Information ecosystem today is overwhelmed by unprecedented quantity of data on versatile topics ... more Information ecosystem today is overwhelmed by unprecedented quantity of data on versatile topics are with varied quality. However, the quality of information disseminated in the field of medicine has been questioned as the negative health consequences of health misinformation can be life threatening. There is currently no generic automated tool for evaluating the quality of online health information spanned over broad range. To address this gap, in this paper, we applied data mining approach to automatically assess the quality of online health articles based on 10 quality criteria. We have prepared a labelled dataset with 53012 features and applied different feature selection methods to identify the best feature subset with which our trained classifier achieved an accuracy of 84% − 90% varied over 10 criteria. Our semantic analysis of features shows the underpinning associations between the selected features & assessment criteria and further rationalize our assessment approach. Our findings will help in identifying high quality health articles and thus aiding users in shaping their opinion to make right choice while picking health related help from online.
The rapid dissemination of health misinformation poses an increasing risk to public health. To be... more The rapid dissemination of health misinformation poses an increasing risk to public health. To best understand the way of combating health misinformation, it is important to acknowledge how the fundamental characteristics of misinformation differ from domain to domain. This paper presents a pathway towards domain-specific characterization of misinformation so that we can address the concealed behavior of health misinformation compared to others and take proper initiative accordingly for combating it. With this aim, we have mentioned several possible approaches to identify discriminating features of medical misinformation from other types of misinformation. Thereafter, we briefly propose a research plan followed by possible challenges to meet up. The findings of the proposed research idea will provide new directions to the misinformation research community.
Video coding using dynamic background frame achieves better compression compared to the tradition... more Video coding using dynamic background frame achieves better compression compared to the traditional techniques by encoding background and foreground separately. This process reduces coding bits for the overall frame significantly; however, encoding background still requires many bits that can be compressed further for achieving better coding efficiency. The cuboid coding framework has been proven to be one of the most effective methods of image compression which exploits homogeneous pixel correlation within a frame and has better alignment with object boundary compared to traditional block-based coding. In a video sequence, the cuboid-based frame partitioning varies with the changes of the foreground. However, since the background remains static for a group of pictures, the cuboid coding exploits better spatial pixel homogeneity. In this work, the impact of cuboid coding on the background frame for high-resolution videos (Ultra-High-Definition (UHD) and 360-degree videos) is investigated using the multilayer framework of SHVC. After the cuboid partitioning, the method of coarse frame generation has been improved with a novel idea by keeping human-visual sensitive information. Unlike the traditional SHVC scheme, in the proposed method, cuboid coded background and the foreground are encoded in separate layers in an implicit manner. Simulation results show that the proposed video coding method achieves an average BD-Rate reduction of 26.69% and BD-PSNR gain of 1.51 dB against SHVC with significant encoding time reduction for both UHD and 360 videos. It also achieves an average of 13.88% BD-Rate reduction and 0.78 dB BD-PSNR gain compared to the existing relevant method proposed by X. HoangVan [18].
IEEE Journal of Biomedical and Health Informatics, 2021
Information ecosystem today is overwhelmed by unprecedented quantity of data on versatile topics ... more Information ecosystem today is overwhelmed by unprecedented quantity of data on versatile topics are with varied quality. However, the quality of information disseminated in the field of medicine has been questioned as the negative health consequences of health misinformation can be life threatening. There is currently no generic automated tool for evaluating the quality of online health information spanned over broad range. To address this gap, in this paper, we applied data mining approach to automatically assess the quality of online health articles based on 10 quality criteria. We have prepared a labelled dataset with 53012 features and applied different feature selection methods to identify the best feature subset with which our trained classifier achieved an accuracy of 84% − 90% varied over 10 criteria. Our semantic analysis of features shows the underpinning associations between the selected features & assessment criteria and further rationalize our assessment approach. Our findings will help in identifying high quality health articles and thus aiding users in shaping their opinion to make right choice while picking health related help from online.
