Cmc-computers Materials & Continua最新文献_第7页

Adaptive Fuzzy Logic Controller for Harmonics Mitigation Using Particle Swarm Optimization 基于粒子群优化的自适应模糊控制器谐波抑制

IF 3.1 4区计算机科学

Cmc-computers Materials & Continua Pub Date : 2022-01-01 DOI: 10.32604/cmc.2022.023588

Waleed Rafique, Ayesha Khan, Ahmad S. Almogren, J. Arshad, Adnan Yousaf, Mujtaba Hussain Jaffery, Ateeq Ur Rehman, Muhammad Shafiq

引用次数: 5

Cross Intelligence Evaluation for Effective Emotional Intelligence Estimation 有效情绪智力评估的交叉智力评估

IF 3.1 4区计算机科学

Cmc-computers Materials & Continua Pub Date : 2022-01-01 DOI: 10.32604/cmc.2022.020264

Ibrahim Alsukayti, Aman Singh

{"title":"Cross Intelligence Evaluation for Effective Emotional Intelligence Estimation","authors":"Ibrahim Alsukayti, Aman Singh","doi":"10.32604/cmc.2022.020264","DOIUrl":"https://doi.org/10.32604/cmc.2022.020264","url":null,"abstract":": A famous psychologist or researcher, Daniel Goleman, gave a theory on the importance of Emotional Intelligence for the success of an individual’s life. Daniel Goleman quoted in the research that “The contribution of an individual’s Intelligence Quotient (IQ) is only 20% for their success, the remaining 80% is due to Emotional Intelligence (EQ)”. However, in the absence of a reliable technique for EQ evaluation, this factor of overall intelligence is ignored in most of the intelligence evaluation mechanisms. This research presented an analysis based on basic statistical tools along with more sophisticated deep learning tools. The proposed cross intelligence evaluation uses two different aspects which are similar, i.e., EQ and SQ to estimate EQ by using a trained model over SQ Dataset. This presented analysis ensures the resemblance between the Emotional and Social Intelligence of an Individual. The research authenticates the results over standard statistical tools and is practically inspected by deep learning tools. Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF) and Social IQ dataset are deployed over a Multi-layered Long-Short Term Memory (M-LSTM) based deep learning model for accessing the resemblance between EQ and SQ. The M-LSTM based trained deep learning model registered, the high positive resemblance between Emotional and Social Intelligence and concluded that the resemblance factor between these two is more than 99.84%. This much resemblance allows future researchers to calculate human emotional intelligence with the help of social intelligence. This flexibility also allows the use of Big Data available on social networks, to calculate the emotional intelligence of an individual.","PeriodicalId":10440,"journal":{"name":"Cmc-computers Materials & Continua","volume":"40 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74126205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Model Identification and Control of Evapotranspiration for Irrigation Water Optimization 灌溉水优化蒸散发模型辨识与控制

IF 3.1 4区计算机科学

Cmc-computers Materials & Continua Pub Date : 2022-01-01 DOI: 10.32604/cmc.2022.019071

Wafa Difallah, F. Bounaama, B. Draoui, Khelifa Benahmed, A. Laaboudi

{"title":"Model Identification and Control of Evapotranspiration for Irrigation Water Optimization","authors":"Wafa Difallah, F. Bounaama, B. Draoui, Khelifa Benahmed, A. Laaboudi","doi":"10.32604/cmc.2022.019071","DOIUrl":"https://doi.org/10.32604/cmc.2022.019071","url":null,"abstract":": Water conservation starts from rationalizing irrigation, as it is the largest consumer of this vital source. Following the critical and urgent nature of this issue, several works have been proposed. The idea of most researchers is to develop irrigation management systems to meet the water needs of plants with optimal use of this resource. In fact, irrigation water requirement is only the amount of water that must be applied to compensate the evapotranspiration loss. Penman-Monteith equation is the most common formula to evaluate reference evapotranspiration, but it requires many factors that cannot be available in many cases. This leads to a trend towards behavior model estimation. System identification with control is one of the most promising applicationsin this axis. The idea behind this proposal depends on three stages: First, the estimation of reference evapotranspiration (ET0) by a linear ARX model, where temperature, relative humidity, insolation duration and wind speed are used as inputs, and ET0 estimated by Penman-Monteith equation as output. The results show that the values estimated by this method were in good agreement with the measured data. The second part of this paper is to manage the quantity of water. For this purpose, two controllers are used for testing, lead-lag and PID. To adjust the first controller and optimize the choice of its parameters, Nelder-Mead algorithm is used. In the last part, a comparative study is done between the two used controllers.","PeriodicalId":10440,"journal":{"name":"Cmc-computers Materials & Continua","volume":"158 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73134717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Efficient Forgery Detection Approaches for Digital Color Images 数字彩色图像的有效伪造检测方法

