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Improved Transient Search Optimization with Machine Learning Based Behavior Recognition on Body Sensor Data

Computers, Materials & Continua 2023年第5期75卷 4593-4609页

作者： Baraa Wasfi Salim Bzar Khidir Hussan zainab Salih Ageed Subhi R.M.Zeebaree ITM Department Technical College of AdministrationDuhok Polytechnic UniversityDuhokIraq Information System Engineering Department Erbil Technical Engineering CollegeErbil Polytechnic UniversityErbilIraq Computer Science Department College of ScienceNawroz UniversityDuhokIraq Energy Eng.Department Technical College of EngineeringDuhok Polytechnic UniversityDuhokIraq

Recently,human healthcare from body sensor data has gained considerable interest from a wide variety of human-computer communication and pattern analysis research owing to their real-time applications namely smart healthcare *** though there are various forms of utilizing distributed sensors to monitor the behavior of people and vital signs,physical human action recognition(HAR)through body sensors gives useful information about the lifestyle and functionality of an *** article concentrates on the design of an Improved Transient Search Optimization with Machine Learning based BehaviorRecognition(ITSOMLBR)technique using body sensor *** presented ITSOML-BR technique collects data from different body sensors namely electrocardiography(ECG),accelerometer,and *** addition,the ITSOML-BR technique extract features like variance,mean,skewness,and standard ***,the presented ITSOML-BR technique executes a micro neural network(MNN)which can be employed for long term healthcare monitoring and ***,the parameters related to the MNN model are optimally selected via the ITSO *** experimental result analysis of the ITSOML-BR technique is tested on the MHEALTH *** comprehensive comparison study reported a higher result for the ITSOMLBR approach over other existing approaches with maximum accuracy of 99.60%.

关键词： Behavior recognition transient search optimization machine learning healthcare sensors wearables

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Mutagenic and cytotoxic potential of Endosulfan and Lambda-cyhalothrin—In vitro study describing individual and combined effects of pesticides

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Journal of Environmental Sciences 2014年第7期26卷 1471-1479页

作者： Umber Saleem Sohail Ejaz Muhammad Ashraf Muhammad Ovais Omer Imran Iltaf zainab Batool Riffat Fatima Msbah Afzal Department of Pharmacology & Toxicology University of Veterinary and Animal Sciences Lahore 54000 Pakistan Department of Clinical Neurosciences Neurology Unit Addenbrooke's Hospital University of Cambridge Cambridge UK Microbiology Section Quality Operations Laboratory University of Veterinary and Animal Sciences Lahore Pakistan

Excessive use of pesticides poses increased risks to non target species including humans. In the developing countries, lack of proper awareness about the toxic potential of pesticides makes the farmer more vulnerable to pesticide linked toxicities, which could lead to diverse pathological conditions. The toxic potential of a pesticide could be determined by their ability to induce genetic mutations and cytotoxicity. Hence, determination of genetic mutation and cytotoxicity of each pesticide is unavoidable to legislate health and safety appraisal about pesticides. The objective of current investigation was to determine the genotoxic and cytotoxic potential of Endosulfan（EN） and Lambda-cyhalothrin（LC）; individually and in combination. 3-（4,5-Dimethylthiazol-2-yl）-2,5-Diphenyltetrazolium Bromide（MTT） assay was utilized to determine cytotoxicity, while two mutant histidine dependent Salmonella strains（TA98, TA100） were used to determine the mutagenicity of EN and ***, mutagenicity assay was conducted with and without S9 to evaluate the effects of metabolic activation on mutagenicity. Even though a dose dependent increase in the number of revertant colonies was detected with EN against both bacterial strains, a highly significant（p 〈 0.05） increase in the mutagenicity was detected in TA98 with S9. In comparison, data obtained from LC revealed less mutagenic potential than EN. Surprisingly,the non-mutagenic individual-concentrations of EN and LC showed dose dependent mutagenicity when combined. Combination of EN and LC synergistically induced mutagenicity both in TA98 and TA100. MTT assay spotlighted comparable dose dependent cytotoxicity effects of both pesticides. Interestingly, the combination of EN and LC produced increased reversion and cytotoxicity at lower doses as compared to each pesticide, concluding that pesticide exposure even at sub-lethal doses can produce cytotoxicity and genetic mutations, which could lead to carcinogenicity.

