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| 1 | An Energy-Efficient Mobile Agent-Based Data Aggregation Scheme for Wireless Body Area Networks显示文摘Due to the advancement in wireless technology and miniaturization,Wireless Body Area Networks(WBANs)have gained enormous popularity,having various applications,especially in the healthcare sector.WBANs are intrinsically resource-constrained;therefore,they have specific design and development requirements.One such highly desirable requirement is an energy-efficient and reliable Data Aggregation(DA)mechanism for WBANs.The efficient and reliableDAmay ultimately push the network to operate without much human intervention and further extend the network lifetime.The conventional client-serverDAparadigm becomes unsuitable and inefficient for WBANs when a large amount of data is generated in the network.Similarly,in most of the healthcare applications(patient’s critical conditions),it is highly important and required to send data as soon as possible;therefore,reliable data aggregation in WBANs is of great concern.To tackle the shortcomings of the client-serverDAparadigm,theMobile Agent-Basedmechanismproved to be a more workable solution.In aMobile Agent-Based mechanism,a taskspecific mobile agent(code)traverses to the intended sources to gather data.Thesemobile agents travel on a predefined path called itinerary;however,planning a suitable and reliable itinerary for a mobile agent is also a challenging issue inWBANs.This paper presents a new Mobile Agent-Based DA scheme for WBANs,which is energy-efficient and reliable.Firstly,in the proposed scheme,the network is divided into clusters,and cluster-heads are selected.Secondly,a mobile agent is generated from the base station to collect the required data from cluster heads.In the case,if any fault occurs in the existing itinerary,an alternate itinerary is planned in real-time without compromising the network performance.In our simulation-based validation,we have found that the proposed system delivers significantly improved fault-tolerance and reliability with energy-efficiency and extended network lifetime in WBANs. | Gulzar Mehmood Muhammad Zahid Khan Muhammad Fayaz Mohammad Faisal Haseeb Ur Rahman Jeonghwan Gwak | 2022 | Computers, Materials & Continua2022，，3： | 0 |
| 2 | Impediments of Cognitive System Engineering in Machine-Human Modeling显示文摘A comprehensive understanding of human intelligence is still an ongoing process,i.e.,human and information security are not yet perfectly matched.By understanding cognitive processes,designers can design humanized cognitive information systems(CIS).The need for this research is justified because today’s business decision makers are faced with questions they cannot answer in a given amount of time without the use of cognitive information systems.The researchers aim to better strengthen cognitive information systems with more pronounced cognitive thresholds by demonstrating the resilience of cognitive resonant frequencies to reveal possible responses to improve the efficiency of human-computer interaction(HCI).Apractice-oriented research approach included research analysis and a review of existing articles to pursue a comparative research model;thereafter,amodel development paradigm was used to observe and monitor the progression of CIS during HCI.The scope of our research provides a broader perspective on how different disciplines affect HCI and how human cognitive models can be enhanced to enrich complements.We have identified a significant gap in the current literature on mental processing resulting from a wide range of theory and practice. | Fayaz Ahmad Fayaz Arun Malik Isha Batra Akber Abid Gardezi Syed Immamul Ansarullah Shafiq Ahmad Mejdal Alqahtani Muhammad Shafiq | 2023 | Computers, Materials & Continua2023，，3： | 0 |
