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Finger Vein Authentication Based on Wavelet Scattering Networks

Computers, Materials & Continua 2022年第8期72卷 3369-3383页

作者： Amjad Rehman Majid Harouni Maedeh Omidiravesh Suliman Mohamed Fati Saeed ali Bahaj Artificial Intelligence&Data Analytics Lab CCIS Prince Sultan UniversityRiyadh11586Saudi Arabia Department of Computer Engineering Dolatabad BranchIslamic Azad UniversityIsfahanIran Faculty of Computer Engineering Najafabad BranchIslamic Azad UniversityIsfahanIran MIS Department College of Business Administration Prince Sattam bin Abdulaziz UniversityAlkharj11942Saudi Arabia

Biometric-based authentication systems have attracted more attention than traditional authentication techniques such as passwords in the last two *** biometrics such as fingerprint,palm,iris,palm vein and finger vein and other biometrics have been *** of the challenges in biometrics is physical *** of finger vein is of the biometrics least exposed to physical *** methods have been proposed for authentication with the help of this biometric that suffer from weaknesses such as high computational complexity and low identification *** paper presents a novel method of scattering wavelet-based identity *** wavelet extracts image features from Gabor wavelet filters in a structure similar to convolutional neural *** distinguishes this algorithm from other popular feature extraction methods such as deep learning methods,filter-based methods,statistical methods,etc.,is that this algorithm has very high skill and accuracy in differentiating similar images but belongs to different classes,even when the image is subject to serious damage such as noise,angle changes or pixel location,this descriptor still generates feature vectors in away thatminimizes classifier *** improves classification and *** proposed method has been evaluated using two databases Finger Vein USM(FV-USM)and Homologous Multimodal biometrics Traits(SDUMLA-HMT).In addition to having reasonable computational complexity,it has recorded excellent identification rates in noise,rotation,and transmission *** best,it has a 98.2%identification rate for the SDUMLA-HMT database and a 96.1%identification rate for the FV-USM database.

关键词： Biometrics finger veins wavelet scattering vein authentication disaster risk reduction

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Price Prediction of Seasonal Items Using Time Series Analysis

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Computer Systems Science & Engineering 2023年第7期46卷 445-460页

作者： Ahmed Salah Mahmoud Bekhit Esraa Eldesouky Ahmed ali Ahmed Fathalla Faculty of Computers and Informatics Zagazig UniversitySharkeya44523Egypt Information Technology Department the University of Technology and Applied SciencesIbriOman School of Electrical and Data Engineering University of Technology SydneySydney2007Australia College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Computer Science Department Faculty of Computers and InformaticsSuez Canal UniversityIsmailia41522Egypt Higher Future Institute for Specialized Technological Studies Cairo3044Egypt Department of Mathematics Faculty of ScienceSuez Canal UniversityIsmailia41522Egypt

The price prediction task is a well-studied problem due to its impact on the business *** are several research studies that have been conducted to predict the future price of items by capturing the patterns of price change,but there is very limited work to study the price prediction of seasonal goods(e.g.,Christmas gifts).Seasonal items’prices have different patterns than normal items;this can be linked to the offers and discounted prices of seasonal *** lack of research studies motivates the current work to investigate the problem of seasonal items’prices as a time series *** proposed utilizing two different approaches to address this problem,namely,1)machine learning(ML)-based models and 2)deep learning(DL)-based ***,this research tuned a set of well-known predictive models on a real-life *** models are ensemble learning-based models,random forest,Ridge,Lasso,and Linear ***,two new DL architectures based on gated recurrent unit(GRU)and long short-term memory(LSTM)models are ***,the performance of the utilized ensemble learning and classic ML models are compared against the proposed two DL architectures on different accuracy metrics,where the evaluation includes both numerical and visual comparisons of the examined *** obtained results show that the ensemble learning models outperformed the classic machine learning-based models(e.g.,linear regression and random forest)and the DL-based models.

