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Lived Experience of Sickle Cell Patients during and after Crisis

Open Journal of Nursing 2021年第4期11卷 219-229页

作者： Mudhar Mohammed al Adawi Hanan Said al Hamami fathiya suliman al harrasi Badriya Salim al Hinai Kamila al alawi Department of Nursing Royal Hospital MOH Muscat Oman Department of Nursing Rustaq Hospital MOH Rustaq Oman Oman College of Health Science South Batinah Oman WHO-Oman Muscat Oman

Aims and Objectives: To understand the lived experience and needs of patients with sickle cell disease during and two weeks after their crisis and identify the obstacles faced by patients while they are in the hospital. Background: although there is no specific data of a number of affected individuals with sickle cell disease in Oman based on their age, the majority of the Omani population are youth. This category of the population is either in their high school or working in the governmental or private sector in the country. When the most productive category of the population are getting frequently absent due to sickle cell crisis and complication of sickle cell crisis from their work, this leads to huge financial and human resource burden. Design: Phenomenology. Method: This qualitative descriptive research was conducted using face-to-face interviews based on an interview protocol. The interview protocol was developed by the authors based on a framework called domains of well-being. Twenty adult patients have been recruited for the interview after meeting inclusion criteria and were asked about their well-being and lived experience during sickle cell crisis. Authors used SRQR checklist in reporting the study. Results: Thirteen themes were identified related to patients’ lived experience and their well-being during sickle cell crisis. Patients reported physical, emotional, social, and spiritual alteration. Major themes that emerged are communication, medical team interpretation of genuine pain, Emotional disturbance during the crisis, What does this study contribute to the wider global clinical community? Nurses and doctors should use therapeutic communication when dealing with sickle cell patients. Nurses should establish rapport and trust with patients. In each health care setting, there should be a social worker to deal with patients with chronic illness social relationships bet

关键词： Sickle Cell Patients Lived Experience Phenomenology Face to Face Interview Well-Being of Patients

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Occupational health risks among healthcare workers during the COVID-19 pandemic in Saudi Arabia: preparing for the future pandemics

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Nursing Communications 2024年第2期8卷 1-5页

作者： Reham suliman al Kharyef Aisha ali al Harbi Mohammed Abdelhamied Genedy Mohamed K.M.Khalil suliman Mohamed al Eidi Ministry of Health Riyadh 13352Saudi Arabia Consultant Public Health and Research Development.Cairo 11728 Egypt

Background:This study aimed to assess the occupational risks encountered by Healthcare Workers(HCWs)in Saudi Arabia during the COVID-19 ***:A cross-sectional survey was carried out from May to October *** a multi-stage stratified random sampling technique,an online questionnaire was sent to the recruited HCWs,across Saudi ***:Of the 768 HCWs recruited,702 participated in the survey.A significant majority(over 80%)reported working beyond 8 hours ***-19 infection,confirmed via PCR,was identified in 25%of the ***,infection was significantly correlated with direct or close contact(p=0.0007).Psychological distress was reported by 81%,with anxiety being the most prevalent(33%),followed by stress(19%),depression(17%),and insomnia(12%).Around 20%experienced headaches post-PPE use,while 14%reported adverse skin reactions,predominantly allergy and dermatitis.A concerning one-third of respondents reported exposure to ***:High infection rate,physical and psychological risks among HCWs especially those in direct contact with patients,reflect the need for enhancing the entirety of outbreak preparedness and response,specifically *** surveillance system,is crucial to adequately monitor and support HCWs during pandemic scenarios.

关键词： COVID-19 pandemic healthcare worker risk Saudi Arabia

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Location-Aware Personalized Traveler Recommender System(LAPTA)Using Collaborative Filtering KNN

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Computers, Materials & Continua 2021年第11期69卷 1553-1570页

作者： Mohanad al-Ghobari Amgad Muneer suliman Mohamed Fati School of Information Technology Asia Pacific UniversityKuala Lumpur57000Malaysia Department of Computer and Information Sciences Universiti Teknologi PETRONASSeri Iskandar32160Malaysia Department of Information Systems Prince Sultan UniversityRiyadh11586Saudi Arabia