Rapid developments in the fields of information and communication technology and microelectronics... more Rapid developments in the fields of information and communication technology and microelectronics allowed seamless interconnection among various devices letting them to communicate with each other. This technological integration opened up new possibilities in many disciplines including healthcare and well-being. With the aim of reducing healthcare costs and providing improved and reliable services, several healthcare frameworks based on Internet of Healthcare Things (IoHT) have been developed. However, due to the critical and heterogeneous nature of healthcare data, maintaining high quality of service (QoS)-in terms of faster responsiveness and data-specific complex analytics-has always been the main challenge in designing such systems. Addressing these issues, this paper proposes a five-layered heterogeneous mist, fog, and cloud-based IoHT framework capable of efficiently handling and routing (near-)real-time as well as offline/batch mode data. Also, by employing software defined networking and link adaptation-based load balancing, the framework ensures optimal resource allocation and efficient resource utilization. The results, obtained by simulating the framework, indicate that the designed network via its various components can achieve high QoS, with reduced end-to-end latency and packet drop rate, which is essential for developing next generation e-healthcare systems.
Current developments in nanotechnology make electromagnetic communication possible at the nanosca... more Current developments in nanotechnology make electromagnetic communication possible at the nanoscale for applications involving body sensor networks (BSNs). This specialized branch of wireless sensor networks, drawing attention from diverse fields, such as engineering, medicine, biology, physics, and computer science, has emerged as an important research area contributing to medical treatment, social welfare, and sports. The concept is based on the interaction of integrated nanoscale machines by means of wireless communications. One key hurdle for advancing nanocommunications is the lack of an apposite networking protocol to address the upcoming needs of the nanonetworks. Recently, some key challenges have been identified, such as nanonodes with extreme energy constraints, limited computational capabilities, terahertz frequency bands with limited transmission range, and so on, in designing protocols for wireless nanosensor networks. This work proposes an improved performance scheme of nanocommunication over terahertz bands for wireless BSNs making it suitable for smart e-health applications. The scheme containsa new energy-efficient forwarding routine for electromagnetic communication in wireless nanonetworks consisting of hybrid clusters with centralized scheduling; a model designed for channel behavior taking into account the aggregated impact of molecular absorption, spreading loss, and shadowing; and an energy model for energy harvesting and consumption. The outage probability is derived for both single and multilinks and extended to determine the outage capacity. The outage probability for a multilink is derived using a cooperative fusion technique at a predefined fusion node. Simulated using a nano-sim simulator, performance of the proposed model has been evaluated for energy efficiency, outage capacity, and outage probability. The results demonstrate the efficiency of the proposed scheme through maximized energy utilization in both single and multihop communications; multisensor fusion at the fusion node enhances the link quality of the transmission. INDEX TERMS EM communication, terahertz band, nano cluster, energy harvesting.
2015 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE), 2015
In this work, a useful synergy between nano technology and electromagnetic communication among na... more In this work, a useful synergy between nano technology and electromagnetic communication among nano sensors using Terahertz Band has been considered. A cluster based routing scheme has been proposed for Body Area Network using wireless channel in Terahertz band to facilitate health care application. The joint impact of shadowing, molecular absorption attenuation and spreading losses have been considered to calculate total path loss. Monte Carlo simulations have been performed in Matlab. Simulation shows that in term of outage probability, proposed scheme outperforms the random forwarding scheme.
2015 IEEE International Conference on Telecommunications and Photonics (ICTP), 2015
This paper presents an adaptive route selection algorithm that can be employed in the Cognitive C... more This paper presents an adaptive route selection algorithm that can be employed in the Cognitive Cooperative Network (CCN). Here each Cognitive node (CN), also called Secondary User (SU), communicates with other SUs and has the capability to change its transmission and receiption efficiency without interfering Primary User (PU). In this paper, we propose a modified Bat Algorithm for selecting best relay that is able to achieve considerable performance gain in CCN. The aim of the proposed approach is attaining a best link to send data, lesser packet delivery time, and higher throughput. For achieving lesser transmission time and better throughput we use Digital Network Coding (DNC) scheme along with Decode and Forward (DF) relaying protocol. The DF protocol with modified Bat algorithm improved CCN's routing efficiency. Monte Carlo simulation is used to evaluate the performance and obtained results are compared with other protocols and performance evaluation reveals that network performance has improved in throughput.
