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Enhancing Telemarketing Success Using Ensemble-Based Online Machine Learning

American Journal of Analytical Chemistry（美国分析化学） 2024年第5期 151页

作者： md.nazmus sakib chowdhury Sreekanta Nath Dalal md.Ariful Islam md.Anwar Hossain Pranab Kumar Das Shakawat Hossain Parajit Das

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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

Robustness Study and Superior Method Development and Validation for Analytical Assay Method of Atropine Sulfate in Pharmaceutical Ophthalmic Solution

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American Journal of Analytical Chemistry 2024年第5期15卷 151-164页

作者： md. nazmus sakib chowdhury Sreekanta Nath Dalal md. Ariful Islam md. Anwar Hossain Pranab Kumar Das Shakawat Hossain Parajit Das Department of Pharmacy Bangabandhu Sheikh Mujibur Rahman Science and Technology University Gopalganj Bangladesh Department of Applied Chemistry and Chemical Engineering University of Dhaka Dhaka Bangladesh Department of Applied Chemistry and Chemical Engineering University of Chittagong Chattogram Bangladesh Department of Applied Chemistry and Chemical Engineering Islamic University Kushtia Bangladesh Department of Applied Chemistry and Chemical Engineering University of Rajshahi Rajshahi Bangladesh Department of Pharmacy International Islamic University Chittagong Chittagong Bangladesh Department of Applied Chemistry and Chemical Engineering Bangabandhu Sheikh Mujibur Rahman Science and Technology University Gopalganj Bangladesh

Background: The robustness is a measurement of an analytical chemical method and its ability to contain unaffected by little with deliberate variation of analytical chemical method parameters. The analytical chemical method variation parameters are based on pH variability of buffer solution of mobile phase, organic ratio composition changes, stationary phase (column) manufacture, brand name and lot number variation;flow rate variation and temperature variation of chromatographic system. The analytical chemical method for assay of Atropine Sulfate conducted for robustness evaluation. The typical variation considered for mobile phase organic ratio change, change of pH, change of temperature, change of flow rate, change of column etc. Purpose: The aim of this study is to develop a cost effective, short run time and robust analytical chemical method for the assay quantification of Atropine in Pharmaceutical Ophthalmic Solution. This will help to make analytical decisions quickly for research and development scientists as well as will help with quality control product release for patient consumption. This analytical method will help to meet the market demand through quick quality control test of Atropine Ophthalmic Solution and it is very easy for maintaining (GDP) good documentation practices within the shortest period of time. Method: HPLC method has been selected for developing superior method to Compendial method. Both the compendial HPLC method and developed HPLC method was run into the same HPLC system to prove the superiority of developed method. Sensitivity, precision, reproducibility, accuracy parameters were considered for superiority of method. Mobile phase ratio change, pH of buffer solution, change of stationary phase temperature, change of flow rate and change of column were taken into consideration for robustness study of the developed method. Results: The limit of quantitation (LOQ) of developed method was much low than the compendial method. The % RSD fo

关键词： Robustness Method Validation HPLC Compendial Method Method Development GDP LOQ

OAM-based diffractive all-optical classification

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Advanced Photonics 2024年第1期6卷 6-7页

作者： md Sadman sakib Rahman Aydogan Ozcan University of California Electrical and Computer Engineering DepartmentLos AngelesCaliforniaUnited States University of California Bioengineering DepartmentLos AngelesCaliforniaUnited States University of California California NanoSystems Institute(CNSI)Los AngelesCaliforniaUnited States

Object classification is an important aspect of machine *** practices in object classification entail the digitization of object information followed by the application of digital algorithms such as deep neural *** execution of digital neural networks is power-consuming,and the throughput is *** existing von Neumann digital computing paradigm is also less suited for the implementation of highly parallel neural network architectures.^(1)

关键词： consuming digit neural

Neural Network-Powered License Plate Recognition System Design

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Engineering（科研） 2024年第9期16卷 284-300页

作者： sakib Hasan md Nagib Mahfuz Sunny Abdullah Al Nahian Mohammad Yasin School of Information and Electronics Beijing Institute of Technology Beijing China Department of Engineering and Technology Trine University Fort Wayne USA Department of Information Technology Management Westcliff University Irvine USA

