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An Ingenious IoT Based Crop Prediction System Using ML and EL

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Computers, Materials & Continua 2024年第4期79卷 183-199页

作者： Shabana ramzan Yazeed Yasin Ghadi Hanan Aljuaid Aqsa Mahmood Basharat Ali Department of Computer Science&IT Government Sadiq CollegeWomen UniversityBahawalpur63100Pakistan Department of Computer Science/Software Engineering Al Ain UniversityAl Ain64141UAE Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman University(PNU)Riyadh11671Saudi Arabia Agronomic Research Station Bahawalpur63100Pakistan

Traditional farming procedures are time-consuming and expensive as based on manual labor. Farmers haveno proper knowledge to select which crop is suitable to grow according to the environmental factors and soilcharacteristics. This is the main reason for the low yield of crops and the economic crisis in the agricultural sectorof the different countries. The use of modern technologies such as the Internet of Things (IoT), machine learning,and ensemble learning can facilitate farmers to observe different factors such as soil electrical conductivity (EC),and environmental factors like temperature to improve crop yield. These parameters play a vital role in suggestinga suitable crop to cope the food scarcity. This paper proposes a systemcomprised of twomodules, first module usesstatic data and the second module takes hybrid data collection (IoT-based real-time data and manual data) withmachine learning and ensemble learning algorithms to suggest the suitable crop in the farm to maximize the *** is used to train the model that predicts the crop. This system proposed an intelligent and low-cost solutionfor the farmers to process the data and predict the suitable *** implemented the proposed system in the *** efficiency and accuracy of the proposed system are confirmed by the generated results to predict the crop.

关键词： Machine learning Internet of Things sensors ensemble learning

Overcoming side reaction effects in the colloidal synthesis of ZnSe/ZnS core/shell quantum dots with an etching strategy

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Nano Research 2024年第8期17卷 7020-7026页

作者： Jinhua He Chenhui Wang Mingrui Liu Muhammad ramzan Zhiwei Long Xian-gang Wu Yu Chen Haizheng Zhong MIIT Key Laboratory for Low-Dimensional Quantum Structure and Devices School of Materials Science and EngineeringBeijing Institute of TechnologyBeijing 100081China Beijing Engineering Research Center for Mixed Reality and Advanced Display Technology School of Optics and PhotonicsBeijing Institute of TechnologyBeijing 100081China

The potential use of large-size ZnSe quantum dots as blue emitters for display applications has greatly inspired the colloidal ***,we report the negative effects of side reactions of large-size ZnSe quantum *** side reactions between oleic acid and oleylamine generated amidation products and H_(2)O,which led to the hydrolysis of Zn(OA)2 to Zn(OH)2 and the subsequent formation of zinc oxide(ZnO)and zinc bis[diphenylphosphinate](Zn(DPPA)2)*** side reactions resulted in the formation of a defective surface including a Se-rich surface and oxygen-related *** negative effects can be overcome by adopting an etching strategy using potassium fluoride and myristic acid in *** overcoating a ZnS shell,blue emissive ZnSe/ZnS quantum dots with a maximum photoluminescence quantum yield of up to 91%were *** further fabricated ZnSe quantum dots-based blue light-emitting diodes with an emission peak at 456 *** device showed a turn-on voltage of 2.7 V with a maximum external quantum efficiency of 4.2%and a maximum luminance of 1223 cd·m^(−2).

关键词： quantum dots ZnSe side reactions surface etching light-emitting diodes

Deep Convolutional Neural Networks for Accurate Classification of Gastrointestinal Tract Syndromes

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Computers, Materials & Continua 2024年第1期78卷 1207-1225页

作者： Zahid Farooq Khan Muhammad ramzan Mudassar Raza Muhammad Attique Khan Khalid Iqbal Taerang Kim Jae-Hyuk Cha Department of Computer Science COMSATS University IslamabadWah CampusWah47040Pakistan Department of Computer Science and Mathematics Lebanese American UniversityBeirut13-5053Lebanon Department of Computer Science HITEC UniversityTaxila47080Pakistan Department of Computer Science COMSATS University IslamabadAttock CampusAttock43600Pakistan Department of Computer Science Hanyang UniversitySeoul04763Korea

