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Morphometry of leaf and shoot variables to assess aboveground biomass structure and carbon sequestration by different varieties of white mulberry(Morus alba L.)

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Journal of Forestry Research 2021年第6期32卷 2291-2300页

作者： ghulam ali Bajwa Muhammad Umair Yasir Nawab Zahid Rizwan Pakistan Forest Institute Peshawar 25130Pakistan National Textile University Faisalabad 37610Pakistan

Mulberry is economically important and can also play a pivotal role in mitigating greenhouse *** and shoot traits were measured for Morus alba ***,*** ***,*** ***,and *** ***-1 to assess aboveground biomass(AGB)and carbon ***-specific and multivariety allometric AGB models were developed using the equivalent diameter at breast height(EDBH)and plant height(H).The completeharvest method was used to measure leaf and shoot traits and biomass,and the ash method was used to measure organic carbon *** results showed significant(p<0.01)varietal differences in leaf and shoot traits,AGB and carbon ***-1 variety had the greatest leaf density(mean±SE:1828.3±0.3 leaves tree^(-1)),Karyansuban had the largest mean leaf area(185.94±8.95 cm^(2)).A diminishing return was found between leaf area and leaf *** had the highest shoot density per tree(46.6±1.83 shoots tree^(-1)),total shoot length(264.1±2.32 m),dry biomass(16.69±0.58 kg tree^(-1)),carbon sequestration(9.99±0.32 kg tree^(-1))and CO_(2) mitigation(36.67±1.16 kg).The variety-specific AGB models b(EDBH)and b(EDBH)2 showed good fit and reasonable accuracy with a coefficient of determination(R^(2))=0.98-0.99,standard error of estimates(SEE)=0.1125-0.3130 and root mean square error(RMSE)=*** multivariety models bln(EDBH)and(EDBH)0.756 showed good-fitness and accuracy with R^(2)=0.85-0.86,SEE=1.6231-1.6445 and RMSE=*** the basis of these findings,variety Latifolia has good potential for biomass production,and allometric equations based on EDBH can be used to estimate AGB with a reasonable accuracy.

关键词： Allometry Biomass estimation CO_(2)mitigation Moraceae Mulberry Regression models

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Deep Learning Framework for Precipitation Prediction Using Cloud Images

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Computers, Materials & Continua 2022年第8期72卷 4201-4213页

作者： Mirza Adnan Baig ghulam ali Mallah Noor Ahmed Shaikh Shah Abdul Latif University Khairpur77150Pakistan

Precipitation prediction(PP)have become one of the significant research areas of deep learning(DL)and machine vision(MV)techniques are frequently used to predict the weather variables(WV).Since the climate change has left significant impact upon weather variables(WV)and continuously changes are observed in temperature,humidity,cloud patterns and other *** cloud images contain sufficient information to predict the precipitation pattern but due to changes in climate,the complex cloud patterns and rapid shape changing behavior of clouds are difficult to consider for rainfall *** of rainfall would provide more meticulous assistance to the farmers to know about the weather conditions and to care their cash *** research proposes a framework to classify the dark cloud patterns(DCP)for prediction of *** framework consists upon three steps to classify the cloud images,first step tackles noise reduction operations,feature selection and preparation of *** step construct the decision model by using convolutional neural network(CNN)and third step presents the performance visualization by using confusion matrix,precision,recall and accuracy *** research contributes(1)real-world clouds datasets(2)method to prepare datasets(3)highest classification accuracy to predict estimated as 96.90%.

