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3. Preparation of Nano Membranes with Triethylenetetramine Dihydrochloride (TETA-DH) and Multiwalled Carbon Nanotubes (MWCNT) for Seawater Desalination

Author

Alghamdi Ahmed

Subjects
multiwalled carbon nanotubes (mwcnt), triethylenetetramine dihydrochloride (teta-dh), contact angle, foulant layer thickness, Chemistry, QD1-999
Abstract

Seawater Desalination uses hydrophobic membranes. Many techniques have been developed to improve membrane hydrophobicity by depositing particles on the membrane surface. In this study, a nanocomposite membrane utilizing Triethylenetetramine (TETA) is suggested. The membrane incorporates Multiwalled Carbon Nanotubes (MWCNT) in conjunction with Triethylenetetramine Dihydrochloride (TETA-DH). In water bath, different percentages of TETA-DH films are formed. Electro-spin fabrication of MWCNTs using TETA-DH yields smooth, low-pore membranes. Membranes and their characteristics are identified by contact angle, layer thickness, and conductivity measurements. Membrane performance is examined for heat flux and salt rejection. Compared to commercial membranes, the proposed membrane exhibits superior antifouling and anti-wetting features. The membrane exhibited permeation and rejection ratio of 46 Kg m2 h−1 and 99.99% respectively which is superior as compared with other membranes. The hydrophilic Surface Modifying Macromolecules percentage (LSMM%) is evaluated because it depends on average pore size, hydrophobicity, surface porosity, and shape. The tests demonstrate the excellent performance of the proposed membrane for controlling membrane fouling.

Published
2024
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4. Characteristics and Capabilities of the Saudi Low Power Research Reactor (LPRR)

Author

Alomari, Abdullah S., Alqahtani, Meshari, Alwafi, Anas, Alghamdi, Ahmed, Chaari, Fakher, Series Editor, Gherardini, Francesco, Series Editor, Ivanov, Vitalii, Series Editor, Haddar, Mohamed, Series Editor, Cavas-Martínez, Francisco, Editorial Board Member, di Mare, Francesca, Editorial Board Member, Kwon, Young W., Editorial Board Member, Tolio, Tullio A. M., Editorial Board Member, Trojanowska, Justyna, Editorial Board Member, Schmitt, Robert, Editorial Board Member, Xu, Jinyang, Editorial Board Member, Shams, Afaque, editor, Al-Athel, Khaled, editor, Tiselj, Iztok, editor, Pautz, Andreas, editor, and Kwiatkowski, Tomasz, editor

Published
2024
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10. An unsupervised framework for analysing heterogeneous log-files to identify multi-stage attacks

Author

Alghamdi, Ahmed, Reger, Giles, and Mu, Tingting

Subjects
unsupervised machine learning, Threat modelling, threats analysis, Cybersecurity, behaviour patterns, logs analysis
Abstract

Cyberattacks have become increasingly advanced and prevalent on a global scale. One of the most detrimental types of cyberattacks is the multi-stage attack, often referred to as an Advanced Persistent Threat (APT), which combines espionage and sabotage, often over long time periods. Detection of these attacks is extremely challenging due to their deceptive approaches. The sequential events of these attacks might appear benign when performed individually or from different sources. Furthermore, existing tools often restrict their attention to single sources or rely on known patterns of behaviour. Thus, there is a need for approaches that employ empirical behaviour analysis to overcome the lack of existing tools and enhance existing multi-layered defence strategies. This research develops a novel framework to identify patterns and correlations be- tween malicious behaviours of multi-stage attacks such as APT. This framework applies unsupervised learning to heterogeneous logs and is therefore called the Unsupervised Analysis for Heterogeneous Log-files (UAHL) framework. This framework investigates multi-origin heterogeneous log files, using machine learning, in three main phases to extract inner-behaviours of log files and construct patterns of those behaviours over the analysed files. Finally, an Action Centre is developed to present sequential behaviours of attacks, utilising a custom visualisation method. In addition, the Action Centre allows administrators to browse and filter attack profiles along with the ability to show similarity rates between those profiles in terms of their contained behaviours. The framework utilises a dynamic method to eliminate the need for manually pre- defining the clustering parameters, requiring a high field knowledge and significantly affecting results. Moreover, to evaluate the framework, we have produced a (publicly available) labelled version of the SotM43 dataset, as well as using another dataset for the evaluation. Our results demonstrate that the framework can (i) efficiently cluster inner-behaviours of security-related logs with high accuracy, (ii) extract patterns of malicious behaviour and correlation between those patterns from real-world data, and (iii) present results in a meaningful format, along with effectively measuring similarities between the attack profiles.

Published
2022

15. English Language Teaching: Historical Overview, Current Issues and Suggestions for Enhancing Speaking Proficiency in EFL Contexts

Author

Alghamdi, Yahya Ali, Alghamdi, Ahmed Mohamm, and Alsolami, Turki Gabr

Abstract

The history of English Language Teaching (ELT) and learning in English as a Second and Foreign Language (ESL and EFL) contexts has gone through different practices. The role of memorization and repetition of English language structures has always been a dominant teaching attitude. This attitude has revealed unsuccessful results in promoting speaking proficiency among English language learners when communicating in real-world situations beyond the classroom context. Therefore, it is essential to address such practices and shed light on some of the issues that hinder English Language Learners (ELLs) from effectively using English in real-world communicative situations. This review paper focuses on ELT practices that have been unsuccessful in promoting English language learners' speaking proficiency. Additionally, it provides implications for classroom teaching instructions that integrate authentic tasks and materials. Implementing meaningful tasks that represent real-world situations could be a promising solution for enhancing ELLs' language competencies to enable them to transfer the language they learn to real-life situations beyond school settings. Some practical suggestions and recommendations are provided to enhance ELT in EFL contexts.

Published
2019

20. Detection of Myocardial Infarction Based on Novel Deep Transfer Learning Methods for Urban Healthcare in Smart Cities

Author

Alghamdi, Ahmed, Hammad, Mohamed, Ugail, Hassan, Abdel-Raheem, Asmaa, Muhammad, Khan, Khalifa, Hany S., and El-Latif, Ahmed A. Abd

Subjects
Computer Science - Machine Learning, Electrical Engineering and Systems Science - Signal Processing, Statistics - Machine Learning
Abstract

In this paper, an effective computer-aided diagnosis (CAD) system is presented to detect MI signals using the convolution neural network (CNN) for urban healthcare in smart cities. Two types of transfer learning techniques are employed to retrain the pre-trained VGG-Net (Fine-tuning and VGG-Net as fixed feature extractor) and obtained two new networks VGG-MI1 and VGG-MI2. In the VGG-MI1 model, the last layer of the VGG-Net model is replaced with a specific layer according to our requirements and various functions are optimized to reduce overfitting. In the VGG-MI2 model, one layer of the VGG-Net model is selected as a feature descriptor of the ECG images to describe it with informative features. Considering the limited availability of dataset, ECG data is augmented which has increased the classification performance. Physikalisch-technische bundesanstalt (PTB) Diagnostic ECG database is used for experimentation, which has been widely employed in MI detection studies. In case of using VGG-MI1, we achieved an accuracy, sensitivity, and specificity of 99.02%, 98.76%, and 99.17%, respectively and we achieved an accuracy of 99.22%, a sensitivity of 99.15%, and a specificity of 99.49% with VGG-MI2 model. Experimental results validate the efficiency of the proposed system in terms of accuracy sensitivity, and specificity.

