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Quality and Crop Yield Potential of Moderately Degraded Alfisols Under Different Nutrient Inputs and Cropping Patterns

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Pedosphere 2019年第2期29卷 235-247页

作者： Wiqar AHMAD Farmanullah khan Zahir SHAH muhammad jamal khan Department of Soil and Environmental Sciences The University of Agriculture PeshawarAMK Campus Department of Soil and Environmental Sciences The University of AgriculturePeshawar

Crop performance on degraded soil needs special management practices to overcome soil quality limitations. In a 2-year(from summer 2006 to winter 2007–2008) field trial on a moderately degraded Alfisol in Swabi District(34°7′12′′N, 72°28′20′′E), Pakistan,the effects of three cropping patterns, cereal-cereal(CC), cereal-legume(CL), and cereal-cereal and legume intercrop(CLI), were tested in main plots under four fertilization treatments in sub-plots, including no fertilization(control), farmers' practice(FP, 60:45 kg ha^(-1) N:P_2O_5), recommended dose(RD, 120:90:60 kg ha^(-1) N:P_2O_5:K_2O), and integrated nutrient management(INM, 20 t ha^(-1) farmyard manure integrated with 50% N, 100% P, and K of recommended dose), using a split-plot randomized complete block design. The performance of CL was superior than CC in plant height, leaf area index(LAI), cob length, grain yield, biological yield, and grain protein(8%, 26%, 8%, 5%, 10%, and 8% increases, respectively), while CLI confirmed significant improvement only in LAI(25%) over CC. Response to nutrient inputs from all sources was in the order of INM > RD > FP > control, and the maximum net economic return by INM(23% and 2.5 times higher than RD and FP, respectively) indicated severe deficiency of both macro-and micro-nutrients in the soil as well as degraded physical properties. Increases in soil organic matter, total N, total mineral N, available P and K, total porosity, and available water-holding capacity by 6%, 34%, 24%, 50%, 13%, 5%, and 7%, respectively, and decrease in soil bulk density by 4% after four crop seasons indicated optimistic changes in soil quality as a result of the combined effects of fertilization from organic and inorganic sources and legumes within crop rotation. This study suggests that keeping the soil covered under cereal-legume rotation crops all year round and treatment with INM(50% N from organic source and 50% from inorganic source) are the best management practice for sustained produc

关键词： crop rotation crop performance degraded soil farmyard manure integrated nutrient management legume intercrop sustained production

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FPGA Implementation of Elliptic-Curve Diffie Hellman Protocol

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Computers, Materials & Continua 2022年第10期73卷 1879-1894页

作者： Sikandar Zulqarnain khan Sajjad Shaukat jamal Asher Sajid muhammad Rashid Department of Aeronautical Engineering Estonian Aviation AcademyTartu61707Estonia Department of Mathematics College of ScienceKing Khalid UniversityAbha61413Saudi Arabia Department of Electrical Engineering Bahria UniversityIslamabad44000Pakistan Department of Computer Engineering Umm Al-Qura UniversityMakkah21955Saudi Arabia

This paper presents an efficient crypto processor architecture for key agreement using ECDH(Elliptic-curve Diffie Hellman)protocol over GF2163.The composition of our key-agreement architecture is expressed in consisting of the following:(i)Elliptic-curve Point Multiplication architecture for public key generation(DESIGN-I)and(ii)integration of DESIGN-I with two additional routing multiplexers and a controller for shared key generation(DESIGN-II).The arithmetic operators used in DESIGN-I and DESIGNII contain an adder,squarer,a multiplier and inversion.A simple shift and add multiplication method is employed to retain lower hardware ***,an essential inversion operation is operated using the Itoh-Tsujii algorithm with similar hardware resources of used squarer and multiplier *** proposed architecture is implemented in a Verilog *** implementation results are given on a Xilinx Virtex-7 FPGA(field-programmable gate array)*** DESIGN-I and DESIGN-II over GF2163,(i)the utilized Slices are 3983 and 4037,(ii)the time to compute one public key and a shared secret is 553.7μs and 1170.7μs and(iii)the consumed power is 29μW and 57μ***,the achieved area optimized and power reduced results show that the proposed ECDH architecture is a suitable alternative(to generate a shared secret)for the applications that require low hardware resources and power consumption.

