{"title":"Driving Aid for Rotator Cuff Injured Patients using Hand Gesture Recognition","authors":"Krishnasree Vasagiri","doi":"10.37394/232014.2024.20.3","DOIUrl":"https://doi.org/10.37394/232014.2024.20.3","url":null,"abstract":"Gesture recognition is a way for computers to understand how humans move and express themselves without using traditional methods like typing or clicking. Instead of relying on text or graphics, gesture recognition focuses on reading body movements, such as those made by the hands or face. Currently, there is a specific interest in recognizing hand gestures by analyzing the veins on the back of the hand. Scientists have found that each person has a unique arrangement of veins beneath the skin of their hand. When the hand moves, the position of these veins changes, and this change is considered a gesture. These gestures are then translated into specific actions or tasks by coding the hand movements. This technology is particularly helpful for individuals with rotator cuff injuries. The rotator cuff is a group of muscles and tendons in the shoulder that can get injured, causing pain and limiting movement. People with these injuries may have difficulty steering a car, especially if their job or sport involves repetitive overhead motions. With gesture recognition technology, a person can control the car by simply moving their wrist, eliminating the need to use the shoulder. In summary, gesture recognition technology reads the unique patterns of hand veins to interpret hand movements, making it a practical solution for individuals with rotator cuff injuries who may struggle with certain tasks, like steering a car.","PeriodicalId":305800,"journal":{"name":"WSEAS TRANSACTIONS ON SIGNAL PROCESSING","volume":"123 21","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140985443","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":"Robust Recursive Least-Squares Fixed-Point Smoother and Filter using Covariance Information in Linear Continuous-Time Stochastic Systems with Uncertainties","authors":"S. Nakamori","doi":"10.37394/232014.2024.20.2","DOIUrl":"https://doi.org/10.37394/232014.2024.20.2","url":null,"abstract":"This study develops robust recursive least-squares (RLS) fixed-point smoothing and filtering algorithms for signals in linear continuous-time stochastic systems with uncertainties. The algorithms use covariance information, such as the cross-covariance function of the signal with the observed value and the autocovariance function of the degraded signal. A finite Fourier cosine series expansion approximates these functions. Additive white Gaussian noise is present in the observation of the degraded signal. A numerical simulation compares the estimation accuracy of the proposed robust RLS filter with the robust RLS Wiener filter, showing similar mean square values (MSVs) of the filtering errors. The MSVs of the proposed robust RLS fixed-point smoother are also compared to those of the proposed robust RLS filter.","PeriodicalId":305800,"journal":{"name":"WSEAS TRANSACTIONS ON SIGNAL PROCESSING","volume":"13 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140985236","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":"CTM Tongue Image Consulting System based on Deep Learning Technology","authors":"Jingxuan Fang, Liu Fei, Fang Xiang, Lingtao Su","doi":"10.37394/232014.2024.20.1","DOIUrl":"https://doi.org/10.37394/232014.2024.20.1","url":null,"abstract":"Internet is an important development step in information times. With the tide of Internet development, internet plus health will become a trend of new times. The Chinese Traditional Medicine (CTM) tongue image consulting system based on deep learning technology has created a more perfect and intelligent personal health management system by connecting smart devices to mobile platforms. The system will serve customers perfectly through health food therapy, medical consultation, etc.","PeriodicalId":305800,"journal":{"name":"WSEAS TRANSACTIONS ON SIGNAL PROCESSING","volume":"41 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139593868","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":"Robust Estimators for Missing Observations in Linear Discrete-Time Stochastic Systems with Uncertainties","authors":"S. Nakamori","doi":"10.37394/232014.2023.19.18","DOIUrl":"https://doi.org/10.37394/232014.2023.19.18","url":null,"abstract":"As a first approach to estimating the signal and the state, Theorem 1 proposes recursive least-squares (RLS) Wiener fixed-point smoothing and filtering algorithms that are robust to missing measurements in linear discrete-time stochastic systems with uncertainties. The degraded quantity is given by multiplying the Bernoulli random variable by the degraded signal caused by the uncertainties in the system and observation matrices. The degraded quantity is observed