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Enhancing ChatGPT’s Querying Capability with Voice-Based Interaction and CNN-Based Impair Vision Detection Model

Computers, Materials & Continua 2024年第3期78卷 3129-3150页

作者： Awais Ahmad Sohail Jabbar Sheeraz Akram Anand Paul Umar Raza nuha mohammed alshuqayran College of Computer and Information Sciences Imam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudia Arabia 2 School of Computer Science and EngineeringKyungpook National UniversityDaegu41566South Korea 3 Department of EngineeringManchester Metropolitan UniversityManchesterM156BHUK

This paper presents an innovative approach to enhance the querying capability of ChatGPT,a conversational artificial intelligence model,by incorporating voice-based interaction and a convolutional neural network(CNN)-based impaired vision detection *** proposed system aims to improve user experience and accessibility by allowing users to interact with ChatGPT using voice ***,a CNN-based model is employed to detect impairments in user vision,enabling the system to adapt its responses and provide appropriate *** research tackles head-on the challenges of user experience and inclusivity in artificial intelligence(AI).It underscores our commitment to overcoming these obstacles,making ChatGPT more accessible and valuable for a broader *** integration of voice-based interaction and impaired vision detection represents a novel approach to conversational ***,this innovation transcends novelty;it carries the potential to profoundly impact the lives of users,particularly those with visual *** modular approach to system design ensures adaptability and scalability,critical for the practical implementation of these ***,the solution places the user at its *** responses for those with visual impairments demonstrates AI’s potential to not only understand but also accommodate individual needs and preferences.

关键词： Accessibility in conversational AI CNN-based impair vision detection ChatGPT voice-based interaction recommender system

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Improved Multileader Optimization with Shadow Encryption for Medical Images in IoT Environment

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Computers, Materials & Continua 2023年第2期74卷 3133-3149页

作者： Mesfer Al Duhayyim mohammed Maray Ayman Qahmash Fatma S.Alrayes nuha alshuqayran Jaber S.Alzahrani mohammed Alghamdi Abdullah Mohamed Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam Bin Abdulaziz UniversitySaudi Arabia Department of Information Systems College of Computer ScienceKing Khalid UniversityAbhaSaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia Department of Information Systems College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic UniversitySaudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversitySaudi Arabia Department of Information and Technology Systems College of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia Research Centre Future University in EgyptNew Cairo11845Egypt

Nowadays,security plays an important role in Internet of Things(IoT)environment especially in medical services’domains like disease prediction and medical data *** healthcare sector,huge volumes of data are generated on a daily basis,owing to the involvement of advanced health care *** general terms,health care images are highly sensitive to alterations due to which any modifications in its content can result in faulty *** the same time,it is also significant to maintain the delicate contents of health care images during reconstruction ***,an encryption system is required in order to raise the privacy and security of healthcare data by not leaking any sensitive *** current study introduces Improved Multileader Optimization with Shadow Image Encryption for Medical Image Security(IMLOSIE-MIS)technique for IoT *** aim of the proposed IMLOSIE-MIS model is to accomplish security by generating shadows and encrypting them *** do so,the presented IMLOSIE-MIS model initially generates a set of shadows for every input medical ***,shadow image encryption process takes place with the help of Multileader Optimization(MLO)withHomomorphic Encryption(IMLO-HE)technique,where the optimal keys are generated with the help of MLO *** the receiver side,decryption process is initially carried out and shadow image reconstruction process is *** experimentation analysis was carried out on medical images and the results inferred that the proposed IMLOSIE-MIS model is an excellent performer compared to other *** comparison study outcomes demonstrate that IMLOSIE-MIS model is robust and offers high security in IoT-enabled healthcare environment.

