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Investigation of contact behavior on a model of the dual-mobility artificial hip joint for Asians in different inner liner thicknesses

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World Journal of Orthopedics 2024年第4期15卷 321-336页

作者： Taufiq Hidayat muhammad imam ammarullah Rifky Ismail Eko Saputra M Danny Pratama Lamura Chethan K N Athanasius Priharyoto Bayuseno J Jamari Department of Mechanical Engineering Universitas Muria KudusKudus 59352Central JavaIndonesia Department of Mechanical Engineering Universitas DiponegoroSemarang 50275Central JavaIndonesia Undip Biomechanics Engineering&Research Centre Universitas DiponegoroSemarang 50275Central JavaIndonesia Center for Biomechanics Biomaterials Biomechatronics and Biosignal Processing Universitas DiponegoroSemarang 50275Central JavaIndonesia Department of Mechanical Engineering Politeknik Negeri SemarangSemarang 50275Central JavaIndonesia Department of Aeronautical and Automobile Engineering Manipal Institute of TechnologyManipalManipal Academy of Higher EducationManipal 576104KarnatakaIndia

BACKGROUND The four components that make up the current dual-mobility artificial hip joint design are the femoral head,the inner liner,the outer liner as a metal cover to prevent wear,and the acetabular *** acetabular cup and the outer liner were constructed of 316L stainless *** the same time,the inner liner was made of ultra-high-molecular-weight polyethylene(UHMWPE).As this new dual-mobility artificial hip joint has not been researched extensively,more tribological research is needed to predict *** thickness of the inner liner is a significant component to consider when calculating the contact *** To make use of finite element analysis to gain a better understanding of the contact behavior in various inner liner thicknesses on a new model of a dual-mobility artificial hip joint,with the ultimate objective of determining the inner liner thickness that was most suitable for this particular type of dual-mobility artificial hip *** In this study,the size of the femoral head was compared between two diameters(28 mm and 36 mm)and eight inner liner thicknesses ranging from 5 mm to 12 *** the finite element method,the contact parameters,including the maximum contact pressure and contact area,have been evaluated in light of the Hertzian contact *** simulation was performed statically with dissipated energy and asymmetric *** types of interaction were surface-to-surface contact and normal contact *** The maximum contact pressures in the inner liner(UHMWPE)at a head diameter of 28 mm and 36 mm are between 3.7-13.5 MPa and 2.7-10.4 MPa,*** maximum von Mises of the inner liner,outer liner,and acetabular cup are 2.4–11.4 MPa,15.7–44.3 MPa,and 3.7–12.6 MPa,respectively,for 28 mm *** the maximum von Mises stresses of the 36 mm head are 1.9-8.9 MPa for the inner liner,9.9-32.8 MPa for the outer liner,and 2.6-9.9 MPa for the acetabular cup.A head with a diameter of 28 mm should have an inner line

关键词： Contact behavior Contact pressure Finite element analysis Dual-mobility Artificial hip joint

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A Lightweight Intrusion Detection System Using Convolutional Neural Network and Long Short-Term Memory in Fog Computing

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Computers, Materials & Continua 2024年第9期80卷 4703-4728页

作者： Hawazen Alzahrani Tarek Sheltami Abdulaziz Barnawi muhammad imam Ansar Yaser Computer Engineering Department Interdisciplinary Research Center of Smart Mobility and LogisticsKing Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia Computer Engineering Department Interdisciplinary Research Center for Intelligent Secure SystemsKing Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia Transportation Research Institute(IMOB) Hasselt UniversityHasselt3500Belgium