Many tourists who travel to explore different cultures and cities worldwide aim to find the best tourist sites,accommodation,and food according to their *** objective makes it harder for tourists to decide and plan where to go and what to *** from hiring a local guide,an option which is beyond most travelers’budgets,the majority of sojourners nowadays use mobile devices to search for or recommend interesting sites on the basis of user ***,this work utilizes the prevalent recommender systems and mobile app technologies to overcome this ***,this study proposes location-aware personalized traveler assistance(LAPTA),a system which integrates user preferences and the global positioning system(GPS)to generate personalized and location-aware *** integration will enable the enhanced recommendation of the developed scheme relative to those from the traditional recommender systems used in customer ***,LAPTA separates the data obtained from Google locations into name and category *** the data separation,the system fetches the keywords from the user’s input according to the user’s past research *** proposed system uses the K-Nearest algorithm to match the name and category tags with the user’s input to generate personalized *** system also provides suggestions on the basis of nearby popular attractions using the Google point of interest feature to enhance system *** experimental results showed that LAPTA could provide more reliable and accurate recommendations compared to the reviewed recommendation applications.

关键词： LAPTA recommender system KNN collaborative filtering users’preference mobile application location awareness

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Changing patterns of hepatitis A prevalence within the Saudi population over the last 18 years

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World Journal of Gastroenterology 2008年第48期14卷 7371-7375页

作者： Faleh al Faleh suliman al Shehri Saleh al Ansari Mohammed al Jeffri Yaqoub al Mazrou Ahmad Shaffi Ayman A Abdo Department of Medicine College of Medicine King Saud University Ministry of Education Ministry of Health Department of Community Medicine College of Medicine King Saud University

AIM： To determine the seroprevalence of Hepatitis A （HAV） amongst Saudi children and compare it with previously reported prevalence data from the same population. METHODS： A total of 1357 students were randomly selected between the ages of 16 and 18 years （689 males and 668 females） from three different regions of Saudi Arabia （Madinah, AI-Qaseem, and Aseer） and tested for ***： The overall prevalence of anti-HAV-IgG among the study population was 18.6%. There was no difference between males and females but there was a significant difference in the seroprevalence （P = 0.0001） between the three different regions, with Madinah region showing the highest prevalence （27.4%）. When classified according to socioeconomic status, lower class students had a prevalence of 36.6%, lower middle class 16.6%, upper middle class 9.6%, and upper class 5.9% （P = 0.0001）. Comparing the current study results with those of previous studies in 1989 and 1997 involving the same population, there was a marked reduction in the overall prevalence of HAV from 52% in 1989, to 25% in 1997, to 18.6% in 2008 （P 〈 0.0001）.CONCLUSION： Over the last 18 years, there has been a marked decline in the prevalence of HAV in Saudi children and adolescents. The current low prevalence rates call for strict adherence to vaccination policies in high-risk patients and raises the question of a universal HAV vaccination program.

关键词： Hepatitis A Saudi Arabia Epidemiology Prevalence Serology

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Effects of a low-radiotoxicity uranium salt(uranyl acetate) on biochemical and hematological parameters of the catfish,Clarias gariepinus

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Chinese Journal of Oceanology and Limnology 2016年第1期34卷 109-117页

作者： Khalid.A.al-GHANIM Zubair AHMAD Hmoud F.al-Kahem al-BalAWI Fahad al-MISNED Shahid MABOOB El-Amin M.suliman Department of Zoology College of ScienceP.O.Box 2455King Saud University

Specimens of Clarias gariepinus were treated with lethal(70,75,80,85,90,and 95 mg/L) and sub-lethal concentrations(8,12 and 16 mg/L) of uranyl acetate,a low-radiotoxicity uranium salt. The LC 50 value was registered as 81.45 mg/L. The protein and glycogen concentrations in liver and muscles were decreased in the fish exposed to sub-lethal concentrations. The red blood cell(RBC) and white blood cell(WBC) counts,haemoglobin(Hb) concentration and haematocrit(Hct) values were decreased. Different blood indices like mean corpuscular volume(MCV),mean corpuscular haemoglobin(MCH) and mean corpuscular haemoglobin concentration(MCHC) were negatively affected. Level of plasma glucose was elevated whereas protein was decreased. The level of calcium concentration(Ca) was declined in the blood of exposed fish whereas magnesium(Mg) remains unchanged. The activity level of glutamic-oxaloacetic transaminase(GOT) and glutamic-pyruvic transaminase(GPT) was elevated in exposed fish. These effects were more pronounced in the last period of exposure and in higher concentrations. Results of the present study indicate that uranyl acetate has adverse effects on C larias gariepinus and causes changes in the biochemical and hematological parameters of the fish.

