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Relational Turkish Text Classification Using Distant Supervised Entities and Relations

Computers, materials & Continua 2024年第5期79卷 2209-2228页

作者： Halil ibrahim Okur Kadir Tohma Ahmet Sertbas Department of Computer Engineering Faculty of Engineering and Natural SciencesIskenderun Technical UniversityHatay31200Turkey Department of Computer Engineering Faculty of EngineeringIstanbul University-CerrahpasaIstanbul34310Turkey

Text classification,by automatically categorizing texts,is one of the foundational elements of natural language processing *** study investigates how text classification performance can be improved through the integration of entity-relation information obtained from the Wikidata(Wikipedia database)database and BERTbased pre-trained Named Entity Recognition(NER)*** on a significant challenge in the field of natural language processing(NLP),the research evaluates the potential of using entity and relational information to extract deeper meaning from *** adopted methodology encompasses a comprehensive approach that includes text preprocessing,entity detection,and the integration of relational *** conducted on text datasets in both Turkish and English assess the performance of various classification algorithms,such as Support Vector machine,Logistic Regression,Deep Neural Network,and Convolutional Neural *** results indicate that the integration of entity-relation information can significantly enhance algorithmperformance in text classification tasks and offer new perspectives for information extraction and semantic analysis in NLP *** of this work include the utilization of distant supervised entity-relation information in Turkish text classification,the development of a Turkish relational text classification approach,and the creation of a relational *** demonstrating potential performance improvements through the integration of distant supervised entity-relation information into Turkish text classification,this research aims to support the effectiveness of text-based artificial intelligence(AI)***,it makes significant contributions to the development ofmultilingual text classification systems by adding deeper meaning to text content,thereby providing a valuable addition to current NLP studies and setting an important reference point for future research.

关键词： Text classification relation extraction NER distant supervision deep learning machine learning

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Outcome of percutaneous reconstruction of chronic lateral collateral ligament rupture

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Chinese Journal of Traumatology 2024年第1期27卷 58-62页

作者： Soliudeen Adebayo Arojuraye ibrahim Abolaji Alabi ibrahim Usman mustapha Department of Orthopaedics National Orthopaedic Hospital Dala-KanoNigeria Department of Surgery Bayero University KanoNigeria

Purpose:many techniques have been described for the reconstruction of chronic lateral collateral ligament(LCL)rupture with different autograft *** advantages of percutaneous LCL reconstruction include small incisions,minimal soft tissue disruption,less postoperative pain,and speedy rehabilitation and *** aim of this study was to report the functional outcome of percutaneous LCL reconstruction and overall patient satisfaction in ***:This prospective and interventional study involving 51 patients with chronic LCL rupture who had percutaneous LCL reconstruction using peroneus longus autograft was conducted between January 2021 and December 2022 in National Orthopaedic Hospital,Dala-Kano,*** inclusion criteria were patients between the ages of 18 and 45 years with chronic isolated LCL and not more than 1 injury of knee *** criteria were active infection,and multi-ligament knee injury requiring 2-staged *** knee functions were assessed preoperatively,3 months,6 months,and 12 months postoperatively using the Lysholm scoring *** satisfaction with the outcome of the treatment was assessed using a 5-point Likert *** information was recorded into microsoft Excel sheet and data was analyzed using SPSS version 23.0 for *** paired samples t-test was used to compare the clinical outcomes as continuous *** significance was considered at pmean age of the patients was(30.10±5.90)*** median time from injury to surgery was 7 months(ranging from 3 to 28 months).The mean follow-up period was(14.07±3.13)*** mean preoperative and 1-year postoperative Lysholm scores were 44.33±12.97 and 97.96±1.23,***:Percutaneous LCL reconstruction using peroneus longus autograft significantly improves patient knee function and results in excellent patient satisfaction。

关键词： rupture ligament percutaneous

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(Sm/Eu/Tm)^(3+) doped tantalum semiconductor system for photovoltaic and electrochemical functionality amplification

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Journal of Rare Earths 2024年第8期42卷 1586-1594,I0007页

作者： Shaan Bibi Jaffri Khuram Shahzad Ahmad Isaac Abrahams ibrahim A.A materials and Environmental Chemistry Lab Lab-E21Department of Environmental SciencesFatima Jinnah Women UniversityRawalpindiPakistan School of Physical and Chemical Sciences Queen Mary University of LondonLondonUnited Kingdom Department of Botany and microbiology College of ScienceKing Saud UniversityP.O.Box 2455Riyadh11451Saudi Arabia