| 3 | Improved Sequencing Heuristic DSDV Protocol Using Nomadic Mobility Model for FANETS显示文摘Most interesting area is the growing demand of flying-IoT mergers with smart cities.However,aerial vehicles,especially unmanned aerial vehicles(UAVs),have limited capabilities for maintaining node energy efficiency.In order to communicate effectively,IoT is a key element for smart cities.While improving network performance,routing protocols can be deployed in flying-IoT to improve latency,packet drop rate,packet delivery,power utilization,and average-end-to-end delay.Furthermore,in literature,proposed techniques are verymuch complex which cannot be easily implemented in realworld applications.This issue leads to the development of lightweight energyefficient routing in flying-IoT networks.This paper addresses the energy conservation problem in flying-IoT.This paper presents a novel approach for the internet of flying vehicles using DSDV routing.ISH-DSDV gives the notion of bellman-ford algorithm consisting of routing updates,information broadcasting,and stale method.DSDV shows optimal results in comparison with other contemporary routing protocols.Nomadic mobility model is utilized in the scenario of flying networks to check the performance of routing protocols. | Inam Ullah Khan Muhammad Abul Hassan Muhammad Fayaz Jeonghwan Gwak Muhammad Adnan Aziz | 2022 | Computers, Materials & Continua2022，，2： | 0 |
| 4 | Application of the Deep Convolutional Neural Network for the Classification of Auto Immune Diseases显示文摘IIF(Indirect Immune Florescence)has gained much attention recently due to its importance in medical sciences.The primary purpose of this work is to highlight a step-by-step methodology for detecting autoimmune diseases.The use of IIF for detecting autoimmune diseases is widespread in different medical areas.Nearly 80 different types of autoimmune diseases have existed in various body parts.The IIF has been used for image classification in both ways,manually and by using the Computer-Aided Detection(CAD)system.The data scientists conducted various research works using an automatic CAD system with low accuracy.The diseases in the human body can be detected with the help of Transfer Learning(TL),an advanced Convolutional Neural Network(CNN)approach.The baseline paper applied the manual classification to the MIVIA dataset of Human Epithelial cells(HEP)type II cells and the Sub Class Discriminant(SDA)analysis technique used to detect autoimmune diseases.The technique yielded an accuracy of up to 90.03%,which was not reliable for detecting autoimmune disease in the mitotic cells of the body.In the current research,the work has been performed on the MIVIA data set of HEP type II cells by using four well-known models of TL.Data augmentation and normalization have been applied to the dataset to overcome the problem of overfitting and are also used to improve the performance of TL models.These models are named Inception V3,Dens Net 121,VGG-16,and Mobile Net,and their performance can be calculated through parameters of the confusion matrix(accuracy,precision,recall,and F1 measures).The results show that the accuracy value of VGG-16 is 78.00%,Inception V3 is 92.00%,Dense Net 121 is 95.00%,and Mobile Net shows 88.00%accuracy,respectively.Therefore,DenseNet-121 shows the highest performance with suitable analysis of autoimmune diseases.The overall performance highlighted that TL is a suitable and enhanced technique compared to its counterparts.Also,the proposed technique is used to detect autoimmune diseases with a minimal margin of errors and flaws. | Fayaz Muhammad Jahangir Khan Asad Ullah Fasee Ullah Razaullah Khan Inayat Khan Mohammed ElAffendi Gauhar Ali | 2023 | Computers, Materials & Continua2023，77，10： | 0 |
| 5 | An Efficient and Robust Hand Gesture Recognition System of Sign Language Employing Finetuned Inception-V3 and Efficientnet-B0 Network显示文摘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 gestures.The 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 body.The importance of HGR has increased due to the increasing number of touchless applications and the rapid growth of the hearing-impaired population.Therefore,real-time HGR is one of the most effective interaction methods between computers and humans.Developing a user-free interface with good recognition performance should be the goal of real-time HGR systems.Nowadays,Convolutional Neural Network(CNN)shows great recognition rates for different image-level classification tasks.It 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 images.However,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 dataset.Experiments 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. | Adnan Hussain Sareer Ul Amin Muhammad Fayaz Sanghyun Seo | 2023 | Computer Systems Science & Engineering2023，46，9： | 0 |
