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Automatic Finding of Brain-Tumour Group Using CNN Segmentation and Moth-Flame-algorithm,Selected Deep and Handcrafted Features

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Computers, Materials & Continua 2024年第5期79卷 2585-2608页

作者： Imad saud al Naimi Syed alwee aljunid Syed Junid Muhammad lmran Ahmad K.Suresh Manic Faculty of Electronic Engineering Technology University Malaysia Perils(UniMAP)Pauh Putra CampusArauPerlis02600Malaysia Department of Electrical and Communication Engineering National University of Science and TechnologyAL HailAL Seeb130Sultanate of Oman Department of Research and Innovation Saveetha School of EngineeringSaveetha Institute of Medical and Technical Sciences(SIMATS)ChennaiTamiNadu602105India

Augmentation of abnormal cells in the brain causes brain tumor(BT),and early screening and treatmentwill reduce its harshness in ***’s clinical level screening is usually performed with Magnetic Resonance Imaging(MRI)due to its multi-modality *** overall aims of the study is to introduce,test and verify an advanced image processing technique with algorithms to automatically extract tumour sections from brain MRI scans,facilitating improved *** research intends to devise a reliable framework for detecting the BT region in the twodimensional(2D)MRI slice,and identifying its class with improved *** methodology for the devised framework comprises the phases of:(i)Collection and resizing of images,(ii)Implementation and Segmentation of Convolutional Neural Network(CNN),(iii)Deep feature extraction,(iv)Handcrafted feature extraction,(v)Moth-Flame-algorithm(MFA)supported feature reduction,and(vi)Performance *** study utilized clinical-grade brain MRI of BRATS and TCIA datasets for the *** framework segments detected the glioma(low/high grade)and glioblastoma class *** work helped to get a segmentation accuracy of over 98%with VGG-UNet and a classification accuracy of over 98%with the VGG16 *** study has confirmed that the implemented framework is very efficient in detecting the BT in MRI slices with/without the skull section.

关键词： Brain tumour VGG-UNet VGG16 moth-flame-algorithm classification

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Anomaly-Based Intrusion DetectionModel Using Deep Learning for IoT Networks

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Computer Modeling in Engineering & Sciences 2024年第10期141卷 823-845页

作者： Muaadh A.alsoufi Maheyzah Md Siraj Fuad A.Ghaleb Muna al-Razgan Mahfoudh Saeed al-Asaly Taha alfakih faisal Saeed Faculty of Computing Universiti Teknologi Malaysia(UTM)Johor Bahru81310Malaysia DAAI Research Group College of Computing and Digital TechnologyBirmingham City UniversityBirminghamB47XGUK Department of Software Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11345Saudi Arabia

The rapid growth of Internet of Things(IoT)devices has brought numerous benefits to the interconnected ***,the ubiquitous nature of IoT networks exposes them to various security threats,including anomaly intrusion *** addition,IoT devices generate a high volume of unstructured *** intrusion detection systems often struggle to cope with the unique characteristics of IoT networks,such as resource constraints and heterogeneous data *** the unpredictable nature of network technologies and diverse intrusion methods,conventional machine-learning approaches seem to lack *** numerous research domains,deep learning techniques have demonstrated their capability to precisely detect *** study designs and enhances a novel anomaly-based intrusion detection system(AIDS)for IoT ***,a Sparse Autoencoder(SAE)is applied to reduce the high dimension and get a significant data representation by calculating the reconstructed ***,the Convolutional Neural Network(CNN)technique is employed to create a binary classification *** proposed SAE-CNN approach is validated using the Bot-IoT *** proposed models exceed the performance of the existing deep learning approach in the literature with an accuracy of 99.9%,precision of 99.9%,recall of 100%,F1 of 99.9%,False Positive Rate(FPR)of 0.0003,and True Positive Rate(TPR)of *** addition,alternative metrics,such as training and testing durations,indicated that SAE-CNN performs better.

