2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA)最新文献_第3页

Parameter-Replacement Functions for Stability-Guaranteed Variable Digital Filters 稳定保证变量数字滤波器的参数替换函数

2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA) Pub Date : 2023-03-03 DOI: 10.1109/CSPA57446.2023.10087739

T. Deng

{"title":"Parameter-Replacement Functions for Stability-Guaranteed Variable Digital Filters","authors":"T. Deng","doi":"10.1109/CSPA57446.2023.10087739","DOIUrl":"https://doi.org/10.1109/CSPA57446.2023.10087739","url":null,"abstract":"Digital filters are the most basic and most useful signal-processing systems that are used to pass through some frequency components in a signal and eliminate others. During filtering operations, a digital filter being applied usually needs to change its frequency-domain characteristic (frequency response) as quickly as possible. To achieve this objective, a digital filter must have the capability to change its frequency response in a real-time manner, and such a digital filter is called variable digital filter (VDF). VDFs have changeable coefficients, and thus variable frequency responses. To get a new frequency response, a VDF needs to change its coefficients. On the other hand, changing the coefficients of a recursive VDF may cause a big problem, which is instability. That is, the new coefficients may make the recursive VDF become unstable. Therefore, it is mandatory to ensure the filter stability when the filter coefficients are changed. So far, a technique for ensuring the stability of a recursive VDF has been revealed. The tactic is based on coefficient replacements. Specifically, this technique uses a function to replace the denominator coefficients of the transfer function with a kind of composite functions, and those composite functions involve a few new parameters. In the VDF design, the new parameters involved in the composite functions are sought by minimizing a specific error measure (say, mean-squared error). The key point is that no matter what values the new parameters take, the composite functions can always ensure the stability of a recursive VDF. To replace the denominator coefficients with composite functions, a special function called parameter-replacement (PR) function is employed. In this paper, a wide variety of PR functions are presented.","PeriodicalId":268233,"journal":{"name":"2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124655453","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

EmHM: A Novel Hybrid Model for the Emotion Recognition based on EEG Signals EmHM:一种基于脑电图信号的情绪识别混合模型

2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA) Pub Date : 2023-03-03 DOI: 10.1109/CSPA57446.2023.10087500

Ramnivas Sharma, Hemant Kumar Meena

{"title":"EmHM: A Novel Hybrid Model for the Emotion Recognition based on EEG Signals","authors":"Ramnivas Sharma, Hemant Kumar Meena","doi":"10.1109/CSPA57446.2023.10087500","DOIUrl":"https://doi.org/10.1109/CSPA57446.2023.10087500","url":null,"abstract":"Emotion is a fundamental aspect of daily life and is crucial for human interactions. This study suggests a unique electroencephalogram (EEG)-based technique for identifying human emotions. For EEG-based emotion analysis, the proposed model is tested on the SEED and DEAP datasets. For the DEAP dataset, we consider valence and arousal emotions for classification purposes, and for the SEED dataset, three emotions, neutral, positive, and negative, have been considered. The differential entropy (DE) is used for the SEED dataset, and for the DEAP dataset, the power spectral density (PSD) is used as a feature. For precise emotion recognition, an EmHM (Emotion Hybrid Model) based on long short-term memory (LSTM) and a convolutional neural network (CNN) are constructed. Furthermore, we applied the CNN, LSTM, and EmHM models, and all three models for emotion recognition are fed with the retrieved information. Various methods improved on already-existing models to accurately classify human emotion. To get better accuracy than the existing techniques, we suggested a model that uses a different approach known as EmHM. By applying all three models such as CNN, LSTM and EmHM, we got the highest accuracy 86.50%, 87.98% and 91.56% respectively on dataset. To improve prediction results, the CNN and the LSTM models are combined to make the EmHM hybrid model.","PeriodicalId":268233,"journal":{"name":"2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124928845","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

Color-assisted Multi-input Convolutional Neural Network for Cancer Classification on Mammogram Images 彩色辅助多输入卷积神经网络在乳房x光图像上的癌症分类

2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA) Pub Date : 2023-03-03 DOI: 10.1109/CSPA57446.2023.10087371

Noorma Razali, I. Isa, S. N. Sulaiman, N. Karim, M. K. Osman

{"title":"Color-assisted Multi-input Convolutional Neural Network for Cancer Classification on Mammogram Images","authors":"Noorma Razali, I. Isa, S. N. Sulaiman, N. Karim, M. K. Osman","doi":"10.1109/CSPA57446.2023.10087371","DOIUrl":"https://doi.org/10.1109/CSPA57446.2023.10087371","url":null,"abstract":"The use of Convolutional Neural Network (CNN) in the computer-aided diagnostic (CAD) system in the radiological medicine field involving breast cancer is gaining wider attention due to the ability of this system to use mammogram images directly to obtain a robust model. However, large amounts of data are required to produce the best model. Moreover, their effectiveness may be hindered since grayscale mammogram images show atypical color distributions compared to those observed in three-channel RGB images by the network during training. This study proposes a multi-input CNN method to classify benign and malignant breast masses in mammograms. The converted images served as additional data from the original image and are trained parallelly. Using threechannel scaled-color images provides additional features that can be learned to construct more distinct learning weights for each class. We use an established digital mammogram dataset, the INbreast, to test the proposed method. The best model shows an increase in accuracy performance at 92.54% and an AUROC score of 0.9820 when using multi-input CNN. The fusion of features from the additional images that have been processed to three-channel as an addition to the original image shows performance improvement without the need for other external images by exploiting existing data.","PeriodicalId":268233,"journal":{"name":"2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130044136","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

