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| 1 | Decision Making Algorithmic Approaches Based on Parameterization of Neutrosophic Set under Hypersoft Set Environment with Fuzzy, Intuitionistic Fuzzy and Neutrosophic Settings显示文摘Hypersoft set is an extension of soft set as it further partitions each attribute into its corresponding attribute-valued set.This structure is more flexible and useful as it addresses the limitation of soft set for dealing with the scenarios having disjoint attribute-valued sets corresponding to distinct attributes.The main purpose of this study is to make the existing literature regarding neutrosophic parameterized soft set in line with the need of multi-attribute approximate function.Firstly,we conceptualize the neutrosophic parameterized hypersoft sets under the settings of fuzzy set,intuitionistic fuzzy set and neutrosophic set along with some of their elementary properties and set theoretic operations.Secondly,we propose decision-making-based algorithms with the help of these theories.Moreover,illustrative examples are presented which depict the structural validity for successful application to the problems involving vagueness and uncertainties.Lastly,the generalization of the proposed structure is discussed. | Atiqe Ur Rahman Muhammad Saeed Sultan S.Alodhaibi Hamiden Abd El-Wahed Khalifa | 2021 | Computer Modeling in Engineering & Sciences2021，，8： | 2 |
| 2 | Early selection of bread wheat genotypes using morphological and photosynthetic attributes conferring drought tolerance显示文摘Genetic diversity is the base of any genetic improvement breeding program aimed at stress breeding.The variability among breeding materials is of primary importance in the achievements of a good crop production.Herein,105 wheat genotypes were screened against drought stress using factorial completely randomized design at seedling stage to determine the genetic diversity and traits association conferring drought tolerance.Analysis of variances revealed that all the studied parameters differed significantly among all genotypes,indicating the significance genetic variability existed among all genotypes for studied indices.The 10 best performance genotypes G1,G6,G11,G16,G21,G26,G39,G44,G51,and G61 were screened as drought tolerant,while five lowest performance genotypes G3,G77,G91,G98,and G105 were screened as drought susceptible.Root length,chlorophyll a,chlorophyll b,and carotenoid contents were significantly correlated among themselves which exhibited the importance of these indices for rainfed areas in future wheat breeding scheme.Shoot length exhibited non-significant and negative association with other studied traits,and its selection seems not to be a promising criteria for this germplasm for drought stress.Best performance genotypes under drought stress conditions will be useful in future wheat breeding program and early selection will be effective for developing high yielding and drought tolerant wheat varieties. | Hafiz Ghulam Muhu-Din Ahmed Abdus Salam khan LI Ming-ju Sultan Habibullah Khan Muhammad Kashif | 2019 | Journal of Integrative Agriculture2019，18，11： | 2 |
| 3 | Use of Ethnomedicinal Plants by the People Living around Indus River显示文摘 | Sakina Mussarat Nasser M. AbdEl-Salam Akash Tariq Sultan Mehmood Wazir Riaz Ullah Muhammad Adnan John R. S. Tabuti | 2014 | Evidence-Based Complementary and Alternative Medicine2014，，： | 1 |
| 4 | Hyposper-matogenesis and spermatozoa maturation arrest in rats in-duced by mobile phone radiation 显示文摘 | Sultan A M Muhammad A Shahzad R | 2011 | JCPSP-J Coll Phy2011，21，5： | 1 |
| 5 | Stable Huh-7 cell lines expressing non-structural proteins of genotype 1a of hepatitis C virus显示文摘 | Imran Shahid Sana Gull Bushra Ijaz Waqar Ahmad Muhammad Ansar Sultan Asad Humera Kausar Muhammad Tahir Sarwar Muhammad Kazim Khan Sajida Hassan | 2013 | Journal of Virological Methods2013，，1： | 1 |
