2022 Second International Conference on Advanced Technologies in Intelligent Control, Environment, Computing & Communication Engineering (ICATIECE)最新文献

{"title":"Research of Financial Robot Control System Based on Hopfield Neural Network","authors":"Xiangling Yu, Chenglei Wang, Shaojun Zhang, Tianxiang Niu, Shiqi Xu","doi":"10.1109/ICATIECE56365.2022.10047388","DOIUrl":"https://doi.org/10.1109/ICATIECE56365.2022.10047388","url":null,"abstract":"In order to improve the intelligence level of financial management, a financial service robot based on Hopfield neural network is proposed. The manipulator is one of the important components of the robot system, and the trajectory tracking control of the manipulator is the key problem for the robot to perform the follow-up work. Due to the influence of uncertain factors such as external interference, the trajectory tracking control of manipulator has poor stability, low accuracy and long time. Therefore, an improved HOPFIELD neural network trajectory tracking control method for manipulator is proposed. Using Lagrange function, this design defines the dynamic equation of manipulator system and establishes the dynamic model of manipulator. Using the term function of Newton algorithm, the system trains HOPFIELD neural network and realizes the trajectory tracking control of the manipulator. Combined with the principle of robot kinematics, HOPFIELD neural network is used to control the robot arm. Finally, the above scheme is verified by simulation. The results show that the financial service robot designed in this study can run normally, and the robot can realize the planning and control of the manipulator through the controller.","PeriodicalId":199942,"journal":{"name":"2022 Second International Conference on Advanced Technologies in Intelligent Control, Environment, Computing & Communication Engineering (ICATIECE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128355252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementation of PMSG Based Wind Energy Conversion System with Solar based Battery storage","authors":"Koduganti Aswita, P. Bhargavi, R. Mahalakshmi, V. Sailaja","doi":"10.1109/ICATIECE56365.2022.10046802","DOIUrl":"https://doi.org/10.1109/ICATIECE56365.2022.10046802","url":null,"abstract":"This paper illustrates the Wind Energy Conversion System (WECs) study and its designing. For this power generation process, overall system requires a Wind Turbine generator (WTG) and here a PMSG based Wind Turbine is usedamong different types of wind turbine generators. DC TO DC converter topologies (boost and bidirectional converters) connection is required in the Wind Energy Conversion systems as there are changes in the wind i.e., with variable wind speed and the load. The other way of generating electricity is throughthe solar array charging the battery, and the energy from the battery comes into picture when there is less wind or probably no wind i.e., at zero wind speed. The paper deals with powergeneration using both the Wind Turbine (WECS) and also a battery getting charged through the Solar Array. The major aim of the proposed work is to coordinate control techniques among system components like Wind Turbine Generator, DC TO DC converter topologies, battery controller etc. under various wind speeds. The MPPT technique is also employed to obtain maximum power and maintaining constant output DC voltage. The propounded work has been simulated and modeled with the help of MATLAB - SIMULINK software.","PeriodicalId":199942,"journal":{"name":"2022 Second International Conference on Advanced Technologies in Intelligent Control, Environment, Computing & Communication Engineering (ICATIECE)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125608303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ability to Apply Mathematical Modeling on Account of DBDT Algorithm","authors":"Yongming Lu","doi":"10.1109/ICATIECE56365.2022.10046921","DOIUrl":"https://doi.org/10.1109/ICATIECE56365.2022.10046921","url":null,"abstract":"In the era of big data, more and more information is shared, which provides sufficient resources for the development of social science and technology. All these dynamic developments are inseparable from mathematical models. In the information environment, students' modeling ability and consciousness are at the lower middle level. Improving this ability is a huge task to be solved. It is a good breakthrough to cultivate students' mathematical modeling application ability from the perspective of algorithm. Try to use algorithm theory to solve the suspicious and difficult points of mathematical modeling application ability. The research on improving the application ability of mathematical modeling on account of DBDT algorithm is a subject of contemporary significance, which must be strengthened. This paper studies the definition, concept and related knowledge on account of DBDT algorithm, and points out a series of knowledge and theories to improve the application ability of mathematical modeling on account of DBDT algorithm. In the text, the data is tested, and the results show that the improvement of mathematical modeling application ability on account of DBDT algorithm achieves 82.20%, 90.54%, 93.05% and 98.12% high efficiency in terms of system feasibility, innovation, fault tolerance and self-optimization performance.","PeriodicalId":199942,"journal":{"name":"2022 Second International Conference on Advanced Technologies in Intelligent Control, Environment, Computing & Communication Engineering (ICATIECE)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125292628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MIMO-NOMA oriented CRN Physical Layer Security on Imperfect CSI using Power Optimization and Beamforming Methods","authors":"Hitendra Agrawal, Manish Joshi","doi":"10.1109/ICATIECE56365.2022.10047600","DOIUrl":"https://doi.org/10.1109/ICATIECE56365.2022.10047600","url":null,"abstract":"To improve the PLS for a MIMONOMA-based CRN, this paper proposes a transmit-zero-forcing beamforming technique to message alignment, using the ideal channel state data available at the earth station. The above investigation makes