关键词： Clarias gariepinus uranyl acetate sub-lethal concentration biochemical and haematological parameters

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An Intelligent HealthCare Monitoring Framework for Daily Assistant Living

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Computers, Materials & Continua 2022年第8期72卷 2597-2615页

作者： Yazeed Yasin Ghadi Nida Khalid suliman A.alsuhibany Tamara al Shloul Ahmad Jalal Jeongmin Park Department of Computer Science and Software Engineering Al Ain UniversityAl Ain15551UAE Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Humanities and Social Science Al Ain UniversityAl Ain15551UAE Department of Computer Engineering Korea Polytechnic UniversitySiheung-siGyeonggi-do237Korea

Human Activity Recognition(HAR)plays an important role in life care and health monitoring since it involves examining various activities of patients at homes,hospitals,or ***,the proposed system integrates Human-Human Interaction(HHI)and Human-Object Interaction(HOI)recognition to provide in-depth monitoring of the daily routine of *** propose a robust system comprising both RGB(red,green,blue)and depth *** particular,humans in HHI datasets are segmented via connected components analysis and skin detection while the human and object in HOI datasets are segmented via saliency *** track the movement of humans,we proposed orientation and thermal features.A codebook is generated using Linde-Buzo-Gray(LBG)algorithm for vector ***,the quantized vectors generated from image sequences of HOI are given to Artificial Neural Network(ANN)while the quantized vectors generated from image sequences of HHI are given to K-ary tree hashing for *** are two publicly available datasets used for experimentation on HHI recognition:Stony Brook University(SBU)Kinect interaction and the University of Lincoln’s(UoL)3D social activity ***,two publicly available datasets are used for experimentation on HOI recognition:Nanyang Technological University(NTU)RGB-D and Sun Yat-Sen University(SYSU)3D HOI *** results proved the validity of the proposed system.

关键词： Artificial neural network human-human interaction humanobject interaction k-ary tree hashing machine learning

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Self-Care Assessment for Daily Living Using Machine Learning Mechanism

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Computers, Materials & Continua 2022年第7期72卷 1747-1764页

作者： Mouazma Batool Yazeed Yasin Ghadi suliman A.alsuhibany Tamara al Shloul Ahmad Jalal Jeongmin Park Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Computer Science and Software Engineering Al Ain UniversityAl Ain15551UAE Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Humanities and Social Science Al Ain UniversityAl Ain15551UAE Department of Computer Engineering Korea Polytechnic University237 Sangidaehak-ro Siheung-siGyeonggi-do15073Korea

Nowadays,activities of daily living(ADL)recognition system has been considered an important field of computer *** and optical sensors are widely used to assess the daily living activities in healthy people and people with certain *** conventional ADL utilizes RGB optical sensors but an RGB-D camera with features of identifying depth(distance information)and visual cues has greatly enhanced the performance of activity *** this paper,an RGB-D-based ADL recognition system has been ***,human silhouette has been extracted from the noisy background of RGB and depth images to track human movement in a *** on these silhouettes,full body features and point based features have been extracted which are further optimized with probability based incremental learning(PBIL)***,random forest classifier has been used to classify activities into different *** n-fold crossvalidation scheme has been used to measure the viability of the proposed model on the RGBD-AC benchmark dataset and has achieved an accuracy of 92.71%over other state-of-the-art methodologies.

关键词： Angular geometric features decision tree classifier human activity recognition probability based incremental learning ridge detection

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Pedestrian Physical Education Training Over Visualization Tool

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Computers, Materials & Continua 2022年第11期73卷 2389-2405页

作者： Tamara al Shloul Israr Akhter suliman A.alsuhibany Yazeed Yasin Ghadi Ahmad Jalal Jeongmin Park Department of Humanities and Social Science Al Ain UniversityAl Ain15551UAE Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Computer Science and Software Engineering Al Ain UniversityAl Ain15551UAE Department of Computer Engineering Korea Polytechnic UniversitySiheung-siGyeonggi-do237Korea

