2017 20th International Conference of Computer and Information Technology (ICCIT)
VANET (Vehicular Ad-hoc NETwork) is a network architecture designed to provide road safety, impro... more VANET (Vehicular Ad-hoc NETwork) is a network architecture designed to provide road safety, improve transport efficiency, and reduce traffic congestion by combining vehicles with high mobility and fixed road-side units with or without Vehicular Cloud. Connected vehicles aided with sensors need to be authenticated before transmitting message. Two major problems in existing state-of-the-art schemes which are redundant authentication of vehicles with each RSUs it passes through and authenticating each message by trusted authority with large cryptographic overheads. In this paper we proposed an authentication scheme which exploits a very new technique of successive message passing among different RSUs (Road-side Units) to verify vehicles which are already authenticated. In our scheme, RSUs share authentication related information of vehicles with the help of newly proposed RSUs detection algorithm. In addition to that, messages from vehicles are verified with assistance from RSUs using symmetric key based Hashed Message Authentication Code (HMAC) signatures. This results in remarkably reduced cryptographic overheads and communication delay occurred during authentication of vehicles and messages in VANETs. Extensive performance evaluations and comparison with state-of-the-art schemes will show how our scheme provides exceptionally improved performance for VANETs.
2017 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE), 2017
With the advancement of Information technologies and applications, a copious amount of data is ge... more With the advancement of Information technologies and applications, a copious amount of data is generated, which attracts both the research community to utilize this information for extracting knowledge and the industry for developing the knowledge-based system. Visualization of data, pattern mining from datasets and analyzing data drift for the different features are three highly used applications of machine learning and data science fields. A generic web-based tool integrated with such features will provide prodigious support for preprocessing the dataset and thus extracting accurate information. In this work, we propose such a data visualization tool, named VIM, which is a web-based comprehensive tool for generic data visualization, data preprocessing and mining suitable knowledge with drift analysis of data. Given a dataset, it can envisage the distribution of data with convenient statistical diagrams for different selected features. Moreover, users can employ VIM to generate association rules by selecting multiple features. We have developed VIM using Python Django framework and GraphLab library. We have deployed this tool to make this publicly usable, which can be accessed at http://210.4.73.237:9999/
Advances in Intelligent Systems and Computing, 2018
In phage therapy, bacteriophage proteins are used to kill bacteria that cause infection. The know... more In phage therapy, bacteriophage proteins are used to kill bacteria that cause infection. The knowledge of the location of the bacteriophage proteins plays an important role here. In this paper, we propose a supervised learning based method to predict the locations of bacteriophage proteins. First, we address the problem of predicting whether a bacteriophage is extracellular or located in the host cell. Second, we also address the subcellular location prediction problem of the phage proteins. For the host located proteins, the proteins could either be located in cell membrane or in the cytoplasm. We have successfully used deep feed-forward neural network on a standard training dataset and achieved good results for both of the prediction problems. Our method uses an optimal set of features for classification and achieves 87.7% and 98.5% accuracy for two of the prediction problems which is 3.5% and 6.3% improved than the previous state-of-the-art results achieved for these problems, re...
A field experiment was conducted during the winter season (rabi) of 1991-92, 1993-93 and 1993-94 ... more A field experiment was conducted during the winter season (rabi) of 1991-92, 1993-93 and 1993-94 to study the performance of indian mustard [Brassica junced (L.) Czernj. & Cosson] + lentil (Lens culinaris Medikus) and gram (Cicer arietinum L.) intercropping for yield. The highest seed of indian mustard and lentil was obtained with N,P and K @ 80, 17.5 and 33.3 kg/ha from 2.2 and 1.1 row ration respectively. Intercropping of indian mustard and lentil with a fertilizer does of 80 kg N/ha, 17.5 kg P/ha and 33.3 kg K/ha recorded higher land-equivalent ratio and monetary advantage from 1:1 row ratio during 1991-92 and 1992-93 and from 2:2 row ratio during 1993-94.
