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Neural Network-Powered License Plate Recognition System Design

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

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Catalytic Reduction of Textile Dyes by N-Doped Ti-Melamine Capped Ag₂S Nano Composites

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Open Journal of Applied Sciences 2022年第6期12卷 892-900页

作者： Mohammad Farhadur Rahman Nargish Jahan Ara sakib hasan Zubair hasan Department of Chemistry Bangladesh University of Textiles Dhaka Bangladesh Department of Fabric Engineering Bangladesh University of Textiles Dhaka Bangladesh Department of Mathematics and Physical Science East West University Dhaka Bangladesh

Waste water expulsion containing toxic and hazardous ingredients from textile industry is one of the biggest concerns in this modern age. N-doped nano composites as an efficient catalyst are playing a significant role in reducing the toxicity of that textile effluent. N-doped Ti-Mel capped Ag2S NCs (N-Ti-C/Ag2S NCs) and N-doped TiO2 capped Ag2S NCs (TiO2/Ag2S NCs) were synthesized via calcinations at 700°C, whereas Ag2S NCs was prepared by simple hydrothermal treatment process at 120°C and confirmed by FTIR and SEM (EDX). N-Ti-C/Ag2S NCs were applied in presence of reducing agent NaBH4 with a green method to decolorize the textile dyes Levafix Amber RR (LA) and Remazol Blue RR (RB). Moreover, Ag2S NCs, TiO2/Ag2S NCs, NaBH4 and TiO2 were also investigated. Using UV-visible spectroscopy the progress time was measured to decolorize textile dye RB and completed within 3.15 mins, 12.15 mins, 12.15 mins for N-Ti-C/Ag2S NCs, Ag2S NCs and TiO2/Ag2S NCs respectively, while for LA the catalytic reduction taken for the same NCs was 8.15 mins, 12.15 mins and 30.15 mins respectively. N-Ti-C/Ag2S NCs based catalyst afforded excellent catalytic reduction activity in both cases. Interestingly the effect of NaBH4 itself and TiO2 in presence of NaBH4 was less than 5% after 30 mins. Finally, the reusability for Ti-Mel capped Ag2S NCs evaluated up to four cycles.

关键词： Catalytic Reduction N-Doped Nano-Composites Levafix Amber RR Remazol Blue RR

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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

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孟加拉国哈比卜集团中层管理者工作满意度研究

孟加拉国哈比卜集团中层管理者工作满意度研究

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作者：何穆（MOHAMMAD MAHMUDUL hasan sakib）贵州大学

学位级别：硕士

如今随着经济全球化的发展,国家间的竞争主要体现为科技程度的竞争和管理水平的竞争,这些竞争最终体现为人才的竞争。随着世界市场越来越透明,以人才为主导的各国竞争会进一步加剧,各个国家间也在不断的调整他们的抢夺人才政策和策略,... 详细信息

如今随着经济全球化的发展,国家间的竞争主要体现为科技程度的竞争和管理水平的竞争,这些竞争最终体现为人才的竞争。随着世界市场越来越透明,以人才为主导的各国竞争会进一步加剧,各个国家间也在不断的调整他们的抢夺人才政策和策略,面对如此严峻的的竞争环境,企业更应该思考如何留住的人才,特别是稀缺的中高层次人才。对工作满意度的研究由来已久,但现有研究涉及的深度和广度稍显欠缺,针对中高层管理者满意度的研究更显不足。作为一名孟加拉国留学生,在经过研究生学习生活之后,对企业管理有了更多的兴趣。因此本研究基于马斯洛需求理论和双因素理论形成概念和框架,并选择了五个员工比较关注的工作满意度的影响的因素:薪酬、企业文化、管理实践、组织信任和团队合作,以一手和二手数据为基础对孟加拉国哈比卜集团中层管理者的工作满意度进行研究。由于各个要素对于职工的表现和工作满意度影响程度的不同,本研究将围绕着哈比卜集团的中层管理者工作满意度近况,以及产生这些近况的原因,提出解决对策和保障措施进行研究。本文的研究的主要目的是为了探究影响哈比卜集团员工工作满意度的因素。在实证分析中主要调查了薪酬、企业文化、管理实践、组织信任、团队合作五个因素与工作满意度的关系,经过回归分析后,研究结果表明薪酬、组织文化对工作满意度的影响不明显,而管理实践、组织信任、团队合作能够显著影响工作满意度。本研究希望通过这项调查帮助哈比卜集团提高管理员工的效率,激发中层管理者的工作积极性和降低离职率提供一些参考。

关键词：工作满意度哈比卜集团因素分析影响因素中层管理者

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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

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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

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Advances in coamorphous drug delivery systems

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Acta Pharmaceutica Sinica B 2019年第1期9卷 19-35页

