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Journal of Integrative Agriculture 2019年第6期18卷 1369-1378页

作者： muhammad Zahir Aziz muhammad Yaseen Tanveer Abbas muhammad Naveed adnan Mustafa Yasir Hamid Qudsia Saeed XU Ming-gang Institute of Soil and Environmental Sciences University of AgricultureFaisalabad 38040Pakistan National Engineering Laboratory for Improving Quality of Arable Land Institute of Agricultural Resources and Regional PlanningChinese Academy of Agricultural SciencesBeijing 100081P.R.China College of Environmental and Resources Science Zhejiang UniversityHangzhou 310058P.R.China College of Natural Resources and Environment Northwest Agriculture and Forestry UniversityYangling 712100P.R.China

Globally about half of the world’s population is under micronutrient malnutrition due to poor quality food *** overcome this problem,fortification and biofortification techniques are often *** is considered a better option than fortification due to the easy control of nutrient deficiencies present in daily *** field experiment was conducted to evaluate the effects of foliar application of a micronutrient mixture(MNM)consisting of zinc(Zn),iron(Fe),copper(Cu),manganese(Mn)and boron(B)on yield and flour quality of *** results show the effectiveness of foliar feeding for growth and yield parameters,in addition to the enriching of wheat grains with Zn,Cu,Fe,Mn and *** to the control without foliar feeding,foliar application on wheat crop increased tillering ability,spike length,grain yield and the contents of Zn,Cu,Mn,Fe and B by 21,47,22,22 and 25%in wheat flour,***,foliar feeding of micronutrients could be an effective approach to enrich wheat grains with essential nutrients for correcting malnutrition.

关键词： enrichment biofortification malnutrition micronutrients wheat flour

An Efficient Internet Traffic Classification System Using Deep Learning for IoT

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Computers, Materials & Continua 2022年第4期71卷 407-422页

作者： muhammad Basit Umair Zeshan Iqbal muhammad Bilal Jamel Nebhen Tarik adnan Almohamad Raja Majid Mehmood Department of Computer Science University of Engineering and TechnologyTaxila47050Pakistan Division of Computer and Electronics Systems Engineering Hankuk University of Foreign StudiesYongin-siKorea Electrical-Electronics Engineering Department Faculty of EngineeringKarabük University78050KarabükTurkey Prince Sattam bin Abdulaziz University College of Computer Engineering and SciencesAlkharj11942Saudi Arabia Information and Communication Technology Department School of Electrical and Computer EngineeringXiamen University MalaysiaSepang43900Malaysia

Internet of Things(IoT)defines a network of devices connected to the internet and sharing a massive amount of data between each other and a central *** IoT devices are connected to a network therefore prone to *** management tasks and network operations such as security,intrusion detection,Quality-of-Service provisioning,performance monitoring,resource provisioning,and traffic engineering require traffic *** to the ineffectiveness of traditional classification schemes,such as port-based and payload-based methods,researchers proposed machine learning-based traffic classification systems based on shallow neural ***,machine learning-based models incline to misclassify internet traffic due to improper feature *** this research,an efficient multilayer deep learning based classification system is presented to overcome these challenges that can classify internet *** examine the performance of the proposed technique,Moore-dataset is used for training the *** proposed scheme takes the pre-processed data and extracts the flow features using a deep neural network(DNN).In particular,the maximum entropy classifier is used to classify the internet *** experimental results show that the proposed hybrid deep learning algorithm is effective and achieved high accuracy for internet traffic classification,i.e.,99.23%.Furthermore,the proposed algorithm achieved the highest accuracy compared to the support vector machine(SVM)based classification technique and k-nearest neighbours(KNNs)based classification technique.

