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小麦秸秆发酵产生的真菌Pleurotus ostreatus IBL-02锰过氧化物酶的溶胶-凝胶固定化及其催化污水脱色(英文)

催化学报 2013年第9期34卷 1756-1761页

作者： muhammad Asgher Bazgha aslam Hafiz muhammad Nasir Iqbal Industrial Biotechnology Laboratory Department of Chemistry and BiochemistryUniversity of Agriculture

Solid state bio-processing of wheat straw was carried out through an indigenous fungal strain Pleurotus ostreatus IBL-02 under pre-optimized fermentation conditions. The maximum activity, 692±12 U/mL, of the industrially important manganese peroxidase (MnP) enzyme was recorded after five days of still culture incubation. The crude MnP was 2.1-fold purified with a specific activity of 860 U/mg after purification on a Sephadex-G-100 gel column. On native and SDS-PAGE electrophoresis gels, the purified MnP fraction was a single homogenous band of 45 kDa. An active fraction of MnP was immobilized using hydrophobic sol-gel entrapment comprising tetramethoxysilane (T) and propyltrimethoxysilane (P) at different T:P molar ratios. Characterization revealed that after 24 h incubation at varying pH and temperatures, the MnP fraction immobilized at a T:P ratio of 1:2 in the sol-gel retained 82% and 75% of its original activity at pH4 and 70 ℃, respectively. The optimally active fraction at a 1:2 T:P ratio was tested against MnSO4 as a substrate to determine the kinetic catalytic constants KM and Vmax . To explore the industrial applicability of P. ostreatus IBL-02 MnP, both the free and immobilized MnP were used for the decolorization of four different textile industrial effluents. A maximum of 100% decolorization was achieved for the different textile effluents within the shortest time period. A lower KM , higher Vmax , hyper-activation, and enhanced acidic and thermal resistance up to 70 ℃ were the novel catalytic features of the sol-gel immobilized MnP, suggesting that it may be a potential candidate for biotechnological applications particularly for textile bioremediation purposes.

关键词： Pleurotus ostreatus IBL-02 Bio-catalysis Manganese peroxidase Immobilization Sol-gel Textile effluent Decolorization

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New type of cancer patients based on triangular cubic hesitant fuzzy TOPSIS method

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International Journal of Biomathematics 2020年第1期13卷 55-78页

作者： Aliya Fahmi muhammad aslam Fuad Ali Ahmed Almahdi Fazli Amin Department of Mathematics Hazara University MansehraPakistan Department of Mathematics College of Sciences King Khalid UniversityAbhaSaudi Arabia

In this paper,we define the new idea of triangular cubic hesitant fuzzy number(TCHFN).We discuss some basic operational laws of triangular cubic hesitant fuzzy number and hamming distance of *** introduce the new concept of triangular cubic hesitant TOPSIS ***,we extend the classical cubic hesitant the technique for order of preference by similarity to ideal solution(TOPSIS)method to solve the Multi-Criteria decision-making(MCDM)method based on triangular cubic hesitant TOPSIS *** new ranking method for TCHFNs is used to rank the ***,an illustrative example is given to verify and demonstrate the practicality and effectiveness of the proposed method.

关键词： Triangular cubic hesitant fuzzy number MCDM triangular cubic hesitant fuzzy TOPSIS method numerical application.

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Sustainable food industrial waste management through single cell protein production and characterization of protein enriched bread

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Food Bioscience 2022年第2期46卷 639-646页

作者： muhammad Kashif Iqbal Khan muhammad Asif Zafar Ullah Razzaq Akmal Nazir Abid aslam Maan Department of Food Engineering University of AgricultureFaisalabadPakistan National Institute of Food Science and Technology University of AgricultureFaisalabadPakistan Department of Food Science College of Agriculture and Veterinary MedicineUnited Arab Emirates UniversityAl AinUnited Arab Emirates

Production of single cell protein(SCP)from food waste is one of the promising approaches for excellent waste *** the present study,SCP was produced through submerged fermentation using selected food wastes(banana peel,citrus peel,carrot pomace and potato peel).During process optimization,combinations of various temperature and nitrogen sources were studied for optimum SCP yield(g/100g).The results indicated that maximum SCP yield was obtained at 30℃ for 7 days on potato peels,whereas citrus and banana peels exhibited the lowest SCP yield at the same process *** SCP compositional analysis indicated that the amount of non-essential amino acids was significantly higher than wheat ***,SCP enriched bread was prepared by adding SCP at different concentrations(0,4,8,and 12%).The organoleptic properties indicated that SCP addition up to 4%was acceptable to prepare protein enriched ***,SCP may be effectively used for food waste management and food security.

