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Effect of Gamma Irradiation Doses on Morphological and Biochemical Attributes of Grape Saplings

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Agricultural Sciences 2015年第5期6卷 505-512页

作者： A. F. M. Saiful Islam M. Muzahedul Islam md. mehedi hasan md. mehedi hasan Department of Crop Botany & Tea Production Technology Sylhet Agricultural University Sylhet Bangladesh

The demand of grape in Bangladesh is fulfilled through import from foreign countries. The fruits of local cultivars of grapes are sour and seeded. Development of seedless grape varieties having increased sweetness, higher yield with better nutritional quality is necessary to reduce the import dependency. The present research activities are the part of a grape improvement project. A pot experiment was conducted at the Bangladesh Institute of Nuclear Agriculture (BINA), Mymensingh, during June to November 2011 to determine the suitable gamma irradiation doses on growth, leaf area and biochemical characters of grape saplings. Three vegetative bud stages viz. bud initiation stage, 4-leaf stage and 8-leaf stage, and four doses of gamma irradiation viz. 0, 5, 10, and 15 Gy were used as treatments. The experiment was laid out in a Randomized Complete Block Design with four replications. Different irradiation doses and vegetative bud stages showed significant variations in respect of plant growth characters, leaf area, soluble protein and total sugar content. Interaction effects also had significant variations on most of the parameters studied. Higher doses of gamma irradiation had showed detrimental effect on grape saplings. Generally, increased in irradiation doses showed decreased and detrimental effects on most of the parameters under study. Maximum numbers and length of roots, total dry matter, leaf area and chlorophyll-a and chlorophyll-b content were found at 5 Gy irradiation dose. Total soluble protein and sugar content of leaf were found maximum at no irradiation and 15 Gy, respectively. Higher number of roots and length, total dry matter, leaf area, chlorophyll-a, and b and soluble protein content of leaf were observed at bud initiation stage while 8-leaf stage showed maximum total sugar of leaf. In the combined effect of gamma irradiation and vegetative bud stages, all parameters showed best results in 5 Gy with bud initiation stage except total sugar content of

关键词： Grape Sapling Gamma Irradiation Morphological and Biochemical Parameters Leaf Area Soluble Protein

Next-generation blockchain enabled smart grid: Conceptual framework, keytechnologies and industry practices review

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Energy and AI 2023年第2期12卷 187-205页

作者： Shekh S.Uddin Rahul Joysoyal Subrata K.Sarker S.M.Muyeen md.Firoj Ali md.mehedi hasan Sarafat Hussain Abhi md.Robiul Islam md.Hafiz Ahamed md.Manirul Islam Sajal K.Das md.Faisal R.Badal Prangon Das Zinat Tasneem Department of Mechatronics Engineering Rajshahi University of Engineering&TechnologyRajshahi 6204Bangladesh Department of Electrical Engineering Qatar UniversityQatar

Technological advancements in smart grid energy systems (SGESs) are introducing sustainable frameworksto meet the demand for the fourth industrial energy revolution. These frameworks are planned to be usedin the forthcoming future to maintain the energy network operation with optimization, energy trading, gridautomation, and so on. Blockchain (BCn), developing after passing a diverse period of the research journey,comes to the mind of researchers and its integration in SGES paves the way to reach the goal of energydemand. However, still of interest is ongoing in the improvement of BCn features which can be regarded asthe next-generation blockchain framework. This paper exhibits the technical framework of the next-generationBCn framework and explores its benefits and challenges in performing the emerging aspects of SGES. Thisframework enables some advanced features for the sustainable operation of SGES like smart metering, peer-topeer (P2P) energy trading, self-operation, and transparency. The technical explanation of this BCn technologyestablished on essential features and requisites is also presented in this paper from various points of viewwhich include smart mechanism, intelligent storage system, and interoperability. We also highlight the recentprogress and limitations of the current BCn framework in SGES. Finally, some challenges towards integratingthe next-generation BCn technology in SGES are reported. This work can provide extended support for thepractitioner and researcher in the context of BCn technology and SGES.