关键词： Deep learning internet traffic classification network traffic management QoS aware application classification

Prediction of Time Series Empowered with a Novel SREKRLS Algorithm

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Computers, Materials & Continua 2021年第5期67卷 1413-1427页

作者： Bilal Shoaib Yasir Javed muhammad adnan Khan Fahad Ahmad Rizwan Majeed muhammad Saqib Nawaz muhammad Adeel Ashraf Abid Iqbal muhammad Idrees School of Computer Science Minhaj University LahoreLahore54000Pakistan Prince Sultan University Riyadh11586Saudi Arabia Department of Computer Science Riphah International University Lahore CampusLahore54000Pakistan Department of Basic Sciences Deanship of Common First YearJouf UniversitySakakaAljouf72341Saudi Arabia Directorate of IT The Islamia University of BahawalpurBahawalpur63100Pakistan Department of Computer Science University of Management and TechnologyLahore54770Pakistan PUCIT University of the PunjabLahore54000Pakistan

For the unforced dynamical non-linear state–space model,a new Q1 and efficient square root extended kernel recursive least square estimation algorithm is developed in this *** proposed algorithm lends itself towards the parallel implementation as in the FPGA *** the help of an ortho-normal triangularization method,which relies on numerically stable givens rotation,matrix inversion causes a computational burden,is *** computation possesses many excellent numerical properties such as singularity,symmetry,skew symmetry,and triangularity is achieved by using this *** proposed method is validated for the prediction of stationary and non-stationary Mackey–Glass Time Series,along with that a component in the x-direction of the Lorenz Times Series is also predicted to illustrate its *** the learning curves regarding mean square error(MSE)are witnessed for demonstration with prediction performance of the proposed algorithm from where it’s concluded that the proposed algorithm performs better than *** new SREKRLS based design positively offers an innovative era towards non-linear systolic arrays,which is efficient in developing very-large-scale integration(VLSI)applications with non-linear input *** experiments are carried out to validate the reliability,effectiveness,and applicability of the proposed algorithm and with different noise levels compared to the Extended kernel recursive least-squares(EKRLS)algorithm.

关键词： Kernel methods square root adaptive filtering givens rotation mackey glass time series prediction recursive least squares kernel recursive least squares extended kernel recursive least squares square root extended kernel recursive least squares algorithm

A Fused Machine Learning Approach for Intrusion Detection System

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Computers, Materials & Continua 2023年第2期74卷 2607-2623页

作者： muhammad Sajid Farooq Sagheer Abbas Atta-ur-Rahman Kiran Sultan muhammad adnan Khan Amir Mosavi School of Computer Science National College of Business Administration and EconomicsLahore54000Pakistan Department of Computer Science College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam 31441Saudi Arabia Department of CIT The Applied CollegeKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Software Gachon UniversitySeongnam13120Korea John von Neumann Faculty of Informatics Obuda UniversityBudapest1034Hungary Institute of Information Engineering Automation and MathematicsSlovak University of Technology in BratislavaBratislava81107Slovakia Faculty of Civil Engineering TU-DresdenDresden01062Germany

The rapid growth in data generation and increased use of computer network devices has amplified the infrastructures of *** interconnectivity of networks has brought various complexities in maintaining network availability,consistency,and *** learning based intrusion detection systems have become essential to monitor network traffic for malicious and illicit *** intrusion detection system controls the flow of network traffic with the help of computer *** deep learning algorithms in intrusion detection systems have played a prominent role in identifying and analyzing intrusions in network *** this purpose,when the network traffic encounters known or unknown intrusions in the network,a machine-learning framework is needed to identify and/or verify network *** Intrusion detection scheme empowered with a fused machine learning technique(IDS-FMLT)is proposed to detect intrusion in a heterogeneous network that consists of different source networks and to protect the network from malicious *** proposed IDS-FMLT system model obtained 95.18%validation accuracy and a 4.82%miss rate in intrusion detection.