关键词： Elliptic curve cryptography point multiplication key-agreement diffie hellman area optimized architecture FPGA

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Heat Transfer Enhancement of an Automobile Engine Radiator using ZnO Water Base Nanofluids

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Journal of Thermal Science 2020年第4期29卷 1010-1024页

作者： muhammad QASIM muhammad SAJID KAMRAN muhammad AMMAR muhammad ALI jamal muhammad YASAR JAVAID Department of Mechanical Engineering University of Engineering and TechnologyLahore 54890Pakistan Department of Chemical Engineering Technology Government College UniversityFaisalabad 38000Pakistan Department of Mechanical Engineering Technology Government College UniversityFaisalabad 38000Pakistan

In this research paper, the forced convective heat transfer enhancement of a Suzuki Mehran(VXR) 2016 radiator(heat exchanger) along with pressure drop and friction factor by utilizing Zinc oxide(Zn O) water based nanofluids has been experimentally studied. Three types of nanofluids with different volumetric concentrations of Zn O nanoparticles(0–0.3%) were employed in order to understand its effect on heat transfer enhancement. The experimental setup was completely designed as closely as possible to the car cooling system. The experimentation has been done under laminar flow conditions(186≤Re≤1127) at different fluid volume flow rates(2–12 L/min) and constant fluid inlet temperature(70°C) to the automobile radiator. A maximum enhancement in heat transfer rate, overall heat transfer coefficient and Nusselt number was obtained up to 41%, 50% and 31% by using nanofluid with 0.2% volumetric concentration of nanoparticles respectively. On the other hand, the mean enhancement in pressure drop and friction factor was obtained up to 47% and 46% by using nanofluid with the same volumetric concentration of nanoparticles i.e. 0.2% respectively. The experimental results also revealed that the heat transfer rate, overall heat transfer coefficient and Nusselt number of nanofluids increases by increasing the volume flow rates and volumetric concentration of nanoparticles. However, these thermal performance parameters of nanofluids started to decline when the volumetric concentration of nanoparticles was increased from 0.2% to 0.3%. Furthermore, pressure drop and friction factor of nanofluids increase by increasing the volumetric concentration of nanoparticles, while pressure drop increases and friction factor decreases by increasing the volume flow rate of nanofluids respectively. At the end, the thermal efficiency of automobile radiator with high cooling rates was obtained by using nanofluid with 0.2% volumetric concentration of nanoparticles.

关键词： ZnO nanoparticles heat transfer enhancement thermal efficiency automobile radiator

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Variable range hopping transport and dielectric relaxation mechanism in GdCrO_(3) rare-earth orthochromite perovskite

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Journal of Rare Earths 2024年第7期42卷 1304-1316,I0004页

作者： muhammad Javed Ayaz Arif khan jamal Kazmi Naeem Akbar Said Nasir Khisro Amanullah Dar Aleem Dad khan Tareen Mohd Ambri Mohamed Department of Physics The University of Azad Jammu and KashmirMuzaffarabad13100Pakistan Department of Physics University of Kotli Azad Jammu and KashmirKotli11100Pakistan Institute of Microengineering and Nanoelectronics Universiti Kebangsaan Malaysia43600BangiSelangorMalaysia Department of Mathematics University of Kotli Azad Jammu and KashmirKotli11100Pakistan

The polycrystalline GdCrO_(3)(GCO)perovskite orthochromite was synthesized by the sol-gel auto-combustion *** Rietveld refined X-ray diffraction(XRD)profile of GCO confirms that the orthorhombic phase crystallizes in perovskite crystal structure with space group *** transmission electron microscopy and selected area electron diffraction divulge the polycrystalline nature of the perovskite *** field emission scanning electron microscopy(FESEM)images reveal the microstructural polyhedral growth of grains separated by sharp grain *** chemical states of the ions present in the compound were investigated by X-ray photoelectron spectroscopy(XPS)studies,and the electrical pathways were *** impedance studies were carried out in the experimental frequency and temperature ranges of 40 Hz-4 MHz and 178-408 K,*** equivalent circuit model(RGQG)(RGBQGB)resolves the impedance response into two contributions originating from the intra-grain and inter-granular micro-constituents of the *** electrical conduction mechanism is based on the Mott variable range hopping *** complex electric modulus studies demonstrate the short-and long-range mobility of the charge carriers and rule out the presence of electrode effects on the dielectric relaxation mechanism of the *** decreasing pattern of dielectric permittivity with frequency is explained by the Maxwell-Wagner type of *** frequency dependence of the loss factor exhibits the presence of thermally activated relaxation time distribution in the material.

