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Neglected congenital bilateral knee dislocation treated by quadricepsplasty with semitendinosus and sartorius transfer:A case report

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World Journal of Orthopedics 2024年第8期15卷 807-812页

作者： Osama M Qasim abdulaziz A abdulaziz Nibras K aljabri Khalid S albaqami Rayan M Suqaty College of Medicine Umm Al-Qura UniversityMecca 21955Makkah al MukarramahSaudi Arabia Department of Orthopedic King Faisal Medical Complex TaifTaif 26514TaifSaudi Arabia Department of Orthopedic Alnoor Specialist HospitalMecca 24241Makkah al MukarramahSaudi Arabia

BACKGROUND Congenital knee dislocation(CKD)is a rare condition,which accounts for 1%of congenital hip *** can present as an isolated condition or coexist with other genetic *** options include serial casting,percutaneous quadriceps recession,and V-Y quadricepsplasty(VYQ).The pathogenesis and hereditary patterns of CKD are not fully understood,with most cases being *** is usually managed immediately after ***,in this report,the patient was neglected for 2 *** SUMMARY A 2-year-old girl with bilateral CKD after birth presented to our hospital after failed serial casting;the patient had seizures and limited access to healthcare because of her family’s low socioeconomic *** birth was noted for a breech presentation accompanied by *** delivery took a long time,requiring immediate medical *** an infant,she had chronic diseases,including a small patent ductus arteriole,multicystic dysplastic kidney disease,and *** was found to have a bilateral knee dislocation of approximately-90°on hyperextension.A multidisciplinary team was involved,and medical care was *** underwent VYQ plus semitendinosus and sartorius *** four postoperative follow-ups,her knees were regaining mobility,and she could walk for 2-3 steps without *** This report highlights the importance of early intervention and recommends extensive studies of the management in similar cases.

关键词： Knee dislocation Congenital knee dislocation V-Y quadricepsplasty Neglect Neglected knee dislocation Pediatric orthopedics Case report

Multi-Features Disease Analysis Based Smart Diagnosis for COVID-19

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Computer Systems Science & Engineering 2023年第4期45卷 869-886页

作者： Sirisati Ranga Swamy SPhani Praveen Shakeel Ahmed Parvathaneni Naga Srinivasu abdulaziz alhumam Department of CSE Vignan’s Institute of Management and Technology for Women GhatkesarTelanganaIndia Department of CSE PVPSITVijayawadaAndhra Pradesh520007India Department of Computer Science College of Computer Sciences and Information TechnologyKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Computer Science and Engineering-AIML VNR Vignana Jyothi Institute of Engineering and TechnologyHyderabadTelangana500090India

Coronavirus 2019(COVID-19)is the current global buzzword,putting the world at *** pandemic’s exponential expansion of infected COVID-19 patients has challenged the medical field’s resources,which are already *** established nations would not be in a perfect position to manage this epidemic correctly,leaving emerging countries and countries that have not yet begun to grow to address the *** problems can be solved by using machine learning models in a realistic way,such as by using computer-aided images during medical *** models help predict the effects of the disease outbreak and help detect the effects in the coming *** this paper,Multi-Features Decease Analysis(MFDA)is used with different ensemble classifiers to diagnose the disease’s impact with the help of Computed Tomography(CT)scan *** are various features associated with chest CT images,which help know the possibility of an individual being affected and how COVID-19 will affect the persons suffering from *** current study attempts to increase the precision of the diagnosis model by evaluating various feature sets and choosing the best combination for better *** model’s performance is assessed using Receiver Operating Characteristic(ROC)curve,the Root Mean Square Error(RMSE),and the Confusion *** is observed from the resultant outcome that the performance of the proposed model has exhibited better efficient.

关键词： Chest CT COVID-19 classification ROC curves multi-feature disease analysis

Causative bacteria of ventilator-associated pneumonia in intensive care unit in Bahrain:Prevalence and antibiotics susceptibility pattern

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World Journal of Critical Care Medicine 2023年第3期12卷 165-175页