This work reports the synthesis,characterization,and energy focused applications of the novel lanthanides co-doped tantalum pentoxide hetero-system(Sm^(3+)-Eu^(3+)-Tm^(3+):Ta_(2)O_(5)).Ln^(3+)-doped Ta_(2)O_(5) express excellent opto-electronic features reflected by the narrow band gap energy of 3.87 *** vibrations confirm the presence of Ta-O-Ta and Ta-O *** synthesized system possesses orthorhombic geometry with 59.46 nm particle *** the smoother and compact morphology,the synthesized material succeeds in augmenting the performance of different systems aimed at energy *** ambient perovskite solar cell device fabricated with the Ln^(3+)-doped Ta_(2)O_(5) as an electron transport layer excels in achieving an efficiency and fill factor of 14.17% and 76% under artificial *** device was marked by the negligible hysteresis behavior showing profound photovoltaic *** electrochemical activity of the Ln^(3+)-doped Ta_(2)O_(5) decorated electrode was evaluated for electrical charge storage potential with pseudocapacitive behavior,With the highest specific capacitance of 355.39 F/g and quicker ionic diffusion rate,the designed electrode excels conventionally used ***-catalysis of water with Ln^(3+)-doped Ta_(2)O_(5) material indicates its capacity for H_(2) production with the lowest overpotential and Tafel slope values of 148 and 121.2 mV/dec,while the O_(2) generation is comparatively *** the stable electrochemical output,this rare earth modified material has the potential to replace conventionally used environmentally perilous and costly materials.

关键词： Lanthanide doping Rare earth materials Perovskite solar cells Supercapacitors Water splitting

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Insulin resistance as the molecular link between diabetes and Alzheimer's disease

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World Journal of Diabetes 2024年第7期15卷 1430-1447页

作者： mona mohamed ibrahim Abdalla Department of Human Biology School of MedicineInternational Medical UniversityBukit Jalil 57000Kuala LumpurMalaysia

Diabetes mellitus(Dm)and Alzheimer's disease(AD)are two major health concerns that have seen a rising prevalence *** studies have indicated a possible link between Dm and an increased risk of developing ***,while primarily known for its role in regulating blood sugar,also plays a vital role in protecting brain *** resistance(IR),especially prevalent in type 2 diabetes,is believed to play a significant role in AD's *** insulin signalling becomes dysfunctional,it can negatively affect various brain functions,making individuals more susceptible to AD's defining features,such as the buildup of beta-amyloid plaques and tau protein *** research suggests that addressing insulin-related issues might help reduce or even reverse the brain changes linked to *** review aims to explore the relationship between Dm and AD,with a focus on the role of *** also explores the molecular mechanisms by which IR might lead to brain changes and assesses current treatments that target *** IR's role in the connection between Dm and AD offers new possibilities for treatments and highlights the importance of continued research in this interdisciplinary field.

关键词： Alzheimer's disease Insulin resistance Obesity Dementia Diabetes metabolic syndrome

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Urban Electric Vehicle Charging Station Placement Optimization with Graylag Goose Optimization Voting Classifier

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Computers, materials & Continua 2024年第7期80卷 1163-1177页

作者： Amel Ali Alhussan Doaa Sami Khafaga El-Sayed m.El-kenawy marwa m.Eid Abdelhameed ibrahim Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute for Engineering and TechnologyMansoura35511Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt

To reduce the negative effects that conventional modes of transportation have on the environment,researchers are working to increase the use of electric *** demand for environmentally friendly transportation may be hampered by obstacles such as a restricted range and extended rates of *** establishment of urban charging infrastructure that includes both fast and ultra-fast terminals is essential to address this ***,the powering of these terminals presents challenges because of the high energy requirements,whichmay influence the quality of *** the maximum hourly capacity of each station based on its geographic location is necessary to arrive at an accurate estimation of the resources required for charging *** is vital to do an analysis of specific regional traffic patterns,such as road networks,route details,junction density,and economic zones,rather than making arbitrary conclusions about traffic *** vehicle traffic is simulated using this data and other variables,it is possible to detect limits in the design of the current traffic engineering ***,the binary graylag goose optimization(bGGO)algorithm is utilized for the purpose of feature ***,the graylag goose optimization(GGO)algorithm is utilized as a voting classifier as a decision algorithm to allocate demand to charging stations while taking into consideration the cost variable of traffic *** on the results of the analysis of variance(ANOVA),a comprehensive summary of the components that contribute to the observed variability in the dataset is *** results of the Wilcoxon Signed Rank Test compare the actual median accuracy values of several different algorithms,such as the voting GGO algorithm,the voting grey wolf optimization algorithm(GWO),the voting whale optimization algorithm(WOA),the voting particle swarm optimization(PSO),the voting firefly algorithm(FA),and the voting genetic algori

关键词： Electric vehicle graylag goose optimization metaheuristics optimization machine learning

