Egyptian Informatics Journal最新文献

HD-MVCNN: High-density ECG signal based diabetic prediction and classification using multi-view convolutional neural network HD-MVCNN：利用多视角卷积神经网络进行基于高密度心电信号的糖尿病预测和分类

IF 5 3区计算机科学

Egyptian Informatics Journal Pub Date : 2024-11-06 DOI: 10.1016/j.eij.2024.100573

D. Santhakumar , K. Dhana Shree , M. Buvanesvari , A. Saran Kumar , Ayodeji Olalekan Salau

{"title":"HD-MVCNN: High-density ECG signal based diabetic prediction and classification using multi-view convolutional neural network","authors":"D. Santhakumar , K. Dhana Shree , M. Buvanesvari , A. Saran Kumar , Ayodeji Olalekan Salau","doi":"10.1016/j.eij.2024.100573","DOIUrl":"10.1016/j.eij.2024.100573","url":null,"abstract":"<div><div>Diabetes mellitus, also known as diabetes, is a medical condition marked by high blood sugar levels and impacts a large population worldwide. Treating diabetes is not feasible. It can be managed. Hence, it is crucial to promptly identify a diagnosis of diabetes. This study explores the effects of diabetes on the heart, focusing on heart rate variability (HRV) signals, which can offer valuable information about the existence and seriousness of diabetes through the evaluation of diabetes-related heart problems. Extracting crucial data from the irregular and nonlinear HRV signal can be quite challenging. Studying cardiac diagnostics involves a thorough analysis of electrocardiogram (ECG) signals. Traditional electrocardiogram recordings utilize twelve channels, each capturing a complex combination of activities originating from different regions of the heart. Examining ECG signals recorded on the body’s surface may not be an effective method for studying and diagnosing diabetic issues. The study introduces a research proposal utilizing a high-density resolution electrocardiogram (ECG) system with a minimum of 64 channels and multi-view convolutional neural network classification (HD-MVCNN) to address the mentioned challenges. This framework may help identify the hypoglycaemia effects on brain regions, leading to decreased complexity and increased theta and delta power during scalp electrocardiogram procedures. The convolutional architectural model primarily contributes to enhancement and optimization through its Stochastic Gradient Descent (SGD) along with convolutional layers and according to results, the HD-MVCNN demonstrated better stability and accuracy in comparison to traditional classification models. Thus, HD-MVCNN shows promise as a powerful method for classifying features in diabetes clinical data.</div></div>","PeriodicalId":56010,"journal":{"name":"Egyptian Informatics Journal","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142593126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A hybrid encryption algorithm based approach for secure privacy protection of big data in hospitals 基于混合加密算法的医院大数据隐私安全保护方法

IF 5 3区计算机科学

Egyptian Informatics Journal Pub Date : 2024-11-05 DOI: 10.1016/j.eij.2024.100569

Wei Li , Qian Huang

{"title":"A hybrid encryption algorithm based approach for secure privacy protection of big data in hospitals","authors":"Wei Li , Qian Huang","doi":"10.1016/j.eij.2024.100569","DOIUrl":"10.1016/j.eij.2024.100569","url":null,"abstract":"<div><div>Aiming at the hidden danger of information security caused by the lack of medical big data information security firewall, this paper proposes a security privacy protection method for hospital big data based on hybrid encryption algorithm. First, collect hospital big data including hospital medical business system, mobile wearable devices and big health data; Secondly, use byte changes to compress hospital big data to achieve safe transmission of hospital big data; Then, the hospital sender uses the AES session key to encrypt the hospital big data and the ECC public key to encrypt the AES session key, uses SHA-1 to calculate the hash value of the medical big data, and uses the ECC public key to sign the hash value; The hospital receiver uses the ECC private key to verify the signature, and decrypts the AES session key using the ECC private key. After the AES session key decrypts, the hospital big data, the hospital big data security privacy protection is completed. The experimental results show that the method is superior to conventional ECC algorithm or RSA and AES hybrid encryption algorithm in terms of encryption and decryption time and security strength. The average correlation coefficient of encrypted hospital big data is only 0.0576, and the RL curve value is low and gentle. The encrypted data has good scrambling effect and low privacy leakage probability, which ensures the confidentiality and integrity of medical data in the transmission process.</div></div>","PeriodicalId":56010,"journal":{"name":"Egyptian Informatics Journal","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142586849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A new probabilistic linguistic decision-making process based on PL-BWM and improved three-way TODIM methods 基于 PL-BWM 和改进的三向 TODIM 方法的新概率语言决策过程

