bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Analyze of Relationship between Revenue and Customer Payment Methods in Small Medium Enterprise Based on Clustering K-Means
Authors: Marisa Fitri , Sakinah Syed Ahmad Sharifah , Izzah Mohd Yusof Zeratul , Mohammad Akhriza Tubagus , Purnomowati Wiwin , Kumar Pandey Rakesh 
Published: July 2021

AbstractBusiness capital and revenue are not only the decisive of the health of SMEs but also they must be balanced. In general, customers find their benefit from the flexible payment methods while on the other hand the SMEs should get their benefit too. So that, it needs to be studied whether it is necessary for SMEs to get their profit in accordance to this situation. One of the methods that suitable to be applied is by applying customer groupings based on revenue and payment namely the K-means clustering method since it can raise several groups that have not been known before. This information is useful for SMEs to be utilized based on their needs. Data in this study were gathered from customer attributes, number of transactions, and payment methods. The number of centroids was 3. The grouping results were stopped at the 5thiteration. The finding showed that the ratio value of the 4thiteration and the 5thiteration having the same ratio value, 0.07393. From the results of the iterations can be found; first, based on the customers’ number, the groups can be classified into three C1(18%), C2 (45%), C3 (36%). Second, based on the average number of transactions, post-paid payments was in the first rank (12.7 / week). From the results, it can be analyzed that this situation is burdensome for SMEs because the more the number of transactions, the more investment must be prepared for accounts receivable.
Analysis Of Drug Data Mining With Clustering Technique Using K-Means Algorithm
Authors: Lia Hananto April , Assiroj Priati , Priyatna Bayu , Nurhayati  , Fauzi Ahmad , Yuniar Rahman Aviv , Shofiah Hilabi Shofa 
Published: July 2021

Abstract
Data processing is very important in the development of information technology. Almost all fields of work have information data. Data can be used to help analysis in work. At present, health information data is very important to be processed in order to help medical personnel to make decisions. So that the results of the right decision to help patients. Lately, drug data has been misused for information eliminating a depressed patient without a doctor’s prescription with a total data of 53766. The results shown are very large. So it requires very much attention from the government. As a result of the deviation of information and applied to the patient will result in death. Therefore, research needs to be conducted to group data on drug data. The source of research data is obtained from the UCI Machine Learning Repository Education website. The method proposed in this research is data mining. This solution can help researchers in the analysis of these data. One technique in data mining with clustering is using the K-means algorithm. The variables used are drug name, condition, useful count. The first research results can classify three categories consisting of using the highest drugs, using medium drugs and using lace drugs. Then the accuracy of the data is obtained with condition 99.45% valid records 53471, drug name 100% with valid records 53766, useful count 100% with valid records 53766.
Pineal Eye for Blind using Ultrasonic sensors
Authors: Sahana M S , Tejaswini S , Bhanu H S , Bhargavi K , Praveena K S , Jayanna S S 
Published: July 2021

Abstract
In regular day to day existence, blind individuals face various issues for their navigation. The fundamental aim is to acquire a gadget which is suitable for the entire visually impaired community. Ongoing occasions, they have developed various gadgets to help. However, most of them have certain issues and limitations, and it needs a lot of training to utilise. The normally existing strategies are difficult to utilise, so as to defeat with their confinements we have to propose another framework that gives less reliance on their day-by-day exercises. This system is proposed to build a device that helps the blind navigate and use public transport with ease and certainty.
Comparative analysis of CNN and Viola-Jones for face mask detection
Authors: SivaKumar M , Saranprasath N , Sridharan N S , Shanmuga Praveen V 
Published: July 2021

Abstract
According to the World Health Organization, the Coronavirus (COVID-19) pandemic is causing a worldwide emergency, and one safe way to cover oneself is to wear masks. This pandemic constrained governments everywhere in the world to force lock-downs to avoid the transmission of infection. Reports show that wearing masks at work diminishes the danger of infection. We assemble our model by utilizing the concept of deep neural learning and AI. The dataset comprises pictures with masked faces and non-masked faces. Several computer algorithms are there for face detection. But this analysis centers around two of the most widely recognized procedures: The Viola-Jones algorithm and the Convolution Neural Networks. We will check whether the individual in the image/video wears a mask or not with a CV and Deep neural learning. Not only finding out about face mask detection, but this project also introduced the chance to delve into the field of computer algorithms.
A Study on Different hardware and Cloud based Internet of Things Platforms
Authors: Payal Ravi , Singh Amit Prakash 
Published: July 2021