关键词： Deep learning price prediction seasonal goods time series analysis

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Wearable UWB Antenna-Based Bending and Wet Performances for Breast Cancer Detection

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Computers, Materials & Continua 2022年第12期73卷 5575-5587页

作者： ali Hanafiah Rambe Muzammil Jusoh Samir Salem Al-Bawri Mahmoud A.Abdelghany Department of Electrical Engineering Universitas Sumatera UtaraMedan20155Indonesia Advanced Communication Engineering(ACE) Centre of ExcellenceFaculty of Electronic Engineering TechnologyUniversiti Malaysia PerlisMalaysia Department of General Educational Development Faculty of Science and Information Technology(FSIT)Daffodil International UniversityDhaka1341Bangladesh Space Science Centre Climate Change InstituteUniversiti Kebangsaan MalaysiaBangiMalaysia Department of Electronics and Communication Engineering Faculty of EngineeringHadhramout UniversityAl-MukallaYemen Electrical Engineering Department College of EngineeringPrince Sattam Bin Abdulaziz UniversityWadi Addwasir11991Saudi Arabia Department of Electrical Engineering Faculty of EngineeringMinia UniversityMinia61519Egypt

This paper proposed integrating the communication system on the garment,which can be utilized to detect breast cancer at an early stage by using an ultra-wideband(UWB)wearable *** cancer is an abnormal cell that is located in the breast *** detection of breast cancer plays an important role,and it helps in the long term for all *** proposed UWB wearable antenna successfully operates at 3.1-10.6 GHz under an acceptable reflection coefficient of−10 *** fabricated wearable antenna was made from Shieldit Super and felt both conductive and nonconductive wearable *** measurement studies of bending angles have been carried out that covered 2°,4°,6°,8°,and 10°.In addition,the performance of UWB antennas in wet environments is studied in four stages:in water,instantly wet,nearly dry,and entirely *** is good agreement between the measured and simulated *** on the experimental results,the proposed antenna could be helpful for a home breast cancer detection system.

关键词： Wearable antenna UWB antenna bioelectromagnetic antenna propagation

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Analysis of Silver Nanoparticles in Engine Oil: Atangana–Baleanu Fractional Model

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Computers, Materials & Continua 2021年第6期67卷 2915-2932页

作者： Saqib Murtaza Farhad ali Nadeem Ahmad Sheikh Ilyas Khan Kottakkaran Sooppy Nisar Department of Mathematics City University of Science and Information TechnologyPeshawar25000Pakistan Computational Analysis Research Group Ton Duc Thang UniversityHo Chi Minh City70000Vietnam Faculty of Mathematics and Statistics Ton Duc Thang UniversityHo Chi Minh City70000Vietnam Department of Mathematics College of Science Al-ZulfiMajmah UniversityAl-Majmah11952Saudi Arabia Department of Mathematics College of Arts and SciencePrince Sattam bin Abdulaziz UniversityWadi Al-Dawaser11991Saudi Arabia

The present article aims to examine the heat and mass distribution in a free convection flow of electrically conducted,generalized Jeffrey nanofluid in a heated rotatory *** flow analysis is considered in the presence of thermal radiation and the transverse magnetic field of strength *** medium is porous accepting generalized Darcy’s *** motion of the fluid is due to the cosine oscillations of the *** has been formed by the uniform dispersing of the Silver nanoparticles in regular engine *** problem has been modeled in the form of classical partial differential equations and then generalized by replacing time derivative with Atangana–Baleanu(AB)time-fractional *** taking the Laplace transform technique(LTT)and using physical boundary conditions,exact expressions have been obtained for momentum,energy,and concentration *** impact of a number of parameters on fluid flow is shown *** numerical tables have been computed for variation in the rate of heat and mass transfer with respect to rooted ***,the classical solution is recovered by taking the fractional parameter approaching *** is worth noting that by adding silver nanoparticles in regular engine oil,its heat transfer rate increased by 14.59%,which will improve the life and workability of the engine.