IF 5 3区计算机科学

Egyptian Informatics Journal Pub Date : 2024-11-04 DOI: 10.1016/j.eij.2024.100567

Jie Chen , Chuancun Yin

{"title":"A new probabilistic linguistic decision-making process based on PL-BWM and improved three-way TODIM methods","authors":"Jie Chen , Chuancun Yin","doi":"10.1016/j.eij.2024.100567","DOIUrl":"10.1016/j.eij.2024.100567","url":null,"abstract":"<div><div>Probabilistic linguistic term sets (PLTSs) provide a flexible tool to express linguistic preferences, which allow decision-makers to label linguistic information with different probabilities. In this paper, a method based on a PLTS is proposed to address multi-criteria decision-making problems (MCDM). We develop the theory of PLTSs and put forward a novel best–worst method (BWM), termed PL-BWM, based on PLTS. Our method fully reflects the preference information of decision-makers and accurately provides the importance level of the criteria. The combined weight of the criteria is obtained by merging PL-BWM-based subjective weights and similarity minimization-based objective weights. Upon introducing a three-way decision system to improve the TODIM method, a novel three-way TODIM method is proposed and showcased on an optimal new energy vehicle selection problem. The effectiveness and accuracy of the proposed method are verified by sensitivity analysis and comparative analysis. Our approach paves the way for new developments in solving MCDM problems and for novel applications in otherwise difficult ranking problems.</div></div>","PeriodicalId":56010,"journal":{"name":"Egyptian Informatics Journal","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142578487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Interval valued inventory model with different payment strategies for green products under interval valued Grey Wolf optimizer Algorithm fitness function 区间值灰狼优化算法拟合函数下不同付款策略的绿色产品区间值库存模型

IF 5 3区计算机科学

Egyptian Informatics Journal Pub Date : 2024-11-02 DOI: 10.1016/j.eij.2024.100561

Subhash Chandra Das , Md. Al-Amin Khan , Ali Akbar Shaikh , Adel Fahad Alrasheedi

{"title":"Interval valued inventory model with different payment strategies for green products under interval valued Grey Wolf optimizer Algorithm fitness function","authors":"Subhash Chandra Das , Md. Al-Amin Khan , Ali Akbar Shaikh , Adel Fahad Alrasheedi","doi":"10.1016/j.eij.2024.100561","DOIUrl":"10.1016/j.eij.2024.100561","url":null,"abstract":"<div><div>Numerous studies have explored pricing and lot-sizing strategies for various payment methods, but most have focused primarily on the buyer’s perspective. This study, however, approaches these strategies from a different perspective, incorporating key and relevant factors often overlooked. The volume of sales increases when a seller accepts a buyer’s credit. However, it reduces sales volume when a seller requests a buyer make a payment in advance. To boost sales and profitability, a vendor occasionally provides a price reduction in exchange for a down payment. Demanding a down payment from a customer earns interest and carries without any risk of default. When a vendor offers customers the option to pay with credit, a higher delay payment period facility plan may boost sales volume, but it also increases the risk of default. To maximize profit per unit of time, the vendor aims to simultaneously determine the optimal selling price, replenishment schedule, and payment method. This is achieved by comparing and calculating the vendor’s profit per time unit for credit, cash, and advance payment options. This is done by comparing and calculating the seller’s profit for each piece of time for credit, cash, and advance payments. The following managerial impacts are highlighted by means of numerical analyses: (1) A particular payment type, among the three available options, yields the seller’s highest profit under certain conditions. (2) It is vitally crucial for a vendor to provide a price reduction if an advance payment is required. (3) Advance payment results in higher profit than delayed payment if sales volume does not significantly fall while switching from credit to advance payments, or vice versa. To solve the optimization problem, a popular metaheuristic algorithm (viz., Grey Wolf Optimizer) is used and finally performed a post optimality analysis for making a fruitful conclusion.</div></div>","PeriodicalId":56010,"journal":{"name":"Egyptian Informatics Journal","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142571498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Intelligent SDN to enhance security in IoT networks 智能 SDN 提高物联网网络的安全性

