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Papers by Mir Riyanul Islam

Transportation Research Procedia

CERN European Organization for Nuclear Research - Zenodo, Oct 31, 2022

CERN European Organization for Nuclear Research - Zenodo, Aug 25, 2022

Applied Sciences, 2022

Artificial intelligence (AI) and machine learning (ML) have recently been radically improved and ... more Artificial intelligence (AI) and machine learning (ML) have recently been radically improved and are now being employed in almost every application domain to develop automated or semi-automated systems. To facilitate greater human acceptability of these systems, explainable artificial intelligence (XAI) has experienced significant growth over the last couple of years with the development of highly accurate models but with a paucity of explainability and interpretability. The literature shows evidence from numerous studies on the philosophy and methodologies of XAI. Nonetheless, there is an evident scarcity of secondary studies in connection with the application domains and tasks, let alone review studies following prescribed guidelines, that can enable researchers’ understanding of the current trends in XAI, which could lead to future research for domain- and application-specific method development. Therefore, this paper presents a systematic literature review (SLR) on the recent de...

Applied Sciences, 2022

Air Traffic Management (ATM) will be more complex in the coming decades due to the growth and inc... more Air Traffic Management (ATM) will be more complex in the coming decades due to the growth and increased complexity of aviation and has to be improved in order to maintain aviation safety. It is agreed that without significant improvement in this domain, the safety objectives defined by international organisations cannot be achieved and a risk of more incidents/accidents is envisaged. Nowadays, computer science plays a major role in data management and decisions made in ATM. Nonetheless, despite this, Artificial Intelligence (AI), which is one of the most researched topics in computer science, has not quite reached end users in ATM domain. In this paper, we analyse the state of the art with regards to usefulness of AI within aviation/ATM domain. It includes research work of the last decade of AI in ATM, the extraction of relevant trends and features, and the extraction of representative dimensions. We analysed how the general and ATM eXplainable Artificial Intelligence (XAI) works, a...

2021 8th International Conference on Soft Computing & Machine Intelligence (ISCMI)

In the pursuit of reducing traffic accidents, drivers’ mental workload (MWL) has been considered ... more In the pursuit of reducing traffic accidents, drivers’ mental workload (MWL) has been considered as one of the vital aspects. To measure MWL in different driving situations Electroencephalography (EEG) of the drivers has been studied intensely. However, in the literature, mostly, manual analytic methods are applied to extract and select features from the EEG signals to quantify drivers’ MWL. Nevertheless, the amount of time and effort required to perform prevailing feature extraction techniques leverage the need for automated feature extraction techniques. This work investigates deep learning (DL) algorithm to extract and select features from the EEG signals during naturalistic driving situations. Here, to compare the DL based and traditional feature extraction techniques, a number of classifiers have been deployed. Results have shown that the highest value of area under the curve of the receiver operating characteristic (AUC-ROC) is 0.94, achieved using the features extracted by co...

This report presents a research study plan on human subjects – the influence of stress and alcoho... more This report presents a research study plan on human subjects – the influence of stress and alcohol in simulated traffic situations under an H2020 project named SIMUSAFE. This research study focuses on road-users’, i.e., car drivers, motorcyclists, bicyclists and pedestrians, behaviour in relation to retrospective studies, where interaction between the users are considered. Here, the study includes sample size, inclusion/exclusion criteria, detailed study plan, protocols, potential test scenarios and all related ethical issues. The study plan has been included in a national ethics application and received approval for implementation.

Explainability of intelligent systems in health-care domain is still in its initial state. Recent... more Explainability of intelligent systems in health-care domain is still in its initial state. Recently, more efforts are made to leverage machine learning in solving causal inference problems of disease diagnosis, prediction and treatments. This research work presents an ontology based causal inference model for hypothyroid disease diagnosis using case-based reasoning. The effectiveness of the proposed method is demonstrated with an example from hypothyroid disease domain. Here, the domain knowledge is mapped into an expert defined ontology and causal inference is performed based on this domain-specific ontology. The goal is to incorporate this causal inference model in traditional case-based reasoning cycle enabling explanation for each solved problem. Finally, a mechanism is defined to deduce explanation for a solution to a problem case from the combined causal statements of similar cases. The initial result shows that case-based reasoning can retrieve relevant cases with 95% accuracy.

2017 IEEE Region 10 Humanitarian Technology Conference (R10-HTC)

YouTube is the most popular video contents sharing platform around the world. As a consequence, Y... more YouTube is the most popular video contents sharing platform around the world. As a consequence, YouTube has become one of the most preferred choices to the movie producers and studios for connecting/communicating with their potential viewers through sharing trailers and teasers. Data regarding the trailers of a movie from YouTube can provide useful insights for predicting the gross income of movies. In this paper, we have prepared a dataset of 7988 movie trailers from YouTube. The dataset contains different attributes like opening income, number of views, number of likes, number of dislikes, number of comments. We prepared two prediction models and applied four regression techniques to find out the most suitable technique for predicting the gross income of a movie. The comparative analysis has depicted that linear regression is the most suitable method regarding the prediction of movies gross income using these attributes. Furthermore, we have provided future research issues from where our work has ended.

