Considering the need to optimize electric vehicle performance and the impact of efficient driveline configurations in achieving this, a brief study has been conducted. The drivelines of electric vehicles (EV) are critically examined in this survey. Also, promising motor topologies for usage in electric vehicles are presented. Additionally, the benefits and drawbacks of each kind of electric motor are examined from a system viewpoint. The majority of commercially available EV are powered by a permanent magnet motor or single induction type motors and a standard mechanical differential driveline. Considering these, a holistic review has been performed by including driveline configurations and different battery types. The authors suggest that motors be evaluated and contrasted using a standardized driving cycle.
{"title":"Trends and Challenges in Electric Vehicle Motor Drivelines - A Review","authors":"Ashwin Kavasseri Venkitaraman, Venkata Satya Rahul Kosuru","doi":"10.32985/ijeces.14.4.12","DOIUrl":"https://doi.org/10.32985/ijeces.14.4.12","url":null,"abstract":"Considering the need to optimize electric vehicle performance and the impact of efficient driveline configurations in achieving this, a brief study has been conducted. The drivelines of electric vehicles (EV) are critically examined in this survey. Also, promising motor topologies for usage in electric vehicles are presented. Additionally, the benefits and drawbacks of each kind of electric motor are examined from a system viewpoint. The majority of commercially available EV are powered by a permanent magnet motor or single induction type motors and a standard mechanical differential driveline. Considering these, a holistic review has been performed by including driveline configurations and different battery types. The authors suggest that motors be evaluated and contrasted using a standardized driving cycle.","PeriodicalId":41912,"journal":{"name":"International Journal of Electrical and Computer Engineering Systems","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48553945","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}
In image processing applications, texture is the most important element utilized by human visual systems for distinguishing dissimilar objects in a scene. In this research article, a variational model based on the level set is implemented for crosshatched texture segmentation. In this study, the proposed model’s performance is validated on the Brodatz texture dataset. The cross-hatched texture segmentation in the lower resolution texture images is difficult, due to the computational and memory requirements. The aforementioned issue has been resolved by implementing a variational model based on the level set that enables efficient segmentation in both low and high-resolution images with automatic selection of the filter size. In the proposed model, the multi-resolution feature obtained from the frequency domain filters enhances the dissimilarity between the regions of crosshatched textures that have low-intensity variations. Then, the resultant images are integrated with a level set-based active contour model that addresses the segmentation of crosshatched texture images. The noise added during the segmentation process is eliminated by morphological processing. The experiments conducted on the Brodatz texture dataset demonstrated the effectiveness of the proposed model, and the obtained results are validated in terms of Intersection over the Union (IoU) index, accuracy, precision, f1-score and recall. The extensive experimental investigation shows that the proposed model effectively segments the region of interest in close correspondence with the original image. The proposed segmentation model with a multi-support vector machine has achieved a classification accuracy of 99.82%, which is superior to the comparative model (modified convolutional neural network with whale optimization algorithm). The proposed model almost showed a 0.11% improvement in classification accuracy related to the existing model.
