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Planar Scintigraphic Images Denoising

Open Journal of Medical Imaging 2013年第4期3卷 116-124页

作者： fatma makhlouf Hatem Besbes Nawres Khalifa Chokri Ben Amar Basel Solaiman Department Image and Information Processing Technopole Brest-Iroise Bretagne France Higher Institute of Medical Technology of Tunis University of Tunis El Manar Tunis Tunisia Research Group on Intelligent Machines University of Sfax National Engineering School of Sfax Sfax Tunisia Research Unit of Biophysics Faculty of Medicine of Tunis Tunis Tunisia

Scintigraphic images are generally affected by a Poisson type random noise which diminishes qualitatively and quantitatively the images. Restoration techniques aim to “find” an object from one (or several) degraded observation(s). The objective of the restoration is then to produce an image closer to the physical reality. So that the restoration is successful, it is very useful to know the nature of degradation. In this work, we present a planar scintigraphic acquisition chain modeling. This model takes into account the Poisson noise and its stationarity aspect. Then, we present a comparative study of the multi-resolution methods used to reduce the noise in scintigraphic images. Scintigraphy is a tool for exploring functionally several pathologies: the ventricular ejection fraction, the renal clearance and the thyroid activity. Given the fact that scintigraphic images are strongly affected by noise, the objective in this work is to enhance scintigraphic images for a reliable diagnosis and better orientation and understanding of the pathological phenomenon. This paper focuses on two main parts: the first deals with the degradation of model while the second takes into consideration the comparison of the multi-resolution methods for assessing the quality of scintigraphic images to reduce noise using wavelet, contourlet, curvelet, ridgelet and bandelet transformations.

关键词： Poisson-Noise Scintigraphy Acquisition Wavelet Contourlet Curvelet Ridgelet Bandelet

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Nitrogen mineralization in the oldest climax communities in the eastern Mediterranean region

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Journal of Forestry Research 2024年第1期35卷 213-228页

作者： fatma Selcen Sakar Gürcan Güleryüz Department of Biology Section Ecology GörükleGraduate School of Natural and Applied ScienceUniversity of Bursa Uludağ16059 NilüferBursaTurkey Department of Biology Section Ecology GörükleFaculty of Science and ArtsUniversity of Bursa Uludağ16059 NilüferBursaTurkey

In this study,we investigated how tree species affect N mineralization in connection to some soil properties and seconder metabolite levels of litter,in the soil of the old-est native forest *** the oldest pure communi-ties of Pinus nigra(PN),Fagus orientalis(FO),and Abies bornmuelleriana(AB)in the mountain range of Mount Uludağ,Bursa,Turkey,annual net yield and N mineraliza-tion in the 0-5-and 5-20-cm soil layers were determined in a field incubation study over 1 *** locations were chosen from 1300 to 1600 m a.s.l.,and moisture content(%),pH,water-holding capacity(%),organic C,total N,and C/N ratio,and annual net mineral N yield of the soil and hydro-lyzed tannic acid and total phenolic compounds in litter were compared for these forest *** had the highest annual net Nmin yield(43.9±4.8 kg ha^(-1) a^(-1)),*** the lowest(30.5±4.2 kg ha^(-1) a^(-1)).Our findings show that in the oldest forest ecosystems,the seasonal soil moisture content and tree species play an essential role in N cycling and that hydrolyzed tannic acids and total phenolic compounds effectively control N *** acid and total phenolics in the litter were found to inhibit nitrification,but total phenolics were found to stimulate ammonification.

关键词： Oldest forest communities Nitrogen mineralization Nitrification Tannic acid Total phenolic Litter

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Exploring Sequential Feature Selection in Deep Bi-LSTM Models for Speech Emotion Recognition

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Computers, Materials & Continua 2024年第2期78卷 2689-2719页

作者： fatma Harby Mansor Alohali Adel Thaljaoui Amira Samy Talaat Computer Science Department Future Academy-Higher Future Institute for Specialized Technological StudiesCairo12622Egypt Department of Computer Science and Information College of Science at Zulfi Majmaah UniversityP.O.Box 66Al-Majmaah11952Saudi Arabia Preparatory Institute for Engineering Studies of Gafsa ZarrougGafsa2112Tunisia Computers and Systems Department Electronics Research InstituteCairo12622Egypt

