Iraqi Journal for Computer Science and Mathematics最新文献_第3页

Kernel semi-parametric model improvement based on quasi-oppositional learning pelican optimization algorithm 基于准对立学习鹈鹕优化算法的核半参数模型改进

Iraqi Journal for Computer Science and Mathematics Pub Date : 2023-04-20 DOI: 10.52866/ijcsm.2023.02.02.013

Z. Algamal, F. AL-Taie, O. Qasim

引用次数: 0

An Articulate Heart Attack Detection System Using Mine Blast Optimization (MBO) Based Multilayer Perceptron Neural Network (MLPNN) Model 基于矿井爆破优化(MBO)的多层感知器神经网络(MLPNN)模型的清晰心梗检测系统

Iraqi Journal for Computer Science and Mathematics Pub Date : 2023-04-16 DOI: 10.52866/ijcsm.2023.02.02.012

Rajesh Pandian N, S. D, Selvaganesh N

{"title":"An Articulate Heart Attack Detection System Using Mine Blast Optimization (MBO) Based Multilayer Perceptron Neural Network (MLPNN) Model","authors":"Rajesh Pandian N, S. D, Selvaganesh N","doi":"10.52866/ijcsm.2023.02.02.012","DOIUrl":"https://doi.org/10.52866/ijcsm.2023.02.02.012","url":null,"abstract":"The creation of an automated system for heart disease detection was once one of the more common\u0000undertakings in the healthcare industries. For this purpose, the different types of big data analytics technologies are\u0000developed in the conventional works to predict the heart disease. Still, it limits with the problems associated to the\u0000elements of high complexity, time consumption, over fitting, and mis-prediction results. Because the previous\u0000methods did not optimize the best features, they did not give accurate results in heart attack detection, so the\u0000system is needed to control the death ratio.Therefore, the proposed work objects to implement a novel Mine Blast\u0000Optimization (MBO) based Multi-Layer Perceptron Neural Network (MLPNN) technique to predict the heart\u0000attack from the given datasets. The proposed detection framework includes the stages of preprocessing, feature\u0000optimization, and classification. Here, the regression based preprocessing model is implemented to normalize the\u0000attributes for increasing the quality. Then, the MBO technique is also used to choose the relevant features based on\u0000the best optimal solution. It also helps to reduce the increase the training of classifier with reduced time\u0000consumption and high detection accuracy. Finally, the MLPNN technique is utilized to predict the classified label\u0000as whether normal or disease affected. During analysis, the results of the proposed MBO-MLPNN technique is\u0000validated and compared by using various measures. Here the proposed method achieved 98% accuracy\u0000performance for heart attack detection than former methods.","PeriodicalId":158721,"journal":{"name":"Iraqi Journal for Computer Science and Mathematics","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121459082","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

EAMSA 512: New 512 Bits Encryption Al-gorithm Based on Modified SALSA20 EAMSA 512:基于改进SALSA20的新的512位加密算法

Iraqi Journal for Computer Science and Mathematics Pub Date : 2023-04-16 DOI: 10.52866/ijcsm.2023.02.02.011

Jolan Rokan Naif, I. S. Ahmed, Nashwan Alani, Haider K. Hoomod

引用次数: 0

Some Methods to Estimate the Parameters of Generalized Exponential Rayleigh Model by Simulation 用仿真方法估计广义指数Rayleigh模型的参数

Iraqi Journal for Computer Science and Mathematics Pub Date : 2023-04-16 DOI: 10.52866/ijcsm.2023.02.02.010

R. N. Shalan, I. Alkanani

引用次数: 0

Estimating Long-run Elasticity between Crude Oil Consumption, Real Oil Price, and Real GDP in Global Markets 估计全球市场中原油消费、实际油价和实际GDP之间的长期弹性

Iraqi Journal for Computer Science and Mathematics Pub Date : 2023-03-29 DOI: 10.52866/ijcsm.2023.02.02.009