在图像处理应用中，纹理是人类视觉系统用来区分场景中不同物体的最重要的元素。本文提出了一种基于水平集的变分模型，用于交叉纹理分割。在本研究中，在Brodatz纹理数据集上验证了该模型的性能。由于对计算量和内存的要求，在低分辨率纹理图像中进行交叉孵化纹理分割是很困难的。通过实现基于水平集的变分模型，上述问题已经得到解决，该模型可以在低分辨率和高分辨率图像中进行有效分割，并自动选择过滤器大小。在该模型中，由频域滤波器获得的多分辨率特征增强了具有低强度变化的交叉纹理区域之间的不相似性。然后，将生成的图像与基于水平集的活动轮廓模型集成，该模型解决了交叉纹理图像的分割问题。通过形态学处理消除分割过程中增加的噪声。在Brodatz纹理数据集上进行的实验验证了该模型的有效性，并从IoU (Intersection over The Union)指数、准确率、精密度、f1-score和召回率等方面对所得结果进行了验证。大量的实验研究表明，该模型可以有效地分割出与原始图像密切对应的感兴趣区域。本文提出的多支持向量机分割模型的分类准确率达到99.82%，优于对比模型(带有鲸鱼优化算法的改进卷积神经网络)。与现有模型相比，该模型的分类精度提高了0.11%。
{"title":"Multi-Resolution Feature Embedded Level Set Model for Crosshatched Texture Segmentation","authors":"P. K., Sadyojatha K.M.","doi":"10.32985/ijeces.14.4.1","DOIUrl":"https://doi.org/10.32985/ijeces.14.4.1","url":null,"abstract":"In image processing applications, texture is the most important element utilized by human visual systems for distinguishing dissimilar objects in a scene. In this research article, a variational model based on the level set is implemented for crosshatched texture segmentation. In this study, the proposed model’s performance is validated on the Brodatz texture dataset. The cross-hatched texture segmentation in the lower resolution texture images is difficult, due to the computational and memory requirements. The aforementioned issue has been resolved by implementing a variational model based on the level set that enables efficient segmentation in both low and high-resolution images with automatic selection of the filter size. In the proposed model, the multi-resolution feature obtained from the frequency domain filters enhances the dissimilarity between the regions of crosshatched textures that have low-intensity variations. Then, the resultant images are integrated with a level set-based active contour model that addresses the segmentation of crosshatched texture images. The noise added during the segmentation process is eliminated by morphological processing. The experiments conducted on the Brodatz texture dataset demonstrated the effectiveness of the proposed model, and the obtained results are validated in terms of Intersection over the Union (IoU) index, accuracy, precision, f1-score and recall. The extensive experimental investigation shows that the proposed model effectively segments the region of interest in close correspondence with the original image. The proposed segmentation model with a multi-support vector machine has achieved a classification accuracy of 99.82%, which is superior to the comparative model (modified convolutional neural network with whale optimization algorithm). The proposed model almost showed a 0.11% improvement in classification accuracy related to the existing model.","PeriodicalId":41912,"journal":{"name":"International Journal of Electrical and Computer Engineering Systems","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44452869","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}
Venkata Sai Charishma Pathala, V. Y. Jayasree Pappu
The electronic devices are exposed to external electromagnetic signals that produce an unwanted signal called noise in the circuit, which causes electromagnetic interference [EMI] problems. It occurs in two modes: radiated mode and conducted mode. In the radiation mode, the shielding technique is used for radiation mode, in conduction mode filtering technique is used. The design of an EMI filter depends upon the type of noise generated by the Switched Mode Power supply circuit [SMPS]. The SMPS circuit used in this paper is a DC-DC power converter, the Boost converter is a step-up converter and Buck converter is step down converter are considered as equipment for generation of noise, the Line Impedance Stabilization Network [LISN]is used for generating the common output impedance to the power converters, the EMI filters are designed to eliminate noise generated by the circuits. There noise generated by this power converters is Common Mode [CM] noise and Differential Mode [DM] noise. The separation of noise from the equipment is done by using a noise separator. In this paper, CM noise generated by these power converters is eliminated by designing an EMI filter called an inductor filter and a PI filter. The comparison between the LC inductor filter and the PI filter for the boost and buck converters is observed. The PI filter has better performance characteristics when compared to the inductor filter for both SMPS circuits as per the Comité International Special des Perturbations Radioélectriques [CISPR] standards. This standard gives the conducted emission range for different electronic devices.
