Attacks on self-driving cars and their countermeasures : a survey
- Chowdhury, Abdullahi, Karmakar, Gour, Kamruzzaman, Joarder, Jolfaei, Alireza, Das, Rajkumar
- Authors: Chowdhury, Abdullahi , Karmakar, Gour , Kamruzzaman, Joarder , Jolfaei, Alireza , Das, Rajkumar
- Date: 2020
- Type: Text , Journal article , Review
- Relation: IEEE Access Vol. 8, no. (2020), p. 207308-207342
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- Description: Intelligent Traffic Systems (ITS) are currently evolving in the form of a cooperative ITS or connected vehicles. Both forms use the data communications between Vehicle-To-Vehicle (V2V), Vehicle-To-Infrastructure (V2I/I2V) and other on-road entities, and are accelerating the adoption of self-driving cars. The development of cyber-physical systems containing advanced sensors, sub-systems, and smart driving assistance applications over the past decade is equipping unmanned aerial and road vehicles with autonomous decision-making capabilities. The level of autonomy depends upon the make-up and degree of sensor sophistication and the vehicle's operational applications. As a result, self-driving cars are being compromised perceived as a serious threat. Therefore, analyzing the threats and attacks on self-driving cars and ITSs, and their corresponding countermeasures to reduce those threats and attacks are needed. For this reason, some survey papers compiling potential attacks on VANETs, ITSs and self-driving cars, and their detection mechanisms are available in the current literature. However, up to our knowledge, they have not covered the real attacks already happened in self-driving cars. To bridge this research gap, in this paper, we analyze the attacks that already targeted self-driving cars and extensively present potential cyber-Attacks and their impacts on those cars along with their vulnerabilities. For recently reported attacks, we describe the possible mitigation strategies taken by the manufacturers and governments. This survey includes recent works on how a self-driving car can ensure resilient operation even under ongoing cyber-Attack. We also provide further research directions to improve the security issues associated with self-driving cars. © 2013 IEEE.
- Authors: Chowdhury, Abdullahi , Karmakar, Gour , Kamruzzaman, Joarder , Jolfaei, Alireza , Das, Rajkumar
- Date: 2020
- Type: Text , Journal article , Review
- Relation: IEEE Access Vol. 8, no. (2020), p. 207308-207342
- Full Text:
- Reviewed:
- Description: Intelligent Traffic Systems (ITS) are currently evolving in the form of a cooperative ITS or connected vehicles. Both forms use the data communications between Vehicle-To-Vehicle (V2V), Vehicle-To-Infrastructure (V2I/I2V) and other on-road entities, and are accelerating the adoption of self-driving cars. The development of cyber-physical systems containing advanced sensors, sub-systems, and smart driving assistance applications over the past decade is equipping unmanned aerial and road vehicles with autonomous decision-making capabilities. The level of autonomy depends upon the make-up and degree of sensor sophistication and the vehicle's operational applications. As a result, self-driving cars are being compromised perceived as a serious threat. Therefore, analyzing the threats and attacks on self-driving cars and ITSs, and their corresponding countermeasures to reduce those threats and attacks are needed. For this reason, some survey papers compiling potential attacks on VANETs, ITSs and self-driving cars, and their detection mechanisms are available in the current literature. However, up to our knowledge, they have not covered the real attacks already happened in self-driving cars. To bridge this research gap, in this paper, we analyze the attacks that already targeted self-driving cars and extensively present potential cyber-Attacks and their impacts on those cars along with their vulnerabilities. For recently reported attacks, we describe the possible mitigation strategies taken by the manufacturers and governments. This survey includes recent works on how a self-driving car can ensure resilient operation even under ongoing cyber-Attack. We also provide further research directions to improve the security issues associated with self-driving cars. © 2013 IEEE.