关键词： Fruit waste Food security Single cell protein Bread Protein deficiency Malnourishment

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Two-Stream Deep Learning Architecture-Based Human Action Recognition

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Computers, Materials & Continua 2023年第3期74卷 5931-5949页

作者： Faheem Shehzad muhammad Attique Khan muhammad Asfand E.Yar muhammad Sharif Majed Alhaisoni usman Tariq Arnab Majumdar Orawit Thinnukool Department of Computer Science COMSATS University IslamabadWah CampusPakistan Department of Computer Science HITEC UniversityTaxilaPakistan Department of Computer Science Bahria UniversityIslamabadPakistan Computer Sciences Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia College of Computer Engineering and Science Prince Sattam Bin Abdulaziz UniversityAl-Kharaj11942Saudi Arabia Faculty of Engineering Imperial College LondonLondonSW72AZUK College of Arts Mediaand TechnologyChiang Mai UniversityChiang Mai50200Thailand

Human action recognition(HAR)based on Artificial intelligence reasoning is the most important research area in computer *** breakthroughs in this field have been observed in the last few years;additionally,the interest in research in this field is evolving,such as understanding of actions and scenes,studying human joints,and human posture *** HAR techniques are introduced in the ***,the challenge of redundant and irrelevant features reduces recognition *** also faced a few other challenges,such as differing perspectives,environmental conditions,and temporal variations,among *** this work,a deep learning and improved whale optimization algorithm based framework is proposed for *** proposed framework consists of a few core stages i.e.,frames initial preprocessing,fine-tuned pre-trained deep learning models through transfer learning(TL),features fusion using modified serial based approach,and improved whale optimization based best features selection for final *** pre-trained deep learning models such as InceptionV3 and Resnet101 are fine-tuned and TL is employed to train on action recognition *** fusion process increases the length of feature vectors;therefore,improved whale optimization algorithm is proposed and selects the best *** best selected features are finally classified usingmachine learning(ML)*** publicly accessible datasets such as Ut-interaction,Hollywood,Free Viewpoint Action Recognition usingMotion History Volumes(IXMAS),and centre of computer vision(UCF)Sports,are employed and achieved the testing accuracy of 100%,99.9%,99.1%,and 100%*** with state of the art techniques(SOTA),the proposed method showed the improved accuracy.

关键词： Human action recognition deep learning transfer learning fusion of multiple features features optimization

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Security Requirement Management for Cloud-Assisted and Internet of Things—Enabled Smart City

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Computers, Materials & Continua 2021年第4期67卷 625-639页

作者： muhammad usman Tariq muhammad Babar Mian Ahmad Jan Akmal Saeed Khattak Mohammad Dahman Alshehri Abid Yahya Abu Dhabi School of Management Abu Dhabi6844United Arab Emirates Department of Computing and Technology Iqra UniversityIslamabad44000Pakistan Institute of Research and Development Duy Tan UniversityDa Nang550000Vietnam The Faculty of Information Technology Duy Tan UniversityDa Nang550000Vietnam Department of Computer Sciences Abdul Wali Khan UniversityMardan23200Pakistan Department of Computer Sciences Quaid-i-Azam UniversityIslamabad44000Pakistan Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Botswana International University of Science and Technology Palapye016Botswana

The world is rapidly changing with the advance of information *** expansion of the Internet of Things(IoT)is a huge step in the development of the smart *** IoT consists of connected devices that transfer *** IoT architecture permits on-demand services to a public pool of *** computing plays a vital role in developing IoT-enabled smart *** integration of cloud computing enhances the offering of distributed resources in the smart *** management of security requirements of cloud-assisted IoT systems can bring about risks to availability,security,performance,condentiality,and *** key reason for cloud-and IoT-enabled smart city application failure is improper security practices at the early stages of *** article proposes a framework to collect security requirements during the initial development phase of cloud-assisted IoT-enabled smart city *** three-layered architecture includes privacy preserved stakeholder analysis(PPSA),security requirement modeling and validation(SRMV),and secure cloud-assistance(SCA).A case study highlights the applicability and effectiveness of the proposed framework.A hybrid survey enables the identication and evaluation of signicant challenges.