关键词： Blockchain Smart grid energy system Smart contract

Insights into Manipulation: Unveiling Tampered Images Using Modified ELA, Deep Learning, and Explainable AI

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Journal of Computer and Communications 2024年第6期12卷 135-151页

作者： md. mehedi hasan md. Masud Rana Abu Sayed md. Mostafizur Rahaman Department of Information and Communication Technology Bangladesh University of Professionals Dhaka Bangladesh Department of Computer Science and Engineering Jahangirnagar University Dhaka Bangladesh

Digital image forgery (DIF) is a prevalent issue in the modern age, where malicious actors manipulate images for various purposes, including deception and misinformation. Detecting such forgeries is a critical task for maintaining the integrity of digital content. This thesis explores the use of Modified Error Level Analysis (ELA) in combination with a Convolutional Neural Network (CNN), as well as, Feedforward Neural Network (FNN) model to detect digital image forgeries. Additionally, incorporation of Explainable Artificial Intelligence (XAI) to this research provided insights into the process of decision-making by the models. The study trains and tests the models on the CASIA2 dataset, emphasizing both authentic and forged images. The CNN model is trained and evaluated, and Explainable AI (SHapley Additive exPlanation— SHAP) is incorporated to explain the model’s predictions. Similarly, the FNN model is trained and evaluated, and XAI (SHAP) is incorporated to explain the model’s predictions. The results obtained from the analysis reveals that the proposed approach using CNN model is most effective in detecting image forgeries and provides valuable explanations for decision interpretability.

关键词： IFD DIF ELA CNN FNN XAI SHAP CASIA2.0

Towards electric digital twin grid: Technology and framework review

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Energy and AI 2023年第1期11卷 179-195页

作者： md.Mhamud Hussen Sifat Safwat Mukarrama Choudhury Sajal K.Das md.Hafiz Ahamed S.M.Muyeen md.mehedi hasan md.Firoj Ali Zinat Tasneem md.Manirul Islam md.Robiul Islam md.Faisal R.Badal Sarafat H.Abhi Subrata K.Sarker Prangon Das Department of Mechatronics Engineering Rajshahi University of Engineering&TechnologyRajshahi6204Bangladesh Department of Electrical Engineering Qatar UniversityDoha2713Qatar

The major hindrances in the energy system are ecological consciousness, lack of clean and sustainableenergy management, insufficient energy distribution–transmission–optimization, expensive power transfercosts, and increased customer knowledge of energy charges. Thus why, universal access to the grid with highcybersecurity, and reliability is needed to solve all these challenges. The digital twin concept turns a newdimension of technology into the world. Electric Digital Twin grid can perform online analysis of the grid inreal-time and integrates all the past and present data and express the current grid status to the producers andconsumers and also predicts the future grid status. Thus, the power grid transmission loss and location of theoverheated line and power connection missing can be detected in addition decision-making and self-healingcan possible. The future prediction saves the power grid from small to long accidents such as power outagesand even blackout problems. The whole consumers and nation feel relief from these types of accidents andsaves from large economic and business loss. The blockchain-enabled digital twin grid provides high securityfor the grid from cyberattacks. The paper conveys the framework of the electric digital twin grid and theconcept of the DT grid processing and the way of serving the producer, prosumers, consumers even the wholenation in infrastructure, education, research, economic, business, and political development.

关键词： Electric digital twin grid Online analysis of grid Cloud platform of grid Real-time grid analysis Self-healing Cybersecurity

Ru/NiMnB spherical cluster pillar for highly proficient green hydrogen electrocatalyst at high current density

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Journal of Energy Chemistry 2025年第1期100卷 397-408页

作者： md Ahasan Habib Shusen Lin mehedi hasan Joni Sumiya Akter Dristy Rutuja Mandavkar Jae-Hun Jeong Jihoon Lee Department of Electronic Engineering College of Electronics and Information Kwangwoon University

