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Can training extend current guidelines for cochlear implant candidacy?

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Neural Regeneration Research 2015年第5期10卷 718-720页

作者： amal Isaiah Douglas E.h.hartley Department of Otorhinolaryngology-head and Neck Surgery University of Maryland School of Medicine National Institute for h.alth Research (NIhR) Nottingham Hearing Biomedical Research Unit Otology and hearing Group Division of Clinical NeuroscienceSchool of MedicineUniversity of Nottingham Medical Research Council (MRC) Institute of hearing Research

Since their introduction in the 1960s, cochlear implants （CIS） have undergone several transformations, ulti- mately positioning themselves as the best-performing neural prosthesis available today. They have also been recognized as a unique tool for studying the potential protective effects of patterned electrical stimulation on the developing auditory system, with results from animal models often changing the manner in which CIs are used clinically to deliver auditory information to the brain （Moore and Shannon, 2009）. From the development of the first successful commercial single-channel device, they have evolved into multi-channel devices that are part of the national h.alth programmes of several coun- tries. From the limited speech information provided by the early, rudimentary cochlear implants, these devices are now in a position to deliver intelligible speech infor- mation to the auditory system, largely due to advances in signal processing. Concerted efforts from several dis- ciplines, including engineering, acoustics, neurobiology and otolaryngology have ensured that the continued development of CI technology has resulted in signifi- cant benefits to individuals with profound sensorineural hearing loss.

关键词： Can training extend current guidelines for cochlear implant candidacy CI

A Deep Real-Time Fire Prediction Parallel D-CNN Model on UDOO BOLT V8

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Computers, Materials & Continua 2022年第12期73卷 6237-6252页

作者： amal h.alharbi hanan A.hosni Mahmoud Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

hazardous incidences have significant influences on human life,and fire is one of the foremost causes of such hazard in most *** prediction and classification model from a set of fire images can decrease the risk of losing human lives and *** promotion of fire emergency can be of great ***,construction of these prediction models is relevant and *** article proposes an operative fire prediction model that depends on a prediction unit embedded in the processor UDOO BOLT V8 hardware to predict fires in real time.A fire image database is improved to enhance the images quality prior to classify them as either fire or *** proposed deep learning-based Very Deep Convolutional Networks Visual Geometry Group(VGG-16)model(Parallel VGG-16)is an enhanced version of the VGG-16 model,by incorporating parallel convolution layers and a fusion module for better *** experimental results validate the performance of the Parallel VGG-16 which achieves an accuracy of 97%,compared to the compared state-of-the-art ***,we integrate the prediction module into a UDOO BOLT V8 computer,which precisely controlled the fire alarm so that it can cautious people from fire in real *** this paper we propose a complete fire prediction model using a camera and the UDOO BOLT V8 embedded *** experiments validate the effectiveness and applicability of the proposed fire model.

关键词： Fire prediction UDOO BOLT V8 deep learning

Deep Learning Prediction Model for NiCralY Diffusion Barrier Thickness for Tungsten Wires

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Computers, Materials & Continua 2022年第12期73卷 5755-5769页

作者： amal h.alharbi hanan A.hosni Mahmoud Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

In the last decades,technology has used Copper for IC interconnect and it has been the best material used in the wire ***,Copper is now showing inefficiency as downscaling is getting *** research starts to show Tungsten(W)as a possible replacement,for its better downsizing *** scaling-down of interconnects dimension has to be augmented with thin diffusion *** is crucial to subdue tungsten diffusion in the nickel-based thermal spray Flexicord(NiCralY)coating ***,diffusion barriers with thicknesses less than 4.3 nm do not to execute *** the introduction of two dimensional layers,hexagonal boron has been recommended as a substitute for Tungsten diffusion barrier layers with thicknesses less than 1.5 Nano meters(nm).Nevertheless,vacancies flaws may develop into a Tungsten dissemination path,which is a problematic issue in the manufacturing of diffusion *** energy layer density,of Tungsten atom diffusion via a di-vacancy in NiCralY,is computed by density functions *** has complex energy barrier which is thicker than other materials such as *** is due to the sturdier contact and charge variance of NI and Cr in ***,we utilize the energy barriers of several vacancy constructions and produce a dataset to be employed in the proposed 3-imensional deep learning model(3D-DNN).Our trained deep learning neural model can predict the energy barrier of Tungsten diffusion through arbitrarily configured NiCralY with accuracy greater than 98.4%in 5×5 *** results generate directors on selecting barriers through energy computation.