Brain Sciences

Analysis of physiological signals, electroencephalography more specifically, is considered a very... more Analysis of physiological signals, electroencephalography more specifically, is considered a very promising technique to obtain objective measures for mental workload evaluation, however, it requires a complex apparatus to record, and thus, with poor usability in monitoring in-vehicle drivers’ mental workload. This study proposes a methodology of constructing a novel mutual information-based feature set from the fusion of electroencephalography and vehicular signals acquired through a real driving experiment and deployed in evaluating drivers’ mental workload. Mutual information of electroencephalography and vehicular signals were used as the prime factor for the fusion of features. In order to assess the reliability of the developed feature set mental workload score prediction, classification and event classification tasks were performed using different machine learning models. Moreover, features extracted from electroencephalography were used to compare the performance. In the pre...

IEEE Region 10 Humanitarian Technology Conference, 2017

Semantic web can be seen as an extension of the world wide web which offers a common structure th... more Semantic web can be seen as an extension of the world wide web which offers a common structure that permits data to be pooled and reused across applications, enterprises, and community limitations. Some researchers defined it as a web of formal data. On the other hand, ontologies define the concepts as well as the relationships among them to formally represent a specific domain of interest. They are the elementary unit for inference techniques on the Semantic Web. When ontology contains instances then it becomes a knowledge base. In Bangladesh Tourism has become a major area for improvement because often the information found on the web is not organized and consistent enough. This paper presents OnTraNetBD, a knowledge base containing the formal relationship among the tourist attractions and the other complementary elements of travelling. The main purpose of this knowledge base is to present the travel information to any end users or machines which will facilitate both to understand the domain information and use it according to the individual requirements. Moreover, OnTraNetBD is furnished with such a design so that it can be mapped with other travel ontology or knowledge base to extend the information domain.

1st International Conference on Electrical Engineering and Information Communication Technology (ICEEICT 2014), Apr 10, 2014

The sudden eruption of sentiment analysis and opinion mining has opened new possibilities to impr... more The sudden eruption of sentiment analysis and opinion mining has opened new possibilities to improve our information gathering interests. We are always keen to know what others say about the devices or applications we are going to use. Its observed that sometimes the numeric rating has vast difference than the reviews given by the users. To remove this ambiguity a unified rating system has been proposed here. The starred rating and a generated numeric polarity of the reviews are combined to generate the final rating. The proposition is based on sentiment analysis and an optimized probabilistic approach described by a group of researchers. The approach is proved for
its efficiency in a diverse corpus of writings where the targets are of different categories.

The Second International Conference on Education Technologies and Computers (ICETC2015)

Today the number of students in every educational institution increased a lot. As a result more c... more Today the number of students in every educational institution increased a lot. As a result more courses are to be offered by the institutions and employ more teachers as well. Day by day due the increase of the courses and course teachers the assigning of teachers to respective courses has become time worthy and difficult.This raises a problem in the educational sector. Till now a lot of researches have been carried out to find reasonable algorithms for efficient automated processes. In this paper we tried to solve the problem of assigning teachers to respective courses. The problem arises when a timetable is to be prepared without overlapping the class timings. We have developed an algorithm for automated system based on searching and sorting. Moreover the process will advance with two separate lists of teachers and course. As an additional constraint we have considered the preferred course for each teacher. The final output will be a complete time table. The algorithm was designed on the basis of a simulation with a set of teachers and class schedules of a University. The simulation produced solutions that can be favorably compared with the solutions proposed by the experts.

Thesis Chapters by Mir Riyanul Islam

Ontologies are the essentials tools of intelligent systems that are used with different purposes ... more Ontologies are the essentials tools of intelligent systems that are used with different purposes and with various modalities in diverse domains and communities. In Bangladesh Tourism and Travel has become a significant area for improvement and digitalization. The travel domain of Bangladesh is diversely extended. In this thesis work we have accumulated the information about the tourism of Bangladesh in OnTraNetBD. OnTraNetBD is a classification ontology containing the relationship among the tourist attractions and the other complementary elements of travelling. Furthermore, it contains a relational database developed on the basis of the concepts and relations of OnTraNetBD. This ontology can present the whole travel domain to any end users or machines in a hierarchical fashion which will facilitate the users and machines to understand the domain information and use according to the individual requirement. Moreover, OnTraNetBD is furnished with such design that can be mapped with other ontologies for gathering more information to extend the domain of interest.