关键词： Machine vision SIFT features dark cloud patterns precipitation agriculture

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A Secure and Efficient Information Authentication Scheme for E-Healthcare System

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Computers, Materials & Continua 2023年第9期76卷 3877-3896页

作者： Naveed Khan Jianbiao Zhang ghulam ali Mallah Shehzad Ashraf Chaudhry Faculty of Information Technology Beijing University of TechnologyBeijing100124China Department of Computer Science Shah Abdul Latif UniversityKhairpur66111Pakistan Department of Computer Engineering Faculty of Engineering ArchitectureNisantasi UniversityIstanbul34398Turkey

The mobile cellular network provides internet connectivity for heterogeneous Internet of Things(IoT)*** cellular network consists of several towers installed at appropriate locations within a smart *** cellular towers can be utilized for various tasks,such as e-healthcare systems,smart city surveillance,traffic monitoring,infrastructure surveillance,or sidewalk *** is a primary concern in data broadcasting,particularly authentication,because the strength of a cellular network’s signal is much higher frequency than the associated one,and their frequencies can sometimes be aligned,posing a significant *** a result,that requires attention,and without information authentication,such a barrier cannot be ***,we design a secure and efficient information authentication scheme for IoT-enabled devices tomitigate the flaws in the e-healthcare *** proposed protocol security shall check formally using the Real-or-Random(ROR)model,simulated using ProVerif2.03,and informally using pragmatic *** comparison,the performance phenomenon shall tackle by the already result available in the MIRACL cryptographic lab.

关键词： IoT-enable device e-healthcare authentication edge computing

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Decision Support System for Diagnosis of Irregular Fovea

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Computers, Materials & Continua 2022年第6期71卷 5343-5353页

作者： ghulam ali Mallah Jamil Ahmed Muhammad Irshad Nazeer Mazhar ali Dootio Hidayatullah Shaikh Aadil Jameel Shah Abdul Latif University Khairpur77150Pakistan Sukkur IBA University Sukkur7720Pakistan Shaheed Benazir University Layari Karachi77202Pakistan

Detection of abnormalities in human eye is one of the wellestablished research areas of Machine *** Learning techniques are widely used for the diagnosis of RetinalDiseases(RD).Fovea is one of the significant parts of retina which would be prevented before the involvement of Perforated Blood Vessels(PBV).Retinopathy Images(RI)contains sufficient information to classify structural changes incurred upon PBV but Macular Features(MF)and Fovea Features(FF)are very difficult to detect because features ofMFand FF could be found with Similar Color Movements(SCM)with minor *** paper presents novel method for the diagnosis of Irregular Fovea(IF)to assist the doctors in diagnosis of irregular *** considering all above problems this paper proposes a three-layer decision support system to explore the hindsight knowledge of RI and to solve the classification problem of *** first layer involves data preparation,the second layer builds the decision model to extract the hidden patterns of fundus images by using Deep Belief Neural Network(DBN)and the third layer visualizes the results by using confusion *** paper contributes a data preparation algorithm for irregular fovea and a highest estimated classification accuracy measured about 96.90%.

关键词： Machine learning deep belief neural network eye disease fovea

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Effect of Co substitution on the structural,electrical,and magnetic properties of Bi_(0.9)La_(0.1)FeO_3 by sol-gel synthesis

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International Journal of Minerals,Metallurgy and Materials 2013年第2期20卷 166-171页

作者： ghulam ali Saadat A.Siddiqi Shahid M.Ramay Shahid Atiq Murtaza Saleem Centre of Excellence in Solid State Physics University of the Punjab Interdisciplinary Research Centre in Biomedical Materials COMSATS Institute of Information Technology Chemical Engineering Department College of EngineeringKing Saud University

Cobalt （Co）-doped ***3 multiferroics were synthesized by a sol-gel method based on the auto- combustion technique. As-synthesized powder was examined using various characterization techniques to explore the effect of Co substitution on the properties of Bi0.9La0.1FeO3. X-ray diffraction reveals that Co-doped Bi0.9La0.1FeO3 preserves the perovskite-type rhombohedral structure of BiFeO3, and the composition without Co preserves the original structure of the phase; however, a second-phase Bi2Fe409 has been identified in all other compositions. Surface morphological studies were performed by scanning electron microscopy. Temperature-dependent resistivity of the samples reveals the characteristic insulating behavior of the multiferroic material. The resistivity is found to decrease with the increase both in temperature and Co content. Room temperature frequency-dependent dielectric measurements were also reported. Magnetic measurements show the enhancement in magnetization with the increase in Co content.