Aysar Y. Fahad, A. H. Battal, Asmaa Yaseen

引用次数: 0

Auto–Transition in RADG based on chaotic System 基于混沌系统的RADG自动转换

Iraqi Journal for Computer Science and Mathematics Pub Date : 2023-03-22 DOI: 10.52866/ijcsm.2023.02.02.008

Laith M. Kadhum, Ahmad Firdaus, Mohamad Fadli Bin Zolkipli, S. Hisham, L. Bayuaji, Mohd Faizal Ab Razak

{"title":"Auto–Transition in RADG based on chaotic System","authors":"Laith M. Kadhum, Ahmad Firdaus, Mohamad Fadli Bin Zolkipli, S. Hisham, L. Bayuaji, Mohd Faizal Ab Razak","doi":"10.52866/ijcsm.2023.02.02.008","DOIUrl":"https://doi.org/10.52866/ijcsm.2023.02.02.008","url":null,"abstract":"The RADG (Reaction Automata Direct Graph) cryptosystem is the automata direct graph and reaction states combination. The classical RADG does not require key exchange (keyless), or agreement between users just the design of RADG, which is static. The RADG algorithm with keys has two agreements between users, one is on the keys, and other is a design of RADG. The RADG design depends on states and transitions between them, since transitions between states are static transitions, or dynamic transitions have agreement between users to determine the type of state (Jump state, Reaction state) of RADG algorithm with keys, and the transition between states must cover each states scenario of RADG design .This article presents algorithm called (Auto- Transition Function (ATF)), which merge properties of RADG algorithm with chaotic system to obtain on transitions between states are automatic. The parameters of ATF are chaotic initial value, parameter of chaotic function, and characteristics of RADG, then ATF is an auto creation of transitions among all states in RADG, and it satisfies each scenario of RADG design.","PeriodicalId":158721,"journal":{"name":"Iraqi Journal for Computer Science and Mathematics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128920059","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

A New Approach to Improve Transmitting and Receiving Timing in Orthogonal Frequency Division Multiplexing (OFDM) Systems 正交频分复用(OFDM)系统中提高收发定时的新方法

Iraqi Journal for Computer Science and Mathematics Pub Date : 2023-03-04 DOI: 10.52866/ijcsm.2023.02.02.007

Ghassan A. Abed

{"title":"A New Approach to Improve Transmitting and Receiving Timing in Orthogonal Frequency Division Multiplexing (OFDM) Systems","authors":"Ghassan A. Abed","doi":"10.52866/ijcsm.2023.02.02.007","DOIUrl":"https://doi.org/10.52866/ijcsm.2023.02.02.007","url":null,"abstract":"Nowadays, most wireless communications employ OFDM technology to reduce signal interference. Its sensitivity to timing faults, however, can cause a severe performance reduction. This study suggests a new approach to enhance communication systems' transmitting and receiving time. Although OFDM is a widely used modulation strategy in communication systems, it is vulnerable to timing faults, which can seriously affect performance. A frequency interference processing method is created that uses OFDM technology and goes through numerous steps, such as correcting CFO, adding a periodic prefix to prevent frequency distortion, calculating the time delay between transmission and reception, and spotting timing mistakes. It is clear that the lack of synchronization between the transmitter and channel interference has caused the Signal-to-Noise Ratio (SNR) to decline correspondingly. The initial approach had a piece of code that computed the transmission and reception times while recording their differences. As a result, it handles signal interference and frequency and temporal synchronization, two key aspects of OFDM. Timing precision varies from 0 to 1, and the time gap between transmission and reception is only a fraction of a second. When the SNR was available, timing errors and the lag between transmission and reception timing were seen, which suggests that there is a small probability of having too many locks or losing codes while utilizing OFDM. Simulation exercises show that the suggested method considerably enhances the system's Bit Error Rate (BER) performance in a variety of time offset conditions. The outcomes imply that the suggested strategy could be a workable remedy for OFDM systems with timing issues.","PeriodicalId":158721,"journal":{"name":"Iraqi Journal for Computer Science and Mathematics","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116564275","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: 16

