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Mining the Chatbot Brain to Improve COVID-19 Bot Response Accuracy

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Computers, Materials & Continua 2022年第2期70卷 2619-2638页

作者： Mukhtar Ghaleb Yahya Almurtadha Fahad Algarni Monir abdullah Emad Felemban ali M.Alsharafi Mohamed Othman Khaled Ghilan Department of Information Systems College of Sciences and ArtsUniversity of BishaAl Namas67392Saudi Arabia Department of Computer Science College of Computing and Information TechnologyUniversity of TabukTabuk71491Saudi Arabia Department of Computer Science College of Computing and Information TechnologyUniversity of BishaBisha61922Saudi Arabia Computer Engineering Department Umm Al-Qura UniversityMakkah21955Saudi Arabia Department of Communication Technology and Network Universiti Putra MalaysiaSelangor43400Malaysia Faculty of Public Health and Tropical Medicine Jazan UniversityJazan45142Saudi Arabia

People often communicate with auto-answering tools such as conversational agents due to their 24/7 availability and unbiased ***,chatbots are normally designed for specific purposes and areas of experience and cannot answer questions outside their *** employ Natural Language Understanding(NLU)to infer their *** is a need for a chatbot that can learn from inquiries and expand its area of experience with *** chatbot must be able to build profiles representing intended topics in a similar way to the human brain for fast *** study proposes a methodology to enhance a chatbot’s brain functionality by clustering available knowledge bases on sets of related themes and building representative *** used a COVID-19 information dataset to evaluate the proposed *** pandemic has been accompanied by an“infodemic”of fake *** chatbot was evaluated by a medical doctor and a public trial of 308 real *** obtained and statistically analyzed tomeasure effectiveness,efficiency,and satisfaction as described by the ISO9214 *** proposed COVID-19 chatbot system relieves doctors from answering *** provide an example of the use of technology to handle an infodemic.

关键词： Machine learning text classification e-health chatbot COVID-19 awareness natural language understanding

Deep Image Restoration Model: A Defense Method Against Adversarial Attacks

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Computers, Materials & Continua 2022年第5期71卷 2209-2224页

作者： Kazim ali Adnan N.Quershi Ahmad Alauddin Bin Arifin Muhammad Shahid Bhatti Abid Sohail Rohail hassan Department of Information Technology University of Central PunjabLahore54000Pakistan Department of Communication Technology and Network Faculty of Computer Science and Information TechnologyUniversity Putra MalaysiaSalengor43400Malaysia Department of Computer Science Comsats University IslamabadLahore Campus54000Pakistan Othman Yeop abdullah Graduate School of Business University Utara MalaysiaKuala Lumpur50300Malaysia

These days,deep learning and computer vision are much-growing fields in this modern world of information *** learning algorithms and computer vision have achieved great success in different applications like image classification,speech recognition,self-driving vehicles,disease diagnostics,and many *** success in various applications,it is found that these learning algorithms face severe threats due to adversarial *** examples are inputs like images in the computer vision field,which are intentionally slightly changed or *** changes are humanly *** are misclassified by a model with high probability and severely affects the performance or *** this scenario,we present a deep image restoration model that restores adversarial examples so that the target model is classified correctly *** proved that our defense method against adversarial attacks based on a deep image restoration model is simple and state-of-the-art by providing strong experimental results *** have used MNIST and CIFAR10 datasets for experiments and analysis of our defense *** the end,we have compared our method to other state-ofthe-art defense methods and proved that our results are better than other rival methods.

关键词： Computer vision deep learning convolutional neural networks adversarial examples adversarial attacks adversarial defenses

SDN-Enabled Content Dissemination Scheme for the Internet of Vehicles

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Computers, Materials & Continua 2023年第5期75卷 2383-2396页

作者： Abida Sharif Muhammad Imran Sharif Muhammad Attique Khan Nisar ali abdullah Alqahtani Majed Alhaisoni Ye Jin Kim Byoungchol Chang Department of Computer Science COMSATS University IslamabadPakistan Department of Computer Science HITEC University TaxilaPakistan College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz UniversityAl-KharjSaudi Arabia Computer Sciences Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Science Hanyang UniversitySeoul04763Korea Center for Computational Social Science Hanyang UniversitySeoul04763Korea

The content-centric networking(CCN)architecture allows access to the content through name,instead of the physical location where the content is stored,which makes it a more robust and flexible content-based ***,in CCN,the broadcast nature of vehicles on the Internet of Vehicles(IoV)results in latency and network *** IoVbased content distribution is an emerging concept in which all the vehicles are connected via the *** to the high mobility of vehicles,however,IoV applications have different network requirements that differ from those of many other networks,posing new *** this,a novel strategy mediator framework is presented in this paper for managing the network resources ***-defined network(SDN)controller is deployed for improving the routing flexibility and facilitating in the interinteroperability of heterogeneous devices within the *** to the limited memory of edge devices,the delectable bloom filters are used for caching and ***,the proposed scheme is compared with the existing variants for validating its effectiveness.