{"title":"Elimination of CM Noise from SMPS Circuit using EMI Filter","authors":"Venkata Sai Charishma Pathala, V. Y. Jayasree Pappu","doi":"10.32985/ijeces.14.4.10","DOIUrl":"https://doi.org/10.32985/ijeces.14.4.10","url":null,"abstract":"The electronic devices are exposed to external electromagnetic signals that produce an unwanted signal called noise in the circuit, which causes electromagnetic interference [EMI] problems. It occurs in two modes: radiated mode and conducted mode. In the radiation mode, the shielding technique is used for radiation mode, in conduction mode filtering technique is used. The design of an EMI filter depends upon the type of noise generated by the Switched Mode Power supply circuit [SMPS]. The SMPS circuit used in this paper is a DC-DC power converter, the Boost converter is a step-up converter and Buck converter is step down converter are considered as equipment for generation of noise, the Line Impedance Stabilization Network [LISN]is used for generating the common output impedance to the power converters, the EMI filters are designed to eliminate noise generated by the circuits. There noise generated by this power converters is Common Mode [CM] noise and Differential Mode [DM] noise. The separation of noise from the equipment is done by using a noise separator. In this paper, CM noise generated by these power converters is eliminated by designing an EMI filter called an inductor filter and a PI filter. The comparison between the LC inductor filter and the PI filter for the boost and buck converters is observed. The PI filter has better performance characteristics when compared to the inductor filter for both SMPS circuits as per the Comité International Special des Perturbations Radioélectriques [CISPR] standards. This standard gives the conducted emission range for different electronic devices.","PeriodicalId":41912,"journal":{"name":"International Journal of Electrical and Computer Engineering Systems","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47111417","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}
Shamla Beevi A, R. S, Saidalavi Kalady, Jenu James Chakola
In computer vision, the extraction of robust features from images to construct models that automate image recognition and classification tasks is a prominent field of research. Handcrafted feature extraction and representation techniques become critical when dealing with limited hardware resource settings, low-quality images, and larger datasets. We propose two state-of-the-art handcrafted feature extraction techniques, Oriented FAST and Rotated BRIEF (ORB) and Accelerated KAZE (AKAZE), in combination with Bag of Visual Word (BOVW), to classify standard echocardiogram views using Machine learning (ML) algorithms. These novel approaches, ORB and AKAZE, which are rotation, scale, illumination, and noise invariant methods, outperform traditional methods. The despeckling algorithm Speckle Reduction Anisotropic Diffusion (SRAD), which is based on the Partial Differential Equation (PDE), was applied to echocardiogram images before feature extraction. Support Vector Machine (SVM), decision tree, and random forest algorithms correctly classified the feature vectors obtained from the ORB with accuracy rates of 96.5%, 76%, and 97.7%, respectively. Additionally, AKAZE's SVM, decision tree, and random forest algorithms outperformed state-of-the-art techniques with accuracy rates of 97.7%, 90%, and 99%, respectively.
在计算机视觉中，从图像中提取鲁棒特征以构建自动图像识别和分类任务的模型是一个突出的研究领域。当处理有限的硬件资源设置、低质量图像和较大的数据集时，手工特征提取和表示技术变得至关重要。我们提出了两种最先进的手工特征提取技术，定向FAST和旋转BRIEF (ORB)和加速KAZE (AKAZE)，结合Bag of Visual Word (BOVW)，使用机器学习(ML)算法对标准超声心动图视图进行分类。这些新颖的方法ORB和AKAZE，即旋转、缩放、光照和噪声不变性方法，优于传统方法。在超声心动图图像特征提取之前，将基于偏微分方程(PDE)的散斑减少各向异性扩散(SRAD)去斑算法应用于图像去斑。支持向量机(SVM)、决策树(decision tree)和随机森林(random forest)算法对ORB得到的特征向量进行正确分类，准确率分别为96.5%、76%和97.7%。此外，AKAZE的SVM、决策树和随机森林算法分别以97.7%、90%和99%的准确率优于最先进的技术。
{"title":"Feature Extraction Based on ORB- AKAZE for Echocardiogram View Classification","authors":"Shamla Beevi A, R. S, Saidalavi Kalady, Jenu James Chakola","doi":"10.32985/ijeces.14.4.3","DOIUrl":"https://doi.org/10.32985/ijeces.14.4.3","url":null,"abstract":"In computer vision, the extraction of robust features from images to construct models that automate image recognition and classification tasks is a prominent field of research. Handcrafted feature extraction and representation techniques become critical when dealing with limited hardware resource settings, low-quality images, and larger datasets. We propose two state-of-the-art handcrafted feature extraction techniques, Oriented FAST and Rotated BRIEF (ORB) and Accelerated KAZE (AKAZE), in combination with Bag of Visual Word (BOVW), to classify standard echocardiogram views using Machine learning (ML) algorithms. These novel approaches, ORB and AKAZE, which are rotation, scale, illumination, and noise invariant methods, outperform traditional methods. The despeckling algorithm Speckle Reduction Anisotropic Diffusion (SRAD), which is based on the Partial Differential Equation (PDE), was applied to echocardiogram images before feature extraction. Support Vector Machine (SVM), decision tree, and random forest algorithms correctly classified the feature vectors obtained from the ORB with accuracy rates of 96.5%, 76%, and 97.7%, respectively. Additionally, AKAZE's SVM, decision tree, and random forest algorithms outperformed state-of-the-art techniques with accuracy rates of 97.7%, 90%, and 99%, respectively.","PeriodicalId":41912,"journal":{"name":"International Journal of Electrical and Computer Engineering Systems","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46782309","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}
