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Transfer learning from T1-weighted to T2-weighted Magnetic resonance sequences for brain image segmentation

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CAAI Transactions on Intelligence Technology 2024年第1期9卷 26-39页

作者： Imene Mecheter Maysam Abbod Habib Zaidi Abbes amira Brunel University LondonUK Geneva University Hospital GenevaSwitzerland Geneva University GenevaSwitzerland University of Groningen GroningenNetherlands University of Southern Denmark OdenseDenmark University of Sharjah SharjahUAE De Montfort University LeicesterUK

Magnetic resonance(MR)imaging is a widely employed medical imaging technique that produces detailed anatomical images of the human *** segmentation of MR im-ages plays a crucial role in medical image analysis,as it enables accurate diagnosis,treatment planning,and monitoring of various diseases and *** to the lack of sufficient medical images,it is challenging to achieve an accurate segmentation,especially with the application of deep learning *** aim of this work is to study transfer learning from T1-weighted(T1-w)to T2-weighted(T2-w)MR sequences to enhance bone segmentation with minimal required computation *** the use of an excitation-based convolutional neural networks,four transfer learning mechanisms are proposed:transfer learning without fine tuning,open fine tuning,conservative fine tuning,and hybrid transfer ***,a multi-parametric segmentation model is proposed using T2-w MR as an intensity-based augmentation *** novelty of this work emerges in the hybrid transfer learning approach that overcomes the overfitting issue and preserves the features of both modalities with minimal computation time and *** segmentation results are evaluated using 14 clinical 3D brain MR and CT *** results reveal that hybrid transfer learning is superior for bone segmentation in terms of performance and computation time with DSCs of 0.5393±*** T2-w-based augmentation has no significant impact on the performance of T1-w MR segmentation,it helps in improving T2-w MR segmentation and developing a multi-sequences segmentation model.

关键词： computer vision convolution image segmentation learning(artificial intelligence)

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

A Weighted Multi-Layer Analytics Based Model for Emoji Recommendation

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Computers, Materials & Continua 2024年第1期78卷 1115-1133页

作者： amira M.Idrees Abdul Lateef Marzouq Al-Solami Faculty of Computers and Information Technology Future University in EgyptCairo11835Egypt Alkamil College of Science and Arts University of JeddahJeddah21959Saudi Arabia

The developed system for eye and face detection using Convolutional Neural Networks(CNN)models,followed by eye classification and voice-based assistance,has shown promising potential in enhancing accessibility for individuals with visual *** modular approach implemented in this research allows for a seamless flow of information and assistance between the different components of the *** research significantly contributes to the field of accessibility technology by integrating computer vision,natural language processing,and voice *** leveraging these advancements,the developed system offers a practical and efficient solution for assisting blind *** modular design ensures flexibility,scalability,and ease of integration with existing assistive ***,it is important to acknowledge that further research and improvements are necessary to enhance the system’s accuracy and ***-tuning the CNN models and expanding the training dataset can improve eye and face detection as well as eye classification ***,incorporating real-time responses through sophisticated natural language understanding techniques and expanding the knowledge base of ChatGPT can enhance the system’s ability to provide comprehensive and accurate ***,this research paves the way for the development of more advanced and robust systems for assisting visually impaired *** leveraging cutting-edge technologies and integrating them into amodular framework,this research contributes to creating a more inclusive and accessible society for individuals with visual *** work can focus on refining the system,addressing its limitations,and conducting user studies to evaluate its effectiveness and impact in real-world scenarios.

关键词： Social networks text analytics emoji prediction features extraction information retrieval

A Proposed Feature Selection Particle Swarm Optimization Adaptation for Intelligent Logistics--A Supply Chain Backlog Elimination Framework

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Computers, Materials & Continua 2024年第6期79卷 4081-4105页

作者： Yasser Hachaichi Ayman E.Khedr amira M.Idrees College of Computing and Information Technology at Khulais Department of Information SystemsUniversity of JeddahJeddah21959Saudi Arabia Faculty of Computers and Information Technology Future University in EgyptCairo11835Egypt

The diversity of data sources resulted in seeking effective manipulation and *** challenge that arises from the increasing dimensionality has a negative effect on the computation performance,efficiency,and stability of *** of the most successful optimization algorithms is Particle Swarm Optimization(PSO)which has proved its effectiveness in exploring the highest influencing features in the search space based on its fast convergence and the ability to utilize a small set of parameters in the search *** research proposes an effective enhancement of PSO that tackles the challenge of randomness search which directly enhances PSO *** the other hand,this research proposes a generic intelligent framework for early prediction of orders delay and eliminate orders backlogs which could be considered as an efficient potential solution for raising the supply chain *** proposed adapted algorithm has been applied to a supply chain dataset which minimized the features set from twenty-one features to ten significant *** confirm the proposed algorithm results,the updated data has been examined by eight of the well-known classification algorithms which reached a minimum accuracy percentage equal to 94.3%for random forest and a maximum of 99.0 for Naïve ***,the proposed algorithm adaptation has been compared with other proposed adaptations of PSO from the literature over different *** proposed PSO adaptation reached a higher accuracy compared with the literature ranging from 97.8 to 99.36 which also proved the advancement of the current research.