A blockchain-based deep-learning-driven architecture for quality routing in wireless sensor networks
- Khan, Zahoor, Amjad, Sana, Ahmed, Farwa, Almasoud, Abdullah, Imran, Muhammad, Javaid, Nadeem
- Authors: Khan, Zahoor , Amjad, Sana , Ahmed, Farwa , Almasoud, Abdullah , Imran, Muhammad , Javaid, Nadeem
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 31036-31051
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- Description: Over the past few years, great importance has been given to wireless sensor networks (WSNs) as they play a significant role in facilitating the world with daily life services like healthcare, military, social products, etc. However, heterogeneous nature of WSNs makes them prone to various attacks, which results in low throughput, and high network delay and high energy consumption. In the WSNs, routing is performed using different routing protocols like low-energy adaptive clustering hierarchy (LEACH), heterogeneous gateway-based energy-aware multi-hop routing (HMGEAR), etc. In such protocols, some nodes in the network may perform malicious activities. Therefore, four deep learning (DL) techniques and a real-time message content validation (RMCV) scheme based on blockchain are used in the proposed network for the detection of malicious nodes (MNs). Moreover, to analyse the routing data in the WSN, DL models are trained on a state-of-the-art dataset generated from LEACH, known as WSN-DS 2016. The WSN contains three types of nodes: sensor nodes, cluster heads (CHs) and the base station (BS). The CHs after aggregating the data received from the sensor nodes, send it towards the BS. Furthermore, to overcome the single point of failure issue, a decentralized blockchain is deployed on CHs and BS. Additionally, MNs are removed from the network using RMCV and DL techniques. Moreover, legitimate nodes (LNs) are registered in the blockchain network using proof-of-authority consensus protocol. The protocol outperforms proof-of-work in terms of computational cost. Later, routing is performed between the LNs using different routing protocols and the results are compared with original LEACH and HMGEAR protocols. The results show that the accuracy of GRU is 97%, LSTM is 96%, CNN is 92% and ANN is 90%. Throughput, delay and the death of the first node are computed for LEACH, LEACH with DL, LEACH with RMCV, HMGEAR, HMGEAR with DL and HMGEAR with RMCV. Moreover, Oyente is used to perform the formal security analysis of the designed smart contract. The analysis shows that blockchain network is resilient against vulnerabilities. © 2013 IEEE.
A blockchain-based deep-learning-driven architecture for quality routing in wireless sensor networks
- Authors: Khan, Zahoor , Amjad, Sana , Ahmed, Farwa , Almasoud, Abdullah , Imran, Muhammad , Javaid, Nadeem
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 31036-31051
- Full Text:
- Reviewed:
- Description: Over the past few years, great importance has been given to wireless sensor networks (WSNs) as they play a significant role in facilitating the world with daily life services like healthcare, military, social products, etc. However, heterogeneous nature of WSNs makes them prone to various attacks, which results in low throughput, and high network delay and high energy consumption. In the WSNs, routing is performed using different routing protocols like low-energy adaptive clustering hierarchy (LEACH), heterogeneous gateway-based energy-aware multi-hop routing (HMGEAR), etc. In such protocols, some nodes in the network may perform malicious activities. Therefore, four deep learning (DL) techniques and a real-time message content validation (RMCV) scheme based on blockchain are used in the proposed network for the detection of malicious nodes (MNs). Moreover, to analyse the routing data in the WSN, DL models are trained on a state-of-the-art dataset generated from LEACH, known as WSN-DS 2016. The WSN contains three types of nodes: sensor nodes, cluster heads (CHs) and the base station (BS). The CHs after aggregating the data received from the sensor nodes, send it towards the BS. Furthermore, to overcome the single point of failure issue, a decentralized blockchain is deployed on CHs and BS. Additionally, MNs are removed from the network using RMCV and DL techniques. Moreover, legitimate nodes (LNs) are registered in the blockchain network using proof-of-authority consensus protocol. The protocol outperforms proof-of-work in terms of computational cost. Later, routing is performed between the LNs using different routing protocols and the results are compared with original LEACH and HMGEAR protocols. The results show that the accuracy of GRU is 97%, LSTM is 96%, CNN is 92% and ANN is 90%. Throughput, delay and the death of the first node are computed for LEACH, LEACH with DL, LEACH with RMCV, HMGEAR, HMGEAR with DL and HMGEAR with RMCV. Moreover, Oyente is used to perform the formal security analysis of the designed smart contract. The analysis shows that blockchain network is resilient against vulnerabilities. © 2013 IEEE.
