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Pneumonia Detection from Chest X-ray Images Based on Sequential Model
Alshehri, Asma,Alharbi, Bayan,Alharbi, Amirah International Journal of Computer ScienceNetwork S 2022 International journal of computer science and netw Vol.22 No.4
Pneumonia is a form of acute respiratory infection that affects the lungs. According to the World Health Organization, pneumonia is the leading cause of death for children worldwide. As a result, pneumonia was the top killer of children under the age of five years old in 2015, which is 15% of all deaths worldwide. In this paper, we used CNN model architectures to compare between the result of proposed a CNN method with VGG based model architecture. The model's performance in detecting pneumonia shows that the proposed model based on VGG can classify normal and abnormal X-rays effectively and more accurately than the proposed model used in this paper.
Integrating Technology into Mathematics Educationin the Saudi Context
( Alshehri Zafer F ) 한국수학교육학회 2014 수학교육 학술지 Vol.2014 No.1
This paper aimed to investigate technology integration into mathematics education in the Saudi context. To achieve that, a wide range of literature was critically reviewed, including research articles, books, government records, dissertations and web sites. As a result, technology has an impact on every aspect of modern life, its use considered as one of the most critical issues facing teacher education programs, and its progress has inevitably made a variety of new demands in all school disciplines such as mathematics. Consequently, mathematics curriculum and its components (objectives, content, teaching methods/ activities/aids, and evaluation/assessment styles) are changing. The integration of technology into mathematics education in Saudi environment is considered as one of the current issues under-investigation; and the term of integration is still a controversy for a great number of mathematics educators and teachers. In addition, recent studies have shown the need to better align mathematics teachers` preparation with the integration of technology in mathematics classrooms. In the light of findings, the paper recommended integrating technology into mathematics education, and suggested the topic itself can be searched further.
Alshehri, Abdulrahman Mohammed,Fenais, Mohammed Saeed International Journal of Computer ScienceNetwork S 2022 International journal of computer science and netw Vol.22 No.10
The prominence of IoTs (Internet of Things) and exponential advancement of computer networks has resulted in massive essential applications. Recognizing various cyber-attacks or anomalies in networks and establishing effective intrusion recognition systems are becoming increasingly vital to current security. MLTs (Machine Learning Techniques) can be developed for such data-driven intelligent recognition systems. Researchers have employed a TFDNNs (Tensor Flow Deep Neural Networks) and DCNNs (Deep Convolution Neural Networks) to recognize pirated software and malwares efficiently. However, tuning the amount of neurons in multiple layers with activation functions leads to learning error rates, degrading classifier's reliability. HTFDNNs ( Hybrid tensor flow DNNs) and MRNs (Modified Residual Networks) or Resnet CNNs were presented to recognize software piracy and malwares. This study proposes HTFDNNs to identify stolen software starting with plagiarized source codes. This work uses Tokens and weights for filtering noises while focusing on token's for identifying source code thefts. DLTs (Deep learning techniques) are then used to detect plagiarized sources. Data from Google Code Jam is used for finding software piracy. MRNs visualize colour images for identifying harms in networks using IoTs. Malware samples of Maling dataset is used for tests in this work.
Phishing Attacks on Cryptocurrency Traders in Arab States of The Gulf
Sawsan Alshehri,Reem Alhotaylah,Marwa Alyami,Abdullah Alghamdi,Mesfer Alrizq International Journal of Computer ScienceNetwork S 2024 International journal of computer science and netw Vol.24 No.8
With the great development of technology in all fields these days, including the financial field, people have gone into cryptocurrency trading, without prior knowledge or experience, which made them prey and coveted by hackers through phishing attacks. Therefore, we will study cases where people can be a victim of phishing because cryptocurrency occurs without an intermediary, such as banks and monetary institutions. It is a form of peer-to-peer transaction, physical wallets, and fake investing. This study aims to know the concept of a phishing attack on cryptocurrencies, and to measure the extent of peoples awareness of the security risks on these currencies. Previous literature will be reviewed, and a questionnaire will be published on traders who use cryptocurrency trading platforms, and then we collect data and analyze the answers provided, so that we can suggest educational solutions to these phishing problems.
