bluuebunny/crossref_metadata_2025_split huggingface dataset:
Floor Area – Carbon Emission Relationship of Multi Residential Buildings for a Typical Metropolis: A Case of Surat City
Authors: Pastagia D. 
Published: September 2021

Abstract
Energy utilized in private division in India is ever expanding, as 43 percent of all out energy is utilized for air dissemination framework in residential buildings. Be that as it may, two current advancements increment the significance of outflows stages in all structure structures they are immediate and backhanded CO2 discharges relying upon numerous boundaries. The energy execution of a home, volume of a house, number of apparatuses [electricity utilization, fuel utilizes (gas utilization), and number of occupants] are the components thought of. A field investigation of various housing forms in the Indian setting is directed to gather information dependent on different variables. Additionally, conversations on current state of energy utilization conduct in Indian abodes are featured. Based on information investigation, discharge models are created through relapse strategy to streamline arranging and planning of vitality use exercises in private homes.
IoT based real time low cost home quarantine patient aid system using blynk app
Authors: Zaveri Karan A. , Amin Mihir H. , Amin Margiv S. , Patel Mansi R. 
Published: September 2021

Abstract
Recently, the world has been hit by COVID-19 pandemic. Nearly about every country has been devastated as they lack a proper health infrastructure. India is one such country where overpopulation is the key reason not everyone has access to medical facilities and are therefore forced to home quarantine. IoT is an ingenious technology which opens a new digitised path in terms of data storage and processing in today’s medical world to provide the healthcare systems with the best networking techniques. In this present paper, the authors have created a framework of body temperature, oxygen saturation level (SpO2), BPM (heart rate) and air quality sensors based innovative smart disease surveillance system with amalgamation of nodeMCU. The obtained output is displayed on the LCD display and additionally with the aid of IoT-cloud based app (blynk) the doctor can monitor real time health data. Also, a key feature named Report generates and sends the readings in CSV/Excel format. The health parameters of the proposed prototype have a maximum deviation of 1%, is cost-effective, portable, reliable and high functionality as compared to the commercially available one.
Detection Of Albumin And Urea Concentration In Urine Using 2d Photonic Crystals
Authors: Sharma Sanjeev , Gupta Shradha 
Published: September 2021

Abstract
A biosensor has been created for the detection of albumin and urea in urine by using 2-D photonic crystal. The refractive index of whole urine is a function of wavelength, it constitutes such as albumin, urea etc. for sensed transmittance, quality factor and power efficiency. In case of albumin and urea in urine, the concentration varies with respect to the refractive index of urine. The resonant wavelength as well as transmission efficiency of the biosensor is shifted towards the higher order of wavelength region when the refractive index of urine component varies from high to low. It’s also observed that both albumin and urea in urine have a low quality factor, high transmission efficiency and good sensitivity.
Development of Pervasive IoT Based Healthcare Monitoring System for Alzheimer Patients
Authors: Yadav Piyush , Kumar Pratik , Kishan Prem , Raj Prince , raj Utkarsh 
Published: September 2021

Abstract
Alzheimer is a neurological degenerative disease that steadily and gradually progresses. This disease is incurable at present and those who suffer from it have the hesitation to travel beyond their homes in comparison to normal people. The main aim of this paper is to offer a continuous mechanism that enhances the Alzheimer patient’s quality of life as well as that of their caregivers. Proposed work is based on the Internet of things (IoT) based sensors data that figure out different parameters of the patient body like temperature, blood pressure, striding action, striding speed, and so on. All these sensory data will be obtained with the help of the Atmega Microcontroller. All the collected data are then sent to the cloud server with the help of parallel communication for data analysis. The desired parameter of the patient is retrieved which will help in providing real time support to the patients.
Influence of N-Butanol Composition on Membrane Performance in Coagulation Bath for Membrane Distillation
Authors: Dayanandan Nanditha , Palanisamy Kavin Kalyaan Marappan , Kapoor Ashish , Sivaraman Prabhakar 
Published: September 2021

Abstract
Membrane Distillation is one of the extensively used desalination technologies for the utilization of the waste heat in the industries. The membranes used in for membrane distillation have to be hydrophobic in nature so as to permeate only vapour through the membrane pores. In this background, there is a necessity to develop membranes with better hydrophobicity and mechanical strength for overall performance. In this paper, we discuss the preparation of polyvinylidene fluoride homopolymer by phase inversion technique using N-methyl pyrrolidone as solvent. Water and n – butanol in varying compositions by weight percent from 0 to 100% is used as non-solvent. Contact angle and permeate flux were measured for the synthesized membranes. The results indicated that the membranes made of PVDF immersed in 100 % n-butanol coagulation solution shows good hydrophobic behaviour and also achieved higher permeate flux compared to the other membranes reported in literature.
Analogous Research of Classical PI Controller and Fuzzy Logic Controller to Control the Speed of D.C. Servo Motor
Authors: Dipraj  , Singh Anurag , Singh Rishikesh Kumar , Sharma Savitri 
Published: September 2021

