Displaying all 19 publications

  1. Alam MM, Wei H, Wahid ANM
    Aust Econ Pap, 2020 Nov 27.
    PMID: 33349733 DOI: 10.1111/1467-8454.12215
    The outbreak of COVID-19 has weakened the economy of Australia and its capital market since early 2020. The overall stock market has declined. However, some sectors become highly vulnerable while others continue to perform well even in the crisis period. Given this new reality, we seek to investigate the initial volatility and the sectoral return. In this study, we analyse data for eight sectors such as, transportation, pharmaceuticals, healthcare, energy, food, real estate, telecommunications and technology of the Australian stock market. In doing so, we obtain data from Australian Securities Exchange (ASX) and analysed them based on 'Event Study' method. Here, we use the 10-days window for the event of official announcement of the COVID-19 outbreak in Australia on 27 February 2020. The findings of the study show that on the day of announcement, the indices for food, pharmaceuticals and healthcare exhibit impressive positive returns. Following the announcement, the telecommunications, pharmaceuticals and healthcare sectors exhibit good performance, while poor performance is demonstrated by the transportation industry. The findings are vital for investors, market participants, companies, private and public policymakers and governments to develop recovery action plans for vulnerable sectors and enable investors to regain their confidence to make better investment decisions.
  2. Umar B, Alam MM, Al-Amin AQ
    Environ Sci Pollut Res Int, 2021 Jan;28(2):1973-1982.
    PMID: 32862348 DOI: 10.1007/s11356-020-10641-2
    The increasing level of greenhouse gas carbon emission currently exacerbates the devastating effect of global warming on the Earth's ecosystem. Energy usage is one of the most important determinants that is increasing the amount of carbon gases being released. Simultaneously, the level of energy usage is derived by the price, and therefore, this study examines the contribution of energy price to carbon gas emissions in thirteen African nations for the period spanning 1990 to 2017. It does this by utilising the cross-sectional dependence (CD), augmented mean group (AMG) and pooled mean group (PMG) panel modelling methods. The findings of the AMG model suggest that a 1% increase in energy price leads to a 0.02% decrease in carbon emission. The results further reveal that a 1% increase in energy intensity and technological innovation leads to 0.04% and 3.65% increase in carbon emission, respectively, in the selected African countries. Findings will help policymakers to implement effective energy price policies to reduce carbon emissions and achieve sustainable development goals especially in the emerging economies of Africa.
  3. Wahaj Z, Alam MM, Al-Amin AQ
    Environ Sci Pollut Res Int, 2022 Mar;29(11):16739-16748.
    PMID: 34989992 DOI: 10.1007/s11356-021-18402-5
    Pandemics leave their mark quickly. This is true for all pandemics, including COVID-19. Its multifarious presence has wreaked havoc on people's physical, economic, and social life since late 2019. Despite the need for social science to save lives, it is also critical to ensure future generations are protected. COVID-19 appeared as the world grappled with the epidemic of climate change. This study suggests policymakers and practitioners address climate change and COVID-19 together. This article offers a narrative review of both pandemics' impacts. Scopus and Web of Science were sought databases. The findings are reported analytically using important works of contemporary social theorists. The analysis focuses on three interconnected themes: technology advancements have harmed vulnerable people; pandemics have macro- and micro-dimensions; and structural disparities. To conclude, we believe that collaborative effort is the key to combating COVID-19 and climate change, while understanding the lessons learnt from the industrialised world. Finally, policymakers can decrease the impact of global catastrophes by addressing many socioeconomic concerns concurrently.