Published
2019

24. Use of Telemedicine for Postdischarge Assessment of the Surgical Wound: International Cohort Study, and Systematic Review With Meta-analysis

Author

Glasbey, James, Trout, Issi, Adeyeye, Victoria, Ademuyiwa, Adesoji, Adisa, Adewale, Bhatt, Alisha, Biccard, Bruce, Brocklehurst, Peter, Chakrabortee, Sohini, Allen Ingabire, Jean De La Croix, Dossou, Francis Moïse, Durán, Irani, Dutta, Rohini, Ghosh, Dhruva, Gyamfi, Frank, Hardy, Pollyanna, Hyman, Gabriella, Jain, Ritu, Kadir, Bryar, Knight, Stephen, Ladipo-Ajayi, Oluwaseun, Lawani, Ismail, Lawani, Souliath, Lillywhite, Rachel, Macefield, Rhiannon, Magill, Laura, Martin, Janet, Mathers, Jonathan, McLean, Kenneth, Mistry, Unam, Mittal, Rohin, Moore, Rachel, Morton, Dion, Ntirenganya, Faustin, Ofori, Emmanuel, Pearse, Rupert, Peón, Alberto, Pinkney, Thomas, Medina, Antonio Ramos de la, Ronald, Tubasiime, Roman, David, Simoes, Joana, Slade, Anita, Tabiri, Stephen, Smith, Donna, Harrison, Ewen, Bhangu, Aneel, Glasbey, James, Trout, Issi, Bhangu, Aneel, Runigamugabo, Azmina Verjee Emmy, Ademuyiwa, Adesoji O, Adisa, Adewale O, Aguilera, Maria Lorena, Altamini, Afnan, Alexander, Philip, Al-Saqqa, Sara W, Borda-Luque, Giuliano, Cornick, Jen, Costas-Chavarri, Ainhoa, Drake, Thomas M, Fergusson, Stuart J, Fitzgerald, J Edward, Glasbey, James, Ingabire, J.C Allen, Ismaïl, Lawani, Jaffry, Zahra, Salem, Hosni Khairy, Khatri, Chetan, Kirby, Andrew, Kojo, Anyomih Theophilus Teddy, Lapitan, Marie Carmela, Lilford, Richard, Mihaljevic, Andre L, Mohan, Midhun, Morton, Dion, Mutabazi, Alphonse Zeta, Nepogodiev, Dmitri, Ntirenganya, Faustin, Ots, Riinu, Pata, Francesco, Pinkney, Thomas, Poškus, Tomas, Qureshi, Ahmad Uzair, la Medina, Antonio Ramos-De, Rayne, Sarah, Recinos, Gustavo, Søreide, Kjetil, Shaw, Catherine A, Shu, Sebastian, Spence, Richard, Smart, Neil, Tabiri, Stephen, Lilford, Richard, Morton, Dion, Harrison, Ewen M, Bhangu, Aneel, Modolo, Maria Marta, Iyer, Dushyant, King, Sebastian, Arthur, Tom, Nahar, Sayeda Nazmum, Waterman, Ade, Ismaïl, Lawani, Walsh, Michael, Agarwal, Arnav, Zani, Augusto, Firdouse, Mohammed, Rouse, Tyler, Liu, Qinyang, Correa, Juan Camilo, Salem, Hosni Khairy, Talving, Peep, Worku, Mengistu, Arnaud, Alexis, Tabiri, Stephen, Kalles, Vassilis, Aguilera, Maria Lorena, Recinos, Gustavo, Kumar, Basant, Kumar, Sunil, Amandito, Radhian, Quek, Roy, Pata, Francesco, Ansaloni, Luca, Altibi, Ahmed, Venskutonis, Donatas, Zilinskas, Justas, Poskus, Tomas, Whitaker, John, Msosa, Vanessa, Tew, Yong Yong, Farrugia, Alexia, Borg, Elaine, la Medina, Antonio Ramos-De, Bentounsi, Zineb, Ademuyiwa, Adesoji O, Søreide, Kjetil, Gala, Tanzeela, Al-Slaibi, Ibrahim, Tahboub, Haya, Alser, Osaid H., Romani, Diego, Shu, Sebestian, Major, Piotr, Mironescu, Aurel, Bratu, Matei, Kourdouli, Amar, Ndajiwo, Aliyu, Altwijri, Abdulaziz, Alsaggaf, Mohammed Ubaid, Gudal, Ahmad, Jubran, Al Faifi, Seisay, Sam, Lieske, Bettina, Rayne, Sarah, Spence, Richard, Ortega, Irene, Jeyakumar, Jenifa, Senanayake, Kithsiri J., Abdulbagi, Omar, Cengiz, Yucel, Raptis, Dmitri, Altinel, Yuksel, Kong, Chia, Teasdale, Ella, Irwin, Gareth, Stoddart, Michael, Kabariti, Rakan, Suresh, Sukrit, Gash, Katherine, Narayanan, Ragavan, Maimbo, Mayaba, Grizhja, Besmir, Ymeri, Shpetim, Galiqi, Gezim, Klappenbach, Roberto, Antezana, Diego, Beleño, Alvaro Enrique Mendoza, Costa, Cecilia, Sanchez, Belen, Marta Modolo, Susan Aviles Maria, Fermani, Claudio Gabriel, Balmaceda, Rubén, Villalobos, Santiago, Carmona, Juan Manuel, Hamill, Daniel, Deutschmann, Peter, Sandler, Simone, Cox, Daniel, Nataraja, Ram, Sharpin, Claire, Ljuhar, Damir, Gray, Demi, Iyer, Morgan Haines Dush, Niranjan, Nithya, D’Amours, Scott, Ashtari, Morvarid, Franco, Helena, Mitul, Ashrarur Rahman, Karim, Sabbir, Aman, Nowrin F., Umme Salma, Mahnuma Mahfuz Estee, Razzaque, Joyeta, Kanta, Tasnia Hamid, Tori, Sayeeda Aktar, Alamin, Shadid, Roy, Swapnil, Amin, Shadid Al, Haque, Rezaul Karim Muhtarima, Faruq, Amreen, Iftekhar, Farhana, O’Shea, Margaret, Padmore, Greg, Litvin, Ramesh Jonnalagadda Andrey, Filatau, Aliaksandr, Paulouski, Dzmitry, Shubianok, Maryna, Shachykava, Tatsiana, Khokha, Dzianis, Djivoh, Vladimir Khokha