Abstract
This paper talk about various types of available Platforms related to Internet of things. For running various Internet of thing applications, there is a need of Hardware platforms and Software Platforms. Various types of Cloud based Internet of things (IoT) platforms are available. These IoT platforms are used for creating various types of research applications, scientific applications etc. Paper is divided into three main sections, first section discuss first about IoT, second section tells about various types of cloud based Internet of things (IoT) Platforms and third section talks about hardware platforms. Comparison between of Latest Cloud based IoT platforms is done.
Driver drowsiness detection system with opencv and keras
Authors: Vishnu R. , Vishvaragul S. , Srihari P. , Nithiavathy R. , Asmitha shree R. 
Published: July 2021

Abstract
Drowsiness of the drivers is the principal cause of injuries in the world. Because of loss of sleep and tiredness, drowsiness can occur even as riding. The first-rate manner to keep away from accidents because of drivers’ drowsiness is to come across drowsiness of the driving force and warn him before fall into sleep. To discover drowsiness many techniques like eye retina detection, facial function recognition has been used. Here on this paper, we suggest a way of detecting motive force drowsiness, the usage of eye retina detection and pulse charge detection of the driving force. On this record, we endorse an extra accurate drowsiness detection approach which is a hybrid technique of eye retina detection and pulse sample detection.
Sensor based Automized Solar Water Management System
Authors: Murugan K , Jeevitha E , Harini R K , Aswath S , Kabilesh B 
Published: July 2021

Abstract
Automized hot water management system is an automatic system for management of water, to form our standard of living simple and economical. The automated use of water referred to as water automation that may be a method to make sure the right use of water and scale back the human effort. The solar water heater may be a device that uses alternative energy to heat water for domestic, commercial, industrial desires and numerous desires. In solar heater, we do not get plight instantly. It’ll nearly take twenty liters of traditional water to produce plight in sunny days and in cloudy days quite fifty liters of water. On a median someone wastes 0-45 liters of water per day, nearly one hundred twenty five million liters of water wasted daily. In our system once there’s no availableness of plight from solar heater the cold water is taken to electrical heater and plight is made to user. Temperature sensor device is mounted on the faucet to acknowledge whether or not the new water is ready or not. The main objective of our project is to save lots of water and to form economical usage of water while not wasting.
Hybrid Chinese text classification model based on pretraining model
Authors: Zhaoye Xing , Xiaoqun Liu , Peijie Sun 
Published: July 2021

Abstract
In order to solve the problems of fuzzy boundary of Chinese words, polysemy of one word and the inability of traditional models to reflect the importance of each word in the text, a hybrid text classification model based on Ernie CNN and bilstm attention (mecba) is proposed. Firstly, Ernie model is used to generate the corresponding word vector, which can retain rich semantic information and enhance the semantic representation of words. Then, the word vector is input into CNN to extract local information, and the context feature is extracted by bilstm attention, and the output of the two is spliced; Finally, softmax classifier is used for classification. The experimental results show that the model is better than CNN, bilstm and other classification models, and can effectively improve the performance of Chinese text classification.
Research on Location Convergence Method Based on BeiDou Navigation System Satellite Enhancement
Authors: Hu Bo , Li Guangye , Cui Wenjun , Wang Tao , Zhang Jiaxin 
Published: July 2021

Abstract
Through mobile communication data transmission, the precise ephemeris and precise clock offset of the IGS website are obtained in real time, and the BeiDou star-based enhanced differential data is obtained through the receiver antenna; then a combination of dual-frequency ionospheric non-difference observations is used to eliminate the impact of the ionosphere. The average clustering algorithm is used to classify the location results, and the center point of each cluster is obtained. The center points of each cluster are added and averaged to get the starting point of PPP convergence. Finally, the fast convergence of PPP positioning results is achieved by using hatch algorithm.
Traffic signal image detection technology based on YOLO
Authors: Gao Hui , Wang Wenhao , Yang Chengjin , Jiao Weile , Chen Ziwei , Zhang Tong 
Published: July 2021

Abstract
The detection and recognition of traffic signal image is an important content in intelligent transportation system. It can be applied to driver assistance system to effectively recognize traffic signal signs on the road, so as to reduce the occurrence of traffic accidents. At the same time, it also provides strong technical support for the future unmanned driving system. The main content of this paper is based on the deep learning method, using YOLOv3 and YOLOv4 algorithm to detect and recognize the traffic signal image on the road. The experimental results show that the recognition result of YOLOv4 network is better than that of YOLOv3 network.
Image registration of SAR and Optical based on salient image sub-patches
Authors: Ge Yuchen , Xiong Zhaolong , Lai Zuomei 
Published: July 2021