Machine Learning(ML)algorithms play a pivotal role in Speech Emotion Recognition(SER),although they encounter a formidable obstacle in accurately discerning a speaker’s emotional *** examination of the emotional states of speakers holds significant importance in a range of real-time applications,including but not limited to virtual reality,human-robot interaction,emergency centers,and human behavior *** identifying emotions in the SER process relies on extracting relevant information from audio *** studies on SER have predominantly utilized short-time characteristics such as Mel Frequency Cepstral Coefficients(MFCCs)due to their ability to capture the periodic nature of audio signals *** these traits may improve their ability to perceive and interpret emotional depictions appropriately,MFCCS has some *** this study aims to tackle the aforementioned issue by systematically picking multiple audio cues,enhancing the classifier model’s efficacy in accurately discerning human *** utilized dataset is taken from the EMO-DB database,preprocessing input speech is done using a 2D Convolution Neural Network(CNN)involves applying convolutional operations to spectrograms as they afford a visual representation of the way the audio signal frequency content changes over *** next step is the spectrogram data normalization which is crucial for Neural Network(NN)training as it aids in faster *** the five auditory features MFCCs,Chroma,Mel-Spectrogram,Contrast,and Tonnetz are extracted from the spectrogram *** attitude of feature selection is to retain only dominant features by excluding the irrelevant *** this paper,the Sequential Forward Selection(SFS)and Sequential Backward Selection(SBS)techniques were employed for multiple audio cues features ***,the feature sets composed from the hybrid feature extraction methods are fed into the deep Bidirectional Long Short

关键词： Artificial intelligence application multi features sequential selection speech emotion recognition deep Bi-LSTM

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Time-varying nexus and causality in the quantile between Google investor sentiment and cryptocurrency returns

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Blockchain(Research and Applications) 2024年第2期5卷 1-12页

作者： fatma Ben Hamadou Taicir Mezghani Mouna Boujelbene Abbes Faculty of Economics and Management of Sfax Laboratory URECASfax UniversityBP1169.3029SfaxTunisia

Understanding the interplay between investor sentiment and cryptocurrency returns has become a critical area of ***,this study aims to uncover the role of Google investor sentiment on cryptocurrency returns(including Bitcoin,Litecoin,Ethereum,and Tether),especially during the 2017-18 bubble(January 01,2017,to December 31,2018)and the COVID-19 pandemic(January 01,2020,to March 15,2022).To achieve this,we use two techniques:quantile causality and wavelet ***,the quantile causality test revealed that investors’optimistic sentiments have notably higher cryptocurrency returns,whereas pessimistic sentiments have significantly opposite ***,the wavelet coherence analysis shows that co-movement between investor sentiment and Tether cannot be considered *** result supports the role of Tether as a stablecoin in portfolio diversification *** fact,the findings will help investors improve the accuracy of cryptocurrency return forecasts in times of stressful events and pave the way for enhanced decision-making utility.

关键词： Cryptocurrency COVID-19 pandemic Wavelet coherence Causality-in-quantile approach Google trends

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A survey on automatic dashboard recommendation systems

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Visual Informatics 2024年第1期8卷 67-79页

作者： Praveen Soni Cyril de Runz fatma Bouali Gilles Venturini LIFAT University of Tours64 avenue Jean PortalisTours37200France IUT C University of Lille53 Rue de l’AlmaRoubaix59100France

This paper presents a survey on automatic or semi-automatic recommendation systems that help users create *** starts by showing the important role that dashboards play in data science,and gives an informal definition of dashboards,i.e.,a set of visualizations possibly with linkage,a screen layout and user *** are mainly interested in systems that use a fully or partially automatic mechanism to recommend dashboards to *** automation includes the suggestion of data and visualizations,the optimization of the layout and the use of user *** position our work with respect to existing *** from a set of over 1000 papers,we have selected and analyzed 19 papers/systems along several *** main dimensions were the set of considered visualizations,the suggestion method,the utility/objective functions,the layout,and the user *** conclude by highlighting the main achievements in this domain and by proposing perspectives.