关键词： Security privacy smart city Internet of Things cloud computing

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Conversion of adverse data corpus to shrewd output using sampling metrics

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Visual Computing for Industry,Biomedicine,and Art 2020年第1期3卷 202-214页

作者： Shahzad Ashraf Sehrish Saleem Tauqeer Ahmed Zeeshan aslam Durr muhammad College of Internet of Things Engineering Hohai UniversityChangzhouJiangsu 210032China muhammad Nawaz Sharif University of Engineering&Technology Multan 66000Pakistan Petroweld Kurdistan Region Erbil 42002Iraq Pakistan Steel Mills Karachi Karachi 75200Pakistan

An imbalanced dataset is commonly found in at least one class,which are typically exceeded by the other ones.A machine learning algorithm(classifier)trained with an imbalanced dataset predicts the majority class(frequently occurring)more than the other minority classes(rarely occurring).Training with an imbalanced dataset poses challenges for classifiers;however,applying suitable techniques for reducing class imbalance issues can enhance classifiers’*** this study,we consider an imbalanced dataset from an educational ***,we examine all shortcomings regarding the classification of an imbalanced ***,we apply data-level algorithms for class balancing and compare the performance of *** performance of the classifiers is measured using the underlying information in their confusion matrices,such as accuracy,precision,recall,and F *** results show that classification with an imbalanced dataset may produce high accuracy but low precision and recall for the minority *** analysis confirms that undersampling and oversampling are effective for balancing datasets,but the latter dominates.

关键词： Classification Machine learning Spread subsampling Class imbalance

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Cache in fog computing design,concepts,contributions,and security issues in machine learning prospective

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Digital Communications and Networks 2023年第5期9卷 1033-1052页

作者： muhammad Ali Naeem Yousaf Bin Zikria Rashid Ali usman Tariq Yahui Meng Ali Kashif Bashir School of Science Guangdong University of Petrochemical TechnologyMaoming525000China Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Republic of Korea Department of Information and Communication Technologies Universitat Pompeu FabraBarcelonaSpain College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Department of Computing and Mathematics Manchester Metropolitan UniversityManchesterUnited Kingdom Woxsen School of Business Woxsen UniversityHyderabadIndia Department of Computer Science and Mathematics Lebanese American UniversityBeirutLebanon

The massive growth of diversified smart devices and continuous data generation poses a challenge to communication *** deal with this problem,communication networks consider fog computing as one of promising technologies that can improve overall communication *** brings on-demand services proximate to the end devices and delivers the requested data in a short *** computing faces several issues such as latency,bandwidth,and link utilization due to limited resources and the high processing demands of end *** this end,fog caching plays an imperative role in addressing data dissemination *** study provides a comprehensive discussion of fog computing,Internet of Things(IoTs)and the critical issues related to data security and dissemination in fog ***,we determine the fog-based caching schemes and contribute to deal with the existing issues of fog ***,this paper presents a number of caching schemes with their contributions,benefits,and challenges to overcome the problems and limitations of fog *** also identify machine learning-based approaches for cache security and management in fog computing,as well as several prospective future research directions in caching,fog computing,and machine learning.

关键词： Internet of things Cloud computing Fog computing Caching Latency

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Impact of Tillage and Herbicides on Weed Density, Yield and Quality of Cotton in Wheat Based Cropping System

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Journal of Integrative Agriculture 2013年第9期12卷 1568-1579页

作者： Khalid usman Niamatullah Khan muhammad Umar Khan Aziz ur Rehman Said Ghulam Department of Agronomy Faculty of AgricultureGomal University Department of Agriculture Chemistry Faculty of AgricultureGomal University Department of Soil & Environmental Sciences Faculty of AgricultureGomal University

