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The present world is badly affected by the novel coronavirus (COVID-19). Using medical kits to identify coronavirus-affected persons is very slow. What happens in the next, nobody knows. The world is facing an erratic problem and doesn't know what will happen in near future. This paper is trying to make a prognosis of the coronavirus recovery cases using LSTM(Long Short Term Memory). This work exploited data from 258 regions, their latitude and longitude, and the number of death in 403 days ranging from 22-01-2020 to 27-02-2021. Specifically, advanced deep learning-based algorithms known as the LSTM, play a great effect in extracting highly essential features for time series data (TSD) analysis. There are lots of methods which already use to analyze propagation prediction. The main task of this paper culminates in analyzing the spreading of Coronavirus across worldwide recovery cases using LSTM deep learning-based architectures.

In recent years, quantum image processing got a lot of attention in the field of image processing due to the opportunity to place huge image data in quantum Hilbert space. Hilbert space or Euclidean space has infinite dimensions to locate and process the image data faster. Moreover, several types of research show that the computational time of the quantum process is faster than classical computers. Encoding and compressing the image in the quantum domain is still a challenging issue. From the literature survey, we have proposed a DCT-EFRQI (Direct Cosine Transform Efficient Flexible Representation of Quantum Image) algorithm to represent and compress gray image efficiently which save computational time and minimize the complexity of preparation. This work aims to represent and compress various gray image sizes in quantum computers using the DCT (Discrete Cosine Transform) and EFRQI (Efficient Flexible Representation of Quantum Image) approaches together. The Quirk simulation tool is used to design the corresponding quantum image circuit. Due to the limitation of qubits, a total of 16 numbers of qubits is used to represent the coefficient and its position of the grayscale image. Among those, 8 number of qubits are used to map the coefficient values and the rest are used to generate the corresponding coefficient XY-coordinate position. Theoretical analysis and experimental results show that the proposed DCT-EFRQI scheme provides better representation and compression compared to DCT-GQIR, DWT-GQIR, and DWT-EFRQI in terms of PSNR(Peak Signal to Noise Ratio), and bit rate.

The inference procedure under generalized linear model breaks down when there exists too many zeros in count data that the parent distribution cannot accommodate. We argue that the process of separ...

Background: Hypertension is a major non-communicable disease all over the world. This study determines the role of occupation along with other potential covariates on hypertension for Bangladeshi women.Methods: The analysis had been used the data from Bangladesh demographic and health survey 2017-18. Univariate and bivariate analyses were performed to check patterns and correlates of hypertension. To explore the influence of demographic, socioeconomic, and biological factors affecting hypertension, binary logistic regression models were used.Results: The prevalence of hypertension among non-working women was 30.31%. The role of occupation on hypertension was significant in both the unadjusted and adjusted models. Women who were not working during the survey were 1.176 times more likely to have hypertension than physically working women while controlling for other variables. In Bangladesh, after controlling the effect of occupation other significant risk factors for hypertension were age, BMI, marital status, education, and region.Conclusion: Occupation is an essential subject for our life and livelihood. Since physically active women were less likely to be hypertensive than non-working women, occupation could be utilized as a significant tool to prevent hypertension.

The laminar forced convection of fluids flow inside a non-circular duct has been investigated both experimentally and numerically by numerous researchers. These studies mainly focused on exploring the characteristics of nanofluid flow and duct shape to increase the heat transfer coefficient and decrease the pressure drop using various nanoparticle concentration. However, there still exists many challenges which need to be resolved to find out perfect nanofluid and suitable duct shape. This paper summarizes most of the laminar forced convective heat transfer literatures concentrated on the flow inside non-circular ducts in order to identify the challenges and propose the targeted solutions of these problems to improve the overall heat transfer efficiency. This research also analyzed the several parameters such as types of nanoparticles, particle size, host fluid, particle volume concentration, various thermal and hydrodynamic effects characteristics of laminar convective heat transfer with nanofluids. In addition, the paper also offers details on the most widely used correlations used to predict the efficient thermophysical properties of nanofluids.