Fernande, Ismaïl, Lawani, Morel Seto, Francis Dossou Djifid, Gbessi, Dansou Gaspard, Noukpozounkou, Bruno, Souaibou, Yacoubou Imorou, Keke, Kpèmahouton René, Stephane Ahounou, Fred Hodonou Ernest Yemalin, Bedada, Thierry Alihonou Alemayehu Ginbo, Nsengiyumva, Carlos, Kwizera, Sandrine, Choi, Venerand Barendegere Philip, Stock, Simon, Jamal, Luai, Firdouse, Mohammed, Zani, Augusto, Azzie, Georges, Kushwaha, Sameer, Agarwal, Arnav, Chen, Tzu-Ling, Yip, Chingwan, Montes, Irene, Zapata, Felipe, Sierra, Sebastian, Lanau, Maria Isabel Villegas, Arango, Maria Clara Mendoza, Restrepo, Ivan Mendoza, Sierra, Sebastian, Giraldo, Ruben Santiago Restrepo, Arango, Maria Clara Mendoza, Domini, Edgar, Karlo, Robert, Mihanovic, Jakov, Youssef, Mohamed, Elfeki, Hossam, Thabet, Waleed, Sanad, Aly, Tawfik, Gehad, Zaki, Ahmed, Abdel-Hameed, Noran, Mostafa, Mohamed, Omar, Muhammad Fathi Waleed, Ghanem, Ahmed, Abdallah, Emad, Denewar, Adel, Emara, Eman, Rashad, Eman, Sakr, Ahmad, Elashry, Rehab, Emile, Sameh, Khafagy, Toqa, Elhamouly, Sara, Elfarargy, Arwa, Mohamed, Amna Mamdouh, Nagy, Ghada Saied, Esam, Abeer, Elwy, Eman, Hammad, Aya, Khallaf, Salwa, Ibrahim, Eman, Saidbadr, Ahmed, Moustafa, Ahmed, Mohammed, Amany Eldosouky, Elgheriany, Mohammed, Abdelmageed, Eman, Raouf, Eman Abd Al, Elbanby, Esraa Samir, Elmasry, Maha, Farahat, Mahitab Morsy, Mansor, Eman Yahya, Hegazy, Eman Magdy, Gamal, Esraa, Gamal, Heba, Kandil, Hend, Abdelrouf, Doaa Maher, Moaty, Mohamed, Gamal, Dina, El-Sagheer, Nada, Salah, Mohamed, Magdy, Salma, Salah, Asmaa, Essam, Ahmed, Ali, Ahmed, Badawy, Mahmoud, Ahmed, Sara, Mohamed, Mazed, Assal, Abdelrahman, Sleem, Mohamed, Ebidy, Mai, Elrazek, Aly Abd, Zahran, Diaaaldin, Adam, Nourhan, Nazir, Mohamed, Hassanein, Adel B, Ismail, Ahmed, Elsawy, Amira, Mamdouh, Rana, Mabrouk, Mohamed, Ahmed, Lopna Ahmed Mohamed, Alnaby, Mohamed Hassab, Magdy, Eman, Abd-Elmawla, Manar, Fahim, Marwan, Mowafy, Bassant, Mahmoud, Moustafa Ibrahim, Allam, Meran, Alkelani, Muhammad, El Gendy, Noran Halim, Aboul-Naga, Mariam Saad, El-Din, Reham Alaa, Elgendy, Alyaa Halim, Ismail, Mohamed, Shalaby, Mahmoud, Elsharkawy, Aya Adel, Moghazy, Mahmoud Elsayed, Elbisomy, Khaled Hesham, Shakshouk, Hend Adel Gawad, Hamed, Mohamed Fouad, Ebidy, Mai Mohamed, Abdelkader, Mostafa, Ahmed, Mohamed Karkeet Hayam, Adel, Israa, Omar, Mohammad Elsayed, Ibrahim, Mohamed, Ghoneim, Omar, Hesham, Omar, Gamal, Shimaa, Hilal, Karim, Arafa, Omar, Awad, Sawsan Adel, Salem, Menatalla, Elsherif, Fawzia Abdellatif, Elsabbagh, Nourhan, Aboelsoud, Moustafa R., Rida, Ahmed Hossam Eldin Fouad, Hossameldin, Amr, Hany, Ethar, Asar, Yomna Hosny, Anwar, Nourhan, Gadelkarim, Mohamed, Abdelhady, Samar, Morshedy, Eman Mohamed, Saad, Reham, Soliman, Nourhan, Ezzat, Mahmoud Salama Eslam, Mohamed, Arwa, Ibrahim, Arwa, Fergany, Alaa, Mohammed, Sara, Reda, Aya, Allam, Yomna, Saad, Hanan Adel, Abdelfatah, Afnan, Fathy, Aya Mohamed, El-Sehily, Ahmed, Kasem, Esraa Abdalmageed, Hassan, Ahmed Tarek Abdelbaset, Mohammed, Ahmed Rabeih, Saad, Abdalla Gamal, Elfouly, Yasmin, Elfouly, Nesma, Ibrahim, Arij, Hassaan, Amr, Mohammed, Mohammed Mustafa, Elhoseny, Ghada, Magdy, Mohamed, Elkhalek, Esraa Abd, Zakaria, Yehia, Ezzat, Tarek, El Dahab, Ali Abo, Kelany, Mohamed, Arafa, Sara, Hassan, Osama Mokhtar Mohamed, Badwi, Nermin Mohamed, Sleem, Ahmad Saber, Ahmed, Hussien, Abdelbadeai, Kholoud, Abdullah, Mohamed Abozed, Lokman, Muhammad Amsyar Auni, Bahar, Suraya, Abdelazeam, Anan Rady, Adelshone, Abdelrahman, Bin Hasnan, Muhammad, Zulkifli, Athirah, Kamarulzamil, Siti Nur Alia, Elhendawy, Abdelaziz, Latif, Aliang, Bin Adnan, Ahmad, Shaharuddin, Shahadatul, Abdul Majid, Aminah Hanum Haji, Amreia, Mahmoud, Al-Marakby, Dina, Salma, Mahmoud, Bin Ismail, Mohamad Jeffrey, Basir, Elissa Rifhan Mohd, Ali, Citra Dewi Mohd, Maha Nasr, Aya Yehia Ata, Rezq, Asmaa, Sheta, Ahmed, Tariq, Sherif, Sallam, Abd Elkhalek, Darwish, Abdelrhman KZ, Elmihy, Sohaila, Elhadry, Shady, Farag, Ahmed, Hajeh, Haidar, Abdelaal, Abdelaziz, Aglan, Amro, Zohair, Ahmed, Essam, Mahitab, Moussa, Omar, El-Gizawy, Esraa, Samy, Mostafa, Ali, Safia, Elhalawany, Esraa, Ata, Ahmed, El Halawany, Mohamed, Nashat, Mohamed, Soliman, Samar, Elazab, Alaa, Samy, Mostada, Abdelaziz, Mohamed