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A Robust Approach for Multi Classification-Based Intrusion Detection through Stacking Deep Learning Models

Computers, Materials & Continua 2024年第6期79卷 4845-4861页

作者： samia Allaoua Chelloug Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia

Intrusion detection is a predominant task that monitors and protects the network ***,many datasets have been published and investigated by researchers to analyze and understand the problem of intrusion prediction and *** particular,the Network Security Laboratory-Knowledge Discovery in Databases(NSL-KDD)is an extensively used benchmark dataset for evaluating intrusion detection systems(IDSs)as it incorporates various network traffic *** is worth mentioning that a large number of studies have tackled the problem of intrusion detection using machine learning models,but the performance of these models often decreases when evaluated on new *** has led to the utilization of deep learning techniques,which have showcased significant potential for processing large datasets and therefore improving detection *** that reason,this paper focuses on the role of stacking deep learning models,including convolution neural network(CNN)and deep neural network(DNN)for improving the intrusion detection rate of the NSL-KDD *** base model is trained on the NSL-KDD dataset to extract significant *** the base models have been trained,the stacking process proceeds to the second stage,where a simple meta-model has been trained on the predictions generated from the proposed base *** combination of the predictions allows the meta-model to distinguish different classes of attacks and increase the detection *** experimental evaluations using the NSL-KDD dataset have shown the efficacy of stacking deep learning models for intrusion *** performance of the ensemble of base models,combined with the meta-model,exceeds the performance of individual *** stacking model has attained an accuracy of 99%and an average F1-score of 93%for the multi-classification ***,the training time of the proposed ensemble model is lower than the training time of benchmark techniques,demonstrating its efficien

关键词： Intrusion detection multi classification deep learning stacking NSL-KDD

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Determination of the Potency of Extracted, Purified and Formulated Insulin from the Pancreatic Organs of the Sudanese Beef Cattle

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Pharmacology & Pharmacy 2013年第6期4卷 467-472页

作者： abdella Emam abdella Baragob Waleed Hassan AlMalki Imran Shahid Ragia Mahmood Hegazy Khojali Salwa Muhammed samia abdella Department of Pharmacology and Toxicology College of Pharmacy Umm Al Qura University Makkah KSA Department of Pharmacology and Toxicology College of Pharmacy Umm Al Qura University Makkah KSA Veterinary Research Institute Khartoum Sudan.

The treatment of type 1 diabetes is mainly dependent on insulin therapy and current formulated insulin formulations are used for its control all over the world. The presented study was designed to evaluate the potency of extracted, purified and formulated insulin from the pancreatic organs of the Sudanese beef cattle. Twenty healthy rabbits were used to conduct the study following subcutaneous administration of the sample insulin, to determine the hypoglycemic effect and to analyze the potency of the testing insulin by the hypoglycemic seizure method, blood sugar method and glucose enzymatic colorimetric test (GOD-PAP) respectively. The potency of the injected insulin samples was estimated by comparing the variation in blood glucose levels produced in the treated animals with that produced by a standard insulin preparation under the suitable conditions of the blood sugar method. The results revealed that the potency of the testing beef insulin samples was slightly higher (i.e., 2.2 USP units/ml, 9%) compared to the standard and assumed potency of the prepared insulin preparations (i.e., 1-2 USP units/ml) which indicated that the solvents and diluents used to prepare the assay dilution might be of higher potency and must be diluted to such an extent that the testing insulin potency must be compatible with the standard dilutions. Furthermore, to determine the choice of an assay to analyze the potency of insulin preparations, not only the accuracy of the result but also the purpose for which the test is to be used and the time limit must be taken into consideration.