The electrical energy demand of the Kingdom of Saudi Arabia (KSA) has been observing a surging growth due to high population growth and urbanization rate. The generation mostly comes from the burning of petroleum products. The electricity sector emits more than one-third of the national greenhouse gas (GHG) of the country. Thus, it is essential to reduce the GHG from the electricity generation sector to maintain sustainability. This article mainly concentrates on the existing electricity generation and focuses on the Kingdom’s GHG emissions mitigation initiatives. Although the use of natural gas and the number of cogeneration plants have been increased in electricity generation, the country has also been focusing on other initiatives, including the adaptation of combined cycle power plants, carbon capture, utilization, and sequestration (CCUS), renewable and alternative energy sources, and various utility-scale energy efficiency measures. The ambitious and inspirational renewable energy (RE) targets of the Saudi Vision 2030 will significantly facilitate GHG emission avoidance, which will support the Kingdom to meet its Nationally Determined Contributions. This article recommends various mitigation measures, including the usage of the efficient internal combustion engine, poly-generation, combined heat and power (CHP) systems, deployment of renewable resources in the distribution and microgrid systems, bio-mass engine, and ocean thermal energy conversion plants. The decision-makers and the researchers will find the discussions and recommendations helpful in determining suitable and appropriate mitigation initiatives and technologies.

Soil organic carbon (SOC) is a key soil quality indicator, as it is a source and storage of plant nutrients and plays a vital role in soil fertility and productivity maintenance. Intensification of agriculture is known to cause SOC decline; however, much of the evidence stems from field-scale experimental trials. The primary aim of this study is to investigate how more than 20 years of agricultural land use intensification in Bangladesh has influenced SOC levels at landscape levels. This was achieved by revisiting in 2012 four sub-sites from the Brahmaputra and Ganges alluviums which were previously sampled (1989–92) by the Soil Resource Development Institute and collecting 190 new samples. These were located at different elevations and subjected to differing amounts of inundation. The SOC was determined using the same method, potassium dichromate wet oxidation, used in the 1989-92 campaign. A comparison of the SOC in the 2012 samples with their historic levels (1989–92) revealed that overall SOC declined significantly across both alluviums as well at their four sub-sites. Further analysis, however, showed that SOC has declined more at higher sites. The higher sites are inundated to a limited level, which makes them suitable for growing multiple crops. Among the land types considered here, the low land sites (because of their topographical position) remain inundated for a greater part of the year, allowing a maximum of only one crop of submerged rice. As a result of reduced biomass decomposition due to anaerobic conditions when inundated, and lower land use/cropping intensity, SOC accretion has occurred in the lower land sites.\ud The SOC levels in South Asian countries are inherently low and agricultural land use intensification fuelled by growing food production demand is causing further SOC loss, which has the potential to jeopardise food security and increase the environmental impact of agriculture.

Background Unmet need for family planning (FP) is a core concept in designing FP programmes and reduction of unmet need for FP can improve reproductive and maternal health services. Bangladesh is still away from achieving the target regarding unmet need for FP. This study aimed to explore the composite effect of economic status and place of residence on unmet need for FP among currently married women of reproductive age in Bangladesh after controlling the effect of other selected covariates. Methods The study used the data extracted from the Bangladesh Demographic and Health Survey (BDHS) 2017–2018, which is a nationally representative survey implemented using a stratified two-stage cluster sample design. A total of 13,031 currently married women of reproductive age were included in the final analysis. Binary logistic regression model has been employed to identify the factors influencing the unmet need for FP. Model-I investigated the effect of composite variable place-wealth on unmet need for FP and Model-II examined the effect of place-wealth on unmet need for FP after adjusting for the effect of other selected covariates. The Odds Ratios with p-values were reported to identify significant covariates. Results The rate of unmet need for FP was 15.48%. The composite factor of economic status and place of residence had significant influence on unmet need for FP in both models. Generally, rural women were significantly more likely to have unmet need for FP than their urban counterparts. In particular, women from rural areas and belong to rich families had the highest likelihoods of unmet need for FP. The other selected covariates also had significant influence on unmet need for FP. Conclusion This study shows that rural women had higher odds of unmet need for FP than urban women. The healthcare providers and stakeholders should take necessary actions to motivate women to use contraceptive specially the women who are residing in the rural areas.