with additional white observation noise. The probability that the degraded signal is present in the observation equation is assumed to be known. The design feature of the proposed robust estimators is the fitting of the degraded signal to a finite-order autoregressive (AR) model. Theorem 1 is transformed into Corollary 1, which expresses the covariance information in a semi-degenerate kernel form. The autocovariance function of the degraded state and the cross-covariance function between the nominal state and the degraded state is expressed in semi-degenerate kernel forms. Theorem 2 shows the robust RLS Wiener fixed-point and filtering algorithms for estimating the signal and state from degraded observations in the second method. The robust estimation algorithm of Theorem 2 has the advantage that, unlike Theorem 1 and the usual studies, it does not use information on the existence probability of the degraded signal. This is a unique feature of Theorem 2.","PeriodicalId":305800,"journal":{"name":"WSEAS TRANSACTIONS ON SIGNAL PROCESSING","volume":"190 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139145570","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}
Tae-yong Kim, J. Jeong, Chaekyu Lee, Seong-Gi Oh, Lee Jieun, Yongju Na
{"title":"Pattern Wafer x/y Auto Align System using Machine Vision","authors":"Tae-yong Kim, J. Jeong, Chaekyu Lee, Seong-Gi Oh, Lee Jieun, Yongju Na","doi":"10.37394/232014.2023.19.6","DOIUrl":"https://doi.org/10.37394/232014.2023.19.6","url":null,"abstract":"The paper proposes an Automatic Semiconductor Measurement System using Wafer Auto Align using Pattern for semiconductor wafer measurement. The measurement of semiconductors is crucial for the semiconductor industry, and the proposed model aims to improve the semiconductor production automation process. The proposed system consists of three main components: the stage, the vision system, and the pattern alignment algorithm. The stage includes theWafer holder, Ellipsometer, and controller, and plays a critical role in aligning the X and Y axes of the Wafer to 100 mm/s after pattern analysis. The vision system captures highquality images of the Wafer and analyzes the patterns on the Wafer to detect any defects or deviations from the standard. The pattern alignment algorithm uses the information obtained from the vision system to align the Wafer accurately. The Auto align process is fully automated and does not require any user intervention. The process operates in three major steps: selecting the Wafer Recipe, photographing the pattern of the designated recipe, and executing the Auto align. The proposed system offers a comprehensive and automated solution for Wafer alignment and measurement, providing high accuracy and efficiency, while also reducing the risk of errors and improving the semiconductor production process.","PeriodicalId":305800,"journal":{"name":"WSEAS TRANSACTIONS ON SIGNAL PROCESSING","volume":"553 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131787524","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":"Linear H-Infinity Tracking Control in Discrete-Time Stochastic Systems with Uncertain Parameters","authors":"S. Nakamori","doi":"10.37394/232014.2023.19.5","DOIUrl":"https://doi.org/10.37394/232014.2023.19.5","url":null,"abstract":"","PeriodicalId":305800,"journal":{"name":"WSEAS TRANSACTIONS ON SIGNAL PROCESSING","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116480270","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":"Two-Stage Kalman Filter Based Estimation of Boeing 747 Actuator/Control Surface Stuck Faults","authors":"Akan Guven, C. Hajiyev","doi":"10.37394/232014.2023.19.4","DOIUrl":"https://doi.org/10.37394/232014.2023.19.4","url":null,"abstract":"This research aims to construct a two-stage Kalman filter (TSKF) that is available to estimate the control effectiveness of the actuator on behalf of an actuator stuck fault incident occurring on Boeing-747 commercial airplane. The actuator faults can be diagnosed via TSKF that maintains the states and stuck positions or control loss by two section encapsulated estimation algorithms. The performance of the TSKF algorithm is tested. The source of accidents can be as a result from a control surface stuck such an aileron, rudder, elevator; also, it can be present and appear as bird strike that could tear some part of the control surfaces located on the wings or tail of the airplane. In this study, there is a stuck fault on the rudder control surface and the proposed algorithm introduces the value of the stuck of the broken control surface and it is achieved that utilizing TSKF performs satisfying estimation values which are verified as well on lateral dynamics of the airplane.","PeriodicalId":305800,"journal":{"name":"WSEAS TRANSACTIONS ON SIGNAL