2015 2nd International Conference on Electrical Information and Communication Technologies (EICT), 2015
The emergence of nano-electromagnetic communication becomes appealing for potential applications ... more The emergence of nano-electromagnetic communication becomes appealing for potential applications in nano-scale Body Area Network. In this work a new energy aware communication model for nano-electromagnetic communication in Terahertz Band is developed based on clustering scheme for the performance improvement of BAN. The proposed conceptual network model is used to determine channel capacity. A closed-form expression for outage probability is also derived. The approach is extended to determine outage capacity for maintaining a constant rate with a specified outage probability. Simulation shows that in term of capacity, proposed scheme outperforms the random forwarding scheme.
2014 17th International Conference on Computer and Information Technology (ICCIT), 2014
In this paper, we present the performance evaluation of coded wireless ad-hoc network for emergen... more In this paper, we present the performance evaluation of coded wireless ad-hoc network for emergency response communication. Due to the limited transmission range, a number of intermediate relaying nodes may exist between source and destination and these convey source transmission using hybrid Amplify-and-forward (AF)/Decode-and-forward (DF) protocol. All nodes contain single antenna and OFDM based Low Density Parity Check (LDPC) coded transmission is considered over Rician fading channel. The closed form bit-error-rate (BER) expression has been deduced for the proposed system. Performance evaluation reveals that BER of the LDPC coded ad-hoc network is better than that of non-coded ad-hoc network.
2014 International Conference on Electrical Engineering and Information & Communication Technology, 2014
ABSTRACT This paper presents a multi-priority and multi-path selection algorithm for heterogeneou... more ABSTRACT This paper presents a multi-priority and multi-path selection algorithm for heterogeneous traffic for wireless ad-hoc networks. The main objectives are achieving higher throughput, better resource utilization through load balancing and relinquish network congestion. The proposed algorithm has considered signal-to-interference plus noise ratio (SINR), available link bandwidth, link delay (transmission delay and queuing delay), trust value of a node and traffic class (such as real time and non-real time traffic) to select optimal path. The performance of the proposed Multi-Priority and Trusted Multi-Path Selection (MTMS) algorithm has been evaluated by OPNET Modeler 14.5 simulator. It is found that in terms of average throughput (bit/second) and link delay proposed MTMS algorithm outperforms ad-hoc on-demand distant vector (AODV) and dynamic source routing (DSR).
2020 IEEE 22nd International Workshop on Multimedia Signal Processing (MMSP), 2020
With the growth of video technologies, super-resolution videos, including 360-degree immersive vi... more With the growth of video technologies, super-resolution videos, including 360-degree immersive video has become a reality due to exciting applications such as augmented/virtual/mixed reality for better interaction and a wide-angle user-view experience of a scene compared to traditional video with narrow-focused viewing angle. The new generation video contents are bandwidth-intensive in nature due to high resolution and demand high bit rate as well as low latency delivery requirements that pose challenges in solving the bottleneck of transmission and storage burdens. There is limited optimisation space in traditional video coding schemes for improving video coding efficiency in intra-frame due to the fixed size of processing block. This paper presents a new approach for improving intra-frame coding especially at low bit rate video transmission for 360-degree video for lossy mode of HEVC. Prior to using traditional HEVC intra-prediction, this approach exploits the global redundancy of entire frame by extracting common important information using multi-level discrete wavelet transformation. This paper demonstrates that the proposed method considering only low frequency information of a frame and encoding this can outperform the HEVC standard at low bit rates. The experimental results indicate that the proposed intra-frame coding strategy achieves an average of 54.07% BD-rate reduction and 2.84 dB BD-PSNR gain for low bit rate scenario compared to the HEVC. It also achieves a significant improvement in encoding time reduction of about 66.84% on an average. Moreover, this finding also demonstrates that the existing HEVC block partitioning can be applied in the transform domain for better exploitation of information concentration as we applied HEVC on wavelet frequency domain.