The development of economical and sustainable eco-friendly renewable source powered power electronic converters have become more attractive in various areas such as automotive, household and industrial applications etc., Bucking and boosting of voltage according to the requirement is also much needed. So, this work proposes a solar PV powered single switch buck-boost converter which reduces implementation cost, minimal voltage and current stress across the capacitors and diodes and less switching power losses. The work structure comprises of solar PV source with modified P and O algorithm based MPPT, single switch buck-boost dc-dc converter, battery backup to store excess energy, three phase inverter with sinusoidal PWM to find optimal switching angles for harmonic control and 3Φ induction motor load. Here reduction of THD is applied to the line to line voltage of the inverter. Performance analysis of the proposed circuit is done using MATLAB/SIMULINK platform. A detailed steady state analysis of the dc-dc converter topology is also analyzed to system stability. The proposed single switch buck-boost converter is designed to provide an output voltage and current of 363V, 45.5A DC from 520V, 35A PV array. The designed converter is then employed to run a three phase full bridge inverter with 440V, 15A AC. From the simulation results, it is found that the solar powered single switch buck-boost with MPPT is stable, efficient with minimal losses and less THD with better quality output.
{"title":"Design and analysis of three phase inverter based\u0000Solar PV powered single switch Buck-Boost converter with reduced THD for industrial applications","authors":"Maheshwari L., P. T. R.","doi":"10.32985/ijeces.14.4.11","DOIUrl":"https://doi.org/10.32985/ijeces.14.4.11","url":null,"abstract":"The development of economical and sustainable eco-friendly renewable source powered power electronic converters have become more attractive in various areas such as automotive, household and industrial applications etc., Bucking and boosting of voltage according to the requirement is also much needed. So, this work proposes a solar PV powered single switch buck-boost converter which reduces implementation cost, minimal voltage and current stress across the capacitors and diodes and less switching power losses. The work structure comprises of solar PV source with modified P and O algorithm based MPPT, single switch buck-boost dc-dc converter, battery backup to store excess energy, three phase inverter with sinusoidal PWM to find optimal switching angles for harmonic control and 3Φ induction motor load. Here reduction of THD is applied to the line to line voltage of the inverter. Performance analysis of the proposed circuit is done using MATLAB/SIMULINK platform. A detailed steady state analysis of the dc-dc converter topology is also analyzed to system stability. The proposed single switch buck-boost converter is designed to provide an output voltage and current of 363V, 45.5A DC from 520V, 35A PV array. The designed converter is then employed to run a three phase full bridge inverter with 440V, 15A AC. From the simulation results, it is found that the solar powered single switch buck-boost with MPPT is stable, efficient with minimal losses and less THD with better quality output.","PeriodicalId":41912,"journal":{"name":"International Journal of Electrical and Computer Engineering Systems","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49558412","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}
Online review data attracts the attention of researchers and practitioners in various fields, but its application in tourism is still limited. The social media data can finely reflect tourist arrivals forecasting. Accurate prediction of tourist arrivals is essential for tourism decision-makers. Although current studies have exploited deep learning and internet data (especially search engine data) to anticipate tourism demand more precisely, few have examined the viability of using social media data and deep learning algorithms to predict tourism demand. This study aims to find the key topics extracted from online reviews and integrate them into the deep learning model to forecast tourism demand. We present a novel forecasting model based on TripAdvisor reviews. Latent topics and their associated keywords are captured from reviews through Latent Dirichlet Allocation (LDA), These generated features are then employed as an additional feature into the deep learning (DL) algorithm to forecast the monthly tourist arrivals to Hong Kong from USA. We used machine learning models, artificial neural networks (ANNs), support vector regression (SVR), and random forest (RF) as benchmark models. The empirical results show that the proposed forecasting model is more accurate than other models, which rely only on historical data. Furthermore, our findings indicate that integration of the topics extracted from social media reviews can enhance the prediction.