The Internet of Things(IoT)links various devices to digital services and significantly improves the quality of our ***,as IoT connectivity is growing rapidly,so do the risks of network vulnerabilities and *** interesting Intrusion Detection Systems(IDSs)are presented based on machine learning(ML)techniques to overcome this *** the resource limitations of fog computing environments,a lightweight IDS is *** paper introduces a hybrid deep learning(DL)method that combines convolutional neural networks(CNN)and long short-term memory(LSTM)to build an energy-aware,anomaly-based *** test this system on a recent dataset,focusing on reducing overhead while maintaining high accuracy and a low false alarm *** compare CICIoT2023,KDD-99 and NSL-KDD datasets to evaluate the performance of the proposed IDS model based on key metrics,including latency,energy consumption,false alarm rate and detection rate *** findings show an accuracy rate over 92%and a false alarm rate below 0.38%.These results demonstrate that our system provides strong security without excessive resource *** practicality of deploying IDS with limited resources is demonstrated by the successful implementation of IDS functionality on a Raspberry Pi acting as a Fog *** proposed lightweight model,with a maximum power consumption of 6.12 W,demonstrates its potential to operate effectively on energy-limited devices such as low-power fog nodes or edge *** prioritize energy efficiency whilemaintaining high accuracy,distinguishing our scheme fromexisting *** experiments demonstrate a significant reduction in false positives,ensuring accurate identification of genuine security threats while minimizing unnecessary alerts.

关键词： Intrusion detection fog computing CNN LSTM energy consumption

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Machine Learning Techniques Using Deep Instinctive Encoder-Based Feature Extraction for Optimized Breast Cancer Detection

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Computers, Materials & Continua 2024年第2期78卷 2441-2468页

作者： Vaishnawi Priyadarshni Sanjay Kumar Sharma Mohammad Khalid imam Rahmani Baijnath Kaushik Rania Almajalid Department of Computer Science Gautam Buddha UniversityGreater NoidaUttar PradeshIndia College of Computing and Informatics Saudi Electronic UniversityRiyadh11673Saudi Arabia School of Computer Science Shri Vaishno Devi UniversityKatraIndia

Breast cancer(BC)is one of the leading causes of death among women worldwide,as it has emerged as the most commonly diagnosed malignancy in *** detection and effective treatment of BC can help save women’s *** an efficient technology-based detection system can lead to non-destructive and preliminary cancer detection *** paper proposes a comprehensive framework that can effectively diagnose cancerous cells from benign cells using the Curated Breast Imaging Subset of the Digital Database for Screening Mammography(CBIS-DDSM)data *** novelty of the proposed framework lies in the integration of various techniques,where the fusion of deep learning(DL),traditional machine learning(ML)techniques,and enhanced classification models have been deployed using the curated *** analysis outcome proves that the proposed enhanced RF(ERF),enhanced DT(EDT)and enhanced LR(ELR)models for BC detection outperformed most of the existing models with impressive results.

关键词： Autoencoder breast cancer deep neural network convolutional neural network image processing machine learning deep learning

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Deep Learning-Based ECG Classification for Arterial Fibrillation Detection

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Computers, Materials & Continua 2024年第6期79卷 4805-4824页

作者： muhammad Sohail Irshad Tehreem Masood Arfan Jaffar muhammad Rashid Sheeraz Akram Abeer Aljohani Faculty of Computer Science&Information Technology The Superior UniversityLahore54000Pakistan Intelligent Data Visual Computing Research(IDVCR) Lahore54000Pakistan Department of Computer Science National University of TechnologyIslamabad45000Pakistan Information Systems Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia Department of Computer Science Applied CollegeTaibah UniversityMedina42353Saudi Arabia

The application of deep learning techniques in the medical field,specifically for Atrial Fibrillation(AFib)detection through Electrocardiogram(ECG)signals,has witnessed significant *** and timely diagnosis increases the patient’s chances of ***,issues like overfitting and inconsistent accuracy across datasets remain *** a quest to address these challenges,a study presents two prominent deep learning architectures,ResNet-50 and DenseNet-121,to evaluate their effectiveness in AFib *** aim was to create a robust detection mechanism that consistently performs *** such as loss,accuracy,precision,sensitivity,and Area Under the Curve(AUC)were utilized for *** findings revealed that ResNet-50 surpassed DenseNet-121 in all evaluated *** demonstrated lower loss rate 0.0315 and 0.0305 superior accuracy of 98.77%and 98.88%,precision of 98.78%and 98.89%and sensitivity of 98.76%and 98.86%for training and validation,hinting at its advanced capability for AFib *** insights offer a substantial contribution to the existing literature on deep learning applications for AFib detection from ECG *** comparative performance data assists future researchers in selecting suitable deep-learning architectures for AFib ***,the outcomes of this study are anticipated to stimulate the development of more advanced and efficient ECG-based AFib detection methodologies,for more accurate and early detection of AFib,thereby fostering improved patient care and outcomes.