关键词： Internet of vehicles(IOV) content dissemination multi mediator data traffic management

Oral Health Status and Gingival Response to Three Different Restorative Materials among Saudi Patients: A Clinical &Histopathological Study

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International Journal of Clinical Medicine 2019年第2期10卷 78-90页

作者： Mohammed M. A. abdullah Al-Abdaly hassan Mohammed Al-Harthi Salem Mohammed Al-Harthi Redwan abdullah ali Almalki Periodontics and Community Dental Sciences Department College of Dentistry King Khalid University Abha Saudi Arabia College of Dentistry King Khalid University Abha Saudi Arabia

Background: The correlation between oral health and dental restoration is fundamental. For the gingival and periodontal tissues to stay healthy, dental restoration should be in regularity with the surrounding tissues. This study aims to assess the oral health status and histopathological gingival response to three different restorative materials among Saudi patients. Methods: The study groups consist of 240 patients (50% males and 50% females), aged 18 - 45, with inclusion and exclusion criteria in the study. Participants are divided into three equal groups: those with composite resin restorations, those with amalgam restorations and those with glass ionomer restorations. Biopsies were taken from adjacent gingival tissues. Clinical parameters were determined by: plaque index (PLI), gingival index (GI) and clinical attachment loss (CAL). All data were collected and evaluated by through statistical analysis. Results: The clinical findings of the current study revealed that amalgam restorations produce a higher means of PLI, GI and CAL compared with composite resin restorations and glass ionomer restorations, but not insignificant levels, except CAL (p = 0.004*). As for histopathological findings, there were significant differences in gingival tissue response to amalgam restorations, composite resin restorations and glass ionomer cement fillings, where there were statistically significant differences in numbers of chronic inflammatory cells (p Conclusion: At the end of the present study, we concluded that the amalgam restorations are less biocompatible compared to composite resin restorations and glass ionomer restorations.

关键词： Gingival Response Histopathological Study Oral Health Status

Hybrid Sine Cosine and Stochastic Fractal Search for Hemoglobin Estimation

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Computers, Materials & Continua 2022年第8期72卷 2467-2482页

作者： Marwa M.Eid Fawaz Alassery Abdelhameed Ibrahim Bandar abdullah Aloyaydi Hesham Arafat ali Shady Y.El-Mashad Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Mechanical Engineering Department Qassim UniversityBuraidah51452Saudi Arabia Department of Computer Systems Engineering Faculty of Engineering at ShoubraBenha UniversityEgypt

The sample’s hemoglobin and glucose levels can be determined by obtaining a blood sample from the human body using a needle and analyzing ***(HGB)is a critical component of the human body because it transports oxygen from the lungs to the body’s tissues and returns carbon dioxide from the tissues to the *** the HGB level is a critical step in any blood analysis *** often indicate whether a person is anemic or polycythemia *** ensemble models by combining two or more base machine learning(ML)models can help create a more improved *** purpose of this work is to present a weighted average ensemble model for predicting hemoglobin *** optimization method is utilized to get the ensemble’s optimum *** optimum weight for this work is determined using a sine cosine algorithm based on stochastic fractal search(SCSFS).The proposed SCSFS ensemble is compared toDecision Tree,Multilayer perceptron(MLP),Support Vector Regression(SVR)and Random Forest Regressors as model-based approaches and the average ensemble *** SCSFS results indicate that the proposed model outperforms existing models and provides an almost accurate hemoglobin estimate.

关键词： Sine cosine optimization metaheuristics optimization hemoglobin estimation weight average ensemble

Outcomes of staged hepatectomies for liver malignancy

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World Journal of Hepatology 2019年第6期11卷 513-521页

作者： Naif A Albati ali A Korairi Ibrahim Al Hasan Helayel K Almodhaiberi abdullah A Algarni Hepatobiliary and Liver Transplant Unit Department of General Surgery Prince Sultan Military Medical City

Liver malignancies are the fifth most common cause of death *** intervention with curative intent is the treatment of choice for liver tumors as it provides long-term ***,only 20%of patients with metastatic liver lesions can be managed by curative liver *** most of the cases,hepatectomy is not feasible because of insufficient future liver remnant(FLR).Two-stage hepatectomy is advocated to achieve liver resection in a patient who is considered to not be a candidate for *** of staged hepatectomy include conventional two-stage hepatectomy,portal vein embolization,and associating liver partition and portal vein ligation for a staged *** success is high for each of these procedures but variable between *** the procedures have been reported as being effective in achieving a satisfactory FLR and completing the second-stage ***,the overall survival and disease-free survival rates have improved significantly for patients who were otherwise considered nonresectable;yet,an increase in the morbidity and mortality rates has been *** suggest that this type of procedure should be carried out in high-flow centers and through a multidisciplinary *** experienced surgeon is key to the success of those interventions.