E-learning approaches are one of the most important learning platforms for the learner through electronic *** study techniques are useful for other groups of learners such as the crowd,pedestrian,sports,transports,communication,emergency services,management systems and education sectors.E-learning is still a challenging domain for researchers and developers to find new trends and advanced tools and *** of them are currently working on this domain to fulfill the requirements of industry and the *** this paper,we proposed a method for pedestrian behavior mining of aerial data,using deep flow feature,graph mining technique,and convocational neural *** input data,the state-of-the-art crowd activity University of Minnesota(UMN)dataset is adopted,which contains the aerial indoor and outdoor view of the pedestrian,for simplification of extra information and computational cost reduction the pre-processing is *** flow features are extracted to find more accurate ***,to deal with repetition in features data and features mining the graph mining algorithm is applied,while Convolution Neural Network(CNN)is applied for pedestrian behavior *** proposed method shows 84.50%of mean accuracy and a 15.50%of error ***,the achieved results show more accuracy as compared to state-ofthe-art classification algorithms such as decision tree,artificial neural network(ANN).

关键词： Artificial intelligence behavior mining convolution neural network(CNN) deep flow e-learning environment

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Improving the Ambient Intelligence Living Using Deep Learning Classifier

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Computers, Materials & Continua 2022年第10期73卷 1037-1053页

作者： Yazeed Yasin Ghadi Mouazma Batool Munkhjargal Gochoo suliman Aalsuhibany Tamara al Shloul Ahmad Jalal Jeongmin Park Department of Computer Science and Software Engineering Al Ain UniversityAl Ain15551UAE Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Computer Science and Software Engieering United Arab Emirates UniversityAl Ain15551UAE Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Humanities and Social Science Al Ain UniversityAl Ain15551UAE Department of Computer Engineering Tech University of KoreaGyeonggi-do15073Korea

Over the last decade,there is a surge of attention in establishing ambient assisted living(Aal)solutions to assist individuals live *** a social and economic perspective,the demographic shift toward an elderly population has brought new challenges to today’s *** can offer a variety of solutions for increasing people’s quality of life,allowing them to live healthier and more independently for *** this paper,we have proposed a novel Aal solution using a hybrid bidirectional long-term and short-term memory networks(BiLSTM)and convolutional neural network(CNN)*** first pre-processed the signal data,then used timefrequency features such as signal energy,signal variance,signal frequency,empirical mode,and empirical mode *** convolutional neural network-bidirectional long-term and short-term memory(CNN-biLSTM)classifier with dimensional reduction isomap algorithm was then used to select ideal *** assessed the performance of our proposed system on the publicly accessible human gait database(HuGaDB)benchmark dataset and achieved an accuracy rates of 93.95 percent,*** reveal that hybrid method gives more accuracy than single classifier in Aal *** suggested system can assists persons with impairments,assisting carers and medical personnel.

关键词： Ambient assisted living convolutional neural network dimensionality reduction frequency-time features wearable technology

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An Intelligent Framework for Recognizing Social Human-Object Interactions

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Computers, Materials & Continua 2022年第10期73卷 1207-1223页

作者： Mohammed alarfaj Manahil Waheed Yazeed Yasin Ghadi Tamara al Shloul suliman A.alsuhibany Ahmad Jalal Jeongmin Park Department of Electrical Engineering College of EngineeringKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Computer Science and Software Engineering Al Ain UniversityAl Ain15551UAE Department of Humanities and Social Science Al Ain UniversityAl Ain15551UAE Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Computer Engineering Tech University of KoreaSiheung-si15073Gyeonggi-doKorea

Human object interaction(HOI)recognition plays an important role in the designing of surveillance and monitoring systems for healthcare,sports,education,and public *** involves localizing the human and object targets and then identifying the interactions between ***,it is a challenging task that highly depends on the extraction of robust and distinctive features from the targets and the use of fast and efficient ***,the proposed system offers an automated body-parts-based solution for HOI *** system uses RGB(red,green,blue)images as input and segments the desired parts of the images through a segmentation technique based on the watershed ***,a convex hullbased approach for extracting key body parts has also been *** identifying the key body parts,two types of features are ***,the entire feature vector is reduced using a dimensionality reduction technique called t-SNE(t-distributed stochastic neighbor embedding).Finally,a multinomial logistic regression classifier is utilized for identifying class labels.A large publicly available dataset,MPII(Max Planck Institute Informatics)Human Pose,has been used for system *** results prove the validity of the proposed system as it achieved 87.5%class recognition accuracy.

关键词： Dimensionality reduction human-object interaction key point detection machine learning watershed segmentation

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