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| 1 | Advanced Reproductive Age and Fertility显示文摘 | Kimberly Liu Allison Case Anthony P. Cheung Sony Sierra Saleh AlAsiri Belina Carranza-Mamane Allison Case Cathie Dwyer James Graham Jon Havelock Robert Hemmings Francis Lee Kimberly Liu Ward Murdock Vyta Senikas Tannys D.R. Vause Benjamin Chee-Man Wong | 2011 | International Journal of Gynecology and Obstetrics2011，，1： | 1 |
| 2 | Skeletal muscle metastasis as an initial presentation of follicular thyroid carcinoma: a case report and a review of the literature 显示文摘 | Tunio M A Alasiri M Riaz K | 2013 | Case Rep Endocrinol2013，2013，19： | 1 |
| 3 | Renal cell carcinoma meta- static to thyroid gland, presenting like anaplastic carcinoma of ttly- roid显示文摘 | Rias K Tunio MA Alasiri M el al | 2013 | Case Rep U rol2013，2013，65： | 1 |
| 4 | Determining 2D Positions of sensor network nodes for temperature distribution measurement显示文摘 | OHYAMA S ALASIRY A H TAKAYAMA J | 2007 | Sensors & Actuators A2007，135，1： | 1 |
| 5 | Renal cell carcinoma metastatic to thyroid gland, presenting like anaplastic carcinoma of thyroid显示文摘 | Riaz K Tunio MA Alasiri M | 2013 | Case Rep Uro12013，，： | 1 |
| 6 | Comual polyps of the fallopian tube are associated with endometriosis and anovulation显示文摘 | Alasiri S A Ghahremani M McComb P F | 2011 | Obstet Gynecol Int2011，56，5： | 1 |
| 7 | Age, Body mass index, And number of previous trials: are they prognosticators of intra-uterine-insemination for infertility treatment 显示文摘 | Isa AM Abu-rafea B Alasiri SA | 2014 | Fertil Steril2014，8，3： | 1 |
| 8 | Renal cell carcinoma meta- static to thyroid gland, presenting like anaplastic carcinoma of thy- roid显示文摘 | Riaz K Tunio MA Alasiri M | 2013 | Case Rep Urol2013，2013，65： | 1 |
| 9 | Accurate diagnosis as a prognostic factor in intrauterine insemination treatment of infertile saudi patients 显示文摘 | Isa AM1 Abu- rafea B Alasiri SA | 2014 | Reprod lnfertil2014，15，4： | 1 |
| 10 | A Trailblazing Framework of Security Assessment for Traffic Data Management显示文摘Connected and autonomous vehicles are seeing their dawn at this moment.They provide numerous benefits to vehicle owners,manufacturers,vehicle service providers,insurance companies,etc.These vehicles generate a large amount of data,which makes privacy and security a major challenge to their success.The complicated machine-led mechanics of connected and autonomous vehicles increase the risks of privacy invasion and cyber security violations for their users by making them more susceptible to data exploitation and vulnerable to cyber-attacks than any of their predecessors.This could have a negative impact on how well-liked CAVs are with the general public,give them a poor name at this early stage of their development,put obstacles in the way of their adoption and expanded use,and complicate the economic models for their future operations.On the other hand,congestion is still a bottleneck for traffic management and planning.This research paper presents a blockchain-based framework that protects the privacy of vehicle owners and provides data security by storing vehicular data on the blockchain,which will be used further for congestion detection and mitigation.Numerous devices placed along the road are used to communicate with passing cars and collect their data.The collected data will be compiled periodically to find the average travel time of vehicles and traffic density on a particular road segment.Furthermore,this data will be stored in the memory pool,where other devices will also store their data.After a predetermined amount of time,the memory pool will be mined,and data will be uploaded to the blockchain in the form of blocks that will be used to store traffic statistics.The information is then used in two different ways.First,the blockchain’s final block will provide real-time traffic data,triggering an intelligent traffic signal system to reduce congestion.Secondly,the data stored on the blockchain will provide historical,statistical data that can facilitate the analysis of traffic conditions according to past behavior. | Abdulaziz Attaallah Khalil al-Sulbi Areej Alasiry Mehrez Marzougui Neha Yadav Syed Anas Ansar Pawan Kumar Chaurasia Alka Agrawal | 2023 | Intelligent Automation & Soft Computing2023，37，8： | 0 |