DCNN Optimization Using Multi-Resolution Image Fusion
( Abdullah A. Alshehri ),( Adam Lutz ),( Soundararajan Ezekiel ),( Larry Pearlstein ),( And John Conlen ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.11
In recent years, advancements in machine learning capabilities have allowed it to see widespread adoption for tasks such as object detection, image classification, and anomaly detection. However, despite their promise, a limitation lies in the fact that a network’s performance quality is based on the data which it receives. A well-trained network will still have poor performance if the subsequent data supplied to it contains artifacts, out of focus regions, or other visual distortions. Under normal circumstances, images of the same scene captured from differing points of focus, angles, or modalities must be separately analysed by the network, despite possibly containing overlapping information such as in the case of images of the same scene captured from different angles, or irrelevant information such as images captured from infrared sensors which can capture thermal information well but not topographical details. This factor can potentially add significantly to the computational time and resources required to utilize the network without providing any additional benefit. In this study, we plan to explore using image fusion techniques to assemble multiple images of the same scene into a single image that retains the most salient key features of the individual source images while discarding overlapping or irrelevant data that does not provide any benefit to the network. Utilizing this image fusion step before inputting a dataset into the network, the number of images would be significantly reduced with the potential to improve the classification performance accuracy by enhancing images while discarding irrelevant and overlapping regions.
Saudi Experts Consensus on Diagnosis and Management of Pediatric Functional Constipation
Dhafer B. Alshehri,Haifa Hasan Sindi,Ibrahim Mohamod AlMusalami,Ibrahim Hosamuddin Rozi,Mohamed Shagrani,Naglaa M. Kamal,Najat Saeid Alahmadi,Samia Saud Alfuraikh,Yvan Vandenplas 대한소아소화기영양학회 2022 Pediatric gastroenterology, hepatology & nutrition Vol.25 No.3
Although functional gastrointestinal disorders (FGIDs) are very common in pediatric patients, there is a scarcity of published epidemiologic data, characteristics, and management patterns from Saudi Arabia, which is the 2nd largest Arabic country in terms of area and the 6th largest Arabic country in terms of population, with 10% of its population aged <5 years. Functional constipation (FC) is an FGID that has shown a rising prevalence among Saudi infants and children in the last few years, which urges us to update our clinical practices. Nine pediatric consultants attended two advisory board meetings to discuss and address current challenges, provide solutions, and reach a Saudi national consensus for the management of pediatric constipation. The pediatric consultants agreed that pediatricians should pay attention to any alarming signs (red flags) found during history taking or physical examinations. They also agreed that the Rome IV criteria are the gold standard for the diagnosis of pediatric FC. Different therapeutic options are available for pediatric patients with FC. Dietary treatment is recommended for infants with constipation for up to six months of age. When non-pharmacological interventions fail to improve FC symptoms, pharmacological treatment with laxatives is indicated. First, the treatment is aimed at disimpaction to remove fecal masses. This is achieved by administering a high dose of oral polyethylene glycol (PEG) or lactulose for a few days. Subsequently, maintenance therapy with PEG should be initiated to prevent the re-accumulation of feces. In addition to PEG, several other options may be used, such as Mg-rich formulas or stimulant laxatives. However, rectal enemas and suppositories are usually reserved for cases that require acute pain relief. In contrast, infant formulas that contain prebiotics or probiotics have not been shown to be effective in infant constipation, while the use of partially hydrolyzed formula is inconclusive. These clinical practice recommendations are intended to be adopted by pediatricians and primary care physicians across Saudi Arabia.
Mohammed Ali Mohamed Ahmed ALI(Mohammed Ali Mohamed Ahmed ALI ),Ahmed Saied Rahama ABDALLAH(Ahmed Saied Rahama ABDALLAH ),SalimAhmed Mohamed AlSHEHRI(SalimAhmed Mohamed AlSHEHRI ) 한국유통과학회 2023 The Journal of Asian Finance, Economics and Busine Vol.10 No.2
This research aims to identify the role that small and medium enterprises (SMEs) can play in achieving the economic goals of the vision of Saudi Arabia 2030. The study relied on descriptive analysis, designing a standard model, and analyzing it using the Eviews9 program. The study also adopted the questionnaire as a tool for data collection. The study area covered Alkharj and Hawtat Bani Tamim governorates. The sample size of the study was 142 participants. The study’s results confirmed the existence of a significant impact of changes in independent variables (X1, X2, X3, X4), which are (GDP, non-oil exports, number of employees, and public revenues), respectively. The dependent variable (Y) represents the number of small and medium-sized businesses in the Kingdom of Saudi Arabia. Additionally, it was found that 61.3% of small and medium-sized enterprises in the governorates of Al-Kharj and Hawtat Bani Tamim operate in the commercial sector. Most study participants concur that SMEs significantly lowered the unemployment rate and helped boost the GDP rate in the Kingdom of Saudi Arabia. The obstacles and difficulties facing the establishment of these enterprises were financial problems, marketing problems, and corporate monopoly. Furthermore, most of the small and medium l enterprises faced financing problems.