| 6 | COVID-19 and comorbidities of hepatic diseases in a global perspective显示文摘The worldwide outbreak of coronavirus disease 2019(COVID-19) has challenged the priorities of healthcare system in terms of different clinical management and infection transmission, particularly those related to hepatic-disease comorbidities. Epidemiological data evidenced that COVID-19 patients with altered liver function because of hepatitis infection and cholestasis have an adverse prognosis and experience worse health outcomes. COVID-19-associated liver injury is correlated with various liver diseases following a severe acute respiratory syndrome-coronavirus type 2(SARS-CoV-2) infection that can progress during the treatment of COVID-19 patients with or without pre-existing liver disease. SARS-CoV-2 can induce liver injury in a number of ways including direct cytopathic effect of the virus on cholangiocytes/hepatocytes, immune-mediated damage, hypoxia, and sepsis. Indeed, immediate cytopathogenic effects of SARSCoV-2 via its potential target, the angiotensin-converting enzyme-2 receptor, which is highly expressed in hepatocytes and cholangiocytes, renders the liver as an extra-respiratory organ with increased susceptibility to pathological outcomes. But, underlying COVID-19-linked liver disease pathogenesis with abnormal liver function tests(LFTs) is incompletely understood. Hence, we collated COVID-19-associated liver injuries with increased LFTs at the nexus of pre-existing liver diseases and COVID-19, and defining a plausible pathophysiological triad of COVID-19, hepatocellular damage, and liver disease. This review summarizes recent findings of the exacerbating role of COVID-19 in pre-existing liver disease and vice versa as well as international guidelines of clinical care, management, and treatment recommendations for COVID-19 patients with liver disease. | Aqsa Ahmad Syeda Momna Ishtiaq Junaid Ali Khan Rizwan Aslam Sultan Ali Muhammad Imran Arshad | 2021 | World Journal of Gastroenterology2021，27，13： | 1 |
| 7 | Nutritional and medicinal aspects of coriander ( Coriandrum sativum L.): A review显示文摘 | Muhammad Nadeem Faqir Muhammad Anjum Muhammad Issa Khan Saima Tehseen Ahmed El-Ghorab Javed Iqbal Sultan | 2013 | British Food Journal2013，，5： | 1 |
| 8 | Numerical Simulation and Experimental Verification of CMOD in SENT Specimen: Application on FCGR of Welded Tool Steel显示文摘Single-edged notched tension (SENT) specimen is used to study the fatigue crack growth rate (FCGR) behavior of AISI 50100 steel using MTS 810. Calibration tests are run to get plots of crack mouth opening displacement (CMOD) vs. load and CMOD vs. crack length-to-width ratio with the known crack lengths. Numerical simulation is also done to try to establish a relation between crack length and CMOD. FCGR of welded and un-welded specimens are plotted against stress intensity factor range to show the effect of welding on fatigue crack growth rate of AISI 50100 steel. The experimentally obtained CMOD values are compared with values obtained by numerical simulation using ABAQUS/StandardTM software package. Results show that numerical values are in good agreement with experimental data for small crack lengths and lower values of applied load. | Amir SULTAN Riffat Asim PASHA Mifrah ALI Muhammad Zubair KHAN Muhammad Afzal KHAN Naeem Ullah DAR Masood SHAH | 2013 | Acta Metallurgica Sinica(English Letters)2013，26，1： | 1 |
| 9 | First report on molecular characterization of Leishmania species from cutaneous leishmaniasis patients in southern Khyber Pakhtunkhwa province of Pakistan显示文摘Objective: To report presence of Leishmania major in Khyber Pakhtunkhwa of Pakistan, where cutaneous leishmaniasis(CL) is endemic and was thought to be caused by Leishmania tropica only. Methods: Biopsy samples from 432 CL suspected patients were collected from 3 southern districts of Khyber Pakhtunkhwa during years 2011–2016. Microscopy on Giemsa stained slides were done followed by amplification of the ribosomal internal transcribed spacer 1 gene. Results: Leishmania amastigotes were detected by microscopy in 308 of 432 samples(71.3%) while 374 out of 432 samples(86.6%) were positive by ribosomal internal transcribed spacer 1 PCR. Subsequent restriction fragment length polymorphism confirmed Leishmania tropica in 351 and Leishmania major in 6 biopsy samples. Conclusions: This study is the first molecular characterization of Leishmania species in southern Khyber Pakhtunkhwa. It confirmed the previous assumptions that anthroponotic CL is the major CL form present in Khyber Pakhtunkhwa province. Furthermore, this is the first report of Leishmania major from a classical anthroponotic CL endemic focus identified in rural areas of Kohat district in southern Khyber Pakhtunkhwa. | Mubbashir Hussain Shahzad Munir Sultan Ayaz Bahar Ullah Khattak Taj Ali Khan Niaz Muhammad Muhammad Anees Hazir Rahman Muhammad Qasim Muhammad Ameen Jamal Irfan Ahmed Kashif Rahim Humaira Mazhar Noha Watanay Mohamed Kasbari | 2017 | Asian Pacific Journal of Tropical Medicine2017，10，7： | 1 |