关键词： Convolution neural network atrial fibrillation area under curve ECG false positive rate deep learning classification

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Nodule Detection Using Local Binary Pattern Features to Enhance Diagnostic Decisions

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Computers, Materials & Continua 2024年第3期78卷 3377-3390页

作者： Umar Rashid Arfan Jaffar muhammad Rashid Mohammed S.Alshuhri Sheeraz Akram Faculty of Computer Science and Information Technology The Superior UniversityLahore54600Pakistan Intelligent Data Visual Computing Research(IDVCR) Lahore54600Pakistan Department of Computer Science National University of TechnologyIslamabad45000Pakistan Department of Radiological Sciences and Medical Imaging College of AppliedMedical SciencesPrince Sattam Bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Information Systems Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh12571Saudi Arabia

Pulmonary nodules are small, round, or oval-shaped growths on the lungs. They can be benign (noncancerous) or malignant (cancerous). The size of a nodule can range from a few millimeters to a few centimeters in diameter. Nodules may be found during a chest X-ray or other imaging test for an unrelated health problem. In the proposed methodology pulmonary nodules can be classified into three stages. Firstly, a 2D histogram thresholding technique is used to identify volume segmentation. An ant colony optimization algorithm is used to determine the optimal threshold value. Secondly, geometrical features such as lines, arcs, extended arcs, and ellipses are used to detect oval shapes. Thirdly, Histogram Oriented Surface Normal Vector (HOSNV) feature descriptors can be used to identify nodules of different sizes and shapes by using a scaled and rotation-invariant texture description. Smart nodule classification was performed with the XGBoost classifier. The results are tested and validated using the Lung Image Consortium Database (LICD). The proposed method has a sensitivity of 98.49% for nodules sized 3–30 mm.

关键词： Pulmonary nodules segmentation histogram thresholding

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Adding chitosan nanoparticles of green tea extract in diluent and thawing temperatures ameliorate the post-thawed quality of Boer buck semen

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Asian pacific Journal of Reproduction 2024年第1期13卷 42-48页

作者： Suherni Susilowati imam Mustofa Tri Wahyu Suparyogi Adeyinka Oye Akintunde Djoko Agus Purwanto Wurlina Wurlina Suzanita Utama Sri Mulyati Division of Veterinary Reproduction Faculty of Veterinary MedicineUniversitas AirlanggaKampus C UnairMulyorejoSurabaya 60115Indonesia Department of Agriculture and Industrial Technology Babcock UniversityIlishan-RemoOgun State 121103Nigeria Department of Pharmaceutical Chemistry Faculty of PharmacyUniversitas AirlanggaKampus C MulyorejoSurabaya 601155East JavaIndonesia

Objective:To improve the quality of post-thawing Boer buck semen for artificial insemination by adding green tea extract chitosan nanoparticles to skimmed egg yolk diluent,and the proper thawing ***:The ejaculate of Boer buck was added to skimmed egg yolk diluent without(the control group)and with adding 1μg of chitosan nanoparticles of green tea extract per mL of diluent(the treatment group).Then,the diluted semen was filled in French mini straws containing 60×106 live sperm per straw,frozen in a standard protocol,and stored as frozen semen at−196℃for a *** replicates from each group were diluted for 30 s at 37℃or 39℃sterile water to evaluate the semen ***:Post-thawing(at 37℃or 39℃)of live sperm,progressive motility,and plasma membrane integrity were lower compared to those of the pre-freezing stage(P0.05).The live sperm,progressive motility,and plasma membrane of the treatment group in the pre-freezing stage,and post-thawed at 39℃were higher compared to those of the control group(P0.05).Conclusions:Higher quality post-thawing Boer buck semen is achieved by adding 1μg/mL of chitosan nanoparticles of green tea extract to the skimmed egg yolk diluent and thawing at 39℃.