Simulation Program for Modeling Temperature Distribution in a Food Dehydrator 食品脱水机温度分布建模仿真程序

2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA) Pub Date : 2023-03-03 DOI: 10.1109/CSPA57446.2023.10087530

Esther Hee Ying Lim, A. H. Tan, C. Cham

引用次数: 0

Universal Robust Vehicle Identification System 通用鲁棒车辆识别系统

2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA) Pub Date : 2023-03-03 DOI: 10.1109/CSPA57446.2023.10087726

Lorenz Joshua S. Alfonso, Tiffany Joy F. Benitez, Cseanne Jaycons O. Cabalquinto, Francis Jerome T. Perez, Janet Yang, Engr. Leonard U. Ambata

{"title":"Universal Robust Vehicle Identification System","authors":"Lorenz Joshua S. Alfonso, Tiffany Joy F. Benitez, Cseanne Jaycons O. Cabalquinto, Francis Jerome T. Perez, Janet Yang, Engr. Leonard U. Ambata","doi":"10.1109/CSPA57446.2023.10087726","DOIUrl":"https://doi.org/10.1109/CSPA57446.2023.10087726","url":null,"abstract":"With the exponential rise in vehicular traffic volume, an intelligent system that is able to detect and classify would be essential. Image processing has already placed its significance for real-world applications on machine learning, one of which is traffic analysis. Through this study, the researchers developed a system that allows vehicular tracking and identification using the methods of neural networks for object detection, specifically the YOLOv5 algorithm. The system training utilized an initial dataset generated by the researchers that eliminated the manual intervention of image annotation. The developed system was intervened under the conditions of two different locations. It showed its detection and recognition capabilities through the integrated system features, namely, counting, vehicle type classification, and traffic condition assessment. A region of interest (ROI) line was the primary basis for counting, and a lane-per-lane evaluation was displayed. These features were analyzed individually, between the actual and detected and wrong and correct detections. The increasing trend on accuracy proves the efficiency of the fine-tuning process implemented on the system implementation except for the color that requires a separate training process. After the last finetuning process, an accuracy of 92.57% for vehicle class, 93% for type identification, 82% for color identification and 96.67% for detection count were achieved in the final video run.","PeriodicalId":268233,"journal":{"name":"2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127655369","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

Detection of Bacterial Leaf Blight Disease Using RGB-Based Vegetation Indices and Fuzzy Logic 基于rgb植被指数和模糊逻辑的细菌性叶枯病检测

2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA) Pub Date : 2023-03-03 DOI: 10.1109/CSPA57446.2023.10087429

Nor Hafiza Aziz, Rohayu Haron Narashid, T. R. Razak, Siti Aminah Anshah, N. Talib, Z. Latif, N. Hashim, K. Zainuddin

{"title":"Detection of Bacterial Leaf Blight Disease Using RGB-Based Vegetation Indices and Fuzzy Logic","authors":"Nor Hafiza Aziz, Rohayu Haron Narashid, T. R. Razak, Siti Aminah Anshah, N. Talib, Z. Latif, N. Hashim, K. Zainuddin","doi":"10.1109/CSPA57446.2023.10087429","DOIUrl":"https://doi.org/10.1109/CSPA57446.2023.10087429","url":null,"abstract":"Paddy planting becomes the primary source of income and livelihood for paddy farmers, especially small-scale farmers and landless laborers. Unfortunately, rice production has been threatened by paddy disease. The bacteria leaf blight disease (BLB) is one of Malaysia’s most significant paddy diseases, causing substantial harm to rice production. This study aims to determine the bacteria leaf blight (BLB) disease from the utilized techniques of RGB-Based Vegetation Indices and Fuzzy Logic on the Unmanned Aerial Vehicle (UAV) images during the first paddy season 2022 in Perlis. In this study, the RGB-based indices of Normalized Green Red Different Index (NGRDI) and Green Leaf Index (GLI) were applied to the UAV Images captured at 20m altitudes. Then the fuzzy logic classification technique was applied to identify the BLB disease severity which consists of healthy and infected paddy leaves with the acceptable accuracy of 90.16%. Based on the classified BLB severeness with fuzzy logic, the result shows that the NGRDI was more significant to identify paddy disease in the area. In contrast, the GLI index is more significant to identify the non-paddy area. The NGRDI and GLI index ranges for BLB were found between -0.054 to 0.092 and 0.005 to 0.222. For more improvement of the study, the multispectral UAV Image should be applied to increase the accuracy of paddy disease detection like BLB and the images will also be taken and verified in other paddy plots with the aid of a spectroradiometer.","PeriodicalId":268233,"journal":{"name":"2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114063844","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