Conservation tillage may improve yield of cotton in addition to improvement in soil quality if practiced for longer period. However, the practice may not be productive in short-term particularly when severe weeds are infesting the crops such as Cynodon dactylon, Conyza canadensis, Tribulus terrestris, and Cyperus rotundus, etc. Recent studies indicate that conventional tillage （CT） is more productive than zero tillage （ZT）/reduced tillage （RT）. Performance of cotton under three tillage systems, viz., ZT, RT and CT; and five herbicides, i.e., haloxyfop-R-methyl 10.8 EC （108 g a.i. ha^-1）, lactofen 24 EC （168 g a.i. ha^-1）, haloxyfop 10.8 EC ＋ lactofen 24 EC, hand weeding, and weedy check were evaluated during 2010-2011 at Gomal University, ***, Pakistan, to explore the best management option for effective weed control, enhanced yield and quality of cotton grown after wheat. The results revealed that hand weeding and Haloxyfop as post emergence alone or in combination with Lactofen reduced weed density to the minimum irrespective of the tillage systems. Excessive rainfall and cooler temperature limited cotton growth and yield in 2010. The adverse weather conditions had more adverse effect on boll weight under ZT and RT than CT. Haloxyfop ＋ lactofen produced higher seed cotton yield in RT than ZT, however, it could not exceed CT. Broad-spectrum herbicides x CT produced the highest number of bolls/plant, boll weight and seed cotton yield. Fiber quality and net returns were also the highest in broad-spectrum herbicides x CT. In conclusion, broad-spectrum herbicides under CT were more productive in wheat based cropping system on silty clay soil of ***.

关键词： tillage herbicide cotton seed cotton yield weed density net return

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Intelligent Sound-Based Early Fault Detection System for Vehicles

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Computer Systems Science & Engineering 2023年第9期46卷 3175-3190页

作者： Fawad Nasim Sohail Masood Arfan Jaffar usman Ahmad muhammad Rashid Superior University LahorePakistan Intelligent Data Visual Computing Research(IDVCR) LahorePakistan National University of Technology IslamabadPakistan

An intelligent sound-based early fault detection system has been proposed for vehicles using machine *** system is designed to detect faults in vehicles at an early stage by analyzing the sound emitted by the *** detection and correction of defects can improve the efficiency and life of the engine and other mechanical *** system uses a microphone to capture the sound emitted by the vehicle and a machine-learning algorithm to analyze the sound and detect faults.A possible fault is determined in the vehicle based on this processed *** classification is done at the first stage to differentiate between faulty and healthy *** collected noisy and normal sound samples of the car engine under normal and different abnormal conditions from multiple workshops and verified the data from *** used the time domain,frequency domain,and time-frequency domain features to detect the normal and abnormal conditions of the vehicle *** used abnormal car data to classify it into fifteen other classical vehicle *** experimented with various signal processing techniques and presented the comparison *** the detection and further problem classification,random forest showed the highest results of 97%and 92%with time-frequency features.

关键词： Sound classification signal processing random forest random tree time-frequency domain J48

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Cotton Leaf Diseases Recognition Using Deep Learning and Genetic Algorithm

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Computers, Materials & Continua 2021年第12期69卷 2917-2932页

作者： muhammad Rizwan Latif Muhamamd Attique Khan muhammad Younus Javed Haris Masood usman Tariq Yunyoung Nam Seifedine Kadry Department of Computer Science HITEC University TaxilaTaxilaPakistan Wah Engineering College University of WahWah Cantt47080Pakistan College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-KhrajSaudi Arabia Department of Computer Science and Engineering Soonchunhyang UniversityAsanKorea Faculty of Applied Computing and Technology Noroff University CollegeKristiansandNorway

Globally,Pakistan ranks 4th in cotton production,6th as an importer of raw cotton,and 3rd in cotton *** 10%of GDP and 55%of the country’s foreign exchange earnings depend on cotton *** 1.5 million people in Pakistan are engaged in the cotton value ***,several diseases such as Mildew,Leaf Spot,and Soreshine affect cotton *** diagnosis is not a good solution due to several factors such as high cost and unavailability of an ***,it is essential to develop an automated technique that can accurately detect and recognize these diseases at their early *** this study,a new technique is proposed using deep learning architecture with serially fused features and the best feature *** proposed architecture consists of the following steps:(a)a self-collected dataset of cotton diseases is prepared and labeled by an expert;(b)data augmentation is performed on the collected dataset to increase the number of images for better training at the earlier step;(c)a pre-trained deep learning model named ResNet101 is employed and trained through a transfer learning approach;(d)features are computed from the third and fourth last layers and serially combined into one matrix;(e)a genetic algorithm is applied to the combined matrix to select the best points for further *** final recognition,a Cubic SVM approach was utilized and validated on a prepared *** the newly prepared dataset,the highest achieved accuracy was 98.8%using Cubic SVM,which shows the perfection of the proposed framework..

关键词： Plants diseases data augmentation deep learning features fusion features selection

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