Recent advancements in the field of computer vision with the help of deep neural networks have le... more Recent advancements in the field of computer vision with the help of deep neural networks have led us to explore and develop many existing challenges that were once unattended due to the lack of necessary technologies. Hand Sign/Gesture Recognition is one of the significant areas where the deep neural network is making a substantial impact. In the last few years, a large number of researches has been conducted to recognize hand signs and hand gestures, which we aim to extend to our mother-tongue, Bangla (also known as Bengali). The primary goal of our work is to make an automated tool to aid the people who are unable to speak. We developed a system that automatically detects hand sign based digits and speaks out the result in Bangla language. According to the report of the World Health Organization (WHO), 15% of people in the world live with some kind of disabilities. Among them, individuals with communication impairment such as speech disabilities experience substantial barrier in social interaction. The proposed system can be invaluable to mitigate such a barrier. The core of the system is built with a deep learning model which is based on convolutional neural networks (CNN). The model classifies hand sign based digits with 92% accuracy over validation data which ensures it a highly trustworthy system. Upon classification of the digits, the resulting output is fed to the text to speech engine and the translator unit eventually which generates audio output in Bangla language. A web application to demonstrate our tool is available at http://bit.ly/signdigits2banglaspeech.
An antigen is a protein capable of triggering an effective immune system response. Protective ant... more An antigen is a protein capable of triggering an effective immune system response. Protective antigens are the ones that can invoke specific and enhanced adaptive immune response to subsequent exposure to the specific pathogen or related organisms. Such proteins are therefore of immense importance in vaccine preparation and drug design. However, the laboratory experiments to isolate and identify antigens from a microbial pathogen are expensive, time consuming and often unsuccessful. This is why Reverse Vaccinology has become the modern trend of vaccine search, where computational methods are first applied to predict protective anti-* Corresponding author.
A DNA-binding protein (DNA-BP) is a protein that can bind and interact with a DNA. Identification... more A DNA-binding protein (DNA-BP) is a protein that can bind and interact with a DNA. Identification of DNA-BPs using experimental methods is expensive as well as time consuming. As such, fast and accurate computational methods are sought for predicting whether a protein can bind with a DNA or not. In this paper, we focus on building a new computational model to identify DNA-BPs in an efficient and accurate way. Our model extracts meaningful information directly from the protein sequences, without any dependence on functional domain or structural information. After feature extraction, we have employed Random Forest (RF) model to rank the features. Afterwards, we have used Recursive Feature Elimination (RFE) method to extract an optimal set of features and trained a prediction model using Support Vector Machine (SVM) with linear kernel. Our proposed method, named as DNA-binding Protein Prediction model using Chou's general PseAAC (DPP-PseAAC), demonstrates superior performance compa...
Glycation is chemical reaction by which sugar molecule bonds with a protein without the help of e... more Glycation is chemical reaction by which sugar molecule bonds with a protein without the help of enzymes. This is often cause to many diseases and therefore the knowledge about glycation is very important. In this paper, we present iProtGly-SS, a protein lysine glycation site identification method based on features extracted from sequence and secondary structural information. In the experiments, we found the best feature groups combination: Amino Acid Composition, Secondary Structure Motifs and Polarity. We used support vector machine classifier to train our model and used an optimal set of features using a group based forward feature selection technique. On standard benchmark datasets, our method is able to significantly outperform existing methods for glycation prediction. A web server for iProtGly-SS is implemented and publicly available to use: http://brl.uiu.ac.bd/iprotgly-ss/. This article is protected by copyright. All rights reserved.
Bacteriophage proteins are viruses that can significantly impact on the functioning of bacteria a... more Bacteriophage proteins are viruses that can significantly impact on the functioning of bacteria and can be used in phage based therapy. The functioning of Bacteriophage in the host bacteria depends on its location in those host cells. It is very important to know the subcellular location of the phage proteins in a host cell in order to understand their working mechanism. In this paper, we propose iPHLoc-ES, a prediction method for subcellular localization of bacteriophage proteins. We aim to solve two problems: discriminating between host located and non-host located phage proteins and discriminating between the locations of host located protein in a host cell (membrane or cytoplasm). To do this, we extract sets of evolutionary and structural features of phage protein and employ Support Vector Machine (SVM) as our classifier. We also use recursive feature elimination (RFE) to reduce the number of features for effective prediction. On standard dataset using standard evaluation criteria, our method significantly outperforms the state-of-the-art predictor. iPHLoc-ES is readily available to use as a standalone tool from: https:// github.com/swakkhar/iPHLoc-ES/ and as a web application from: http://brl.uiu.ac.bd/iPHLoc-ES/ .