关键词： Deep learning tungsten NiCralY thickness barrier

An Optimal Big Data Analytics with Concept Drift Detection on high-Dimensional Streaming Data

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Computers, Materials & Continua 2021年第9期68卷 2843-2858页

作者： Romany F.Mansour Shaha al-Otaibi amal al-Rasheed hanan aljuaid Irina V.Pustokhina Denis A.Pustokhin Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga72511Egypt Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Entrepreneurship and Logistics Plekhanov Russian University of EconomicsMoscow117997Russia Department of Logistics State University of ManagementMoscow109542Russia

Big data streams started becoming ubiquitous in recent years,thanks to rapid generation of massive volumes of data by different *** is challenging to apply existing data mining tools and techniques directly in these big data *** the same time,streaming data from several applications results in two major problems such as class imbalance and concept *** current research paper presents a new Multi-Objective Metaheuristic Optimization-based Big Data Analytics with Concept Drift Detection(MOMBD-CDD)method on high-Dimensional Streaming *** presented MOMBD-CDD model has different operational stages such as pre-processing,CDD,and ***-CDD model overcomes class imbalance problem by Synthetic Minority Over-sampling Technique(SMOTE).In order to determine the oversampling rates and neighboring point values of SMOTE,Glowworm Swarm Optimization(GSO)algorithm is ***,Statistical Test of Equal Proportions(STEPD),a CDD technique is also ***,Bidirectional Long Short-Term Memory(Bi-LSTM)model is applied for *** order to improve classification performance and to compute the optimum parameters for Bi-LSTM model,GSO-based hyperparameter tuning process is carried *** performance of the presented model was evaluated using high dimensional benchmark streaming datasets namely intrusion detection(NSL KDDCup)dataset and ECUE spam *** extensive experimental validation process confirmed the effective outcome of MOMBD-CDD *** proposed model attained high accuracy of 97.45%and 94.23%on the applied KDDCup99 Dataset and ECUE Spam datasets respectively.

关键词： Streaming data concept drift classification model deep learning class imbalance data

MIoT Based Skin Cancer Detection Using Bregman Recurrent Deep Learning

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Computers, Materials & Continua 2022年第12期73卷 6253-6267页

作者： Nithya Rekha Sivakumar Sara Abdelwahab Ghorashi Faten Khalid Karim Eatedal alabdulkreem amal al-Rasheed Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia

Mobile clouds are the most common medium for aggregating,storing,and analyzing data from the medical Internet of Things(MIoT).It is employed to monitor a patient’s essential h.alth signs for earlier disease diagnosis and *** the various disease,skin cancer was the wide variety of cancer,as well as enhances the endurance *** recent years,many skin cancer classification systems using machine and deep learning models have been developed for classifying skin tumors,including malignant melanoma(MM)and other skin ***,accurate cancer detection was not performed with minimum time *** order to address these existing problems,a novel Multidimensional Bregman Divergencive Feature Scaling Based Cophenetic Piecewise Regression Recurrent Deep Learning Classification(MBDFS-CPRRDLC)technique is introduced for detecting cancer at an earlier *** MBDFS-CPRRDLC performs skin cancer detection using different layers such as input,hidden,and output for feature selection and *** patient information is composed of *** patient information was stored in mobile clouds server for performing predictive *** collected data are sent to the recurrent deep learning *** the first hidden layer,the feature selection process is carried out using the Multidimensional Bregman Divergencive Feature Scaling technique to find the significant features for disease identification resulting in decreases time *** by,the disease classification is carried out in the second hidden layer using cophenetic correlative piecewise regression for analyzing the testing and training *** process is repeatedly performed until the error gets *** this way,disease classification is accurately performed with higher *** evaluation is carried out for factors namely Accuracy,precision,recall,F-measure,as well as cancer detection time,by the amount of patient *** observed result confirms that the pr