关键词： Medical image security image encryption shadow images homomorphic encryption optimal key generation

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Optimal Fuzzy Logic Enabled Intrusion Detection for Secure IoT-Cloud Environment

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Computers, Materials & Continua 2023年第3期74卷 6737-6753页

作者： Fatma S.Alrayes nuha alshuqayran Mohamed K Nour Mesfer Al Duhayyim Abdullah Mohamed Amgad Atta Abdelmageed mohammed Gouse Pasha mohammed Ishfaq Yaseen Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic UniversitySaudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia Research Centre Future University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Recently,Internet of Things(IoT)devices have developed at a faster rate and utilization of devices gets considerably increased in day to day *** the benefits of IoT devices,security issues remain challenging owing to the fact that most devices do not include memory and computing resources essential for satisfactory security ***,IoT devices are vulnerable to different kinds of attacks.A single attack on networking system/device could result in considerable data to data security and *** the emergence of artificial intelligence(AI)techniques can be exploited for attack detection and classification in the IoT *** this view,this paper presents novel metaheuristics feature selection with fuzzy logic enabled intrusion detection system(MFSFL-IDS)in the IoT *** presented MFSFL-IDS approach purposes for recognizing the existence of intrusions and accomplish security in the IoT *** achieve this,the MFSFL-IDS model employs data pre-processing to transform the data into useful ***,henry gas solubility optimization(HGSO)algorithm is applied as a feature selection approach to derive useful feature ***,adaptive neuro fuzzy inference system(ANFIS)technique was utilized for the recognition and classification of intrusions in the ***,binary bat algorithm(BBA)is exploited for adjusting parameters involved in the ANFIS model.A comprehensive experimental validation of the MFSFL-IDS model is carried out using benchmark dataset and the outcomes are assessed under distinct *** experimentation outcomes highlighted the superior performance of the MFSFL-IDS model over recentapproaches with maximum accuracy of 99.80%.

关键词： Cloud computing security fuzzy logic intrusion detection internet of things metaheuristics

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Optimal Bottleneck-Driven Deep Belief Network Enabled Malware Classification on IoT-Cloud Environment

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Computers, Materials & Continua 2023年第2期74卷 3101-3115页

作者： mohammed Maray Hamed Alqahtani Saud S.Alotaibi Fatma S.Alrayes nuha alshuqayran Mrim M.Alnfiai Amal S.Mehanna Mesfer Al Duhayyim Department of Information Systems College of Computer ScienceKing Khalid UniversityAbhaSaudi Arabia Department of Information Systems College of Computer ScienceCenter of Artificial IntelligenceUnit of CybersecurityKing Khalid UniversityAbhaSaudi Arabia Department of Information Systems College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of information systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic UniversitySaudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11845Egypt Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam Bin Abdulaziz UniversitySaudi Arabia

Cloud Computing(CC)is the most promising and advanced technology to store data and offer online services in an effective *** such fast evolving technologies are used in the protection of computerbased systems from cyberattacks,it brings several advantages compared to conventional data protection *** of the computer-based systems that effectively protect the data include Cyber-Physical Systems(CPS),Internet of Things(IoT),mobile devices,desktop and laptop computer,and critical *** software(malware)is nothing but a type of software that targets the computer-based systems so as to launch cyberattacks and threaten the integrity,secrecy,and accessibility of the *** current study focuses on design of Optimal Bottleneck driven Deep Belief Network-enabled Cybersecurity Malware Classification(OBDDBNCMC)*** presentedOBDDBN-CMCmodel intends to recognize and classify the malware that exists in IoT-based cloud *** attain this,Zscore data normalization is utilized to scale the data into a uniform *** addition,BDDBN model is also exploited for recognition and categorization of *** effectually fine-tune the hyperparameters related to BDDBN model,GrasshopperOptimizationAlgorithm(GOA)is *** scenario enhances the classification results and also shows the novelty of current *** experimental analysis was conducted upon OBDDBN-CMC model for validation and the results confirmed the enhanced performance ofOBDDBNCMC model over recent approaches.