  4. Aktar MA, Alam MM, Harun M
    PMID: 35028847 DOI: 10.1007/s11356-021-18257-w
    Reduced electricity demand through the implementation of an energy efficiency policy is a central pillar of the Malaysian government's energy strategy. Energy efficiency first emerged as part of Malaysia's energy policy agenda in 1979 but only came into force during the 2000s. Initially, it was seen from global fears about the shortage of fossil fuels, then as a way of combating climate change. This paper offers a comprehensive review of Malaysia's energy policies with a focus on adopting policies to improve energy efficiency. Starting with Malaysia's preliminary policy in response to the OPEC-driven global oil crisis in 1973, the paper discusses how policymakers are considering energy efficiency from Malaysia's sustainable development perspective and what relevant government efforts have been made to improve it. The review evaluates the progress that has been made over the past 25 years to address energy efficiency in the economy and highlights the achievements and remaining difficulties. Findings show that the level of energy efficiency while having shown improvement during 1990-2015 was lower than expected. In terms of electricity intensity of GDP, Malaysia has a relatively large position among the ASEAN countries and the world's largest electricity consumers. Researchers, scientists, and practitioners will benefit from the extensive review material of this study, which will help them better understand energy efficiency and the sustainability strategy implemented in Malaysia to date.
  5. Waheed M, Ahmad R, Ahmed W, Drieberg M, Alam MM
    Sensors (Basel), 2018 Feb 13;18(2).
    PMID: 29438278 DOI: 10.3390/s18020565
    The fabrication of lightweight, ultra-thin, low power and intelligent body-borne sensors leads to novel advances in wireless body area networks (WBANs). Depending on the placement of the nodes, it is characterized as in/on body WBAN; thus, the channel is largely affected by body posture, clothing, muscle movement, body temperature and climatic conditions. The energy resources are limited and it is not feasible to replace the sensor's battery frequently. In order to keep the sensor in working condition, the channel resources should be reserved. The lifetime of the sensor is very crucial and it highly depends on transmission among sensor nodes and energy consumption. The reliability and energy efficiency in WBAN applications play a vital role. In this paper, the analytical expressions for energy efficiency (EE) and packet error rate (PER) are formulated for two-way relay cooperative communication. The results depict better reliability and efficiency compared to direct and one-way relay communication. The effective performance range of direct vs. cooperative communication is separated by a threshold distance. Based on EE calculations, an optimal packet size is observed that provides maximum efficiency over a certain link length. A smart and energy efficient system is articulated that utilizes all three communication modes, namely direct, one-way relay and two-way relay, as the direct link performs better for a certain range, but the cooperative communication gives better results for increased distance in terms of EE. The efficacy of the proposed hybrid scheme is also demonstrated over a practical quasi-static channel. Furthermore, link length extension and diversity is achieved by joint network-channel (JNC) coding the cooperative link.
  6. Aktar MA, Alam MM, Al-Amin AQ
    Sustain Prod Consum, 2021 Apr;26:770-781.
    PMID: 33786357 DOI: 10.1016/j.spc.2020.12.029
    The COVID-19 pandemic has emerged as one of the deadliest infectious diseases on the planet. Millions of people and businesses have been placed in lockdown where the main aim is to stop the spread of the virus. As an extreme phenomenon, the lockdown has triggered a global economic shock at an alarming pace, conveying sharp recessions for many countries. In the meantime, the lockdowns caused by the COVID-19 pandemic have drastically changed energy consumption patterns and reduced CO2 emissions throughout the world. Recent data released by the International Monetary Fund and International Energy Agency for 2020 further forecast that emissions will rebound in 2021. Still, the full impact of COVID-19 in terms of how long the crisis will be and how the consumption pattern of energy and the associated levels of CO2 emissions will be affected are unclear. This review aims to steer policymakers and governments of nations toward a better direction by providing a broad and convincing overview on the observed and likely impacts of the pandemic of COVID-19 on the world economy, world energy demand, and world energy-related CO2 emissions that may well emerge in the next few years. Indeed, given that immediate policy responses are required with equal urgency to address three things-pandemic, economic downturn, and climate crisis. This study outlines policy suggestions that can be used during these uncertain times as a guide.
  7. Ayoub Kamal M, Alam MM, Sajak AAB, Mohd Su'ud M
    Comput Intell Neurosci, 2023;2023:5183062.