关键词： Jeffrey fluid silver nanoparticles engine oil Atangana-Baleanu fractional derivatives Laplace transform technique

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Zooneuston and zooplankton abundance and diversity in relation to spatial and nycthemeral variations in the Gulf of Aqaba and northern Red Sea

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Acta Oceanologica Sinica 2019年第12期38卷 59-72页

作者： Gopikrishna Mantha Abdulmohsin AAl-Sofyani Al-Aidaroos ali M Michael P Crosby Department of Marine Biology Faculty of Marine SciencesKing Abdulaziz UniversityPB-80209Jeddah 21589Saudi Arabia MOTE Marine Laboratory and Aquarium SarasotaFL 34236USA Environment and Life Sciences Research Center Kuwait Institute for Scientific ResearchPB-1638Salmiya 22017Kuwait Marina Labs NerkundrumChennai 600107India

Zooplankton and zooneuston observations were made at seven stations(four from the Gulf of Aqaba and three from the northern Red Sea), during September and October 2016. The main objective of this study was to assess the variability of nycthemeral fauna in relation to the sampling methods using two different types of nets namely,WP2 net and Neuston net along the two study sites, i.e., the Gulf of Aqaba and the northern Red Sea. Zooplankton was sampled vertically using a standard WP2 net from a depth of 200 m to the surface, whereas zooneuston was made using a standard Neuston net from a depth of 0–10 cm of the water surface. Total zooplankton density was maximum during night time((617.83 ± 201.84) ind./m^3) at the Gulf of Aqaba and total zooneuston was maximum during night at the northern Red Sea((60.94±29.48) ind./m^3), respectively. The most abundant taxa were Copepoda, Gastropoda, Bivalva, Chaetognatha, Tunicata and Ostracoda. The abundance was almost 50% higher at night time at both the Gulf of Aqaba and the northern Red Sea. Overall, 30 taxa covering 10 phyla and 27 taxa covering 8 phyla were recorded in the Gulf of Aqaba and the northern Red Sea.

关键词： zooplankton zooneuston nycthemeral variation Cyclopoida Gulf of Aqaba northern Red Sea

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Multiple Pedestrian Detection and Tracking in Night Vision Surveillance Systems

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Computers, Materials & Continua 2023年第5期75卷 3275-3289页

作者： ali Raza Samia Allaoua Chelloug Mohammed Hamad Alatiyyah Ahmad Jalal Jeongmin Park Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Sciences and Humanities in AflajPrince Sattam Bin Abdulaziz UniversityAl-KharjSaudi Arabia Department of Computer Engineering Tech University of Korea237 Sangidaehak-roSiheung-siGyeonggi-do15073Korea

Pedestrian detection and tracking are vital elements of today’s surveillance systems,which make daily life safe for ***,human detection and visualization have become essential inventions in the field of computer ***,developing a surveillance system with multiple object recognition and tracking,especially in low light and night-time,is still ***,we propose a novel system based on machine learning and image processing to provide an efficient surveillance system for pedestrian detection and tracking at *** particular,we propose a system that tackles a two-fold problem by detecting multiple pedestrians in infrared(IR)images using machine learning and tracking them using particle ***,a random forest classifier is adopted for image segmentation to identify pedestrians in an *** result of detection is investigated by particle filter to solve pedestrian *** the extensive experiment,our system shows 93%segmentation accuracy using a random forest algorithm that demonstrates high accuracy for background and roof ***,the system achieved a detection accuracy of 90%usingmultiple templatematching techniques and 81%accuracy for pedestrian ***,our system can identify that the detected object is a ***,our system provided the best results compared to the state-ofart systems,which proves the effectiveness of the techniques used for image segmentation,classification,and *** presented method is applicable for human detection/tracking,crowd analysis,and monitoring pedestrians in IR video surveillance.

