Classification of medical images is a very important area of research for both the medical industry and academia. In recent years, automated classification algorithms have become very important in most medical applications, saving time and effort, such as disease detection and diagnostic radiology. Deep learning offers a plethora of advantages when applied to medical image classification, revolutionizing medical diagnosis and patient care. In this study, deep convolutional neural networks (DCNNs) is used to classify medical im-ages and multi-wavelet transform will be applied to extract features. The proposed method aims to improve medical image classification accuracy, thereby assisting healthcare professionals in making more accurate and efficient diagnoses. DCNNs based on the VGG16 model were trained and used in this study. Combining VGG16, a powerful convolutional neural network (CNN), with multiwavelet transform offers several advantages for image processing and analysis tasks, particularly in areas like image classification and feature extraction. To evaluate the performance of the proposed method six publicly available brain tumour MRI datasets are analysed with DCNNs. A fully connected layer is used to categorize the extracted features. According to the results, the deep CNN model combined with the multi-wavelet trans-form achieves an impressive accuracy of 96.43 %. It is evident from this high level of accuracy that the proposed approach is effective in accurately classifying medical images.
{"title":"Enhancing Medical Image Classification: A Deep Learning Perspective with Multi Wavelet Transform","authors":"Maryam. I. Al-Khuzaie, W. A. Al-Jawher","doi":"10.36371/port.2023.4.7","DOIUrl":"https://doi.org/10.36371/port.2023.4.7","url":null,"abstract":"Classification of medical images is a very important area of research for both the medical industry and academia. In recent years, automated classification algorithms have become very important in most medical applications, saving time and effort, such as disease detection and diagnostic radiology. Deep learning offers a plethora of advantages when applied to medical image classification, revolutionizing medical diagnosis and patient care. In this study, deep convolutional neural networks (DCNNs) is used to classify medical im-ages and multi-wavelet transform will be applied to extract features. The proposed method aims to improve medical image classification accuracy, thereby assisting healthcare professionals in making more accurate and efficient diagnoses. DCNNs based on the VGG16 model were trained and used in this study. Combining VGG16, a powerful convolutional neural network (CNN), with multiwavelet transform offers several advantages for image processing and analysis tasks, particularly in areas like image classification and feature extraction. To evaluate the performance of the proposed method six publicly available brain tumour MRI datasets are analysed with DCNNs. A fully connected layer is used to categorize the extracted features. According to the results, the deep CNN model combined with the multi-wavelet trans-form achieves an impressive accuracy of 96.43 %. It is evident from this high level of accuracy that the proposed approach is effective in accurately classifying medical images.","PeriodicalId":502904,"journal":{"name":"Journal Port Science Research","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139159139","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}
Through the development of communication technology, fast and efficient tools are required to practically secure the process of data exchange in securing images. This paper presents a new method of encryption for protecting images against many attacks from unsafe public networks. Lorenz chaos map is used to generate a sequence of random numbers for each stage depending on the initial parameters. The Hunter Prey optimization algorithm is applied in order to obtain these parameters to use them based on the original image. Therefore, the random sequence number generated by the Lorenz chaotic map will be different from one image to another. That will make it unpredictable and very difficult to discover the process of encryption. The results of simulation experiments demonstrate that the encryption algorithm have passed the plaintext sensitivity test with the NPCR of 0.99785 and the UACI of 0.33623. As well as the correlation coefficient test values in the three directions gave the values of (v = -0.0007, h = -0.0000, d = 0.0005). Also, the calculated information entropy test value was 7.9983. These results demonstrate that this algorithm is very strong enough to withstand the various types of attacks that images can be exposed during transmission on the Internet or any public network. The security analysis's comparison of the proposed changes to similar ones revealed that the proposed encryption system is more efficient.