关键词： Automatic visualization Dashboard recommendation Multiple view interfaces

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Phenolic Profile and Volatiles of in vitro Propagated Lavandula angustifolia ***

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Phyton-International Journal of Experimental Botany 2024年第3期93卷 427-444页

作者： Mir Abdullatif Yahya fatma Tunali Dilek Killi Atalay Sökmen Biotechnology Department Konya Food and Agriculture UniversityKonya42080Türkiye Plant Production and Technologies Department Konya Food and Agriculture UniversityKonya42080Türkiye

An effective in vitro propagation protocol was designed for Lavandula angustifolia Miller,a medicinal aromatic plant that is a prominent source of volatile organic compounds(VOCs).Murashige and Skoog media were supplemented with various concentrations of Plant Growth Regulators(PGRs),and the growth parameters of the nodal segments were *** explants formed callus when they were supplemented with 2 mg/L of 6-Benzylaminopurine(BAP).The superior hormonal concentration of Murashige and Skoog(MS)media for the proliferation of shoots from callus cultures(39.33%)was 5 mg/L of 2-Isopentenyl adenine(2iP),and the favorable media for the growth of *** callus cultures was 1 and 2 mg/L of BAP,with a 98%for-mation rate in each *** callus cultures and in vitro propagated *** seedlings obtained from var-ious PGR concentrations of MS media were exposed to qualitative and quantitative analysis in terms of phenolic proﬁles,ﬂavonoids,High-performance liquid chromatography(HPLC)analysis of phenolic acids,and headspace-SPME analysis for *** analysis revealed that micropropagated seedlings grown in media containing 1 mg/L of 6-Furfurylaminopurine(KIN)accumulated the highest yield(11.95±0.01 mg GAE/g)of phenolic *** contrast,the lowest concentration(2.17±0.04 mg GAE/g)was detected in 0.5 mg/L of BAP+0.5 mg/L of Naphthaleneacetic acid(NAA)*** plantlets grown in 0.5 mg/L of BAP+0.5 mg/L of NAA media showed the highestﬂavonoid yield(31.67±0.06μg/g QE/g).In contrast,callus samples exhibited the lowest yield(11.59±0.02μg/g QE/g)ofﬂavonoids in MS media supplemented with a concentration of 0.5 mg/L of *** analysis revealed the variability of phenolic acid contents within the callus cultures as well as plantlets,with gallic acid,4-OH benzoic acid,chlorogenic acid,vanillic acid,caffeic acid,cinnamic acid,and rosmarinic acid being the prominent *** presence of twenty-two chemicals was revealed by headspace-SPME ***

关键词： Lavender indirect organogenesis micropropagation This

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Aggravation of Cancer,Heart Diseases and Diabetes Subsequent to COVID-19 Lockdown via Mathematical Modeling

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Computer Modeling in Engineering & Sciences 2024年第7期140卷 485-512页

作者： fatma Nese Efil Sania Qureshi Nezihal Gokbulut Kamyar Hosseini Evren Hincal Amanullah Soomro Near East University Department of MathematicsNicosia99010North Cyprus Mehran University of Engineering and Technology Department of Basic Sciences and Related StudiesJamshoro76090Pakistan Department of Computer Science and Mathematics Lebanese American UniversityP.O.Box 13-5053BeirutLebanon Near East University Mathematics Research CenterNicosia99010North Cyprus

The global populationhas beenandwill continue to be severely impacted by theCOVID-19 *** primary objective of this research is to demonstrate the future impact of COVID-19 on those who suffer from other fatal conditions such as cancer,heart disease,and ***,using ordinary differential equations(ODEs),two mathematical models are developed to explain the association between COVID-19 and cancer and between COVID-19 and diabetes and heart *** that,we highlight the stability assessments that can be applied to these *** analysis is used to examine how changes in certain factors impact different aspects of *** sensitivity analysis showed that many people are still nervous about seeing a doctor due to COVID-19,which could result in a dramatic increase in the diagnosis of various ailments in the years to *** correlation between diabetes and cardiovascular illness is also illustrated *** effects of smoking and obesity are also found to be significant in disease *** fitting is also provided for interpreting the relationship between real data and the results of *** people,in particular,need tomonitor their health conditions closely and practice heart health *** with heart diseases should undergo regular checks so that they can protect themselves from diabetes and take some precautions including suitable *** main purpose of this study is to emphasize the importance of regular checks,to warn people about the effects of COVID-19(including avoiding healthcare centers and doctors because of the spread of infectious diseases)and to indicate the importance of family history of cancer,heart diseases and *** provision of the recommendations requires an increase in public consciousness.