Information ecosystem today is overwhelmed by unprecedented quantity of data on versatile topics ... more Information ecosystem today is overwhelmed by unprecedented quantity of data on versatile topics are with varied quality. However, the quality of information disseminated in the field of medicine has been questioned as the negative health consequences of health misinformation can be life threatening. There is currently no generic automated tool for evaluating the quality of online health information spanned over broad range. To address this gap, in this paper, we applied data mining approach to automatically assess the quality of online health articles based on 10 quality criteria. We have prepared a labelled dataset with 53012 features and applied different feature selection methods to identify the best feature subset with which our trained classifier achieved an accuracy of 84% − 90% varied over 10 criteria. Our semantic analysis of features shows the underpinning associations between the selected features & assessment criteria and further rationalize our assessment approach. Our findings will help in identifying high quality health articles and thus aiding users in shaping their opinion to make right choice while picking health related help from online.
The rapid dissemination of health misinformation poses an increasing risk to public health. To be... more The rapid dissemination of health misinformation poses an increasing risk to public health. To best understand the way of combating health misinformation, it is important to acknowledge how the fundamental characteristics of misinformation differ from domain to domain. This paper presents a pathway towards domain-specific characterization of misinformation so that we can address the concealed behavior of health misinformation compared to others and take proper initiative accordingly for combating it. With this aim, we have mentioned several possible approaches to identify discriminating features of medical misinformation from other types of misinformation. Thereafter, we briefly propose a research plan followed by possible challenges to meet up. The findings of the proposed research idea will provide new directions to the misinformation research community.
Video coding using dynamic background frame achieves better compression compared to the tradition... more Video coding using dynamic background frame achieves better compression compared to the traditional techniques by encoding background and foreground separately. This process reduces coding bits for the overall frame significantly; however, encoding background still requires many bits that can be compressed further for achieving better coding efficiency. The cuboid coding framework has been proven to be one of the most effective methods of image compression which exploits homogeneous pixel correlation within a frame and has better alignment with object boundary compared to traditional block-based coding. In a video sequence, the cuboid-based frame partitioning varies with the changes of the foreground. However, since the background remains static for a group of pictures, the cuboid coding exploits better spatial pixel homogeneity. In this work, the impact of cuboid coding on the background frame for high-resolution videos (Ultra-High-Definition (UHD) and 360-degree videos) is investigated using the multilayer framework of SHVC. After the cuboid partitioning, the method of coarse frame generation has been improved with a novel idea by keeping human-visual sensitive information. Unlike the traditional SHVC scheme, in the proposed method, cuboid coded background and the foreground are encoded in separate layers in an implicit manner. Simulation results show that the proposed video coding method achieves an average BD-Rate reduction of 26.69% and BD-PSNR gain of 1.51 dB against SHVC with significant encoding time reduction for both UHD and 360 videos. It also achieves an average of 13.88% BD-Rate reduction and 0.78 dB BD-PSNR gain compared to the existing relevant method proposed by X. HoangVan [18].
IEEE Journal of Biomedical and Health Informatics, 2021
Information ecosystem today is overwhelmed by unprecedented quantity of data on versatile topics ... more Information ecosystem today is overwhelmed by unprecedented quantity of data on versatile topics are with varied quality. However, the quality of information disseminated in the field of medicine has been questioned as the negative health consequences of health misinformation can be life threatening. There is currently no generic automated tool for evaluating the quality of online health information spanned over broad range. To address this gap, in this paper, we applied data mining approach to automatically assess the quality of online health articles based on 10 quality criteria. We have prepared a labelled dataset with 53012 features and applied different feature selection methods to identify the best feature subset with which our trained classifier achieved an accuracy of 84% − 90% varied over 10 criteria. Our semantic analysis of features shows the underpinning associations between the selected features & assessment criteria and further rationalize our assessment approach. Our findings will help in identifying high quality health articles and thus aiding users in shaping their opinion to make right choice while picking health related help from online.