{"title":"Deep learning approach and topic modelling for forecasting tourist arrivals","authors":"Houria Laaroussi, F. Guerouate, M. Sbihi","doi":"10.32985/ijeces.14.4.5","DOIUrl":"https://doi.org/10.32985/ijeces.14.4.5","url":null,"abstract":"Online review data attracts the attention of researchers and practitioners in various fields, but its application in tourism is still limited. The social media data can finely reflect tourist arrivals forecasting. Accurate prediction of tourist arrivals is essential for tourism decision-makers. Although current studies have exploited deep learning and internet data (especially search engine data) to anticipate tourism demand more precisely, few have examined the viability of using social media data and deep learning algorithms to predict tourism demand. This study aims to find the key topics extracted from online reviews and integrate them into the deep learning model to forecast tourism demand. We present a novel forecasting model based on TripAdvisor reviews. Latent topics and their associated keywords are captured from reviews through Latent Dirichlet Allocation (LDA), These generated features are then employed as an additional feature into the deep learning (DL) algorithm to forecast the monthly tourist arrivals to Hong Kong from USA. We used machine learning models, artificial neural networks (ANNs), support vector regression (SVR), and random forest (RF) as benchmark models. The empirical results show that the proposed forecasting model is more accurate than other models, which rely only on historical data. Furthermore, our findings indicate that integration of the topics extracted from social media reviews can enhance the prediction.","PeriodicalId":41912,"journal":{"name":"International Journal of Electrical and Computer Engineering Systems","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45326667","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}
In an environment of rising internet usage, it is difficult to manage network traffic while maintaining a high quality of service. In highly trafficked networks, load balancers are crucial for ensuring the quality of service. Although different approaches to load-balancing have been proposed in traditional networks, some of them require manual reconfiguration of the device to accommodate new services due to a lack of programmability. These problems can be solved through the use of software-defined networks. This research paper presents a dynamic load-balancing algorithm for software-defined networks based on server response time and content mapping. The proposed technique dispatches requests to servers based on real-time server loads. This technique comprises three different modules, such as a request classification module, a server monitoring module, and an optimized dynamic load-balancing module using content-based routing. There are a variety of robust mathematical tools to address complex problems that have multiple objectives. Multi-Criteria Decision-Making is one of them. The performance of the proposed scheme has been validated by applying the Weighted Sum Method of the multi-criteria decision-making technique. The proposed method Server load balancing based on Multi-criteria Decision Making[SDLB-MCDM] is compared with different load-balancing schemes such as round robin, random, load-balancing scheme based on server response time [LBBSRT], and An SDN-aided mechanism for web load- balancing based on server statistics [SD-WLB]. The experimental results of SDLB-MCDM show a significant improvement of 58% when weights are equal and 50% when unequal weights are assigned to various QoS parameters in comparison with the ROUND ROBIN, RANDOM, LBBSRT and SD-WLB techniques.
