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Check FAQAbout Rashidul
Rashidul Islam is a Broadcast and Print journalist based in Dhaka, Bangladesh. I am a Newsroom Editor and a Staff Reporter. I worked in Various Electronic, Print, and Online news media in Dhaka. My Present work station is Global TV Bangladesh. My Previews work station was Wiki Bangla . I spent 5 years in Television and Newspaper and Online journalism. I am interested to work in media and communication. I am also interested in Political Issues and Investigative Reporting, Entertainment, Sports, and Cultural Reporting.
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Portfolio
Optimizing Short-Term Photovoltaic Power Forecasting: A Novel Approach with Gaussian Process Regression and Bayesian Hyperparameter Tuning
The study proposes a machine learning model based on Gaussian process regression (GPR) for short-term photovoltaic (PV) power output forecasting, leveraging Bayesian optimization for hyperparameter tuning. The model uses solar radiation intensity data collected at 60-min and 30-min intervals, demonstrating superior performance compared to contemporary machine learning models and traditional neural network models. The research highlights significant improvements in forecasting accuracy, robustness, and flexibility, contributing to more reliable and stable power systems.
Native Trichoderma Induced the Defense-Related Enzymes and Genes in Rice against Xanthomonas oryzae pv. oryzae (Xoo)
The study investigates the effectiveness of four strains of Trichoderma in inducing defense-related enzymes and genes in rice to combat bacterial blight caused by Xanthomonas oryzae pv. oryzae. The research demonstrates that Trichoderma strains significantly reduce lesion length in rice leaves by enhancing the expression of core defense-related enzymes and genes associated with salicylic acid (SA) and jasmonic acid (JA) pathways. The findings suggest that Trichoderma can be an effective biocontrol agent, offering an environmentally friendly alternative to chemical treatments for managing bacterial blight in rice.
Differential Fairness: An Intersectional Framework for Fair AI
The article proposes 'differential fairness,' a new framework for ensuring fairness in AI and machine learning systems through the lens of intersectionality. This framework considers multiple protected attributes simultaneously and provides economic, privacy, and generalization guarantees. The authors present a learning algorithm that respects these fairness criteria and demonstrate its utility through case studies on various datasets. The research aims to bridge the gap between technical definitions of fairness and their real-world implications, emphasizing the need for interdisciplinary approaches to address fairness in AI.
Fancy cheating! | অভিনব কায়দায় প্রতারণা!
The only female member of the banned militant group was arrested | নিষিদ্ধ জঙ্গি সংগঠনের একমাত্র নারী সদস্য গ্রেফতার
9 arrested with the terrible drug ice-yaba | ভয়ংকর মাদক আইস-ইয়াবাসহ গ্রেফতার ৯
Noman group's stolen clothes and covered van recovered: 3 arrested | নোমান গ্রুপের চুরি যাওয়া কাপড় ও কাভার্ড ভ্যান উদ্ধার : গ্রেফতার ৩
Imam of a mosque in Brahmanbaria killed: 3 arrested | ব্রাহ্মণবাড়িয়ায় মসজিদের ইমাম হত্যা : আটক ৩
Fancy fraud in the form of secretary: 4 arrested | সচিব পরিচয়ে অভিনব কায়দায় প্রতারণা : গ্রেফতার ৪
The ‘dream’ super shop of hacking | হ্যাকিং এর স্বীকার ‘স্বপ্ন’ সুপার সপ
Sed ut perspiciatis unde omnis iste natus error sit voluptatem accusantium
doloremque laudantium,
totam rem aperiam, eaque ipsa quae ab illo inventore veritatis et quasi architecto beatae vitae dicta sunt explicabo. Nemo enim ipsam voluptatem quia voluptas sit aspernatur aut odit aut fugit, sed quia consequuntur magni dolores eos qui ratione voluptatem sequi nesciunt. Neque porro quisquam est, qui dolorem ipsum quia dolor sit amet, consectetur, adipisci velit, sed quia non numquam eius modi tempora incidunt ut labore et dolore magnam aliquam quaerat voluptatem. Ut enim ad minima veniam, quis nostrum exercitationem ullam corporis suscipit laboriosam, nisi ut aliquid ex ea commodi consequatur?
doloremque laudantium,
totam rem aperiam, eaque ipsa quae ab illo inventore veritatis et quasi architecto beatae vitae dicta sunt explicabo. Nemo enim ipsam voluptatem quia voluptas sit aspernatur aut odit aut fugit, sed quia consequuntur magni dolores eos qui ratione voluptatem sequi nesciunt. Neque porro quisquam est, qui dolorem ipsum quia dolor sit amet, consectetur, adipisci velit, sed quia non numquam eius modi tempora incidunt ut labore et dolore magnam aliquam quaerat voluptatem. Ut enim ad minima veniam, quis nostrum exercitationem ullam corporis suscipit laboriosam, nisi ut aliquid ex ea commodi consequatur?
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