A, Ibrahim, Khaled, Ibrahim, Ahmed mohamed, Gado, Ammar, Alm Eldeen, Usama Hantour Esraa, loaloa, Mohamed Reda, Abouzaid, Arwa, Eldin, Mostafa Ahmed Bahaa, Hashad, Eman, Sroor, Fathy, Gamil, Doaa, Abdulhakeem, Eman Mahmoud, Zakaria, Mahmoud, Mohamed, Fawzy, Abubakr, Marwan, Ali, Elsayed, Magdy, Hesham, Ramadan, Menna Tallah, Mohamed, Mohamed Abdelaty, Mansour, Salma, Amin, Hager Abdul Aziz, Mohamed, Ahmed Rabie, Saami, Mahmoud, Elsayed, Nada Ahmed Reda, Tarek, Adham, Mahmoud, Sabry Mohy Eldeen, El Sayed, Islam Magdy, Reda, Amira, Shawky, Martina Yusuf, Salem, Mohammed Mousa, El-Din, Shahinaz Alaa, Soliman, Noha Abdullah, Talaat, Muhammed, Alaael-Dein, Shahinaz, Elhusseiny, Ahmed Abd Elmoen, Abdullah, Noha, Elshaar, Mohammed, Ibraheem, Aya AbdelFatah, Abdulaziz, Hager, Ismail, Mohammed Kamal, Madkor, Mona Hamdy, Abdelaty, Mohamed, Abdel-Kader, Sara Mahmoud, Salah, Osama Mohamed, Eldafrawy, Mahmoud, Eldeeb, Ahmed Zaki, Attia, Mostafa Mahmoud Eid Attia, El-Dien, Khalid Salah, Shwky, Ayman, Badenjki, Mohamed Adel, Soliman, Abdelrahman, Attar, Samaa Mahmoud Al, Sayed, Farrag, Sabour, Fahd Abdel, Azizeldine, Mohammed G., Shawqi, Muhammad, Hashim, Abdullah, Aamer, Ahmed, Abdelraouf, Ahmed Mahmoud, Abdelshakour, Mahmoud, Ibrahim, Amal, Mahmoud, Basma, Mahmoud, Mohamed Ali, Qenawy, Mostafa, Rashed, Ahmed M., Dahy, Ahmed, Sayed, Marwa, Shamsedine, Ahmed W., Mohamed, Bakeer, Hasan, Ahmad, Saad, Mahmoud M., Khalid Abd El-Latif, Khalil Abdul Bassit Nadia, Elzahed, Nada, El Kashash, Ahmed, Bekhet, Nada Mohamed, Hafez, Sarah, Gad, Ahmed, Maher, Mahmoud Elkhadragy, Elsameea, Ahmed Abd, Hafez, Mohamed, Sabe, Ahmad, Ahmed, Ataa, Shahine, Ahmed, Dawood, Khaled, Gaafar, Shireen, Husseiny, Reem, Aboelmagd, Omnia, Soliman, Ahmed, Mesbah, Nourhan, Emadeldin, Hossam, Meligy, Amgad Al, Bekhet, Amira Hassan, Hasan, Doaa, Alhady, Khaled, Sabe, Ahmad Khaled, Elnajjar, Mahmoud A., Aboelella, Majed, Hamsho, Ward, Hassan, Ihab, Saad, Hala, Abdelazim, Galaleldin, Mahmoud, Hend, Wael, Noha, Kandil, Ahmedali M, Magdy, Ahmed, Elkholy, Shimaa Said, Adel, Badr Eldin, Dabbour, Kareem, Elsherbiney, Saged, Mattar, Omar, Abdrabou, Abdulshafi Khaled, Aly, Mohammed Yahia Mohamed, Geuoshy, Abdelrahman, Elnagar, Ahmedglal, Ahmed, Saraibrahim, Abdelmotaleb, Ibrahem, Saleh, Amr Ahmed, Saeed, Manar, Mahmoud, Shady, Tawfik, Badreldin Adel, Ismail, Samar Adel, Zakaria, Esraay, Gad, Mariam O., Elhelbawy, Mohamed Salah, Bassem, Monica, Maraie, Noha, Elhadary, Nourhan Medhat, Semeda, Nourhan, Mohamed, Shaza Rabie, Bakry, Hesham Mohammed, Essam, AA, Tarek, Dina, Ashour, Khlood, Elhadad, Alaa, Abdel-Aty, Abdulrahman, Rakha, Ibrahim, Matter, Sara Mamdouh, Abdelhamed, Rasha, Abdelkader, Omar, Hassaan, Ayat, Soliman, Yasmin, Mohamed, Amna, Ghanem, Sara, Farouk, Sara Amr Mohamed, Ibrahim, Eman Mohamed, Mostafa, Esraa El-Taher Merna, Badr, Mohamed Fawzy Mahrous, Elsemelawy, Rofida, El-Sawy, Aya, Bakr, Ahmad, Al Rafati, Ahmad Abdel Razaq, Saar, Sten, Reinsoo, Arvo, Talving, Peep, Seyoum, Nebyou, Worku, Tewodros, Fitsum, Agazi, Tolonen, Matti, Leppäniemi, Ari, Sallinen, Ville, Parmentier, Benoît, Peycelon, Matthieu, Irtan, Sabine, Dardenne, Sabrina, Robert, Elsa, Maillot, Betty, Courboin, Etienne, Arnaud, Alexis Pierre, Hascoet, Juliette, Abbo, Olivier, Kaci, Amir Ait, Prudhomme, Thomas, Ballouhey, Quentin, Grosos, Céline, Fourcade, Laurent, Cecilia, Tolg, Jean-Francois, Colombani, Delforge, Francois-Coridon Helene Xavier, Haraux, Elodie, Dousset, Bertrand, Schiavone, Roberto, Gaujoux, Sebastien, Marret, Jean-Baptiste, Haffreingue, Aurore, Rod, Julien, Jean-François Lecompte, Mariette Renaux-Petel, Bréaud, Jean, Gastaldi, Pauline, Taieb, Chouikh, Claire, Raquillet, Anis, Echaieb, Bustangi, Nasir, Lopez, Manuel, Scalabre, Aurelien, Grella, Maria Giovanna, Mariani, Aurora, Podevin, Guillaume, Schmitt, Françoise, Hervieux, Erik, Broch, Aline, Muller, Cecile, Tabiri, Stephen, Kojo, Anyomih Theophilus Teddy, Bandoh, Dickson, Abantanga, Francis, Kyereh, Martin, Asumah, Hamza, Appiah, Eric