{"title":"An Intelligent Server load balancing based on Multi-criteria decision-making in SDN","authors":"Vani K. A., Rama Mohan Babu K. N.","doi":"10.32985/ijeces.14.4.7","DOIUrl":"https://doi.org/10.32985/ijeces.14.4.7","url":null,"abstract":"In an environment of rising internet usage, it is difficult to manage network traffic while maintaining a high quality of service. In highly trafficked networks, load balancers are crucial for ensuring the quality of service. Although different approaches to load-balancing have been proposed in traditional networks, some of them require manual reconfiguration of the device to accommodate new services due to a lack of programmability. These problems can be solved through the use of software-defined networks. This research paper presents a dynamic load-balancing algorithm for software-defined networks based on server response time and content mapping. The proposed technique dispatches requests to servers based on real-time server loads. This technique comprises three different modules, such as a request classification module, a server monitoring module, and an optimized dynamic load-balancing module using content-based routing. There are a variety of robust mathematical tools to address complex problems that have multiple objectives. Multi-Criteria Decision-Making is one of them. The performance of the proposed scheme has been validated by applying the Weighted Sum Method of the multi-criteria decision-making technique. The proposed method Server load balancing based on Multi-criteria Decision Making[SDLB-MCDM] is compared with different load-balancing schemes such as round robin, random, load-balancing scheme based on server response time [LBBSRT], and An SDN-aided mechanism for web load- balancing based on server statistics [SD-WLB]. The experimental results of SDLB-MCDM show a significant improvement of 58% when weights are equal and 50% when unequal weights are assigned to various QoS parameters in comparison with the ROUND ROBIN, RANDOM, LBBSRT and SD-WLB techniques.","PeriodicalId":41912,"journal":{"name":"International Journal of Electrical and Computer Engineering Systems","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49537157","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}
Gehan Mounir, A. Idrees, El Sayed M. Khater, Eman Mosallam, Ayman E. Khedr
Applying ISO 21001:2018 standard ensures that universities have a competitive advantage as well as the achievement of their objectives. This study aims to identify the impact of implementing ISO 21001: 2018 management systems standards on the performance quality of higher education institutions. The study investigates the reasons why private higher education institutions seek ISO standards certificates in general and the specifications of management systems for educational institutions in particular. The study applied a set of statistical testing methods on paired samples as well as independent samples to ensure quality assurance. The study also proposes the required prerequisites that should be considered. The study investigated a hypothesis stating that "there are no statistically significant differences before and after applying the ISO 21001:2018 management systems specification for educational institutions in improving the quality of performance in higher education institutions" which was rejected by conducting an experiment in Future University in Egypt and accepting the alternative hypothesis. The study confirmed the impact of quality which was previously investigated by prior research that has been discussed in this study. The study further presented the need to apply quality based on determined criteria which were not considered in prior studies. Moreover, the study proposed the impact of ISO standards in educational institutions in general and in Egypt in specific. This recommendation is proved by this study to enhance the quality level in educational institutions.