关键词： Auto-combustion Perovskite Electro-ceramic Dielectric Electrical transport Impedance

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Classification of Citrus Plant Diseases Using Deep Transfer Learning

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Computers, Materials & Continua 2022年第1期70卷 1401-1417页

作者： muhammad Zia Ur Rehman Fawad Ahmed muhammad Attique khan Usman Tariq Sajjad Shaukat jamal Jawad Ahmad Iqtadar Hussain Department of Electrical Engineering HITEC UniversityTaxilaPakistan Department of Computer Science HITEC UniversityTaxilaPakistan College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-KhrajSaudi Arabia Department of Mathematics College of ScienceKing Khalid UniversityAbhaSaudi Arabia School of Computing Edinburgh Napier UniversityUK Department of Mathematics Statisticsand PhysicsQatar UniversityDoha2713Qatar

In recent years,the field of deep learning has played an important role towards automatic detection and classification of diseases in vegetables and *** in turn has helped in improving the quality and production of vegetables and *** fruits arewell known for their taste and nutritional *** are one of the natural and well known sources of vitamin C and planted *** are several diseases which severely affect the quality and yield of citrus *** this paper,a new deep learning based technique is proposed for citrus disease *** different pre-trained deep learning models have been used in this *** increase the size of the citrus dataset used in this paper,image augmentation techniques are ***,to improve the visual quality of images,hybrid contrast stretching has been *** addition,transfer learning is used to retrain the pre-trainedmodels and the feature set is enriched by using feature *** fused feature set is optimized using a meta-heuristic algorithm,the Whale Optimization Algorithm(WOA).The selected features are used for the classification of six different diseases of citrus *** proposed technique attains a classification accuracy of 95.7%with superior results when compared with recent techniques.

关键词： Citrus plant disease classification deep learning feature fusion deep transfer learning

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Deep Learning-Based Classification of Fruit Diseases:An Application for Precision Agriculture

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Computers, Materials & Continua 2021年第2期66卷 1949-1962页

作者： Inzamam Mashood Nasir Asima Bibi jamal Hussain Shah muhammad Attique khan muhammad Sharif Khalid Iqbal Yunyoung Nam Seifedine Kadry Department of Computer Science HITEC UniversityTaxila47040Pakistan Department of Computer Science COMSATS University IslamabadWah CampusWah Cantt47080Pakistan Department of Computer Science COMSATS University IslamabadAttock CampusAttockPakistan Department of Computer Science and Engineering Soonchunhyang UniversityAsanSouth Korea Department of Mathematics and Computer Science Faculty of ScienceBeirut Arab UniversityBeirutLebanon

Agriculture is essential for the economy and plant disease must be *** recognition of problems is important,but the manual inspection is slow,error-prone,and has high manpower and time *** intelligence can be used to extract fruit color,shape,or texture data,thus aiding the detection of ***,the convolutional neural network(CNN)techniques show a massive success for image classification *** extracts more detailed features and can work efficiently with large *** this work,we used a combined deep neural network and contour feature-based approach to classify fruits and their diseases.A fine-tuned,pretrained deep learning model(VGG19)was retrained using a plant dataset,from which useful features were ***,contour features were extracted using pyramid histogram of oriented gradient(PHOG)and combined with the deep features using serial based *** the fusion process,a few pieces of redundant information were added in the form of ***,a“relevance-based”optimization technique was used to select the best features from the fused vector for the final *** the use of multiple classifiers,an accuracy of up to 99.6%was achieved on the proposed method,which is superior to previous ***,our approach is useful for 5G technology,cloud computing,and the Internet of Things(IoT).