Kofi, Wondoh, Paul, Gyedu, Adam, Dally, Charles, Agbedinu, Kwabena, Amoah, Michael, Yifieyeh, Abiboye, Owusu, Frank, Amoako-Boateng, Mabel, Dayie, Makafui, Hagan, Richmond, Debrah, Sam, Ohene-Yeboah, Micheal, Clegg-Lampety, Joe-Nat, Etwire, Victor, Dakubo, Jonathan, Essoun, Samuel, Bonney, William, Glover-Addy, Hope, Osei-Nketiah, Samuel, Amoako, Joachim, Adu-Aryee, Niiarmah, Appeadu-Mensah, William, Bediako-Bowan, Antoinette, Dedey, Florence, Ekow, Mattew, Akatibo, Emmanuel, Yakubu, Musah, Kordorwu, Hope Edem Kofi, Asare-Bediako, Kwasi, Tackie, Enoch, Aaniana, Kenneth, Acquah, Emmanuel, Opoku-Agyeman, Richard, Avoka, Anthony, Kusi, Kwasi, Maison, Kwame, Gyamfi, Frank Enoch, Barnabas, Gandau Naa, Amoako, Saiba Abdul-Latif Philip Taah, Davor, Anthony, Dassah, Victor, Dagoe, Enoch, Kwakyeafriyie, Prince, Akoto, Elliot, Ackom, Eric, Mensah, Ekow, Atkins, Ebenezer Takyi, Coompson, Christian Lari, Ivros, Nikolaos, Ferousis, Christoforos, Kalles, Vasileios, Agalianos, Christos, Kyriazanos, Ioannis, Barkolias, Christos, Tselos, Angelos, Tzikos, Georgios, Lytras, Evangelos Voulgaris Dimitrios, Bamicha, Athanasia, Psarianos, Kyriakos, Stefanopoulos, Anastasios, Patoulias, Ioannis, Sfougaris, Dimitrios, Valioulis, Ioannis, Balalis, Dimitrios, Korkolis, Dimitrios, Manatakis, Dimitrios K, Kyrou, Georgios, Karabelias, Georgios, Konstantina, Iason-Antonios Papaskarlatos Kolonia, Zampitis, Nikolaos, Papailia, Stylianos Germanos Aspasia, Theodosopoulos, Theodosios, Gkiokas, Georgios, Mitroudi, Magdalini, Panteli, Christina, Feidantsis, Thomas, Farmakis, Konstantinos, Kyziridis, Dimitrios, Ioannidis, Orestis, Gemenetzis, Styliani Parpoudi Georgios, Parasyris, Stavros, Anthoulakis, Christos, Nikoloudis, Nikolaos, Aguilera-Arevalo, Michail Margaritis Maria-Lorena, Coyoy-Gaitan, Otto, Tale, Javier Rosales Luis, Soley, Rafael, Rodriguez, Emmanuel Barrios Servio Tulio Torres, Galvez, Carlos Paz, Cruz, Danilo Herrera, Rosenberg, Guillermo Sanchez, Matheu, Alejandro, Cohen, David Monterroso, Paul, Marie, Charles, Angeline, Lam, Justin Chak Yiu, Yeung, Man Hon Andrew, Fok, Chi Ying Jacquelyn, Li, Ka Hin Gabriel, Lai, Anthony Chuk-Him, Cheung, Yuk Hong Eric, Wong, Hong Yee, Leung, Ka Wai, Lee, Tien Seng Bryan, Lam, Wai Him, Dao, Weihei, Kwok, Stephanie Hiu-wai, Chan, Tsz-Yan Katie, Ng, Yung Kok, Liu, TWC Mak Qinyang, Foo, Chi Chung, Yang, James, Kumar, Basant, Bhatnagar, Ankur, Upadhyaya, Vijaid, Muddebihal, Sunil Kumar Uday, Dar, Wasim, Alexander, KC Janardha Philip, Aruldas, Neerav, Adella, Fidelis Jacklyn, Rulie, Anthonius Santoso, Iskandar, Ferdy, Setiawan, Jonny, Evajelista, Cicilia Viany, Natalie, Hani, Suyadi, Arlindawati, Gunawan, Rudy, Karismaningtyas, Herlin, Mata, Lusi Padma Sulistianingsih, Andika, Ferry Fitriya Ayu, Hasanah, Afifatun, Widiastini, T Ariani, Purwaningsih, Nurlaila Ayu, Mukin, Annisa Dewi Fitriana, Rahmah, Dina Faizatur, Nurqistan, Hazmi Dwinanda, Arsyad, Hasbi Maulana, Adhitama, Novia, Jeo, Wifanto Saditya, Sutandi, Nathania, Clarissa, Audrey, Gultom, Phebe Anggita, Billy, Matthew, Haloho, Andreass, Amandito, Radhian, Johanna, Nadya, Lee, Felix, Radin Dorani, Radin Mohd Nurrahman, Glynn, Martha, Alherz, Mohammad, Goh, Wennweoi, Shiwani, Haaris A., Sproule, Lorraine, Conlon, Kevin C., Bala, Miklosh, Turati, Asaf Kedar Luca, Bianco, Federica, Steccanella, Francesca, Gallo, Gaetano, Trompetto, Mario, Papandrea, Giuseppe Clerico Matteo, Sammarco, Giuseppe, Sacco, Rosario, Benevento, Angelo, Pata, Francesco, Giavarini, Luisa, Giglio, Mariano Cesare, Bucci, Luigi, Pagano, Gianluca, Sollazzo, Viviana, Peltrini, Roberto, Birindelli, Gaetano Luglio Arianna, Di Saverio, Salomone, Tugnoli, Gregorio, Paludi, Miguel Angel, Mingrone, Pietro, Pata, Domenica, Selvaggi, Francesco, Selvaggi, Lucio, Pellino, Gianluca, Curletti, Natale Di Martino Gianluca, Aonzo, Paolo, Galleano, Raffaele, Berti, Stefano, Francone, Elisa, Boni, Silvia, Lorenzon, Laura, Conte, Annalisa lo, Balducci, Genoveffa, Confalonieri, Gianmaria, Laura Gavagna, Giovanni Pesenti, Vasquez, Giorgio, Targa, Simone, Occhionorelli, Savino, Pata, Dario Andreotti Giacomo, Armellini, Andrea, Aquilino, Deborah Chiesa Fabrizio, Chetta, Nicola, Abdelkhalek, Arcangelo Picciariello Mohamed, Belli, Andrea, Bigaran, Silvia De Franciscis Annamaria, Favero, Alessandro, Salusso, Stefano M.M Basso