    PMID: 36654727 DOI: 10.1155/2023/5183062
    LoRa is an ISM-band based LPWAN communication protocol. Despite their wide network penetration of approximately 20 kilometers or higher using lower than 14 decibels transmitting power, it has been extensively documented and used in academia and industry. Although LoRa connectivity defines a public platform and enables users to create independent low-power wireless connections while relying on external architecture, it has gained considerable interest from scholars and the market. The two fundamental components of this platform are LoRaWAN and LoRa PHY. The consumer LoRaWAN component of the technology describes the network model, connectivity procedures, ability to operate the frequency range, and the types of interlinked gadgets. In contrast, the LoRa PHY component is patentable and provides information on the modulation strategy which is being utilized and its attributes. There are now several LoRa platforms available. To create usable LoRa systems, there are presently several technical difficulties to be overcome, such as connection management, allocation of resources, consistent communications, and security. This study presents a thorough overview of LoRa networking, covering the technological difficulties in setting up LoRa infrastructures and current solutions. Several outstanding challenges of LoRa communication are presented depending on our thorough research of the available solutions. The research report aims to stimulate additional research toward enhancing the LoRa Network capacity and allowing more realistic installations.
  8. Khan MN, Islam MM, Shariff AA, Alam MM, Rahman MM
    PLoS One, 2017;12(5):e0177579.
    PMID: 28493956 DOI: 10.1371/journal.pone.0177579
    BACKGROUND: Globally the rates of caesarean section (CS) have steadily increased in recent decades. This rise is not fully accounted for by increases in clinical factors which indicate the need for CS. We investigated the socio-demographic predictors of CS and the average annual rates of CS in Bangladesh between 2004 and 2014.

    METHODS: Data were derived from four waves of nationally representative Bangladesh Demographic and Health Survey (BDHS) conducted between 2004 and 2014. Rate of change analysis was used to calculate the average annual rate of increase in CS from 2004 to 2014, by socio-demographic categories. Multi-level logistic regression was used to identify the socio-demographic predictors of CS in a cross-sectional analysis of the 2014 BDHS data.

    RESULT: CS rates increased from 3.5% in 2004 to 23% in 2014. The average annual rate of increase in CS was higher among women of advanced maternal age (≥35 years), urban areas, and relatively high socio-economic status; with higher education, and who regularly accessed antenatal services. The multi-level logistic regression model indicated that lower (≤19) and advanced maternal age (≥35), urban location, relatively high socio-economic status, higher education, birth of few children (≤2), antenatal healthcare visits, overweight or obese were the key factors associated with increased utilization of CS. Underweight was a protective factor for CS.

    CONCLUSION: The use of CS has increased considerably in Bangladesh over the survey years. This rising trend and the risk of having CS vary significantly across regions and socio-economic status. Very high use of CS among women of relatively high socio-economic status and substantial urban-rural difference call for public awareness and practice guideline enforcement aimed at optimizing the use of CS.

  9. Sarkar T, Alam MM, Parvin N, Fardous Z, Chowdhury AZ, Hossain S, et al.
    Toxicol Rep, 2016;3:346-350.
    PMID: 28959555 DOI: 10.1016/j.toxrep.2016.03.003
    This study is aimed to assess the heavy metals contamination and health risk in Shrimp (Macrobrachium rosenbergii and Penaeus monodon) collected from Khulna-Satkhira region in Bangladesh. The results showed that the Pb concentrations (0.52-1.16 mg/kg) in all shrimp samples of farms were higher than the recommended limit. The Cd levels (0.05-0.13 mg/kg) in all samples and Cr levels in all farms except tissue content at Satkhira farm were higher than the permissible limits. The individual concentration of Pb, Cd, and Cr between shrimp tissue and shell in all rivers and farms were not statistically significant (P > 0.05). Target hazard quotient (THQ) and hazard index (HI) were estimated to assess the non-carcinogenic health risks. Shrimp samples from all locations under the current study were found to be safe for consumption, the possibility of health risk associated with non-carcinogenic effect is very low for continuous consumption for 30 years.
  10. Arafath MA, Kwong HC, Adam F, Mohiuddin M, Sarker MS, Salim M, et al.
    Acta Crystallogr E Crystallogr Commun, 2020 Jan 01;76(Pt 1):91-94.
