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| 1 | 基于激光跟踪仪的机身桶段测量技术研究显示文摘目前传统测量技术已难以满足飞机制造中不断提高的检测要求,数字化测量技术已成为提高飞机产品检测效率与质量的重要手段。针对这一发展趋势,通过基于激光跟踪仪的机身桶段测量技术研究,系统地总结了飞机产品测量中激光跟踪仪测量场的组成、建立飞机测量坐标系的方法以及激光跟踪仪转站的原理。结合某型飞机前机身桶段的测量过程,重点介绍了利用激光跟踪仪对机身桶段关键特性和关键对接点进行在线测量及数据分析的方法,分析验证了激光跟踪仪系统在飞机产品测量中的应用情况。 | 王巍 李昂 MD HELAL MIAH | 2017 | 装备制造技术2017，，12： | 4 |
| 2 | A comparative study on the effect of rice threshing methods on grain quality 显示文摘 | Md Abdual Kaddus Miah Roy B C Md Abdual Hafiz | 1994 | Agricultural Mechanization in Asia Af- rica and Latin America1994，25，3： | 1 |
| 3 | China's Non--Performing Bank Loan Crisis: The Role of Economic Rents 显示文摘 | Yasushi Suzuki Md Dulal Miah J inyi Yuan | 2008 | Asian-- Pacific Economic Literature2008，，1： | 1 |
| 4 | A comparative study on the effect of rice threshing methods on grain quality显示文摘 | Md Abduat Kaddus Miah Roy B C Md Abdual Hafiz | 1994 | Agricultural Mechanization in Asia Africa and Latin America1994，25，3： | 1 |
| 5 | A comparative study on the effect of rice threshing methods on grain quality显示文摘 | Md Abdual Kaddus Miah Roy B C Md Abdual Hafiz | 1994 | Agricultural Mechanization in Asia Africa and Latin America1994，25，3： | 1 |
| 6 | A comparative study on the effect office threshing methods on grain quality显示文摘 | Md Abdual Kaddus Miah Roy B C Md Abdual Hafiz | 1994 | Agricultural Mechanization in Asia Africa and Latin America1994，25，3： | 1 |
| 7 | Assessment of crop damage by wildlife in Chunati Wilklife Sanctuary显示文摘 | Miah MD Rehman ML Ahsan MF | 2001 | Balgladesh Tiger- paper2001，28，4： | 1 |
| 8 | Virtual Keyboard:A Real-Time Hand Gesture Recognition-Based Character Input System Using LSTM and Mediapipe Holistic显示文摘In the digital age,non-touch communication technologies are reshaping human-device interactions and raising security concerns.A major challenge in current technology is the misinterpretation of gestures by sensors and cameras,often caused by environmental factors.This issue has spurred the need for advanced data processing methods to achieve more accurate gesture recognition and predictions.Our study presents a novel virtual keyboard allowing character input via distinct hand gestures,focusing on two key aspects:hand gesture recognition and character input mechanisms.We developed a novel model with LSTM and fully connected layers for enhanced sequential data processing and hand gesture recognition.We also integrated CNN,max-pooling,and dropout layers for improved spatial feature extraction.This model architecture processes both temporal and spatial aspects of hand gestures,using LSTM to extract complex patterns from frame sequences for a comprehensive understanding of input data.Our unique dataset,essential for training the model,includes 1,662 landmarks from dynamic hand gestures,33 postures,and 468 face landmarks,all captured in real-time using advanced pose estimation.The model demonstrated high accuracy,achieving 98.52%in hand gesture recognition and over 97%in character input across different scenarios.Its excellent performance in real-time testing underlines its practicality and effectiveness,marking a significant advancement in enhancing human-device interactions in the digital age. | Bijon Mallik Md Abdur Rahim Abu Saleh Musa Miah Keun Soo Yun Jungpil Shin | 2024 | Computer Systems Science & Engineering2024，48，2： | 0 |
| 9 | Quality of life of COVID-19 recovered patients:a 1-year follow-up study from Bangladesh显示文摘BackgroundThe COVID-19 pandemic posed a danger to global public health because of the unprecedented physical,mental,social,and environmental impact affecting quality of life(QoL).The study aimed to find the changes in QoL among COVID-19 recovered individuals and explore the determinants of change more than 1 year after recovery in low-resource settings.MethodsCOVID-19 patients from all eight divisions of Bangladesh who were confirmed positive by reverse transcription-polymerase chain reaction from June 2020 to November 2020 and who subsequently recovered were followed up twice,once immediately after recovery and again 1 year after the first follow-up.The follow-up study was conducted from November 2021 to January 2022 among 2438 individuals using the World Health Organization