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Enhancing Wireless Sensor Network Efficiency through Al-Biruni Earth Radius Optimization

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Computers, materials & Continua 2024年第6期79卷 3549-3568页

作者： Reem ibrahim Alkanhel Doaa Sami Khafaga Ahmed mohamed Zaki marwa m.Eid Abdyalaziz A.Al-mooneam Abdelhameed ibrahim S.K.Towfek Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Computer Science and Intelligent Systems Research Center BlacksburgVirginia24060USA Delta Higher Institute for Engineering and Technology Mansoura35511Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Artificial Intelligence and Computational Intelligence Research Center MeridenConnecticut06450USA School of ICT Faculty of EngineeringDesign and Information&Communications Technology(EDICT)Bahrain PolytechnicP.O.Box 33349Isa TownBahrain

The networks of wireless sensors provide the ground for a range of applications,including environmental moni-toring and industrial *** the networks can overcome obstacles like power and communication reliability and sensor coverage is the crux of network *** infrastructure planning should be focused on increasing performance,and it should be affected by the detailed data about node *** work recommends the creation of each sensor’s specs and radius of influence based on a particular geographical location,which will contribute to better network planning and *** using the ARImA model for time series forecasting and the Al-Biruni Earth Radius algorithm for optimization,our approach bridges the gap between successive terrains while seeking the equilibrium between exploration and *** implementing adaptive protocols according to varying environments and sensor constraints,our study aspires to improve overall network *** compare the Al-Biruni Earth Radius algorithm along with Gray Wolf Optimization,Particle Swarm Optimization,Genetic Algorithms,and Whale Optimization about performance on real-world *** the most efficient in the optimization process,Biruni displays the lowest error rate at *** two other statistical techniques,like ANOVA,are also useful in discovering the factors influencing the nature of sensor data and network-specific *** to the multi-faceted support the comprehensive approach promotes,there is a chance to understand the dynamics that affect the optimization outcomes better so decisions about network design can be *** delivering better performance and reliability for various in-situ applications,this research leads to a fusion of time series forecasters and a customized optimizer algorithm.

关键词： Wireless sensor networks optimization ARImA model BER algorithm metaheuristic algorithms

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Gradient Optimizer Algorithm with Hybrid Deep Learning Based Failure Detection and Classification in the Industrial Environment

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Computer modeling in Engineering & Sciences 2024年第2期138卷 1341-1364页

作者： mohamed Zarouan ibrahim m.mehedi Shaikh Abdul Latif md.masud Rana Department of Electrical and Computer Engineering(ECE) King Abdulaziz UniversityJeddah21589Saudi Arabia Center of Excellence in Intelligent Engineering Systems(CEIES) King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Nuclear Engineering King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Electrical and Electronic Engineering Rajshahi University of Engineering and TechnologyRajshahiBangladesh

Failure detection is an essential task in industrial systems for preventing costly downtime and ensuring the seamlessoperation of the system. Current industrial processes are getting smarter with the emergence of Industry ***, various modernized industrial processes have been equipped with quite a few sensors to collectprocess-based data to find faults arising or prevailing in processes along with monitoring the status of *** diagnosis of rotating machines serves a main role in the engineering field and industrial production. Dueto the disadvantages of existing fault, diagnosis approaches, which greatly depend on professional experienceand human knowledge, intellectual fault diagnosis based on deep learning (DL) has attracted the researcher’sinterest. DL reaches the desired fault classification and automatic feature learning. Therefore, this article designs a Gradient Optimizer Algorithm with Hybrid Deep Learning-based Failure Detection and Classification (GOAHDLFDC)in the industrial environment. The presented GOAHDL-FDC technique initially applies continuous wavelettransform (CWT) for preprocessing the actual vibrational signals of the rotating machinery. Next, the residualnetwork (ResNet18) model was exploited for the extraction of features from the vibration signals which are thenfed into theHDLmodel for automated fault detection. Finally, theGOA-based hyperparameter tuning is performedtoadjust the parameter valuesof theHDLmodel *** experimental result analysis of the GOAHDL-FD Calgorithm takes place using a series of simulations and the experimentation outcomes highlight the better resultsof the GOAHDL-FDC technique under different aspects.