关键词： Fused machine learning heterogeneous network intrusion detection

Enhancing Collaborative and Geometric Multi-Kernel Learning Using Deep Neural Network

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Computers, Materials & Continua 2022年第9期72卷 5099-5116页

作者： Bareera Zafar Syed Abbas Zilqurnain Naqvi muhammad Ahsan Allah Ditta Ummul Baneen muhammad adnan Khan Department of Mechatronics and Control Engineering University of Engineering and TechnologyLahore54890Pakistan Department of Information Sciences Division of Science and TechnologyUniversity of EducationLahore54000Pakistan Riphah School of Computing&Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department Software Gachon UniversitySeongnam13120Korea

This research proposes a method called enhanced collaborative andgeometric multi-kernel learning (E-CGMKL) that can enhance the CGMKLalgorithm which deals with multi-class classification problems with non-lineardata distributions. CGMKL combines multiple kernel learning with softmaxfunction using the framework of multi empirical kernel learning (MEKL) inwhich empirical kernel mapping (EKM) provides explicit feature constructionin the high dimensional kernel space. CGMKL ensures the consistent outputof samples across kernel spaces and minimizes the within-class distance tohighlight geometric features of multiple classes. However, the kernels constructed by CGMKL do not have any explicit relationship among them andtry to construct high dimensional feature representations independently fromeach other. This could be disadvantageous for learning on datasets with complex hidden structures. To overcome this limitation, E-CGMKL constructskernel spaces from hidden layers of trained deep neural networks (DNN).Due to the nature of the DNN architecture, these kernel spaces not onlyprovide multiple feature representations but also inherit the compositionalhierarchy of the hidden layers, which might be beneficial for enhancing thepredictive performance of the CGMKL algorithm on complex data withnatural hierarchical structures, for example, image data. Furthermore, ourproposed scheme handles image data by constructing kernel spaces from aconvolutional neural network (CNN). Considering the effectiveness of CNNarchitecture on image data, these kernel spaces provide a major advantageover the CGMKL algorithm which does not exploit the CNN architecture forconstructing kernel spaces from image data. Additionally, outputs of hiddenlayers directly provide features for kernel spaces and unlike CGMKL, do notrequire an approximate MEKL framework. E-CGMKL combines the consistency and geometry preserving aspects of CGMKL with the compositionalhierarchy of kernel spaces extracted from DNN hidde

关键词： CGMKL multi-class classification deep neural network multiplekernel learning hierarchical kernel spaces

Post-traumatic stress disorder and resilience among adult burn patients in Pakistan: a cross-sectional study

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Burns & Trauma 2018年第1期6卷 49-54页

作者： Akhtar Bibi Sundas Kalim muhammad adnan Khalid Department of Psychology Mental Health Research and Treatment CenterRuhr UniversityBochumGermany National University of Modern Language IslamabadPakistan Institute for Sport Sciences and Psychology Westfalische Wilhelms-UniversitatMunsterGermany

Background: Post-traumatic stress disorder (PTSD) is one of the major psychological disorders developed after burn injuries, though this subject of burn injuries and their destructive chronic psychological impact are not considered as thoughtfully in developing countries like Pakistan. Hence, the current study investigated the relationship between PTSD symptoms and resilience among burn patients in Pakistan, exploring the variance occurrence of the two variables concerning male burn patients and female burn patients. Methods: Seventy burn patients from three burn units of Rawalpindi and Islamabad, Pakistan, during January 2015 to September 2015 were recruited. Patients with psychiatric disorder which would restrict the study procedures were excluded from the study. PTSD symptoms of burn patients were measured by PTSD CheckList-Civilian Version (PCL-C) and resilience was measured by Connor-Davidson Resilience scale (CD-RISC). Spearman’s Rank-Order correlation was used to analyze the relationship between symptoms of PTSD and resilience in burn patients, and analysis of covariance (ANCOVA) was applied to analyze the gender difference in symptoms of PTSD and level of resilience. Results: Negative correlation between PTSD and resilience among burn patients was found (r=-0.72, p<0.001). Moreover, significant gender differences were observed on PTSD symptoms and resilience between male and female burn patients when demographic variables such as age, socioeconomic status, marital status, and educational background were controlled. Female burn patients showed more PTSD symptoms (η2=0.18, p< 0.001) and less resilience (η2=0.25, p< 0.001) when compared to male burn patients. Conclusions: PTSD and resilience were negatively correlated in burn patients. Female burn patients have more PTSD symptoms and lower resilience compared to male burn patients.