关键词： Blood Sugar Method Glucose Oxidase Method Hypoglycemic Effect Insulin Potency

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Investigate Evaluation of Oxidative Stress and Lipid Profile in STZ-Induced Rats Treated with Antioxidant Vitamin

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Pharmacology & Pharmacy 2014年第3期5卷 272-279页

作者： abdella Emam abdella Baragob Waleed Hassan AlMalki Hassan Elsiddig Hassan Farag Alla Asim Ibrahim Salwa Khojali Muhammed samia abdella Department of Pharmaceuticalchemistry Faculty of Pharmacy Umm Al Qura University Makkah Saudi Arabia Department of Pharmacology and Toxicology Faculty of Pharmacy Umm Al Qura University Makkah Saudi Arabia Department of Public Health Health Sciences College at Al-lieth Umm Al Qura University Makkah Saudi Arabia Department of Histopathology and Cytology College of Medical La-boratory Science Sudan University of Science and Technology Khartoum Sudan Veterinary Research Institute Department of Biochemistry Khartoum Sudan Veterinary Research Institute Department of Pharmacology Khartoum Sudan

The objective of this study was designed to investigate, evaluate the effect of vitamin E on streptozotocin (STZ)-induced diabetic rats by showing significant changes in blood glucose, water, food intake, lipid profile, serum urea and ceratinine level, and antioxidant enzyme parameters activity. Streptozotocin (STZ)-induced toxicity was studied in male Waster rats;each divided into four groups: G1, GII, GIII, and GIV. Control rats GI, rats treated with vitamin E (GII), STZ-induced diabetic rats (GIII), and STZ-induced diabetic rats treated with vitamin E (G1V). Moreover, vitamin E reduced (p < 0.05) blood glucose and urea, thus, our study improved the lipid profile (reduced the serum levels of amount of total cholesterol, LDL, VLDL, cholesterol and triacyglycerols, and increased HDL cholesterol) and increased total amount protein in STZ-induced diabetic rats (GIV). Vitamin prevented modification in the activity of superoxide dismutase (SOD) and glutathione peroxidase (GSX-Px) and in the concentration of the lipid hydroperoxide. Finally the study suggested that vitamin E improved hyperglycaemia and dyslipidaemia while inhibiting the progression of oxidative stress in STZ-induced diabetic rats.

关键词： Investigate Lipid Profile STZ Oxidative Stress Vitamin E

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Determination of the Stability Studies of the Sudanese Camel Insulin

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Pharmacology & Pharmacy 2013年第7期4卷 549-555页

作者： abdella Imam abdella Baragob Waleed Hassan AlMalki Imran Shahid Hanouf Saeed Bafhaid Fatimah Abdullah Bakhdhar Salwa Muhamed Khojali samia abdella Department of Pharmacology and Toxicology College of Pharmacy Umm Al Qura University Makkah The kingdom of Saudi Arabia Faculty of Pharmacy Khartoum University Khartoum Sudan

The main objective of the presented study was to characterize the stability of the Sudanese camel insulin after 6 months of its extraction, purification and formulation from the fresh pancreatic glands of the camel, slaughtered for local and export consumption. The stability and purity of the formulated insulin samples were compared to standard insulin sam-ples that of the leading manufacturing companies using some analytical techniques such as HPLC, gel electrophoresis and atomic absorption. In another part of the study, the direct transfer method was used to accomplish sterility test by complete immersion of the insulin samples into thioglycollate and soybean medium. The data were presented as mean ± S.E.M (standard error of means) for the comparison of zinc (mg/units) and nitrogen (in percentage) concentrations in standard and testing camel insulin samples, respectively. Similarly, the linear equation was derived and the coefficient factors for standard and testing insulin samples were compared to determine the peak area and the concentrations of the camel insulin samples (mean ± S.E.M) after HPLC elution. The P value,

关键词： Analytical Techniques Camel Insulin Stability Studies Shelf Life

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Road Traffic Monitoring from Aerial Images Using Template Matching and Invariant Features

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Computers, Materials & Continua 2024年第3期78卷 3683-3701页

作者： Asifa Mehmood Qureshi Naif Al Mudawi Mohammed Alonazi samia Allaoua Chelloug Jeongmin Park Department of Creative Technologies Air UniversityIslamabad46000Pakistan Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Department of Information Systems College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Engineering Tech University of KoreaGyeonggi-do15073South Korea