关键词： Fault detection Industry 4.0 gradient optimizer algorithm deep learning rotating machineries artificial intelligence

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Image Splicing Forgery Detection Using Feature-Based of Sonine Functions and Deep Features

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Computers, materials & Continua 2024年第1期78卷 795-810页

作者： Ala’a R.Al-Shamasneh Rabha W.ibrahim Department of Computer Science College of Computer&Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Computer Science and mathematics Lebanese American UniversityBeirut11022801Lebanon Department of mathematics Mathematics Research CenterNear East UniversityNicosia99138Turkey Information and Communication Technology Research Group Scientific Research CenterAlayen UniversityDhi Qar64001Iraq

The growing prevalence of fake images on the Internet and social media makes image integrity verification a crucial research *** of the most popular methods for manipulating digital images is image splicing,which involves copying a specific area from one image and pasting it into *** were made to mitigate the effects of image splicing,which continues to be a significant research *** study proposes a new splicing detectionmodel,combining Sonine functions-derived convex-based features and deep *** stages make up the proposed *** first step entails feature extraction,then classification using the“support vector machine”(SVm)to differentiate authentic and spliced *** proposed Sonine functions-based feature extraction model reveals the spliced texture details by extracting some clues about the probability of image *** proposed model achieved an accuracy of 98.93% when tested with the CASIA V2.0 dataset“Chinese Academy of Sciences,Institute of Automation”which is a publicly available dataset for forgery *** experimental results show that,for image splicing forgery detection,the proposed Sonine functions-derived convex-based features and deep features outperform state-of-the-art techniques in terms of accuracy,precision,and ***,the obtained detection accuracy attests to the benefit of using the Sonine functions alongside deep feature *** the regions or locations where image tampering has taken place is limited by the *** research will need to look into advanced image analysis techniques that can offer a higher degree of accuracy in identifying and localizing tampering regions.

关键词： Image forgery image splicing deep learning Sonine functions

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Consecutive narrow and broad quasi-periodic fast-propagating wave trains associated with a flare

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Science China(Physics,mechanics & Astronomy) 2024年第5期67卷 200-211页

作者： Xinping Zhou Yuandeng Shen Chengrui Zhou Zehao Tang Ahmed Ahmed ibrahim College of Physics and Electronic Engineering Sichuan Normal UniversityChengdu 610068China State Key Laboratory of Space Weather Chinese Academy of SciencesBeijing 100190China Yunnan Observatories Chinese Academy of SciencesKunming 650216China Department of Physics and Astronomy College of ScienceKing Saud UniversityP.O.Box 2455Riyadh 11451Saudi Arabia

The excitation mechanism of coronal quasi-period fast-propagating(QFP)wave trains remains *** Atmospheric Imaging Assembly onboard the Solar Dynamics Observatory observations,we study a narrow and a broad QFP wave trains excited one after another during the successive eruptions of filaments hosted within a fan-spine magnetic system on October 20,*** consecutive occurrence of these two types of QFP wave trains in the same event provides an excellent opportunity to explore their excitation mechanisms and compare their physical *** observational results reveal that narrow and broad QFP wave trains exhibit distinct speeds,periods,energy fluxes,and relative intensity amplitudes,although originating from the same active region and being associated with the same GOES C2.9 *** wavelet analysis,we find that the narrow QFP wave train shares a similar period with the flare itself,suggesting its possible excitation through the pulsed energy release in the magnetic reconnection process that generated the accompanying *** the other hand,the broad QFP wave train appears to be associated with the energy pulses released by the successive expansion and unwinding of filament ***,it is plausible that the broad QFP wave train was also excited by the sequential stretching of closed magnetic field lines driven by the erupting *** findings shed light on the different excitation mechanisms and origins of the QFP wave trains.

关键词： narrow wave excitation

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multiple thoracic and abdominal foregut duplication cysts:A case report

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World Journal of Clinical Cases 2024年第8期12卷 1504-1509页

作者： Tuqa Adil Alsinan Tariq ibrahim Altokhais Department of Pediatric Surgery Prince Sultan Military Medical CityRiyadh 12233Saudi Arabia Devision of Pediatric Surgery Department of SurgeryCollege of MedicineKing Saud UniversityRiyadh 4545Saudi Arabia

BACKGROUND Congenital enteric duplication cysts are tubular or cystic structures that normally lie alongside the gastrointestinal(GI)*** duplication cysts are typically solitary lesions that occur anywhere near the GI tract from the neck to the rectum,but having multiple duplication cysts is rare,and presentation within the pancreas is extremely *** SUmmARY We herein demonstrate a case of esophageal,gastric,and gastric-type duplication cyst of the pancreas in a seventeen-month-old girl who presented with failure to thrive,abdominal pain,vomiting,hematemesis,and melena since the age of three *** cysts were excised by thoracoscopy and laparoscopy in the same *** our knowledge,no such case has been *** Enteric duplications can occur throughout the entire alimentary *** they occur in the pancreas,they present a formidable challenge in both diagnosis and *** to the risk of complications and malignant transformation,surgical removal is the recommended treatment of all duplication cysts.

关键词： Congenital Duplication cyst Foregut duplication Gastric duplication Pancreas Case report

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