关键词： COVID-19 mathematical modeling cancer diabetes heart diseases sensitivity analysis

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Network Security Enhanced with Deep Neural Network-Based Intrusion Detection System

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Computers, Materials & Continua 2024年第7期80卷 1457-1490页

作者： fatma S.Alrayes Mohammed Zakariah Syed Umar Amin Zafar Iqbal Khan Jehad Saad Alqurni Information Systems Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia College of Computer and Information Sciences King Saud UniversityRiyadh11362Saudi Arabia College of Computer and Information Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Department of Educational Technologies College of EducationImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia

This study describes improving network security by implementing and assessing an intrusion detection system(IDS)based on deep neural networks(DNNs).The paper investigates contemporary technical ways for enhancing intrusion detection performance,given the vital relevance of safeguarding computer networks against harmful *** DNN-based IDS is trained and validated by the model using the NSL-KDD dataset,a popular benchmark for IDS *** model performs well in both the training and validation stages,with 91.30%training accuracy and 94.38%validation ***,the model shows good learning and generalization capabilities with minor losses of 0.22 in training and 0.1553 in ***,for both macro and micro averages across class 0(normal)and class 1(anomalous)data,the study evaluates the model using a variety of assessment measures,such as accuracy scores,precision,recall,and F1 *** macro-average recall is 0.9422,the macro-average precision is 0.9482,and the accuracy scores are ***,macro-averaged F1 scores of 0.9245 for class 1 and 0.9434 for class 0 demonstrate the model’s ability to precisely identify anomalies *** research also highlights how real-time threat monitoring and enhanced resistance against new online attacks may be achieved byDNN-based intrusion detection systems,which can significantly improve network *** study underscores the critical function ofDNN-based IDS in contemporary cybersecurity procedures by setting the foundation for further developments in this *** research aims to enhance intrusion detection systems by examining cooperative learning techniques and integrating up-to-date threat knowledge.

关键词： Machine-Learning Deep-Learning intrusion detection system security privacy deep neural network NSL-KDD Dataset

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Revolutionizing Healthcare—The Integration of Virtual Worlds, AR, and Metaverse Technology

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Open Journal of Applied Sciences 2024年第1期14卷 27-37页

作者： fatma Kilic The View Hospital Doha Qatar

This paper explores the transformative impact of virtual worlds, augmented reality (AR), and the metaverse in the healthcare sector. It delves into the ways these technologies are reshaping patient care, medical education, and research, while also addressing the challenges and opportunities they present. The paper highlights the potential benefits of these technologies and emphasizes the need for comprehensive regulatory frameworks and ethical guidelines to ensure responsible integration. Finally it outlines their transformative impact and discusses the challenges and opportunities they present for the future of healthcare provision.

关键词： Virtual Worlds Augmented Reality Metaverse Healthcare Patient Care Medical Education Research Transformative Technologies Regulatory Frameworks Ethical Guidelines

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Flavone improves liver damage in nicotine-exposed rats via the Nrf2/HO-1 pathway

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Asian Pacific Journal of Tropical Biomedicine 2024年第8期14卷 341-349页

作者： Nora A.Elsayed fatma SM Moawed Esraa SA Ahmed Ahmed Hammad Omayma AR Abo-Zaid Biochemistry and Molecular Biology Department Faculty of Vet.Med.Benha UniversityBenha cityEgypt Health Radiation Research National Center for Radiation Research and TechnologyEgyptian Atomic Energy AuthorityCairoEgypt Radiation Biology Department National Center for Radiation Research and TechnologyEgyptian Atomic Energy AuthorityCairoEgypt

Objective:To assess the hepatoprotective effects of flavone on nicotine-induced liver ***:Thirty-six rats were allocated into six groups:the control group,the nicotine group,the flavone alone groups(10 and 25 mg/kg/body weight),and the nicotine groups treated with flavone(10 and 25 mg/kg/body weight).Liver function,oxidative stress,Nrf2 pathway(HO-1,Nrf2,and Keap-1),and inflammatory markers(IL-17,TNF-α,and NF-κB)were ***,a histopathological examination of liver tissues was ***:Nicotine increased liver damage,inflammation,and oxidative ***,flavone suppressed nicotine-induced liver enzymes,oxidative stress,and inflammation,as manifested by increased antioxidants and decreased malondialdehyde level,liver enzymatic activities,and inflammatory ***(10 and 25 mg/kg/body weight)also reduced the level of Keap-1 and increased HO-1 and Nrf2 levels in the liver of nicotine-exposed ***:Flavone has hepatoprotective properties and may slow the progression of liver injury by reducing oxidative stress,liver enzymes,and inflammation possibly via the Nrf2 pathway.

关键词： Flavone Nicotine Liver Nrf2 HO-1 NF-κB

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