Peoples’ Perception towards Telemedicine: A Case Study on Rural Area of Bangladesh

Telemedicine is a two-way, real time interactive session between the patient and the physician or practitioner at the remote location for the purpose of providing consultation. Telemedicine has enormous prospect to reduce health care service gap between rural area and urban area of Bangladesh. The aim of this paper is to demonstrate the peoples’ perception towards telemedicine and the factors influencing peoples’ perception in telemedicine. The chi-square analysis and descriptive statistics have been used as statistical tools to test the hypotheses. A self-administered questionnaire has been developed and snowball sampling method is used to collect data from the study area. In addition to the traditional health care system, urban specialist doctors provide medical consultation in rural area by telemedicine. The findings of this study have revealed that age, gender, educational qualification, trust, privacy and confidentiality, awareness, service quality, existing equipment status, proper coordination, treatment cost and IT infrastructure have significant influence on the perception of telemedicine. The findings and recommendations may be taken by policymakers to make effective decisions regarding telemedicine services. Keywords: Telemedicine, Urban area, Peoples’ perception, Bangladesh

The Impact of Sound Industrial Relations on Job Satisfaction: A Case of Different Manufacturing Industries in Bangladesh

Comparing to the enormous changes in the infrastructure and communication with the dramatic diversity at the workplace the norms, values and personal thinking of the workers have been changing drastically and the effect of those mental revolution influences at the workplace. As Bangladesh is a flourishing economy, the industrial sector faces different challenges at workplace. The focus of this study is to find out the current industrial relations practices and the relative job satisfaction at different manufacturing industrial sector in Bangladesh. The study is based on field survey where randomly selected twelve manufacturing industries in Barisal division through observing and talking with workers and managers information are collected through ninety seven respondents. It is found that for maintaining harmonious relationship at industrial premises twelve factors are much  influential such as Job security, work environment, healthy and safely measures, Fair practices of Labor court, Wages & monetary benefit, Grievance handling procedures, Industrial democracy, Participation in Decision making, training and development, structured conflict resolution procedures, strong collective bargaining agent, Existence of Trade union and have positive influences with job satisfaction. Through this study it is found that there is a positive relationship exists between sound industrial relations and job satisfaction and the study developed by using hypothesis with multiple regression models. Finally the research finished on the conclusion that workers job satisfaction is the result of sound industrial relations. Keywords: Industrial Relations, job Satisfaction, Manufacturing industrial sector, multiple regression mode

大規模チャネルアクセスを用いた超高信頼性および超低遅延通信

早大学位記番号:新8550早稲田大

Design and Hardware Implementation Considerations of Modified Multilevel Cascaded H-Bridge Inverter for Photovoltaic System

Inverters are an essential part in many applications including photovoltaic generation. With the increasing penetration of renewable energy sources, the drive for efficient inverters is gaining more and more momentum. In this paper, output power quality, power loss, implementation complexity, cost, and relative advantages of the popular cascaded multilevel H-bridge inverter and a modified version of it are explored. An optimal number of levels and the optimal switching frequency for such inverters are investigated, and a five-level architecture is chosen considering the trade-offs. This inverter is driven by level shifted in-phase disposition pulse width modulation technique to reduce harmonics, which is chosen through deliberate testing of other advanced disposition pulse width modulation techniques. To reduce the harmonics further, the application of filters is investigated, and an LC filter is applied which provided appreciable results. This system is tested in MATLAB/Simulink and then implemented in hardware after design and testing in Proteus ISIS. The general cascaded multilevel H-bridge inverter design is also implemented in hardware to demonstrate a novel low-cost MOSFET driver build for this study. The hardware setups use MOSFETs as switching devices and low-cost ATmega microcontrollers for generating the switching pulses via level shifted in-phase disposition pulse width modulation. This implementation substantiated the effectiveness of the proposed design

Computational Analysis of Thermal Adaptation in Extremophilic Chitinases: The Achilles' Heel in Protein Structure and Industrial Utilization.

peer reviewedUnderstanding protein stability is critical for the application of enzymes in biotechnological processes. The structural basis for the stability of thermally adapted chitinases has not yet been examined. In this study, the amino acid sequences and X-ray structures of psychrophilic, mesophilic, and hyperthermophilic chitinases were analyzed using computational and molecular dynamics (MD) simulation methods. From the findings, the key features associated with higher stability in mesophilic and thermophilic chitinases were fewer and/or shorter loops, oligomerization, and less flexible surface regions. No consistent trends were observed between stability and amino acid composition, structural features, or electrostatic interactions. Instead, unique elements affecting stability were identified in different chitinases. Notably, hyperthermostable chitinase had a much shorter surface loop compared to psychrophilic and mesophilic homologs, implying that the extended floppy surface region in cold-adapted and mesophilic chitinases may have acted as a "weak link" from where unfolding was initiated. MD simulations confirmed that the prevalence and flexibility of the loops adjacent to the active site were greater in low-temperature-adapted chitinases and may have led to the occlusion of the active site at higher temperatures compared to their thermostable homologs. Following this, loop "hot spots" for stabilizing and destabilizing mutations were also identified. This information is not only useful for the elucidation of the structure-stability relationship, but will be crucial for designing and engineering chitinases to have enhanced thermoactivity and to withstand harsh industrial processing conditions

QCovSML: A reliable COVID-19 detection system using CBC biomarkers by a stacking machine learning model