| 11 | Glaucoma among Saudi Arabian population:a scoping review显示文摘Despite its high risk of leading to permanent visual dysfunction,glaucoma remains underdiagnosed in primary care settings.About 11%of glaucoma patients in Saudi Arabia end up with bilateral blindness.This scoping review investigates and presents results on the glaucoma profile,including its prevalence,knowledge,attitude,and practice of Saudi Arabians towards the disease.An online search using four databases through online software(www.rayyan.ai)was performed to extract the relevant articles.Out of 76 records,21 articles were eligible for the analysis.All included studies were published between the years 2014 and 2022.Most studies were in Riyadh city,followed by Jeddah.All participants(n=11388)were adults>18 years old,and male participants were generally higher than females.The findings showed poor knowledge of glaucoma among the general population,while the knowledge among glaucoma patients was acceptable.The attitude was positive,while the compliance and practice were fair.More educational programs about glaucoma,its risk to the eyes,and the overall quality of life are highly recommended. | Ismail Abuallut Mohammed Khalid Arishi Ahmed Mustafa Albarnawi Sumayyah Ali Jafar Abdullah Mohammed Alamer Tahani Hassan Altubayqi Mohammed Ahmed Hadadi Mohand Abdullah Alasiri | 2023 | International Journal of Ophthalmology(English edition)2023，16，12： | 0 |
| 12 | CONTROL OF ILLICIT TRAFFICKING OF NUCLEAR MATERIAL USED FOR TERRORIST PURPOSES显示文摘 | Abdul- Wali Ajlouni Mohammed A. Al-Saad Alanoud Mosa Alasiri | 2014 | US-China Law Review2014，11，9： | 0 |
| 13 | Deep Transfer Learning Based Detection and Classification of Citrus Plant Diseases显示文摘Citrus fruit crops are among the world’s most important agricultural products,but pests and diseases impact their cultivation,resulting in yield and quality losses.Computer vision and machine learning have been widely used to detect and classify plant diseases over the last decade,allowing for early disease detection and improving agricultural production.This paper presented an automatic system for the early detection and classification of citrus plant diseases based on a deep learning(DL)model,which improved accuracy while decreasing computational complexity.The most recent transfer learning-based models were applied to the Citrus Plant Dataset to improve classification accuracy.Using transfer learning,this study successfully proposed a Convolutional Neural Network(CNN)-based pre-trained model(EfficientNetB3,ResNet50,MobiNetV2,and InceptionV3)for the identification and categorization of citrus plant diseases.To evaluate the architecture’s performance,this study discovered that transferring an EfficientNetb3 model resulted in the highest training,validating,and testing accuracies,which were 99.43%,99.48%,and 99.58%,respectively.In identifying and categorizing citrus plant diseases,the proposed CNN model outperforms other cuttingedge CNN model architectures developed previously in the literature. | Shah Faisal Kashif Javed Sara Ali Areej Alasiry Mehrez Marzougui Muhammad Attique Khan Jae-Hyuk Cha | 2023 | Computers, Materials & Continua2023，，7： | 0 |
| 14 | Security Test Case Prioritization through Ant Colony Optimization Algorithm显示文摘Security testing is a critical concern for organizations worldwide due to the potential financial setbacks and damage to reputation caused by insecure software systems.One of the challenges in software security testing is test case prioritization,which aims to reduce redundancy in fault occurrences when executing test suites.By effectively applying test case prioritization,both the time and cost required for developing secure software can be reduced.This paper proposes a test case prioritization technique based on the Ant Colony Optimization(ACO)algorithm,a metaheuristic approach.The performance of the ACO-based technique is evaluated using the Average Percentage of Fault Detection(APFD)metric,comparing it with traditional techniques.It has been applied to a Mobile Payment Wallet application to validate the proposed approach.The results demonstrate that the proposed technique outperforms the traditional techniques in terms of the APFD metric.The ACO-based technique achieves an APFD of approximately 76%,two percent higher than the second-best optimal ordering technique.These findings suggest that metaheuristic-based prioritization techniques can effectively identify the best test cases,saving time and improving software security overall. | Abdulaziz Attaallah Khalil al-Sulbi Areej Alasiry Mehrez Marzougui Mohd Waris Khan Mohd Faizan Alka Agrawal Dhirendra Pandey | 2023 | Computer Systems Science & Engineering2023，47，12： | 0 |
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