IF 3.1 4区计算机科学

Cmc-computers Materials & Continua Pub Date : 2022-01-01 DOI: 10.32604/cmc.2022.021047

A. Baumy, Abeer D. Algarni, M. Abdalla, W. El-shafai, Fathi E. Abd El-Samie, Naglaa. F. Soliman

{"title":"Efficient Forgery Detection Approaches for Digital Color Images","authors":"A. Baumy, Abeer D. Algarni, M. Abdalla, W. El-shafai, Fathi E. Abd El-Samie, Naglaa. F. Soliman","doi":"10.32604/cmc.2022.021047","DOIUrl":"https://doi.org/10.32604/cmc.2022.021047","url":null,"abstract":": This paper is concerned with a vital topic in image processing: color image forgery detection. The development of computing capabilities has led to a breakthrough in hacking and forgery attacks on signal, image, and data communicated over networks. Hence, there is an urgent need for developing efficient image forgery detection algorithms. Two main types of forgery are considered in this paper: splicing and copy-move. Splicing is performed by inserting a part of an image into another image. On the other hand, copy-move forgery is performed by copying a part of the image into another position in the same image. The proposed approach for splicing detection is based on the assumption that illumination between the original and tampered images is different. To detect the difference between the original and tampered images, the homomorphic transform separates the illumination component from the reflectance component. The illumination histogram derivative is used for detecting the difference in illumination, and hence forgery detection is accomplished. Prior to performing the forgery detection process, some pre-processing techniques, including histogram equalization, histogram matching, high-pass filtering, homomorphic enhancement, and single image super-resolution, are introduced to reinforce the details and changes between the original and embedded sections. The proposed approach for copy-move forgery detection is performed with the Speeded Up Robust Features (SURF) algorithm, which extracts feature points and feature vectors. Searching for the copied partition is accomplished through matching with Euclidian distance and hierarchical clustering. In addition, some preprocessing methods are used with the SURF algorithm, such as histogram equalization and single-mage super-resolution. Simulation results proved the feasibility and the robustness of the pre-processing step in homomorphic detection and SURF detection algorithms for splicing and copy-move forgery detection, respectively.","PeriodicalId":10440,"journal":{"name":"Cmc-computers Materials & Continua","volume":"36 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75847157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Numerical Analysis of Laterally Loaded Long Piles in Cohesionless Soil 无粘性土中横向荷载长桩的数值分析

IF 3.1 4区计算机科学

Cmc-computers Materials & Continua Pub Date : 2022-01-01 DOI: 10.32604/cmc.2022.021899

Ayman Abd-Elhamed, M. Fathy, K. M. Abdelgaber

{"title":"Numerical Analysis of Laterally Loaded Long Piles in Cohesionless Soil","authors":"Ayman Abd-Elhamed, M. Fathy, K. M. Abdelgaber","doi":"10.32604/cmc.2022.021899","DOIUrl":"https://doi.org/10.32604/cmc.2022.021899","url":null,"abstract":": The capability of piles to withstand horizontal loads is a major design issue. The current research work aims to investigate numerically the responses of laterally loaded piles at working load employing the concept of a beam-on-Winkler-foundation model. The governing differential equation for a laterally loaded pile on elastic subgrade is derived. Based on Legendre-Galerkin method and Runge-Kutta formulas of order four and five, the flexural equation of long piles embedded in homogeneous sandy soils with modulus of subgrade reaction linearly variable with depth is solved for both free- and fixed-headed piles. Mathematica, as one of the world’s leading computational software, was employed for the implementation of solutions. The proposed numerical techniques provide the responses for the entire pile length under the applied lateral load. The utilized numerical approaches are validated against experimental and analytical results of previously published works showing a more accurate estimation of the response of laterally loaded piles. Therefore, the proposed approaches can maintain both mathematical simplicity and comparable accuracy with the experimental results.","PeriodicalId":10440,"journal":{"name":"Cmc-computers Materials & Continua","volume":"30 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75113724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Realistic Smile Expression Recognition Approach Using Ensemble Classifier with Enhanced Bagging 基于增强Bagging的集成分类器的真实微笑表情识别方法

