2022 IEEE 18th International Colloquium on Signal Processing & Applications (CSPA)最新文献_第6页

BAWS3TS: Browsing Authentication Web-Based Smartphone Using 3D Touchscreen Sensor BAWS3TS:浏览身份验证基于web智能手机使用3D触摸屏传感器

2022 IEEE 18th International Colloquium on Signal Processing & Applications (CSPA) Pub Date : 2022-05-12 DOI: 10.1109/CSPA55076.2022.9781888

Moceheb Lazam Shuwandy, H. A. Aljubory, N. M. Hammash, M. M. Salih, M. A. Altaha, Z. T. Alqaisy

{"title":"BAWS3TS: Browsing Authentication Web-Based Smartphone Using 3D Touchscreen Sensor","authors":"Moceheb Lazam Shuwandy, H. A. Aljubory, N. M. Hammash, M. M. Salih, M. A. Altaha, Z. T. Alqaisy","doi":"10.1109/CSPA55076.2022.9781888","DOIUrl":"https://doi.org/10.1109/CSPA55076.2022.9781888","url":null,"abstract":"Modern mobile devices, especially smartphones, have developed rapidly and are widely adopted by people of all ages. Smartphones can assist users in various activities, i.e., from social networking to online shopping, but they have also become an attractive target for cybercriminals due to their stored personal data and sensitive information. Traditional authentication mechanisms such as the PIN suffer from limitations and drawbacks known in the security community; Thus, haptic behavioral authentication has been getting much attention lately. Intuitively, it was not easy to build a standalone authentication system based on free touches. However, in this work, we advocate that such authentication can consider users' actions within some mobile applications such as web browsers and then propose a multi-layer touch authentication system using a 3D touch sensor called BAWS3TS. The pressure force on the touch screen applies to many users, and the layer level, the pressure force, and the location of the touch can provide a comprehensive authentication option during the use of the browser, and the browser has within its design a certain level at a specific location within the processing of the 3D touch sensor. So, it has a unique pattern for the user on a particular smartphone browser. Three adult volunteers had a high accuracy rate of 98% as a consequence of the studies, according to their experience. We will increase the number of participants and conduct a study to determine the effect of future use of this technology.","PeriodicalId":174315,"journal":{"name":"2022 IEEE 18th International Colloquium on Signal Processing & Applications (CSPA)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116088905","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}

引用次数: 3

Modeling RTK-GNSS Trajectory Data using Sparse Gaussian Process Models 基于稀疏高斯过程模型的RTK-GNSS轨迹数据建模

2022 IEEE 18th International Colloquium on Signal Processing & Applications (CSPA) Pub Date : 2022-05-12 DOI: 10.1109/CSPA55076.2022.9781923

R. Nahar, K. M. Ng, F. H. K. Zaman, J. Johari

{"title":"Modeling RTK-GNSS Trajectory Data using Sparse Gaussian Process Models","authors":"R. Nahar, K. M. Ng, F. H. K. Zaman, J. Johari","doi":"10.1109/CSPA55076.2022.9781923","DOIUrl":"https://doi.org/10.1109/CSPA55076.2022.9781923","url":null,"abstract":"The Gaussian process regression (GPR) has been applied to model trajectory points from Global Navigation Satellite System (GNSS). Trajectory modeling using GP in previous works did not demonstrate its performance when training the GP using various kernel functions. In addition, residuals were not analyzed to ascertain the goodness of fit. In this paper, we aim to develop sparse GPR model with the best performing covariance function to model trajectory data collected using the RTK-GNSS (Real-Time Kinematics-Global Navigation Satellite Systems) in a sub-urban area. The sparse GPR was trained on three data sets collected using five types of kernel or covariance functions. The model was validated using 10-fold cross validation. The Bayesian information (BIC) and mean square error (MAE) from the cross-validation were used to identify the best performing kernel function. Subsequently sparse GPR model with the best kernel was implemented to predict the trajectory. Model residuals were analyzed using the autocorrelation, partial correlation, histograms and QuantileQuantile (Q-Q) plot. The sparse GPR could improve positioning errors ranging from 9.93 % to 34.91 %. However, the analyses on the residuals reveal poor model fit and the presence of correlation in the data.","PeriodicalId":174315,"journal":{"name":"2022 IEEE 18th International Colloquium on Signal Processing & Applications (CSPA)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125202226","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}

引用次数: 0

Development of LPG Leakage Simulation System Integrated with the Internet of Things (IoT) 结合物联网的LPG泄漏仿真系统开发

2022 IEEE 18th International Colloquium on Signal Processing & Applications (CSPA) Pub Date : 2022-05-12 DOI: 10.1109/CSPA55076.2022.9781880

