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mLysPTMpred: Multiple Lysine PTM Site Prediction Using Combination of SVM with Resolving Data Imbalance Issue

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Natural Science 2018年第9期10卷 370-384页

作者： md. Al mehedi hasan Shamim Ahmad Department of Computer Science and Engineering Rajshahi University of Engineering and Technology Rajshahi Bangladesh Department of Computer Science and Engineering University of Rajshahi Rajshahi Bangladesh

Post-translational modification (PTM) increases the functional diversity of proteins by introducing new functional groups to the side chain of amino acid of a protein. Among all amino acid residues, the side chain of lysine (K) can undergo many types of PTM, called K-PTM, such as “acetylation”, “crotonylation”, “methylation” and “succinylation” and also responsible for occurring multiple PTM in the same lysine of a protein which leads to the requirement of multi-label PTM site identification. However, most of the existing computational methods have been established to predict various single-label PTM sites and a very few have been developed to solve multi-label issue which needs further improvement. Here, we have developed a computational tool termed mLysPTMpred to predict multi-label lysine PTM sites by 1) incorporating the sequence-coupled information into the general pseudo amino acid composition, 2) balancing the effect of skewed training dataset by Different Error Cost method, and 3) constructing a multi-label predictor using a combination of support vector machine (SVM). This predictor achieved 83.73% accuracy in predicting the multi-label PTM site of K-PTM types. Moreover, all the experimental results along with accuracy outperformed than the existing predictor iPTM-mLys. A user-friendly web server of mLysPTMpred is available at http://***/mLysPTMpred/.

关键词： Multi-Label PTM Site Predictor Sequence-Coupling Model General PseAAC Data Imbalance Issue Different Error Costs Support Vector Machine

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

Complete Garment Costing with Major Cost Breakdown

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Journal of Textile Science and Technology 2023年第2期9卷 115-126页

作者： md. Monirul Islam Rajib md. mehedi hasan Parvez md. Shofiul Islam Tanveer Ahmed md. Rashedul Islam Department of Apparel Manufacturing & Technology BGMEA University of Fashion & Technology (BUFT) Dhaka Bangladesh

Apparel business is one of the oldest global businesses. Emergence of different apparel manufacturing nations, rapid development of global supply chains and increasingly higher demand for fast fashion items are exposing the apparel manufacturers to competitive product prices. Alongside, the persistent global depression has also forced the apparel business to curtail the prices to remain sustainable in the industry. Garment costing is the systematic process of meticulously calculating the total cost of a certain quantity of garments from raw material purchase to converting them to the final products, plus other terms and conditions stated by the customers. The sum of these costs adding the profit margin is the selling price. This research outlines the process of preparing cost sheets for basic garment products. The research proposes a clear method of generating easily understandable, complete garment cost sheets for the apparel industry.

关键词： Apparel Costing Shirt Trousers T-Shirt

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

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

Investigation of the Antimicrobial Activity and <i>in Vivo </i>Cytotoxicity of <i>Diospyros malabarica </i>(Desr.) Kostel. Fruit Extracts

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Natural Science 2021年第8期13卷 331-351页

作者： Razib Datta Shubhra Shakil Ahmed Polash md. Monir Hossain Amir Hamza md. mehedi hasan Tushar Tanushree Saha md. Ashraful hasan md. Maniruzzaman Sikder Nuhu Alam Zinia Islam md. Sharif Hossain Satya Ranjan Sarker Department of Biotechnology and Genetic Engineering Jahangirnagar University Savar Bangladesh Department of Textile Engineering Dhaka University of Engineering and Technology Gazipur Bangladesh Department of Biochemistry and Molecular Biology Jahangirnagar University Savar Bangladesh Department of Botany Jahangirnagar University Savar Bangladesh

Mankind is facing an unprecedented threat of existence due to the antibiotic resistance developed by bacteria. The unripe fruits of Diospyros malabarica (Desr.) Kostel. (family: Ebenaceae) can be considered as one of the natural sources to tackle this issue. The present study is designed to assess the antimicrobial activity of D. malabarica seed and flesh ex-tracts. Herein, D. malabarica extracts were prepared using polar solvents (i.e., water and 70% ethanol) and their antimicrobial activity as well as in vivo toxicity was investigated. Their antibacterial activity was investigated against gram positive (Bacillus subtilis) and gram negative (Escherichia coli DH5α, and Salmonella typhi) bacteria at different time points. All the extracts showed the highest antibacterial activity after 2 hours of incubation. The aqueous seed extract showed the maximum zone of inhibition (i.e., ~13 mm) against Bacillus subtilis with a minimum inhibitory concentration (MIC) value of 2 μg/μl. The an-tibacterial propensity was also confirmed through trypan blue dye exclusion assay, CellToxTM Green assay, and lipid peroxidation (LPO) assay. On the other hand, the etha-nolic seed extract demonstrated higher antifungal activity through inhibition of mycelial growth. All the extracts showed excellent hemocompatibility against both human and rat red blood cells (RBCs). They also did not show any toxicity to rat liver and kidneys. Taken together, this study demonstrates that the aqueous and ethanolic extracts of D. malabarica seed and flesh could be an effective source of natural antimicrobial agents with no cytotox-ic activity.