Secure Heart Disease Classification System Based on Three Pass Protocol and Machine Learning 基于三遍协议和机器学习的安全心脏病分类系统

Iraqi Journal for Computer Science and Mathematics Pub Date : 2023-02-26 DOI: 10.52866/ijcsm.2023.02.02.003

Randa Shaker, H. Obayes, Farah Al-Shareefi

{"title":"Secure Heart Disease Classification System Based on Three Pass Protocol and Machine Learning","authors":"Randa Shaker, H. Obayes, Farah Al-Shareefi","doi":"10.52866/ijcsm.2023.02.02.003","DOIUrl":"https://doi.org/10.52866/ijcsm.2023.02.02.003","url":null,"abstract":"Heart disease is one of the worst life-threatening conditions. Correct and early diagnosis of this disease is crucial for saving patients’ life and avoiding other complications. On the other hand, keeping the patient’s data, diagnosis process, and treatment plan secured is equally important to the defactomedical procedure. This research proposes a system that is consisting of two phases: security provision and patients’ condition diagnosis. Typically, the first phase exercises a security protocol, called three-pass protocol, to ensure that the people who can access the patient's information are authorized. In order to obtain a high accuracy level in the diagnosis process, artificial intelligence with machine learning methods are employed in the later phase. The proposed system relies on a data set which includes a number of vital indicators, by which the patient's status can be classified as having heart disease or not. The KNN algorithm and the random forest tree algorithm are applied to carry out the classification task. The accuracy scale results reveals that the randomforest tree algorithm (99%) gave higher accuracy than KNN (97%).","PeriodicalId":158721,"journal":{"name":"Iraqi Journal for Computer Science and Mathematics","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114733513","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: 2

Numerical Solution of Fractional Integro-Differential Equations Via Fourth-Degree Hat Functions 分数阶积分微分方程的四次帽函数数值解

Iraqi Journal for Computer Science and Mathematics Pub Date : 2023-02-26 DOI: 10.52866/ijcsm.2023.02.02.001

J. K. Mohammed, Ayad R. Khudair

引用次数: 8

Heart disease classification using optimized Machine learning algorithms 使用优化的机器学习算法进行心脏病分类

Iraqi Journal for Computer Science and Mathematics Pub Date : 2023-02-26 DOI: 10.52866/ijcsm.2023.02.02.004

Mohammad Abood Kadhim, A. Radhi

{"title":"Heart disease classification using optimized Machine learning algorithms","authors":"Mohammad Abood Kadhim, A. Radhi","doi":"10.52866/ijcsm.2023.02.02.004","DOIUrl":"https://doi.org/10.52866/ijcsm.2023.02.02.004","url":null,"abstract":"Early detection of heart disease is exceptionally critical to saving the lives of human beings. Heart attack is one of the primary causes of high death rates throughout the world, due to the lack of human and logistical resources in addition to the high costs of diagnosing heart diseases which plays a key role in the healthcare sector, this model is suggested. In the field of cardiology, patient data plays an essential role in the healthcare system. This paper presents a proposed model that aims to identify the optimal machine learning algorithm that can predict heart attacks with high accuracy in the early stages. The concepts of machine learning are used for training and testing the model based on the patient's data for effective decision-making. The proposed model consists of three stages, the first stage is patient data collection and processing, and the second stage is data training and testing using machine learning algorithms Random Forest, Support Vector Machines, K-Nearest Neighbor, and Decision Tree) that show The best classification (94.958 percent) with the Random Forest algorithm and the third stage is optimized the classification results using one of the hyperparameters optimization techniques random search that shows The best accuracy was (95.4 percent) obtained also with RF","PeriodicalId":158721,"journal":{"name":"Iraqi Journal for Computer Science and Mathematics","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132476485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5