关键词： Endosulfan Lambda-cyhalothrin Mutagenicity Cytotoxicity

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Corrosion Protection of 5083 AA in SalineWater by Polyacrylonitrile Nanofibers

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Journal of Renewable Materials 2021年第11期9卷 1927-1939页

作者： Enas H.Ali Juman A.Naser zainab W.Ahmed Taki A.Himdan Department of Chemistry College of Education for Pure Science-Ibn Al-HaithamUniversity of BaghdadBaghdadIraq

Polymeric nanofibers are a promising technology to protect the metal surfaces from *** the literature search,the use of polyacrylonitrile nanofibres(PANNFs)as a corrosion inhibitor coating for aluminum alloys has not been *** work includes the development of a new,lightweight,high surface area and efficient coating of PANNFs that produced using electrospinning process to resist the corrosion of aluminum alloys(AA5083)which immersed in 0.6 M NaCl at alkaline medium(pH=12)and acidic medium(pH=1)at a range of temperatures(293–323)*** PANNFs coating was successfully deposited on AA 5083 specimens,where these samples were considered as a collector electrode in the electrospinning *** corrosion experiments of the aluminum alloys coated with PANNFs before and after immersion in both corrosive mediums were investigated using cyclic potential polarization(CPP).The results confirmed that the PANNFs coating was able to protect the surface of the aluminum specimens from corrosion,by reducing the corrosion current and increasing the surface polarization resistance,thus reducing the corrosion *** protection efficiency was found in the alkaline medium 98.8%while in the acidic medium 83.3%.So,it was in both mediums decreased with the increase in *** shape,distribution and size of the polymeric nanofibers that formed the coating were also examined using field emission scanning electron microscopy(FE-SEM)and the percentages of the structural components of these fibers were detected using the X-ray dispersion spectroscopy(EDS).The surface of aluminum specimens was completely covered by *** electrospun nanofibers have worn out and lined up spacing after immersion in the corrosive *** diameters average of PANNFs was found to be about 200 and 150 nm before and after immersion,respectively.

关键词： Corrosion protection nanofibers polyacrylonitrile aluminum alloy saline medium protection efficiency

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Modified Wild Horse Optimization with Deep Learning Enabled Symmetric Human Activity Recognition Model

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Computers, Materials & Continua 2023年第5期75卷 4009-4024页

作者： Bareen Shamsaldeen Tahir zainab Salih Ageed Sheren Sadiq Hasan Subhi R.M.Zeebaree Accounting Department College of Administration and EconomicsUniversity of DuhokDuhokIraq Computer Science Department College of ScienceNawroz UniversityDuhokIraq ITM Department Technical College of AdministrativeDuhok Polytechnic UniversityDuhokIraq Energy Eng.Department Technical College of EngineeringDuhok Polytechnic UniversityDuhokIraq

Traditional indoor human activity recognition(HAR)is a timeseries data classification problem and needs feature ***,considerable attention has been given to the domain ofHARdue to the enormous amount of its real-time uses in real-time applications,namely surveillance by authorities,biometric user identification,and health monitoring of older *** extensive usage of the Internet of Things(IoT)and wearable sensor devices has made the topic of HAR a vital subject in ubiquitous and mobile *** more commonly utilized inference and problemsolving technique in the HAR system have recently been deep learning(DL).The study develops aModifiedWild Horse Optimization withDLAided Symmetric Human Activity Recognition(MWHODL-SHAR)*** major intention of the MWHODL-SHAR model lies in recognition of symmetric activities,namely jogging,walking,standing,sitting,*** the presented MWHODL-SHAR technique,the human activities data is pre-processed in various stages to make it compatible for further processing.A convolution neural network with an attention-based long short-term memory(CNNALSTM)model is applied for activity *** MWHO algorithm is utilized as a hyperparameter tuning strategy to improve the detection rate of the CNN-ALSTM *** experimental validation of the MWHODL-SHAR technique is simulated using a benchmark *** extensive comparison study revealed the betterment of theMWHODL-SHAR technique over other recent approaches.