关键词： multiferroics cobalt doping microstructure electric properties magnetic properties sol-gel process

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Real-Time Multiple Guava Leaf Disease Detection from a Single Leaf Using Hybrid Deep Learning Technique

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Computers, Materials & Continua 2023年第1期74卷 1235-1257页

作者： Javed Rashid Imran Khan ghulam ali Shafiq ur Rehman Fahad Alturise Tamim Alkhalifah Department of CS&SE Islamic International UniversityIslamabad44000Pakistan Department of IT Services University of OkaraOkara56310Pakistan Department of CS University of OkaraOkara56310Pakistan Department of Botany University of OkaraOkara56310Pakistan Department of Computer College of Science and Arts in Ar RassQassim UniversityAr RassQassim52571Saudi Arabia

The guava plant has achieved viable significance in subtropics and tropics owing to its flexibility to climatic environments,soil conditions and higher human *** is cultivated in vast areas of Asian and Non-Asian countries,including *** guava plant is vulnerable to diseases,specifically the leaves and fruit,which result in massive crop and profitability *** existing plant leaf disease detection techniques can detect only one disease from a ***,a single leaf may contain symptoms of multiple *** study has proposed a hybrid deep learning-based framework for the real-time detection of multiple diseases from a single guava leaf in several ***,Guava Infected Patches Modified MobileNetV2 and U-Net(GIP-MU-NET)has been proposed to segment the infected guava *** proposed model consists of modified MobileNetv2 as an encoder,and the U-Net model’s up-sampling layers are used as a decoder ***,the Guava Leaf SegmentationModel(GLSM)is proposed to segment the healthy and infected *** the final step,the Guava Multiple Leaf Diseases Detection(GMLDD)model based on the YOLOv5 model detects various diseases from a guava *** self-collected datasets(the Guava Patches Dataset and the Guava Leaf Diseases Dataset)are used for training and *** proposed method detected the various defects,including five distinct classes,i.e.,anthracnose,insect attack,nutrition deficiency,wilt,and *** average,the GIP-MU-Net model achieved 92.41%accuracy,the GLSM gained 83.40%accuracy,whereas the proposed GMLDD technique achieved 73.3%precision,73.1%recall,71.0%mAP@0.5 and 50.3 mAP@0.5:0.95 scores for all the aforesaid classes.

关键词： Guava leaf diseases guava leaf segmentation guava patches segmentation multiple leaf diseases guava leaf diseases dataset

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A Machine Learning-Based Attack Detection and Prevention System in Vehicular Named Data Networking

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Computers, Materials & Continua 2023年第11期77卷 1445-1465页

作者： Arif Hussain Magsi ali ghulam Saifullah Memon Khalid Javeed Musaed Alhussein Imad Rida State Key Laboratory of Networking and Switching Technology Beijing University of Post and TelecommunicationBeijing100876China Information Technology Center Sindh Agriculture UniversityTandojam70050Pakistan Department of Computer Engineering College of Computing and InformaticsUniversity of SharjahSharjah27272United Arab Emirate Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Laboratory Biomechanics and Bioengineering University of Technology of CompiegneCompiegne60200France