关键词： MIoT skin cancer detection recurrent deep learning classification multidimensional bregman divergencive scaling cophenetic correlative piecewise regression

Examining the Types and Consequences of Female Genital Mutilation in Somalia: A Cross-Sectional Study on the Burden and Impact of Acute and Long-Term Complications

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Open Journal of Obstetrics and Gynecology 2024年第9期14卷 1322-1334页

作者： Rahma Yusuf haji Mohamud Nur Adam Mohamed Mohamed Yaqub hassan Khadija Yusuf ali Marian Muse Osman amal Nor ali Ifrah Adan hilowle Iftin Mohamed Osman Mohamed Farah Yusuf Mohamud Department of Nursing Mogadishu Somali Turkiye Recep Tayyip Erdogan Training and Research Hospital Mogadishu Somalia Department of Psychiatry and Behavioral Sciences Mogadishu Somali Turkiye Recep Tayyip Erdogan Training and Research Hospital Mogadishu Somalia Department of Pediatric Mogadishu Somali Turkiye Recep Tayyip Erdogan Training and Research Hospital Mogadishu Somalia Department of Obstetrics and Gynecology Mogadishu Somali Turkiye Recep Tayyip Erdogan Training and Research Hospital Mogadishu Somalia Research Department National Institute of Health Mogadishu Somalia Department of Pulmonology Mogadishu Somali Turkiye Recep Tayyip Erdogan Training and Research Hospital Mogadishu Somalia Department of Emergency Medicine Mogadishu Somali Turkiye Recep Tayyip Erdogan Training and Research Hospital Mogadishu Somalia

Background: In Africa, female genital mutilation (FGM) is a widespread and harmful practice, with Somalia having the highest incidence at 98%. This practice has severe and long-lasting physical and mental h.alth consequences. The aim of the study was to evaluate the different types of FGM;immediate and long-term complications associated with the practice, and identify factors related to its prevalence. Method: In a one-year cross-sectional hospital-based study, data were collected from females aged 18 - 50 with a history of FGM. Face-to-face semi-structured questionnaires were used for data collection. Data analysis was performed using SPSS version 26, utilizing univariate and bivariate analyses to identify correlations between variables, which were presented in tables. Results: In a study involving 255 female participants, 65.5% were between 18 and 30 years old. The majority (82.7%) were married, while 47.1% were illiterate. FGM cases were more prevalent in rural areas (61.6%). Among the participants, 45.1% were employed. Type 3 FGM was the most common (44.3%), followed by Type 2 (32.2%) and Type 1 (23.9%). In terms of short-term complications experienced by circumcised women, the most common were bleeding, reported by 29.8% of participants, followed by infection (25.1%), and urinary retention (19.2%). Among the long-term complications observed, recurrent vaginal infections were the most prevalent, affecting 29.8% of the surveyed females. This was episiotomy during delivery (22.3%) and genital scarring (10.2%). Conclusion: The study reveals that Type 3 FGM is highly prevalent among the surveyed females, contributing to an increased risk of recurrent vaginal infections, prolonged second stage of labor, higher likelihood of episiotomy during delivery, and genital scarring. These findings emphasize the urgent need for effective preventive strategies and implementation from both international and local organizations to eliminate the harmful practice of FGM.

关键词： Female Genital Mutilation Women Obstetrics and Gynecology Somalia

Promising hollow multi-shelled structures:discovering the temporal-spatial ordering

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National Science Review 2020年第11期7卷 1763-1764页

作者： Rose amal School of Chemical Engineering University of New South Wales

harvesting incident photons is the first step in a photo-induced process such as photocatalysis, photovoltaics or photodetection, which crucially governs the process performance. Unfortunately,extensive energy losses are observed in this step due to severe surface reflections and limited optical paths of the shortwavelength light [1]. Thus,

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Entropy Bayesian Analysis for the Generalized Inverse Exponential Distribution Based on URRSS