IF 3.1 4区计算机科学

Cmc-computers Materials & Continua Pub Date : 2022-01-01 DOI: 10.32604/cmc.2022.019125

Oday A. Hassen, N. Azman Abu, Z. Zainal Abidin, Saad M. Darwish

{"title":"Realistic Smile Expression Recognition Approach Using Ensemble Classifier with Enhanced Bagging","authors":"Oday A. Hassen, N. Azman Abu, Z. Zainal Abidin, Saad M. Darwish","doi":"10.32604/cmc.2022.019125","DOIUrl":"https://doi.org/10.32604/cmc.2022.019125","url":null,"abstract":": A robust smile recognition system could be widely used for many real-world applications. Classification of a facial smile in an unconstrained setting is difficult due to the invertible and wide variety in face images. In this paper, an adaptive model for smile expression classification is suggested that integrates a fast features extraction algorithm and cascade classifiers. Our model takes advantage of the intrinsic association between face detection, smile, and other face features to alleviate the over-fitting issue on the limited training set and increase classification results. The features are extracted taking into account to exclude any unnecessary coefficients in the feature vector; thereby enhancing the discriminatory capacity of the extracted features and reducing the computational process. Still, the main causes of error in learning are due to noise, bias, and variance. Ensemble helps to minimize these factors. Combinations of multiple classifiers decrease variance, especially in the case of unstable classifiers, and may produce a more reliable classification than a single classifier. However, a shortcoming of bagging as the best ensemble classifier is its random selection, where the classification performance relies on the chance to pick an appropriate subset of training items. The suggested model employs a modified form of bagging while creating training sets to deal with this challenge (error-based bootstrapping). The experimental results for smile classification on the JAFFE, CK+, and CK+48 benchmark datasets show the feasibility of our proposed model.","PeriodicalId":10440,"journal":{"name":"Cmc-computers Materials & Continua","volume":"57 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88242852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Diabetes Prediction Algorithm Using Recursive Ridge Regression L2 基于递归岭回归的糖尿病预测算法

IF 3.1 4区计算机科学

Cmc-computers Materials & Continua Pub Date : 2022-01-01 DOI: 10.32604/cmc.2022.020687

A. Velu, Menakadevi Thangavelu

引用次数: 2

PSO Based Multi-Objective Approach for Controlling PID Controller 基于粒子群算法的PID控制器多目标控制方法

IF 3.1 4区计算机科学

Cmc-computers Materials & Continua Pub Date : 2022-01-01 DOI: 10.32604/cmc.2022.019217

H. Goud, Prakash Chandra Sharma, K. Nisar, Ag. Asri Ag. Ibrahim, Muhammad Reazul Haque, Narendra Singh Yadav, P. Swarnkar, Manoj Gupta, Laxmi Chand

{"title":"PSO Based Multi-Objective Approach for Controlling PID Controller","authors":"H. Goud, Prakash Chandra Sharma, K. Nisar, Ag. Asri Ag. Ibrahim, Muhammad Reazul Haque, Narendra Singh Yadav, P. Swarnkar, Manoj Gupta, Laxmi Chand","doi":"10.32604/cmc.2022.019217","DOIUrl":"https://doi.org/10.32604/cmc.2022.019217","url":null,"abstract":": CSTR (Continuous stirred tank reactor) is employed in process control and chemical industries to improve response characteristics and system efficiency. It has a highly nonlinear characteristic that includes complexities in its control and design. Dynamic performance is compassionate to change in system parameters which need more effort for planning a significant controller for CSTR. The reactor temperature changes in either direction from the defined reference value. It is important to note that the intensity of chemical actions inside the CSTR is dependent on the various levels of temperature, and deviation from reference values may cause degradation of biomass quality. Design and implementation of an appropriate adaptive controller for such a nonlinear system are essential. In this paper, a conventional Proportional Integral Derivative (PID) controller is designed. The conventional techniques to deal with constraints suffer severe limitations like it has fixed controller parameters. Hence, A novel method is applied for computing the PID controller parameters using a swarm algorithm that overcomes the conventional controller’s limitation. In the proposed technique, PID parameters are tuned by Particle Swarm Optimization (PSO). It is not easy to choose the suitable objective function to design a PID controller using PSO to get an optimal response. In this article, a multi-objective function is proposed for PSO based controller design of CSTR.","PeriodicalId":10440,"journal":{"name":"Cmc-computers Materials & Continua","volume":"203 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72947920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Adversarial Neural Network Classifiers for COVID-19 Diagnosis in Ultrasound Images 对抗神经网络分类器在超声图像中诊断COVID-19