{"title":"The Impact of Applying ISO Standards Systems on Improving the Quality of the Performance in Higher Educational Institutions in Egypt","authors":"Gehan Mounir, A. Idrees, El Sayed M. Khater, Eman Mosallam, Ayman E. Khedr","doi":"10.32985/ijeces.14.4.9","DOIUrl":"https://doi.org/10.32985/ijeces.14.4.9","url":null,"abstract":"Applying ISO 21001:2018 standard ensures that universities have a competitive advantage as well as the achievement of their objectives. This study aims to identify the impact of implementing ISO 21001: 2018 management systems standards on the performance quality of higher education institutions. The study investigates the reasons why private higher education institutions seek ISO standards certificates in general and the specifications of management systems for educational institutions in particular. The study applied a set of statistical testing methods on paired samples as well as independent samples to ensure quality assurance. The study also proposes the required prerequisites that should be considered. The study investigated a hypothesis stating that \"there are no statistically significant differences before and after applying the ISO 21001:2018 management systems specification for educational institutions in improving the quality of performance in higher education institutions\" which was rejected by conducting an experiment in Future University in Egypt and accepting the alternative hypothesis. The study confirmed the impact of quality which was previously investigated by prior research that has been discussed in this study. The study further presented the need to apply quality based on determined criteria which were not considered in prior studies. Moreover, the study proposed the impact of ISO standards in educational institutions in general and in Egypt in specific. This recommendation is proved by this study to enhance the quality level in educational institutions.","PeriodicalId":41912,"journal":{"name":"International Journal of Electrical and Computer Engineering Systems","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46199978","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}
In this era of smartphones, a huge amount of multimedia files like audio, video, images, animation, and plain text are shared. And with this comes the threat of data being stolen and misused. Most people don’t think about the security of data before uploading it to any platform. Most apps used on smartphones upload our data to their server. Not only this, but other third-party apps can also read that data while it is being transmitted. One solution to this problem is encrypting the data before sharing it and decrypting it back at the other end so that even if it is intercepted in between the transmission, it would be impossible to decrypt it. In this paper, a newly designed hybrid encryption algorithm EMAES that includes the efficiency of MAES (Modified Advanced Encryption Standard) and security of ECC (Elliptic Curve Cryptography) was implemented in MATLAB as well as in android studio 4.0. using a mobile messaging application. Also, it was tested for different speeds and security parameters. Further, it was compared with standard algorithms like the RC4, RC6 and Blowfish as well as with other hybrid algorithms like RC4+ECC, RC6+ECC and Blowfish+ECC. The EMAES was found 30% more efficient in terms of encryption and decryption time. The security of EMAES also showed improvement when compared with other hybrid algorithms for parameters like SSIM (structural similarity index measure), SNR (Signal to Noise Ratio), PSNR(Peak Signal to Noise Ratio), MSE (Mean Squared Error) and RMSE (Root Mean Squared Error). And finally, no significant improvement was found in the CPU and RAM usage.
在这个智能手机时代，共享了大量的多媒体文件，如音频、视频、图像、动画和纯文本。随之而来的是数据被窃取和滥用的威胁。大多数人在将数据上传到任何平台之前都不会考虑数据的安全性。智能手机上使用的大多数应用程序都会将我们的数据上传到他们的服务器。不仅如此，其他第三方应用程序也可以在数据传输时读取数据。这个问题的一个解决方案是在共享数据之前对数据进行加密，并在另一端将其解密，这样即使在传输之间被拦截，也不可能对其进行解密，在MATLAB和android studio 4.0中实现了一种新设计的混合加密算法EMAES，该算法既考虑了MAES（Modified Advanced encryption Standard）的效率，又考虑了ECC（Elliptic Curve Cryptography）的安全性。使用移动消息收发应用程序。此外，它还针对不同的速度和安全参数进行了测试。此外，将其与诸如RC4、RC6和Blowfish的标准算法以及诸如RC4+ECC、RC6+ECC和Blowfish+ECC的其他混合算法进行比较。在加密和解密时间方面，EMAES的效率提高了30%。与其他混合算法相比，EMAES在SSIM（结构相似性指数测度）、SNR（信噪比）、PSNR（峰值信噪比）、MSE（均方误差）和RMSE（均方根误差）等参数方面的安全性也有所提高。最后，在CPU和RAM的使用方面没有发现显著的改进。