Abstract
Servo motors are widely used in several fields such as industrial, electronics and robotics etc. The precise positioning & speed control of servo motor is compulsory for desired result and output. In this study, the speed control of dc servo motor is compared utilizing two different controllers. First is a classical PI controller while the second one is a fuzzy logic controller (FLC). PI controller and FLC both can be utilized for controlling the speed of servo motor. Both techniques provide good results but the fast response for the proposed calculation is achieved by the fuzzy logic controller. MATLAB/SIMULINK provide the conventional tool to analyze the model precisely so that the performance of servo motor is satisfactory. The performance of both controllers is compared and analyzed on different parameters such as speed, current for DC Servo Motor.
A review on elicit potentials in the brain to recognize Brain-Machine interface
Authors: Jafar Mohd Rizwan , Srivastava Ashish Kumar 
Published: September 2021

Abstract
Brain-machine interface is a technique with the help of which a user can generate a control signal to operate a machine by manipulating its state of cognition. In this technique, electrical signals generated in the central/peripheral nervous system are used to generate commands to interact with machines. In this paper, authors reviewed this technique in detail to find out the state of the art. This paper is written in such a way that a beginner can understand what a brain machine actually is. In this paper different types of methods to elicit signals for brain machine interface is explained along with different types of methods to record the signals. It is also described the state of the art in feature extraction and classification methods used in brain machine interface.
Real Time Vehicle Recognition System for Secure Environment
Authors: Rai Amrita , Agrawal Reshu , Karatangi Shylaja V. , nayak Seema 
Published: September 2021

Abstract
An automatic system based on “Digital Image Processing” technology is developed using MATLAB tool to recognize the vehicle by identifying the license plate. A database is linked to the MATLAB processor, which takes input as the detected number plate. Information about the owner is extracted and electronic format of the challan is generated if the number plate is in wrong format. Also in case of theft or crime, the required number plate is fed to the database system and if it is matched with the detected number plate, an alert is generated. The captured image is in RGB format which is converted into grey scale. Here theories and techniques used to identify the area and Edge detector operators is used to measure threshold values to get the dilated image. After that flood fill operation can be used to stuff the wholes to get a fine binary picture. The fundamental steps to identify the vehicle license plate and plate size, then the partitioned picture is amplified with gray scale only to get the license plate of vehicle. Afterwards the template matching process done to match the image from license plate and template’s picture, thus the number plate detected is then matched with one stored in the database system to get complete information of the vehicle owner. The first section in your paper.
Investigation of dynamic behavior of Hollow Rotor Shaft System through FEM
Authors: Gupta Ashish , Yadav Viswajeet Singh , Chauhan Sandeep 
Published: September 2021

Abstract
Generally, there is two kinds of rotor system used for transforming the power from one source to another, one is solid rotor system, and another is the hollow rotor shaft system. In comparison to solid shaft, the hollow shaft is of less weight, for a given diameter and length. In addition, the hollow shaft has a larger Strength to weight ratio and has a greater polar moment of inertia. Thus, they can transmit more torque compared to solid shafts. The main purpose of this paper is to analyze the dynamic behavior of hollow shafts with a particular interest in estimation of damping. This study also evaluate the dynamic response of different rotor thicknesses at various speeds where hollow shafts and solid shafts modelled through ANSYS 16. The proposed analysis performed in both frequencies as well as time domains, in which the Campbell diagram, the critical speed, and the orbits are numerically determined. Further, this study also illustrates the convenience of the hollow shafts at different inner diameters for rotor dynamics applications. The analytical results (ANSYS 16) were validated through the experimental results.
Low-Cost Asset Tracking and Inventory Management System (ATIM)
Authors: Vadi Vivek , Kotadiya Ayush , Solanki Rajdipsinh , Khambalkar Mohan M. 
Published: September 2021

Abstract
In any supply chain, the warehouse is the main component in linking the chain partners and nowadays it acts as a competitive factor. Current Inventory management Systems are slow, inefficient concerning managing and tracking the huge demand for large inventory traffic and hence make a poor customer experience while managing large, urgent and important inventories. Internet of Things (IoT) is a promising technology that can be used in the context of Industry 4.0. This paper aims to improve inventory management efficiency multi-folds and enhance stock SCM (supply chain management) analysis for market planning. This solution strengthens store operations & inventory management smartly, safely and efficiently. Also, the blocks and layers of IoT are illustrated. Finally, the benefits and challenges of implementing IoT in the SCM and the warehouse are discussed.
Design and Implementation of a SSH Proxy System Based on B/S Architecture
Authors: Cui Wenchao , Gou Minghao 
Published: September 2021