作者： Qin Shi sakib M.Moinuddin Ting Cai State Key Laboratory of Natural Medicines Department of Pharmaceutics School of Pharmacy China Pharmaceutical University

In recent years, the coamorphous drug delivery system has been established as a promising formulation approach for delivering poorly water-soluble drugs. The coamorphous solid is a single-phase system containing an active pharmaceutical ingredient(API) and other low molecular weight molecules that might be pharmacologically relevant APIs or excipients. These formulations exhibit considerable advantages over neat crystalline or amorphous material, including improved physical stability, dissolution profiles, and potentially enhanced therapeutic efficacy. This review provides a comprehensive overview of coamorphous drug delivery systems from the perspectives of preparation, physicochemical characteristics,physical stability, in vitro and in vivo performance. Furthermore, the challenges and strategies in developing robust coamorphous drug products of high quality and performance are briefly discussed.

关键词： Coamorphous Preparation Characterization Physical stability Dissolution Bioavailability

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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

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Reduction of chromium ore by recycled silicon cutting sludge waste with carbon addition

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Journal of Iron and Steel Research International 2019年第8期26卷 806-817页

作者： Woo-gwang Jung sakib Tanvir Hossain Fatima Tuz Johra Jong-ho Kim Young-chul Chang School of Materials Science and Engineering Kookmin University Seoul 02707 Korea Department of Materials Science and Engineering Graduate School of Kookmin University Seoul 02707 Korea Advanced Metals Research Group Research Institute of Industrial Science and Technology (RIST) Pohang City 37673 Korea Department of Mechatronics Engineering Korea University of Technology and Education Cheonan-si 31253 Korea

A basic study on the feasibility of producing ferrochrome (silicon) alloys using Si sludge waste collected from the silicon ingot cutting process was carried out, and the effects of the addition of carbon components, reaction time, and reaction temperature on the silicothermic reduction of chromium ore by Si sludge were studied. The cordierite (Mg2Al4Si5O18) phase was generated in the slag, and the Fe-Cr(-Si)-C alloy was formed by the silicothermic reduction. Moreover, the addition of carbon powder lowered the reduction initiating temperature, and the reduction ratio based on the oxygen content was evaluated at around 68-88% at 1573 K, which increased with an increase in carbon. However, it was difficult to find a significant difference in the reduction behavior in response to increasing the holding time. The reduced fer-rochrome (Fe-Cr) metal alloy droplets coalesced more intensively with an increase in reduction temperature, and for manufacturing the Fe-Cr alloy, it is estimated that a temperature of 1773 K or higher is required for good separation of the slag and the metal. Furthermore, the metallization ratio was defined, and higher values are evaluated for Fe than for Cr.

关键词： Chromium ore Ferrochrome alloy Silicon sludge waste Silicothermic reduction Reduction ratio Metallization ratio

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Comparative Study on Foreign Direct Investment Laws and Policies between Bangladesh and China with Prospects and Challenges

Comparative Study on Foreign Direct Investment Laws and Poli...

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作者： Omweo Al sakib 西北大学

学位级别：硕士

外国直接投资政策是一个有效的工具,可以帮助像孟加拉国这样的发展中国家,因为孟加拉国获得资本的机会有限,吸引更多的投资,发展一个有利于投资的制度和税收结构,提高国内劳动力的技术和管理能力,并帮助该国经济融入全球经济。外国直接...

外国直接投资政策是一个有效的工具,可以帮助像孟加拉国这样的发展中国家,因为孟加拉国获得资本的机会有限,吸引更多的投资,发展一个有利于投资的制度和税收结构,提高国内劳动力的技术和管理能力,并帮助该国经济融入全球经济。外国直接投资(FDI)对中国经济产生了有利影响,但也对中国的劳动力和中国成为全球经济巨头的能力产生了负面影响。除其他一些因素外,孟加拉国缺乏外国直接投资的主要原因是该国普遍存在的腐败和繁重的监管要求。事实上,近年来中国的对外投资政策更加优惠,中国的整体投资水平也有所提高。尽管如此,作为新冠病毒-19效应的直接影响,全世界的外国投资额仍大幅下降。然而,为了吸引更多的投资,孟加拉国应该向中国学习,制定良好的外国直接投资政策,欢迎更多的外国投资。与孟加拉国的外国直接投资政策相比,该政策要求对几乎所有经济部门进行重大调整。即使中国的许多外国直接投资法规已经被用作模板,该国仍需要对其在外国直接投资政策方面的做法进行一些调整。如果中国真的想增加其获得的外国直接投资(FDI),那么该国需要努力改善其投资记录、税收制度和资本转移规则。另一方面,为了加强政策制定,孟加拉国需要学习中国的外国直接投资政策、劳动力结构和动态出口规则。在本文中,我们将分析FDI法规以及两国之间可能通过投资政策建立的联系。在最后一节中,有一些要素可以调整,以增加两国接受的外国直接投资额。

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