关键词： Human activity recognition symmetry deep learning machine learning pattern recognition time series classification

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Automated Colonic Polyp Detection and Classification Enabled Northern Goshawk Optimization with Deep Learning

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Computers, Materials & Continua 2023年第5期75卷 3677-3693页

作者： Mohammed Jasim Mohammed Jasim Bzar Khidir Hussan Subhi R.M.Zeebaree zainab Salih Ageed Engineering College Al-Kitab UniversityKirkukIraq Information System Engineering Department Erbil Technical Engineering CollegeErbil Polytechnic UniversityErbilIraq Energy Eng.Department Technical College of EngineeringDuhok Polytechnic UniversityDuhokIraq Computer Science Department College of ScienceNawroz UniversityDuhokIraq

The major mortality factor relevant to the intestinal tract is the growth of tumorous cells(polyps)in various *** specifically,colonic polyps have a high rate and are recognized as a precursor of colon cancer *** is the conventional technique for detecting colon polyps,and considerable research has proved that automated diagnosis of image regions that might have polyps within the colon might be used to help experts for decreasing the polyp miss *** automated diagnosis of polyps in a computer-aided diagnosis(CAD)method is implemented using statistical ***,Deep Learning,particularly throughConvolution Neural networks(CNN),is broadly employed to allowthe extraction of representative *** manuscript devises a new Northern Goshawk Optimization with Transfer Learning Model for Colonic Polyp Detection and Classification(NGOTL-CPDC)*** NGOTL-CPDC technique aims to investigate endoscopic images for automated colonic polyp *** accomplish this,the NGOTL-CPDC technique comprises of adaptive bilateral filtering(ABF)technique as a noise removal process and image pre-processing ***,the NGOTL-CPDC model applies the Faster SqueezeNet model for feature extraction purposes in which the hyperparameter tuning process is performed using the NGO ***,the fuzzy Hopfield neural network(FHNN)method can be employed for colonic poly detection and classification.A widespread simulation analysis is carried out to ensure the improved outcomes of the NGOTL-CPDC *** comparison study demonstrates the enhancements of the NGOTL-CPDC model on the colonic polyp classification process on medical test images.

关键词： Biomedical imaging artificial intelligence colonic polyp classification medical image classification computer-aided diagnosis

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Metabolomics in drug discovery: Restoring antibiotic pipeline

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亚太热带生物医学杂志:英文版 2023年第9期13卷 378-383页

作者： Faiza Azhar Mariam Busharat Shah Rukh Arshad Chaudhary zainab Waheed Muhammad Nauman Jamil Department of Pharmaceutical Chemistry Punjab University College of PharmacyUniversity of the PunjabLahorePakistan School of Medical Indigenous and Health SciencesUniversity of WollongongNew South WalesAustralia Department of General Surgery Lahore General HospitalLahorePakistan Department of Pharmaceutical Chemistry Hamza College of PharmacyLahorePakistan

Metabolomics has emerged as a valuable tool in drug discovery and development,providing new insights into the mechanisms of action and toxicity of potential therapeutic *** focuses on the comprehensive analysis of primary as well as secondary metabolites,within biological *** provides a comprehensive understanding of the metabolic changes that occur within microbial pathogens when exposed to therapeutic agents,thus allowing for the identification of unique metabolic targets that can be exploited for therapeutic *** approach can also uncover key metabolic pathways essential for survival,which can serve as potential targets for novel *** analyzing the metabolites produced by diverse microbial communities,metabolomics can guide the discovery of previously unexplored sources of *** review explores some examples that enable medicinal chemists to optimize drug structure,enhancing efficacy and minimizing toxicity via metabolomic approaches.