Accurate detection and classification of artifacts within the gastrointestinal(GI)tract frames remain a significant challenge in medical image *** science combined with artificial intelligence is advancing to automate the diagnosis and treatment of numerous *** to this is the development of robust algorithms for image classification and detection,crucial in designing sophisticated systems for diagnosis and *** study makes a small contribution to endoscopic image *** proposed approach involves multiple operations,including extracting deep features from endoscopy images using pre-trained neural networks such as Darknet-53 and ***,feature optimization utilizes the binary dragonfly algorithm(BDA),with the fusion of the obtained feature *** fused feature set is input into the ensemble subspace k nearest neighbors(ESKNN)*** Kvasir-V2 benchmark dataset,and the COMSATS University Islamabad(CUI)Wah private dataset,featuring three classes of endoscopic stomach images were *** assessments considered various feature selection techniques,including genetic algorithm(GA),particle swarm optimization(PSO),salp swarm algorithm(SSA),sine cosine algorithm(SCA),and grey wolf optimizer(GWO).The proposed model excels,achieving an overall classification accuracy of 98.25% on the Kvasir-V2 benchmark and 99.90% on the CUI Wah private *** approach holds promise for developing an automated computer-aided system for classifying GI tract syndromes through endoscopy images.

关键词： Feature fusion Darknet-53 Xception binary dragonfly algorithm ensemble

Impact of Cattaneo-Christov Heat Flux in the Nanofluid Flow over an Inclined Permeable Surface with Irreversibility Analysis

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Journal of Applied Mathematics and Physics 2024年第4期12卷 1582-1595页

作者： Muhammad ramzan Hina Gul Department of Computer Science Bahria University Islamabad Pakistan

This study discusses the magnetohydrodynamic nanofluid flow over an inclined permeable surface influenced by mixed convection, and Cattaeo-Christov heat flux. The heat transfer analysis is performed in the presence of a heat source/sink and thermal stratification. To gauge the energy loss during the process, an irreversibility analysis is also performed. A numerical solution to the envisaged problem is obtained using the bvp4c package of MATLAB. Graphs are drawn to assess the consequences of the arising parameters against the associated profiles. The results show that an augmentation in the magnetic field and nanomaterial volume fraction results in an enhancement in the temperature profile. A strong magnetic field can significantly reduce the fluid velocity. The behavior of the Skin friction coefficient against the different estimates of emerging parameters is discussed. .

关键词： Nanofluid Flow Cattaneo-Christov Heat Flux Permeable Surface Mixed Convection Heat Source/Sink Thermal Stratification

Identifying and validating MMP family members(MMP2,MMP9,MMP12,and MMP16)as therapeutic targets and biomarkers in kidney renal clear cell carcinoma(KIRC)

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Oncology Research 2024年第4期32卷 737-752页

作者： KUNLUN LI DANDAN LI BARBOD HAFEZ MOUNIR M.SALEM BEKHIT YOUSEF A.BIN JARDAN FARS KAED ALANAZI EHAB I.TAHA SAYED H.AUDA FAIQAH ramzan MUHAMMAD JAMIL The Second Affiliated Hospital of Harbin Medical University Harbin Medical UniversityHarbinChina Department of Pharmaceutical Engineering Jiangsu Ocean UniversityLianyungangChina Department of Biological Engineering University of SalfordSalfordUK Department of Pharmaceutics College of PharmacyKing Saud UniversityRiyadhSaudi Arabia Department of Animal and Poultry Production Faculty of Veterinary and Animal SciencesGomal UniversityDera Ismail KhanPakistan Department of Arid Zone Research PARC instituteDera Ismail KhanPakistan