Advanced OER/HER electrocatalytic alternatives are crucial for the wide adaptation of green hydrogen ***,Ru/NiMnB spherical cluster pillar （SCP）,denoted as Ru/NiMnB,is synthesized using a combination of electro-deposition and hydrothermal *** investigation of Ru doping in the NiMnB matrix revealed significant improvements in electrocatalytic *** Ru/NiMnB SCPs demonstrate superior OER/HER activity with low overpotentials of 150 and 103 mV at 50mA/cm2in 1 M KOH,making them highly competitive with state-of-the-art ***,the Ru/NiMnB SCPs exhibit a low 2-E cell voltage of 2.80 V at ultra-high current density of 2,000 m A/cm2in 1 M KOH,outperforming the standard benchmark electrodes of RuO2||Pt/C,thereby positioning Ru/NiMnB as one of the best bifunctional *** SCPs exhibit exceptional high-current characteristics,stability and corrosion resistance,as evidenced by continuous operation at 1,000 mA/cm2high-current density for over 150 h in 6 M KOH at elevated temperatures under harsh industrial *** a small amount of Ru incorporation significantly enhances the electrocatalytic performances of NiMnB,attributed to increased active sites and improved intrinsic properties such as conductivity,adsorption/desorption capability and reaction ***,Ru/NiMnB SCPs present a promising bi-functional electrode concept for efficient green H2production.

关键词： Advanced electrocatalyst High current Corrosion resistance Industrial requirement

Feature Selection for Intrusion Detection Using Random Forest

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Journal of Information Security 2016年第3期7卷 129-140页

作者： md. Al mehedi hasan Mohammed Nasser Shamim Ahmad Khademul Islam Molla Department of Computer Science & Engineering University of Rajshahi Rajshahi Bangladesh

An intrusion detection system collects and analyzes information from different areas within a computer or a network to identify possible security threats that include threats from both outside as well as inside of the organization. It deals with large amount of data, which contains various ir-relevant and redundant features and results in increased processing time and low detection rate. Therefore, feature selection should be treated as an indispensable pre-processing step to improve the overall system performance significantly while mining on huge datasets. In this context, in this paper, we focus on a two-step approach of feature selection based on Random Forest. The first step selects the features with higher variable importance score and guides the initialization of search process for the second step whose outputs the final feature subset for classification and in-terpretation. The effectiveness of this algorithm is demonstrated on KDD’99 intrusion detection datasets, which are based on DARPA 98 dataset, provides labeled data for researchers working in the field of intrusion detection. The important deficiency in the KDD’99 data set is the huge number of redundant records as observed earlier. Therefore, we have derived a data set RRE-KDD by eliminating redundant record from KDD’99 train and test dataset, so the classifiers and feature selection method will not be biased towards more frequent records. This RRE-KDD consists of both KDD99Train+ and KDD99Test+ dataset for training and testing purposes, respectively. The experimental results show that the Random Forest based proposed approach can select most im-portant and relevant features useful for classification, which, in turn, reduces not only the number of input features and time but also increases the classification accuracy.

关键词： Feature Selection KDD’99 Dataset RRE-KDD Dataset Random Forest Permuted Importance Measure

Towards next generation Internet of Energy system: Framework and trends

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Energy and AI 2023年第4期14卷 660-681页

作者： Muqit Farhan Tanzim N.Reza Faisal R.Badal md.R.Islam S M Muyeen Z.Tasneem md.mehedi hasan md.F.Ali md.H.Ahamed S.H.Abhi md.Manirul Islam Subrata K.Sarker Sajal K.Das Prangon Das Department of Mechatronics Engineering Rajshahi University of Engineering TechnologyRajshahi 6204Bangladesh Department of Electrical Engineering Qatar UniversityDohaQatar

The quickening propensity of growth within the areas of information and communications technology and en-ergy networks has triggered the emergence of a central idea termed as Internet of Energy(IoE).Such a concept relates the internet of things,which is the term used in describing the usage of sophisticated digital control devices with the capability of transmitting data via IT *** concept of an interconnected energy network is being formed in the upcoming days through upgrades in the field of intelligent energy systems to control real-time energy optimization and *** energy industry has had a sustained expansion,reaching the IoE milestone and continuing to this cutting-edge power system,which is the next generation of IoE.A directional pathway from the traditional power system to the IoE has been conducted in this research work by addressing the importance of integrating the smart transmission and communication infrastructure,smart metering,pricing and energy management scheme.A detailed investigation of the IoE with respect to technical angles,such as communication architecture,IoE on the supply&demand side,and IoE protocol based on fundamental elements and essential technologies has been carried out to indicate the blueprint and jurisdiction *** inte-gration,security and energy management challenges may deviate the performance of the IoE technology that has been focused with proper control issues and ***,a directional framework to establish the next-generation IoE system has been constructed with future scopes to insure higher resiliency,cyber-security and stability.