Transportation Research Procedia

CERN European Organization for Nuclear Research - Zenodo, Oct 31, 2022

CERN European Organization for Nuclear Research - Zenodo, Aug 25, 2022

Applied Sciences, 2022

Artificial intelligence (AI) and machine learning (ML) have recently been radically improved and ... more Artificial intelligence (AI) and machine learning (ML) have recently been radically improved and are now being employed in almost every application domain to develop automated or semi-automated systems. To facilitate greater human acceptability of these systems, explainable artificial intelligence (XAI) has experienced significant growth over the last couple of years with the development of highly accurate models but with a paucity of explainability and interpretability. The literature shows evidence from numerous studies on the philosophy and methodologies of XAI. Nonetheless, there is an evident scarcity of secondary studies in connection with the application domains and tasks, let alone review studies following prescribed guidelines, that can enable researchers’ understanding of the current trends in XAI, which could lead to future research for domain- and application-specific method development. Therefore, this paper presents a systematic literature review (SLR) on the recent de...

Applied Sciences, 2022

Air Traffic Management (ATM) will be more complex in the coming decades due to the growth and inc... more Air Traffic Management (ATM) will be more complex in the coming decades due to the growth and increased complexity of aviation and has to be improved in order to maintain aviation safety. It is agreed that without significant improvement in this domain, the safety objectives defined by international organisations cannot be achieved and a risk of more incidents/accidents is envisaged. Nowadays, computer science plays a major role in data management and decisions made in ATM. Nonetheless, despite this, Artificial Intelligence (AI), which is one of the most researched topics in computer science, has not quite reached end users in ATM domain. In this paper, we analyse the state of the art with regards to usefulness of AI within aviation/ATM domain. It includes research work of the last decade of AI in ATM, the extraction of relevant trends and features, and the extraction of representative dimensions. We analysed how the general and ATM eXplainable Artificial Intelligence (XAI) works, a...

2021 8th International Conference on Soft Computing & Machine Intelligence (ISCMI)

In the pursuit of reducing traffic accidents, drivers’ mental workload (MWL) has been considered ... more In the pursuit of reducing traffic accidents, drivers’ mental workload (MWL) has been considered as one of the vital aspects. To measure MWL in different driving situations Electroencephalography (EEG) of the drivers has been studied intensely. However, in the literature, mostly, manual analytic methods are applied to extract and select features from the EEG signals to quantify drivers’ MWL. Nevertheless, the amount of time and effort required to perform prevailing feature extraction techniques leverage the need for automated feature extraction techniques. This work investigates deep learning (DL) algorithm to extract and select features from the EEG signals during naturalistic driving situations. Here, to compare the DL based and traditional feature extraction techniques, a number of classifiers have been deployed. Results have shown that the highest value of area under the curve of the receiver operating characteristic (AUC-ROC) is 0.94, achieved using the features extracted by co...

This report presents a research study plan on human subjects – the influence of stress and alcoho... more This report presents a research study plan on human subjects – the influence of stress and alcohol in simulated traffic situations under an H2020 project named SIMUSAFE. This research study focuses on road-users’, i.e., car drivers, motorcyclists, bicyclists and pedestrians, behaviour in relation to retrospective studies, where interaction between the users are considered. Here, the study includes sample size, inclusion/exclusion criteria, detailed study plan, protocols, potential test scenarios and all related ethical issues. The study plan has been included in a national ethics application and received approval for implementation.

Explainability of intelligent systems in health-care domain is still in its initial state. Recent... more Explainability of intelligent systems in health-care domain is still in its initial state. Recently, more efforts are made to leverage machine learning in solving causal inference problems of disease diagnosis, prediction and treatments. This research work presents an ontology based causal inference model for hypothyroid disease diagnosis using case-based reasoning. The effectiveness of the proposed method is demonstrated with an example from hypothyroid disease domain. Here, the domain knowledge is mapped into an expert defined ontology and causal inference is performed based on this domain-specific ontology. The goal is to incorporate this causal inference model in traditional case-based reasoning cycle enabling explanation for each solved problem. Finally, a mechanism is defined to deduce explanation for a solution to a problem case from the combined causal statements of similar cases. The initial result shows that case-based reasoning can retrieve relevant cases with 95% accuracy.

2017 IEEE Region 10 Humanitarian Technology Conference (R10-HTC)

YouTube is the most popular video contents sharing platform around the world. As a consequence, Y... more YouTube is the most popular video contents sharing platform around the world. As a consequence, YouTube has become one of the most preferred choices to the movie producers and studios for connecting/communicating with their potential viewers through sharing trailers and teasers. Data regarding the trailers of a movie from YouTube can provide useful insights for predicting the gross income of movies. In this paper, we have prepared a dataset of 7988 movie trailers from YouTube. The dataset contains different attributes like opening income, number of views, number of likes, number of dislikes, number of comments. We prepared two prediction models and applied four regression techniques to find out the most suitable technique for predicting the gross income of a movie. The comparative analysis has depicted that linear regression is the most suitable method regarding the prediction of movies gross income using these attributes. Furthermore, we have provided future research issues from where our work has ended.