关键词： Optimization particle swarm optimization algorithm feature selection logistics supply chain management backlogs

Solute transport and geochemical modeling of the coastal quaternary aquifer, Delta Dahab Basin, South Sinai, Egypt

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Acta Geochimica 2024年第1期43卷 16-39页

作者： amira Samy Mustafa Eissa Seham Shahen Moustafa M.Said Rabab M.Abou-shahaba Division of Water Resources and Arid Land Department of HydrogeochemistryDesert Research CenterCairoEgypt Egypt Desalination Research Center of Excellence Desert Research CenterCairoEgypt Center for Water Supply Studies S&E-Physical&Environmental SciencesTexas A&M University Corpus ChristiCorpus ChristiUSA Department of Chemistry Faculty of Science(Girls)Al-Azhar UniversityYousef Abbas StrNasr CityP.O.Box:11754CairoEgypt

The wadi dahab delta is in a dry, arid coastal zone within Egypt’s south Sinai Peninsula’s eastern portion. The primary water source is the Quaternary coastal alluvial aquifer. The groundwater salinity varies from 890to 8213 mg/L, with a mean value of 3417 mg/L. The dissolved major ions have been used to calculate the seawater mixing index(SWMI) using a linear equation that discriminates the groundwater mostly affected by water–rock interaction(SWMI 1>) and other samples mixed with Seawater(SWMI < 1). The isotopic composition of groundwater for specifically chosen groundwater samples ranges from-0.645‰ to +5.212‰ for δ^(18)O and from-9.582‰ to + 22.778‰ for δ^(2)H, where the seawater represented by a Red Sea water sample(δ^(18)O + 1.64‰-δ^(2)H + 9.80‰) and reject brine water are considerably enriched the isotopic groundwater values. The geochemical NETPATH model constrained by the dissolved significant ions, isotopes, and the rock aquifer forming minerals as phases indicate the mixing percent with the seawater ranges from 9% to 97% of seawater from 91% to 3% of original recharge water. According to the SEAWAT 3-D flow models, seawater has penetrated the Northeastern Dahab delta aquifer, with the intrusion zone extending1500 m inland. The salt dissolution, upwelling of saline water, recharge from the upstream mountain block, and seawater encroachment are the primary aspects contributing to the deterioration of groundwater quality. These findings may have significance for effective groundwater withdrawal management in arid locations worldwide with similar hydrogeological systems.

关键词： Groundwater geochemistry Seawater intrusion Solute transport SEAWAT

Natural Convection of a Power-Law Nanofluid in a Square Cavity with a Vertical Fin

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Fluid Dynamics & Materials Processing 2024年第9期20卷 2091-2108页

作者： amira M’hadbi Mohammed El Ganaoui Haïkel Ben Hamed Amenallah Guizani Khalid Chtaibi LERMAB Department of Transition and Energy Efficiency ProfessionsIUT H Poincaréde LongwyUniversity of LorraineLongwy54400France LPT Center for Energy Research and Technologies(Borj Cedria2084)University of Tunis El ManarTunis1068Tunisia LTI Department of Mechanical Engineering and ProductionIUTUniversity of Picardie Jules-VerneAmiens80025France

The behavior of non-Newtonian power-law nanofluids under free convection heat transfer conditions in a cooled square enclosure equipped with a heated fin is investigated *** particular,the impact of nanofluids,composed of water and Al_(2)O_(3),TiO_(2),and Cu nanoparticles,on heat transfer enhancement is *** aim of this research is also to analyze the influence of different parameters,including the Rayleigh number(Ra=10^(4)-10^(6)),nanoparticle volume fraction(φ=0%-20%),non-Newtonian power-law indexes(n=0.6-1.4),and fin dimensions(Ar=0.3,0.5,and 0.7).Streamlines and isotherms are used to depict flow and related heat transfer *** indicate that thermal performance improves with increasing Rayleigh number,regardless of the nanoparticle type or nanofluid rheological *** suggests that the buoyancy force has a significant impact on heat transfer,particularly near the heat *** Nusselt number is more sensitive to variations in Cu nanoparticle volume fractions compared to Al₂O₃and TiO₂.Moreover,the average Nusselt numbers for power-law nanofluids with n1)are greater(smaller)than for Newtonian fluids due to the decrease(increase)in viscosity with increasing(decreasing)shear rate,at the same values of Rayleigh number Ra owing to the amplification(attenuation)of the convective ***,the most substantial enhancement is observed with Cu-water shear-thinning nanofluid,where the Nusselt number increases by 136%when changing from Newtonian to shear thinning behavior and by 154.9%when adding 16%nanoparticle volume ***,an even larger increase of 57%in the average Nusselt number is obtained on increasing the fin length from 0.3 to 0.7.