关键词： Diospyros malabarica (Desr.) Kostel. Antibacterial Activity Trypan Blue Assay Cell ToxTM Green Assay In Vivo Cytotoxicity

Japanese Sign Language Recognition by Combining Joint Skeleton-Based Handcrafted and Pixel-Based Deep Learning Features with Machine Learning Classification

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 2605-2625页

作者： Jungpil Shin md.Al mehedi hasan Abu Saleh Musa Miah Kota Suzuki Koki Hirooka School of Computer Science and Engineering The University of AizuAizuwakamatsu965-8580Japan Department of Computer Science&Engineering Rajshahi University of Engineering&TechnologyRajshahi6204Bangladesh

Sign language recognition is vital for enhancing communication accessibility among the Deaf and hard-of-hearing *** Japan,approximately 360,000 individualswith hearing and speech disabilities rely on Japanese Sign Language(JSL)for ***,existing JSL recognition systems have faced significant performance limitations due to inherent *** response to these challenges,we present a novel JSL recognition system that employs a strategic fusion approach,combining joint skeleton-based handcrafted features and pixel-based deep learning *** system incorporates two distinct streams:the first stream extracts crucial handcrafted features,emphasizing the capture of hand and body movements within JSL ***,a deep learning-based transfer learning stream captures hierarchical representations of JSL gestures in the second ***,we concatenated the critical information of the first stream and the hierarchy of the second stream features to produce the multiple levels of the fusion features,aiming to create a comprehensive representation of the JSL *** reducing the dimensionality of the feature,a feature selection approach and a kernel-based support vector machine(SVM)were used for the *** assess the effectiveness of our approach,we conducted extensive experiments on our Lab JSL dataset and a publicly available Arabic sign language(ArSL)*** results unequivocally demonstrate that our fusion approach significantly enhances JSL recognition accuracy and robustness compared to individual feature sets or traditional recognition methods.

关键词： Japanese Sign Language(JSL) hand gesture recognition geometric feature distance feature angle feature GoogleNet

Gas Blowout Impacts on Ground Water Environs around the Tengratila Gas Field, Chattak, Bangladesh

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Journal of Water Resource and Protection 2013年第2期5卷 164-170页

作者： M Farhad Howladar md. mehedi hasan Saiful Islam Fazle Mohammad Mohi Shine Chowdhury Quamruzzaman Department of Civil and Environmental Engineering Shahjalal University of Science and Technology Sylhet Bangladesh Department of Geology and Mining University of Rajshahi Rajshahi Bangladesh Department of Geology University of Dhaka Dhaka Bangladesh Department of Petroleum and Mining Engineering Shahjalal University of Science and Technology Sylhet Bangladesh

Gas blowout is one of the major hazard in petroleum field which normally damages the gas bearing geologic formation, structure, local tectonic setting, environment and so on. In Bangladesh, there have been three well known gas blowouts. Among them, the most dangerous gas well blowout took place on 8 January 2005 in Sunamganj district when chattak-2 (also known as Tengratila) gas field was drilled. As a result, the surrounding area is facing various problems among them water is the top of the list. From this point of view, the present study has been considered to find the impact of blowout on water around the gas blowout area. In this regard, the water samples (some are very near and some are away from the well) are collected and analyzed in the laboratory following the standard method. Some physical and chemical parameters of water such as pH, turbidity, EC, total solids, dissolved solids, suspended solids, manganese ion, calcium ion, magnesium, iron, chloride and total hardness have measured where without turbidity, manganese and iron, all are still in tolerable state for all purposes and ranging within standard limit based on WHO, EU and EQS for Bangladesh. The quality of the near well tube wells water is much decreased than far away tube wells water which might be the direct or indirect influence of the blowout incident around the area.

关键词： Tengratila Gas Field Gas Blowout Water Quality Blow out Impact