2017 20th International Conference of Computer and Information Technology (ICCIT)
VANET (Vehicular Ad-hoc NETwork) is a network architecture designed to provide road safety, impro... more VANET (Vehicular Ad-hoc NETwork) is a network architecture designed to provide road safety, improve transport efficiency, and reduce traffic congestion by combining vehicles with high mobility and fixed road-side units with or without Vehicular Cloud. Connected vehicles aided with sensors need to be authenticated before transmitting message. Two major problems in existing state-of-the-art schemes which are redundant authentication of vehicles with each RSUs it passes through and authenticating each message by trusted authority with large cryptographic overheads. In this paper we proposed an authentication scheme which exploits a very new technique of successive message passing among different RSUs (Road-side Units) to verify vehicles which are already authenticated. In our scheme, RSUs share authentication related information of vehicles with the help of newly proposed RSUs detection algorithm. In addition to that, messages from vehicles are verified with assistance from RSUs using symmetric key based Hashed Message Authentication Code (HMAC) signatures. This results in remarkably reduced cryptographic overheads and communication delay occurred during authentication of vehicles and messages in VANETs. Extensive performance evaluations and comparison with state-of-the-art schemes will show how our scheme provides exceptionally improved performance for VANETs.
2017 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE), 2017
With the advancement of Information technologies and applications, a copious amount of data is ge... more With the advancement of Information technologies and applications, a copious amount of data is generated, which attracts both the research community to utilize this information for extracting knowledge and the industry for developing the knowledge-based system. Visualization of data, pattern mining from datasets and analyzing data drift for the different features are three highly used applications of machine learning and data science fields. A generic web-based tool integrated with such features will provide prodigious support for preprocessing the dataset and thus extracting accurate information. In this work, we propose such a data visualization tool, named VIM, which is a web-based comprehensive tool for generic data visualization, data preprocessing and mining suitable knowledge with drift analysis of data. Given a dataset, it can envisage the distribution of data with convenient statistical diagrams for different selected features. Moreover, users can employ VIM to generate association rules by selecting multiple features. We have developed VIM using Python Django framework and GraphLab library. We have deployed this tool to make this publicly usable, which can be accessed at http://210.4.73.237:9999/
Advances in Intelligent Systems and Computing, 2018
In phage therapy, bacteriophage proteins are used to kill bacteria that cause infection. The know... more In phage therapy, bacteriophage proteins are used to kill bacteria that cause infection. The knowledge of the location of the bacteriophage proteins plays an important role here. In this paper, we propose a supervised learning based method to predict the locations of bacteriophage proteins. First, we address the problem of predicting whether a bacteriophage is extracellular or located in the host cell. Second, we also address the subcellular location prediction problem of the phage proteins. For the host located proteins, the proteins could either be located in cell membrane or in the cytoplasm. We have successfully used deep feed-forward neural network on a standard training dataset and achieved good results for both of the prediction problems. Our method uses an optimal set of features for classification and achieves 87.7% and 98.5% accuracy for two of the prediction problems which is 3.5% and 6.3% improved than the previous state-of-the-art results achieved for these problems, re...
A field experiment was conducted during the winter season (rabi) of 1991-92, 1993-93 and 1993-94 ... more A field experiment was conducted during the winter season (rabi) of 1991-92, 1993-93 and 1993-94 to study the performance of indian mustard [Brassica junced (L.) Czernj. & Cosson] + lentil (Lens culinaris Medikus) and gram (Cicer arietinum L.) intercropping for yield. The highest seed of indian mustard and lentil was obtained with N,P and K @ 80, 17.5 and 33.3 kg/ha from 2.2 and 1.1 row ration respectively. Intercropping of indian mustard and lentil with a fertilizer does of 80 kg N/ha, 17.5 kg P/ha and 33.3 kg K/ha recorded higher land-equivalent ratio and monetary advantage from 1:1 row ratio during 1991-92 and 1992-93 and from 2:2 row ratio during 1993-94.
