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Decentralized content sharing in mobile ad-hoc networks:A survey

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Digital Communications and Networks 2023年第6期9卷 1363-1398页

作者： shahriar Kaisar Joarder Kamruzzaman Gour Karmakar md Mamunur Rashid Department of Information Systems and Business Analytics RMIT UniversityAustralia School of Engineering IT and Physical SciencesFederation University AustraliaVictoriaAustralia School of Engineering and Technology Central Queensland UniversityAustralia

The evolution of smart mobile devices has significantly impacted the way we generate and share contents and introduced a huge volume of Internet *** address this issue and take advantage of the short-range communication capabilities of smart mobile devices,the decentralized content sharing approach has emerged as a suitable and promising *** content sharing uses a peer-to-peer network among colocated smart mobile device users to fulfil content *** articles have been published to date to address its different aspects including group management,interest extraction,message forwarding,participation incentive,and content *** survey paper summarizes and critically analyzes recent advancements in decentralized content sharing and highlights potential research issues that need further consideration.

关键词： Decentralized content sharing Mobile ad-hoc networks Delay-tolerant networks Flying ad hoc networks Message forwarding Content caching Incentive Group formation Misbehavior detection

Computational model generation and RVE design o self-healing concrete

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Frontiers of Structural and Civil Engineering 2015年第4期9卷 383-396页

作者： md. shahriar QUAYUM Xiaoying ZHUANG Timon RABCZUK Institute of Structural Mechanics Bauhaus-Universitat Weimar Weimar 99425 Germany Department of Geotechnical Engineering College of Civil Engineering Tongji University Shanghai 200092 China

Computational homogenization is a versatile tool that can extract effective properties of heterogeneous or composite material through averaging technique. Self-healing concrete (SHC) is a heterogeneous material which has different constituents as cement matrix, sand and healing agent carrying capsules. Computational homogenization tool is applied in this paper to evaluate the effective properties of self-healing concrete. With this technique, macro and micro scales are bridged together which forms the basis for multi-scale modeling. Representative volume element (RVE) is a small (microscopic) cell which contains all the microphases of the microstructure. This paper presents a technique for RVE design of SHC and shows the influence of volume fractions of different constituents, RVE size and mesh uniformity on the homogenization results.

关键词： homogenization self-healing concrete (SHC) representative volume element multiscale modelling

Enhancing Telemarketing Success Using Ensemble-Based Online Machine Learning

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Big Data Mining and Analytics 2024年第2期7卷 294-314页

作者： shahriar Kaisar md Mamunur Rashid Abdullahi Chowdhury Sakib shahriar Shafin Joarder Kamruzzaman Abebe Diro Department of Information Systems and Business Analytics RMIT UniversityMelbourne 3000Australia School of Engineering and Technology Central Queensland UniversityRockhampton 4700Australia Faculty of Engineering Computer and Mathematical ScienceUniversity of AdelaideAdelaide 5005Australia Centre for Smart Analytics Federation University AustraliaBallarat 3350Australia School of Accounting Information Systems and Supply ChainRMIT UniversityMelbourne 3000Australia

Telemarketing is a well-established marketing approach to offering products and services to prospective *** effectiveness of such an approach,however,is highly dependent on the selection of the appropriate consumer base,as reaching uninterested customers will induce annoyance and consume costly enterprise resources in vain while missing interested *** introduction of business intelligence and machine learning models can positively influence the decision-making process by predicting the potential customer base,and the existing literature in this direction shows promising ***,the selection of influential features and the construction of effective learning models for improved performance remain a ***,from the modelling perspective,the class imbalance nature of the training data,where samples with unsuccessful outcomes highly outnumber successful ones,further compounds the problem by creating biased and inaccurate ***,customer preferences are likely to change over time due to various reasons,and/or a fresh group of customers may be targeted for a new product or service,necessitating model retraining which is not addressed at all in existing works.A major challenge in model retraining is maintaining a balance between stability(retaining older knowledge)and plasticity(being receptive to new information).To address the above issues,this paper proposes an ensemble machine learning model with feature selection and oversampling techniques to identify potential customers more accurately.A novel online learning method is proposed for model retraining when new samples are available over *** newly introduced method equips the proposed approach to deal with dynamic data,leading to improved readiness of the proposed model for practical adoption,and is a highly useful addition to the *** experiments with real-world data show that the proposed approach achieves excellent results in all cases(e.g.,98.6

