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Production and characterization of organic manure from liquorice residues

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Information Processing in Agriculture 2020年第2期7卷 233-241页

作者： Raghad S.Mouhamad zainab J.Mohammed Ahmad A.Abdulhadi Mazhar Abbas Munawar iqbal Arif Nazir Soil and Water Resources Center Ministry of Sciences&TechnologyBaghdadIraq Section of Biochemistry Department of Basic SciencesCollege of Veterinary and Animal Sciences(CVAS)JhangUniversity of Veterinary and Animal Sciences(UVAS)LahorePakistan Department of Chemistry The University of LahoreLahorePakistan

In present investigation,organic manure was produced and characterized from liquorice residues using activated Effective Microoganism(AEM).The liquorice waste residues were fermented for the period of 6 months in the presence of activated AEM at the rate of 2.5%and 5%of total fermented ***(62.5 g)was used per 10 kg of liquorice and moister was maintained at 55–60%during *** AEM manure production efficiency was evaluated on the basis of pH,C/N ratio,electrical conductivity(EC)and mineral *** final pH of organic manure was 6.2,C/N ratio reduced from 13.5 to 6.5,EC and the mineral contents were increased of composted *** revealed that the AEM are effective to produce organic manure from agricultural waste matter since the organic manure physico-chemical properties were within the permissible limit and AEM could be used for the production of compost ***,this technique can also be extended to other agricultural waste materials for the production of organic manure.

关键词： Liquorice Organic manure Fermentation Physico-chemical

Indirect plant defense against insect herbivores： a review

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Insect Science 2018年第1期25卷 2-23页

作者： zainab Aljbory Ming-Shun Chen Department of Entomology Kansas State University Manhattan Kansas USA Hard Winter Wheat Genetics Research Unit USDA-ARS Kansas State University Manhattan Kansas USA

Plants respond to herbivore attack by launching 2 types of defenses： direct defense and indirect defense. Direct defense includes all plant traits that increase the resistance of host plants to insect herbivores by affecting the physiology and/or be- havior of the attackers. Indirect defense includes all traits that by themselves do not have significant direct impact on the attacking herbivores, but can attract natural en- emies of the herbivores and thus reduce plant loss. When plants recognize herbivore- associated elicitors, they produce and release a blend of volatiles that can attract preda- tors, parasites, and other natural enemies. Known herbivore-associated elicitors include fatty acid-amino acid conjugates, sulfur-containing fatty acids, fragments of cell walls, peptides, esters, and enzymes. Identified plant volatiles include terpenes, nitrogenous compounds, and indoles. In addition, constitive traits including extrafloral nectars, food bodies, and domatia can be further induced to higher levels and attract natural enemies as well as provide food and shelter to carnivores. A better understanding of indirect plant defense at global and componential levels via advanced high throughput technolo- gies may lead to utilization of indirect defense in suppression of herbivore damage to plants.

关键词： elicitor indirect plant defense natural enemies volatile

Custom emoji based emotion recognition system for dynamic business webpages

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International Journal of Intelligent Computing and Cybernetics 2022年第4期15卷 497-509页

作者： Fatima Isiaka zainab Adamu Computer Science Sheffield Hallam UniversitySheffieldUK Ahmadu Bello University ZariaNigeria

Purpose-One of the contributions of artificial intelligent(AI)in modern technology is emotion recognition which is mostly based on facial expression and modification of its inference *** facial recognition scheme is mostly built to understand user expression in an online business webpage on a marketing site but has limited abilities to recognise elusive *** basic emotions are expressed when interrelating and socialising with other personnel *** most times,studying how to understand user expression is often a most tedious task,especially the subtle *** emotion recognition system can be used to optimise and reduce complexity in understanding users’subconscious thoughts and reasoning through their pupil ***/methodology/approach-This paper demonstrates the use of personal computer(PC)webcam to read in eye movement data that includes pupil changes as part of distinct user attributes.A custom eye movement algorithm(CEMA)is used to capture users’activity and record the data which is served as an input model to an inference engine(artificial neural network(ANN))that helps to predict user emotional response conveyed as emoticons on the ***-The result from the error in performance shows that ANN is most adaptable to user behaviour prediction and can be used for the system’s modification *** limitations/implications-One of the drawbacks of the analytical tool is its inability in some cases to set some of the emoticons within the boundaries of the visual field,this is a limitation to be tackled within subsequent runs with standard ***/value-The originality of the proposed model is its ability to predict basic user emotional response based on changes in pupil size between average recorded baseline boundaries and convey the emoticons chronologically with the gaze points.