关键词： IoT anomaly intrusion detection deep learning sparse autoencoder convolutional neural network

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Design and Performance Analysis of DSS (Dual Sink Based Scheme) Protocol for WBASNs

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Advances in Remote Sensing 2017年第4期6卷 245-259页

作者： Abdul Ahad saud al faisal Farzand ali Bahlool Jan Niamat Ullah Department of Computer Science Virtual University of Lahore Lahore Pakistan Department of Electronics Engineering Comsats University Islamabad Pakistan Department of Computer Science Preston University Islamabad Pakistan Department of Computer Science University of Swat Swat Pakistan Department of Computer Science Abdul Wali Khan University Mardan Pakistan

After a large improvement in health care services, Wireless Body Area Sensor Network (WBASN) is used in different fields where health care monitoring can be done continuously and from a distance. Many selected protocols are given in literature work which can improve the performance of WBASN by focusing on delay, routing and energy efficiency. In our research, we will focus on improving throughput, network life time, and decrease end-to-delay. In given research, the two sink nodes utilized and AnyCasting concept will be used. Dual Sinks based Scheme (DSS) for WBASN will be compared with existing DARE, SIMPLE, LAEEBA and M-ATTEMPT protocols. DSS performance found more efficient than DARE, SIMPLE, LAEEBA and M-ATTEMPT respectively in throughput. From results, DSS network life time is greater than DARE, SIMPLE, LAEEBA and M-ATTEMPT with minimum delay. In DSS, energy parameter is in tradeoff with the improved parameters, because of a computation of RSSI which do more process and utilize more energy.

关键词： WBASNs Network Life Time End-to-End Delay Throughput Energy Consumption AnyCasting RSSI

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Efficient Object Segmentation and Recognition Using Multi-Layer Perceptron Networks

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Computers, Materials & Continua 2024年第1期78卷 1381-1398页

作者： Aysha Naseer Nouf Abdullah almujally saud S.alotaibi Abdulwahab alazeb Jeongmin Park Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Information System Department Umm Al-Qura UniversityMakkahSaudi Arabia Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Department of Computer Engineering Tech University of KoreaGyeonggi-do15073South Korea

Object segmentation and recognition is an imperative area of computer vision andmachine learning that identifies and separates individual objects within an image or video and determines classes or categories based on their *** proposed system presents a distinctive approach to object segmentation and recognition using Artificial Neural Networks(ANNs).The system takes RGB images as input and uses a k-means clustering-based segmentation technique to fragment the intended parts of the images into different regions and label thembased on their ***,two distinct kinds of features are obtained from the segmented images to help identify the objects of *** Artificial Neural Network(ANN)is then used to recognize the objects based on their *** were carried out with three standard datasets,MSRC,MS COCO,and Caltech 101 which are extensively used in object recognition research,to measure the productivity of the suggested *** findings from the experiment support the suggested system’s validity,as it achieved class recognition accuracies of 89%,83%,and 90.30% on the MSRC,MS COCO,and Caltech 101 datasets,respectively.

关键词： K-region fusion segmentation recognition feature extraction artificial neural network computer vision

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Construction of robust and durable Cu_(2)Se-V_(2)O_(5) nanosheet electrocatalyst for alkaline oxygen evolution reaction

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Frontiers of Chemical Science and Engineering 2024年第6期18卷 71-83页

作者： Tauseef Munawar Ambreen Bashir Khalid Mujasam Batoo Saman Fatima faisal Mukhtar Sajjad Hussain Sumaira Manzoor Muhammad Naeem Ashiq Shoukat alim Khan Muammer Koc faisal Iqbal Institute of Physics The Islamia University of BahawalpurBahawalpur 63100Pakistan King Abdullah Institute for Nanotechnology King Saud UniversityRiyadh 11451Saudi Arabia Hybrid Materials Center(HMC) Sejong UniversitySeoul 05006Republic of Korea Department of Nanotechnology and Advanced Materials Engineering Sejong UniversitySeoul 05006Republic of Korea Institute of Chemical Sciences Bahauddin Zakariya UniversityMultan 60800Pakistan Division of Sustainable Development College of Science and EngineeringHamad Bin Khalifa UniversityQatar FoundationDoha 34110Qatar