Rapid developments in the fields of information and communication technology and microelectronics... more Rapid developments in the fields of information and communication technology and microelectronics allowed seamless interconnection among various devices letting them to communicate with each other. This technological integration opened up new possibilities in many disciplines including healthcare and well-being. With the aim of reducing healthcare costs and providing improved and reliable services, several healthcare frameworks based on Internet of Healthcare Things (IoHT) have been developed. However, due to the critical and heterogeneous nature of healthcare data, maintaining high quality of service (QoS)-in terms of faster responsiveness and data-specific complex analytics-has always been the main challenge in designing such systems. Addressing these issues, this paper proposes a five-layered heterogeneous mist, fog, and cloud-based IoHT framework capable of efficiently handling and routing (near-)real-time as well as offline/batch mode data. Also, by employing software defined networking and link adaptation-based load balancing, the framework ensures optimal resource allocation and efficient resource utilization. The results, obtained by simulating the framework, indicate that the designed network via its various components can achieve high QoS, with reduced end-to-end latency and packet drop rate, which is essential for developing next generation e-healthcare systems.
Current developments in nanotechnology make electromagnetic communication possible at the nanosca... more Current developments in nanotechnology make electromagnetic communication possible at the nanoscale for applications involving body sensor networks (BSNs). This specialized branch of wireless sensor networks, drawing attention from diverse fields, such as engineering, medicine, biology, physics, and computer science, has emerged as an important research area contributing to medical treatment, social welfare, and sports. The concept is based on the interaction of integrated nanoscale machines by means of wireless communications. One key hurdle for advancing nanocommunications is the lack of an apposite networking protocol to address the upcoming needs of the nanonetworks. Recently, some key challenges have been identified, such as nanonodes with extreme energy constraints, limited computational capabilities, terahertz frequency bands with limited transmission range, and so on, in designing protocols for wireless nanosensor networks. This work proposes an improved performance scheme of nanocommunication over terahertz bands for wireless BSNs making it suitable for smart e-health applications. The scheme containsa new energy-efficient forwarding routine for electromagnetic communication in wireless nanonetworks consisting of hybrid clusters with centralized scheduling; a model designed for channel behavior taking into account the aggregated impact of molecular absorption, spreading loss, and shadowing; and an energy model for energy harvesting and consumption. The outage probability is derived for both single and multilinks and extended to determine the outage capacity. The outage probability for a multilink is derived using a cooperative fusion technique at a predefined fusion node. Simulated using a nano-sim simulator, performance of the proposed model has been evaluated for energy efficiency, outage capacity, and outage probability. The results demonstrate the efficiency of the proposed scheme through maximized energy utilization in both single and multihop communications; multisensor fusion at the fusion node enhances the link quality of the transmission. INDEX TERMS EM communication, terahertz band, nano cluster, energy harvesting.
2015 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE), 2015
In this work, a useful synergy between nano technology and electromagnetic communication among na... more In this work, a useful synergy between nano technology and electromagnetic communication among nano sensors using Terahertz Band has been considered. A cluster based routing scheme has been proposed for Body Area Network using wireless channel in Terahertz band to facilitate health care application. The joint impact of shadowing, molecular absorption attenuation and spreading losses have been considered to calculate total path loss. Monte Carlo simulations have been performed in Matlab. Simulation shows that in term of outage probability, proposed scheme outperforms the random forwarding scheme.
2015 IEEE International Conference on Telecommunications and Photonics (ICTP), 2015
This paper presents an adaptive route selection algorithm that can be employed in the Cognitive C... more This paper presents an adaptive route selection algorithm that can be employed in the Cognitive Cooperative Network (CCN). Here each Cognitive node (CN), also called Secondary User (SU), communicates with other SUs and has the capability to change its transmission and receiption efficiency without interfering Primary User (PU). In this paper, we propose a modified Bat Algorithm for selecting best relay that is able to achieve considerable performance gain in CCN. The aim of the proposed approach is attaining a best link to send data, lesser packet delivery time, and higher throughput. For achieving lesser transmission time and better throughput we use Digital Network Coding (DNC) scheme along with Decode and Forward (DF) relaying protocol. The DF protocol with modified Bat algorithm improved CCN's routing efficiency. Monte Carlo simulation is used to evaluate the performance and obtained results are compared with other protocols and performance evaluation reveals that network performance has improved in throughput.
