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| 1 | Science and Technology Networks: A Helping Hand to Boost Implementation of the Sendai Framework for Disaster Risk Reduction 2015–2030?显示文摘The Sendai Framework for Disaster Risk Reduction 2015–2030 underlines the importance of Science and Technology(S&T) and S&T networks for effective disaster risk reduction(DRR). The knowledge of existing S&T networks and their exact role in DRR,however, is limited. This opinion piece initiates a discussion on the role of S&T networks in the implementation of the Sendai Framework. The article highlights that current practice is oriented towards a narrative that emphasizes the potential of S&T for DRR and stresses a collaborative approach delivered through networks. But a true understanding of whether and how S&T networks can mobilize and enable S&T for DRR is missing. We call for a review of existing S&T networks for DRR and the development of good practice guidelines on S&T networks for DRR. This review should include knowledge on how to overcome common challenges and maximize the benefits, along with a framework for successful evaluation of such networks.This knowledge would provide much needed guidance for existing and emerging networks. | Robert sakic Trogrlic Lydia Cumiskey Annisa Triyanti Melanie J.Duncan Nuha Eltinay Rick J.Hogeboom Mansi Jasuja Chinaporn Meechaiya Christina J.Pickering Virginia Murray | 2017 | International Journal of Disaster Risk Science2017，8，1： | 2 |
| 2 | Hepatoprotective effect of Lepidium sativum against carbontetrachloride-induced damage in rats显示文摘 | Afaf I Abuelgasim Nuha H S Mohammed A H | | 0，，： | 1 |
| 3 | Using Web-base computer graphics to teach surgery显示文摘 | Brodlie Ken El-khalili Nuha Li Ying | 2000 | Computer & Graphics (S0097-8493)2000，24，： | 1 |
| 4 | Use of group-specific and RAPD-PCR analyses for rapid differentiation of Lactobacilhs Strains from Probiotic yogurts显示文摘 | Ulrich Schillinger Nuha M Yousif K Lilijana Sesar Charles A Franz P | 2003 | Current Microbiology2003，47，： | 1 |
| 5 | Performance Evaluation of Crumb Rubber Modified Stone Mastic Asphalt Pavement in Malaysia显示文摘 | Nuha Salim Mashaan Asim H Ali Suhana Koting | 2013 | Advances in Materials Science and Engineering2013，，2013： | 1 |
| 6 | Use of Group-specific and RAPD-PCtL Analyses for Rapid Differentiation of Lactobacillus Strains from Probiotic Yogurts 显示文摘 | ULRICH S NUHA M YOUSIF K | 2003 | Current Microbiology2003，47，： | 1 |
| 7 | Molecular targeted therapies for cancer: Sorafenib mono-therapy andits combination with other therapies (Review)显示文摘 | Nuha Ibrahim Yan Yu William Walsh Jia-Lin Yang | 2012 | Oncology Reports2012，，5： | 1 |
| 8 | A Multimodal Discourse Analysis of Saudi Arabic Television Commercials显示文摘This study provides a multimodal discourse analysis of Saudi Arabic TV commercials from a linguistic and visual semiotic perspective,linking communication,language,and culture.The study draws on pragmatics,semiotics,and language and culture,within the framework of discourse analysis.The data consisted of five commercials of personal care items,with the analysis focusing on figurative linguistic elements,including metaphorical expressions and personification,as well as visual elements,including visual metaphors and semiotic symbols.The analysis is based on Lakoff and Johnson’s(2003)conceptual metaphor theory,Saussure’s(1966)theory of semiology,and Grice’s(1975)theory of conversational implicatures.The findings contribute to the existing literature on visual and linguistic metaphors and could serve as a foundation for future studies to examine how the interaction between language and visuals in advertising is represented across cultures.It could also have implications for the practice of advertising in international business and marketing communication. | Nuha Khalid Alsalem | 2020 | Language and Semiotic Studies2020，6，3： | 1 |
| 9 | Hepatoprotective effect of Le- pidium sativum against carbontetrachloride induced damage in rats 显示文摘 | Afar I Abuelgasim Nuha H S | 2008 | Res J Animal Veterinary Sci2008，3，： | 1 |
| 10 | Optimal Bottleneck-Driven Deep Belief Network Enabled Malware Classification on IoT-Cloud Environment显示文摘Cloud Computing(CC)is the most promising and advanced technology to store data and offer online services in an effective manner.When such fast evolving technologies are used in the protection of computerbased systems from cyberattacks,it brings several advantages compared to conventional data protection methods.Some 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 systems.Malicious 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 information.The current study focuses on design of Optimal Bottleneck driven Deep Belief Network-enabled Cybersecurity Malware Classification(OBDDBNCMC)model.The presentedOBDDBN-CMCmodel intends to recognize and classify the malware that exists in IoT-based cloud platform.To attain this,Zscore data normalization is utilized to scale the data into a uniform format.In addition,BDDBN model is also exploited for recognition and categorization of malware.To effectually fine-tune the hyperparameters related to BDDBN model,GrasshopperOptimizationAlgorithm(GOA)is applied.This scenario enhances the classification results and also shows the novelty of current study.The experimental analysis was conducted upon OBDDBN-CMC model for validation and the results confirmed the enhanced performance ofOBDDBNCMC model over recent approaches. | Mohammed Maray Hamed Alqahtani Saud S.Alotaibi Fatma S.Alrayes Nuha Alshuqayran Mrim M.Alnfiai Amal S.Mehanna Mesfer Al Duhayyim | 2023 | Computers, Materials & Continua2023，，2： | 0 |