Abstract
As a fundamental and critical task in multi-source image fusion, the registration of optical image and synthetic aperture radar (SAR) image can identify corresponding identical or similar structures from two heterogeneous images. Although Pseudo Siamese network has achieved notable success in matching heterogeneous images, the network prone to mismatch when there are blurred, duplicate or similar scenes appeared in the search image. To improve the performance, in this paper, the OPT-to-SAR image pair is cut into sub-patch pairs through a pre-defined sliding window. Then a two-stage image filtering mechanism is proposed to maintain candidate sub-patches with ideal texture information. After sending all the qualified sub-patch pairs into the Pseudo Siamese network, the final matching result will be passed through a RANSAC module. In this way, the interference from invalid image areas can be reduced and the model robustness can be ensured by using the statistic information of the whole image pair. A series of experiments conducted under various data scenarios proved the effectiveness of the method.
Geological hazard risk assessment based on GIS in Mianchi County
Authors: Liu Yingran , Sun Yu , Dong Qi , Wei Ningyu 
Published: July 2021

Abstract
The probability of surface collapse, landslide, collapse and debris flow is very high in hilly and mountainous areas of Mianchi County of western Henan province. The article obtained geological hazard district of Mianchi County though the analytic hierarchy process(AHP) to carry on the geological hazard risk assessment in the study area. Eight disaster-inducing factors were selected the density of disasters, slope gradient, slope height, slope shape, rock-soil body types, vegetation index, rainfall index, and engineering activity intensity based on the GIS platform and combined with the field investigation result of geological disaster points.
Counting of Pine Wood Nematode Disease Trees Based on Threshold Segmentation
Authors: Yu Bowen , Liu Yifan , Zhao Tong 
Published: July 2021

Abstract
Pine wood nematode disease is a very contagious and devastating forest pest. Finding infected trees in time, counting them, and clearing or selective cutting according to different diseased tree densities is the main way to control the spread of the disease. In this paper, threshold segmentation technology is used to reduce the adverse effects of interference factors such as buildings, rocks, and soil in the data set on density estimation, and finally a higher-quality density map is obtained to realize the counting of pine wood nematode diseased trees. Compared with the classic density estimation algorithm, the mean absolute error of this algorithm has dropped by 9.2, the root mean square error has dropped by 7.4, the variance of absolute error has dropped by 65.0, and the counting accuracy has increased by 19.6%.
Application Analysis of Virtual Simulation Training Platform in Practical Teaching
Authors: Liu Juan 
Published: July 2021

Abstract
This article starts with the application of virtual simulation training platform to practical teaching, and analyzes and researches the integration of practical teaching and virtual simulation technology. This article briefly describes the significance of integrating virtual simulation training platform into practical teaching, the specific path of applying virtual simulation training platform in practical teaching, and the precautions of virtual simulation training platform in practical teaching application. The author hopes that this article can provide a feasible new path reference for advancing the application of practical teaching in the new era.
Exploration and Research of Noise Automatic Processing Algorithm Based on Multi-scale Convolution Neural Network
Authors: Huang Jing , Chen Bidong , Tan Meijuan , Liu Miao , Jia Chao 
Published: July 2021

Abstract
This paper introduces the secondary development process of simcenter Test.Lab software. Using simcenter Test.Lab software’s multi language support and its advantages in noise test and analysis, combined with computer image recognition technology, an automatic noise processing algorithm system (LMS Test.Lab) based on Simcenter Test.Lab software test data is developed. The system is simple to use, high accuracy of data recognition, and can intelligently judge specific abnormal conditions. Engineers can use the secondary development program to do intelligent processing of specific data and automatic generation of test reports, which effectively improves the accuracy and efficiency of automatic data processing.
Path guidance based on landmark user preference fuzzy entropy weight model
Authors: Wei Chang , Wei Bo 
Published: July 2021

Abstract
Compared with electronic map or static point of interest (POI), the path guidance integrating landmarks with salience features can reduce the cognitive burden better. However, due to the influence of various factors on the significance of landmarks, specific mathematical formulas need to be constructed, and there is no unified formula construction standard. To solve this problem, considering the consistency of the idea between multiple factor comprehensive of landmark and multiple constraint optimal scheme decision of fuzzy decision, this paper constructs a fuzzy entropy weight model of landmark based on user preferences, which the actual values of landmark significance are converted to vague set values, and the weights of landmark factors are determined by fuzzy entropy of Vague soft sets. Subsequently, the landmark preference model and path guidance model are obtained and applied in the case of path guidance. Compared with the mathematical formula, the constructed landmark user preference model by fuzzy entropy of Vague soft sets reduces the construction complexity, and is an effective method to realize landmark preference and apply in path guidance.
Research on Crop Disease Classification Algorithm Based on Mixed Attention Mechanism
Authors: Chen Zhen , Cao Maoyong , Ji Peng , Ma Fengying 
Published: July 2021

