on the corrosion resistance quenched 420 martensitic stainless steel and annealed 316 austenitic stainless steel in dilute H2SO4 and HCl acid concentration
Authors: Loto Roland T , Loto Cleophas , Aiguwurhuo Osazaenaye , Evana Ukene 
Published: June 2020

Abstract
The effect of quenching heat treatment on 420 martensitic stainless steel and annealing heat treatment on 316 austenitic stainless steel was studied by weight loss method in 1 - 6 M H2SO4 and HCl solution with their obtained values compared to their as-received counterparts. Calculated data showed heat treatment marginally improves the corrosion resistance of ST316 and significantly, the corrosion resistance of ST420. Results show increase in H2SO4 and HCl concentration general increased the corrosion rate of as-received and heat treated steels. However, corrosion rate values of as-received 420 and 316 stainless steels were significantly higher than the heat treated steels in both acids Heat treatment has limited effect on the corrosion resistance of ST420 in HCl.
Data on the comparative assessment of corrosion resistance of 2101 duplex and 410 martensitic stainless steel for application in petrochemical crude distillation system
Authors: Loto Roland T 
Published: June 2020

Abstract
The corrosion resistance of 2101 lean duplex stainless steel and 410 martensitic stainless steel were studied and compared in 1M – 6M H2SO4 solution by coupon measurement for application in extreme process environments. Data obtained showed 2101 duplex steel is significantly more resistant to corrosion at lower concentrations (1M and 2 M H2SO4 solution) of the acid solution with final corrosion rate values of 0.000010 mm/y and 0.00028 mm/y compared to the values obtained for 410 martensitic steel at 0.0019 mm/y and 0.0738 mm/y. H2SO4 concentration at 4M - 6M narrowed the margin between the corrosion rates of both steel with final values of 0.0235 mm/y, 0.0326 mm/y and 0.0459 mm/y for 2101 duplex steel, and 0.0479 mm/y, 0.0482 mm/y and 0.0511 mm/y for 410 martensitic steel which signifies the corrosion resistance of both steels are comparable and generally similar at higher concentrations of SO4
2− anions. Statistical analysis through analysis of variance shows H2SO4 concentration strongly influence the corrosion rate value of both steel compared to exposure time which has limited influence.
Experimental investigation and finite element analysis of Magnesium Alloy (AZ31B) in Micro Electrical Discharge Machining μEDM)
Authors: Izzuddin Z , Azuddin M 
Published: June 2020

Abstract
Electric discharge machining (EDM) is a non-conventional machining use thermal energy from overheated electron source to remove small portion of material. EDM process has an advantage on high geometric complexity and micro leveling of dimensioning. The present of thermal energy to eliminate the unwanted material in EDM are highly depending on heat affected zone. This can contribute to decreasing of the product quality with surface roughness and micro crack existing after machining. Magnesium alloys (AZ31B) material has the special characteristic to explore the heat distribution effect on the heated surface. Finite element analysis with heat flux Gaussian boundary condition is applied to understand the governing equation of the heat behavior. At the same time, finding the size of spark created on the AZ31B gap is studied. The ANSYS software applied to simulate the heat distributes on the AZ31B surface. The simulation of ANSYS indicates potential zone of material removal through heat distribution. The simulation is compare to the actual experimental of μEDM and finds the similarities. The heat distribution on AZ31B with different size of spark shows a good agreement between simulation and experimental results.