The development of scientific inquiry and research has yielded numerous benefits in the realm of intelligent traffic control systems, particularly in the realm of automatic license plate recognition for vehicles. The design of license plate recognition algorithms has undergone digitalization through the utilization of neural networks. In contemporary times, there is a growing demand for vehicle surveillance due to the need for efficient vehicle processing and traffic management. The design, development, and implementation of a license plate recognition system hold significant social, economic, and academic importance. The study aims to present contemporary methodologies and empirical findings pertaining to automated license plate recognition. The primary focus of the automatic license plate recognition algorithm was on image extraction, character segmentation, and recognition. The task of character segmentation has been identified as the most challenging function based on my observations. The license plate recognition project that we designed demonstrated the effectiveness of this method across various observed conditions. Particularly in low-light environments, such as during periods of limited illumination or inclement weather characterized by precipitation. The method has been subjected to testing using a sample size of fifty images, resulting in a 100% accuracy rate. The findings of this study demonstrate the project’s ability to effectively determine the optimal outcomes of simulations.

关键词： Intelligent Traffic Control Systems Automatic License Plate Recognition (ALPR) Neural Networks Vehicle Surveillance Traffic Management License Plate Recognition Algorithms Image Extraction Character Segmentation Character Recognition Low-Light Environments Inclement Weather Empirical Findings Algorithm Accuracy Simulation Outcomes Digitalization

Ensemble learning of diffractive optical networks

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Light(Science & Applications) 2021年第1期10卷 123-135页

作者： md Sadman sakib Rahman Jingxi Li Deniz Mengu Yair Rivenson Aydogan Ozcan Electrical and Computer Engineering Department University of CaliforniaLos AngelesCA 90095USA Bioengineering Department University of CaliforniaLos AngelesCA 90095USA California NanoSystems Institute(CNSI) University of CaliforniaLos AngelesCA 90095USA

A plethora of research advances have emerged in the fields of optics and photonics that benefit from harnessing the power of machine ***,there has been a revival of interest in optical computing hardware due to its potential advantages for machine learning tasks in terms of parallelization,power efficiency and computation *** deep neural networks(D^(2)NNs)form such an optical computing framework that benefits from deep learning-based design of successive diffractive layers to all-optically process information as the input light diffracts through these passive layers.D^(2)NNs have demonstrated success in various tasks,including object classification,the spectral encoding of information,optical pulse shaping and ***,we substantially improve the inference performance of diffractive optical networks using feature engineering and ensemble *** independently training 1252 D^(2)NNs that were diversely engineered with a variety of passive input filters,we applied a pruning algorithm to select an optimized ensemble of D^(2)NNs that collectively improved the image classification *** this pruning,we numerically demonstrated that ensembles of N=14 and N=30 D^(2)NNs achieve blind testing accuracies of 61.14±0.23%and 62.13±0.05%,respectively,on the classification of GFAR-10 test images,providing an inference improvennent of>16%compared to the average performance of the individual D^(2)NNs within each *** results constitute the highest inference accuracies achieved to date by any diffractive optical neural network design on the same dataset and might provide a significant leap to extend the application space of diffractive optical image classification and machine vision systems.

关键词： networks collective successive

My Medical Career in China

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China News Release 2023年第2期 48-50页

作者： nazmus sakib Peking University First Hospital

“Amid the blasts of firecrackers the old year is over.”Fireworks light up a new year,also a new chapter of my stories in *** always,I look forward with expectation toward the new chapter,whatever it will ***,Chapte... 详细信息

关键词： crack China Fireworks

Heterogeneous length-of-stay modeling of post-acute care residents in the nursing home with competing discharge dispositions

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Frontiers of Engineering Management 2022年第4期9卷 577-591页

作者： nazmus sakib Xuxue SUN Nan KONG Chris MASTERSON Hongdao MENG Kelly SMITH Mingyang LI Department of Industrial and Management Systems Engineering University of South FloridaTampaFL 33620USA College of Media Engineering Communication University of ZhejiangHangzhou 310019China Weldon School of Biomedical Engineering Purdue UniversityWest LafayetteIN 47907USA Greystone Health Network TampaFL 33610USA School of Aging Studies University of South FloridaTampaFL 33620USA

