bluuebunny/crossref_metadata_2025_split huggingface dataset:
Preparation, Microstructure and Electrical Conductivity of LATP/LB Glass Ceramic Solid Electrolytes
Authors: Luo Jiajia , Zhong Yang , Chen Guohua 
Published: November 2021

Abstract
The Li2O-Al2O3-TiO2-P2O5 system glass ceramic solid electrolytes were prepared by adding Li3BO3 (LB) frits. The phase composition, microstructure and electrical properties of glass ceramics were investigated by using X-ray diffraction, scanning electron microscopy and AC impedance spectroscopy. The results show that the principal crystalline phase of all glass ceramic samples was LiTi2(PO4)3. The grain sizes of glass ceramic sample increase with the increase of sintering temperature. When the additive amount of LB is 1wt %, the glass ceramic solid electrolyte sintered at 950 oC shows the highest room-temperature ionic conductivity of 1.9×10−4 S.cm−1, which can be expected to be used in solid-state lithium-ion batteries.
Corrosion Behavior of 7075 and 2A12 Aluminum Alloys in Different Water Environments
Authors: Wu Zhipeng , Wang Shan , Zhen Nan 
Published: November 2021

Abstract
The corrosion of 7075 and 2A12 aluminium alloys are studied in three types of water, including freshwater lake water, salt lake water and saline lake brine in the Qinghai-Tibet Plateau region. The samples are immersed into the different water for different time, which are divided into four types of 30d, 60d, 90d and 120d. After undergoing dry and wet cycle immersion corrosion under natural conditions, it can be concluded that the two aluminum alloy samples have more serious corrosion in freshwater lakes, and 2A12 aluminum alloy is more corrosion resistant than the 7075 aluminum alloy. The corrosion is mainly pitting, accompanied by crevice corrosion and galvanic corrosion. Cl
− can pass through the passivation film on the surface of the samples to form pitting pits, while the dissolved Al
3+ in the matrix and

S

O
4

2
−

in the water can form stable Al
2(SO
4)3 ▪ xH
2
O, which plays a certain protective role for the sample.
Experiment and Research on Calculation Methods on Flexural Mechanical Behaviors of Non-Metallic Reinforced ECC Beams
Authors: Li Yang , You Yicai , Zhou Xiaoyong 
Published: November 2021

Abstract
Engineered cementitious composites (ECC) has high tenacity and the characteristics of strain hardening. In the bending test, ECC beams equipped with carbon fiber reinforced polymer (CFRP) in the tensile region show good deformation ability and bending ability. In this paper, the constitutive models of ECC and CFRP materials are established by uniaxial tensile compression test. Based on the plane section supposition, the analysis theory of bending capacity of cross section for ECC beams with non-metallic reinforcement is proposed. The calculation results are compared with the four-point bending test results. The results show that: (1) ECC beams with non-metallic reinforcement reflect the advantages of the two materials, and have strong deformation capacity before bending failure. (2) The calculation results based on the theory of flexural capacity of normal section are in good agreement with the experimental results, and the maximum error is less than 4%. The research results can provide the basis and reference for the calculation analysis and practical application of non-metallic reinforced high toughness material structure.
Research Progress on Microstructure Characterization of Silicon Carbide Fibers
Authors: Zhang Xingjian , Cai Zixi , Fan Jinjuan , Liu Changkui , Ye Jinfa 
Published: November 2021

AbstractCeramic matrix composites have excellent properties such as high temperature resistance and oxidation resistance, and have good application prospects in the hot end parts of engines. In ceramic matrix composites, the microstructure composition of silicon carbide fibers determines their macroscopic properties. Therefore, this article takes silicon carbide fiber as the research object, summarizes the existing SiC fibers structure, composition, and morphology characterization methods, compares the development and advantages and disadvantages of XRD, SEM, TEM and other testing equipment analysis, and proposes The problems of sample preparation, surface defects and internal structure changes in the microstructure characterization of silicon carbide fibers are discussed, which provides a reference for the preparation of high-performance SiC fibers and the improvement of their characterization work.
Architecture of a Spatial Disorientation Platform and Serious Game
Authors: Castañeda Claudia , Sánchez Natalia , Aviles Oscar F. , Mauledoux Mauricio 
Published: November 2021