Paola, Perino, Martina, Mochet, Sylvie, Sasia, Diego, Riente, Francesco, Merlini, Marco Migliore David, Basilicò, Silvia, Lazzari, Carlo Corbellini Veronica, Macchitella, Yuri, Angelieri, Luigi Bonavina Daniele, Coletta, Diego, Falaschi, Federica, Catani, Marco, Reali, Claudia, Malavenda, Mariastella, Basso, Celeste Del, Ribaldi, Sergio, Coletti, Massimo, Natili, Andrea, Depalma, Norma, Iannone, Immacolata, 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Dragatas Arturas, Mazelyte, Ruta, Kaselis, Antanas Zadoroznas Nerijus, Žiubrytė, Greta, Rahantasoa, Finaritra Casimir Fleur Prudence, Samison, Luc Hervé, Rasoaherinomenjanahary, Fanjandrainy, Tolotra, Todisoa Emmanuella Christina, Mukuzunga, Cornelius, Msosa, Vanessa, Kwatiwani, Chimwemwe, Chai, Nelson Msiska Feng Yih, Asilah, Siti Mohd Desa, Pui Xin Chin, Khuzaimah Zahid Syibrah, Salleh, Afizah, Roslani, Nur Zulaika Riswan April Camilla, Chong, Hoong-Yin, Aziz, Nora Abdul, Poh, Keat-Seong, Chai, Chu-Ann, Kumar, Sandip, Taher, Mustafa Mohammed, Kosai, Nik Ritza, Aziz, Dayang Nita Abdul, Julaihi, Reynu Rajan Rokayah, Jethwani, Durvesh Lacthman, Yahaya, Muhammad Taqiyuddin, Abdullah, Nik Azim Nik, Mathew, Susan Wndy, Chung, Kuet Jun, Nirumal, Milaksh Kumar, Tze, R. 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Pluke, Kuok Chung Lee Kent, Dedekind, Britta, Nashidengo, Puyearashid, Hampton, Mark Ian, Joosten, Johanna, Sobnach, Sanju, Roodt, Liana, Sander, Anthony, Pape, James, Spence, Richard, Maistry, Niveshni, Ndwambi, Phumudzo, Kinandu, Kamau, Tun, Myint, Toit, Frederick Du, Ellison, Quinn, Burger, Sule, Grobler, DC, Khulu, Lawrence Bongani, Moore, Rachel, Jennings, Vicky, Leusink, Astrid, Kariem, Nazmie, Gouws, Juan, Chu, Kathryn, Bougard, Heather, Noor, Fazlin, Dell, Angela, Rayne, Sarah, Van Straten, Stephanie, Khamajeet, Arvin, Tshisola, Serge Kapenda, Kabongo, Kalangu, Kong, Victor, Moodley, Yoshan, Anderson, Frank, Madiba, Thandinkosi, du Plooy, Flip, Hartford, Leila, Chilton, Gareth, Mabitsela, Parveen Karjiker Matlou Ernest, Ndlovu, Sibongile Ruth, Badicel, Maria, Jaich, Robert, Garcia-Florez, Jaime Ruiz-Tovar Luis, Otero-Díez, Jorge L., Pérez, Virginia Ramos, García, Nuria Aguado Suárez Javier Minguez, Moreno, Sara Corral, Collado, Maria Vicenta, Carneros, Virginia Jiménez, Gonzalez, Javier García Septiem Mariana, Picardo, Antonio, Esteban, Enrique, Ferrero, Esther, Ortega, Irene, Espin-Basany, Eloy, Blanco-Colino, Ruth, Andriola, Valeria, García, Lorena Solar, Contreras, Elisa, Bernardo, Carmen García, Pagnozzi, Janet, Sanz, Sandra, de León, Alberto Miyar, Dorismé, Asnel, Rodicio, Joseluis, Suarez, Aida, Stuva, Jessica, Fernandez-Vega, Tamara Diaz Vico Laura, Soldevila-Verdeguer, Carla, Sena-Ruiz, Fatima, Pujol-Cano, Natalia, Diaz-Jover, Paula, Garcia-Perez, José Maria, Segura-Sampedro, Juan Jose, Pineño-Flores, Cristina, Ambrona-Zafra, David, Craus-Miguel, Andrea, Jimenez-Morillas, Patricia, Jayathilake, Angela Mazzella A.B, Thalgaspitiya, S.P.B, Wijayarathna, L.S., Sanni, P.M.S.N. 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Murat, Cengiz, Turgut Bora, Tansoker, Ilkan, Işler, Vedatcan, Cevik, Muazzez, Mutlu, Deniz, Ozben, Volkan, Ozmen, Berk Baris, Bayram, Sefa, Yolcu, Sinem, Kobal, Berna Buse, Toto, Ömer Faruk, Karabulut, Haluk Cem Çakaloğlu Kagan, Mutlu, Vahit, Ozkan, Bahar Busra, Celik, Saban, Semiz, Anil, Bodur, Selim, Gül, Enisburak, Murutoglu, Busra, Yildirim, Reyyan, Baki, Bahadir Emre, Arslan, Ekin, Ulusahin, Mehmet, Walker, Ali Guner Nathan, Shrimanker, Nikhita, Stoddart, Michael, Cole, Simon, Breslin, Ryan, Srinivasan, Ravi, Elshaer, Mohamed, Hunter, Kristina, Liew, Ahmed Al-Bahrani Ignatius, Mairs, Nora Grace, Rocke, Alistair, Dick, Lachlan, Chowdhury, Mobeen Qureshi Debkumar, Wright, Naomi, Skerritt, Clare, Kufeji, Dorothy, Ho, Adrienne, Dissanayake, Tharindra, Tennakoon, Athula, Ali, Wadah, Lim, Shujing Jane, Tan, Charlene, O’Neill, Stephen, Jones, Catrin, Knight, Stephen, Nassif, Dima, Sharma, Abhishek, Warren, Oliver, White, Rebecca, Mehdi, Aia, Post, Nathan, Kalakouti, Eliana, Dashnyam, 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Laurie, Kirsten, Connor, Katie, Mann, Thomas, Nepogodiev, Dmitri, Mansuri, Anahita, Davies, Rachel, Griffiths, Ewen, Shahbaz, Aized