Quality of Life Brief Version(WHOQOL-BREF).After excluding 48 deaths,95 were rejected to participate,618 were inaccessible,and there were 45 cases of incomplete data.Descriptive statistics,paired-sample analyses,generalized estimating equation(GEE)analysis,and multivariable logistic regression analyses were performed to test the mean difference in participants’QoL scores between the two interviews.ResultsMost participants(n=1710,70.1%)were male,and one-fourth(24.4%)were older than 46.The average physical domain score decreased significantly from baseline to follow-up,and the average scores in psychological,social,and environmental domains increased significantly at follow-up(P<0.05).By the GEE equation approach,after adjusting for other factors,we found that older age groups(P<0.001),being female(P<0.001),having hospital admission during COVID-19 illness(P<0.001),and having three or more chronic diseases(P<0.001),were significantly associated with lower physical and psychological QoL scores.Higher age and female sex[adjusted odd ratio(aOR)=1.3,95%confidence interval(CI)1.0–1.6]were associated with reduced social domain scores on multivariable logistic regression analysis.Urban or semi-urban people were 49%less likely(aOR=0.5,95%CI 0.4–0.7)and 32%less likely(aOR=0.7,95%CI 0.5–0.9)to have a reduced QoL score in the psychological domain and the social domain respectively,than rural people.Higher-income people were more likely to experience a decrease in QoL scores in physical,psychological,social,and environmental domains.Married people were 1.8 times more likely(aOR=1.8,95%CI 1.3–2.4)to have a decreased social QoL score.In the second interview,people admitted to hospitals during their COVID-19 infection showed a 1.3 times higher chance(aOR=1.3,95%CI 1.1–1.6)of a decreased environmental QoL score.Almost 13%of participants developed one or more chronic diseases between the first and second interviews.Moreover,7.9%suffered from reinfection by COVID-19 during this 1-year time.ConclusionsThe present study found that the QoL of COVID-19 recovered people improved 1 year after recovery,particularly in psychological,social,and environmental domains.However,age,sex,the severity of COVID-19,smoking habits,and comorbidities were significantly negatively associated with QoL.Events of reinfection and the emergence of chronic disease were independent determinants of the decline in QoL scores in psychological,social,and physical domains,respectively.Strong policies to prevent and minimize smoking must be implemented in Bangladesh,and we must monitor and manage chronic diseases in people who have recovered from COVID-19. | Mohammad Delwer Hossain Hawlader Md Utba Rashid Md Abdullah Saeed Khan Mowshomi Mannan Liza Sharmin Akter Mohammad Ali Hossain Tajrin Rahman Sabrina Yesmin Barsha Alberi Afifa Shifat Mosharop Hossian Tahmina Zerin Mishu Soumik Kha Sagar Ridwana Maher Manna Nawshin Ahmed Sree Shib Shankar Devnath Debu Irin Chowdhury Samanta Sabed Mashrur Ahmed Sabrina Afroz Borsha Faraz Al Zafar Sabiha Hyder Abdullah Enam Habiba Babul Naima Nur Miah Md.Akiful Haque Shopnil Roy K.M.Tanvir Hassan Mohammad Lutfor Rahman Mohammad Hayatun Nabi Koustuv Dalal | 2023 | Infectious Diseases of Poverty2023，12，4： | 0 |
| 10 | Rotation,Translation and Scale Invariant Sign Word Recognition Using Deep Learning显示文摘Communication between people with disabilities and people who do not understand sign language is a growing social need and can be a tedious task.One of the main functions of sign language is to communicate with each other through hand gestures.Recognition of hand gestures has become an important challenge for the recognition of sign language.There are many existing models that can produce a good accuracy,but if the model test with rotated or translated images,they may face some difficulties to make good performance accuracy.To resolve these challenges of hand gesture recognition,we proposed a Rotation,Translation and Scale-invariant sign word recognition system using a convolu-tional neural network(CNN).We have followed three steps in our work:rotated,translated and scaled(RTS)version dataset generation,gesture segmentation,and sign word classification.Firstly,we have enlarged a