Abstract
In recent years there have been several applications for the study of stabilometric mainly in the analysis of disorder, using mechanical structures of one or two degrees of freedom. An architecture of a stabilometric platform is proposed, which can acquire data through a virtual environment, in this case, a Snowboarding environment, since this sport provides greater balance, increases flexibility and strength in the muscles, and strengthens the lower limbs since it can have a displacement movement in one direction. Thanks to this environment, an architecture is proposed to execute several applications, focused on balance rehabilitation. As a result of this proposal, mathematical models were made by applying the Euler Lagrangian theory, and architecture was obtained that can acquire data in real-time, allowing to visualize this data through a sensor, which shows the position of the person with its respective movement. Also, with the implementation of the Self-Assessment Manikin (SAM) a preliminary study was conducted with 10 people in which 70% presented a discussion of different errors in the design and development stage in the virtual environment, also, 10% of the study population showed greater spatial disorientation to one side of the platform. Thanks to this, it was possible to modify the virtual environment and obtain a more efficient response by implementing this method. As future work, it is proposed to develop variable control systems on the platform and a trajectory variation in the virtual environment.
Model-based motion simulation of delta parallel robot
Authors: Makwana Mahesh A , Patolia Haresh P 
Published: November 2021

Abstract
For a parallel configuration of a robot manipulator, the solution of Forward Kinematics (FK) is tough compared to Inverse Kinematics (IK). This paper presents the model-based motion planning of a delta parallel robot in Simulink’s SimScape environment. A model was developed and simulated for motion study. The developed model has been simulated to solve the FK of the parallel manipulator and to check its efficacy. First, a helix curve has been planned within the reachable workspace. Then IK was solved to extract angular positions of the biceps. Obtained angular positions then fed to SimScape model to run a simulation. The path taken by the end effector of the system calculated by simulation is in good approximation to the planned helix path. Further, visual simulation and motion analysis of delta parallel robot can be performed by Model-based simulation and solves mechanical design as well control system design problems. Experimental study also shows that the circular path designed for experiment is well followed in real time simulation.
Design and Analysis of the Spray-Painting Robot for tall statues and monuments
Authors: Shah Darshita , Dave Jatin , Detharia Dipen , Majithiya Ashish 
Published: November 2021

Abstract
The painting on tall structures, statues, monuments and buildings is dangerous task for humans. Robotics finds its applications in operations, which are repetitive, hazardous, and dangerous. The aim of the present work is to design a manipulator for spray painting on surfaces of tall monuments, statues and structures. The robot can be installed on a crane platform for lifting and operated from the ground. A lightweight and compact design is desired that can be easily accommodated within the space of the crane. A Revolute-Revolute-Revolute-Prismatic (RRRP) type Robotic arm is developed and analysed for this application. By establishing the rigid body tree model in Robotics System Toolbox, the numerical model of direct and inverse kinematics using Homogenous Matrix Transformation is prepared in MATLAB. Using the spray patch method and offline programming method, the spray model is prepared in Solid woks to obtain trajectory waypoints. A B-spline path is generated through these waypoints. At each waypoint, joint displacement variables are calculated using an inverse kinematic model. An air-less spray gun is selected and attached with a robot. Controlled motion algorithm for spray painting operation on a circular surface were obtained with simulation results. A smooth trajectory for performing spray painting is obtained.
Jumping robot: A pneumatic jumping locomotion across rough terrain
Authors: Dilip R , Karthik Milan R , Vajrangi Arpit , Chavadi Karthik S , Puneeth A S 
Published: November 2021

Abstract
This paper presents a jumping mechanism using pneumatic actuators adopted in a traditional robotic vehicle’s frame. This is a skeleton for future development on this technology. This is a simple mechanism to overcome obstacles on its way in a robotic vehicle. As we know a traditional wheeled robotic vehicle can not over come an obstacle on ease as it doesn’t have an effective mechanism or it might take an other alternative long route to reach the target. This mechanism has an effective design to overcome obstacles comparing to the traditional robot vehicles. So this model has a higher mobility, flexibility and rapidity. This design has a new type of locomotion to it that is jumping along with wheeled movement which is not present in a traditional robot. This mechanism works from the real time information from the sensors. There are 4 double acting cylinders placed at equidistant from each other and mass distribution of the whole model has been equally divided and each cylinder has the same load. These 4 cylinders are pneumatically actuated as compressed air as source. When these cylinders are actuated there is rapid pressurizing which causes the jump. These cylinders are actuated when the relay receives signal from the sensor module that there is an obstacle ahead. As we know there are many kind of locomotion of robots are been developed these days like wheeled, tracked, crawling, walking and so on but all these robots have difficulty in overcoming obstacle on their way, if it is modified to overcome obstacle too their would be a complex design which in this model is not the case as it has a very simple design. This mechanism is designed to take over rough terrains and uneven and unknown terrains. As a overall outcome we were able to make the robot overcome the obstacles on its way in its unique way.
Design and simulation of disaster mitigation robot using machine vision
Authors: Avinaash M , Andrew D , Visnu S , Abrar M , Seenu N 
Published: November 2021