| 11 | Improved Multileader Optimization with Shadow Encryption for Medical Images in IoT Environment显示文摘Nowadays,security plays an important role in Internet of Things(IoT)environment especially in medical services’domains like disease prediction and medical data storage.In healthcare sector,huge volumes of data are generated on a daily basis,owing to the involvement of advanced health care devices.In general terms,health care images are highly sensitive to alterations due to which any modifications in its content can result in faulty diagnosis.At the same time,it is also significant to maintain the delicate contents of health care images during reconstruction stage.Therefore,an encryption system is required in order to raise the privacy and security of healthcare data by not leaking any sensitive data.The current study introduces Improved Multileader Optimization with Shadow Image Encryption for Medical Image Security(IMLOSIE-MIS)technique for IoT environment.The aim of the proposed IMLOSIE-MIS model is to accomplish security by generating shadows and encrypting them effectively.To do so,the presented IMLOSIE-MIS model initially generates a set of shadows for every input medical image.Besides,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 algorithm.On the receiver side,decryption process is initially carried out and shadow image reconstruction process is conducted.The 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 models.The comparison study outcomes demonstrate that IMLOSIE-MIS model is robust and offers high security in IoT-enabled healthcare environment. | Mesfer Al Duhayyim Mohammed Maray Ayman Qahmash Fatma S.Alrayes Nuha Alshuqayran Jaber S.Alzahrani Mohammed Alghamdi Abdullah Mohamed | 2023 | Computers, Materials & Continua2023，，2： | 0 |
| 12 | Optimal Fuzzy Logic Enabled Intrusion Detection for Secure IoT-Cloud Environment显示文摘Recently,Internet of Things(IoT)devices have developed at a faster rate and utilization of devices gets considerably increased in day to day lives.Despite 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 operation.Consequently,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 privacy.But the emergence of artificial intelligence(AI)techniques can be exploited for attack detection and classification in the IoT environment.In this view,this paper presents novel metaheuristics feature selection with fuzzy logic enabled intrusion detection system(MFSFL-IDS)in the IoT environment.The presented MFSFL-IDS approach purposes for recognizing the existence of intrusions and accomplish security in the IoT environment.To achieve this,the MFSFL-IDS model employs data pre-processing to transform the data into useful format.Besides,henry gas solubility optimization(HGSO)algorithm is applied as a feature selection approach to derive useful feature vectors.Moreover,adaptive neuro fuzzy inference system(ANFIS)technique was utilized for the recognition and classification of intrusions in the network.Finally,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 aspects.The experimentation outcomes highlighted the superior performance of the MFSFL-IDS model over recentapproaches with maximum accuracy of 99.80%. | Fatma S.Alrayes Nuha Alshuqayran Mohamed K Nour Mesfer Al Duhayyim Abdullah Mohamed Amgad Atta Abdelmageed Mohammed Gouse Pasha Mohammed Ishfaq Yaseen | 2023 | Computers, Materials & Continua2023，，3： | 0 |
| 13 | Formation and Biomimetic Deposition of Bone-like Hydroxyapatite on Wollastonite-gypsum Composites显示文摘 | Yaser Greish Nuha Attia Abdel-Hamid Mourad | 2018 | Journal of Bionic Engineering2018，15，5： | 0 |
| 14 | Enhancing ChatGPT’s Querying Capability with Voice-Based Interaction and CNN-Based Impair Vision Detection Model显示文摘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 model.The proposed system aims to improve user experience and accessibility by allowing users to interact with ChatGPT using voice commands.Additionally,a CNN-based model is employed to detect impairments in user vision,enabling the system to adapt its responses and provide appropriate assistance.This 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 audience.The integration of voice-based interaction and impaired vision detection represents a novel approach to conversational AI.Notably,this innovation transcends novelty;it carries the potential to profoundly impact the lives of users,particularly those with visual impairments.The modular approach to system design ensures adaptability and scalability,critical for the practical implementation of these advancements.Crucially,the solution places the user at its core.Customizing responses for those with visual impairments demonstrates AI’s potential to not only understand but also accommodate individual needs and preferences. | Awais Ahmad Sohail Jabbar Sheeraz Akram Anand Paul Umar Raza Nuha Mohammed Alshuqayran | 2024 | Computers, Materials & Continua2024，78，3： | 0 |
| 15 | Linguistic Variations and Use of the 21st Century Arabicisation of English显示文摘 | Nuha Suleiman AI-Shurafa | 2013 | US-China Foreign Language2013，11，9： | 0 |
| 16 | Simultaneous determination of nortriptyline hydrochloride and fluphenazine hydrochloride in microgram quantities from low dosage forms by liquid chromatography-UV detection显示文摘A novel method for the simultaneous high-performance liquid chromatographic determination of nortriptyline hydrochloride and fluphenazine hydrochloride was developed and validated. Fluvastatin sodium was used as internal standard. The determination was performed on a Hypersil Gold C8 column (250 mm 4.6 mm i.d., 5 mm particle size) at 25 ℃; the mobile phase, consisting of a mixture of formic acid (0.1 M, pH 2.16)-methanol (33:67, v/v), was delivered at a flow rate of 1.1 mL/min and detector wavelength at 251 nm. The retention time of nortriptyline, fluphenazine and fluvastatin was found to be 5.11, 8.05 and 11.38 min, respectively. Linearity ranges were 5.0-1350.0 and 10.0-1350.0 mg/ mL with limit of detection values of 0.72 and 0.31 mg/mL, for nortriptyline and fluphenazine, respectively. Results of assay and recovery studies were statistically evaluated for its accuracy and precision. Correlation coefficients (r2) of the regression equations were greater than 0.999 in all cases. According to the validation results, the proposed method was found to be specific, accurate, precise and could be applied to the simultaneous quantitative analysis of nortriptyline and fluphenazine. | Safwan Ashour Nuha Kattan | 2012 | Journal of Pharmaceutical Analysis2012，2，6： | 0 |
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