Post-acute care(PAC)residents in nursing homes(NHs)are recently hospitalized patients with medically complex diagnoses,ranging from severe orthopedic injuries to cardiovascular diseases.A major role of NHs is to maximize restoration of PAC residents during their NH stays with desirable discharge outcomes,such as higher community discharge likelihood and lower re/hospitalization *** prediction of the PAC residents’length-of-stay(LOS)with multiple discharge dispositions(e.g.,community discharge and re/hospitalization)will allow NH management groups to stratify NH residents based on their individualized risk in realizing personalized and resident-centered NH care *** to the highly heterogeneous health conditions of PAC residents and their multiple types of correlated discharge dispositions,developing an accurate prediction model becomes *** predictive analytics methods,such as distribution-/regression-based methods and machine learning methods,either fail to incorporate varied individual characteristics comprehensively or ignore multiple discharge *** this work,a data-driven predictive analytics approach is considered to jointly predict the individualized re/hospitalization risk and community discharge likelihood over time in the presence of varied residents’characteristics.A sampling algorithm is further developed to generate accurate predictive samples for a heterogeneous population of PAC residents in an NH and facilitate facility-level performance evaluation.A real case study using large-scale NH data is provided to demonstrate the superior prediction performance of the proposed work at individual and facility levels through comprehensive comparison with a large number of existing prediction methods as *** developed analytics tools will allow NH management groups to identify the most at-risk residents by providing them with more proactive and focused care to improve resident outcomes.

关键词： nursing home predictive analytics individualized prediction competing risks health outcomes

Analysis of Clinicians' Subjective Approach Based on Three-way Mental Disorders Classification

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Analysis of Clinicians' Subjective Approach Based on Three-w...

作者： md sakib Ullah Sourav 山东财经大学

学位级别：硕士

The traditional psychiatric diagnosis process is based on psychiatric nosology or mental disorders classification that follows a data-driven objective approach which implies an internal information-based analysis that is found unable in solving many complex *** construct a unified framework while in the psychiatric diagnosis process,as well as with other criteria,similar importance should be imposed on practitioners' external analysis consisting of culture-specific knowledge along with domain knowledge,through attained expertise and experience with a subjective *** on the principles of three-way decision,this thesis concentrated on the subjective approach from the clinician and proposed a model for the clinician's subjective approach(CSA)analysis with two *** first step is qualitative and quantitative *** the qualitative approach,we talked about the property of trichotomy,which plays an essential role in representing user *** building a structure using the TAO model,we can rank a set of disorders concerning their *** the quantitative approach,the three-level computing model is *** weights are assigned to disorders using the eigenvector *** second step is utilizing the evaluation-based three-way decision to categorize a disorder set into three classes of different importance in *** use three-way decision theory as our fundamental framework to examine CSA to classify mental disorders in psychiatric *** CSA model might be integrated with the traditional psychiatric diagnosis set up as an effective tool to make the whole diagnostic process more robust and powerful.

关键词： Data-driven decision making Three-way decisions Psychiatric diagnosis Mental disorder classification the Trisecting-Acting-Outcome (TAO) model

Chitosan based bioactive materials in tissue engineering applications-A review

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Bioactive Materials 2020年第1期5卷 164-183页

作者： md.Minhajul Islam md.Shahruzzaman Shanta Biswas md.Nurus sakib Taslim Ur Rashid Department of Applied Chemistry and Chemical Engineering Faculty of Engineering and TechnologyUniversity of DhakaDhaka1000Bangladesh Fiber and Polymer Science North Carolina State UniversityCampus Box 7616RaleighNC27695United States

In recent years,there have been increasingly rapid advances of using bioactive materials in tissue engineering *** materials constitute many different structures based upon ceramic,metallic or polymeric materials,and can elicit specific tissue ***,most of them are relatively brittle,stiff,and difficult to form into complex ***,there has been a growing demand for preparing materials with tailored physical,biological,and mechanical properties,as well as predictable degradation ***-based materials have been shown to be ideal bioactive materials due to their outstanding properties such as formability into different structures,and fabricability with a wide range of bioactive materials,in addition to their biocompatibility and *** review highlights scientific findings concerning the use of innovative chitosan-based bioactive materials in the fields of tissue engineering,with an outlook into their future *** also covers latest developments in terms of constituents,fabrication technologies,structural,and bioactive properties of these materials that may represent an effective solution for tissue engineering materials,making them a realistic clinical alternative in the near future.

关键词： Chitosan Bioactive material Scaffold Tissue engineering