Abstract
The goal is to provide a robust mobile robot to assist recures in their operation by providing real time surveillance, remote operation as well autonomous operation. The mobile robot is capable of mapping using a LIDAR, this provides a map of the disaster zone which is then used to assess and provide a path planning for the most efficient rescue for the Mobile robot as well as the Rescuers. The built-in gas sensor reads the concentration of gases in the area, providing data on the environment in the disaster zone. The use of high definition cameras combined with Artificial Intelligence based image classification provides an edge in autonomous traversing and search and rescue. Disaster mitigation is an extremely dangerous task for the rescuers, a mobile robot such as LV-01 can be the difference between life and death.
AI powered IoT based Real-Time Air Pollution Monitoring and Forecasting
Authors: Mani Geetha , Viswanadhapalli Joshi Kumar , Sriramalakshmi P 
Published: November 2021

Abstract
Air is one of the most fundamental constituents for the sustenance of life on earth. The consumption of non-renewable energy sources and industrial parameters steadily increases air pollution. These factors affect the welfare and prosperity of life on earth; therefore, the nature of Air Quality in our environment needs to be monitored continuously. This paper presents the execution and plan of Internet-of-Things (IoT) based Air Pollution Monitoring and Forecasting utilising Artificial Intelligent (AI) methods. Also, Online Dashboard was created for real-time monitoring of Air pollutants (both live and forecasted data) through ‘firebase’ from the Google cloud server. The air pollutants like Carbon Mono Oxide (CO), Ammonia (NH3), and Ozone (O3) layer information are collected from IoT-based sensor nodes in Vijayawada Region. Time Series modelling techniques like the Naive Bayes Model, Auto Regression Model (AR), Auto Regression Moving Average Model (ARMA), and Auto-Regression Integrating Moving Average Model (ARIMA) used to forecast the individual air pollutants aforementioned. The data collected from the IoT sensor node with a time frame is fed as input features for training the model, and optimised model parameters are obtained. The obtained model parameters are again verified with new unseen data for time. The performances of various Time Series models are validated with the help of performance indices like Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). The machine learning algorithm flashed in Raspberry Pi-3. It acts as an edge computing device. The current air pollutants data and forecasted data are monitored for the next 4 hours through an online dashboard created in an open-source firebase from Google cloud service.
Terrain surveillance system with drone and applied machine vision
Authors: Viswanath Shreya , Krishnamurthy Rohith Jayaraman , Suresh Sunil 
Published: November 2021

Abstract
Road accidents are a major contribution to the Annual death rates all over the world. India, ranks first globally in the number of fatalities from road accidents. According to the Ministry of Roads & Transportation, India saw over 440,000 road accidents in 2019. As a result, over 150,000 lives were lost. Poor road conditions contribute to these directly and indirectly. In India, safety standards and conditions of roads are maintained by local bodies in a given area of jurisdiction. While there have been several attempts at improving the quality of roads, weren’t instrumental in giving proper results [42]. A recent study suggested that Artificial Intelligence (AI) might help achieve the goals. Some of the AI applications have had better results when powered with Computer Vision. While computer vision has been previously used to identify faults in roads, it is not widely implemented or made available for public use. Road inspection still largely remains a time-consuming manual task, hindering the maintenance process in most cities. Moreover, being unaware of unattended faults on roads is often the cause of road accidents, especially in rough weather conditions that make it impossible for drivers to visually gauge any dangers on their route. The proposed model uses a transfer-learning approach; using Mask R-CNN in identifying the defects at an instance level segmentation. As adding this, it requires less labelling and an additional mask helps in blocking out extra noise around the images. This paper trains a Mask R-CNN architecture-based model to identify potholes, discontinuous roads, blind spots, speed bumps, and the type of road--gravel, concrete, asphalt, tar, or mud--with a dataset of images obtained from a drone. The model is further trained to create depth maps and friction estimates of the roads being surveyed. Once trained, the model is tested on a drone-captured live feed of roads in Chennai, India. The results, once sufficiently accurate, will be implemented in a practical application to help users assess road conditions on their path.
Unmanned aerial systems in search and rescue applications with their path planning: a review
Authors: Ajith V S , Jolly KG 
Published: November 2021

Abstract
In recent days, the Unmanned Aerial Systems (UAS) is an emerging technology rapidly across many warfare’s and enable new civilian domains which include real-time monitoring, security, border surveillance, wildlife surveys, providing wireless coverage, weather monitoring, smart farming, surveying, search and rescue, products delivery, farming, and civil structure inspection. Initially, there were many challenges in the design and control of UAS as it lacks an onboard pilot for navigation. Now the condition is improved with the implementation of artificial intelligence techniques in path planning and their coordination. Unmanned Aerial vehicles (UAV) in UAS technology open up new potentials in a variety of fields. This paper presents a review of recent literature, starting with the introduction about the UAS and its types, components, developments, potential applications of UAV in search and rescue and the paper completes with a summary of the different path planning methods used in UAS.
Ocean Surface Cleaning Autonomous Robot (OSCAR) using Object Classification Technique and Path Planning Algorithm
Authors: Adarsh JK , Anush OS , Shrivarshan R , Mithulesh Krishnaan S , Akash JK , Arul R , Angalaeswari S 
Published: November 2021