IF 5 3区计算机科学

Egyptian Informatics Journal Pub Date : 2024-10-30 DOI: 10.1016/j.eij.2024.100564

Safi Ibrahim , Aya M. Youssef , Mahmoud Shoman , Sanaa Taha

{"title":"Intelligent SDN to enhance security in IoT networks","authors":"Safi Ibrahim , Aya M. Youssef , Mahmoud Shoman , Sanaa Taha","doi":"10.1016/j.eij.2024.100564","DOIUrl":"10.1016/j.eij.2024.100564","url":null,"abstract":"<div><div>Software-defined networking (SDN) is a revolutionary technology that has revolutionised network management by providing flexibility and adaptability. As the popularity of SDN increases, it is crucial to address security vulnerabilities in these dynamic networks. This paper proposes a framework for enhancing security in SDN by utilising three separate Deep Learning models, namely Deep Neural Network (DNN), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM). This framework is utilised for the InSDN dataset, a huge dataset specifically created for SDN security research. The dataset consists of a total of 343,939 instances, encompassing both normal and attack traffic. The regular data yields a sum of 68,424, whereas the attack traffic comprises 275,515 occurrences. This study employs multiclassification algorithms to precisely detect and categorise diverse security threats in SDN. The InSDN dataset faces issues related to class imbalance, which are addressed by using the Synthetic Minority Over-sampling Technique (SMOTE). The SMOTE technique is utilised to create artificial instances of the underrepresented class, hence achieving a more equitable distribution of security hazards within the dataset. This strategy improves the efficacy of multiclassification techniques, ultimately resulting in greater accuracy in the identification and classification of different security threats in SDN environments. The initial DNN model exhibited satisfactory performance, with an accuracy of 87%. The second CNN model demonstrated strong and consistent performance, with an accuracy rate of 99%. In addition, an LSTM model attained a 90% accuracy rate.</div></div>","PeriodicalId":56010,"journal":{"name":"Egyptian Informatics Journal","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142553747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fuzzy operator infrared image deblurring algorithm for image blurring in dragon boat races 用于龙舟赛图像模糊处理的模糊算子红外图像去模糊算法

IF 5 3区计算机科学

Egyptian Informatics Journal Pub Date : 2024-10-28 DOI: 10.1016/j.eij.2024.100568

Xiao Tang , Yuan Shen , Genwei Zhu

{"title":"Fuzzy operator infrared image deblurring algorithm for image blurring in dragon boat races","authors":"Xiao Tang , Yuan Shen , Genwei Zhu","doi":"10.1016/j.eij.2024.100568","DOIUrl":"10.1016/j.eij.2024.100568","url":null,"abstract":"<div><div>To address the issues of poor robustness and weak generalization in existing infrared image deblurring methods, a fuzzy operator-based algorithm is proposed to solve the fuzzy imaging in dragon boat races. The experiment showed that the models trained utilizing original and synthesized datasets had very small differences in peak signal-to-noise ratio and structural similarity performance indicators, and the evaluation results were close. For a blurry image with 19 pixels, the number of blurry pixels extracted by the research algorithm was 22, with a difference of 3 pixels. For a blurry image with 35 pixels, the algorithm extracted 34 blurry pixels, with a difference of 1 pixel. This indicated that the deblurring result of the algorithm was accurate. In terms of peak signal-to-noise ratio and structural similarity, the peak signal-to-noise ratio and structure similarity were 30.98 dB and 0.921, respectively, both of which were the optimal values in all algorithms. In terms of the change of pixel gray value, the simulated blur length of the research method was 19 pixels, and the actual blur length was 20 pixels far less than 30 pixels. The results verified the effectiveness and significance of the algorithm for deblurring of dragon boat competition infrared images.</div></div>","PeriodicalId":56010,"journal":{"name":"Egyptian Informatics Journal","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142530564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Lightweight malware detection technique based on hybrid fuzzy simulated annealing clustering in Android apps 基于混合模糊模拟退火聚类的安卓应用程序轻量级恶意软件检测技术