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Computers, Materials & Continua 2021年第12期69卷 3795-3811页

作者： Amer I.al-Omari amal S.hassan heba F.Nagy Ayed R.A.al-Anzi Loai alzoubi Faculty of Science Department of MathematicsAl al-Bayt UniversityMafraq25113Jordan Faculty of Graduate Studies for Statistical Research Cairo UniversityGiza12613Egypt Department of Mathematics College of Science and Human Studies at Hotat SudairMajmaah UniversityMajmaah11952Saudia Arabia

This paper deals with the Bayesian estimation of Shannon entropy for the generalized inverse exponential *** that the observed samples are taken from the upper record ranked set sampling(URRSS)and upper record values(URV)*** of Bayesian estimators are derived depending on a gamma prior distribution considering the squared error,linear exponential and precautionary loss functions,in addition,we obtain Bayesian credible *** random-walk Metropolis-hastings algorithm is handled to generate Markov chain Monte Carlo samples from the posterior ***,the behavior of the estimates is examined at various record *** output of the study shows that the entropy Bayesian estimates under URRSS are more convenient than the other estimates under URV in the majority of the ***,the entropy Bayesian estimates perform well as the number of records *** obtained results validate the usefulness and efficiency of the URV *** data is analyzed for more clarifying purposes which validate the theoretical results.

关键词： Shannon entropy generalized inverse exponential distribution Bayesian estimators loss function ranked set sampling markov chain

Progression of diethylnitrosamine-induced hepatic carcinogenesis in carnitine-depleted rats

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World Journal of Gastroenterology 2009年第11期15卷 1373-1380页

作者： Salim S al-Rejaie Abdulaziz M aleisa Abdulaziz A al-Yahya Saleh A Bakheet Abdulmalik alsheikh amal G Fatani Othman A al-Shabanah Mohamed M Sayed-Ahmed Department of Pharmacology College of PharmacyKing Saud UniversityPO Box 2457Kingdom of Saudi Arabia Department of Pathology College of MedicineKing Saud UniversityPO Box 2457 Kingdom of Saudi Arabia

AIM:To investigate whether carnitine deficiency is a risk factor during the development of diethylnitrosamine (DENA)-induced hepatic carcinogenesis. METhODS:A total of 60 male Wistar albino rats were divided into six groups with 10 animals in each *** in group 1(control group)received a single intraperitoneal(i.p.)injection of normal saline. Animals in group 2(carnitine-supplemented group) were given L-carnitine(200 mg/kg per day)in drinking water for 8 *** in group 3(carnitine-depleted group)were given D-carnitine(200 mg/kg per day)and mildronate(200 mg/kg per day)in drinking water for 8 *** in group 4(DENA group)were injected with a single dose of DENA(200 mg/kg,i.p.)and 2 wk later received a single dose of carbon tetrachloride(2 mL/kg) by gavage as 1:1 dilution in corn *** in group 5(DENA-carnitine depleted group)received the same treatment as group 3 and group *** in group 6 (DENA-carnitine supplemented group)received the same treatment as group 2 and group ***:Administration of DENA resulted in a significant increase in alanine transaminase(alT), gamma-glutamyl transferase(G-GT),alkaline phosphatase(alP),total bilirubin,thiobarbituric acid reactive substances(TBARS)and total nitrate/ nitrite(NOx)and a significant decrease in reduced glutathione(GSh),glutathione peroxidase(GShPx), catalase(CAT)and total carnitine content in liver *** the carnitine-depleted rat model,DENA induced a dramatic increase in serum alT,G-GT,alP and total bilirubin,as well as a progressive reduction in total carnitine content in liver ***, L-carnitine supplementation resulted in a complete reversal of the increase in liver enzymes,TBARS and NOx,and a decrease in total carnitine,GSh,GShPx, and CAT induced by DENA,compared with the control *** examination of liver tissues confirmed the biochemical data,where L-carnitine prevented DENA-induced hepatic carcinogenesis while D-carnitine-mildronate aggravated DENA-

关键词： Carnitine deficiency D-carnitine L-carnitine Diethylnitrosamine hepatic carcinogenesis