| 10 | Combining Phytate/Ca^(2+) Fractionation with Trichloroacetic Acid/Acetone Precipitation Improved Separation of Low-Abundant Proteins of Wheat (Triticum aestivum L.) Leaf for Proteomic Analysis显示文摘Proteomic assessment of low-abundance leaf proteins is hindered by the large quantity of ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) present within plant leaf tissues. In the present study, total proteins were extracted from wheat (Triticum aestivum L.) leaves by a conventional trichloroacetic acid (TCA)/acetone method and a protocol first developed in this work. Phytate/Ca2+ fractionation and TCA/acetone precipitation were combined to design an improved TCA/acetone method. The extracted proteins were analysed by two-dimensional gel electrophoresis (2-DE). The resulting 2-DE images were compared to reveal major differences. The results showed that large quantities of Rubisco were deleted from wheat leaf proteins prepared by the improved method. As many as (758±4) protein spots were detected from 2-DE images of protein extracts obtained by the improved method, 130 more than those detected by the TCA/acetone method. Further analysis indicated that more protein spots could be detected at regions of pI 4.00-4.99 and 6.50-7.00 in the improved method-based 2-DE images. Our findings indicated that the improved method is an efficient protein preparation protocol for separating low-abundance proteins in wheat leaf tissues by 2-DE analysis. The proposed protocol is simple, fast, inexpensive and also applicable to protein preparations of other plants. | Muhammad A R F Sultan LIU Hui CHENG Yu-Feng ZHANG Pei-pei ZHAO Hui-xian | 2013 | Journal of Integrative Agriculture2013，12，7： | 1 |
| 11 | A Fused Machine Learning Approach for Intrusion Detection System显示文摘The rapid growth in data generation and increased use of computer network devices has amplified the infrastructures of internet.The interconnectivity of networks has brought various complexities in maintaining network availability,consistency,and discretion.Machine learning based intrusion detection systems have become essential to monitor network traffic for malicious and illicit activities.An intrusion detection system controls the flow of network traffic with the help of computer systems.Various deep learning algorithms in intrusion detection systems have played a prominent role in identifying and analyzing intrusions in network traffic.For 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.The 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 attacks.The proposed IDS-FMLT system model obtained 95.18%validation accuracy and a 4.82%miss rate in intrusion detection. | Muhammad Sajid Farooq Sagheer Abbas Atta-ur-Rahman Kiran Sultan Muhammad Adnan Khan Amir Mosavi | 2023 | Computers, Materials & Continua2023，，2： | 0 |
| 12 | An Optimization Approach for Convolutional Neural Network Using Non-Dominated Sorted Genetic Algorithm-Ⅱ显示文摘In computer vision,convolutional neural networks have a wide range of uses.Images representmost of today’s data,so it’s important to know how to handle these large amounts of data efficiently.Convolutional neural networks have been shown to solve image processing problems effectively.However,when designing the network structure for a particular problem,you need to adjust the hyperparameters for higher accuracy.This technique is time consuming and requires a lot of work and domain knowledge.Designing a convolutional neural network architecture is a classic NP-hard optimization challenge.On the other hand,different datasets require different combinations of models or hyperparameters,which can be time consuming and inconvenient.Various approaches have been proposed to overcome this problem,such as grid search limited to low-dimensional space and queuing by random selection.To address this issue,we propose an evolutionary algorithm-based approach that dynamically enhances the structure of Convolution Neural Networks(CNNs)using optimized hyperparameters.This study proposes a method using Non-dominated sorted genetic algorithms(NSGA)to improve the hyperparameters of the CNN model.In addition,different types and parameter ranges of existing genetic algorithms are used.Acomparative study was conducted with various state-of-the-art methodologies and algorithms.Experiments have shown that our proposed approach is superior to previous methods in terms of classification accuracy,and the results are published in modern computing literature. | Afia Zafar Muhammad Aamir Nazri Mohd Nawi Ali Arshad Saman Riaz Abdulrahman Alruban Ashit Kumar Dutta Badr Almutairi Sultan Almotairi | 2023 | Computers, Materials & Continua2023，，3： | 0 |