Abstract
The prevention and control of crop diseases is an important measure to ensure the yield of crops, and the prerequisite for achieving this link is to improve the accuracy of crop disease identification. This paper constructs a new hybrid attention mechanism by realizing the serial connection of Spatial attention and Efficient Channel Attention (ECA)and proposes a new hybrid attention module Spatial_Efficient Channel Attention (S_ECA). This module is combined with the neural network to improve the disease classification and recognition ability of the network model, the network stability, and the overall performance of the network. In the classification of a part of the data of the crop disease data set in the 2018AI_Chllenger competition, a classification accuracy of 87.28% was achieved, which is an increase of 0.78% compared to the original network, thus verifying the effectiveness of the algorithm in this paper.
Application of Big Data and Artificial Intelligence Technology in the Prevention and Control of COVID-19 Epidemic
Authors: Wang Xiaoshu 
Published: July 2021

Abstract
This article analyzes the content related to big data and artificial intelligence technology. The author studied the characteristics of the COVID-19 epidemic, epidemic characteristics, and transmission routes. The author has studied the use of big data and artificial intelligence technologies in genome sequencing and analysis, intelligent medical diagnostic services, vaccine research and development and drug screening, reasonable scheduling of anti-epidemic resources, epidemic monitoring and early warning analysis, epidemic prevention inspection robots, unmanned delivery models, and epidemic robots Specific application. The purpose of this article is to give full play to the value of big data and artificial intelligence technology to improve the prevention and control of the COVID-19 epidemic.
Application of Computer Virtual Technology in Ceramic Packaging Design
Authors: Xiong Limei 
Published: July 2021

Abstract
At present, with the continuous development of science and technology, computer virtual technology has become one of the indispensable components in ceramic packaging design. These computer virtual technologies play an important role in the process of ceramic packaging design, effectively improving the efficiency and quality of ceramic packaging design, and the significance of its in-depth research is self-evident. Based on this, this paper discusses the application of computer virtual technology in ceramic packaging design. Firstly, it briefly discusses the related contents of ceramic packaging design and its basic design principles. Then, taking the actual product design as an example, it discusses in detail how the commonly used Rhinoceros and V-rayforrhinoceros can be effectively applied in ceramic packaging design, can be effectively applied in ceramic packaging design and their final results, with a view to providing reference for similar work in the future.
A WebGIS-Based Platform for Sewage Treatment Facilities in Villages and Small Towns Near the Lake Dian
Authors: Luo Wei , Liang Hong , Xu Wenjie , Kang Xiaolin 
Published: July 2021

Abstract
Lake Dian is one of “Three-river and Three-lake Project” that focus on water pollution prevention and control in China. Rural non-point source pollution is increasing year by year. In order to effectively control the amount of sewage from villages and small towns entering the lake, a full coverage of treatment facilities has been built near the Lake Dian. Among them, the facilities are scattered in the eight districts and two counties of Kunming City, Yunnan Province. It is so difficult to manage that we have to rely on WebGIS technology for management and analysis. This paper designs a visualization platform for sewage treatment facilities in villages and small towns, which is a three-tier system architecture of B/S model. The system takes the map engine of ArcGIS API for JavaScript and the component development of Vue.js as the technical core, combined with ArcGIS Online service portal and spatial database technology. It finishes function implementation such as the visualization of the treatment situation and data management. The platform can scientifically analyse the problems in the construction, management, and operation of sewage treatment facilities in villages and small towns. It improves the ability to share information, and provide decision-making support to the sewage treatment department of the Lake Dian.
Interest Contour Region Fusion Method based on Gaussian Mixture Model Segmentation
Authors: He Xinyu , Chen Shu , Li Yi 
Published: July 2021

Abstract
This paper presents an edge feature light-shadow fusion algorithm based on image segmentation. A new edge light shadow feature fusion algorithm based on image segmentation, morphological operation and image filtering is presented to extract target objects from image and fuse them with new background, which is cumbersome, difficult to operate, and lack of fast and effective target acquisition and feature fusion methods. The algorithm first labels the input image through an interactive system, then divides the labeled image to get the image target information, then processes the target object, obtains the edge of the target object, expands the edge to form a mask, combines the target object with the background, and filters through the edge mask to achieve the effect of fusing the target object with the background. The experimental results show that this method can process images with different complexity, not only to generate a combination of portrait and monochrome background, but also to generate a combination of other objects and natural scenery, so that the image can produce transitional natural effects.
Research on Workpiece Assembly Application Based on Machine Vision
Authors: Yang Hongwei , Hui Shuai 
Published: July 2021

Abstract
A workpiece assembly system based on machine vision is designed to resolve the difficulty of manual clamp and high requirements in the industrial production line. The system applies the template matching algorithm into positioning detection of the two workpieces, automatically assemble and unload after secondary calibration. Compared with the manual operation, the system has reduced operation difficulty greatly, and the speed and repeated assembly accuracy are greatly improved, which can meet the requirements of the production line.