Abstract
The SSH protocol is one of the most commonly used protocols in the current operation and maintenance process, but the commonly used SSH clients are all implemented based on the C/S architecture, which causes the operation and maintenance personnel to face cross-platform problems, and when accessing from the external network It is also necessary to develop corresponding VPN according to different platforms. This paper proposes a SSH proxy system based on B/S architecture. The client of the system is based on a browser, which solves the cross-platform problem of different clients and facilitates the use of remote operation and maintenance personnel.
AdaDiff: Adaptive Gradient Descent with the Differential of Gradient
Authors: Huang Dian , Yin Dawei , Zhang Lijun , Peng Dezhong , Li QiLin 
Published: September 2021

Abstract
Optimization methods are crucial to train deep neural networks. Adaptive optimization methods, especially Adam, are wildly used because they aren’t sensitive to the selection of learning rate and converge fast. Recent work point out Adam has a performance gap with SGD and even not converge because of the unstable and extreme learning rates. Many variants of Adam are proposed to solve the problem, such as AMSGrad, AdaBound and AdaBelief. In this paper, we propose a new variant of Adam, called AdaDiff. AdaDiff computing gradient descent step size by the exponential moving average(EMA) of gradient and differential of gradients aiming to make the training of networks more stable. We compare our method with other optimizers on various tasks. The results show AdaDiff outperforms Adam and minimizes the performance gap with SGD.
Collaborative filtering recommendation algorithm integrating user similarity and trust
Authors: Huang Mengge , Cao Kai , Zhang Jingyi , Zhang Chuanlin , Deng Tao 
Published: September 2021

Abstract
The rapid development of the Internet has brought convenience to people and has also produced the problem of “information overload”. In view of the traditional collaborative filtering algorithm facing some bottlenecks to be solved, this study proposes a collaborative filtering algorithm that combines similarity and trust. First of all, in view of the large deviation of traditional similarity calculation and prediction of user ratings, this study proposes an optimized Pearson correlation coefficient calculation method; secondly, the trust relationship is established based on the user’s rating of the common project, and the trust relationship between users who do not have a direct trust relationship is established through the transfer of trust; then find the nearest neighbor set of the target user through the fusion of user similarity and trust; finally, the item is scored and predicted to generate a recommendation list. Experimental results show that the algorithm proposed in this study can effectively improve the accuracy of recommendation.
Semantic Segmentation of Parking Lot Scene Based on Surround View System
Authors: Wu Jie , He Ye , Chen Xiaoan 
Published: September 2021

Abstract
Semantic segmentation of parking lot scenes is the prerequisite of environment perception for automatic parking technology. It provides environmental semantic information for automatic parking of vehicles. However, due to the dim light of the parking lot environment, unclear ground signs, road reflections and other factors, semantic segmentation such as FCN The method is not yet able to segment ground signs such as background and lane lines to meet the perception needs of automatic parking. This paper proposes a parking lot scene semantic segmentation method based on a surround view system. The surround view system consists of 4 fisheye cameras. The images acquired by each camera are subjected to distortion correction, inverse perspective transformation and image stitching fusion to obtain a ring view. Based on the ring view, a semantic segmentation algorithm based on attention and feature fusion is proposed. Experiments are carried out on a self-made parking lot dataset with a size of 1280x960 pixels. The results show that the method proposed in this paper improves the mIoU of the FCN model by 12.3%.
Facemask Detection using Inception V3 Model and Effect on Accuracy of Data Preprocessing Methods
Authors: Li Yongyuan 
Published: September 2021

Abstract
Nowadays, image classification done by Machine Learning can classify images within an instant after an efficient model is built. Such techniques can help identify whether a person correctly puts a mask on. During the Covid situation, it is important to ensure the people in public areas put on a mask correctly so it can cut off the route of mass infection. In this paper, three classes of image classification were tested: with mask, without mask, and mask-weared-incorrectly. Based on the Google Colaboratory platform and Inception V3 model, a three-classes-detect-model with 94.52% testing accuracy was built. In addition to building the models, the effectiveness of data preprocessing has also been tested. After applying different methods for data preprocessing, the testing accuracy for the two-classes-detector model improved to 97.11% but the three-classes-detector model decreased to 94.26%.
Research and design of a data desensitization system
Authors: Li Wei , Li Chuan 
Published: September 2021

Abstract
With the extensive implementation of SG186 Project and SG-ERP Project, State Grid has accumulated abundant data resources, and the hidden information in these data resources can create great value. But at the same time, the security of massive data has become more important. From the perspective of system design, workflow and key technology of power information desensitization system, this paper analyzes and studies the sensitive level and data type of sensitive information, matches the corresponding desensitization strategy and completes a series of operations of desensitization task, so as to realize the protection of sensitive data in power information under big data environment.
Optimization Research on Initial Seeds of the Database Management Systems Fuzzing Framework Squirrel
Authors: Song Manning 
Published: September 2021