Radiation recall is characterized by an acute inflammatory reaction confined to previously irradiated areas that is triggered by the administration of precipitating systemic agents after radiation treatment. The most common responsible drugs are anticancer agents, but other drugs can also cause radiation recall including some antibiotics, antitubercular drugs, simvastatin can also cause radiation recall phenomenon. We report a case of paclitaxel induced radiation recall injury in a 57 year old male with carcinoma left lung with brain metastases. KYAMC Journal Vol. 11, No.-3, October 2020, Page 158-160

Background: Blood group is one of the major genetic risk factors for developing different types of malignancy throughout the world. Objectives: To find out the susceptible blood group in ABO and Rhesus systems in patients with malignancy. Methods and Materials: This study was one at KYAMCH cancer center, Enayetpur, Sirajganj, from October 2018 to February 2019. Total 150 cancer patients attending OPD were included irrespective of age, sex, socioeconomic status. ABO and Rhesus blood groups were determined in laboratory by standard methods. Results: Among 150 patients, 55% were female and 45% were male. Malignancy was predominant in the age group of41-50 years (25.3%) and 33.33% patients were found to have O blood group. Out of the patients, 98.7% had Rh positive of all blood groups of which 32% was belonged to blood group O. Metastasis was found among 34.66% patients and out of this 14.67% were having O blood group. Among 22 metastatic O blood group patients, 90.9% was Rh positive and 9.09% was Rh negative. Conclusion: Various types of malignancy are common among O positive blood group. KYAMC Journal Vol. 10, No.-3, October 2019, Page 133-136

The grid integration of microgrids and the selection of energy management systems (EMS) based on robustness and energy efficiency in terms of generation, storage, and distribution are becoming more challenging with rising electrical power demand. The problems regarding exploring renewable energy resources with efficient and durable energy storage systems demand side management and sustainable solutions to microgrid development to maintain the power system’s stability and security. This article mainly focuses on the overview of the recent developments of microgrid EMS within the control strategies and the implementation challenges of the microgrid. First, it provides energy management strategies for the major microgrid components, including load, generation, and energy storage systems. Then, it presents the different optimization approaches employed for microgrid energy management, such as classical, metaheuristic, and artificial intelligence. Moreover, this article sheds light on the major implementation challenges of microgrids. Overall, this article provides interactive guidelines for researchers to assist them in deciding on their future research.

Background There exists a lack of research in explaining the link between dropout from school and antenatal care (ANC) visits of women during pregnancy in Bangladesh. The aim of this study is to investigate how the drop out from school influences the ANC visits after controlling the relevant covariates using an appropriate count regression model. Methods The association between the explanatory variables and the outcome of interest, ANC visits, have been performed using one-way analysis of variance/independent sample t-test. To examine the adjusted effects of covariates on the marginal mean of count data, Marginalized Poison-Poisson mixture regression model has been fitted. Results The estimated incidence rate of antenatal care visits was 10.6% lower for the mothers who were not continued their education after marriage but had at least 10 years of schooling (p-value p-value Conclusions To ensure the WHO recommended 8+ ANC visits for the pregnant women of Bangladesh, it is essential to promote maternal education so that at least ten years of schooling should be completed by a woman and dropout from school after marriage should be prevented.