Raza, Eng, Calvin, Din, Farhat, L’Heveder, Ariadne, Park, Esther H.G., Ravishankar, Ramanish, McIntosh, Kirsten, Yau, Jih Dar, Chan, Luke, McGarvie, Susan, Tang, Lingshan, Lim, Hui, Yap, Suhhuey, Park, Jay, Ng, Zhan Herr, Mirza, Shahrukh, Ang, Yun Lin, Walls, Luke, Teasdale, Ella, Roy, Chloe, Paterson-Brown, Simon, Camilleri-Brennan, Julian, Mclean, Kenneth, D’Souza, Michelle S, Pronin, Savva, Henshall, David Ewart, Ter, Eunice Zuling, Fouad, Dina, Minocha, Ashish, English, William, Morgan, Catrin, Townsend, Dominic, Maciejec, Laura, Mahdi, Shareef, Akpenyi, Onyinye, Hall, Elisabeth, Caydiid, Hanaan, Rob, Zakaria, Abbott, Tom, Torrance, Hew D, Irwin, Gareth, Johnston, Robin, Gani, Mohammed Akil, Gravante, Gianpiero, Rajmohan, Shivanchan, Majid, Kiran, Dindyal, Shiva, Smith, Christopher, Palliyil, Madanmohan, Patel, Sanjay, Nicholson, Luke, Harvey, Neil, Baillie, Katie, Shillito, Sam, Kershaw, Suzanne, Bamford, Rebecca, Orton, Peter, Reunis, Elke, Tyler, Robert, Soon, Wai Cheong, Jama, Guled M., Dhillon, Dharminder, Patel, Khyati, Nanthakumaran, Shayanthan, Heard, Rachel, Chen, Kar Yan, Barmayehvar, Behrad, Datta, Uttaran, Kamarajah, Sivesh K, Karandikar, Sharad, Tani, Sobhana Iftekhar, Monaghan, Eimear, Donnelly, Philippa, Walker, Michael, Parakh, Jehangirshaw, Blacker, Sarah, Kaul, Anil, Paramasivan, Arjun, Farag, Sameh, Nessa, Ashrafun, Awadallah, Salwa, Lim, Jieqi, Ng, James Chean Khun, Gash, Katherine, Kiran, Ravi P., Murray, Alice, Etchill, Eric, Dasari, Mohini, Puyana, Juan, Haddad, Nadeem, Zielinski, Martin, Caliman, Asad Choudhry Celeste, Beamon, Mieshia, Duane, Therese, Narayanan, Ragavan, Swaroop, Mamta, Myers, Jonathan, Deal, Rebecca, Schadde, Erik, Hemmila, Mark, Napolitano, Lena, To, Kathleen, Makupe, Alex, Musowoya, Joseph, Maimbo, Mayaba, Van Der Naald, Niels, Kumwenda, Dayson, Reece-Smith, Alex, Otten, Kars, Verbeek, Anna, Prins, Marloes, Suarez, Alibeth Andres Baquero, Balmaceda, Ruben, Deane, Chelsea, Dijan, Emilio, Elfiky, Mahmoud, Koskenvuo, Laura, Thollot, Aurore, Limoges, Bernard, Capito, Carmen, Alexandre, Challine, Kotobi, Henri, Leroux, Julien, Rod, Julien, Pinnagoda, Kalitha, Henric, Nicolas, Azzis, Olivier, Rosello, Olivier, Francois, Poddevin, Etienne, Sara, Buisson, Philippe, Hmila, Sophian, Clegg-Lamptey, Joe-Nat, Imoro, Osman, Abem, Owusu Emmanuel, Wondoh, Paul, Papageorgiou, Dimitrios, Soulou, Vasiliki, Asturias, Sabrina, Peña, Lenin, Kumar, Basant, O’Connor, Donal B, Luc, Alberto Realis, Russo, Alfio Alessandro, Ruzzenente, Andrea, Taddei, Antonio, Cona, Camilla, Bottini, Corrado, Pascale, Giovanni, Rotunno, Giuseppe, Solaini, Leonardo, Pascale, Marco Maria, Notarnicola, Margherita, Corbellino, Mario, Sacco, Michele, Ubiali, Paolo, Cautiero, Roberto, Bocchetti, Tommaso, Muzio, Elena, Guglielmo, Vania, Morandi, Eugenio, Mao, Patrizio, De Luca, Emilia, Notarnicola, Margherita, Ali, Farah Mahmoud, Žilinskas, Justas, Strupas, Kestutis, Kondrotas, Paulius, Baltrunas, Robertas, Kutkevicius, Juozas, Ignatavicius, Povilas, Tan, Choy Ling, Siaw, Jia Yng, Yam, Sir Young, Wilson, Ling, Aziz, Mohamed Rezal Abdul, Bondin, John, Zorrilla, Carmina Diaz, Majbar, Anass, Sale, Danjuma, Abdullahi, Lawal, Osagie, Olabisi, Faboya, Omolara, Fatuga, Adedeji, Taiwo, Agboola, Nwabuoku, Emeka, Bliksøen, Marte, Khan, Zain Ali, Coronel, Jazmin, Miranda, Cesar, Vasquez, Idelso, Helguero-Santin, Luis M., Rickard, Jennifer, Mironescu, Aurel, Adedeji, Adesina, Alqahtani, Saleh, Rath, Max, Van Niekerk, Michael, Koto, Modise Zacharia, Matos-Puig, Roel, Israelsson, Leif, Schuetz, Tobias, Yuksek, Mahmut Arif, Mericliler, Meric, Uluşahin, Mehmet, Wolf, Bernhard, Fairfield, Cameron, Yong, Guo Liang, Whitehurst, Katharine, Wilson, Michael, Redgrave, Natalie, Musyoka, Caroluce K, Olivier, James, Lee, Kathryn, Cox, Michael, Farhan-Alanie, Muhamed M H, Callan, Rory, Chibuye, Chali, Ali, Tebian Hassanein Ahmed, Rekhis, Syrine, Rommaneh, Muna, Halhouli, Oday, Sam, Zi Hao, Chen, Jacky Hong Chieh, Roi, Dylan, Ismaïl, Lawani, Kalles, Vasileios, Pata, Francesco, Nita, Gabriela Elisa, Coccolini, Federico, Ansaloni, Luca, Pugliesi, Thays Brunelli, Pardo, Gabriel, Blanco, Ruth, and Escobar, Eugenio Grasset