{"title":"An Image Encryption Method Based on Lorenz Chaotic Map and Hunter-Prey Optimization","authors":"Qutaiba K. Abed, W. A. Al-Jawher","doi":"10.36371/port.2023.4.3","DOIUrl":"https://doi.org/10.36371/port.2023.4.3","url":null,"abstract":"Through the development of communication technology, fast and efficient tools are required to practically secure the process of data exchange in securing images. This paper presents a new method of encryption for protecting images against many attacks from unsafe public networks. Lorenz chaos map is used to generate a sequence of random numbers for each stage depending on the initial parameters. The Hunter Prey optimization algorithm is applied in order to obtain these parameters to use them based on the original image. Therefore, the random sequence number generated by the Lorenz chaotic map will be different from one image to another. That will make it unpredictable and very difficult to discover the process of encryption. The results of simulation experiments demonstrate that the encryption algorithm have passed the plaintext sensitivity test with the NPCR of 0.99785 and the UACI of 0.33623. As well as the correlation coefficient test values in the three directions gave the values of (v = -0.0007, h = -0.0000, d = 0.0005). Also, the calculated information entropy test value was 7.9983. These results demonstrate that this algorithm is very strong enough to withstand the various types of attacks that images can be exposed during transmission on the Internet or any public network. The security analysis's comparison of the proposed changes to similar ones revealed that the proposed encryption system is more efficient.","PeriodicalId":502904,"journal":{"name":"Journal Port Science Research","volume":"113 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139236962","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}
It can be extremely difficult to find the optimal solution in many complex optimization problems. The goal of optimization algorithms in such cases is to locate a feasible solution that is as close as possible to the optimal one. These algorithms are called metaheuristic optimization algorithms and the majority of them take their inspiration from nature and work to solve challenging problems in a variety of fields. In this paper, a combination between GWO and Coot algorithm was proposed. The effectiveness of the GWO algorithm has been demonstrated in many fields, including engineering and medicine. However, GWO has a disadvantage: the potential to enter the local minima due to a lack of diversity. GWO and the Coot algorithm were merged to fix this flaw. Ten benchmark functions were used to evaluate the performance of this hybrid technique, and its results were compared to those of other common optimization algorithms, including GWO, Cuckoo Search (CS), and the Shuffled Frog Leaping algorithm (SFLA). The results show that the suggested algorithm can provide results that are both competitive and more consistent than the other algorithms in most test functions.
{"title":"A proposed Hyper-Heuristic optimizer Nesting Grey Wolf Optimizer and COOT Algorithm for Multilevel Task","authors":"Afrah U. Mosaa, W. Al-Jawher","doi":"10.36371/port.2023.4.1","DOIUrl":"https://doi.org/10.36371/port.2023.4.1","url":null,"abstract":"It can be extremely difficult to find the optimal solution in many complex optimization problems. The goal of optimization algorithms in such cases is to locate a feasible solution that is as close as possible to the optimal one. These algorithms are called metaheuristic optimization algorithms and the majority of them take their inspiration from nature and work to solve challenging problems in a variety of fields. In this paper, a combination between GWO and Coot algorithm was proposed. The effectiveness of the GWO algorithm has been demonstrated in many fields, including engineering and medicine. However, GWO has a disadvantage: the potential to enter the local minima due to a lack of diversity. GWO and the Coot algorithm were merged to fix this flaw. Ten benchmark functions were used to evaluate the performance of this hybrid technique, and its results were compared to those of other common optimization algorithms, including GWO, Cuckoo Search (CS), and the Shuffled Frog Leaping algorithm (SFLA). The results show that the suggested algorithm can provide results that are both competitive and more consistent than the other algorithms in most test functions.","PeriodicalId":502904,"journal":{"name":"Journal Port Science Research","volume":"29 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139261065","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}
Rasha. A. Dihin, Ebtesam N. Al Shemmary, W. Al-Jawher
There are big differences between the field of view of the calculator and the field of natural languages, for example, in the field of vision, the difference is in the size of the object as well as in the accuracy of the pixels in the image, and this contradicts the words in the text, and this makes the adaptation of the transformers to see somewhat difficult.Very recently a vision transformer named Swin Transformer was introduced by the Microsoft research team in Asia to achieve state-of-the-art results for machine translation. The computational complexity is linear and proportional to the size of the input image, because the processing of subjective attention is within each local window separately, and thus results in processor maps that are hierarchical and in deeper layers, and thus serve as the backbone of the calculator's vision in image classification and dense recognition applications. This work focuses on applying the Swin transformer to a demonstrated mathematical example with step-by-step analysis. Additionally, extensive experimental results were carried out on several standardized databases from CIFAR-10, CIFAR-100, and MNIST. Their results showed that the Swin Transformer can achieve flexible memory savings. Test accuracy for CIFAR-10 gave a 71.54% score, while for the CIFAR-100 dataset the accuracy was 46.1%. Similarly, when the Swin transformer was applied to the MNIST dataset, the accuracy increased in comparison with other vision transformer results.