Abstract
Squirrel is one of the most effective fuzzing frameworks for finding memory errors in database management systems. But its efficiency is affected by initial seeds significantly. In order to improve the fuzzing efficiency of Squirrel, we optimized its initial seeds. The main factors affecting its efficiency are the average grammatical distance and the number of texts of initial seeds. Increasing these two factors at the same time can greatly improve the fuzzing efficiency of Squirrel.
Design and Development of Water Supply and Drainage Virtual Simulation Training System
Authors: Xiong Wei , Zhang Hao , Liu Yi 
Published: September 2021

Abstract
Traditional practical teaching of water supply and drainage is often faced with problems such as limited faculty and course time, easy worn-out of equipment and safety risk in practical training, which brings many inconveniences to schools, teachers and students. In order to make up for the shortage of traditional water supply and drainage practical training teaching, the teaching environment and the process was simulated by virtual reality technology, and a virtual simulation training system for water supply and drainage was developed. Taking the course project of steel pipe threading as an example, this paper shows the construction situation of manual and electric steel pipe threading project, systematically explains the principle involved in the virtual training system of water supply and drainage, emphatically expounds the key technologies, and the implementation scheme was given.
A non-integer step ratio parallel computing method for hybrid finite-element and discrete-element on multi-core computer
Authors: Li Tong , Gao Ge , Jin Xianlong 
Published: September 2021

Abstract
Commercial finite-element and discrete-element software usually adopts a unified computational time step and limit the number of our computer cores. In the face of large-scale with refined scale computing models, this will undoubtedly increase the time cost. The multi time step method of integer step ratio is a method to deal with this kind of problem. A non-integer ratio multi-time step computing method based on domain decomposition and subcycling method is proposed and applied to the finite-element and discrete-element engineering problems. The whole model is divided into finite-element method (FEM) subdomains and discrete-element method (DEM) subdomains according to the load balance of CPU. A coupling region between adjacent domains consists of multiple boundary nodes and particles based on the non-integer step ratio. Boundary data in coupling region are transferred through MPI communication protocol. This method can make full use of the advantages of multi-core computer and improve the calculation efficiency of engineering software.
Topic Extraction of Online Curriculum Reviews
Authors: Wang Cheng , Zhou Ya 
Published: September 2021

Abstract
With the advent of the era of intelligent education, online learning has become a new way of learning. Online learning will produce a lot of review data, this paper focuses on how to correctly reflect learners’ emotional attitude towards the curriculum, this paper studies the mining of text topic emotion in MOOC course review data set. Firstly, the balanced algorithm is used for sample equalization, secondly, we use Albert + bilstm model to classify course reviews, finally, the LDA model is used to extract the corresponding topics. Compared with the experimental model, the proposed model has higher accuracy and stability. Machine learning method has some advantages, but the model is more complex, and it can be simplified in the future.
The Quality Evaluation of Online Book Reviews Based on Graph Neural Network
Authors: Zhang Can , Liu Wei , Mu Qi , Zhang Deshan , Meng Fancheng 
Published: September 2021

Abstract
With the development of the Internet, the way people read has changed, the readers are more and more willing to share their reading opinions via the reading platforms. However, as the continuous increase in the number of users and reviews on the book platforms, the review data is growing exponentially. It is difficult for people to find useful information quickly in the massive reviews. Therefore, using automated methods to identify high-quality reviews among a large number of book reviews has become a hot topic in current research. This paper studies a quality evaluation method of book reviews based on graph convolution neural network, which introduces the LDA document topic generation model to add topic nodes on the basis of review and word nodes, builds the relationship between the three nodes as edges to generate heterogeneous graph. The graph is sent to a two-layer GCN model for training. In the last, this article did experimental evaluation and analysis based on the book review data of non-commercial platforms. The results show that the proposed method is superior to the machine learning method and the traditional neural network model.
Security Service Function Chain based on Software-Defined Security
Authors: Zhu Sheng , Zhou Cheng , Wang Cheng 
Published: September 2021

Abstract
Software-defined networks face not only traditional network security threats, but also new network security threats brought by centralized and programmable control planes. To address the above problems, this paper proposes a business chain design mechanism for security protection functions based on software-defined security, which constructs a security service function chain according to user requirements and also realizes security resource scheduling according to the load of hosts, and the security service function chain rules classify and redirect network flows to corresponding security devices sequentially in the form of OpenFlow flow tables to realize network traffic Dynamic control of network traffic. The test shows that this mechanism can effectively realize security service virtualization and provide flexible and dynamic security protection mechanism according to security service requirements.