Published
2023
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28. Prevalence of Classical Extraintestinal Manifestations among Inflammatory Bowel Disease Patients in Saudi Arabia: A Single Tertiary Center Experience

Author

Alotaibi, Abdullah, primary, Alhubayshi, Abrar, additional, Allehibi, Abed, additional, Almtawa, Abdullah, additional, Alotaibi, Nawaf, additional, Alghamdi, Adel, additional, Alrajhi, Saad, additional, Alqutub, Adel, additional, Aleid, Ahmad, additional, Alamr, Abdulrhman, additional, Ibrahim, Bashaar, additional, Alahmari, Mohammed, additional, Alhamidi, Hussam, additional, Ahmad, Shameem, additional, AlBayyat, Hadeel, additional, Alshaya, Osama, additional, Altannir, Youssef, additional, and Alghamdi, Ahmed, additional

Published
2024
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41. Prevalence of Ocular Hypertension and Other Risk Factors of Open-Angle Glaucoma Among Middle-Aged Adults in Al-Baha City, Saudi Arabia

Author

Bashir, Mahadi, primary, Alghamdi, Ali H, additional, Alzahrani, Suhaib A, additional, Alhajji, Abdullah M, additional, Al Thobaiti, Loay Y, additional, Alzahrani, Khalid A, additional, Alghamdi, Ahmed G, additional, Alnemari, Ranin K, additional, Althobaiti, Abdulaziz H, additional, and Alzahrani, Roaa S, additional

Published
2023
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45. Factors affecting body weight in boys in primary school, Makkah, Saudi Arabia : a comparative case study

Author

Alghamdi, Ahmed

Subjects
613.2
Abstract

Childhood is an important period for determining long-term health in life. One of the biggest threats facing children is obesity. Globally, childhood obesity is reaching the level of a serious public health concern. In some countries, rates of obesity have more than doubled in the last two decades. For example, in Saudi Arabia a recent national study of 11,112 children aged from 2-7 years found the prevalence of obesity among Saudi children has almost doubled since 2002. Global literature shows that obesity is a complex issue and that many factors contribute to children becoming overweight. From a review of the Saudi literature, it is clear that no previous study has used observation as a research methodology to explore the factors affecting body weight in Saudi schools and this is the first study completed within the Islamic school context. The aim of this study was to explore factors that affect body weight among boys in three types of school in Saudi Arabia (public, Islamic and private). A case study design and qualitative methods were adopted. Data were generated through observations, interviews with teachers and students, and by analysing documents. Three research committees from Cardiff University and the Saudi Ministry of Education approved the study. The total interviewees numbered 33 students and 18 teachers. The data analysis process was thematic and used inductive techniques, findings across all cases are presented under four major themes. The school’s system and philosophy play a significant role in affecting body weight among Saudi boys in primary schools. This theme includes the teacher’s role, school canteen system, school programmes and the role of the Ministry of Education. For example, in the public and Islamic schools, canteens are important source of income and this directs each school to sell to students what they want regardless of its nutritional value. The school environment, its infrastructure and facilities was the second theme. Unlike the private school, the public and Islamic schools benefited from new, appropriate, designs. Both these two schools have outdoor sports facilities but they are not prepared to maintain and continue physical education lessons in extreme weather conditions. The students’ health behaviours are a further factor affecting body weight among Saudi boys at all types of primary school. This theme includes students’ preferences, society and community. Three factors that exist outside schools can also affect students’ body weight at all types of primary school. These are media, family, and languages. Drawing on these themes, recommendations are made for policy, practice and research.

Published
2017

48. Temporal-Logic-Based Testing Tool Architecture for Dual-Programming Model Systems.

Author

Saad, Salwa, Fadel, Etimad, Alzamzami, Ohoud, Eassa, Fathy, and Alghamdi, Ahmed M.

Subjects
C++, LOGIC design, MESSAGE passing (Computer science), PROGRAMMING languages, SYSTEMS software
Abstract

Today, various applications in different domains increasingly rely on high-performance computing (HPC) to accomplish computations swiftly. Integrating one or more programming models alongside the used programming language enhances system parallelism, thereby improving its performance. However, this integration can introduce runtime errors such as race conditions, deadlocks, or livelocks. Some of these errors may go undetected using conventional testing techniques, necessitating the exploration of additional methods for enhanced reliability. Formal methods, such as temporal logic, can be useful for detecting runtime errors since they have been widely used in real-time systems. Additionally, many software systems must adhere to temporal properties to ensure correct functionality. Temporal logics indeed serve as a formal frame that takes into account the temporal aspect when describing changes in elements or states over time. This paper proposes a temporal-logic-based testing tool utilizing instrumentation techniques designed for a dual-level programming model, namely, Message Passing Interface (MPI) and Open Multi-Processing (OpenMP), integrated with the C++ programming language. After a comprehensive study of temporal logic types, we found and proved that linear temporal logic is well suited as the foundation for our tool. Notably, while the tool is currently in development, our approach is poised to effectively address the highlighted examples of runtime errors by the proposed solution. This paper thoroughly explores various types and operators of temporal logic to inform the design of the testing tool based on temporal properties, aiming for a robust and reliable system. [ABSTRACT FROM AUTHOR]

Published
2024
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49. Weber's Law-based Regularization for Blind Image Deblurring.

Author

Saqib, Malik Najmus, Dawood, Hussain, Alghamdi, Ahmed, and Dawood, Hassan

Subjects
WEBER-Fechner law, COST functions
Abstract

Blind image deblurring aims to recover an output latent image and a blur kernel from a given blurred image. Kernel estimation is a significant step in blind image deblurring and requires a regularization technique to minimize the cost function and the edges of objects to generate a sharp image in a better way. This study proposes a new image regularization technique called Weber's Law Regularization (WLR) based on the Weber law phenomenon. The Weber ratio was used to preserve the edges of small salient objects and to minimize the cost function to obtain a sharp image while minimizing the ringing effect. To validate the WLR, experiments were conducted on benchmark synthetic and real word images and compared with existing state-of-the-art methods. The experimental results showed that WLR can effectively and efficiently deblur images even in the absence of prior knowledge. [ABSTRACT FROM AUTHOR]

Published
2024
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50. Enhanced Skin Cancer Classification using Deep Learning and Nature-based Feature Optimization.

Author

Imran, Talha, Alghamdi, Ahmed S., and Alkatheiri, Mohammed Saeed

Subjects
DEEP learning, TUMOR classification, SKIN cancer, CONVOLUTIONAL neural networks, PATTERN recognition systems, ANT algorithms
Abstract

This paper presents a skin cancer classification model that combines a pre-trained Convolutional Neural Network (CNN) with a nature-inspired feature optimization algorithm. A custom dataset comprising both malignant and benign skin cancer microscopic illustrations is derived from the ISIC dataset of dermoscopic images. Several preprocessing steps are performed on the input pictures, such as histogram equalization, gamma correction, and white balance adjustment, to improve visibility, quality, and make color corrections. Deep feature extraction and pattern recognition are conducted on both enhanced and original dataset images using the pre-trained CNN model EfficientNetB0. As a result of fusing these features, the model can capture rich details from both dataset versions at the same time. Ant Colony Optimization (ACO), a nature-inspired feature selection algorithm is applied to perform model optimization by keeping the most relevant features and discarding the unnecessary ones. The optimized feature vector is then used with various SVM classifier kernels for the skin cancer classification task. The maximum achieved accuracy of the proposed model exceeded 98% through CB-SVM while maintaining an excellent prediction speed and reduced training time. [ABSTRACT FROM AUTHOR]

Published
2024
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