Reducing the production costs of clean energy carriers such as hydrogen through scalable water electrolysis is a potential solution for advancing the hydrogen *** the various material candidates,our group demonstrated transition-metal-based materials with tunable electronic characteristics,various phases,and ***,electrochemical water oxidation using Cu_(2)Se-V_(2)O_(5) as a non-precious metallic electrocatalyst via a hydrothermal approach is *** water-splitting performance of all the fabricated electrocatalysts was evaluated after direct growth on a stainless-steel *** electrochemically tuned Cu_(2)Se-V_(2)O_(5) catalyst exhibited a reduced overpotential of 128 mV and provided a reduced Tafel slope of 57 mV·dec^(−1) to meet the maximum current density of 250 mA·cm^(−2).The optimized strategy for interfacial coupling of the fabricated Cu_(2)Se-V_(2)O_(5) catalyst resulted in a porous structure with accessible active sites,which enabled adsorption of the intermediates and afforded an effective charge transfer rate for promoting the oxygen evolution ***,the combined effect of the catalyst components provided long-term stability for over 110 h in an alkaline solution,which makes the catalyst promising for large-scale practical *** aforementioned advantages of the composite catalyst overcome the limitations of low conductivity,agglomeration,and poor stability of the pure catalysts(Cu2Se and V2O5).

关键词： oxygen evolution reaction Cu_(2)Se-V_(2)O_(5)composite nanosheets metal-diffused ions accessible adsorption sites

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Nasal Dermoid Cyst with Sinus Tract Intranasal Bone: A Case Report

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International Journal of Otolaryngology and Head & Neck Surgery 2024年第2期13卷 149-156页

作者： Sultan Kadasah Abdullah alhelali saud aldhabaan Abdulaziz al Qahtani Abdullah Musleh ali alshahrani Shahd Dlboh Sahar al-Otaibi Department of Surgery College of Medicine University of Bisha Bisha Saudi Arabia Department of Otolaryngology Head and Neck Surgery Abha Children’s Hospital Abha Saudi Arabia Department of Otolaryngology Head and Neck Surgery Armed Forces Southern Region Hospital Khamis Mushait Saudi Arabia Department of Surgery College of Medicine King Khalid University Abha Saudi Arabia College of Medicine King Khalid University Abha Saudi Arabia

Dermoid cysts are benign tumors originating from germ cells, which can form in various locations, including the nasal area in rare cases. They are of unknown exact etiology, but it is suggested that it is due to abnormal tissue migration during early embryonic development. Nasal dermoid cysts albeit rare, can present in various forms such as sinuses, fistulas, or intracranially extending tracts. They can be asymptomatic and incidentally discovered or present with a visible external mass or sinus that is either painful, infected or cosmetically concerning. If nasal dermoid cysts with an intra-nasal bone sinus tract are left untreated, they can lead to life-threatening complications. This report describes the case of a 6-year-old girl with a nasal dermoid cyst connected to a superficial punctum by an intra-nasal tract. She had undergone surgical excision of a nasal swelling previously diagnosed as a dermoid cyst. One year later, she returned to our clinic with a recurrence of the nasal swelling. Imaging tests revealed a nasal dermoid cyst with a tract extending to the nasal tip, without intracranial expansion. The cyst, along with the entire tract, was successfully removed surgically, and the postoperative follow-up indicated no complications. Histopathology confirmed the diagnosis of a dermoid cyst. This case underscores the significance of considering the dermoid tract in nasal cyst cases and the necessity of its complete removal to prevent recurrence.