关键词： AI Static business webpages Artificial neural network Emotion recognition system Pupil changes User expression Eye movement behaviour

Lacunary Generating Functions of Hybrid Type Polynomials in Viewpoint of Symbolic Approach

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Computer Modeling in Engineering & Sciences 2022年第2期130卷 903-921页

作者： Nusrat Raza Umme zainab Serkan Araci Mathematics Section Women’s CollegeAligarh Muslim UniversityAligarh202002India Department of Mathematics AligarhMuslim UniversityAligarh202002India Department of Economics Faculty of EconomicsAdministrative of Social SciencesHasan Kalyoncu UniversityGaziantepTR-27410Turkey

In this paper,we introduce mon-symbolic method to obtain the generating functions of the hybrid class of Hermite-associated Laguerre and its associated *** obtain the series definitions of these hybrid special ***,we derive the double lacunary generating functions of the Hermite-Laguerre polynomials and the Hermite-Laguerre-Wright ***,we find multiplicative and derivative operators for the Hermite-Laguerre-Wright polynomials which helps to find the symbolic differential equation of the Hermite-Laguerre-Wright *** concluding remarks are also given.

关键词： Hermite-laguerre polynomials laguerre-wright polynomials hermite-laguerre-wright polynomials hermite-mittag-leffler functions

Determinants of adoption of multiple sustainable agricultural practices among smallholder farmers in Nigeria

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International Soil and Water Conservation Research 2021年第2期9卷 241-248页

作者： zainab Oyetunde-Usman Kehinde Oluseyi Olagunju Oyinlola Rafiat Ogunpaimo Natural Resources Institute University of GreenwichChatham Maritime ME44TBUK Economics Research Branch Agri-Food and Biosciences Institute18a Newforge Lane BT95PXUK Rural Economy&Development Programme TeagascMellows CampusAthenryCo.GalwayH65 R718Ireland

Despite the important roles of Sustainable Agricultural Practices(SAPs)in improving productivity,welfare,and food security of farming households,the adoption rates of SAPs have been perceived to be generally low,especially in developing *** cross-sectional data collected from the 2015 Nigeria General Household Survey,this study examines the factors influencing the adoption of multiple SAPs,while also considering the drivers of the intensity of adoption of these *** methods of data analysis are based on the Multivariate probit and the Ordered probit *** SAPs considered include improved seeds,inorganic fertilizer,mixed-cropping techniques,and organic *** empirical results show that farmers’adoption of different SAPs and their intensity of use depend significantly on factors such as the age of household head,gender,education,household size,access to extension services,and household wealth *** findings imply that policymakers and agricultural development agencies should seek to maintain or increase household asset bases,and encourage both formal and informal training programme among farming households to facilitate the adoption of SAPs.

关键词： Sustainable land management Adoption intensity Multivariate probit Ordered probit Developing countries

Improving Association Rules Accuracy in Noisy Domains Using Instance Reduction Techniques

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Computers, Materials & Continua 2022年第8期72卷 3719-3749页

作者： Mousa Al-Akhras zainab Darwish Samer Atawneh Mohamed Habib College of Computing and Informatics Saudi Electronic UniversityRiyadh11673Saudi Arabia King Abdullah II School for Information Technology The University of JordanAmman11942Jordan Faculty of Engineering Port Said UniversityPort Said42523Egypt

Association rules’learning is a machine learning method used in finding underlying associations in large *** intentionally or unintentionally present,noise in training instances causes overfitting while building the classifier and negatively impacts classification *** paper uses instance reduction techniques for the datasets before mining the association rules and building the *** reduction techniques were originally developed to reduce memory requirements in instance-based *** paper utilizes them to remove noise from the dataset before training the association rules *** experiments were conducted to assess the accuracy of association rules with different instance reduction techniques,namely:DecrementalReduction Optimization Procedure(DROP)3,DROP5,ALL K-Nearest Neighbors(ALLKNN),Edited Nearest Neighbor(ENN),and Repeated Edited Nearest Neighbor(RENN)in different noise *** show that instance reduction techniques substantially improved the average classification accuracy on three different noise levels:0%,5%,and 10%.The RENN algorithm achieved the highest levels of accuracy with a significant improvement on seven out of eight used datasets from the University of California Irvine(UCI)machine learning *** improvements were more apparent in the 5%and the 10%noise *** RENN was applied,the average classification accuracy for the eight datasets in the zero-noise test enhanced from 70.47%to 76.65%compared to the original *** average accuracy was improved from 66.08%to 77.47%for the 5%-noise case and from 59.89%to 77.59%in the 10%-noise *** confidence was also reported in building the association rules when RENN was *** above results indicate that RENN is a good solution in removing noise and avoiding overfitting during the construction of the association rules classifier,especially in noisy domains.