| 13 | Automated File Labeling for Heterogeneous Files Organization Using Machine Learning显示文摘File labeling techniques have a long history in analyzing the anthological trends in computational linguistics.The situation becomes worse in the case of files downloaded into systems from the Internet.Currently,most users either have to change file names manually or leave a meaningless name of the files,which increases the time to search required files and results in redundancy and duplications of user files.Currently,no significant work is done on automated file labeling during the organization of heterogeneous user files.A few attempts have been made in topic modeling.However,one major drawback of current topic modeling approaches is better results.They rely on specific language types and domain similarity of the data.In this research,machine learning approaches have been employed to analyze and extract the information from heterogeneous corpus.A different file labeling technique has also been used to get the meaningful and`cohesive topic of the files.The results show that the proposed methodology can generate relevant and context-sensitive names for heterogeneous data files and provide additional insight into automated file labeling in operating systems. | Sagheer Abbas Syed Ali Raza MAKhan Muhammad Adnan Khan Atta-ur-Rahman Kiran Sultan Amir Mosavi | 2023 | Computers, Materials & Continua2023，，2： | 0 |
| 14 | Framework for Effective Utilization of Distributed Scrum in Software Projects显示文摘There is an emerging interest in using agile methodologies in Global Software Development(GSD)to get the mutual benefits of both methods.Scrum is currently admired by many development teams as an agile most known meth-odology and considered adequate for collocated teams.At the same time,stake-holders in GSD are dispersed by geographical,temporal,and socio-cultural distances.Due to the controversial nature of Scrum and GSD,many significant challenges arise that might restrict the use of Scrum in GSD.We conducted a Sys-tematic Literature Review(SLR)by following Kitchenham guidelines to identify the challenges that limit the use of Scrum in GSD and to explore the mitigation strategies adopted by practitioners to resolve the challenges.To validate our reviewfindings,we conducted an industrial survey of 305 practitioners.The results of our study are consolidated into a research framework.The framework represents current best practices and recommendations to mitigate the identified distributed scrum challenges and is validated byfive experts of distributed Scrum.Results of the expert review were found supportive,reflecting that the framework will help the stakeholders deliver sustainable products by effectively mitigating the identified challenges. | Basit Shahzad Wardah Naeem Awan Fazal-e-Amin Ahsanullah Abro Muhammad Shoaib Sultan Alyahya | 2023 | Computer Systems Science & Engineering2023，44，1： | 0 |
| 15 | An Efficient Technique to Prevent Data Misuse with Matrix Cipher Encryption Algorithms显示文摘Many symmetric and asymmetric encryption algorithms have been developed in cloud computing to transmit data in a secure form.Cloud cryptography is a data encryption mechanism that consists of different steps and prevents the attacker from misusing the data.This paper has developed an efficient algorithm to protect the data from invaders and secure the data from misuse.If this algorithm is applied to the cloud network,the attacker will not be able to access the data.To encrypt the data,the values of the bytes have been obtained by converting the plain text to ASCII.A key has been generated using the Non-Deterministic Bit Generator(NRBG)mechanism,and the key is XNORed with plain text bits,and then Bit toggling has been implemented.After that,an efficient matrix cipher encryption algorithm has been developed,and this algorithm has been applied to this text.The capability of this algorithm is that with its help,a key has been obtained from the plain text,and only by using this key can the data be decrypted in the first steps.A plain text key will never be used for another plain text.The data has been secured by implementing different mechanisms in both stages,and after that,a ciphertext has been obtained.At the end of the article,the latest technique will be compared with different techniques.There will be a discussion on how the present technique is better than all the other techniques;then,the conclusion will be drawn based on comparative analysis. | Muhammad Nadeem Ali Arshad Saman Riaz Syeda Wajiha Zahra Ashit Kumar Dutta Moteeb Al Moteri Sultan Almotairi | 2023 | Computers, Materials & Continua2023，，2： | 0 |