关键词： Malware detection security Internet of Things cloud computing machine learning parameter adjustment

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Hematological Alterations in an Eastern Sudanese Chronic Kidney Disease Patient Population

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Open Journal of Urology 2024年第6期14卷 359-367页

作者： mohammed Omer Abaker Gibreel Sundus Kamal Ibrahim Wijdan Abdel Aziz Hassan Manar Yahia Mahjoub Leyla mohammed Kheir Hamid Hibatellah Majzoub Abbas nuha Fouzi mohammed Secretariat of Academic Affairs Port Sudan Ahlia University Port Sudan Sudan Department of Hematology and Immunohematology College of Graduate Studies Port Sudan Ahlia University Port Sudan Sudan

Background: Chronic Kidney Disease (CKD), associated with a slow and progressive loss of kidney function over a period of several years, is an important clinical disaster with an increasing rate of morbidity and mortality especially in the least developed countries. Many hematological parameters are thought to alter dramatically during the course of the disease. These include white blood cells, red blood cells, and platelets. Methods: We tried, retrospectively, to evaluate the peripheral blood hematological alterations in a group of patients undergoing hemodialysis in an eastern Sudan dialysis center to add local medical information. Results: Anemia (Low hemoglobin and hematocrit) was detected in 94% of the patients’ group. Mean Erythrocyte count (3.32vs.4.76 (×109/L)), Hemoglobin concentration (9.4vs.13 (g/dl)), Hematocrit (28.7vs.38.7 (L/L)) and platelet count (296 vs. 238 (×109/L)) were significantly lower in the patients’ group than in the control group (P-values Conclusion: Five out of eight studied parameters (Red cell count, hemoglobin, hematocrit, mean cell hemoglobin concentration, and platelets count) have shown a significant alteration in CKD patients. As the complete blood count (CBC) test is the most utilized test in clinical laboratory practice, these alterations may be considered as early indicators for CKD. Furthermore, all patients with CKD must be routinely checked for these alterations.

关键词： Chronic Kidney Disease Chronic Renal Failure Hematological Alterations CBC Eastern Sudan Hemodialysis

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The Awareness of Jazan Females about the Nutrition Related Effects of Polycystic Ovary Syndrome

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Journal of Biosciences and Medicines 2023年第11期11卷 219-234页

作者： Nagwa Elsheikh Eltayeb Malik Saif Elden Babiker Abdalla Muntaser mohammed Fadoul Alhassen Nusayba Abdelrhman Alageb Fattom J. Sayed nuha Y. Alfaifi Kholod K. Alfaifi Aishah A. Hattan Department of Clinical Nutrition College of Applied Medical Science Jazan University Jazan Saudi Arabia Department of Medical Laboratory Science College of Applied Medical Science Jazan University Jazan Saudi Arabia Department of Diagnostic Radiology College of Applied Medical Science Jazan University Jazan Saudi Arabia

Introduction: Polycystic ovary syndrome (PCOS) is one of the most common endocrine and metabolic disorders in premenopausal women affecting 5% - 10% women in reproductive age. Many studies show that good dietary habits and balanced diet in addition to regular exercise can significantly improve the symptoms of the syndrome. The prevalence rate in the Kingdom of Saudi Arabia reached 42.8%. This study aimed to measure the awareness of Jazan females about the nutrition related effects of polycystic ovary syndrome and investigate the association between age and awareness of nutrition related effect on PCOS. Method: Cross sectional study was conducted during a period from January 9th to February 5th 2023, by a questionnaire used to measure the awareness of female in Jazan region about the nutrition related effects of poly cystic ovary syndrome. Data was collected using Google questionnaire survey and it was randomly distributed to Jazan women from 18 to 50 years old. The questionnaire was about general information about PCOS, nutrition-related effects of PCOS, the effects of eating patterns on PCOS, physical activity, and sleeping. The sample size was 384 women. Results: The total response was about 363 women. The results showed that women in the Jazan region did not have sufficient knowledge about PCOS 51.5% and 63.4% had no knowledge about diet recommendations for PCOS. However, there was awareness about healthy eating patterns that reduce the symptoms of PCOS. The level of awareness of PCOS and its association with age among Jazan women was higher in young adult groups (21 to 29 years old). Conclusion: Based on the results of this study, the level of knowledge about PCOS among Jazan women is insufficient. Also, their awareness about diet and lifestyle interventions was low. There is a relationship between age and awareness of the nutrition-related effects of PCOS. Promoting the role of balanced nutrition and nutritional knowledge is an important r

关键词： PCOS Nutrition Awareness Diet and Lifestyle

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