Brain Sciences

Analysis of physiological signals, electroencephalography more specifically, is considered a very... more Analysis of physiological signals, electroencephalography more specifically, is considered a very promising technique to obtain objective measures for mental workload evaluation, however, it requires a complex apparatus to record, and thus, with poor usability in monitoring in-vehicle drivers’ mental workload. This study proposes a methodology of constructing a novel mutual information-based feature set from the fusion of electroencephalography and vehicular signals acquired through a real driving experiment and deployed in evaluating drivers’ mental workload. Mutual information of electroencephalography and vehicular signals were used as the prime factor for the fusion of features. In order to assess the reliability of the developed feature set mental workload score prediction, classification and event classification tasks were performed using different machine learning models. Moreover, features extracted from electroencephalography were used to compare the performance. In the pre...

IEEE Region 10 Humanitarian Technology Conference, 2017

Semantic web can be seen as an extension of the world wide web which offers a common structure th... more Semantic web can be seen as an extension of the world wide web which offers a common structure that permits data to be pooled and reused across applications, enterprises, and community limitations. Some researchers defined it as a web of formal data. On the other hand, ontologies define the concepts as well as the relationships among them to formally represent a specific domain of interest. They are the elementary unit for inference techniques on the Semantic Web. When ontology contains instances then it becomes a knowledge base. In Bangladesh Tourism has become a major area for improvement because often the information found on the web is not organized and consistent enough. This paper presents OnTraNetBD, a knowledge base containing the formal relationship among the tourist attractions and the other complementary elements of travelling. The main purpose of this knowledge base is to present the travel information to any end users or machines which will facilitate both to understand the domain information and use it according to the individual requirements. Moreover, OnTraNetBD is furnished with such a design so that it can be mapped with other travel ontology or knowledge base to extend the information domain.

1st International Conference on Electrical Engineering and Information Communication Technology (ICEEICT 2014), Apr 10, 2014

The sudden eruption of sentiment analysis and opinion mining has opened new possibilities to impr... more The sudden eruption of sentiment analysis and opinion mining has opened new possibilities to improve our information gathering interests. We are always keen to know what others say about the devices or applications we are going to use. Its observed that sometimes the numeric rating has vast difference than the reviews given by the users. To remove this ambiguity a unified rating system has been proposed here. The starred rating and a generated numeric polarity of the reviews are combined to generate the final rating. The proposition is based on sentiment analysis and an optimized probabilistic approach described by a group of researchers. The approach is proved for
its efficiency in a diverse corpus of writings where the targets are of different categories.

The Second International Conference on Education Technologies and Computers (ICETC2015)

Today the number of students in every educational institution increased a lot. As a result more c... more Today the number of students in every educational institution increased a lot. As a result more courses are to be offered by the institutions and employ more teachers as well. Day by day due the increase of the courses and course teachers the assigning of teachers to respective courses has become time worthy and difficult.This raises a problem in the educational sector. Till now a lot of researches have been carried out to find reasonable algorithms for efficient automated processes. In this paper we tried to solve the problem of assigning teachers to respective courses. The problem arises when a timetable is to be prepared without overlapping the class timings. We have developed an algorithm for automated system based on searching and sorting. Moreover the process will advance with two separate lists of teachers and course. As an additional constraint we have considered the preferred course for each teacher. The final output will be a complete time table. The algorithm was designed on the basis of a simulation with a set of teachers and class schedules of a University. The simulation produced solutions that can be favorably compared with the solutions proposed by the experts.

Ontologies are the essentials tools of intelligent systems that are used with different purposes ... more Ontologies are the essentials tools of intelligent systems that are used with different purposes and with various modalities in diverse domains and communities. In Bangladesh Tourism and Travel has become a significant area for improvement and digitalization. The travel domain of Bangladesh is diversely extended. In this thesis work we have accumulated the information about the tourism of Bangladesh in OnTraNetBD. OnTraNetBD is a classification ontology containing the relationship among the tourist attractions and the other complementary elements of travelling. Furthermore, it contains a relational database developed on the basis of the concepts and relations of OnTraNetBD. This ontology can present the whole travel domain to any end users or machines in a hierarchical fashion which will facilitate the users and machines to understand the domain information and use according to the individual requirement. Moreover, OnTraNetBD is furnished with such design that can be mapped with other ontologies for gathering more information to extend the domain of interest.