    PMID: 31921459 DOI: 10.1107/S2056989019016852
    The mol-ecule of the title compound, C28H22N4O9, exhibits crystallographically imposed twofold rotational symmetry, with a dihedral angle of 66.0 (2)° between the planes of the two central benzene rings bounded to the central oxygen atom. The dihedral angle between the planes of the central benzene ring and the terminal phenol ring is 4.9 (2)°. Each half of the mol-ecule exhibits an imine E configuration. An intra-molecular O-H⋯N hydrogen bond is present. In the crystal, the mol-ecules are linked into layers parallel to the ab plane via C-H⋯O hydrogen bonds. The crystal studied was refined as a two-component pseudomerohedral twin.
  11. Kamal MA, Raza HW, Alam MM, Su'ud MM, Sajak ABAB
    Sensors (Basel), 2021 Oct 02;21(19).
    PMID: 34640908 DOI: 10.3390/s21196588
    Fifth-generation (5G) communication technology is intended to offer higher data rates, outstanding user exposure, lower power consumption, and extremely short latency. Such cellular networks will implement a diverse multi-layer model comprising device-to-device networks, macro-cells, and different categories of small cells to assist customers with desired quality-of-service (QoS). This multi-layer model affects several studies that confront utilizing interference management and resource allocation in 5G networks. With the growing need for cellular service and the limited resources to provide it, capably handling network traffic and operation has become a problem of resource distribution. One of the utmost serious problems is to alleviate the jamming in the network in support of having a better QoS. However, although a limited number of review papers have been written on resource distribution, no review papers have been written specifically on 5G resource allocation. Hence, this article analyzes the issue of resource allocation by classifying the various resource allocation schemes in 5G that have been reported in the literature and assessing their ability to enhance service quality. This survey bases its discussion on the metrics that are used to evaluate network performance. After consideration of the current evidence on resource allocation methods in 5G, the review hopes to empower scholars by suggesting future research areas on which to focus.
  12. Ishaq M, Khan A, Su'ud MM, Alam MM, Bangash JI, Khan A
    Comput Math Methods Med, 2022;2022:8691646.
    PMID: 35126641 DOI: 10.1155/2022/8691646
    Task scheduling in parallel multiple sequence alignment (MSA) through improved dynamic programming optimization speeds up alignment processing. The increased importance of multiple matching sequences also needs the utilization of parallel processor systems. This dynamic algorithm proposes improved task scheduling in case of parallel MSA. Specifically, the alignment of several tertiary structured proteins is computationally complex than simple word-based MSA. Parallel task processing is computationally more efficient for protein-structured based superposition. The basic condition for the application of dynamic programming is also fulfilled, because the task scheduling problem has multiple possible solutions or options. Search space reduction for speedy processing of this algorithm is carried out through greedy strategy. Performance in terms of better results is ensured through computationally expensive recursive and iterative greedy approaches. Any optimal scheduling schemes show better performance in heterogeneous resources using CPU or GPU.
  13. Khan A, Khan A, Ullah M, Alam MM, Bangash JI, Suud MM
    Front Comput Neurosci, 2022;16:1001803.
    PMID: 36405784 DOI: 10.3389/fncom.2022.1001803
    Cancer is one of the most prevalent diseases worldwide. The most prevalent condition in women when aberrant cells develop out of control is breast cancer. Breast cancer detection and classification are exceedingly difficult tasks. As a result, several computational techniques, including k-nearest neighbor (KNN), support vector machine (SVM), multilayer perceptron (MLP), decision tree (DT), and genetic algorithms, have been applied in the current computing world for the diagnosis and classification of breast cancer. However, each method has its own limitations to how accurately it can be utilized. A novel convolutional neural network (CNN) model based on the Visual Geometry Group network (VGGNet) was also suggested in this study. The 16 layers in the current VGGNet-16 model lead to overfitting on the training and test data. We, thus, propose the VGGNet-12 model for breast cancer classification. The VGGNet-16 model has the problem of overfitting the breast cancer classification dataset. Based on the overfitting issues in the existing model, this research reduced the number of different layers in the VGGNet-16 model to solve the overfitting problem in this model. Because various models of the VGGNet, such as VGGNet-13 and VGGNet-19, were developed, this study proposed a new version of the VGGNet model, that is, the VGGNet-12 model. The performance of this model is checked using the breast cancer dataset, as compared to the CNN and LeNet models. From the simulation result, it can be seen that the proposed VGGNet-12 model enhances the simulation result as compared to the model used in this study. Overall, the experimental findings indicate that the suggested VGGNet-12 model did well in classifying breast cancer in terms of several characteristics.