Recent advancements in the field of computer vision with the help of deep neural networks have le... more Recent advancements in the field of computer vision with the help of deep neural networks have led us to explore and develop many existing challenges that were once unattended due to the lack of necessary technologies. Hand Sign/Gesture Recognition is one of the significant areas where the deep neural network is making a substantial impact. In the last few years, a large number of researches has been conducted to recognize hand signs and hand gestures, which we aim to extend to our mother-tongue, Bangla (also known as Bengali). The primary goal of our work is to make an automated tool to aid the people who are unable to speak. We developed a system that automatically detects hand sign based digits and speaks out the result in Bangla language. According to the report of the World Health Organization (WHO), 15% of people in the world live with some kind of disabilities. Among them, individuals with communication impairment such as speech disabilities experience substantial barrier in social interaction. The proposed system can be invaluable to mitigate such a barrier. The core of the system is built with a deep learning model which is based on convolutional neural networks (CNN). The model classifies hand sign based digits with 92% accuracy over validation data which ensures it a highly trustworthy system. Upon classification of the digits, the resulting output is fed to the text to speech engine and the translator unit eventually which generates audio output in Bangla language. A web application to demonstrate our tool is available at http://bit.ly/signdigits2banglaspeech.
An antigen is a protein capable of triggering an effective immune system response. Protective ant... more An antigen is a protein capable of triggering an effective immune system response. Protective antigens are the ones that can invoke specific and enhanced adaptive immune response to subsequent exposure to the specific pathogen or related organisms. Such proteins are therefore of immense importance in vaccine preparation and drug design. However, the laboratory experiments to isolate and identify antigens from a microbial pathogen are expensive, time consuming and often unsuccessful. This is why Reverse Vaccinology has become the modern trend of vaccine search, where computational methods are first applied to predict protective anti-* Corresponding author.
A DNA-binding protein (DNA-BP) is a protein that can bind and interact with a DNA. Identification... more A DNA-binding protein (DNA-BP) is a protein that can bind and interact with a DNA. Identification of DNA-BPs using experimental methods is expensive as well as time consuming. As such, fast and accurate computational methods are sought for predicting whether a protein can bind with a DNA or not. In this paper, we focus on building a new computational model to identify DNA-BPs in an efficient and accurate way. Our model extracts meaningful information directly from the protein sequences, without any dependence on functional domain or structural information. After feature extraction, we have employed Random Forest (RF) model to rank the features. Afterwards, we have used Recursive Feature Elimination (RFE) method to extract an optimal set of features and trained a prediction model using Support Vector Machine (SVM) with linear kernel. Our proposed method, named as DNA-binding Protein Prediction model using Chou's general PseAAC (DPP-PseAAC), demonstrates superior performance compa...
Glycation is chemical reaction by which sugar molecule bonds with a protein without the help of e... more Glycation is chemical reaction by which sugar molecule bonds with a protein without the help of enzymes. This is often cause to many diseases and therefore the knowledge about glycation is very important. In this paper, we present iProtGly-SS, a protein lysine glycation site identification method based on features extracted from sequence and secondary structural information. In the experiments, we found the best feature groups combination: Amino Acid Composition, Secondary Structure Motifs and Polarity. We used support vector machine classifier to train our model and used an optimal set of features using a group based forward feature selection technique. On standard benchmark datasets, our method is able to significantly outperform existing methods for glycation prediction. A web server for iProtGly-SS is implemented and publicly available to use: http://brl.uiu.ac.bd/iprotgly-ss/. This article is protected by copyright. All rights reserved.
Bacteriophage proteins are viruses that can significantly impact on the functioning of bacteria a... more Bacteriophage proteins are viruses that can significantly impact on the functioning of bacteria and can be used in phage based therapy. The functioning of Bacteriophage in the host bacteria depends on its location in those host cells. It is very important to know the subcellular location of the phage proteins in a host cell in order to understand their working mechanism. In this paper, we propose iPHLoc-ES, a prediction method for subcellular localization of bacteriophage proteins. We aim to solve two problems: discriminating between host located and non-host located phage proteins and discriminating between the locations of host located protein in a host cell (membrane or cytoplasm). To do this, we extract sets of evolutionary and structural features of phage protein and employ Support Vector Machine (SVM) as our classifier. We also use recursive feature elimination (RFE) to reduce the number of features for effective prediction. On standard dataset using standard evaluation criteria, our method significantly outperforms the state-of-the-art predictor. iPHLoc-ES is readily available to use as a standalone tool from: https:// github.com/swakkhar/iPHLoc-ES/ and as a web application from: http://brl.uiu.ac.bd/iPHLoc-ES/ .
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