Named Data Networking(NDN)is gaining a significant attention in Vehicular Ad-hoc Networks(VANET)due to its in-network content caching,name-based routing,and mobility-supporting ***,existing NDN faces three significant challenges,including security,privacy,and *** particular,security attacks,such as Content Poisoning Attacks(CPA),can jeopardize legitimate vehicles with malicious *** instance,attacker host vehicles can serve consumers with invalid information,which has dire consequences,including road *** such a situation,trust in the content-providing vehicles brings a new *** the other hand,ensuring privacy and preventing unauthorized access in vehicular(VNDN)is another ***,NDN’s pull-based content retrieval mechanism is inefficient for delivering emergency messages in *** this connection,our contribution is *** existing rule-based reputation evaluation,we propose a Machine Learning(ML)-based reputation evaluation mechanism that identifies CPA attackers and legitimate *** on ML evaluation results,vehicles accept or discard served ***,we exploit a decentralized blockchain system to ensure vehicles’privacy by maintaining their information in a secure digital ***,we improve the default routing mechanism of VNDN from pull to a push-based content dissemination using Publish-Subscribe(Pub-Sub)*** implemented and evaluated our ML-based classification model on a publicly accessible BurST-Asutralian dataset for Misbehavior Detection(BurST-ADMA).We used five(05)hybrid ML classifiers,including Logistic Regression,Decision Tree,K-Nearest Neighbors,Random Forest,and Gaussian Naive *** qualitative results indicate that Random Forest has achieved the highest average accuracy rate of 100%.Our proposed research offers the most accurate solution to detect CPA in VNDN for safe,secure,and reliable vehicle communication.

关键词： Named data networking vehicular networks reputation caching machine-learning

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Investigation of the sodium storage mechanism of iron fluoride hydrate cathodes using X-ray absorption spectroscopy and mossbauer spectroscopy

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Journal of Energy Chemistry 2023年第2期77卷 535-542,I0014页

作者： ghulam ali Muhammad Akbar Faiza Jan Iftikhar Qamar Wali Beata Kalska Szostko Dariusz Satuła Kyung Yoon Chung Energy Storage Research Center Korea Institute of Science and TechnologyHwarang-ro 14 gil 5Seongbuk-guSeoul 02792South Korea USPCAS-E National University of Sciences and Technology(NUST)H-12Islamabad 44000Pakistan Division of Energy&Environment Technology KIST SchoolKorea University of Science and Technology(UST)Hwarang-ro 14-gil-5Seongbuk-guSeoul 02792South Korea NUTECH School of Applied Sciences and Humanities National University of TechnologyIslamabad 44000Pakistan University of Białystok Faculty of ChemistryCiołkowskiego 1K15-424 BiałystokPoland University of Białystok Faculty of PhysicsCiołkowskiego 1L15-424 BiałystokPoland

Elucidation of a reaction mechanism is the most critical aspect for designing electrodes for highperformance secondary ***,we investigate the sodium insertion/extraction into an iron fluoride hydrate(FeF_(3)·0.5H_(2)O)electrode for sodium-ion batteries(SIBs).The electrode material is prepared by employing an ionic liquid 1-butyl-3-methylimidazolium-tetrafluoroborate,which serves as a reaction medium and precursor for F^(-)*** crystal structure of FeF_(3)·0.5H_(2)O is observed as pyrochlore type with large open 3-D tunnels and a unit cell volume of 1129A^(3).The morphology of FeF_(3)·0.5H_(2)O is spherical shape with a mesoporous *** microstructure analysis reveals primary particle size of around 10 *** FeF_(3)·0.5H_(2)O cathode exhibits stable discharge capacities of 158,210,and 284 mA h g^(-1) in three different potential ranges of 1.5-4.5,1.2-4.5,and 1.0-4.5 V,respectively at 0.05 C *** specific capacities remained stable in over 50 cycles in all three potential ranges,while the rate capability was best in the potential range of 1.5-4.5 *** electrochemical sodium storage mechanism is studied using X-ray absorption spectroscopy,indicating higher conversion at a more discharged ***-situ M?ssbauer spectroscopy strengthens the results for reversible reduction/oxidation of *** results will be favorable to establish high-performance cathode materials with selective voltage window for SIBs.