Kidney Renal Clear Cell Carcinoma(KIRC)is a malignant tumor that carries a substantial risk of morbidity and *** MMP family assumes a crucial role in tumor invasion and *** study aimed to uncover the mechanistic relevance of the MMP gene family as a therapeutic target and diagnostic biomarker in Kidney Renal Clear Cell Carcinoma(KIRC)through a comprehensive approach encompassing both computational and molecular ***,Cytoscape,UALCAN,GEPIA,OncoDB,HPA,cBioPortal,GSEA,TIMER,ENCORI,DrugBank,targeted bisulfite sequencing(bisulfite-seq),conventional PCR,Sanger sequencing,and RT-qPCR based analyses were used in the present study to analyze MMP gene family members to accurately determine a few hub genes that can be utilized as both therapeutic targets and diagnostic biomarkers for *** performing STRING and Cytohubba analyses of the 24 MMP gene family members,MMP2(matrix metallopeptidase 2),MMP9(matrix metallopeptidase 9),MMP12(matrix metallopeptidase 12),and MMP16(matrix metallopeptidase 16)genes were denoted as hub genes having highest degree *** analyzing MMP2,MMP9,MMP12,and MMP16 via various TCGA databases and RT-qPCR technique across clinical samples and KIRC cell lines,interestingly,all these hub genes were found significantly overexpressed at mRNA and protein levels in KIRC samples relative to *** notable effect of the up-regulated MMP2,MMP9,MMP12,and MMP16 was also documented on the overall survival(OS)of the KIRC ***,targeted bisulfite-sequencing(bisulfite-seq)analysis revealed that promoter hypomethylation pattern was associated with up-regulation of hub genes(MMP2,MMP9,MMP12,and MMP16).In addition to this,hub genes were involved in various diverse oncogenic *** MMP gene family members(MMP2,MMP9,MMP12,and MMP16)may serve as therapeutic targets and prognostic biomarkers in KIRC.

关键词： KIRC MMP gene family Chemotherapy Overall survival

Variable viscosity effects on the flow of MHD hybrid nanofluid containing dust particles over a needle with Hall current——a Xue model exploration

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Communications in Theoretical Physics 2022年第5期74卷 121-131页

作者： Muhammad ramzan Hammad Alotaibi Department of Computer Science Bahria UniversityIslamabad44000Pakistan Department of Mathematics College of ScienceTaif UniversityPOBox 11099Taif 21944Saudi Arabia

This study scrutinizes the flow of engine oil-based suspended carbon nanotubes magnetohydrodynamics(MHD)hybrid nanofluid with dust particles over a thin moving needle following the Xue *** analysis also incorporates the effects of variable viscosity with Hall *** heat transfer analysis,the effects of the Cattaneo–Christov theory and heat generation/absorption with thermal slip are integrated into the temperature *** Tiwari–Das nanofluid model is used to develop the envisioned mathematical *** similarity transformation,the governing equations for the flow are translated into ordinary differential *** bvp4c method based on Runge–Kutta is used,along with a shooting *** are used to examine and depict the consequences of significant parameters on involved *** results revealed that the temperature of the fluid and boundary layer thickness is diminished as the solid volume fraction is ***,with an enhancement in the variable viscosity parameter,the velocity distribution becomes more *** results are substantiated by assessing them with an available study.

关键词： hybrid nanofluid dusty fluid variable viscosity Cattaneo-Christov heat flux model Hall current

Automatic Unusual Activities Recognition Using Deep Learning in Academia

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Computers, Materials & Continua 2022年第1期70卷 1829-1844页

作者： Muhammad ramzan Adnan Abid Shahid Mahmood Awan School of Systems and Technology University of Management and TechnologyLahore54782Pakistan Department of Computer Science and Information Technology University of SargodhaSargodha40100Pakistan School of Electronics Computing and MathematicsUniversity of DerbyDerbyUnited Kingdom