Road traffic monitoring is an imperative topic widely discussed among *** used to monitor traffic frequently rely on cameras mounted on bridges or ***,aerial images provide the flexibility to use mobile platforms to detect the location and motion of the vehicle over a larger *** this end,different models have shown the ability to recognize and track ***,these methods are not mature enough to produce accurate results in complex road ***,this paper presents an algorithm that combines state-of-the-art techniques for identifying and tracking vehicles in conjunction with image *** extracted frames were converted to grayscale,followed by the application of a georeferencing algorithm to embed coordinate information into the *** masking technique eliminated irrelevant data and reduced the computational cost of the overall monitoring ***,Sobel edge detection combined with Canny edge detection and Hough line transform has been applied for noise *** preprocessing,the blob detection algorithm helped detect the *** of varying sizes have been detected by implementing a dynamic thresholding *** was done on the first image of every ***,to track vehicles,the model of each vehicle was made to find its matches in the succeeding images using the template matching *** further improve the tracking accuracy by incorporating motion information,Scale Invariant Feature Transform(SIFT)features have been used to find the best possible match among multiple *** accuracy rate of 87%for detection and 80%accuracy for tracking in the A1 Motorway Netherland dataset has been *** the Vehicle Aerial Imaging from Drone(VAID)dataset,an accuracy rate of 86%for detection and 78%accuracy for tracking has been achieved.

关键词： Unmanned Aerial Vehicles(UAV) aerial images dataset object detection object tracking data elimination template matching blob detection SIFT VAID

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Self-supported copper-based gas diffusion electrodes improve the local CO_(2)concentration for efficient electrochemical CO_(2)reduction

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Frontiers of Chemical Science and Engineering 2024年第3期18卷 51-62页

作者： Azeem Mustafa Bachirou Guene Lougou Yong Shuai Zhijiang Wang Haseeb-ur-Rehman samia Razzaq Wei Wang Ruming Pan Jiupeng Zhao Key Laboratory of Aerospace Thermophysics of MIIT Harbin Institute of TechnologyHarbin150001China School of Energy Science and Engineering Harbin Institute of TechnologyHarbin150001China MIIT Key Laboratory of Critical Materials Technology for New Energy Conversion and Storage School of Chemistry and Chemical EngineeringHarbin Institute of TechnologyHarbin150001China Mechanical Engineering Department University of Engineering and TechnologyTaxila47050Pakistan School of Aerospace Mechanical and Mechatronics EngineeringUniversity of SydneySydney2006Australia

Electrochemical CO_(2)reduction is a sustainable approach in green chemistry that enables the production of valuable chemicals and fuels while mitigating the environmental impact associated with CO_(2)*** its several advantages,this technology suffers from an intrinsically low CO_(2)solubility in aqueous solutions,resulting in a lower local CO_(2)concentration near the electrode,which yields lower current densities and restricts product *** diffusion electrodes(GDEs),particularly those with tubular architectures,can solve these issues by increasing the local CO_(2)concentration and triple-phase interface,providing abundant electroactive sites to achieve superior reaction *** this study,robust and self-supported Cu flow-through gas diffusion electrodes(FTGDEs)were synthesized for efficient formate production via electrochemical CO_(2)*** were further compared with traditional Cu electrodes,and it was found that higher local CO_(2)concentration due to improved mass transfer,the abundant surface area available for the generation of the triple-phase interface,and the porous structure of Cu FTGDEs enabled high formate Faradaic efficiency(76%)and current density(265 mA¸cm^(−2))at–0.9 V *** hydrogen electrode(RHE)in 0.5 mol·L^(−1)*** combined phase inversion and calcination process of the Cu FTGDEs helped maintain a stable operation for several *** catalytic performance of the Cu FTGDEs was further investigated in a non-gas diffusion configuration to demonstrate the impact of local gas concentration on the activity and performance of electrochemical CO_(2)*** study demonstrates the potential of flow-through gas-diffusion electrodes to enhance reaction kinetics for the highly efficient and selective reduction of CO_(2),offering promising applications in sustainable electrochemical processes.

关键词： CO_(2)electroreduction flow-through delivery hollow fiber structure local concentration formate

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Robust Machine Learning Technique to Classify COVID-19 Using Fusion of Texture and Vesselness of X-Ray Images

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Computer Modeling in Engineering & Sciences 2024年第2期138卷 1981-2004页