关键词： Adult Burn injury Gender Post-traumatic stress disorder Resilience

A survey on trust based detection and isolation of malicious nodes in ad-hoc and sensor networks

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Frontiers of Computer Science 2015年第2期9卷 280-296页

作者： adnan AHMED Kamalrulnizam ABU BAKAR muhammad Ibrahim CHANNA Khalid HASEEB Abdul Waheed KHAN Faculty of Computing Universiti Teknologi Malaysia Johor Bahru 81310 Malaysia Department of Information Technology Quaid-e-Awam University of Engineering Science and Technology Nawabshah 67450 Pakistan

Mobile ad-hoc networks （MANETs） and wireless sensor networks （WSNs） have gained remarkable apprecia- tion and technological development over the last few years. Despite ease of deployment, tremendous applications and significant advantages, security has always been a challeng- ing issue due to the nature of environments in which nodes operate. Nodes＇ physical capture, malicious or selfish behav- ior cannot be detected by traditional security schemes. Trust and reputation based approaches have gained global recog- nition in providing additional means of security for decision making in sensor and ad-hoc networks. This paper provides an extensive literature review of trust and reputation based models both in sensor and ad-hoc networks. Based on the mechanism of trust establishment, we categorize the state- of-the-art into two groups namely node-centric trust mod- els and system-centric trust models. Based on trust evidence, initialization, computation, propagation and weight assign- ments, we evaluate the efficacy of the existing schemes. Fi- nally, we conclude our discussion with identification of some unresolved issues in pursuit of trust and reputation manage- ment.

关键词： trust reputation wireless sensor network mo-bile ad-hoc networks routing node misbehavior

An Efficient and Robust Hand Gesture Recognition System of Sign Language Employing Finetuned Inception-V3 and Efficientnet-B0 Network

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Computer Systems Science & Engineering 2023年第9期46卷 3509-3525页

作者： adnan Hussain Sareer Ul Amin muhammad Fayaz Sanghyun Seo Department of Computer Science Islamia College UniversityPeshawar25120Pakistan Department of Computer Science and Engineering Chung-Ang UniversitySeoul06974Korea Department of Computer Engineering Cyprus International UniversityLefkosa99010Rep.of North Cyprus College of Art and Technology Chung-Ang.UniversityAnseong17546Korea

Hand Gesture Recognition(HGR)is a promising research area with an extensive range of applications,such as surgery,video game techniques,and sign language translation,where sign language is a complicated structured form of hand *** fundamental building blocks of structured expressions in sign language are the arrangement of the fingers,the orientation of the hand,and the hand’s position concerning the *** importance of HGR has increased due to the increasing number of touchless applications and the rapid growth of the hearing-impaired ***,real-time HGR is one of the most effective interaction methods between computers and *** a user-free interface with good recognition performance should be the goal of real-time HGR ***,Convolutional Neural Network(CNN)shows great recognition rates for different image-level classification *** is challenging to train deep CNN networks like VGG-16,VGG-19,Inception-v3,and Efficientnet-B0 from scratch because only some significant labeled image datasets are available for static hand gesture ***,an efficient and robust hand gesture recognition system of sign language employing finetuned Inception-v3 and Efficientnet-Bo network is proposed to identify hand gestures using a comparative small HGR *** show that Inception-v3 achieved 90%accuracy and 0.93%precision,0.91%recall,and 0.90%f1-score,respectively,while EfficientNet-B0 achieved 99%accuracy and 0.98%,0.97%,0.98%,precision,recall,and f1-score respectively.

