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378 results on '"Islam, Md. Rashidul"'

1. Identification of cross-frequency interactions in compressible cavity flow using harmonic resolvent analysis

Author

Islam, Md Rashidul and Sun, Yiyang

Subjects
Physics - Fluid Dynamics
Abstract

The resolvent analysis reveals the worst-case disturbances and the most amplified response in a fluid flow that can develop around a stationary base state. The recent work by Padovan et al.(2020) extended the classical resolvent analysis to the harmonic resolvent analysis framework by incorporating the time-varying nature of the base flow. The harmonic resolvent analysis can capture the triadic interactions between perturbations at two different frequencies through a base flow at a particular frequency. The singular values of the harmonic resolvent operator act as a gain between the spatio-temporal forcing and the response provided by the singular vectors. In the current study, we formulate the harmonic resolvent analysis framework for compressible flows based on the linearized Navier-Stokes equation (i.e., operator-based formulation). We validate our approach by applying the technique to the low-mach number flow past an airfoil. We further illustrate the application of this method to compressible cavity flows at Mach numbers of 0.6 and 0.8 with a length-to-depth ratio of $2$. For the cavity flow at Mach number of 0.6, the harmonic resolvent analysis reveals that the nonlinear cross-frequency interactions dominate the amplification of perturbations at frequencies that are harmonics of the leading Rossiter mode in the nonlinear flow. The findings demonstrate a physically consistent representation of an energy transfer from slow-evolving modes toward fast-evolving modes in the flow through cross-frequency interactions. For the cavity flow at Mach number of 0.8, the analysis also sheds light on the nature of cross-frequency interaction in a cavity flow with two coexisting resonances.

Published
2024
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47. Seed Priming with Rhizospheric Bacillus subtilis : A Smart Strategy for Reducing Fumonisin Contamination in Pre-Harvest Maize.

Author

Jannat, Muhtarima, Auyon, Shah Tasdika, Tushar, Abu Sina Md., Tonny, Sadia Haque, Hasan, Md. Hasibul, Shahi, Mangal, Singha, Uday Rana, Sultana, Ayesha, Akter, Sabera, and Islam, Md. Rashidul

Subjects
BACILLUS subtilis, BACILLUS (Bacteria), SEED treatment, FIELD research, FUSARIUM
Abstract

Maize, one of the most important cereal crops in Bangladesh, is severely contaminated by fumonisin, a carcinogenic secondary metabolite produced by Fusarium including Fusarium proliferatum. Biocontrol with Bacillus strains is an effective approach to controlling this F. proliferatum as Bacillus has proven antagonistic properties against this fungus. Therefore, the present study aimed to determine how native Bacillus strains can reduce fumonisin in maize cultivated in Bangladesh, where BDISO76MR (Bacillus subtilis) strains showed the highest efficacy both in vitro in detached cob and in planta under field conditions. The BDISO76MR strain could reduce the fumonisin concentration in detached cob at 98.52% over untreated control, by inhibiting the conidia germination and spore formation of F. proliferatum at 61.56% and 77.01%, respectively in vitro. On the other hand, seed treatment with formulated BDISO76MR showed higher efficacy with a reduction of 97.27% fumonisin contamination compared to the in planta cob inoculation (95.45%) over untreated control. This implies that Bacillus-based formulation might be a potential approach in mitigating fumonisin contamination in maize to ensure safe food and feed. [ABSTRACT FROM AUTHOR]

Published
2024
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48. A case study on integrating energy‐efficient technologies for display devices.