作者： Shaik Mahaboob Basha Victor Hugo Cde Albuquerque samia Allaoua Chelloug Mohamed Abd Elaziz Shaik Hashmitha Mohisin Suhail Parvaze Pathan Department of Electronics and Communication Engineering N.B.K.R.Institute of Science&TechnologyVidyanagarAndhra Pradesh524413India Department of Teleinformatics Engineering Federal University of CearáFortaleza60455-970Brazil Information Technology Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Mathematics Faculty of ScienceZagazig UniversityZagazig44519Egypt Faculty of Computer Science and Engineering Galala UniversitySuez435611Egypt Artificial Intelligence Research Center(AIRC) College of Engineering and Information TechnologyAjman UniversityAjmanUnited Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityByblos13-5053Lebanon Department of Avionics Indian Institute of Space Science and TechnologyThiruvananthapuramKerala695547India Department of Veterinary Clinical Sciences University of MinnesotaSt.PaulMinnesota55108USA

Manual investigation of chest radiography(CXR)images by physicians is crucial for effective decision-making in COVID-19 ***,the high demand during the pandemic necessitates auxiliary help through image analysis and machine learning *** study presents a multi-threshold-based segmentation technique to probe high pixel intensity regions in CXR images of various pathologies,including normal *** information is extracted using gray co-occurrence matrix(GLCM)-based features,while vessel-like features are obtained using Frangi,Sato,and Meijering *** learning models employing Decision Tree(DT)and RandomForest(RF)approaches are designed to categorize CXR images into common lung infections,lung opacity(LO),COVID-19,and viral pneumonia(VP).The results demonstrate that the fusion of texture and vesselbased features provides an effective ML model for aiding *** ML model validation using performance measures,including an accuracy of approximately 91.8%with an RF-based classifier,supports the usefulness of the feature set and classifier model in categorizing the four different ***,the study investigates the importance of the devised features in identifying the underlying pathology and incorporates histogrambased *** analysis reveals varying natural pixel distributions in CXR images belonging to the normal,COVID-19,LO,and VP groups,motivating the incorporation of additional features such as mean,standard deviation,skewness,and percentile based on the filtered ***,the study achieves a considerable improvement in categorizing COVID-19 from LO,with a true positive rate of 97%,further substantiating the effectiveness of the methodology implemented.

关键词： Chest radiography(CXR)image COVID-19 classifier machine learning random forest texture analysis

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Rao Algorithms-Based Structure Optimization for Heterogeneous Wireless Sensor Networks

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Computers, Materials & Continua 2024年第1期78卷 873-897页

作者： Shereen K.Refaay samia A.Ali Moumen T.El-Melegy Louai A.Maghrabi Hamdy H.El-Sayed Faculty of Computers and Artificial Intelligence Sohag UniversitySohag82524Egypt Faculty of Engineering Assiut UniversityAssiut711745Egypt College of Engineering University of Business and TechnologyJeddah23411Saudi Arabia

The structural optimization of wireless sensor networks is a critical issue because it impacts energy consumption and hence the network’s *** studies have been conducted for homogeneous networks,but few have been performed for heterogeneouswireless sensor *** paper utilizes Rao algorithms to optimize the structure of heterogeneous wireless sensor networks according to node locations and their initial *** proposed algorithms lack algorithm-specific parameters and metaphorical *** proposed algorithms examine the search space based on the relations of the population with the best,worst,and randomly assigned *** proposed algorithms can be evaluated using any routing protocol,however,we have chosen the well-known routing protocols in the literature:Low Energy Adaptive Clustering Hierarchy(LEACH),Power-Efficient Gathering in Sensor Information Systems(PEAGSIS),Partitioned-based Energy-efficient LEACH(PE-LEACH),and the Power-Efficient Gathering in Sensor Information Systems Neural Network(PEAGSIS-NN)recent routing *** compare our optimized method with the Jaya,the Particle Swarm Optimization-based Energy Efficient Clustering(PSO-EEC)protocol,and the hybrid Harmony Search Algorithm and PSO(HSA-PSO)*** efficiencies of our proposed algorithms are evaluated by conducting experiments in terms of the network lifetime(first dead node,half dead nodes,and last dead node),energy consumption,packets to cluster head,and packets to the base *** experimental results were compared with those obtained using the Jaya optimization *** proposed algorithms exhibited the best *** proposed approach successfully prolongs the network lifetime by 71% for the PEAGSIS protocol,51% for the LEACH protocol,10% for the PE-LEACH protocol,and 73% for the PEGSIS-NN protocol;Moreover,it enhances other criteria such as energy conservation,fitness convergence,packets to cluster head,and packets to the base sta