关键词： Agriculture deep learning feature selection feature fusion fruit classification

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Brain Tumor Detection and Classification Using PSO and Convolutional Neural Network

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Computers, Materials & Continua 2022年第12期73卷 4501-4518页

作者： muhammad Ali jamal Hussain Shah muhammad Attique khan Majed Alhaisoni Usman Tariq Tallha Akram Ye Jin Kim Byoungchol Chang Department of Computer Science COMSATS University IslamabadWah CampusPakistan Departmnt of Computer Science HITEC University TaxilaPakistan Computer Sciences Department College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz UniversityAl-KharjSaudi Arabia Department of EE COMSATS University IslamabadWah CampusPakistan Department of Computer Science Hanyang UniversitySeoul04763Korea Center for Computational Social Science Hanyang UniversitySeoul04763Korea

Tumor detection has been an active research topic in recent years due to the high mortality *** vision(CV)and image processing techniques have recently become popular for detecting tumors inMRI *** automated detection process is simpler and takes less time than manual *** addition,the difference in the expanding shape of brain tumor tissues complicates and complicates tumor detection for *** proposed a newframework for tumor detection aswell as tumor classification into relevant categories in this *** tumor segmentation,the proposed framework employs the Particle Swarm Optimization(PSO)algorithm,and for classification,the convolutional neural network(CNN)*** preprocessing techniques such as noise removal,image sharpening,and skull stripping are used at the start of the segmentation ***,PSO-based segmentation is *** the classification step,two pre-trained CNN models,alexnet and inception-V3,are used and trained using transfer *** a serial approach,features are extracted from both trained models and fused features for final *** classification,a variety of machine learning classifiers are *** dice values on datasets BRATS-2018 and BRATS-2017 are 98.11 percent and 98.25 percent,respectively,whereas average jaccard values are 96.30 percent and 96.57%(Segmentation Results).The results were extended on the same datasets for classification and achieved 99.0%accuracy,sensitivity of 0.99,specificity of 0.99,and precision of ***,the proposed method is compared to state-of-the-art existingmethods and outperforms them.

关键词： Magnetic resonance imaging(MRI) tumor segmentation deep learning features extraction classification

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Exploring multi-level risk factors and post-war burdens of trachomatous trichiasis among displaced population in Raya Kobo districts, implication for urgent action

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International Journal of Ophthalmology(English edition) 2023年第8期16卷 1299-1308页

作者： muhammad jamal Fassikaw Kebede Mersa Health Center Habru Woreda North WolloWoldiaAmhara 400Ethiopia School of Public Health College of Health ScienceWoldia UniversityWoldiaAmhara 400Ethiopia

AIM:To estimate post-war burdens of trachomatous trichiasis(TT)and multi-level risk factors among displaced population in Raya Kobo districts,implication for urgent ***:A community-based cross-sectional study was conducted among 603 participants from randomly selected 14 displaced slums in the Raya Kobo *** data was collected from February 16th to March 30th,*** participants were selected using the multistage sampling technique.A structured questionnaire and ophthalmic loupe with×2.5 magnificence were used to collect from ***-level binary logistic regression was used to determine associated factors with TT *** odds ratio(AOR)with 95%confidence interval(CI)were claimed for the strength of association at P<***:We recruited 602(99.9%)participants for the final *** the total,126(20.9%)and 98(16.3%,95%CI:13.5%-19.4%)participants were diagnosed with active trachoma&TT infection,*** age≥45y(AOR=7.9,95%CI:2.4-25.3),having multiple eye infections(AOR=2.73,95%CI:1.47-5.29),poor wealth index(AOR=9.2;95%CI:2.7-23.7)and twice face washing per day(AOR=0.082,95%CI:0.03-0.21)has identified as individual as factors for TT ***,distance between clean water source≥10 km(AOR=6.5,95%CI:3.9-31.3),and latrine availability(AOR=0.35,95%CI:0.21-0.58)were the two community-level factors associated with TT ***:The high prevalence of TT infection post-war throughout the study districts indicates a need for urgent clinical intervention in addition to rapid scaling up surgery,antibiotics,facial cleanliness,and environmental improvement(SAFE)strategies,strategy for high-risk ***≥45y,distance from the clean water source,poor wealth indexes,and eye infection are identified to be risk factors for TT ***,community-level preventative factors for TT infection are found as latrine availability and face washing practice.