{"title":"Implementation and evaluation of EMAES – A hybrid encryption algorithm for sharing multimedia files with more security and speed","authors":"Riddhi Somaiya, Atul M. Gonsai, Rashmin Tannna","doi":"10.32985/ijeces.14.4.4","DOIUrl":"https://doi.org/10.32985/ijeces.14.4.4","url":null,"abstract":"In this era of smartphones, a huge amount of multimedia files like audio, video, images, animation, and plain text are shared. And with this comes the threat of data being stolen and misused. Most people don’t think about the security of data before uploading it to any platform. Most apps used on smartphones upload our data to their server. Not only this, but other third-party apps can also read that data while it is being transmitted. One solution to this problem is encrypting the data before sharing it and decrypting it back at the other end so that even if it is intercepted in between the transmission, it would be impossible to decrypt it. In this paper, a newly designed hybrid encryption algorithm EMAES that includes the efficiency of MAES (Modified Advanced Encryption Standard) and security of ECC (Elliptic Curve Cryptography) was implemented in MATLAB as well as in android studio 4.0. using a mobile messaging application. Also, it was tested for different speeds and security parameters. Further, it was compared with standard algorithms like the RC4, RC6 and Blowfish as well as with other hybrid algorithms like RC4+ECC, RC6+ECC and Blowfish+ECC. The EMAES was found 30% more efficient in terms of encryption and decryption time. The security of EMAES also showed improvement when compared with other hybrid algorithms for parameters like SSIM (structural similarity index measure), SNR (Signal to Noise Ratio), PSNR(Peak Signal to Noise Ratio), MSE (Mean Squared Error) and RMSE (Root Mean Squared Error). And finally, no significant improvement was found in the CPU and RAM usage.","PeriodicalId":41912,"journal":{"name":"International Journal of Electrical and Computer Engineering Systems","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48200960","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}
There are various challenges in identifying the speakers accurately. The Extraction of discriminative features is a vital task for accurate identification in the speaker identification task. Nowadays, speaker identification is widely investigated using deep learning. The complex and noisy speech data affects the performance of Mel Frequency Cepstral Coefficients (MFCC); hence, MFCC fails to represent the speaker characteristics accurately. In this proposed work, a novel text-independent speaker identification system is developed to enhance the performance by fusion of Log-MelSpectrum and excitation features. The excitation information is obtained due to the vibration of vocal folds, and it is represented using Linear Prediction (LP) residual. The various types of features extracted from the excitation are residual phase, sharpness, Energy of Excitation (EoE), and Strength of Excitation (SoE). The extracted features were processed with the dilated convolution neural network (dilated CNN) to fulfill the identification task. The extensive evaluation showed that the fusion of excitation features gives better results than the existing methods. The accuracy reaches 94.12% for 11 complex classes and 91.34% for 80 speakers, and Equal Error Rate (EER) is reduced to 1.16% for the proposed model. The proposed model is tested with the Librispeech corpus using Matlab 2021b tool, outperforming the existing baseline models. The proposed model achieves an accuracy improvement of 1.34% compared to the baseline system.
{"title":"Enhancement in Speaker Identification through Feature Fusion using Advanced Dilated Convolution Neural Network","authors":"Hema Kumar Pentapati, S. K","doi":"10.32985/ijeces.14.3.8","DOIUrl":"https://doi.org/10.32985/ijeces.14.3.8","url":null,"abstract":"There are various challenges in identifying the speakers accurately. The Extraction of discriminative features is a vital task for accurate identification in the speaker identification task. Nowadays, speaker identification is widely investigated using deep learning. The complex and noisy speech data affects the performance of Mel Frequency Cepstral Coefficients (MFCC); hence, MFCC fails to represent the speaker characteristics accurately. In this proposed work, a novel text-independent speaker identification system is developed to enhance the performance by fusion of Log-MelSpectrum and excitation features. The excitation information is obtained due to the vibration of vocal folds, and it is represented using Linear Prediction (LP) residual. The various types of features extracted from the excitation are residual phase, sharpness, Energy of Excitation (EoE), and Strength of Excitation (SoE). The extracted features were processed with the dilated convolution neural network (dilated CNN) to fulfill the identification task. The extensive evaluation showed that the fusion of excitation features gives better results than the existing methods. The accuracy reaches 94.12% for 11 complex classes and 91.34% for 80 speakers, and Equal Error Rate (EER) is reduced to 1.16% for the proposed model. The proposed model is tested with the Librispeech corpus using Matlab 2021b tool, outperforming the existing baseline models. The proposed model achieves an accuracy improvement of 1.34% compared to the baseline system.","PeriodicalId":41912,"journal":{"name":"International Journal of Electrical and Computer Engineering Systems","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41338678","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}
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