关键词： Wireless sensor networks Rao algorithms optimization LEACH PEAGSIS

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Preparation of Fe-As alloys by mechanical alloying and vacuum hot-pressed sintering:microstructure evolution,mechanical properties,and mechanisms

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Rare Metals 2024年第8期43卷 3876-3892页

作者： Fei Chai Fei-Ping Zhao Zhan Hu Shi-Yi Wen Ben-Hammouda samia Ze-Lin Fu Xin-Ting Lai Yan-Jie Liang Xiao-Bo Min Li-Yuan Chai School of Metallurgy and Environment Central South University Chinese National Engineering Research Center for Control & Treatment of Heavy Metal Pollution Institute of Environmental EngineeringCentral South University State Key Laboratory of Powder Metallurgy Central South University Department of Building Civiland Environmental Engineering Concordia University

Arsenic materials have attracted great attention due to their unique ***,research concerning iron-arsenic（Fe-As） alloys is very scarce due to the volatility of As at low temperature and the high melting point of ***,a new Fe-As alloy was obtained by mechanical alloying（MA） followed by vacuum hot-pressed sintering（VHPS）.Moreover,a systematic study was carried out on the microstructural evolution,phase composition,leaching toxicity of As,and physical and mechanical properties of Fe-As alloys with varying weight fractions of As（20%,25%,30%,35%,45%,55%,65%,and 75%）.The results showed that pre-alloyed metallic powders（PAMPs） have a fine grain size and specific supersaturated solid solution after MA,which could effectively improve the mechanical properties of Fe-As alloys by VHPS.A high density(> 7.350 g·cm-3),low toxicity,and excellent mechanical properties could be obtained for FeAs alloys sintered via VHPS by adding an appropriate amount of As,which is more valuable than commercial Fe-As *** Fe-25% As alloy with low toxicity and a relatively high density(7.635 g·cm-3) provides an ultra-high compressive strength（1989.19 MPa）,while the Fe-65% As alloy owns the maximum Vickers hardness（HVo.5 899.41）.After leaching by the toxicity characteristic leaching procedure（TCLP）,these alloys could still maintain good mechanical performance,and the strengthening mechanisms of Fe-As alloys before and after leaching were *** in the grain size,micro structure,and phase distribution induced significant differences in the compressive strength and hardness.

关键词： Mechanical alloying Vacuum hot-pressed sintering High-pressure Arsenic–iron alloys Mechanical properties

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Impact of the COVID-19 Pandemic on Cancer Patients: Experience of the medical oncology department of CHU HASSAN II Fez.

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Journal of Cancer Therapy 2024年第3期15卷 83-91页

作者： Khadija Hinaje Oumaima Talbi Lamiae Amaadour Karima Oualla Zineb Benbrahim samia Arifi Nawfel Mellas Department of Medical Oncology Hassan II University Hospital University Sidi Mohamed Ben Abdellah Fez Morocco

Introduction: In December 2019, COVID 19 spread worldwide, but did not officially start in MOROCCO until March 02, 2020. Since then, this pandemic has significantly impacted the health status of patients in general and cancer patients in particular. The main objective of our study is to evaluate the prognosis of patients treated for cancer and infected with COVID-19. Material and method: A descriptive study with prospective collection was carried out at the medical oncology department of CHU Hassan II in FEZ over a period of two years, from March 2020 to March 2022. Data was carried out on the software SPSS. Results: One hundred cancer patients tested positive for COVID-19 infection and were collected within our department. The average age was 56 years [22-91]. The sex ratio was 1.2. Patients with breast cancer were the most affected by this infection (34%). The clinical symptomatology was dominated by the respiratory syndrome (45%).The diagnosis was made through thoracic CT scan in 62% of cases. 76% of patients were in a metastatic stage. 96% of patients were undergoing oncological treatment. For symptomatique patients, the standard treatment approach involved using antibiotics in 76% of cases. Evolution was marked by recovery in 79% of patients, with a death rate of 12% in this cancer patient population. Conclusion: COVID-19 infection is particularly severe in cancer patients. Mortality among these patients remains high and is associated with overall patient characteristics. However, anticancer treatments have not shown deleterious effects on the course of COVID-19.

关键词： COVID-19 Cancer. SARS-CoV-2

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