关键词： trachoma risk factor displaced population

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Improved Shark Smell Optimization Algorithm for Human Action Recognition

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Computers, Materials & Continua 2023年第9期76卷 2667-2684页

作者： Inzamam Mashood Nasir Mudassar Raza jamal Hussain Shah muhammad Attique khan Yun-Cheol Nam Yunyoung Nam Department of Computer Science COMSATS University IslamabadWah CampusWah Cantt47040Pakistan Department of Computer Science HITEC UniversityTaxilaPakistan Department of Architecture Joongbu UniversityGoyang10279South Korea Department of ICT Convergence Soonchunhyang UniversityAsan31538Korea

Human Action Recognition(HAR)in uncontrolled environments targets to recognition of different actions froma *** effective HAR model can be employed for an application like human-computer interaction,health care,person tracking,and video *** Learning(ML)approaches,specifically,Convolutional Neural Network(CNN)models had beenwidely used and achieved impressive results through feature *** accuracy and effectiveness of these models continue to be the biggest challenge in this *** this article,a novel feature optimization algorithm,called improved Shark Smell Optimization(iSSO)is proposed to reduce the redundancy of extracted *** proposed technique is inspired by the behavior ofwhite sharks,and howthey find the best prey in thewhole search *** proposed iSSOalgorithmdivides the FeatureVector(FV)into subparts,where a search is conducted to find optimal local features fromeach subpart of *** local optimal features are selected,a global search is conducted to further optimize these *** proposed iSSO algorithm is employed on nine(9)selected CNN *** CNN models are selected based on their top-1 and top-5 accuracy in ImageNet *** evaluate the model,two publicly available datasets UCF-Sports and Hollywood2 are selected.

关键词： Action recognition improved shark smell optimization convolutional neural networks machine learning

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Detection of ROS and translocation of ERP-57 in apoptotic induced human neuroblastoma(SH-SY5Y)cells

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BIOCELL 2019年第3期43卷 167-174页

作者： ATIF KAMIL MUBARAK ALI khan muhammad AASIM NADIR ZAMAN khan RAHAM SHER khan MUHSIN jamal WAQAR AHMAD MIR AZAM khan FAZAL JALIL Department of Biotechnology Abdul Wali Khan University Mardan(AWKUM)Garden CampusToru RoadMardanKPKPakistan Department of Biotechnology University of Malakand(UOM)ChakdaraLower DirPakistan Department of Microbiology Abdul Wali Khan University Mardan(AWKUM)Garden CampusToru RoadMardanKPKPakistan Department of Pharmacy University of Malakand(UOM)ChakdaraLower DirPakistan

Several toxic compounds are known to induce apoptosis in mammalian cell *** human neuroblastoma cells(SHSH-SY5Y)were exposed to the phosphatase inhibiting toxin okadaic acid(OA)or hydrogen peroxide(H2O2)to induce apoptosis as well as generate reactive oxygen species(ROS).Mitoxantrone(MXT)was used as a positive control for *** SHSH-SY5Y cells were transfected with eukaryotic expression plasmid pHyPer-dMito encoding mitochondrial-targeted fluorescent or pHyPer-dCito encoding cytoplasmic-targeted fluorescent sensor for hydrogen peroxide(HyPer).The ERp57,also called GRP58(Glucose-regulated protein 58),is a stress protein induced in conditions like glucose starvation and viral *** ERp57 was shown to translocate from the endoplasmatic reticulum to the cell surface in anthracycline-induced apoptotic ***57 co-translocation together with calreticulin has been suggested to be crucial for recognizing tumor cells to induce immunogenic cell ***57 translocation after exposure to okadaic acid was studied using immunofluorescence and confocal *** studies indicated that okadaic acid has induced the translocation of ERp57 to the cellular membrane.

关键词： Apoptosis Cytoplasm Endoplasmic recticulum(ER) ERP-57 Human neuroblastoma cell(SHSH-SY5Y) Immunofluorescence Mitochondria Reactive oxygen species(ROS) Transfection

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