作者： Mohamed Eliwa Hassan Safaa abdulaziz al-Khawaja Nermin Kamal Saeed Sana abdulaziz al-Khawaja Mahmood al-Awainati Sara Salah Yusuf Radhi Mohamed Hameed alsaffar Mohammed al-Beltagi Intensive Care Unit Department of Internal medicineSalmaniya Medical ComplexMinistry of HealthManamaKingdom of BahrainManama 12ManamaBahrain Infectious Disease Unit Department of Internal MedicineSalmaniya Medical ComplexMinistry of HealthKingdom of BahrainManama 12ManamaBahrain Medical Microbiology Section Department of PathologySalmaniya Medical ComplexMinistry of HealthKingdom of BahrainManama 12ManamaBahrain Medical Microbiology Section Department of PathologyIrish Royal College of SurgeonBahrainBusiateen 15503MuharraqBahrain Department of Family Medicine Ministry of HealthManamaKingdom of BahrainManama 12ManamaBahrain Department of Pediatrics Faculty of MedicineTanta UniversityTanta 31511AlghrabiaEgypt Department of Pediatrics University Medical CenterKing Abdulla Medical CityArabian Gulf UniversityDr.Sulaiman Al Habib Medical GroupManama 26671ManamaBahrain

BACKGROUND Ventilator-associated pneumonia(VAP)is defined as pneumonia that occurs two calendar days following endotracheal intubation or after *** is the most common infection encountered among intubated *** incidence showed wide variability between *** To define the VAP incidence in the intensive care unit(ICU)in the central gove-rnment hospital in Bahrain and review the risk factors and the predominant bacterial pathogens with their antimicrobial susceptibility *** The research was a prospective cross-sectional observational study over six months from November 2019 to June *** included adult and adolescent patients(>14 years old)admitted to the ICU and required intubation and mechanical *** was diagnosed when it occurred after 48 h after endotracheal intubation using the clinical pulmonary infection score,which considers the clinical,laboratory,microbiological,and radiographic *** The total number of adult patients admitted to the ICU who required intubation and mechanical ventilation during the study period was ***-six patients developed VAP during their ICU stay(29.7%).The calculated VAP rate was 22.14 events per 1000 ventilator days during the study period,with a mean age of 52 years±*** VAP cases had late-onset VAP with a mean number of ICU days before the development of VAP of 9.96±***-negative contributed to most VAP cases in our unit,with multidrug-resistant Acinetobacter being the most identified *** The reported VAP rate in our ICU was relatively high compared to the international benchmark,which should trigger a vital action plan for reinforcing the implementation of the VAP prevention bundle.

关键词： Ventilator-associated pneumonia Intensive care unit Antibiotics susceptibility pattern Kingdom of Bahrain Adults Bacterial resistance Acinetobacter

Intrusion Detection System with Customized Machine Learning Techniques for NSL-KDD Dataset

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Computers, Materials & Continua 2023年第12期77卷 4025-4054页

作者： Mohammed Zakariah Salman A.alQahtani abdulaziz M.alawwad Abdullilah A.alotaibi Department of Computer Science College of Computer and Information ScienceKing Saud UniversityRiyadh11495Saudi Arabia New Emerging Technologies and 5G Network and Beyond Research Chair Department of Computer EngineeringCollege of Computer and Information SciencesKing Saud UniversityRiyadh11495Saudi Arabia Department of Computer Engineering College of Computer and Information ScienceKing Saud UniversityRiyadh11495Saudi Arabia

Modern networks are at risk from a variety of threats as a result of the enormous growth in internet-based *** consuming time and resources,intrusive traffic hampers the efficient operation of network *** effective strategy for preventing,detecting,and mitigating intrusion incidents will increase productivity.A crucial element of secure network traffic is Intrusion Detection System(IDS).An IDS system may be host-based or network-based to monitor intrusive network *** unusual internet traffic has become a severe security risk for intelligent *** systems are negatively impacted by several attacks,which are slowing *** addition,networked communication anomalies and breaches must be detected using Machine Learning(ML).This paper uses the NSL-KDD data set to propose a novel IDS based on Artificial Neural Networks(ANNs).As a result,the ML model generalizes sufficiently to perform well on untried *** NSL-KDD dataset shall be utilized for both training and *** this paper,we present a custom ANN model architecture using the Keras open-source software *** specific arrangement of nodes and layers,along with the activation functions,enhances the model’s ability to capture intricate patterns in network *** performance of the ANN is carefully tested and evaluated,resulting in the identification of a maximum detection accuracy of 97.5%.We thoroughly compared our suggested model to industry-recognized benchmark methods,such as decision classifier combinations and ML classifiers like k-Nearest Neighbors(KNN),Deep Learning(DL),Support Vector Machine(SVM),Long Short-Term Memory(LSTM),Deep Neural Network(DNN),and *** is encouraging to see that our model consistently outperformed each of these tried-and-true techniques in all *** result underlines the effectiveness of the suggested methodology by demonstrating the ANN’s capacity to accurately assess the effectiveness of the developed strategy