In the current era,automatic surveillance has become an active research problem due to its vast real-world applications,particularly for maintaining law and order.A continuous manual monitoring of human activities is a tedious *** use of cameras and automatic detection of unusual surveillance activity has been growing exponentially over the last few *** computer vision techniques have been applied for observation and surveillance of real-world *** research study focuses on detecting and recognizing unusual activities in an academic situation such as examinationhalls,which may help the invigilators observe and restrict the students from cheating or using *** the best of our knowledge,this is the first research work in this area that develops a dataset for unusual activities in the examination and proposes a deep learning model to detect those unusual *** proposed model has been named Automatic Unusual Activity Recognition(AUAR),which employsmotion-based frame extraction approaches to extract key-frames and then applies advanced deep learning Convolutional Neural Network algorithm with diverse *** evaluation using standard performancemeasures confirmthat theAUARmodel outperforms the already proposed approaches for unusual activity *** from evaluating the proposed model on the examination dataset,we also apply AUAR on Violent and Movies datasets,widely used in the relevant literature to detect suspicious *** results reveal that AUAR performs well on various data sets compared to existing state-of-the-art models.

关键词： Deep learning unusual activities examination CNN surveillance human activity recognition

Contextual Text Mining Framework for Unstructured Textual Judicial Corpora through Ontologies

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Computer Systems Science & Engineering 2022年第12期43卷 1357-1374页

作者： Zubair Nabi ramzan Talib Muhammad Kashif Hanif Muhammad Awais Department of Computer Science Government College UniversityFaisalabad38000Pakistan Department of Software Engineering Government College UniversityFaisalabad38000Pakistan

Digitalization has changed the way of information processing, and newtechniques of legal data processing are evolving. Text mining helps to analyze andsearch different court cases available in the form of digital text documents toextract case reasoning and related data. This sort of case processing helps professionals and researchers to refer the previous case with more accuracy in reducedtime. The rapid development of judicial ontologies seems to deliver interestingproblem solving to legal knowledge formalization. Mining context informationthrough ontologies from corpora is a challenging and interesting field. Thisresearch paper presents a three tier contextual text mining framework throughontologies for judicial corpora. This framework comprises on the judicial corpus,text mining processing resources and ontologies for mining contextual text fromcorpora to make text and data mining more reliable and fast. A top-down ontologyconstruction approach has been adopted in this paper. The judicial corpus hasbeen selected with a sufficient dataset to process and evaluate the *** experimental results and evaluations show significant improvements incomparison with the available techniques.

关键词： Natural language processing judicial corpora contextual text mining ontologies information extraction information retrieval

Electronic fingerprint mechanism of NO_(x) sensor based on single-material SnP_(3) logical junction

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npj Computational Materials 2022年第1期8卷 2107-2116页

作者： Muhammad S.ramzan Agnieszka B.Kuc Han Seul Kim Department of Physics and Earth Sciences Jacobs University BremenCampus Ring 128759BremenGermany Institut für Physik Carl von Ossietzky Universität Oldenburg26129OldenburgGermany Helmholtz-Zentrum Dresden-Rossendorf Abteilung RessourcenökologieForschungsstelle LeipzigPermoserstr.1504318LeipzigGermany Division of National Supercomputing R&D Korea Institute of Science and Technology Information(KISTI)245 Daehak-roYuseong-guDaejeon34141Republic of Korea

An extraordinary sensing ability of the SnP3-based single-material logical junction for harmful NO_(x)gases was explored in the present work through a set of first-principles electronic structure *** a sensing platform,a metal-semiconductor-metal lateral junction composed of a single material was designed based on the metallic/semiconducting characteristics of trilayer/monolayer SnP_(3).Lacking a Schottky barrier at the electrode-channel interface,the gas-specific charge transfer between the SnP_(3) layer and gas molecules was precisely detected based on the current-voltage ***_(x)gases with strong adsorption strength and charge transfer amount on the SnP_(3)substrate were shown to be particularly well detected in this manner,in terms of either the absolute magnitude of the current or negative differential resistance(NDR)at a reasonably small bias voltage as a sensing *** work will provide a new pathway to design a Schottky barrier-free metal-semiconductor junction for highly sensitive sensor applications.

关键词： gases barrier charge