H. Saad, Salman Ahmed Siddiqui, N. F. Naim, N. Othman

引用次数: 4

The Development of Driving Simulator Game-Based Learning in Virtual Reality 虚拟现实中基于驾驶模拟器游戏学习的开发

2022 IEEE 18th International Colloquium on Signal Processing & Applications (CSPA) Pub Date : 2022-05-12 DOI: 10.1109/CSPA55076.2022.9781976

Nik Muhammad Amirul Fawwaz Nik Abdullah, Ahmad Huzaifah Ahmad Sharipuddin, Safinaz Mustapha, M. N. Mohammed

引用次数: 3

Development of Integrated Sensor System for Intelligent Transportation System 智能交通系统集成传感器系统的研制

2022 IEEE 18th International Colloquium on Signal Processing & Applications (CSPA) Pub Date : 2022-05-12 DOI: 10.1109/CSPA55076.2022.9781912

John Emmanuel G. Azares, Mark Joshua A. Centino, J. D. dela Cruz, John Paul A. Nopia, Timothy M. Amado

{"title":"Development of Integrated Sensor System for Intelligent Transportation System","authors":"John Emmanuel G. Azares, Mark Joshua A. Centino, J. D. dela Cruz, John Paul A. Nopia, Timothy M. Amado","doi":"10.1109/CSPA55076.2022.9781912","DOIUrl":"https://doi.org/10.1109/CSPA55076.2022.9781912","url":null,"abstract":"Traffic congestion has always been a major problem in the Philippines. This project study developed an integrated sensor system for intelligent transportation, which addressed the lack of automatic traffic monitoring systems to achieve traffic efficiency and safety. The researchers utilized different sensors in gathering data such as water level, temperature, and humidity within a certain area as well as a camera in capturing images and compared the three image compression algorithms, mainly the DCT (Discrete Cosine Transform), DWT (Discrete Wavelet Transform) and SVD (singular value decomposition) in terms of different parameters used in describing and identifying the best type of image compression to be applied prior to transmission to other different nodes. MSE (mean squared error) value, PSNR (Peak signal-to-noise ratio), Compress Ratio, and Process Time were the values of comparison in determining the best compression technique or algorithm for the gathered images. As a result, it was found that DCT characterized the best parameters for image compression. DCT produced the highest PSNR (52.41979dB), the lowest value for MSE (0.37247), and the lowest process time (0.16181s), while SVD was able to produce the most compressed image. This project also utilized solar renewable energy for the power management system, which enabled the system to run independently without any other external power source. This will be beneficial for the community to identify which roads can be used to optimize the mobility of the vehicles and maximize the use of renewable energy; hence will help reduce the traffic congestion issues in the country.","PeriodicalId":174315,"journal":{"name":"2022 IEEE 18th International Colloquium on Signal Processing & Applications (CSPA)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114479974","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}

引用次数: 1

Optimal Cornering for Rack Steering Vehicle using Adaptive Torque-Based Vehicle Slip Control 基于自适应转矩滑移控制的齿条转向车辆最优转弯

2022 IEEE 18th International Colloquium on Signal Processing & Applications (CSPA) Pub Date : 2022-05-12 DOI: 10.1109/CSPA55076.2022.9781974

Norsharimie Mat Adam, A. Irawan

{"title":"Optimal Cornering for Rack Steering Vehicle using Adaptive Torque-Based Vehicle Slip Control","authors":"Norsharimie Mat Adam, A. Irawan","doi":"10.1109/CSPA55076.2022.9781974","DOIUrl":"https://doi.org/10.1109/CSPA55076.2022.9781974","url":null,"abstract":"The paper presents the adaptive torque-based vehicle slip control (AT-VSC) using super-twisting algorithm for the rack steering vehicle (RSV) optimal maneuvering on the cornering path. The inertia of vehicle's slip caused by oversteered on cornering road is a crucial part that need to be considered in vehicle dynamics and control system design. This situation might lead to the accident such as border collision and offroad. Therefore, steering angle, torque, friction, and orientation of the RSV is used as a focus parameter to be controlled in the cornering track. The control objective is to reduce the slip and stabilizing of the vehicle system during cornering period with reference to the different steering angle and vehicle’s torque on driven wheels. The results show that the different positioning on RSV motion of the vehicle was able to reduce when using the proposed AT-VSC. Also, the reduction of vehicle velocity influenced the overall kinetic energy of the system that reduced the inertia effect, thus, able to control the oversteering occurred in cornering from the results of vehicle motion.","PeriodicalId":174315,"journal":{"name":"2022 IEEE 18th International Colloquium on Signal Processing & Applications (CSPA)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126547063","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}

引用次数: 0

V-net Performances for 2D Ultrasound Image Segmentation 二维超声图像分割的V-net性能

2022 IEEE 18th International Colloquium on Signal Processing & Applications (CSPA) Pub Date : 2022-05-12 DOI: 10.1109/CSPA55076.2022.9781973