Author

Rahman, Md. Abdur, Tunny, Salma Sultana, Bhuiyan, Hanif, and Islam, Md. Rashidul

Subjects
INFORMATION display systems, LIQUID crystal devices, DISPLAY systems, ENERGY consumption, MEMORY
Abstract

For liquid crystal display‐based devices, the memory sub‐system and backlight consume a notable amount of energy, posing a critical concern, especially for portable devices. This work introduces an integrated display system (IDS) aimed at combining technologies for energy‐efficient memory usage and backlight power optimization, which have been addressed independently until now in the existing literature. Two modifications of approximated memory are proposed to find an optimal scheme for energy‐efficient memory usage as part of the proposed IDS schemes. Additionally, three distinct IDS schemes are proposed and compared to identify an optimum solution, ensuring energy efficiency maximization while maintaining image quality for each image. Experimental results demonstrate that 42.19% of energy consumption in memory access and 37.57% of the backlight power consumption can be reduced, while maintaining the image quality in terms of two different metrics. [ABSTRACT FROM AUTHOR]

Published
2024
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49. PCR BASED DETECTION OF LATENTLY INFECTED POTATO WITH BROWN ROT PATHOGEN, RALSTONIA SOLANACEARUM.

Author

Hossain, Md. Mokarram, Islam, Md. Rashidul, Das, Ronzon Chandra, Haque, Md. Mahbubul, Hossain, Mohammad Delwar, and Jerin, Faria-Ter

Subjects
*POTATOES, *BACTERIAL wilt of potato, *RALSTONIA solanacearum, *POLYMERASE chain reaction, *POTATO diseases & pests, *PATHOGENIC microorganisms, *POTATO growing, *TUBER crops
Abstract

Brown rot of potato is caused by a soil borne bacterium, Ralstonia solanacearum(Smith), a major limiting factor in the production of many crop plants around the world. An experiment was conducted to assess the status of brown rot disease in potatoes with the development of a rapid detection technique and approaches for production of brown rot free export quality potatoes to boost up potato export from Bangladesh. Survey results revealed a variation in latent infection (%) in tuber samples collected from six major growing areas viz. Dinajpur, Rangpur, Bogra, Joypurhat, Munshigonj and Comilla. The lowest (30%) latent infection was detected in tuber samples collected from Joypurhat as compared to Rangpur and Munshigonj in case of Asterix. However, in Diamant, the lowest (40%) latent infection was observed in Rangpur while 80% latent infection was recorded in Dinajpur and 88% was recorded in Munshigonj. Intriguingly, no latent infection was detected in Cardinal collected from Dinajpur while 40% latent infection was detected in samples from Joypurhat. However, 60% latent infection was detected in Granola which was collected from Dinajpur. The detection of R. solanacearum was reported in latently infected tubers by PCR using primers corresponding to 16SrDNA. In this study, PCR with primers PS-1 and PS-2 (16S rDNA) was used to detect R. solanacearum in latently infected tubers. An amplicon size corresponding to 553bp were obtained using enriched tuber extract as template. [ABSTRACT FROM AUTHOR]

Published
2024
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50. A comparative analysis of different transmission line fault detectors and classifiers during normal conditions and cyber‐attacks.

Author

Tusher, Animesh Sarkar, Rahman, M. A., Islam, Md. Rashidul, and Hossain, M. J.

Subjects
ELECTRIC lines, FAULT diagnosis, COMPUTER crimes, ELECTRIC power distribution, MACHINE learning
Abstract

Transmission lines, the core part of the transmission and distribution system in the smart grid, require effective, efficient, and reliable protective measures against faults to avoid severe damage to physical infrastructure and financial losses. Due to their growing popularity, machine learning models are used in fault detection and classification, whose performances can be severely affected by cyber‐attacks due to their data dependency, posing a critical concern. Hence, this paper introduces false data injection attacks to address the vulnerability of machine learning‐based fault detectors and classifiers. A comparative study of 9 detection models and 6 classification models under normal conditions and during a combination of two models of false data injection attacks is presented to evaluate the severity of cyber‐attacks. Experimental results show that highly accurate models in normal conditions are more susceptible to cyber‐attacks, with up to 69% and 28% degradations in accuracy for fault detectors and classifiers, respectively. Furthermore, the detection models are found to be more vulnerable to cyber‐attacks than the classification models. With no robust detectors and classifiers being found, this work addresses the importance of developing attack‐resilient fault detection and classification schemes considering their academic and industrial significance. [ABSTRACT FROM AUTHOR]

Published
2024
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