关键词： Iron fluoride Sodium-ion batteries Pyrochlore X-ray absorption spectroscopy Mössbauer spectroscopy

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Metabolic investigations in patients with hepatitis B and C

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World Journal of Gastroenterology 2010年第5期16卷 603-607页

作者： Abdul Aziz Mastoi Bikha Ram Devrajani Syed Zulfiquar ali Shah Qasim Rohopoto Sikander ali Memon Marya Baloch ghulam ali Qureshi Waqas Sami M.A.Kazi Institute of Chemistry University of SindJamshoro 75000Pakistan Department of Medicine Liaquat University of Medical and Health SciencesJamshoro 75000Pakistan Medical Research Centre Liaquat University of Medical and Health SciencesJamshoro 75000 Pakistan Department of Biochemistry University of Health SciencesLahore 54600Pakistan

AIM:To investigate the similarities and dissimilarities in patients with hepatitis B and hepatitis C,clinically and metabolically. METHODS:Fifty patients with hepatitis B virus and hepatitis C virus infection were included in this study, along with fifty healthy controls for comparison *** blood(10 mL)samples from patients and healthy subjects were collected and made to clot before serum was separated and immediately levels of the enzymes,alkaline phosphatase(ALK),creatinine phosphokinase(CPK),lactate dehydrogenase (LDH),serum glutamate oxaloacetate transaminase(sGOT)and serum glutamate pyruvate transaminase(sGPT)were determined by a kit *** total con-tent of each metal the serum samples were analyzed using atomic absorption *** of cholesterol,triglycerides,urea,creatinine and uric acid were determined using a kit method on Microlab 300. RESULTS:Serum magnesium and copper levels remained unchanged,whereas the concentration of zinc decreased and iron increased significantly in both groups of *** antioxidant activity was significantly decreased in both hepatitis B and *** the enzymes analyzed,ALK,s-GPT,LDH and s-GOT were all significantly increased in both patients with hepatitis B and C whereas CPK was significantly decreased in patients with hepatitis B and remained unchanged in patients with hepatitis C. CONCLUSION:The information accumulated by this study will help provide a better understanding of involved metabolic processes in order to design appropriate therapeutic approaches for treating these patients,so they can recover and lead normal lives.

关键词： Hepatitis B virus Hepatitis C virus Antioxidant activity Metal content Enzyme activity

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Deep Learning Method to Detect the Road Cracks and Potholes for Smart Cities

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Computers, Materials & Continua 2023年第4期75卷 1863-1881页

作者： Hong-Hu Chu Muhammad Rizwan Saeed Javed Rashid Muhammad Tahir Mehmood Israr Ahmad Rao Sohail Iqbal ghulam ali College of Civil Engineering Hunan UniversityChangsha410082China Department of CS University of OkaraOkara56310Pakistan Department of CS&SE Islamic International UniversityIslamabad44000Pakistan Department of IT Services University of OkaraOkara56310Pakistan Department of CS Government College UniversityFaisalabad38000Pakistan Department of Automation Science Beihang UniversityBeijing100191China

The increasing global population at a rapid pace makes road trafficdense;managing such massive traffic is challenging. In developing countrieslike Pakistan, road traffic accidents (RTA) have the highest mortality percentageamong other Asian countries. The main reasons for RTAs are roadcracks and potholes. Understanding the need for an automated system forthe detection of cracks and potholes, this study proposes a decision supportsystem (DSS) for an autonomous road information system for smart citydevelopment with the use of deep learning. The proposed DSS works in layerswhere initially the image of roads is captured and coordinates attached to theimage with the help of global positioning system (GPS), communicated tothe decision layer to find about the cracks and potholes in the roads, andeventually, that information is passed to the road management informationsystem, which gives information to drivers and the maintenance *** the decision layer, we projected a CNN-based model for pothole crackdetection (PCD). Aimed at training, a K-fold cross-validation strategy wasused where the value of K was set to 10. The training of PCD was completedwith a self-collected dataset consisting of 6000 images from Pakistani *** proposed PCD achieved 98% of precision, 97% recall, and accuracy whiletesting on unseen images. The results produced by our model are higher thanthe existing model in terms of performance and computational cost, whichproves its significance.

关键词： Road cracks and potholes CNN smart cities pothole crack detection decision support system

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