| 6 | Characterization of Endophytic Microorganisms of Rice(Oryza sativa L.)Potentials for Blast Disease Biocontrol and Plant Growth Promoting Agents显示文摘One hundred twenty-five endophytic microorganisms were isolated from the roots,stems,and leaves of four prominent rice cultivars growing in temperate regions.Their potential to combat rice blast disease and promote plant growth was investigated.The dual culture tests highlighted the strong antagonistic activity of five fungal(ranging from 89%–70%)and five bacterial(72%–61%)endophytes.Subsequent examination focused on volatile compounds produced by selected isolates to counter the blast pathogen.Among these,the highest chitinase(13.76μg mL−1)and siderophore(56.64%),was exhibited by Aspergillus flavus,and the highest HCN production was shown by Stenotrophomonas maltophilia(36.15μM mL−1).In terms of growth promotion traits,Aspergillus flavus and Enterobacter cloacae excelled in activities viz,phosphorous solubilization,ammonia production,auxin and gibberellic acid production,and nitrogen fixation.The Identity of these endophytes was confirmed through molecular analysis as Trichoderma afroharzianum,Trichoderma harzianum,Penicillium rubens,Aspergillus flavus,Stenotrophomonas rhizophila,Stenotrophomonas maltophilia,Bacillus cereus,Enterobacter cloacae,and Bacillus licheniformis.Under greenhouse conditions,the highest disease control was shown by isolate Bacillus licheniformis and A.flavus with an inhibition of 79%,followed by S.rhizophila(77%)and T.afroharzianum(73%).The overall results of this study showed that Bacillus licheniformis and Stenotrophomonas rhizophila have great potential to be used as bio-stimulant and biocontrol agents to manage rice blast disease. | Shugufta Parveen Fayaz A.Mohiddin M.Ashraf Bhat Zahoor Ahmed Baba Fehim Jeelani M.Anwar Bhat Sajad Un Nabi Burhan Hamid Saba Bandey Farhanaz Rasool Zakir Amin Ibrahim Al-Ashkar Muhammad Adnan Ayman El Sabagh | 2023 | Phyton-International Journal of Experimental Botany2023，92，11： | 0 |
| 7 | Deep eutectic ionic liquids based on DABCO-derived quaternary ammonium salts: A promising reaction medium in gaining access to terpyridines显示文摘Owing to the directional H-bonding,coordination and π-stacking abilities,terpyridines have been widely used as supramolecular tectons in molecular architectures,skeletons in molecular devices and metallopolymers,and are gaining importance in medicinal chemistry.In this paper,we have synthesized,characterized and applied deep eutectic ionic liquids (DEILs) based on 1,4-diazabicyclo[2.2.2]octane;triethylenediamine (DABCO)-derived quatemary ammonium salts for the preparation ofterpyridines.These DEILs were synthesized through N-alkylation of DABCO with haloalkanes (1-bromopentane or 1-bromoheptane) followed by mixing and heating with methanol or polyethylene glycol as a hydrogen bond donor.The synthesized DEILs were structurally characterized by IR and NMR.The formation of deep eutectic solvent was confirmed by freezing point depression,it composition was investigated through phase diagram,and its thermal stability was determined through differential scanning calorimetry,derivative thermogravimetry and thermal gravimetric analysis studies.Further,these DEILs were investigated for their effectiveness towards synthesis of 2,2':6',2'-terpyridine,3,2':6',3'-terpyridineand 4,2':6',4'-terpyridine derivatives through Kr(o)hnke reaction.The results show that these three types ofterpyridines can be obtained in reasonable yields (80%-97%) by the one-pot reaction of 2-,3-or 4-acetylpyridine with a variety of aromatic aldehydes in the presence of DEIL as a reaction medium,sodium hydroxide as a base and ammonium acetate as a cyclizing agent.This methodology is highly efficient and cost-effective for synthesis of symmetrical as well as unsymmetrical terpyridines.Importantly,these DEILs can be reused several times without an obvious loss of activity and are non-toxic,low-volatile,biodegradable and highly thermally stable.Therefore,these DEILs as a non-conventional reaction medium for the synthesis of terpyridines provides appealing opportunities to be investigated in the domain of green synthesis. | Muhammad Faisal Azeem Haider Quret ul Aein Aamer Saeed Fayaz Ali Larik | 2019 | Frontiers of Chemical Science and Engineering2019，13，3： | 0 |
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