use of a large constructability of several cells. Every group has a “primary user” and a “alternate user” who are responsible for implementing the CRN. Both the PU and SU of each cell are assigned locations at random. Finally, when only imperfect CSI is available at the ground station, we propose an eigen wideband technique to enhance the PLS for a CRN based on MIMO-NOMA. Optimal power allocation algorithms are created for both wideband methods to further improve the PLS. Finally, a closed-form expression for the probability of data lost due to Nakagami-m multi-path fading is presented. The following step involves contrasting the results of simulation studies and other methods currently in use with this statement.","PeriodicalId":199942,"journal":{"name":"2022 Second International Conference on Advanced Technologies in Intelligent Control, Environment, Computing & Communication Engineering (ICATIECE)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114236534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detection of Leukemia from Histopathological Image using Deep Learning Techniques","authors":"V. S. Kumar, Renukadevi S, P. Pareek, V. H. C. de Albuquerque, Deepak Gupta, Ashish Khanna","doi":"10.1109/ICATIECE56365.2022.10047425","DOIUrl":"https://doi.org/10.1109/ICATIECE56365.2022.10047425","url":null,"abstract":"Leukemia is a kind of cancer that is brought on by abnormalities in the body's white blood cells. An inspection of a blood smear that has been collected from the peripheral blood and then seen under a microscope is the method that is considered to be the gold standard for diagnosing leukemia. Techniques such as counting the cells in the blood and doing morphological analysis are two examples of methods that may be used to identify and diagnose leukemia. It is necessary to carefully examine a stained blood smear or an aspiration of bone marrow in order to correctly detect and diagnose leukemia. Both of these procedures involve the removal of bone marrow. This requires prior training and specialized expertise on the subject matter. A tedious and time-consuming operation, the manual evaluation of microscopic pictures of blood samples is one of the steps in the diagnostic procedure. The results are highly dependent on the degree of knowledge and experience that the laboratory worker has. Pathologists are often burdened with an excessive quantity of such data that has to be properly evaluated in order to arrive at a decision. This may be a time-consuming and difficult process. Red blood cells, white blood cells, and blood platelets are the three primary cell types that make up human blood. Platelets are also present in blood. Erythrocyte disease might refer to a collection of diseases that have an effect on hemoglobin. Hemoglobin is a protein found in red blood cells that is responsible for transporting oxygen to cells located throughout the body. This condition is referred to as sickle cell anemia. In sickle cell anemia, the blood contains abnormal hemoglobin molecules known as hemoglobin S. These molecules distort the structure of red blood cells, causing them to take on the form of a crescent or a reaping hook. There is a genetic form of anemia known as sickle cell anemia. This kind of anemia is caused by defective hemoglobin, which causes red blood cells to take on the appearance of sickles when oxygen levels are low. In most cases, the signs and symptoms of an erythrocyte disorder, also known as sickle cell disease, first appear in childhood. The detection of sickle cell anemia places an emphasis on analysis as a means of accurately diagnosing illness. Image processing with the CNN algorithm is what's being used to get this done. Techniques such as Plane Extraction, Arithmetic Operations, Linear Distinction Stretching, bar graph feat and world Thresholding, and Gray Level Co-occurrence Matrix are employed for classification in order to perform segmentation on the images. This is done so that the images can be divided into their constituent parts.","PeriodicalId":199942,"journal":{"name":"2022 Second International Conference on Advanced Technologies in Intelligent Control, Environment, Computing & Communication Engineering (ICATIECE)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123549610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Terrain Feature Extraction Method of Digital Transmission Line based on Depth Self Encoder","authors":"Tang Jie, Zhao Hanghang","doi":"10.1109/ICATIECE56365.2022.10047336","DOIUrl":"https://doi.org/10.1109/ICATIECE56365.2022.10047336","url":null,"abstract":"A terrain feature extraction method of digital transmission line based on depth self encoder is proposed. The proposed method adopts maximum likelihood estimation algorithm and minimum mean square error (MMSE) method, which can extract terrain features with high accuracy. The technology has been tested in three different cases, including case 1, where there is no obstacle in front of the transmitter, case 2, where there is an obstacle in front of the transmitter, and case 3, where there is an obstacle behind the receiver. The results show that for all three cases, features can be extracted with reasonable accuracy. This technique uses the depth information of a single channel to determine the height of a hill or valley in an image captured at different angles relative to the horizontal plane. The height is estimated by comparing the distance between points on two images taken at different angles and intervals","PeriodicalId":199942,"journal":{"name":"2022 Second International Conference on Advanced Technologies in Intelligent Control, Environment, Computing & Communication Engineering (ICATIECE)","volume":"215 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115585022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research and Design of English Auxiliary Learning System Based on Human-Computer Interaction","authors":"Yazhi Wang","doi":"10.1109/ICATIECE56365.2022.10047288","DOIUrl":"https://doi.org/10.1109/ICATIECE56365.2022.10047288","url":null,"abstract":"Computer assisted English learning is a new field of English teaching assisted by computer and its software