The equivalent electric circuit models reflect the electrical characteristics of the photovoltaic (PV) modules. Estimation of PV module parameters is considered as one of the challenging tasks while evaluating the performance. This article presents a new and useful approach to estimate the five-parameter PV module electrical circuit model. It translates the PV module parameter estimation process into an optimization problem using the information provided by the manufacturer on the rear side of the PV modules. It then employs an efficient metaheuristic technique, namely the backtracking search algorithm, to solve the developed optimization problem. The efficacy of the proposed approach is investigated by predicting the parameters of three PV module technologies: monocrystalline, poly-crystalline, and thin film. Finally, to check the feasibility of the proposed technique, this paper compares the approximate parameters of modeled I-V curves with experimental curves. The findings confirm the reliability of the estimated model parameters in simulating the near realistic characteristics of the PV modules.

This paper proposes an intelligent approach to detect and classify the power quality (PQ) events with the combination of machine learning and advanced signal processing techniques. It selects Stockwell transform, one of the efficient signal processing tools for feature extraction from the recorded signals. The extracted features are then fetched to one of the popular machine-learning tools, namely the artificial neural network (ANN), to develop the proposed intelligent PQ events detection and classification approach. This paper selects the hyper-parameters, e.g., number of hidden layer neurons, training algorithm, and activation functions through a systematic trial and error approach. To enhance the proposed approach performance, the weights and biases of the ANN are optimized using the grey wolf optimization (GWO) technique. Simulation results confirm the efficacy of the developed intelligent methodology in distinguishing PQ events from non-PQ events. Moreover, separates different PQ events, e.g., sag, swell, interruption, fluctuation, spike, notch, harmonics, from each other with reasonable accuracy. This research also investigates the efficacy of the proposed signal processing-based machine learning approach in the presence of measurement noises.

Malnutrition is the burning question all over the world’s public health. Bangladesh is one of those countries where level of malnutrition of infant and child is very serious and many problems that results from malnutrition in Bangladesh. The aim of this study is to substantiate whether there exists any influence of parents’ education for child nutrition as well as to find out the potential effects of non-parental household member’s literacy level on child malnutrition. In this study we have found that parents’ education is an important factor for child nutrition. Also other household members’ education has significant impact on stunting (height for age) and underweight (weight for age). The results of this study focus the policies that encourage participation in schools and higher education program as well as improve economic condition of the households to dilute child malnutrition in Bangladesh. Dhaka Univ. J. Sci. 66(1): 1-7, 2018 (January)

Power plant systems are particularly valuable to the country as well to the society development breaches due to the highly require related to every person life through the use of power in the various form. With the growing interest of the Internet of Thing (IoT), optimal placement of sensor in the area of large scale is a big issue to save node energy thereafter enhancing network lifetime. One of the main reasons to consume the network energy drastically by activating all the participate nodes unnecessary due to lack of energy making policy. The simulation data was collected through internet and extensive work has done based on maintenance and construction protocol. Gaussian node energy distribution model was proposed for monitoring plant. For result analysis two types of performance matrices were measured data.

A comparative study was conducted to replace the traditional screening method (MFDS#83) with the Quick, Easy, Cheap, Effective, Rugged and Safe (QuEChERS) EN method for the determination of 267 pesticides/metabolites/plant activators/growth regulators in five representative crop matrices (mandarin, pepper, potato, rice, and soybean). In the traditional method, samples were extracted with acetonitrile and salt, and purified with a solid-phase extraction cartridge. In the QuEChERS method, the sample extraction was carried out using acetonitrile and a mixture of salts, and purification was performed using dispersive solid phase extraction. The limit of quantification (LOQ) for the MFDS#83 method was 0.0004 mg/kg, whereas for the QuEChERS EN method, the LOQ varied from 0.002 to 0.006 mg/kg for all analytes in various matrices. A six-point matrix-matched calibration curve was prepared for all analytes in five matrices for both methods. Both the MFDS#83 and QuEChERS EN methods provided excellent linearity, with the coefficients of determination (R2) ≥ 0.99 for most of the compounds. In both cases, the method was validated in terms of recovery and repeatability after the fortification of two different concentrations with three replicates for each of the concentrations. The QuEChERS EN method provided better recovery than the MFDS#83 method for all matrices except mandarin.