  14. Hassan SI, Alam MM, Zia MYI, Rashid M, Illahi U, Su'ud MM
    Sensors (Basel), 2022 Nov 07;22(21).
    PMID: 36366269 DOI: 10.3390/s22218567
    Rice is one of the vital foods consumed in most countries throughout the world. To estimate the yield, crop counting is used to indicate improper growth, identification of loam land, and control of weeds. It is becoming necessary to grow crops healthy, precisely, and proficiently as the demand increases for food supplies. Traditional counting methods have numerous disadvantages, such as long delay times and high sensitivity, and they are easily disturbed by noise. In this research, the detection and counting of rice plants using an unmanned aerial vehicle (UAV) and aerial images with a geographic information system (GIS) are used. The technique is implemented in the area of forty acres of rice crop in Tando Adam, Sindh, Pakistan. To validate the performance of the proposed system, the obtained results are compared with the standard plant count techniques as well as approved by the agronomist after testing soil and monitoring the rice crop count in each acre of land of rice crops. From the results, it is found that the proposed system is precise and detects rice crops accurately, differentiates from other objects, and estimates the soil health based on plant counting data; however, in the case of clusters, the counting is performed in semi-automated mode.
  15. Khan A, Khan A, Khan MM, Farid K, Alam MM, Su'ud MBM
    Diagnostics (Basel), 2022 Oct 26;12(11).
    PMID: 36359438 DOI: 10.3390/diagnostics12112595
    Cardiovascular disease includes coronary artery diseases (CAD), which include angina and myocardial infarction (commonly known as a heart attack), and coronary heart diseases (CHD), which are marked by the buildup of a waxy material called plaque inside the coronary arteries. Heart attacks are still the main cause of death worldwide, and if not treated right they have the potential to cause major health problems, such as diabetes. If ignored, diabetes can result in a variety of health problems, including heart disease, stroke, blindness, and kidney failure. Machine learning methods can be used to identify and diagnose diabetes and other illnesses. Diabetes and cardiovascular disease both can be diagnosed using several classifier types. Naive Bayes, K-Nearest neighbor (KNN), linear regression, decision trees (DT), and support vector machines (SVM) were among the classifiers employed, although all of these models had poor accuracy. Therefore, due to a lack of significant effort and poor accuracy, new research is required to diagnose diabetes and cardiovascular disease. This study developed an ensemble approach called "Stacking Classifier" in order to improve the performance of integrated flexible individual classifiers and decrease the likelihood of misclassifying a single instance. Naive Bayes, KNN, Linear Discriminant Analysis (LDA), and Decision Tree (DT) are just a few of the classifiers used in this study. As a meta-classifier, Random Forest and SVM are used. The suggested stacking classifier obtains a superior accuracy of 0.9735 percent when compared to current models for diagnosing diabetes, such as Naive Bayes, KNN, DT, and LDA, which are 0.7646 percent, 0.7460 percent, 0.7857 percent, and 0.7735 percent, respectively. Furthermore, for cardiovascular disease, when compared to current models such as KNN, NB, DT, LDA, and SVM, which are 0.8377 percent, 0.8256 percent, 0.8426 percent, 0.8523 percent, and 0.8472 percent, respectively, the suggested stacking classifier performed better and obtained a higher accuracy of 0.8871 percent.
  16. Hasanuzzaman M, Nahar K, Alam MM, Bhowmik PC, Hossain MA, Rahman MM, et al.
    Biomed Res Int, 2014;2014:589341.