2015 2nd International Conference on Electrical Information and Communication Technologies (EICT), 2015
The emergence of nano-electromagnetic communication becomes appealing for potential applications ... more The emergence of nano-electromagnetic communication becomes appealing for potential applications in nano-scale Body Area Network. In this work a new energy aware communication model for nano-electromagnetic communication in Terahertz Band is developed based on clustering scheme for the performance improvement of BAN. The proposed conceptual network model is used to determine channel capacity. A closed-form expression for outage probability is also derived. The approach is extended to determine outage capacity for maintaining a constant rate with a specified outage probability. Simulation shows that in term of capacity, proposed scheme outperforms the random forwarding scheme.
2014 17th International Conference on Computer and Information Technology (ICCIT), 2014
In this paper, we present the performance evaluation of coded wireless ad-hoc network for emergen... more In this paper, we present the performance evaluation of coded wireless ad-hoc network for emergency response communication. Due to the limited transmission range, a number of intermediate relaying nodes may exist between source and destination and these convey source transmission using hybrid Amplify-and-forward (AF)/Decode-and-forward (DF) protocol. All nodes contain single antenna and OFDM based Low Density Parity Check (LDPC) coded transmission is considered over Rician fading channel. The closed form bit-error-rate (BER) expression has been deduced for the proposed system. Performance evaluation reveals that BER of the LDPC coded ad-hoc network is better than that of non-coded ad-hoc network.
2014 International Conference on Electrical Engineering and Information & Communication Technology, 2014
ABSTRACT This paper presents a multi-priority and multi-path selection algorithm for heterogeneou... more ABSTRACT This paper presents a multi-priority and multi-path selection algorithm for heterogeneous traffic for wireless ad-hoc networks. The main objectives are achieving higher throughput, better resource utilization through load balancing and relinquish network congestion. The proposed algorithm has considered signal-to-interference plus noise ratio (SINR), available link bandwidth, link delay (transmission delay and queuing delay), trust value of a node and traffic class (such as real time and non-real time traffic) to select optimal path. The performance of the proposed Multi-Priority and Trusted Multi-Path Selection (MTMS) algorithm has been evaluated by OPNET Modeler 14.5 simulator. It is found that in terms of average throughput (bit/second) and link delay proposed MTMS algorithm outperforms ad-hoc on-demand distant vector (AODV) and dynamic source routing (DSR).
2020 IEEE 22nd International Workshop on Multimedia Signal Processing (MMSP), 2020
With the growth of video technologies, super-resolution videos, including 360-degree immersive vi... more With the growth of video technologies, super-resolution videos, including 360-degree immersive video has become a reality due to exciting applications such as augmented/virtual/mixed reality for better interaction and a wide-angle user-view experience of a scene compared to traditional video with narrow-focused viewing angle. The new generation video contents are bandwidth-intensive in nature due to high resolution and demand high bit rate as well as low latency delivery requirements that pose challenges in solving the bottleneck of transmission and storage burdens. There is limited optimisation space in traditional video coding schemes for improving video coding efficiency in intra-frame due to the fixed size of processing block. This paper presents a new approach for improving intra-frame coding especially at low bit rate video transmission for 360-degree video for lossy mode of HEVC. Prior to using traditional HEVC intra-prediction, this approach exploits the global redundancy of entire frame by extracting common important information using multi-level discrete wavelet transformation. This paper demonstrates that the proposed method considering only low frequency information of a frame and encoding this can outperform the HEVC standard at low bit rates. The experimental results indicate that the proposed intra-frame coding strategy achieves an average of 54.07% BD-rate reduction and 2.84 dB BD-PSNR gain for low bit rate scenario compared to the HEVC. It also achieves a significant improvement in encoding time reduction of about 66.84% on an average. Moreover, this finding also demonstrates that the existing HEVC block partitioning can be applied in the transform domain for better exploitation of information concentration as we applied HEVC on wavelet frequency domain.
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Papers by Fariha Afsana