关键词： Dermoid Cyst Nasal Sinus Sinus Tract Intranasal Bone Benign Tumor Congenital Anomaly

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DeBERTa-GRU: Sentiment Analysis for Large Language Model

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Computers, Materials & Continua 2024年第6期79卷 4219-4236页

作者： Adel Assiri Abdu Gumaei faisal Mehmood Touqeer Abbas Sami Ullah Department of Informatics for Business College of BusinessKing Khalid UniversityAbha61421Saudi Arabia Department of Computer Science College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia School of Electrical and Information Engineering Zhengzhou UniversityZhengzhou450001China Department of Computer Science and Technology Beijing University of Chemical TechnologyBeijing100029China Department of Computer Science Government College University FaisalabadFaisalabadPunjab38000Pakistan

Modern technological advancements have made social media an essential component of daily *** media allow individuals to share thoughts,emotions,and *** analysis plays the function of evaluating whether the sentiment of the text is positive,negative,neutral,or any other personal emotion to understand the sentiment context of the *** analysis is essential in business and society because it impacts strategic *** analysis involves challenges due to lexical variation,an unlabeled dataset,and text distance *** execution time increases due to the sequential processing of the sequence ***,the calculation times for the Transformer models are reduced because of the parallel *** study uses a hybrid deep learning strategy to combine the strengths of the Transformer and Sequence models while ignoring their *** particular,the proposed model integrates the Decoding-enhanced with Bidirectional Encoder Representations from Transformers(BERT)attention(DeBERTa)and the Gated Recurrent Unit(GRU)for sentiment *** the Decoding-enhanced BERT technique,the words are mapped into a compact,semantic word embedding space,and the Gated Recurrent Unit model can capture the distance contextual semantics *** proposed hybrid model achieves F1-scores of 97%on the Twitter Large Language Model(LLM)dataset,which is much higher than the performance of new techniques.

关键词： DeBERTa GRU Naive Bayes LSTM sentiment analysis large language model

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Extracellular vesicles as tools and targets in therapy for diseases

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Signal Transduction and Targeted Therapy 2024年第3期9卷 872-912页

作者： Mudasir A.Kumar Sadaf K.Baba Hana Q.Sadida Sara al.Marzooqi Jayakumar Jerobin faisal H.altemani Naseh algehainy Mohammad A.alanazi Abdul-Badi Abou-Samra Rakesh Kumar Ammira S.al-Shabeeb Akil Muzafar A.Macha Rashid Mir Ajaz A.Bhat Watson-Crick Centre for Molecular Medicine Islamic University of Science and TechnologyAwantiporaKashmir 192122India Department of Human Genetics-Precision Medicine in Diabetes Obesity and Cancer ProgramSidra MedicineDohaQatar Qatar Metabolic Institute Academic Health SystemHamad Medical CorporationDohaQatar Department of Medical Laboratory Technology Prince Fahad Bin Sultan Chair for Biomedical ResearchFaculty of Applied Medical SciencesUniversity of TabukTabukSaudi Arabia School of Biotechnology Shri Mata Vaishno Devi UniversityKatraIndia

Extracellular vesicles(EVs)are nano-sized,membranous structures secreted into the extracellular *** exhibit diverse sizes,contents,and surface markers and are ubiquitously released from cells under normal and pathological *** serum is a rich source of these EVs,though their isolation from serum proteins and non-EV lipid particles poses *** vesicles transport various cellular components such as proteins,mRNAs,miRNAs,DNA,and lipids across distances,influencing numerous physiological and pathological events,including those within the tumor microenvironment(TME).Their pivotal roles in cellular communication make EVs promising candidates for therapeutic agents,drug delivery systems,and disease *** in cancer diagnostics,EV detection can pave the way for early identification and offers potential as diagnostic ***,various EV subtypes are emerging as targeted drug delivery tools,highlighting their potential clinical *** need for non-invasive biomarkers to monitor biological processes for diagnostic and therapeutic purposes remains *** into the unique composition of EVs could unlock advanced diagnostic and therapeutic avenues in the *** this review,we discuss in detail the roles of EVs across various conditions,including cancers(encompassing head and neck,lung,gastric,breast,and hepatocellular carcinoma),neurodegenerative disorders,diabetes,viral infections,autoimmune and renal diseases,emphasizing the potential advancements in molecular diagnostics and drug delivery.