IF 5 3区计算机科学

Egyptian Informatics Journal Pub Date : 2024-10-19 DOI: 10.1016/j.eij.2024.100560

Collins Chimeleze , Norziana Jamil , Nazik Alturki , Zuhaira Muhammad Zain

引用次数: 0

Deep Learning-Assisted Compound Bioactivity Estimation Framework 深度学习辅助化合物生物活性估算框架

IF 5 3区计算机科学

Egyptian Informatics Journal Pub Date : 2024-10-15 DOI: 10.1016/j.eij.2024.100558

Yasmine Eid Mahmoud Yousef , Ayman El-Kilany , Farid Ali , Yassin M. Nissan , Ehab E. Hassanein

引用次数: 0

Delay probability in adaptive systems based on activation function of classical neural networks 基于经典神经网络激活函数的自适应系统中的延迟概率

IF 5 3区计算机科学

Egyptian Informatics Journal Pub Date : 2024-10-14 DOI: 10.1016/j.eij.2024.100555

Maja Lutovac Banduka , Vladimir Mladenović , Danijela Milosević , Vladimir Orlić , Asutosh Kar

引用次数: 0

Heart disease prediction using autoencoder and DenseNet architecture 利用自动编码器和 DenseNet 架构预测心脏病

IF 5 3区计算机科学

Egyptian Informatics Journal Pub Date : 2024-10-14 DOI: 10.1016/j.eij.2024.100559

Norah Saleh Alghamdi , Mohammed Zakariah , Achyut Shankar , Wattana Viriyasitavat

{"title":"Heart disease prediction using autoencoder and DenseNet architecture","authors":"Norah Saleh Alghamdi , Mohammed Zakariah , Achyut Shankar , Wattana Viriyasitavat","doi":"10.1016/j.eij.2024.100559","DOIUrl":"10.1016/j.eij.2024.100559","url":null,"abstract":"<div><div>Heart disease continues to be a prominent cause of death globally, emphasizing the critical requirement for precise prediction techniques and prompt therapies. This research presents a new method that utilizes the collective capabilities of autoencoder and DenseNet architectures to predict heart illness. Our study is based on the Heart Disease UCI Cleveland dataset, which includes 13 variables that cover clinical and demographic parameters such as age, sex, cholesterol levels, and exercise-induced angina. The dataset presents issues due to its varied attribute types, including category and numerical variables. Furthermore, our approach tackles these difficulties by utilizing a dense autoencoder model, which produced exceptional outcomes. The Model attained a mean accuracy of 99.67% on the Heart Disease UCI Cleveland dataset. Further testing showed it was resilient, with a test accuracy of 99.99%. In addition, the Model demonstrated outstanding macro precision, macro recall, and macro F1 score, with percentages of 99.98%, 99.97%, and 99.96%, respectively. In addition, our results indicate that combining autoencoder and DenseNet designs shows potential for predicting cardiac disease, with substantial enhancements in accuracy and performance metrics compared to current approaches. This methodology can improve clinical decision-making and patient outcomes in cardiovascular care by accurately finding and defining complex patterns within the data. Notwithstanding these encouraging outcomes, our investigation has constraints. The specific attributes of the dataset utilized may limit the applicability of our findings. Subsequent studies could examine the suitability of our method for various datasets and analyze supplementary variables that may improve forecast precision. Furthermore, it is necessary to conduct prospective validation studies to evaluate our strategy’s practical effectiveness in clinical environments.</div></div>","PeriodicalId":56010,"journal":{"name":"Egyptian Informatics Journal","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142432234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0