Abstract
Increasing water pollution is one of the biggest concerns in today’s world. It leads to a variety of problems including an increase in the level of toxic concentration in the water. This paper aims to introduce a concept of an ocean/water body cleaning robot that attempts to classify the wastes using a camera with a custom machine learning model and segregate accordingly using separators while collecting them on the basket attached, that can be recycled on the base station. The robot can be deployed on any water surface thus making it more effective than a largescale ocean pollution cleaning technique. It can be used to clean up oil spills from shipwreck and pipeline leakage and can monitor the water quality of the particular location and send a distress signal to the base station if the readings are abnormal. The water quality data and the information about the type of pollutants from the machine learning model can be used to formulate local laws to reduce pollution and create awareness about the type of material that ends up at the ocean/water body.
Drowsiness Detection and Rest Stop Suggestion
Authors: Sabari Mathavan R B , Rohitram V , Ashhwath C , Sasikumar P 
Published: November 2021

Abstract
In recent years, driving accidents have been increasing gradually, with most of them due to drowsiness. To tackle this problem, various methods and systems were developed to alert the driver behind the wheels, and to prevent accidents. A few approaches include heartbeat monitoring, pulse rate check, blink, and yawn detector. This paper discusses a driver mechanism, which is capable of detecting fatigue in real-time, using the Eye Aspect Ratio – EAR – parameter, and also provides a database with an interface for managers to track drivers. When the driver is tired, an email will also be sent to the manager. On the drivers’ side, there will be a buzzer noise to wake the driver up and nearby resting locations will be shown to the driver. Further, mapping to the nearby resting location of the driver’s choice is shown, if the driver feels too drowsy and feels the need for rest. It is essential to fabricate and construct this complete system via IoT and OpenCV methods to address this issue.
Modelling and Simulation of Nonlinear Jump Phenomena of a Non-ideal Rotor Involving Fractional Order PD Controller
Authors: Ghosh Gaurav , Jha Abhishek Kumar , Dasgupta Sovan Sundar 
Published: November 2021

Abstract
Rotating machinery with high speed powered by industrial motors frequently suffers from instability by exhibiting non-linear jump phenomena, formally known as Sommerfeld effect. The drives whose excitation is a function of the system responses, referred to as non-ideal. The system dynamics of such systems exhibit a couple of complex and interesting features when the input power exceeds a critical value. The present research suggests a novel approach to study the efficacy of active magnetic bearing with fractional PD controller to suppress the instability caused by the Sommerfeld effect. The steady-state results obtained by solving the system characteristic equation numerically is compared with the transient analysis. Finally, root locus method is introduced to obtain the bifurcation points at which this kind of instability completely disappears.
Harnessing Energy from Everyday Life
Authors: Roy Madhusree Sankar , Mirunalini A R , Krishna Pavan Sai , Ghosh Ritama , Akash Saravanan B , Manna Shubham , Shwetha S , Sri S Varsha , Augusta Sophy Beulet P 
Published: November 2021

Abstract
Renewable energy will drive the future. The applications of mobile phone is no longer limited to communication between each other but can also be used on an everyday basis starting from grocery shopping to watching series for entertainment. Thus our mobile phones require constant charging of power. It is almost impossible to increase the mAh capacity of the battery indefinitely; therefore the need of a battery re-charging source is inevitable. The objective of this research work is to design a sustainable, portable charger in which power is generated with the help of piezoelectric sensors embedded into the shoes of an individual. The underlying principle is to transduce the pressure applied on the piezoelectric sensors to power. This power can be used to charge mobile phones using a USB cable at any convenient time. The light weight compatibility of the device makes it easily portable. In the proposed system, a grid of piezoelectric sensors of suitable size is incorporated in the shoes and an Android application is developed to monitor the power generated as well as to suggest the optimal walking pace for the user to increase power generation. The key highlight of this prototype is that it is user friendly and is paired with an Android application to facilitate maximum power generation.
Personalized Drug-Disease prediction using Multiple Linear Regression with ReLU
Authors: Vijaya S. 
Published: November 2021

Abstract
Predicting models for personalized Drugs related to specific disease are essential, as traditional methods are expensive and time consuming. The most challenging task in personalized medicine is predicting the status of disease from high dimensionality data. In the biomedical domain the association between drugs and disease plays a vital role as the same drug may treat similar diseases. For the good adaptability to complex and nonlinear behaviour data, Multiple Linear Regression method with ReLU Activation function is used for calculation and to fit the model with Drug –Disease dataset. Based on the results the drug or combination of drugs that treat a specific disease is predicted efficiently.