关键词： Association rules classification instance reduction techniques classification overfitting noise data cleansing

Bioremediation and detoxification of real refinery oily sludge using mixed bacterial cells

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Petroleum Research 2021年第3期6卷 303-308页

作者： Rusul M.Khazaal zainab Z.Ismail Minitry of 0il/Petroleum Research and Development Center Baghdadlraq Department of Environmental Engineering University of BaghdadBaghdadIraq

Anaerobic biotreatment of real field petroleum refinery oily sludge(PROS)was investigated under using four different organic loads(OLs)in the order ofOL4>OL3>OL2>OL1,in bench-scale *** bioremediation of raw PROS was carried out using mixed culture biocatalyst without chemicals addition or any type of *** results revealed a potential performance of the used biocatalyst dominated by Pseudomonas aeruginosa(class:Gammaproteo)and Staphylococcus spp.(class:Bacilli)achieving significant removal of chemical oxygen demand(COD)and total petroleum hydrocarbons(TPH).The highest organic removal rate was recorded in OL4 followed by OL3,0L2,OL1,respectively indicating a positive relationship between the percentage removal of organics and their *** removal efficiencies of 96.7%and 90%were observed for COD and TPH,respectively in OL4 within 14 days *** of polycyclic aromatic hydrocarbons(PAHs)demonstrated that acenaph-thylene and phenanthrene exhibited the maximum removal efficiency(almost complete)among the 8-priority PAHs tested in this ***,the overall degradation of PAHs in the oily sludge was 83.3%.

关键词： Petroleum oily sludge Anaerobic biodegradation Organic loading Total petroleum hydrocarbons Polycyclic aromatic hydrocarbons

Automatic Detection of COVID-19 Using Chest X-Ray Images and Modified ResNet18-Based Convolution Neural Networks

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Computers, Materials & Continua 2021年第2期66卷 1301-1313页

作者： Ruaa A.Al-Falluji zainab Dalaf Katheeth Bashar Alathari University of Babylon Babylon51002Iraq Kufa University Kufa54003Iraq

The latest studies with radiological imaging techniques indicate that X-ray images provide valuable details on the Coronavirus disease 2019(COVID-19).The usage of sophisticated artificial intelligence technology(AI)and the radiological images can help in diagnosing the disease reliably and addressing the problem of the shortage of trained doctors in remote *** this research,the automated diagnosis of Coronavirus disease was performed using a dataset of X-ray images of patients with severe bacterial pneumonia,reported COVID-19 disease,and normal *** goal of the study is to analyze the achievements for medical image recognition of state-of-the-art neural networking *** Learning technique has been implemented in this *** learning is an ambitious task,but it results in impressive outcomes for identifying distinct patterns in tiny datasets of medical *** findings indicate that deep learning with X-ray imagery could retrieve important biomarkers relevant for COVID-19 disease *** all diagnostic measures show failure levels that pose questions,the scientific profession should determine the probability of integration of X-rays with the clinical treatment,utilizing the *** proposed model achieved 96.73%accuracy outperforming the ResNet50 and traditional Resnet18 *** on our findings,the proposed system can help the specialist doctors in making verdicts for COVID-19 detection.

关键词： COVID-19 artificial intelligence convolutional neural network chest x-ray images Resnet18 model

Intrusion Detection System Through Deep Learning in Routing MANET Networks

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Intelligent Automation & Soft Computing 2023年第7期37卷 269-281页

作者： zainab Ali Abbood DoguÇagdaşAtilla Çagatay Aydin Department Electrical and Computer Engineering Altinbas UniversityIstanbulTurkey Department Computer Technology Engineering Al-Esraa UniversityBaghdadIraq Electric Autonomous and Unmanned Vehicles Application and Research CentreAltinbas UniversityIstanbulTurkey Faculty of Engineering and Architecture Altinbas UniversityIstanbulTurkey Department Electrical and Electronics Engineering Ege UniversityIzmirTurkey

Deep learning(DL)is a subdivision of machine learning(ML)that employs numerous algorithms,each of which provides various explanations of the data it consumes;mobile ad-hoc networks(MANET)are growing in *** reasons including node mobility,due to MANET’s potential to provide small-cost solutions for real-world contact challenges,decentralized management,and restricted bandwidth,MANETs are more vulnerable to security *** protecting MANETs from attack,encryption and authentication schemes have their ***,deep learning(DL)approaches in intrusion detection sys-tems(IDS)can adapt to the changing environment of MANETs and allow a sys-tem to make intrusion decisions while learning about its mobility in the *** are a secondary deﬁance system for mobile ad-hoc networks *** since they monitor network trafﬁc and report anything ***,many scientists have employed deep neural networks(DNNs)to address intrusion detection *** paper used MANET to recognize com-plex patterns by focusing on security standards through efﬁciency determination and identifying malicious nodes,and mitigating network attacks using the three algorithms presented Cascading Back Propagation Neural Network(CBPNN),Feedforward-Neural-Network(FNN),and Cascading-Back-Propagation-Neural-Network(CBPNN)(FFNN).In addition to Convolutional-Neural-Network(CNN),these primary forms of deep neural network(DNN)building designs are widely used to improve the performance of intrusion detection systems(IDS)and the use of IDS in conjunction with machine learning(ML).Further-more,machine learning(ML)techniques than their statistical and logical methods provide MANET network learning capabilities and encourage adaptation to differ-ent *** with another current model,The proposed model has better average receiving packet(ARP)and end-to-end(E2E)*** results have been obtained from CBP,FFNN and CNN 74%,82%and 85%,respectively,by the ti

关键词： ARP CBPNN CNN DNN DL E2E FFNN IDS ML MANET security