关键词： Pretrained CNN hand gesture recognition transfer learning

Factors influencing hybrid maize farmers' risk attitudes and their perceptions in Punjab Province,Pakistan

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Journal of Integrative Agriculture 2018年第6期17卷 1454-1462页

作者： Shoaib Akhtar LI Gu-cheng Raza Ullah adnan Nazir muhammad Amjed Iqbal muhammad Haseeb Raza Nadeem Iqbal muhammad Faisal College of Economics & Management Huazhong Agricultural University Institute of Agricultural and Resource Economics University of Agriculture Faisalabad The Management School Lancaster University

Hybrid maize farmers have to face diverse kinds of climate, biological, price and financial risks. Farmers＇ risk perceptions and risk attitudes are essential elements influencing farm operations and management decisions. However, this important issue has been overlooked in the contemporary studies and therefore there is a dearth of literature on this important issue. The present research is therefore, an attempt to fill this gap. This study aims to quantify hybrid maize farmers＇ perceptions of disastrous risks, their attitudes towards risk and to explore the impacts of various farm and farm household factors on farmers＇ risk attitudes and risk perceptions. The present study is conducted in four hybrid maize growing districts of Punjab Province, Pakistan, using cross-sectional data of 400 hybrid maize farmers. Risk matrix and equally likely certainty equivalent （ELCE） method are used to rank farmers＇ perceptions of four catastrophic risk sources including climate, biological, price and financial risks and to investigate farmers＇ risk aversion attitudes, respectively. Furthermore, probit regression is used to analyze the determinants affecting farmers＇ risk attitudes and risk perceptions. The results of the study showed that majority of farmers are risk averse in nature and perceive price, biological and climate to be potential sources of risks to their farm enterprise. In addition, analysis divulges that distance from farm to main market, off-farm income, location dummies for Sahiwal and Okara, age, maize farming experience, access to extension agent, significantly （either negatively or positively） influence farmers＇ risk attitudes and risk perceptions. The study delivers valuable insights for farmers, agricultural insurance sector, extension services researchers and agricultural policy makers about the local understanding of risks to hybrid maize crop in developing countries, like Pakistan, and have implications for research on farmers＇ adaptation to exposed risks.

关键词： risk perceptions risk attitude hybrid maize determinants Punjab Pakistan

Coronavirus: A “Mild” Virus Turned Deadly Infection

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Computers, Materials & Continua 2021年第5期67卷 2631-2646页

作者： Rizwan Ali Naqvi muhammad Faheem Mushtaq Natash Ali Mian muhammad adnan Khan Atta-ur-Rahman muhammad Ali Yousaf muhammad Umair Rizwan Majeed Department of Unmanned Vehicle Engineering Sejong UniversitySeoul05006Korea Department of Information Technology Khwaja Fareed University of Engineering and Information TechnologyRahim Yar Khan64200Pakistan School of Computer and Information Technology Beaconhouse National UniversityTarogilLahore53700Pakistan Riphah School of Computing&Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department of Computer Science College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityDammam31441Saudi Arabia Faculty of Information Technology University of Central PunjabLahore54782Pakistan Directorate of IT The Islamia University of BahawalpurBahawalpur63100Pakistan

Coronaviruses are a family of viruses that can be transmitted from one person to *** strains have only been mild viruses,but the current form,known as coronavirus disease 2019(COVID-19),has become a deadly *** outbreak originated in Wuhan,China,and has since spread *** symptoms of COVID-19 include a dry cough,sore throat,fever,and nasal *** drugs,pathogen–host interaction,and 2 weeks of isolation have been recommended for the treatment of the *** operating procedures,such as the use of face masks,hand sanitizer,handwashing with soap,and social distancing,are also ***,travel bans for cities,states,and countries have been put in place,along with lockdowns to control the *** restrictions,mask use,sanitizer or soap use,and avoidance of touching the face and nose have produced encouraging results,whereas the effectiveness of antibiotics has not been *** results of isolation for the recovery of infected people have also been *** bans and lockdowns have caused a slump in economies,and unemployment has risen sharply,resulting in an increase in mental health cases *** date,vaccines have been developed and are in use in certain countries,but following standard operating procedures remain *** countries following the guidelines can eradicate this *** Zealand was the rst country to eliminate the virus from their territory.

关键词： Coronavirus severe acute respiratory syndrome middle east respiratory syndrome world health organization