关键词： Pedestrian detection machine learning segmentation tracking verification

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Essential oils used in aromatherapy: A systemic review

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Asian Pacific Journal of Tropical Biomedicine 2015年第8期5卷 589-598页

作者： Babar ali Naser ali Al-Wabel Saiba Shams Aftab Ahamad Shah Alam Khan Firoz Anwar College of Pharmacy and Dentistry Buraydah Colleges Siddhartha Institute of Pharmacy Health Information Technology Department Jeddah Community College King Abdulaziz University Department of Pharmacy Oman Medical College Department of Biochemistry Faculty of Science King Abdulaziz University

Nowadays, use of alternative and complementary therapies with mainstream medicine has gained the momentum. Aromatherapy is one of the complementary therapies which use essential oils as the major therapeutic agents to treat several diseases. The essential or volatile oils are extracted from the flowers, barks, stem, leaves, roots, fruits and other parts of the plant by various methods. It came into existence after the scientists deciphered the antiseptic and skin permeability properties of essential oils. Inhalation, local application and baths are the major methods used in aromatherapy that utilize these oils to penetrate the human skin surface with marked aura. Once the oils are in the system, they remodulate themselves and work in a friendly manner at the site of malfunction or at the affected area. This type of therapy utilizes various permutation and combinations to get relief from numerous ailments like depression, indigestion, headache, insomnia, muscular pain, respiratory problems, skin ailments, swollen joints, urine associated complications etc. The essential oils are found to be more beneficial when other aspects of life and diet are given due consideration. This review explores the information available in the literature regarding therapeutic, medical, cosmetic, psychological, olfactory, massage aromatherapy, safety issues and different plants used in aromatherapy. All the available information was compiled from electronic databases such as Academic Journals, Ethnobotany, Google Scholar, PubM ed, Science Direct, Web of Science, and library search.

关键词： Complementary therapy Aromatherapy Essential oils Inhalation

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Week Ahead Electricity Power and Price Forecasting Using Improved DenseNet-121 Method

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Computers, Materials & Continua 2022年第9期72卷 4249-4265页

作者： Muhammad Irfan ali Raza Faisal Althobiani Nasir Ayub Muhammad Idrees Zain ali Kashif Rizwan Abdullah Saeed Alwadie Saleh Mohammed Ghonaim Hesham Abdushkour Saifur Rahman Omar Alshorman Samar Alqhtani Electrical Engineering Department College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Department of Computer Science COMSATS University IslamabadWah Campus22060Pakistan Faculty of Maritime Studies King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science Federal Urdu University of ArtsScience and TechnologyIslamabad44000Pakistan School of Electrical Engineering and Computer Science National University of Science and TechnologyIslamabad44000Pakistan Department of Computer Science and Engineering University of Engineering and TechnologyNarowal CampusLahore54000Pakistan Department of Electrical Engineering HITEC UniversityTaxila47080Pakistan College of Computer Science and Information Systems Najran UniversityNajran61441Saudi Arabia

In the Smart Grid(SG)residential environment,consumers change their power consumption routine according to the price and incentives announced by the utility,which causes the prices to deviate from the initial ***,electricity demand and price forecasting play a significant role and can help in terms of reliability and *** to the massive amount of data,big data analytics for forecasting becomes a hot topic in the SG *** this paper,the changing and non-linearity of consumer consumption pattern complex data is taken as *** minimize the computational cost and complexity of the data,the average of the feature engineering approaches includes:Recursive Feature Eliminator(RFE),Extreme Gradient Boosting(XGboost),Random Forest(RF),and are upgraded to extract the most relevant and significant *** this end,we have proposed the DensetNet-121 network and Support Vector Machine(SVM)ensemble with Aquila Optimizer(AO)to ensure adaptability and handle the complexity of data in the ***,the AO method helps to tune the parameters of DensNet(121 layers)and SVM,which achieves less training loss,computational time,minimized overfitting problems and more training/test *** evaluation metrics and statistical analysis validate the proposed model results are better than the benchmark *** proposed method has achieved a minimal value of the Mean Average Percentage Error(MAPE)rate i.e.,8%by DenseNet-AO and 6%by SVM-AO and the maximum accurateness rate of 92%and 95%,respectively.