    PMID: 25110683 DOI: 10.1155/2014/589341
    Salinity is one of the rising problems causing tremendous yield losses in many regions of the world especially in arid and semiarid regions. To maximize crop productivity, these areas should be brought under utilization where there are options for removing salinity or using the salt-tolerant crops. Use of salt-tolerant crops does not remove the salt and hence halophytes that have capacity to accumulate and exclude the salt can be an effective way. Methods for salt removal include agronomic practices or phytoremediation. The first is cost- and labor-intensive and needs some developmental strategies for implication; on the contrary, the phytoremediation by halophyte is more suitable as it can be executed very easily without those problems. Several halophyte species including grasses, shrubs, and trees can remove the salt from different kinds of salt-affected problematic soils through salt excluding, excreting, or accumulating by their morphological, anatomical, physiological adaptation in their organelle level and cellular level. Exploiting halophytes for reducing salinity can be good sources for meeting the basic needs of people in salt-affected areas as well. This review focuses on the special adaptive features of halophytic plants under saline condition and the possible ways to utilize these plants to remediate salinity.
  17. Haque MA, Jewel MAS, Akhi MM, Atique U, Paul AK, Iqbal S, et al.
    Environ Monit Assess, 2021 Oct 08;193(11):704.
    PMID: 34623504 DOI: 10.1007/s10661-021-09500-5
    Functional classification of phytoplankton could be a valuable tool in water quality monitoring in the eutrophic riverine ecosystems. This study is novel from the Bangladeshi perspective. In this study, phytoplankton cell density and diversity were studied with particular reference to the functional groups (FGs) approach during pre-monsoon, monsoon, and post-monsoon at four sampling stations in Karatoya River, Bangladesh. A total of 54 phytoplankton species were recorded under four classes, viz. Chlorophyceae (21 species) Cyanophyceae (16 species), Bacillariophyceae (15 species), and Euglenophyceae (2 species). A significantly higher total cell density of phytoplankton was detected during the pre-monsoon season (24.20 × 103 cells/l), while the lowest in monsoon (9.43 × 103 cells/l). The Shannon-Wiener diversity index varied significantly (F = 16.109, P = 000), with the highest value recorded during the post-monsoon season. Analysis of similarity (ANOSIM) identified significant variations among the three seasons (P 
  18. Lednicky JA, Tagliamonte MS, White SK, Blohm GM, Alam MM, Iovine NM, et al.
    Clin Infect Dis, 2022 Aug 24;75(1):e1184-e1187.
    PMID: 34718467 DOI: 10.1093/cid/ciab924
    We isolated a novel coronavirus from a medical team member presenting with fever and malaise after travel to Haiti. The virus showed 99.4% similarity with a recombinant canine coronavirus recently identified in a pneumonia patient in Malaysia, suggesting that infection with this virus and/or recombinant variants occurs in multiple locations.
  19. Rahman I, Singh P, Dev N, Arif M, Yusufi FNK, Azam A, et al.
    Materials (Basel), 2022 Nov 15;15(22).
    PMID: 36431551 DOI: 10.3390/ma15228066
    The findings of an extensive experimental research study on the usage of nano-sized cement powder and other additives combined to form cement-fine-aggregate matrices are discussed in this work. In the laboratory, dry and wet methods were used to create nano-sized cements. The influence of these nano-sized cements, nano-silica fumes, and nano-fly ash in different proportions was studied to the evaluate the engineering properties of the cement-fine-aggregate matrices concerning normal-sized, commercially available cement. The composites produced with modified cement-fine-aggregate matrices were subjected to microscopic-scale analyses using a petrographic microscope, a Scanning Electron Microscope (SEM), and a Transmission Electron Microscope (TEM). These studies unravelled the placement and behaviour of additives in controlling the engineering properties of the mix. The test results indicated that nano-cement and nano-sized particles improved the engineering properties of the hardened cement matrix. The wet-ground nano-cement showed the best result, 40 MPa 28th-day compressive strength, without mixing any additive compared with ordinary and dry-ground cements. The mix containing 50:50 normal and wet-ground cement exhibited 37.20 MPa 28th-day compressive strength. All other mixes with nano-sized dry cement, silica fume, and fly ash with different permutations and combinations gave better results than the normal-cement-fine-aggregate mix. The petrographic studies and the Scanning Electron Microscope (SEM) and Transmission Electron Microscope (TEM) analyses further validated the above findings. Statistical analyses and techniques such as correlation and stepwise multiple regression analysis were conducted to compose a predictive equation to calculate the 28th-day compressive strength. In addition to these methods, a repeated measures Analysis of Variance (ANOVA) was also implemented to analyse the statistically significant differences among three differently timed strength readings.
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