关键词： machine learning online learning oversampling telemarketing imbalanced dataset ensemble model

Vision Intelligence for Smart Sheep Farming: Applying Ensemble Learning to Detect Sheep Breeds

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Artificial Intelligence in Agriculture 2024年第1期11卷 1-12页

作者： Galib Muhammad shahriar Himel md Masudul Islam Mijanur Rahaman Bangladesh University of Business and Technology DhakaBangladesh

The ability to automatically recognize sheep breeds holds significant value for the sheep *** farmers often require breed identification to assess the commercial worth of their ***,many farmers specifically the novice one encounter difficulties in accurately identifying sheep breeds without experts in the ***,there is a need for autonomous approaches that can effectively and precisely replicate the breed identification skills of a sheep breed expert while functioning within a farm environment,thus providing considerable benefits the industry-specific to the novice farmers in the *** achieve this objective,we suggest utilizing a model based on convolutional neural networks(CNNs)which can rapidly and efficiently identify the type of sheep based on their facial *** approach offers a cost-effective *** conduct our experiment,we utilized a dataset consisting of 1680 facial images which represented four distinct sheep *** paper proposes an ensemble method that combines Xception,VGG16,InceptionV3,InceptionResNetV2,and DenseNet121 *** the transfer learning using this pre-trained model,we applied several optimizers and loss functions and chose the best combinations out of *** classification model has the potential to aid sheep farmers in precisely and efficiently distinguishing between various breeds,enabling more precise assessments of sector-specific classification for different businesses。

关键词： Computer vision Sheep breed classification Image processing Transfer learning Ensemble learning Meta learner

Bio-inspired optimization algorithms for optical parameter extraction of dielectric materials: A comparative study

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Chinese Physics B 2016年第10期25卷 202-208页

作者： md Ghulam Saber Kh Arif shahriar Ashik Ahmed Rakibul Hasan Sagor Department of Electrical and Electronic Engineering Islamic University of Technology (IUT) Department of Electrical and Electronic Engineering Northern University Bangladesh (NUB)

Particle swarm optimization(PSO) and invasive weed optimization(IWO) algorithms are used for extracting the modeling parameters of materials useful for optics and photonics research community. These two bio-inspired algorithms are used here for the first time in this particular field to the best of our knowledge. The algorithms are used for modeling graphene oxide and the performances of the two are compared. Two objective functions are used for different boundary values. Root mean square(RMS) deviation is determined and compared.

关键词： optical parameter extraction particle swarm optimization invasive weed optimization graphene oxide optimization

Learning from the COVID-19 pandemic:A systematic review of mathematical vaccine prioritization models

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Infectious Disease Modelling 2024年第4期9卷 1057-1080页

作者： Gilberto Gonzalez-Parra md shahriar Mahmud Claus Kadelka Instituto de Matematica Multidisciplinar Universitat Politecnica de ValenciaValenciaSpain Department of Mathematics New Mexico Tech801 Leroy PlaceSocorro87801NMUSA Department of Mathematics Iowa State University411 Morrill RdAmes50011IAUSA

As the world becomes ever more connected,the chance of pandemics increases as *** recent COVID-19 pandemic and the concurrent global mass vaccine roll-out provides an ideal setting to learn from and refine our understanding of infectious disease models for better future *** this review,we systematically analyze and categorize mathematical models that have been developed to design optimal vaccine prioritization strategies of an initially limited *** older individuals are disproportionately affected by COVID-19,the focus is on models that take age explicitly into *** lower mobility and activity level of older individuals gives rise to non-trivial *** research questions concern the optimal time interval between vaccine doses and spatial vaccine *** review showcases the effect of various modeling assumptions on model outcomes.A solid understanding of these relationships yields better infectious disease models and thus public health decisions during the next pandemic.