关键词： diseases sized sizes

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RoGRUT: A Hybrid Deep Learning Model for Detecting Power Trapping in Smart Grids

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Computers, Materials & Continua 2024年第5期79卷 3175-3192页

作者： Farah Mohammad Saad al-Ahmadi Jalal al-Muhtadi Center of Excellence in Information Assurance(CoEIA) King Saud UniversityRiyadh11543Saudi Arabia College of Computer&Information Sciences King Saud UniversityRiyadh11543Saudi Arabia

Electricity theft is a widespread non-technical issue that has a negative impact on both power grids and electricity *** hinders the economic growth of utility companies,poses electrical risks,and impacts the high energy costs borne by *** development of smart grids is crucial for the identification of power theft since these systems create enormous amounts of data,including information on client consumption,which may be used to identify electricity theft using machine learning and deep learning ***,there also exist different solutions such as hardware-based solutions to detect electricity theft that may require human resources and expensive ***-based solutions are presented in the literature to identify electricity theft but due to the dimensionality curse,class imbalance issue and improper hyper-parameter tuning of such models lead to poor *** this research,a hybrid deep learning model abbreviated as RoGRUT is proposed to detect electricity theft as amalicious and non-malicious *** key steps of the RoGRUT are data preprocessing that covers the problem of class imbalance,feature extraction and final theft *** advanced-level models like RoBERTa is used to address the curse of dimensionality issue,the near miss for class imbalance,and transfer learning for *** effectiveness of the RoGRUTis evaluated using the dataset fromactual smartmeters.A significant number of simulations demonstrate that,when compared to its competitors,the RoGRUT achieves the best classification *** performance evaluation of the proposed model revealed exemplary results across *** accuracy achieved was 88%,with precision at an impressive 86%and recall reaching 84%.The F1-Score,a measure of overall performance,stood at 85%.Furthermore,themodel exhibited a noteworthyMatthew correlation coefficient of 78%and excelled with an area under the curve of 91%.

关键词： Electricity theft smart grid RoBERTa GRU transfer learning

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Unilateral Choanal Atresia in Adults: A Case Series

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International Journal of Otolaryngology and Head & Neck Surgery 2024年第3期13卷 187-193页

作者： Sultan Kadasah Abdulaziz al Qahtani Ghalib al-Sayed Abdullah al Helali saud aldhabaan Abdullah Musleh ali Asiry Mohammed Asiri Shahd Dlboh Adnan al-Malki Abdulsalam alqhtani Mohammed al-khulban Sahar al-Otaibi Department of Surgery College of Medicine University of Bisha Bisha Saudi Arabia Department of Otolaryngology Head and Neck Surgery Armed Forces Southern Region Hospital Khamis Mushait Saudi Arabia Department of Otolaryngology Head and Neck Surgery Abha Children&#8217s Hospital Abha Saudi Arabia Department of Surgery College of Medicine King Khalid University Abha Saudi Arabia Department of Otolaryngology Head and Neck Surgery Aseer Central Hospital Abha Saudi Arabia College of Medicine King Khalid University Abha Saudi Arabia

Choanal atresia (CA) is a rare occlusion of the posterior choanae. Unilateral cases have been reported more than bilaterally, and it’s more often right-sided in those patients. According to the literature, mixed bony-membranous atresia is the most common type. There is a high incidence of craniofacial and visceral anomalies associated with congenital choanal atresia. Therefore, investigation for associated congenital anomalies is an important step before the surgery. We report 2 cases of incidental finding of unilateral choanal atresia in a 21- and 17-year-old with nasal discharge being the only complaint in the former and nasal obstruction with headache in the latter. The patients were then scheduled for day-surgery as a case of choanal atresia for transnasal, endoscopic repair and posterior septectomy. The patients were discharged home on the same day with the absence of restenosis or other complications.

关键词： Choanal Atresia Nasal Obstruction Congenital Anomaly

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