IF 3.1 4区计算机科学

Cmc-computers Materials & Continua Pub Date : 2022-01-01 DOI: 10.32604/cmc.2022.018564

M. E. Karar, M. Shouman, C. Chalopin

{"title":"Adversarial Neural Network Classifiers for COVID-19 Diagnosis in Ultrasound Images","authors":"M. E. Karar, M. Shouman, C. Chalopin","doi":"10.32604/cmc.2022.018564","DOIUrl":"https://doi.org/10.32604/cmc.2022.018564","url":null,"abstract":"The novel Coronavirus disease 2019 (COVID-19) pandemic has begun in China and is still affecting thousands of patient lives worldwide daily. Although Chest X-ray and Computed Tomography are the gold standard medical imaging modalities for diagnosing potentially infected COVID-19 cases, applying Ultrasound (US) imaging technique to accomplish this crucial diagnosing task has attracted many physicians recently. In this article, we propose two modified deep learning classifiers to identify COVID-19 and pneumonia diseases in US images, based on generative adversarial neural networks (GANs). The proposed image classifiers are a semi-supervised GAN and a modified GAN with auxiliary classifier. Each one includes a modified discriminator to identify the class of the US image using semi-supervised learning technique, keeping its main function of defining the “realness” of tested images. Extensive tests have been successfully conducted on public dataset of US images acquired with a convex US probe. This study demonstrated the feasibility of using chest US images with two GAN classifiers as a new radiological tool for clinical check of COVID-19 patients. The results of our proposed GAN models showed that high accuracy values above 91.0% were obtained under different sizes of limited training data, outperforming other deep learning-based methods, such as transfer learning models in the recent studies. Consequently, the clinical implementation of our computer-aided diagnosis of US-COVID-19 is the future work of this study. © 2021 Tech Science Press. All rights reserved.","PeriodicalId":10440,"journal":{"name":"Cmc-computers Materials & Continua","volume":"19 31","pages":""},"PeriodicalIF":3.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72535408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Plant Identification Using Fitness-Based Position Update in Whale Optimization Algorithm 鲸鱼优化算法中基于适应度位置更新的植物识别

IF 3.1 4区计算机科学

Cmc-computers Materials & Continua Pub Date : 2022-01-01 DOI: 10.32604/cmc.2022.022177

Ayman Altameem, Sandeep Kumar, Ramesh Chandra Poonia, Abdul Khader Jilani Saudagar

{"title":"Plant Identification Using Fitness-Based Position Update in Whale Optimization Algorithm","authors":"Ayman Altameem, Sandeep Kumar, Ramesh Chandra Poonia, Abdul Khader Jilani Saudagar","doi":"10.32604/cmc.2022.022177","DOIUrl":"https://doi.org/10.32604/cmc.2022.022177","url":null,"abstract":": Since the beginning of time, humans have relied on plants for food, energy, and medicine. Plants are recognized by leaf, flower, or fruit and linked to their suitable cluster. Classification methods are used to extract and select traits that are helpful in identifying a plant. In plant leaf image categorization, each plant is assigned a label according to its classification. The purpose of classifying plant leaf images is to enable farmers to recognize plants, leading to the management of plants in several aspects. This study aims to present a modified whale optimization algorithm and categorizes plant leaf images into classes. This modified algorithm works on different sets of plant leaves. The proposed algorithm examines several benchmark functions with ade-quate performance. On ten plant leaf images, this classification method was validated. The proposed model calculates precision, recall, F-measurement, and accuracy for ten different plant leaf image datasets and compares these parameters with other existing algorithms. Based on experimental data, it is observed that the accuracy of the proposed method outperforms the accuracy of different algorithms under consideration and improves accuracy by 5%.","PeriodicalId":10440,"journal":{"name":"Cmc-computers Materials & Continua","volume":"19 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73300195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2