关键词： Staged hepatectomy Portal vein embolization Portal vein ligation Colorectal liver metastasis Hepatocellular carcinoma Associated liver partition and portal vein ligation for staged hepatectomy

Ameliorative properties of Iranian Trigonella foenum-graecum L. seeds and Punica granatum L. peel extracts in streptozotocin-induced experimental diabetic guinea pigs

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Asian Pacific Journal of Tropical Biomedicine 2017年第3期7卷 234-239页

作者： Nabil Abdel Salam Ahmed Hasona Mohammed Ahmed Qumani Turki Ahmed Alghassab Muath Abdulrahman Alghassab abdullah ali Alghabban Department of Biochemistry College of MedicineHa'il UniversityHa'ilSaudi Arabia Department of Chemistry Faculty of ScienceBeni-Suef UniversityBeni-SuefEgypt Department of Pharmacology College of MedicineHa'il UniversityHa'ilSaudi Arabia

Objective: To assess the ameliorative properties of Iranian Trigonella foenum-graecum L.(T. foenum-graecum) seeds and Punica granatum L.(P. granatum) peel extracts against streptozotocin-induced diabetes in male guinea ***: Sixty guinea pigs were divided into six groups(10 guinea pigs per group).Group 1 consisted of normal animals. Groups 2 and 3 were treated with Iranian T. foenum-graecum seeds and P. granatum peel extract alone, respectively. Group 4 was treated with streptozotocin only; whereas Groups 5 and 6 receiving streptozotocin were treated with Iranian T. foenum-graecum seeds and P. granatum peel extract, *** animals were treated for 30 days, and the body weight, blood and liver biochemical parameters were ***: Guinea pigs exposed to streptozotocin showed an alteration in body weight gain, fasting glucose level, kidney function parameters(blood urea nitrogen and creatinine) as well as decreased serum and hepatic total protein level. In addition, it increased the cholesterol and triglyceride level, while decreasing the hepatic glucose-6 phosphate dehydrogenase activity, glycogen, glutathione content and hepatic catalase activity. Oral treatment with T. foenum-graecum seeds and P. granatum peel extracts revealed significant protective properties with respect to body weight gain and other biochemical parameters ***: The Iranian T. foenum-graecum seeds and P. granatum peel extracts are significantly potent in ameliorating diabetic condition induced by streptozotocin and improving various biochemical parameters in serum and liver of guinea pigs.

关键词： Diabetes Iranian Trigonella foenum-graecum Seeds Punica granatum Peel Streptozotocin

An Efficient Automated Technique for Classification of Breast Cancer Using Deep Ensemble Model

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Computer Systems Science & Engineering 2023年第7期46卷 897-911页

作者： Muhammad Zia Ur Rehman Jawad Ahmad Emad Sami Jaha abdullah Marish ali Mohammed A.Alzain Faisal Saeed Department of Electrical Engineering HITEC UniversityTaxila47080Pakistan School of Computing Edinburgh Napier UniversityEdinburghEH105DTUK Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia DAAI Research Group Department of Computing and Data ScienceSchool of Computing and Digital TechnologyBirmingham City University15 Bartholomew RowBirminghamB55JUUK

Breast cancer is one of the leading cancers among *** has the second-highest mortality rate in women after lung *** detection,especially in the early stages,can help increase survival ***,manual diagnosis of breast cancer is a tedious and time-consuming process,and the accuracy of detection is reliant on the quality of the images and the radiologist’s ***,computer-aided medical diagnosis has recently shown promising results,leading to the need to develop an efficient system that can aid radiologists in diagnosing breast cancer in its early *** research presented in this paper is focused on the multi-class classification of breast *** deep transfer learning approach has been utilized to train the deep learning models,and a pre-processing technique has been used to improve the quality of the ultrasound *** proposed technique utilizes two deep learning models,Mobile-NetV2 and DenseNet201,for the composition of the deep ensemble *** learning models are fine-tuned along with hyperparameter tuning to achieve better ***,entropy-based feature selection is *** cancer identification using the proposed classification approach was found to attain an accuracy of 97.04%,while the sensitivity and F1 score were 96.87%and 96.76%,*** performance of the proposed model is very effective and outperforms other state-of-the-art techniques presented in the literature.

关键词： Breast cancer image enhancement ensemble model transfer learning feature selection

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上下文感知推荐系统：挑战和机遇（英文）

电子科技大学学报 2019年第5期48卷 655-673页

作者： ali Waqar 邵杰 KHAN abdullah Aman TUMRANI Saifullah 电子科技大学计算机科学与工程学院成都611731 拉合尔大学信息技术学院拉合尔巴基斯坦54000

该文梳理了社会和科学领域中上下文感知推荐系统的主要概念、技术、挑战和未来趋势;其次,分类介绍了可用于基于上下文的推荐的一系列技术和主要框架。除了经典的基于内容、基于协同过滤和基于矩阵分解的技术之外,调研了最近的研究方向,... 详细信息

该文梳理了社会和科学领域中上下文感知推荐系统的主要概念、技术、挑战和未来趋势;其次,分类介绍了可用于基于上下文的推荐的一系列技术和主要框架。除了经典的基于内容、基于协同过滤和基于矩阵分解的技术之外,调研了最近的研究方向,即基于深度学习和基于模糊逻辑的方法。最后,描述了在推荐过程中利用上下文信息的潜在研究机会。

关键词：推荐系统上下文感知上下文获取上下文整合