Soufiane Dangoury, Mohammed Sadik, A. Alali, Abderrahim Fail

{"title":"V-net Performances for 2D Ultrasound Image Segmentation","authors":"Soufiane Dangoury, Mohammed Sadik, A. Alali, Abderrahim Fail","doi":"10.1109/CSPA55076.2022.9781973","DOIUrl":"https://doi.org/10.1109/CSPA55076.2022.9781973","url":null,"abstract":"Artificial intelligence (AI) has conquered all areas of human being life through its performance when it is adapted to a particular domain. Nowadays, different research papers are interested in the application of AI in medical area for ultrasound imaging. Hence, the most important task in medical field is imaging and image segmentation since it helps doctors to perform accurate diagnosis and therefore to prescribe the right treatment. In this paper, we study the image segmentation to improve the visualization and quantification of different image regions. To this end we propose the implementation of a 2D version of V-net architecture. The results are compared to the popular medical’s imaging algorithm U-net and its variation U-net++. The performance of our results is validated by the widely used metrics in segmentation field which are Dice coefficient, Sensitivity, Specificity and Accuracy. In addition, losses function has a high influence on training models. Therefore, our model will be experimented under different losses such as function Cross-Entropy, Dice-Similarity-loss, Focal loss and Focal Tversky loss to end up with the good cases for a training model. Extensive simulation of the proposed V-net model shows an improvement of 85.01% in Dice Coefficient, 85% in terms of sensitivity, 99% in specificity and 99% in accuracy.","PeriodicalId":174315,"journal":{"name":"2022 IEEE 18th International Colloquium on Signal Processing & Applications (CSPA)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133317310","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}

引用次数: 0

An Optimized Soil Moisture Prediction Model for Smart Agriculture Using Gaussian Process Regression 基于高斯过程回归的智能农业土壤水分预测优化模型

2022 IEEE 18th International Colloquium on Signal Processing & Applications (CSPA) Pub Date : 2022-05-12 DOI: 10.1109/CSPA55076.2022.9781897

Zoren P. Mabunga, J. D. dela Cruz

引用次数: 3

Object Detection for Inventory Stock Counting Using YOLOv5 使用YOLOv5进行库存盘点的目标检测

2022 IEEE 18th International Colloquium on Signal Processing & Applications (CSPA) Pub Date : 2022-05-12 DOI: 10.1109/CSPA55076.2022.9782028

Isaiah Francis E. Babila, Shawn Anthonie E. Villasor, J. D. dela Cruz

{"title":"Object Detection for Inventory Stock Counting Using YOLOv5","authors":"Isaiah Francis E. Babila, Shawn Anthonie E. Villasor, J. D. dela Cruz","doi":"10.1109/CSPA55076.2022.9782028","DOIUrl":"https://doi.org/10.1109/CSPA55076.2022.9782028","url":null,"abstract":"The study has successfully created a program to detect cellphone boxes namely, Cherry Aqua S9 and Cherry Flare S8 in any orientation. Successful detection was made possible by building the datasets where the target objects will capture using a camera in different scenarios. A total of 1,623 images were collected and automatically split by the Roboflow application. In this study, the best background light source to be used is 9Watts. Based on the data gathered were, both target objects had a perfect count of thirty-two (32) and had a 0.96 average accuracy for S8 and a 0.95 average accuracy for S9. For the 7W lighting source, the S9’s did not detect the side view 180° orientation; for the accuracy test, a 0.95 average accuracy for S8 and a 0.90 average accuracy for S9. Lastly, using 5W, eight (8) misdetections in the system, having a total count of only Twenty-four (24) for S8 and forty (40) for S9, for the accuracy-test a 0.70 average accuracy for S8 and a 0.93 for S9. The You Only Look Once v5 (YOLOv5) algorithm was successfully applied to identify and count the target objects and display the result in the touch display. Based on the outcome for noise reduction, placing different kinds of boxes and boxes with the same size and dimension of the target objects will not be detected. YOLO is the best algorithm for object detection that recognizes only the trained objects. The results show the accuracy, which offers a high precision and high recall curve and decreases all lost when the dataset added more pictures, leading to higher accuracy.","PeriodicalId":174315,"journal":{"name":"2022 IEEE 18th International Colloquium on Signal Processing & Applications (CSPA)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123883728","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}

引用次数: 5

Feature Selection for Metaheuristics Optimization Technique with Chaos 混沌元启发式优化技术的特征选择

2022 IEEE 18th International Colloquium on Signal Processing & Applications (CSPA) Pub Date : 2022-05-12 DOI: 10.1109/CSPA55076.2022.9781989

Sushovan Chaudhury, O. J. Oyebode, Dai-Long Ngo Hoang, F. Rabbi, S. Ajibade

引用次数: 1