关键词： Smart grid deep neural networks consumer demand big data analytics load forecasting price forecasting

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IoMT Enabled Melanoma Detection Using Improved Region Growing Lesion Boundary Extraction

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Computers, Materials & Continua 2022年第6期71卷 6219-6237页

作者： Tanzila Saba Rabia Javed Mohd Shafry Mohd Rahim Amjad Rehman Saeed ali Bahaj Artificial Intelligence&Data Analytics Lab CCIS Prince Sultan UniversityRiyadh11586Saudi Arabia School of Computing Faculty of EngineeringUniversiti Teknologi MalaysiaSkudai81310Johor BahruMalaysia Department of Computer Science Lahore College for Women UniversityLahore54000Pakistan MIS Department College of Business Administration Prince Sattam bin Abdulaziz UniversityAlkharj11942Saudi Arabia

The Internet ofMedical Things(IoMT)and cloud-based healthcare applications,services are beneficial for better decision-making in recent *** is a deadly cancer with a highermortality rate than other skin cancer types such as basal cell,squamous cell,andMerkel ***,detection and treatment at an early stage can result in a higher chance of *** classical methods of detection are expensive and ***,they rely on a trained practitioner’s level,and the availability of the needed equipment is essential for the early detection of *** current improvement in computer-aided systems is providing very encouraging results in terms of precision and *** this article,we propose an improved region growing technique for efficient extraction of the lesion *** analysis and detection ofMelanoma are helpful for the expert *** CNN features are extracted using the pre-trained VGG-19 deep learning *** the end,the selected features are classified by *** proposed technique is gauged on openly accessible two datasets ISIC 2017 and *** the evaluation of our proposed framework,qualitative and quantitative experiments are *** suggested segmentation method has provided encouraging statistical results of Jaccard index 0.94,accuracy 95.7%on ISIC 2017,and Jaccard index 0.91,accuracy 93.3%on the PH2 *** results are notably better than the results of prevalent methods available on the same *** machine learning SVMclassifier executes significantly well on the suggested feature vector,and the comparative analysis is carried out with existing methods in terms of *** proposed method detects and classifies melanoma far better than other ***,our framework gained promising results in both segmentation and classification phases.

关键词： Deep features extraction lesion segmentation melanoma detection SVM VGG-19 healthcare IoMT public health

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Handling Class Imbalance in Online Transaction Fraud Detection

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Computers, Materials & Continua 2022年第2期70卷 2861-2877页

作者： Kanika Jimmy Singla ali Kashif Bashir Yunyoung Nam Najam UI Hasan Usman Tariq School of Computer Science and Engineering Lovely Professional UniversityPunjabIndia Department of Computing and Mathematics ManchesterMetropolitan UniversityUK&School of Electrical Engineering and Computer ScienceNational University of Science and TechnologyIslamabadPakistan Department of Computer Science and Engineering Soonchunhyang UniversityAsan31538Korea Department of Electrical and Computer Engineering Dhofar UniversitySalalahOman College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia

With the rise of internet facilities,a greater number of people have started doing online transactions at an exponential rate in recent years as the online transaction system has eliminated the need of going to the bank physically for every ***,the fraud cases have also increased causing the loss of money to the ***,an effective fraud detection system is the need of the hour which can detect fraudulent transactions automatically in ***,the genuine transactions are large in number than the fraudulent transactions which leads to the class imbalance *** this research work,an online transaction fraud detection system using deep learning has been proposed which can handle class imbalance problem by applying algorithm-level methods which modify the learning of the model to focus more on the minority class i.e.,fraud transactions.A novel loss function named Weighted Hard-Reduced Focal Loss(WH-RFL)has been proposed which has achieved maximum fraud detection rate i.e.,True PositiveRate(TPR)at the cost of misclassification of few genuine transactions as high TPR is preferred over a high True Negative Rate(TNR)in fraud detection system and same has been demonstrated using three publicly available imbalanced transactional ***,Thresholding has been applied to optimize the decision threshold using cross-validation to detect maximum number of frauds and it has been demonstrated by the experimental results that the selection of the right thresholding method with deep learning yields better results.

关键词： Class imbalance deep learning fraud detection loss function thresholding

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