关键词： Metabolomics Infectious diseases Drug discovery Antibiotics Biomarkers

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Ethylene Conversion to Higher Hydrocarbon over Copper Loaded BZSM-5 in the Presence of Oxygen

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Journal of Natural Gas Chemistry 2006年第4期15卷 259-265页

作者： Ramli Mat Nor Aishah Saidina Amin zainab Ramli W.Azelee W.Abu Bakar Dept.of Chemical Engineering Faculty of Chemical & Natural Resources EngineeringUniversiti Teknologi MalaysiaSkudai81310 Johor BahruMalaysia Dept.of Chemistry Universiti Teknologi MalaysiaSkudai81310 Johor BahruMalaysia

The successful production of higher hydrocarbons from methane depends on the stability or the oxidation rate of the intermediate products. The performances of the BZSM-5 and the modified BZSM-5 catalysts were tested for ethylene conversion into higher hydrocarbons. The catalytic experiments were carried out in a fixed-bed micro reactor at atmospheric pressure. The catalysts were characterized using XRD, NH3-TPD, and IR for their structure and acidity. The result suggests that BZSM-5 is a weak acid. The introduction of copper into BZSM-5 improved the acidity of BZSM-5. The conversion of ethylene toward higher hydrocarbons is dependent on the acidity of the catalyst. Only weaker acid site is required to convert ethylene to higher hydrocarbons. The loading of Cu on BZSM-5 improved the selectivity for higher hydrocarbons especially at low percentage. The reactivity of ethylene is dependent on the amount of acidity as well as the presence of metal on the catalyst surface. Cul%BZSM-5 is capable of converting ethylene to higher hydrocarbons. The balances between the metal and acid sites influence the performance of ethylene conversion and higher hydrocarbon selectivity. Higher loading of Cu leads to the formation of COx.

关键词： ethylene conversion BZSM-5 zeolite acidity higher hydrocarbon

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Molecular detection of Anaplasma marginale and Anaplasma ovis in sheep and goat in west highland pasture of Iran

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Asian Pacific Journal of Tropical Biomedicine 2017年第5期7卷 455-459页

作者： Ali Yousefi Sadegh Rahbari Parviz Shayan zainab Sadeghi-dehkordi Alireza Bahonar Department of Microbiology Science and Research BranchIslamic Azad University Department of Parasitology Faculty of Veterinary MedicineUniversity of Tehran Department of Parasitology Faculty of Paraveterinary MedicineBu-Ali Sina University Department of Food Hygiene and Quality Control Faculty of Veterinary MedicineUniversity of Tehran

Objective:To determine the prevalence of Anaplasma marginale(***) and Anaplasma ovis from sheep and goat in different highland pasture in west of ***:From July 2015 to October 2015,370 blood samples of sheep and goat were collected from different regions in Hamedan province,*** DNA extracted from blood and subsequently,16 S r RNA and MSP4 genes were analyzed by nested-PCR,semi nested-PCR and RFLP ***:In the PCR assessment,overall 27.5%(102/370) of sheep and goat were positive for Anaplasma ovis and *** infection,which was lower than reports from tropical and subtropical regions of *** analysis(the Chi-square test) did not show any significant relation between infection and variables such as location,tick infestation age and sex(P > 0.05).No significant correlation between the altitude and the Anaplasma species infection was found(Mann–Whitney test:P > 0.05).However,Anaplasma infection in goat significantly is more than the sheep(P = 0.008).Conclusions:The ecological changes affect the frequency and distribution of Anaplasma ***,our results indicate that sheep as potential reservoirs of ***.