The reverse transcription-polymerase chain reaction (RT-PCR) test is considered the current gold standard for the detection of coronavirus disease (COVID-19), although it suffers from some shortcomings, namely comparatively longer turnaround time, higher false-negative rates around 20–25%, and higher cost equipment. Therefore, finding an efficient, robust, accurate, and widely available, and accessible alternative to RT-PCR for COVID-19 diagnosis is a matter of utmost importance. This study proposes a complete blood count (CBC) biomarkers-based COVID-19 detection system using a stacking machine learning (SML) model, which could be a fast and less expensive alternative. This study used seven different publicly available datasets, where the largest one consisting of fifteen CBC biomarkers collected from 1624 patients (52% COVID-19 positive) admitted at San Raphael Hospital, Italy from February to May 2020 was used to train and validate the proposed model. White blood cell count, monocytes (%), lymphocyte (%), and age parameters collected from the patients during hospital admission were found to be important biomarkers for COVID-19 disease prediction using five different feature selection techniques. Our stacking model produced the best performance with weighted precision, sensitivity, specificity, overall accuracy, and F1-score of 91.44%, 91.44%, 91.44%, 91.45%, and 91.45%, respectively. The stacking machine learning model improved the performance in comparison to other state-of-the-art machine learning classifiers. Finally, a nomogram-based scoring system (QCovSML) was constructed using this stacking approach to predict the COVID-19 patients. The cut-off value of the QCovSML system for classifying COVID-19 and Non-COVID patients was 4.8. Six datasets from three different countries were used to externally validate the proposed model to evaluate its generalizability and robustness. The nomogram demonstrated good calibration and discrimination with the area under the curve (AUC) of 0.961 for the internal cohort and average AUC of 0.967 for all external validation cohort, respectively. The external validation shows an average weighted precision, sensitivity, F1-score, specificity, and overall accuracy of 92.02%, 95.59%, 93.73%, 90.54%, and 93.34%, respectively

A Probabilistic Creep Constitutive Model for Creep Deformation, Damage, and Rupture

The structural analysis of Industrial Gas Turbine (IGT), Aeroengine, Gen IV nuclear components under in-service conditions at various stress and temperature are susceptible to time-dependent creep deformation and creep induced failure. Such failure phenomena are exacerbated by the randomness in material properties, oscillating loading conditions, and other sources of uncertainty. The demand for physically based probabilistic creep modeling is highly sought by alloy designers. The objective of this study is to develop and validate a probabilistic creep-damage model incorporating multi-sources of uncertainty to replace the traditional deterministic and empirical decision-based modeling. In this study, the deterministic Sine-hyperbolic (Sinh) creep-damage model is carefully tuned into a probabilistic model. The creep test data of alloy 304 stainless steel with replicates over a range of stress and temperature are gathered from the literature. First, the Sinh model is calibrated deterministically to determine the test-specific material constants and their associated statistical variability. A probabilistic framework is developed where the hypothesized sources of uncertainty: test conditions (stress and temperature), pre-existing damage, and material properties are introduced. The sources of uncertainties are carefully tuned based on the ASTM standards, statistical goodness-of-fit test, and the nature of deterministically calibrated constants. The probabilistic distribution function (pdfs) of each sources of uncertainty are determined in sequence to encapsulate the full experimental uncertainty. Single source probabilistic predictions are performed to determine the influence of each source of uncertainty on the creep deformation, damage, and rupture predictions. Full interaction probabilistic predictions are performed to demonstrate the interference effect of all the sources of uncertainty on the prediction of creep deformation, ductility, and rupture. The Sinh model constitutive equations are implemented into a USERCREEP.F, user material subroutine of the ANSYS finite element software. For verification and validation (V&V), a finite element simulation in ANSYS Mechanical APDL (ANSYS Parametric Design Language) is conducted on 1-D and 2-D element model. Furthermore, the probabilistic model is applied to an expanded database of engineering alloys to validate the probabilistic prediction. Future work will focus on developing a multi-stage Sinh, stochasticity, time-dependent pdfs for improved uncertainty quantification

Cluster-Based Transmission Diversity Optimization in Ultra Reliable Low Latency Communication

Intra-vehicular communication is an emerging technology explored spontaneously due to higher wireless sensor-based application demands. To meet the upcoming market demands, the current intra-vehicular communication transmission reliability and latency should be improved significantly to fit with the existing 5G and upcoming 6G communication domains. Ultra-Reliable Low-Latency Communication (URLLC) can be widely used to enhance the quality of communication and services of 5G and beyond. The 5G URLLC service is highly dependable for transmission reliability and minimizing data transmission latency. In this paper, a multiple-access scheme named Cluster-based Orthogonal Frequency Subcarrier-based Multiple Access (C-OFSMA) is proposed with 5G URLLC’s high requirement adaptation for intra-vehicular data transmission. The URLLC demanded high reliability of approximately 99.999% of the data transmission within the extremely short latency of less than 1 ms. C-OFSMA enhanced the transmission diversity, which secured more successful data transmission to fulfill these high requirements and adapt to such a network environment. In C-OFSMA, the available sensors transmit data over specific frequency channels where frequency selection is random and special sensors (audio and video) transmit data over dedicated frequency channels. The minimum number of subcarrier channels was evaluated for different arrival rates and different packet duplication conditions in order to achieve 99.999% reliability within an air-interface latency of 0.2 ms. For the fixed frequency channel condition, C-OFSMA and OFSMA were compared in terms of reliability response and other packet duplication. Moreover, the optimal number of clusters was also evaluated in the aspects of the reliability response for the C-OFSMA system