关键词： Artificial neural networks intrusion detection system classification NSL-KDD dataset machine and deep-learning neural network

Securing Consumer Internet of Things for Botnet Attacks: Deep Learning Approach

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Computers, Materials & Continua 2022年第11期73卷 3199-3217页

作者： Tariq Ahamed Ahanger abdulaziz aldaej Mohammed Atiquzzaman Imdad Ullah Mohammed Yousuf Uddin College of Computer Engineering and Science Prince Sattam bin Abdulaziz University Al-Kharj11942Saudi Arabia School of Computer Science University of Oklahoma Norman73019-6151United States

DDoS attacks in the Internet of Things(IoT)technology have increased significantly due to its spread adoption in different industrial *** purpose of the current research is to propose a novel technique for detecting botnet attacks in user-oriented IoT ***,an attack identification technique inspired by Recurrent Neural networks and Bidirectional Long Short Term Memory(BLRNN)is presented using a unique Deep Learning(DL)*** text identification and translation of attack data segments into tokenized form,word embedding is *** performance analysis of the presented technique is performed in comparison to the state-of-the-art DL ***,Accuracy(98.4%),Specificity(98.7%),Sensitivity(99.0%),F-measure(99.0%)and Data loss(92.36%)of the presented BLRNN detection model are determined for identifying 4 attacks over Botnet(Mirai).The results show that,although adding cost to each epoch and increasing computation delay,the bidirectional strategy is more superior technique model over different data instances.

关键词： Internet of Things deep learning security DDoS attack botnet

Predicting Violence-Induced Stress in an Arabic Social Media Forum

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Intelligent Automation & Soft Computing 2023年第2期35卷 1423-1439页

作者： Abeer abdulaziz alArfaj Nada ali Hakami Hanan Ahmed Hosni Mahmoud Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Science College of Computer Science and Information TechnologyJazan UniversityJazanSaudi Arabia

Social Media such as Facebook plays a substantial role in virtual com-munities by sharing ideas and ideologies among different populations over *** interaction analysis aids in deﬁning people’s emotions and aids in assessing public attitudes,towards different issues such as violence against women and *** this paper,we proposed an Arabic language prediction model to identify the issue of Violence-Induced Stress in social *** searched for Arabic posts of many countries through Facebook application programming interface(API).We discovered that the stress state of a battered woman is usually related to her friend’s stress states on *** applied a large real database from Facebook platforms to analytically investigate the correlation of violence-induced stress states and the victim interactions on social *** extracted a set of tex-tual,spatial,and interaction attributes from various ***,we are proposing a hybrid model–an interaction graph model incorporated in a deep learning neural model to leverage post content and interaction data for vio-lence-induced stress *** depict that our proposed hybrid mod-el can enhance the prediction performance by 10%in ***,considering the user interaction information can learn an interesting phenomenon,where,the sparse social interactions of violence-induced stress stressed victims is higher by around 15%percent non-battered users,signifying that the structure of the friends of such victims is less connected than non-stressed users.

关键词： Arabic language analysis violence-induced stress detection hybrid model deep learning

Influences of nanoparticles and chain length on thermodynamic and electrical behavior of fluorine liquid crystals

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Chinese Physics B 2022年第10期31卷 410-416页

作者： Ines Ben Amor Lotfi Saadaoui abdulaziz N.alharbi Talal M.althagafi Taoufik Soltani Université Tunis El Manar Laboratoire de Physique de la Matiére Molle et de la Modélisation Electromagnétique2092 Tunis Physics Department College of ScienceTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia

Hydrogen-bonded polar nematic liquid crystal series with the general formula n OBAF(n = 7-12) is studied. The mesomorphic characterization is demonstrated through differential scanning calorimetry(DSC) and polarized optical microscopy(POM). The complexes with short alkyl chains(n = 7, 8) present a wide nematic range and monotropic smectic F mesophase, whereas the longer alkyl chain(n = 10-12) analogues show high melting and low clearing mesomorphic liquid crystals. The thermal range of the mesophase and the birefringence increase with chain length decreasing. Furthermore, the effect of the nanoparticles(LiNbO_(3)) on the thermal and the electrical behavior of 8OBAF are investigated. The presence of LiNbO_(3) nanoparticles increases the conductivity and reduces the resistivity of the complex.