关键词： Internet of Energy IoT Microgrid Smart grid Virtual power plant Next generation power system

Support Vector Machine and Random Forest Modeling for Intrusion Detection System (IDS)

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Journal of Intelligent Learning Systems and Applications 2014年第1期6卷 45-52页

作者： md. Al mehedi hasan Mohammed Nasser Biprodip Pal Shamim Ahmad Department of Computer Science and Engineering Rajshahi University of Engineering and Technology (RUET) Rajshahi Bangladesh Department of Computer Science and Engineering Rajshahi University of Engineering and Technology (RUET) Rajshahi Bangladesh Department of Computer Science and Engineering University of Rajshahi Rajshahi Bangladesh Department of Statistics University of Rajshahi Rajshahi Bangladesh

The success of any Intrusion Detection System (IDS) is a complicated problem due to its nonlinearity and the quantitative or qualitative network traffic data stream with many features. To get rid of this problem, several types of intrusion detection methods have been proposed and shown different levels of accuracy. This is why the choice of the effective and robust method for IDS is very important topic in information security. In this work, we have built two models for the classification purpose. One is based on Support Vector Machines (SVM) and the other is Random Forests (RF). Experimental results show that either classifier is effective. SVM is slightly more accurate, but more expensive in terms of time. RF produces similar accuracy in a much faster manner if given modeling parameters. These classifiers can contribute to an IDS system as one source of analysis and increase its accuracy. In this paper, KDD’99 Dataset is used and find out which one is the best intrusion detector for this dataset. Statistical analysis on KDD’99 dataset found important issues which highly affect the performance of evaluated systems and results in a very poor evaluation of anomaly detection approaches. The most important deficiency in the KDD’99 dataset is the huge number of redundant records. To solve these issues, we have developed a new dataset, KDD99Train+ and KDD99Test+, which does not include any redundant records in the train set as well as in the test set, so the classifiers will not be biased towards more frequent records. The numbers of records in the train and test sets are now reasonable, which make it affordable to run the experiments on the complete set without the need to randomly select a small portion. The findings of this paper will be very useful to use SVM and RF in a more meaningful way in order to maximize the performance rate and minimize the false negative rate.

关键词： Intrusion Detection KDD’99 SVM Kernel Random Forest

Role of a Coastal NGO in Attaining Climate Resilience in Bangladesh

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American Journal of Climate Change 2018年第2期7卷 187-203页

作者： md. mehedi hasan Mohammed Asaduzzaman Sarker Mohammed Nasir Uddin md. Zulfikar Rahman Baokun Lei Department of Agricultural Extension Education Bangladesh Agricultural University Mymensingh Bangladesh Institute of Agricultural Environment and Resources Yunnan Academy of Agricultural Sciences Kunming China

The emergence of NGOs represents an organized response by civil society especially in those areas in which the state has either failed to reach or done so inadequately. NGOs have been taking a number of steps to promote discussion and debate about climate change issues. The study was conducted to determine the role of a coastal NGO named Speed Trust in attaining resilience in response to climate change in coastal region;viz. Kalapara sub-district under Patuakhali district. The sample size of the study was 80 respondents. The study followed a mixed-method of research design. Both structured and semi-structured questionnaires were prepared for collecting quantitative and qualitative data from the respondent. The empirical data for the study were collected through personal interviewing of the respondents. The findings of the study revealed that the role of Speed Trust in attaining climate resilience of the study area was varied with the change of aspects of climate resilience. It also indicated that majority (80 percent) of the respondents perceived the idea that Speed Trust is playing moderate to highly effective role in attaining climate resilience. While only 1.2 percent had perceived as poor role in attaining resilience in response to climate change. Correlation analysis indicated that among the selected socio-economic characteristics, respondent’s education, organizational participation, training on climate resilience, consequence due to climate change and participation in climate resilience program showed positive and significant relationship with the role of Speed Trust in response to climate resilience. Step-wise multiple regression analysis explored that amongst five variables, three independent variables finally entered into the model and the contribution factors are: participation, training, and organizational participation. They are jointly accounted for 62.2 percent of the total variation with perceived role of Speed Trust in attaining climate resilience.

关键词： Climate Resilience Role of NGO Speed Trust Coastal Region and Bangladesh