Study on Cannabidiol and Pulse Electric Field on Breast Cancer Cells 大麻二酚和脉冲电场对乳腺癌细胞的作用研究

2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA) Pub Date : 2023-03-03 DOI: 10.1109/CSPA57446.2023.10087551

M. Jamil, Nur Adilah Abd Rahman, Mohd Nazib Adon, R. Ambar, F. Javid, M. Youseffi, S. Saidin

{"title":"Study on Cannabidiol and Pulse Electric Field on Breast Cancer Cells","authors":"M. Jamil, Nur Adilah Abd Rahman, Mohd Nazib Adon, R. Ambar, F. Javid, M. Youseffi, S. Saidin","doi":"10.1109/CSPA57446.2023.10087551","DOIUrl":"https://doi.org/10.1109/CSPA57446.2023.10087551","url":null,"abstract":"Discovering a new cancer treatment Researchers are becoming more eager to uncover new medicinal compounds from living species. In the UK, CBD has been rising in demand as an alternative therapeutic agent and is used in various medicinal products. CBD, or cannabidiol, is a phytocannabinoid, one of the identified cannabinoids in cannabis plants. It doesn't contain tetrahydrocannabinol (THC), which is a psychoactive ingredient. While electroporation is one of the non-invasive techniques for nonviral delivery systems, such as molecule introduction and molecule transfer in a variety of sizes depending on the parameter chosen. The cell response to CBD compound combined with the electroporation method was the focus of this study. The findings demonstrated a positive response to the antiproliferative properties of cancer cells, and the treatment was further aided by a pulse electric field of 600 V/cm for $30 mu mathrm{s}$ with a single pulse. The results showed further decrements in cell viability. This finding may contribute toward cancer treatment as an adjunct alternative anticancer agent.","PeriodicalId":268233,"journal":{"name":"2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131296866","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

Machine Learning Curriculums Generated by Classifier Ensembles 由分类器集成生成的机器学习课程

2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA) Pub Date : 2023-03-03 DOI: 10.1109/CSPA57446.2023.10087822

Tzu-Jui Huang, K. Kameyama

引用次数: 0

Cardiovascular Disease Prediction using Ensemble Learning Techniques: A Stacking Approach 使用集成学习技术的心血管疾病预测:堆叠方法

2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA) Pub Date : 2023-03-03 DOI: 10.1109/CSPA57446.2023.10087730

Zahiriddin Rustamov, Jaloliddin Rustamov, Most Sarmin Sultana, Jeanne Ywei, Vimala Balakrishnan, N. Zaki

{"title":"Cardiovascular Disease Prediction using Ensemble Learning Techniques: A Stacking Approach","authors":"Zahiriddin Rustamov, Jaloliddin Rustamov, Most Sarmin Sultana, Jeanne Ywei, Vimala Balakrishnan, N. Zaki","doi":"10.1109/CSPA57446.2023.10087730","DOIUrl":"https://doi.org/10.1109/CSPA57446.2023.10087730","url":null,"abstract":"Cardiovascular diseases (CVDs) are group disorders affecting the heart or involving constricted blood arteries. Early disease detection increases the likelihood of survival. As a result, newer methods such as machine learning emerged, capable of processing and analysing vast quantities of complex medical data and providing a more accurate prediction of diseases, including CVDs. However, due to factors such as overfitting and bias, the single classifier could not ensure optimum prediction. Thus, this study proposes a stacking ensemble classifier, which combines several single classifiers to produce an optimal predictive model. The Framingham Heart Study dataset was used to train the machine learning algorithms. The exploratory data analysis indicates that CVD was more common in males and diabetic individuals. Furthermore, individuals above the age of 65 were more susceptible to CVDs. Feature selection, missing value imputation, and data sampling were performed as part of data preprocessing. The results show that the proposed stacked ensemble classifier achieved 88.33% accuracy, 89.95% precision, 86.27% recall and 88.07% F1-score. Furthermore, the significance test results indicate that the proposed model performs significantly better than most models evaluated in this research. Finally, the comparative analysis showed that the proposed ensemble classifier performs better than most studies using the same dataset. The proposed model achieved a high F1-score, indicating it can accurately predict the cases with and without CVD.","PeriodicalId":268233,"journal":{"name":"2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124946436","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

Providing Unique Solution to Daubechies’s AM-M Oscillator Expansion, and its Limitations 为Daubechies的AM-M振荡器扩展及其局限性提供独特的解决方案

2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA) Pub Date : 2023-03-03 DOI: 10.1109/CSPA57446.2023.10087433

F. Ishiyama

引用次数: 0