关键词： Anaplasma PCR Sheep Goat Iran

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Artificial Intelligence Based Reliable Load Balancing Framework in Software-Defined Networks

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Computers, Materials & Continua 2022年第1期70卷 251-266页

作者： Mohammad Riyaz Belgaum Fuead Ali zainab Alansari Shahrulniza Musa Muhammad Mansoor Alam M.S.Mazliham Malaysian Institute of Information Technology Universiti Kuala LumpurKuala Lumpur50250Malaysia Majan University College Muscat710Oman Institute of Business Management KarachiPakistan Malaysia France Institute Universiti Kuala LumpurKuala Lumpur43650Malaysia

Software-defined networking(SDN)plays a critical role in transforming networking from traditional to intelligent *** increasing demand for services from cloud users has increased the load on the *** efficient system must handle various loads and increasing needs representing the relationships and dependence of businesses on automated measurement systems and guarantee the quality of service(QoS).Themultiple paths from source to destination give a scope to select an optimal path by maintaining an equilibrium of load using some best ***,the requests need to be transferred to reliable network *** address SDN’s current and future challenges,there is a need to know how artificial intelligence(AI)optimization techniques can efficiently balance the *** study aims to explore two artificial intelligence optimization techniques,namely Ant Colony Optimization(ACO)and Particle Swarm Optimization(PSO),used for load balancing in ***,we identified that a modification to the existing optimization technique could improve the performance by using a reliable link and node to form the path to reach the target node and improve load ***,we propose a conceptual framework for SDN futurology by evaluating node and link reliability,which can balance the load efficiently and improve QoS in SDN.

关键词： Ant colony optimization load balancing particle swarm optimization quality of service reliability software-defined networking

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Solar Radiation Prediction Using Satin Bowerbird Optimization with Modified Deep Learning

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Computer Systems Science & Engineering 2023年第9期46卷 3225-3238页

作者： Sheren Sadiq Hasan zainab Salih Agee Bareen Shamsaldeen Tahir Subhi R.M.Zeebaree ITM Department Technical College of AdministrativeDuhok Polytechnic UniversityDuhokIraq Computer Science Department College of ScienceNawroz UniversityDuhokIraq Accounting Department College of Adminstration and EconomicsUniversity of DuhokDuhokIraq Energy Eng.Department Technical College of EngineeringDuhok Polytechnic UniversityDuhokIraq

Solar energy will be a great alternative to fossil fuels since it is clean and *** photovoltaic(PV)mechanism produces sunbeams’green energy without noise or *** PV mechanism seems simple,seldom malfunctioning,and easy to *** energy productivity significantly contributes to smart grids through many small PV *** solar radiation(SR)prediction could substantially reduce the impact and cost relating to the advancement of solar *** recent times,several SR predictive mechanism was formulated,namely artificial neural network(ANN),autoregressive moving average,and support vector machine(SVM).Therefore,this article develops an optimal Modified Bidirectional Gated Recurrent Unit Driven Solar Radiation Prediction(OMBGRU-SRP)for energy *** presented OMBGRU-SRP technique mainly aims to accomplish an accurate and time SR prediction *** accomplish this,the presented OMBGRU-SRP technique performs data preprocessing to normalize the solar ***,the MBGRU model is derived using BGRU with an attention mechanism and skip *** last,the hyperparameter tuning of the MBGRU model is carried out using the satin bowerbird optimization(SBO)algorithm to attain maximum prediction with minimum error *** SBO algorithm is an intelligent optimization algorithm that simulates the breeding behavior of an adult male Satin Bowerbird in the *** experiments were conducted to demonstrate the enhanced SR prediction *** experimental values highlighted the supremacy of the OMBGRU-SRP algorithm over other existing models.

关键词： Solar radiation prediction deep learning parameter optimization energy management sustainability

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