关键词： Boer buck semen Chitosan nanoparticles Semen diluent Higher post-thawing semen quality Prevent undernutrition

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Nitrogen-Doped Amorphous Carbon Homojunction from Palmyra Sugar as a Renewable Solar Cell

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Journal of Renewable Materials 2024年第1期12卷 57-69页

作者： Budhi Priyanto imam Khambali Irma Septi Ardiani Khoirotun Nadhiyah Anna Zakiyatul Laila M.Chasrun Hasani Bima Romadhon Retno Asih Yoyok Cahyono Triwikantoro Darminto Department of Electronic Engineering Faculty of EngineeringUniversitas Muhammadiyah MalangKota MalangIndonesia Advanced Materials Research Group Department of PhysicsFaculty of Science and Data AnalyticsInstitut Teknologi Sepuluh NopemberSurabayaIndonesia Department of Electronic Engineering Faculty of Industrials EngineeringInstitut Teknologi National MalangKota MalangIndonesia

An a-C/a-C:N junction,which used palmyra sugar as the carbon source and ammonium hydroxide(NH4OH)as the dopant source,was successfully deposited on the ITO glass substrate using the nano-spraying *** current-voltage relationship of the junction was found to be a Schottky-like contact,and therefore the junction shows the characteristic *** means the a-C and a-C:N are semiconductors with different types of ***,the samples showed an increase in current and voltage value when exposed to visible light(bright state)compared to the dark condition,thereby,indicating the creation of electron-hole pairs during the *** was also discovered that the relationship between current and voltage for the a-C/a-C:N junction sample formed a curve that satisfies the rule of the photovoltaic effect when exposed to visible light from a light *** exposure of this sample to direct sunlight at AM 1.5 conditions produced a curve that meets the rules for the emergence of the photovoltaic effect with higher characteristics for the current-voltage ***,the a-C/a-C:N junction sample is a solar cell successfully fabricated using a sample method and has a maximum efficiency of 0.0013%.

关键词： Solar cell amorphous carbon palmyra sugar

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Evaluation of the Neurodevelopmental Outcome of Toddlers with Spinal Dysraphism after Surgical Repair Using ASQ-3^™ Scores

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Open Journal of Modern Neurosurgery 2024年第1期14卷 14-29页

作者： Mujahid imam Fawaz Eljili Marhoom Sawsan Aldeaf Ali Awad Ahmed Zidan Mohamed Mustafa Ahmed Sanna Taha Neurosurgery Department National Center for Neurological Sciences (NCNS) Khartoum Sudan Neurosurgery Department Royal Care International Hospital Khartoum Sudan Al Ribat Neurospine Center Khartoum Sudan Neurosurgery Department Haj Almardi (Al Tamyouz) Hospital Khartoum Sudan Neurosurgery Department Al Jazeera Trauma Center Khartoum Sudan

Background: Spinal dysraphism represents a wide spectrum of congenital abnormalities of the spine. Myelomeningocele is considered the most common malformation and the most common we saw in our community, with its morbidity problems seen commonly in the postoperative period. ASQ-3TM Scores are the ages and stages questionnaire, third edition, and represent a tool to assess the development progress, especially in toddlers. Objectives: Evaluation of neurodevelopmental outcome among Sudanese toddlers with spinal dysraphism after surgical closure with or without a VP shunt using ASQ-3TM Scores. Methodology: This is a retrospective hospital-based study of 84 patients who underwent myelomeningocele repair at the National Center for Neurological Sciences (NCNS) during the period from 2017 up to 2019. Data were collected through a constructed questionnaire, including ASQ-3TM Scores. Data were processed and analyzed using the Statistical Package for Social Science (SPSS) computer program. Version 25. Results: 84 patients were included in this study;all patients were diagnosed with spinal dysraphism. Out of them, 51 (60.7%) were 2 years old, 33 (39.3%) were 3 years old, 45 (53.6%) were male, 45 (53.6%) of patients mothers attended ANC irregularly, and 54 (64.3%) their mothers didn’t receive folate supplements. 44 (52.3%) of patients underwent MMC repair only, while 40 (47.7%) underwent MMC repair and VP shunt. The commonest postoperative complication was infection, reported in 12 (14.3%) of patients, followed by VP shunt revision in 9 (10.7%) of patients. Neurological assessment showed that the majority of patients need further assessment with a professional, 57 (67.9%) of children don’t walk, run, or climb like other toddlers as their parent’s state;also, half of patients (42, 50%) had medical problems, and 27 (32.1%) of their parent’s state that they do not talk like other toddlers their age. There was a statistically significant association