| 16 | Impacts of fuel feeding methods on the thermal and emission performance of modern coal burning stoves显示文摘The extensive use of traditional cooking and heating stoves to meet domestic requirements creates a serious problem of indoor and outdoor air pollution.This study reports the impacts of two fuel feeding methods-front-loading and top-loading on the thermal and emissions performance of a modern coal-fired water-heating and cooking stove using a contextual test sequence that replicates typical patterns of domestic use.Known as a low-pressure boiler,when this stove was fueled with raw coal,the findings indicate that front-loading the fuel,which devolatilizes the new fuel gradually,produced consistently higher space heating efficiency and lower emission factors than top-loading the same stove,which devolatilizes new fuel all at once.Comparing the performance at both high and low power gave the similar results:front-loading with raw coal produced consistently better results than top-loading.The average water heating efficiency when front-loading was(58.6±2.3)%and(53.4±1.8)%for top-loading.Over the sixteen-hour test sequence,front-loading produced 22%lower emissions of PM2.5(3.9±0.6)mg/MJNET than top-loading(4.7±0.9)mg/MJNET.The same pattern was observed for carbon monoxide and the CO/CO2 ratio.CO was reduced from(5.0±0.4)g/MJNET to(4.1±0.5)g/MJNET.The combustion efficiency(CO/CO2 ratio)improved from(8.2±0.8)%to(6.6±0.6)%.Briquetted semi-coked coal briquettes are promoted as a raw coal substitute,and the tests were replicated using this fuel.Again,the same pattern of improved performance was observed.Front loading produced 3.5%higher heating efficiency,10%lower CO and a 0.9%lower CO/CO2 ratio.It is concluded that,compared with top loading,the manufacturers recommended front-loading refueling behavior delivered better thermal,emissions and combustion performance under all test conditions with those two fuels. | Riaz Ahmad Yuguang Zhou Nan Zhao Crispin Pemberton-Pigott Harold John Annegarn Muhammad Sultan Renjie Dong Xinxin Ju | 2019 | International Journal of Agricultural and Biological Engineering2019，12，3： | 0 |
| 17 | Genome-wide association analysis for stripe rust resistance in spring wheat(Triticum aestivum L.) germplasm显示文摘Stripe rust is a continuous threat to wheat crop all over the world.It causes considerable yield losses in wheat crop every year.Continuous deployment of adult plant resistance(APR)genes in newly developing wheat cultivars is the most judicious strategy to combat this disease.Herein,we dissected the genetics underpinning stripe rust resistance in Pakistani wheat germplasm.An association panel of 94 spring wheat genotypes was phenotyped for two years to score the infestation of stripe rust on each accession and was scanned with 203 polymorphic SSRs.Based on D’measure,linkage disequilibrium(LD)exhibited between loci distant up to 45 c M.Marker-trait associations(MTAs)were determined using mixed linear model(MLM).Total 31 quantitative trait loci(QTLs)were observed on all 21 wheat chromosomes.Twelve QTLs were newly discovered as well as 19 QTLs and 35 previously reported Yr genes were validated in Pakistani wheat germplasm.The major QTLs were QYr.uaf.2 AL and QYr.uaf.3 BS(PVE,11.9%).Dissection of genes from the newly observed QTLs can provide new APR genes to improve genetic resources for APR resistance in wheat crop. | Sher MUHAMMAD Muhammad SAJJAD Sultan Habibullah KHAN Muhammad SHAHID Muhammad ZUBAIR Faisal Saeed AWAN Azeem iqbal KHAN Muhammad Salman MUBARAK Ayesha TAHIR Muhammad UMER Rumana KEYANI Muhammad InamAFZAL Irfan MANZOOR Javed Iqbal WATTOO Aziz-ur REHMAN | 2020 | Journal of Integrative Agriculture2020，19，8： | 0 |