PROCESSING","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133234003","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":"Sentiment Analysis of User Comment Text based on LSTM","authors":"Feng Li, Chenxi Cui, Yashi Hu, Lingling Wang","doi":"10.37394/232014.2023.19.3","DOIUrl":"https://doi.org/10.37394/232014.2023.19.3","url":null,"abstract":"Taking the user-generated Chinese comment dataset on online platforms as the research object, we constructed word2vec word vectors using gensim and built a sentiment analysis model based on LSTM using the TensorFlow deep learning framework. From the perspective of mining user comment data on the platform, we analyzed the sentiment tendency of user comments, providing data support for hotels to understand consumers' real sentiment tendencies and improve their own service quality. Through analysis of the validation dataset results obtained by crawling the website, the accuracy of this LSTM model can reach up to 0.89, but there is still much room for improvement in the accuracy of sentiment analysis for some datasets. In future research, this model needs further optimization to obtain a stable and more accurate deep-learning model.","PeriodicalId":305800,"journal":{"name":"WSEAS TRANSACTIONS ON SIGNAL PROCESSING","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115950489","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":"Recursive Least-Squares Wiener Consensus Filter and Fixed-Point Smoother in Distributed Sensor Networks","authors":"S. Nakamori","doi":"10.37394/232014.2023.19.1","DOIUrl":"https://doi.org/10.37394/232014.2023.19.1","url":null,"abstract":"Distributed Kalman filter (DKF) is classified into the information fusion Kalman filter (IFKF), i. e. the centralized Kalman filter (CKF), and the Kalman consensus filter (KCF) in distributed sensor networks. The KCF has the advantage to improve the estimate of the state at the sensor node uniformly by incorporating the information of the observations and the filtering estimates at the neighbor nodes. In the first devised KCF, a user adjusts the consensus gain. This paper designs the recursive least-squares (RLS) Wiener consensus filter and fixed-point smoother that do not need to be adjusted in linear discrete-time stochastic systems. In addition to the observation equation at the sensor node, an observation equation is introduced excessively. Here, the new observation is the sum of the filtering estimates of the signals at the neighbor nodes of the sensor node. Thus, it is interpreted that the RLS Wiener consensus estimators incorporate the information of the observations at the neighbor nodes indirectly because the observations are used in the calculations of the filtering estimates. A numerical simulation example shows that the proposed RLS Wiener consensus filter and fixed-point smoother are superior in estimation accuracy to the RLS Wiener estimators.","PeriodicalId":305800,"journal":{"name":"WSEAS TRANSACTIONS ON SIGNAL PROCESSING","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125856034","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}
Asmae Zbiri, Azeddine Hachmi, Fatima Ezzahra El Alaoui-Faris, H. Eerens, Dominique Haesen
{"title":"Efficiency of SPIRITS (Software for Processing and Interpretation of Remotely Sensed Image Time Serie) to Ecological Modeling: New Functionalities and Use Examples","authors":"Asmae Zbiri, Azeddine Hachmi, Fatima Ezzahra El Alaoui-Faris, H. Eerens, Dominique Haesen","doi":"10.37394/232014.2022.18.24","DOIUrl":"https://doi.org/10.37394/232014.2022.18.24","url":null,"abstract":"We studied the effectiveness of SPIRITS processing software used to monitor drought. In this article, we propose practice steps and we prove that ecological modeling can be available with remote sensing data on a larger scale (for any place in the world) with SPIRITS. The studies summarize some important analyses of remote sensing time series at high temporal and medium spatial resolution. The Software for the Processing and Interpretation of Remotely sensed Image Time Series (SPIRITS) is a stand-alone flexible analysis environment created to facilitate the processing and analysis of large image time series and ultimately for providing clear information about vegetation status in various graphical formats to ecological modeling. The examples of operational analyses are taken from several recent drought monitoring articles. We conclude with considerations on SPIRITS use also in view of data processing requirements imposed by the coming generation of remote sensing products at high spatial and temporal resolution, such as those provided by the Sentinel sensors of the European Copernicus program.","PeriodicalId":305800,"journal":{"name":"WSEAS TRANSACTIONS ON SIGNAL PROCESSING","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127441561","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}