关键词： Toddlers’ Neurodevelopmental Outcome Myelomeningocele Evaluation ASQ-3™ Scores Spinal Dysraphasim Neurodevelopmental Outcome

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Fusion of Infrared and Visible Images Using Fuzzy Based Siamese Convolutional Network

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Computers, Materials & Continua 2022年第3期70卷 5503-5518页

作者： Kanika Bhalla Deepika Koundal Surbhi Bhatia Mohammad Khalid imam Rahmani muhammad Tahir Department of Electrical Engineering National Taipei University of TechnologyTaipei10608Taiwan Department Virtualization School of Computer ScienceUniversity of Petroleum&Energy StudiesDehradunIndia College of Computer Science and Information technology King Faisal University36362Saudi Arabia College of Computing and Informatics Saudi Electronic UniversityRiyadh11673Saudi Arabia

Traditional techniques based on image fusion are arduous in integrating complementary or heterogeneous infrared(IR)/visible(VS)*** in various kind of features in these images are vital to preserve in the single fused ***,simultaneous preservation of both the aspects at the same time is a challenging ***,most of the existing methods utilize the manual extraction of features;and manual complicated designing of fusion rules resulted in a blurry artifact in the fused ***,this study has proposed a hybrid algorithm for the integration of multi-features among two heterogeneous ***,fuzzification of two IR/VS images has been done by feeding it to the fuzzy sets to remove the uncertainty present in the background and object of interest of the ***,images have been learned by two parallel branches of the siamese convolutional neural network(CNN)to extract prominent features from the images as well as high-frequency information to produce focus maps containing source image ***,the obtained focused maps which contained the detailed integrated information are directly mapped with the source image via pixelwise strategy to result in fused *** parameters have been used to evaluate the performance of the proposed image fusion by achieving 1.008 for mutual information(MI),0.841 for entropy(EG),0.655 for edge information(EI),0.652 for human perception(HP),and 0.980 for image structural similarity(ISS).Experimental results have shown that the proposed technique has attained the best qualitative and quantitative results using 78 publically available images in comparison to the existing discrete cosine transform(DCT),anisotropic diffusion&karhunen-loeve(ADKL),guided filter(GF),random walk(RW),principal component analysis(PCA),and convolutional neural network(CNN)methods.

关键词： Convolutional neural network fuzzy sets infrared and visible image fusion deep learning

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Quantum Particle Swarm Optimization Based Convolutional Neural Network for Handwritten Script Recognition

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Computers, Materials & Continua 2022年第6期71卷 5855-5873页

作者： Reya Sharma Baijnath Kaushik Naveen Kumar Gondhi muhammad Tahir Mohammad Khalid imam Rahmani School of Computer Science and Engineering SMVDUJ&KIndia College of Computing and Informatics Saudi Electronic UniversityRiyadhSaudi Arabia

Even though several advances have been made in recent years,handwritten script recognition is still a challenging task in the pattern recognition *** field has gained much interest lately due to its diverse application ***,different methods are available for automatic script *** most of the reported script recognition techniques,deep neural networks have achieved impressive results and outperformed the classical machine learning ***,the process of designing such networks right from scratch intuitively appears to incur a significant amount of trial and error,which renders them *** approach often requires manual intervention with domain expertise which consumes substantial time and computational *** alleviate this shortcoming,this paper proposes a new neural architecture search approach based on meta-heuristic quantum particle swarm optimization(QPSO),which is capable of automatically evolving the meaningful convolutional neural network(CNN)*** computational experiments have been conducted on eight different datasets belonging to three popular Indic scripts,namely Bangla,Devanagari,and Dogri,consisting of handwritten characters and ***,the results imply that the proposed QPSO-CNN algorithm outperforms the classical and state-of-the-art methods with faster prediction and higher accuracy.

关键词： Neuro-evolution quantum particle swarm optimization deep learning convolutional neural networks handwriting recognition

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