benchmark dataset of 20 sign words by making different amounts of Rotation,Translation and Scale of the ori-ginal images to create the RTS version dataset.Then we have applied the gesture segmentation technique.The segmentation consists of three levels,i)Otsu Thresholding with YCbCr,ii)Morphological analysis:dilation through opening morphology and iii)Watershed algorithm.Finally,our designed CNN model has been trained to classify the hand gesture as well as the sign word.Our model has been evaluated using the twenty sign word dataset,five sign word dataset and the RTS version of these datasets.We achieved 99.30%accuracy from the twenty sign word dataset evaluation,99.10%accuracy from the RTS version of the twenty sign word evolution,100%accuracy from thefive sign word dataset evaluation,and 98.00%accuracy from the RTS versionfive sign word dataset evolution.Furthermore,the influence of our model exists in competitive results with state-of-the-art methods in sign word recognition. | Abu Saleh Musa Miah Jungpil Shin Md.Al Mehedi Hasan Md Abdur Rahim Yuichi Okuyama | 2023 | Computer Systems Science & Engineering2023，44，3： | 0 |
| 11 | Processed Radio Frequency towards Pancreas Enhancing the Deadly Diabetes Worldwide显示文摘Diabetes is a chronic and debilitating disease,which is associated with a range of complications putting tremendous burden on medical,economic and socio-technological infrastructure globally.Yet the higher authorities of health services are facing the excruciating cumulative reasons of diabetes as a very imperative worldwide issue in the 21st century.The study aims to relook at the misapplication of the processed radio frequency that frailties in the pancreas within and around the personal body boundary area.The administered sensor data were obtained at laboratory experiments from the selected specimens on dogs and cats in light and dark environments.The study shows the frequent urine flow speed varies with sudden infection due to treated wireless sensor networks in active open eyes.The overweight and obese persons are increasingly affected in diabetes with comprehensive urinary pressure due to continuous staying at dark environment.The findings replicate the increasing tide of diabetes globally.The study also represents the difficulties of physicians to provide adequate diabetic management according to their expectancy due to insecure personal area network control unit.Dynamic sensor network is indispensable for healthcare but such network is at risk to health security due to digitalized poisoning within GPS positions.The study recommends the anti-radiation integrated system policy with user’s security alternative approach to inspire dealing with National Health Policy and Sustainable Development Goals 2030. | Md.Rahimullah Miah Mohammad Abdul Hannan AAM Shazzadur Rahman Md.Shahariar Khan Md Mokbul Hossain Ishrat Tasnim Rahman Md.Sabbir Hossain Chowdhury Shadman Shahriar Mohammad Basir Uddin Mohammad Taimur Hossain Talukdar Mohammad Shamsul Alam S.A.M.Imran Hossain Alamgir Adil Samdany Shahriar Hussain Chowdhury Alexander Kiew Sayok | 2021 | Journal of Endocrinology Research2021，3，1： | 0 |
| 12 | Technical Analysis of Security Management in Terms of Crowd Energy and Smart Living显示文摘In this paper, a technical and statistical analysis of security system and security management is provided for crowd energy and smart living. At the same time, a clear understanding is made for crowd energy concept and next generation smart living. Various case examples have been studied and a brief summary has been provided.Furthermore, a statistical analysis has been provided in terms of security management in smart living where it is found that young technocrats give the highest importance to security management in smart living. Last but not the least, current limitation, constraints, and future scope of security implementation have been discussed in terms of crowd energy clustered with next generation smart living. | MD Shahrukh Adnan Khan Muhammad Ahad Rahman Miah Shaikh Rashedur Rahman Mirza Mursalin Iqbal Aseef Iqbal Aravind CV Chua Kein Huat | 2018 | Journal of Electronic Science and Technology2018，16，4： | 0 |
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