关键词： fluorine liquid crystal polar nematic ferroelectric nanoparticles thermal stability dielectric behavior

Timing of Elective Repeat Cesarean Delivery at 38 Weeks versus 39 Weeks: Rate of Spontaneous Onset of Labor before Planned Cesarean Section and Impact on Maternal Outcome: A Retrospective Cohort Study

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Open Journal of Obstetrics and Gynecology 2023年第3期13卷 550-565页

作者： Amal Radi al Somairi Wafa abdulaziz Bedaiwi Yaser Abdulkarim Faden King abdulaziz Medical City Jeddah KSA

Background: The timing of elective repeat cesarean delivery at 38 weeks versus 39 weeks is still a debatable subject, both regarding maternal and neonatal outcomes. In the Saudi context, there is lack of local data to aid decision-making regarding the timing of elective repeat cesarean delivery. Objectives: To estimate the rate of spontaneous onset of labor before the planned gestational age for repeat cesarean section in women who were booked at gestational age of (39 0/7 - 39 6/7) weeks (W39) versus (38 0/7 - 38 6/7) weeks (W38) and to compare the rate of maternal composite outcome between these groups. Design: Retrospective cohort. Setting: This study was conducted at King abdulaziz Medical City, Jeddah, KSA. Method: Delivery registry books were reviewed to identify all deliveries from 1 January 2014 to 31 December 2016 (3 years). all low-risk pregnant women who had 2 or more cesarean deliveries and who met the inclusion criteria were included. Results: A total of 440 women were included of whom 318 (72.3%) were planned for elective cesarean section at W38 gestational age and 122 women at W39 gestational age. Mothers planned at W39 had higher rate of emergency cesarean deliveries versus those planned at W38 (18.0% versus 10.4%, p = 0.030;RR = 13.06), most frequently due to early onset of contractions (16.4% versus 8.2%, p = 0.012;RR = 12.17) or cervical dilatation (11.6% versus 5.4%, p = 0.024, RR = 16.15). No difference in the incidence of individual or composite maternal complications was noted between the two groups. Mother’s age (OR 0.93, p = 0.018) and schedule date at W39 (OR = 1.94, p = 0.028) were independently associated with spontaneous onset of labor before the scheduled gestational age, while no association was found with parity, previous number of spontaneous vaginal deliveries, number of previous cesarean deliveries or interval from last cesarean delivery. Conclusion: Elective cesarean section scheduled at 39 weeks of gestation or beyond carries a h

关键词： Elective Cesarean Emergency Cesarean Repeat Cesarean Previous Cesarean Spontaneous Onset of Labor Maternal Outcome Neonatal Outcome Timing of Delivery Risk Factors

Cardiac Arrhythmia Disease Classifier Model Based on a Fuzzy Fusion Approach

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Computers, Materials & Continua 2023年第5期75卷 4485-4499页

作者： Fatma Taher Hamoud alshammari Lobna Osman Mohamed Elhoseny abdulaziz Shehab Eman Elayat College of Technological Innovation Zayed UniversityDubaiUAE Department of Information Systems College of Computer and Information SciencesJouf UniversitySakakaSaudi Arabia Department of Electronics and Communications Engineering Delta Higher Institute for Engineering&TechnologyMansouraEgypt College of Computing and Informatics University of SharjahSharjahUnited Arab Emirates Department of Information Systems Mansoura UniversityMansoura35516Egypt Department of Teacher Preparation Faculty of Specific EducationMansoura UniversityMansouraEgypt

Cardiac diseases are one of the greatest global health *** to the high annual mortality rates,cardiac diseases have attracted the attention of numerous researchers in recent *** article proposes a hybrid fuzzy fusion classification model for cardiac arrhythmia *** fusion model is utilized to optimally select the highest-ranked features generated by a variety of well-known feature-selection *** ensemble of classifiers is then applied to the fusion’s *** proposed model classifies the arrhythmia dataset from the University of California,Irvine into normal/abnormal classes as well as 16 classes of ***,at the preprocessing steps,for the miss-valued attributes,we used the average value in the linear attributes group by the same class and the most frequent value for nominal ***,in order to ensure the model optimality,we eliminated all attributes which have zero or constant values that might bias the results of utilized *** preprocessing step led to 161 out of 279 attributes(features).Thereafter,a fuzzy-based feature-selection fusion method is applied to fuse high-ranked features obtained from different heuristic feature-selection *** short,our study comprises three main blocks:(1)sensing data and preprocessing;(2)feature queuing,selection,and extraction;and(3)the predictive *** proposed method improves classification performance in terms of accuracy,F1measure,recall,and precision when compared to state-of-the-art *** achieves 98.5%accuracy for binary class mode and 98.9%accuracy for categorized class mode.

关键词： Cardiac arrhythmia preprocessing missing values classification model fusion