关键词： Heat transfer nanofluid non-Newtonian fluid natural convection

Building a Smart Management System for the Field Training Course at the Faculty of Specific Education-Mansoura University

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Computer Systems Science & Engineering 2024年第5期48卷 1213-1250页

作者： Soha A.Shaban amira A.Atta Dalia L.Elsheweikh Department of Computer Science Faculty of Specific EducationMansoura UniversityMansoura35516Egypt

Field training is the backbone of the teacher-preparation *** importance stems from the goals that colleges of education aim to achieve,which include bridging the gap between theory and practice and aligning with contemporary educational trends during teacher ***,trainee students attendance in field training is recordedmanually through signatures on attendance ***,thismethod is prone to impersonation,time wastage,and ***,traditional methods of evaluating trainee students are often susceptible to human errors during the evaluation and scoring *** training also lacks modern technology that the supervisor can use in case of his absence from school to monitor the trainee students’implementation of the required activities and *** shortcomings do not meet the needs of the digital era that universities are currently *** a result,this paper presents a smart management system for field training based on Internet of Things(IoT)and mobile *** includes three subsystems:attendance,monitoring,and *** attendance subsystem uses an R307 fingerprint sensor to record trainee students’*** Arduino Nano microcontroller transmits attendance data to the proposed Android application via an ESP-12F Wi-Fi module,which then forwards it to the Firebase database for *** monitoring subsystem utilizes Global Positioning System(GPS)technology to continually track trainee students’locations,ensuring they remain at the school during *** also enables remote communication between trainee students and supervisors via audio,video,or text by integrating video call and chat *** evaluation subsystem is based on three items:an online exam,attendance,and implementation of required activities and *** results have demonstrated the accuracy and efficiency of the proposed management system in recording attendance,as well as in monitoring and evaluating

关键词： Field training digital transformation mobile technology GPS video call chat online exam

Mixed Neuroendocrine-Non-Neuroendocrine Neoplasm (MiNEN) of the Colon: A Case Report

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Open Journal of Pathology 2024年第1期14卷 16-24页

作者： amira Mohammad Azah Syahrina Alias Department of Pathology Hospital Sultanah Aminah Johor Bahru Johor Malaysia

Here we report a rare case of mixed neuroendocrine-non-neuroendocrine neoplasms (MiNENs). A 51-year-old lady with no known family history of malignancies developed this rare type of malignancy without any active gastrointestinal symptoms. However, during a routine health check, physicians noticed a raised Carcinoembryonic Antigen (CEA) level and the patient subsequently was referred to the surgical department for further management. A colonoscopy and CECT abdomen were done and she was electively admitted for a left hemicolectomy operation for a splenic flexure tumour. The histopathological report revealed the tumour is a case of mixed neuroendocrine-non-neuroendocrine neoplasms (MiNENs) [moderately differentiated adenocarcinoma and neuroendocrine tumour grade 3]. TNM (8th edition, 2016): pT3, pN2 (20/21), pMX. Both resection margins were clear from malignant cells. Colorectal MiNENs, constitute a rare group of gastrointestinal tumours composed of both neuroendocrine and non-neuroendocrine components. Given their non-diagnostic macroscopic features, specific histological features and lack of disease awareness which are responsible for the underestimated incidence and conflicting data. In this case, a multidisciplinary team approach is important in managing patients with this malignancy to achieve the best outcome.

关键词： Mixed Neuroendocrine-Non-Neuroendocrine Neoplasms (MiNENs) Contrast-Enhanced Computed Tomography (CECT) Carcinoembryonic Antigen (CEA)

Mechanical Complications of Osteosynthesis: Frequency and Management at the Orthopedics-Traumatology Department of CHU Ignace DEEN

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Open Journal of Orthopedics 2024年第9期14卷 404-410页

作者： Tafsir Camara amira Aboud Ibrahima Sory Bangoura Madjirabe Nassaradengar Hippolyte Mohamed Youla Urbain Judicael Adou Kouassi Bah Mohamed Lamine Léopold Lamah Orthopedics-Traumatology Department of Ignace Deen University Hospital Conakry Guinea Orthopedics-Traumatology Department of Donka University Hospital Conakry Guinea

Introduction: Mechanical complications after osteosynthesis are spontaneous and harmful modifications of the joint compromising the consolidation process. The aim of this study is to report on the frequency of these complications and their management in the Orthopaedic-Traumatology Department of CHU Ignace Deen. Patients and Methods: we conducted a retrospective descriptive and analytical cross-sectional study from January 2017 to December 2022. It focused on the records of patients hospitalized and treated in the department for a mechanical complication after osteosynthesis. Results: The frequency of mechanical complications was 1.2%, with an average age of 44.2 years and a sex ratio of 3.2 in favor of men. Non-compliance with postoperative instructions, non-compliance with surgical technique, postoperative infection and early loading were the main contributing factors. Disassembly of the screw-plate was the most common cause in 6 cases (35.5%), with a mean delay of 4.1 months. Revision osteosynthesis was carried out using screw plates in 8 cases (47.1%). Conclusion: Mechanical complications of osteosynthesis are less frequent traumatic conditions in our department. Several factors contribute to their occurrence.

关键词： Mechanical Complications Frequency Therapeutics Osteosynthesis