关键词： Review Mathematical model Age COVID-19 Vaccine allocation Vaccine roll-out

Androgen receptor signaling and mutations in prostate cancer

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Asian Journal of Andrology 2010年第5期12卷 639-657页

作者： shahriar Koochekpour Department of Urology and Stanley S. Scott Cancer Center School of Medicine Louisiana State University HealthSciences Center New Orleans LA 70112 USA

Normal and neoplastic growth of the prostate gland are dependent on androgen receptor （AR） expression and function. Androgenic activation of the AR, in association with its coregulatory factors, is the classical pathway that leads to transcriptional activity of AR target genes. Alternatively, cytoplasmic signaling crosstalk of AR by growth factors, neurotrophic peptides, cytokines or nonandrogenic hormones may have important roles in prostate carcinogenesis and in metastatic or androgen-independent （AI） progression of the disease. In addition, cross-modulation by various nuclear transcription factors acting through basal transcriptional machinery could positively or negatively affect the AR or AR target genes expression and activity. Androgen ablation leads to an initial favorable response in a significant number of patients; however, almost invariably patients relapse with an aggressive form of the disease known as castration-resistant or hormone-refractory prostate cancer （PCa）. Understanding critical molecular events that lead PCa cells to resist androgen-deprivation therapy is essential in developing successful treatments for hormone-refractory disease. In a significant number of hormone-refractory patients, the AR is overexpressed, mutated or genomically amplified. These genetic alterations maintain an active presence for a highly sensitive AR, which is responsive to androgens, antiandrogens or nonandrogenic hormones and collectively confer a selective growth advantage to PCa cells. This review provides a brief synopsis of the AR structure, AR coregulators, posttranslational modifications of AR, duality of AR function in prostate epithelial and stromal cells, AR-dependent signaling, genetic changes in the form of somatic and germline mutations and their known functional significance in PCa cells and tissues.

关键词： androgen receptor germline mutation prostate cancer signaling somatic

DNA methylome and the complexity, of discovering prostate cancer biomarkers

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Asian Journal of Andrology 2011年第5期13卷 661-662页

作者： shahriar Koochekpour Departments of Cancer Genetics and Urology RoswellPark Cancer Institute Elm and Carlton Streets BuffaloNY 14263 USA

Prostate cancer （PCa） remains the most common malignancy and a leading cause of cancer-related ＇deaths in men. Molecular discrimination at an early stage between indolent and aggressive primary tumors in pathologic... 详细信息

关键词： Cancer immunotherapy Non-small-cell lung cancer Targeted therapies

Time-series prediction of shellfish farm closure: A comparison of alternatives

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Information Processing in Agriculture 2014年第1期1卷 42-50页

作者： Ashfaqur Rahman md Sumon shahriar Claire D’Este Greg Smith John McCulloch Greg Timms Autonomous Systems Program CSIRO Computational InformaticsHobartTAS 7000Australia

Shellfish farms are closed for harvest when microbial pollutants are *** pollutants are typically present in rainfall runoff from various land uses in *** currently use a number of observable parameters(river flow,rainfall,salinity)as proxies to determine when to close *** have proposed using the short term historical rainfall data as a time-series prediction problem where we aim to predict the closure of shellfish farms based only on ***-series event prediction consists of two steps:(i)feature extraction,and(ii)prediction.A number of data mining challenges exist for these scenarios:(i)which feature extraction method best captures the rainfall pattern over successive days that leads to opening or closure of the farms?,(ii)The farm closure events occur infrequently and this leads to a class imbalance problem;the question is what is the best way to deal with this problem?In this paper we have analysed and compared different combinations of balancing methods(under-sampling and over-sampling),feature extraction methods(cluster profile,curve fitting,Fourier Transform,Piecewise Aggregate Approximation,and Wavelet Transform)and learning algorithms(neural network,support vector machine,k-nearest neighbour,decision tree,and Bayesian Network)to predict closure events accurately considering the above data mining *** have identified the best combination of techniques to accurately predict shellfish farm closure from rainfall,given the above data mining challenges.

关键词： Aquaculture Shellfish farm closure Data mining Time series data