{"title":"Implementation Of The Swin Transformer and Its Application In Image Classification","authors":"Rasha. A. Dihin, Ebtesam N. Al Shemmary, W. Al-Jawher","doi":"10.36371/port.2023.4.2","DOIUrl":"https://doi.org/10.36371/port.2023.4.2","url":null,"abstract":"There are big differences between the field of view of the calculator and the field of natural languages, for example, in the field of vision, the difference is in the size of the object as well as in the accuracy of the pixels in the image, and this contradicts the words in the text, and this makes the adaptation of the transformers to see somewhat difficult.Very recently a vision transformer named Swin Transformer was introduced by the Microsoft research team in Asia to achieve state-of-the-art results for machine translation. The computational complexity is linear and proportional to the size of the input image, because the processing of subjective attention is within each local window separately, and thus results in processor maps that are hierarchical and in deeper layers, and thus serve as the backbone of the calculator's vision in image classification and dense recognition applications. This work focuses on applying the Swin transformer to a demonstrated mathematical example with step-by-step analysis. Additionally, extensive experimental results were carried out on several standardized databases from CIFAR-10, CIFAR-100, and MNIST. Their results showed that the Swin Transformer can achieve flexible memory savings. Test accuracy for CIFAR-10 gave a 71.54% score, while for the CIFAR-100 dataset the accuracy was 46.1%. Similarly, when the Swin transformer was applied to the MNIST dataset, the accuracy increased in comparison with other vision transformer results.","PeriodicalId":502904,"journal":{"name":"Journal Port Science Research","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139262130","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}
Abstract The study aims to test the effect of the independent variable (overlapping waves strategy) and the effect of its implications on the dependent variable (entrepreneurial motivation), for a sample of employees in the Ministry of Interior (the Ministry’s Agency for Administrative and Financial Affairs), represented by (general directors, directorate directors, and department directors), adults. Their number was (160) individuals, as the total study population amounted to (230) individuals. The (analytical exploratory approach) was adopted, and the (questionnaire) was the main tool for this, in addition to some personal interviews according to the requirements of the need for the study. A number of statistical methods were used, represented by analysis Confirmatory construct validity, the Pearson correlation coefficient, to measure the type and degree of relationship between the study variables, structural reliability analysis of the measurement tool (Cronbach's Alpha), and simple and multiple effect testing (structural equation modeling SEM), to determine differences in the sample answers, a set of The most important results are the presence of a positive correlation and a positive effect of the role of the overlapping waves strategy on entrepreneurial motivation.
{"title":"Overlapping Waves Strategy and Its Impact on Entrepreneurial Motivation","authors":"Ahmed Makki Saleh","doi":"10.36371/port.2023.3.9","DOIUrl":"https://doi.org/10.36371/port.2023.3.9","url":null,"abstract":"Abstract The study aims to test the effect of the independent variable (overlapping waves strategy) and the effect of its implications on the dependent variable (entrepreneurial motivation), for a sample of employees in the Ministry of Interior (the Ministry’s Agency for Administrative and Financial Affairs), represented by (general directors, directorate directors, and department directors), adults. Their number was (160) individuals, as the total study population amounted to (230) individuals. The (analytical exploratory approach) was adopted, and the (questionnaire) was the main tool for this, in addition to some personal interviews according to the requirements of the need for the study. A number of statistical methods were used, represented by analysis Confirmatory construct validity, the Pearson correlation coefficient, to measure the type and degree of relationship between the study variables, structural reliability analysis of the measurement tool (Cronbach's Alpha), and simple and multiple effect testing (structural equation modeling SEM), to determine differences in the sample answers, a set of The most important results are the presence of a positive correlation and a positive effect of the role of the overlapping waves strategy on entrepreneurial motivation.","PeriodicalId":502904,"journal":{"name":"Journal Port Science Research","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139267356","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 societies, the change of living patterns, and the interference of investment in various sectors, made most of the legislations directing to setting guarantees, which is one of the reasons that prompt investors to decide where their destination in the world will be precisely, by granting the investor guarantees against any risks that he is exposed to in his investment project. There has been an increased interest in studying tax policies and their effects that may result from their application as a method to direct the economy, as the role of the state has evolved from an intervening state with specific tasks to a state that guards economic activity with the aim of creating balance and achieving stability. The state’s role was to translate the opinions of some economists who advocated The necessity of expanding its functions, stressing that it is the only way to prevent the destruction of economic institutions.
{"title":"The Effectiveness of Tax Mechanisms in Encouraging and Attracting Investment","authors":"Aseel Kamel Agel","doi":"10.36371/port.2023.2.6","DOIUrl":"https://doi.org/10.36371/port.2023.2.6","url":null,"abstract":"The development of societies, the change of living patterns, and the interference of investment in various sectors, made most of the legislations directing to setting guarantees, which is one of the reasons that prompt investors to decide where their destination in the world will be precisely, by granting the investor guarantees against any risks that he is exposed to in his investment project. There has been an increased interest in studying tax policies and their effects that may result from their application as a method to direct the economy, as the role of the state has evolved from an intervening state with specific tasks to a state that guards economic activity with the aim of creating balance and achieving stability. The state’s role was to translate the opinions of some economists who advocated The necessity of expanding its functions, stressing that it is the only way to prevent the destruction of economic institutions.","PeriodicalId":502904,"journal":{"name":"Journal Port Science Research","volume":"106 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139312017","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：