| 18 | Investigation of energy-efficient solid desiccant system for wheat drying显示文摘The study investigates the applicability of solid desiccant system for drying of freshly harvested wheat grains in order to reduce the moisture content to an optimum level.Fast and low-temperature drying systems are required by today’s drying industries in order to provide economical and safe drying.Therefore,comparison of desiccant drying has been made with the conventional method in terms of drying kinetics,allowable time for safe storage,the total time for drying cycle,and overall energy consumption.It has been found that the air conditions of proposed desiccant drying system provides a high drying rate and longer allowable storage time for safe drying.As the desiccants possess water adsorbing ability by means of vapor pressure deficit,therefore,the desiccant system successfully provides low-temperature drying which ensures the quality of wheat grains.Overall energy consumption is estimated for both conventional hot air drying and desiccant drying system.It has been found that the desiccant system requires less energy as drying is accomplished at minimum level of air flow and within allowable storage time.In addition,the overall performance index of the desiccant system is higher at all temperatures.The study is useful for developing a low-cost and sustainable drying technology for various agricultural products. | Shazia Hanif Muhammad Sultan Takahiko Miyazaki Shigeru Koyama | 2019 | International Journal of Agricultural and Biological Engineering2019，12，1： | 0 |
| 19 | Augmenting IoT Intrusion Detection System Performance Using Deep Neural Network显示文摘Due to their low power consumption and limited computing power,Internet of Things(IoT)devices are difficult to secure.Moreover,the rapid growth of IoT devices in homes increases the risk of cyber-attacks.Intrusion detection systems(IDS)are commonly employed to prevent cyberattacks.These systems detect incoming attacks and instantly notify users to allow for the implementation of appropriate countermeasures.Attempts have been made in the past to detect new attacks using machine learning and deep learning techniques,however,these efforts have been unsuccessful.In this paper,we propose two deep learning models to automatically detect various types of intrusion attacks in IoT networks.Specifically,we experimentally evaluate the use of two Convolutional Neural Networks(CNN)to detect nine distinct types of attacks listed in the NF-UNSW-NB15-v2 dataset.To accomplish this goal,the network stream data were initially converted to twodimensional images,which were then used to train the neural network models.We also propose two baseline models to demonstrate the performance of the proposed models.Generally,both models achieve high accuracy in detecting the majority of these nine attacks. | Nasir Sayed Muhammad Shoaib Waqas Ahmed Sultan Noman Qasem Abdullah M.Albarrak Faisal Saeed | 2023 | Computers, Materials & Continua2023，，1： | 0 |
| 20 | Forecast the Influenza Pandemic Using Machine Learning显示文摘Forecasting future outbreaks can help in minimizing their spread.Influenza is a disease primarily found in animals but transferred to humans through pigs.In 1918,influenza became a pandemic and spread rapidly all over the world becoming the cause behind killing one-third of the human population and killing one-fourth of the pig population.Afterwards,that influenza became a pandemic several times on a local and global levels.In 2009,influenza‘A’subtype H1N1 again took many human lives.The disease spread like in a pandemic quickly.This paper proposes a forecasting modeling system for the influenza pandemic using a feed-forward propagation neural network(MSDII-FFNN).This model helps us predict the outbreak,and determines which type of influenza becomes a pandemic,as well as which geographical area is infected.Data collection for the model is done by using IoT devices.This model is divided into 2 phases:The training phase and the validation phase,both being connected through the cloud.In the training phase,the model is trained using FFNN and is updated on the cloud.In the validation phase,whenever the input is submitted through the IoT devices,the system model is updated through the cloud and predicts the pandemic alert.In our dataset,the data is divided into an 85%training ratio and a 15%validation ratio.By applying the proposed model to our dataset,the predicted output precision is 90%. | Muhammad Adnan Khan Wajhe Ul Husnain Abidi Mohammed A.Al Ghamdi Sultan H.Almotiri Shazia Saqib Tahir Alyas Khalid Masood Khan Nasir Mahmood | 2021 | Computers, Materials & Continua2021，，1： | 0 |
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