technology. With the development of computer technology and the popularity of the Internet, computer assisted English teaching has increasingly become an important means of English learning and one of the hot spots of information technology research. It will change the existing English learning environment and teaching mode, and greatly improve the efficiency of students' English learning. The research on English tutoring learning system based on intelligent algorithm is a research carried out by researchers of Ljubljana University in Slovenia. The purpose of this study is to find out how to use different methods to improve English teaching. The main goal of the project is to develop an intelligent algorithm to help teachers improve their skills and students' English teaching ability. Researchers also want to know whether there are some differences in English teaching ability among more or less trained learners.","PeriodicalId":199942,"journal":{"name":"2022 Second International Conference on Advanced Technologies in Intelligent Control, Environment, Computing & Communication Engineering (ICATIECE)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129439953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Scale Space Mining Algorithm and Application Analysis Based on Computer Image Processing","authors":"Rong Fu","doi":"10.1109/ICATIECE56365.2022.10047458","DOIUrl":"https://doi.org/10.1109/ICATIECE56365.2022.10047458","url":null,"abstract":"In the process of computer IP(CIP), computer vision is used as the basis of image processing(IP). Images contain a lot of information, which is the basis for people to analyze image data. However, because images contain noise that affects the analysis results, intelligent extraction of image information has become the key to computer vision analysis of image data. According to the SS theory, this paper proposes three CIP algorithms, such as the EM image segmentation algorithm based on one-dimensional and multi-dimensional feature scale space(SS) and the IP algorithm based on adaptive multi-scale wavelet transform(WT). Compared with the other two algorithms, the three algorithms obtained the MSE value, PSNR value and SSIM value of the Q1 image. With the increase of the denoising level, the WT IP algorithm has the best denoising effect on the image, and with the increase of the denoising level. With the increase of sampling rate, the algorithm also has the best effect on image reconstruction.","PeriodicalId":199942,"journal":{"name":"2022 Second International Conference on Advanced Technologies in Intelligent Control, Environment, Computing & Communication Engineering (ICATIECE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129618200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Auto-detection of Atrial Fibrillation with Improved Classification and Noise Removal Algorithm along with Dimensionality Reduction Methods","authors":"B. S. C. Suresh, Kala K, S. Pavithra, A. D. M. Nithya","doi":"10.1109/ICATIECE56365.2022.10046828","DOIUrl":"https://doi.org/10.1109/ICATIECE56365.2022.10046828","url":null,"abstract":"Atrial fibrillation (AF) is an irregular manner of the heart rhythm commonly called arrhythmia. Most of the cases this type will associated with significant mortality. It is important to diagnosis at early stage to minimize this consequence. This type of timely diagnosis of arrhythmia is difficult since patients may be asymptomatic. In this study, we describe a robust algorithm for the automatic detection of AF with effective noise removal technique. Proximal splitting-based noise removal method was used to evade noise from the signal. Next, 19 features were extracted from the denoised signal, which included features like RR interval, R peak, P wave morphology, power and spectrum. Application of raw extracted feature directly to the classifier reduces its efficiency. The classifier, quadratic Renyi entropy feature selection method and dimensionality reduction algorithm using principle component analysis (PCA) used to improve the performance. Then the reduced feature set is applied in the Support Vector Machine (SVM) classifier where the samples were classified into normal signals and AF signals. Analysis of the performance of the classifier indicated an accuracy of 97.62%in detecting the AF signals.","PeriodicalId":199942,"journal":{"name":"2022 Second International Conference on Advanced Technologies in Intelligent Control, Environment, Computing & Communication Engineering (ICATIECE)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128719309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sign Language Recognition System using Convolutional Neural Network","authors":"T. M. Dudhane, T. R. Chenthil, K. P, Jothibasu M","doi":"10.1109/ICATIECE56365.2022.10046883","DOIUrl":"https://doi.org/10.1109/ICATIECE56365.2022.10046883","url":null,"abstract":"Sign language is the common communication language for the hearing and speech-impaired community. It is hard for most people to communicate in sign language without an interpreter. Sign language refers to the tracking and identification of meaningful human expressions made with the hands, arms, fingers, heads, etc. The method used in this case converts the sign language movements into a spoken language that the listener may easily understand. The communication using sign language is useful for the peoples depend on gestural sign language but it is more complex for the other publics. The existing systems are not efficient since they are struggling with skin tone detection. But, adding a filter symbol can be recognized regardless of skin tone. In this work, primarily focused on analyzing convolutional neural networks (CNN). There are four kinds of layers: convolution layers, fully connected layers, pooling/subsampling layers and nonlinear layers for learning new characteristics.","PeriodicalId":199942,"journal":{"name":"2022 Second International Conference on Advanced Technologies in Intelligent Control, Environment, Computing & Communication Engineering (ICATIECE)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128837289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}