Extending the technology acceptance model for use of e-learning systems by digital learners
- Hanif, Aamer, Jamal, Faheem, Imran, Muhammad
- Authors: Hanif, Aamer , Jamal, Faheem , Imran, Muhammad
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Access Vol. 6, no. (2018), p. 73395-73404
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- Description: Technology-based learning systems enable enhanced student learning in higher-education institutions. This paper evaluates the factors affecting behavioral intention of students toward using e-learning systems in universities to augment classroom learning. Based on the technology acceptance model, this paper proposes six external factors that influence the behavioral intention of students toward use of e-learning. A quantitative approach involving structural equation modeling is adopted, and research data collected from 437 undergraduate students enrolled in three academic programs is used for analysis. Results indicate that subjective norm, perception of external control, system accessibility, enjoyment, and result demonstrability have a significant positive influence on perceived usefulness and on perceived ease of use of the e-learning system. This paper also examines the relevance of some previously used external variables, e.g., self-efficacy, experience, and computer anxiety, for present-world students who have been brought up as digital learners and have higher levels of computer literacy and experience. © 2018 IEEE.
- Authors: Hanif, Aamer , Jamal, Faheem , Imran, Muhammad
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Access Vol. 6, no. (2018), p. 73395-73404
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- Description: Technology-based learning systems enable enhanced student learning in higher-education institutions. This paper evaluates the factors affecting behavioral intention of students toward using e-learning systems in universities to augment classroom learning. Based on the technology acceptance model, this paper proposes six external factors that influence the behavioral intention of students toward use of e-learning. A quantitative approach involving structural equation modeling is adopted, and research data collected from 437 undergraduate students enrolled in three academic programs is used for analysis. Results indicate that subjective norm, perception of external control, system accessibility, enjoyment, and result demonstrability have a significant positive influence on perceived usefulness and on perceived ease of use of the e-learning system. This paper also examines the relevance of some previously used external variables, e.g., self-efficacy, experience, and computer anxiety, for present-world students who have been brought up as digital learners and have higher levels of computer literacy and experience. © 2018 IEEE.
Lost at starting line : predicting maladaptation of university freshmen based on educational big data
- Guo, Teng, Bai, Xiaomei, Zhen, Shihao, Abid, Shagufta, Xia, Feng
- Authors: Guo, Teng , Bai, Xiaomei , Zhen, Shihao , Abid, Shagufta , Xia, Feng
- Date: 2023
- Type: Text , Journal article
- Relation: Journal of the Association for Information Science and Technology Vol. 74, no. 1 (2023), p. 17-32
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- Description: The transition from secondary education to higher education could be challenging for most freshmen. For students who fail to adjust to university life smoothly, their status may worsen if the university cannot offer timely and proper guidance. Helping students adapt to university life is a long-term goal for any academic institution. Therefore, understanding the nature of the maladaptation phenomenon and the early prediction of “at-risk” students are crucial tasks that urgently need to be tackled effectively. This article aims to analyze the relevant factors that affect the maladaptation phenomenon and predict this phenomenon in advance. We develop a prediction framework (MAladaptive STudEnt pRediction, MASTER) for the early prediction of students with maladaptation. First, our framework uses the SMOTE (Synthetic Minority Oversampling Technique) algorithm to solve the data label imbalance issue. Moreover, a novel ensemble algorithm, priority forest, is proposed for outputting ranks instead of binary results, which enables us to perform proactive interventions in a prioritized manner where limited education resources are available. Experimental results on real-world education datasets demonstrate that the MASTER framework outperforms other state-of-art methods. © 2022 The Authors. Journal of the Association for Information Science and Technology published by Wiley Periodicals LLC on behalf of Association for Information Science and Technology.
- Authors: Guo, Teng , Bai, Xiaomei , Zhen, Shihao , Abid, Shagufta , Xia, Feng
- Date: 2023
- Type: Text , Journal article
- Relation: Journal of the Association for Information Science and Technology Vol. 74, no. 1 (2023), p. 17-32
- Full Text:
- Reviewed:
- Description: The transition from secondary education to higher education could be challenging for most freshmen. For students who fail to adjust to university life smoothly, their status may worsen if the university cannot offer timely and proper guidance. Helping students adapt to university life is a long-term goal for any academic institution. Therefore, understanding the nature of the maladaptation phenomenon and the early prediction of “at-risk” students are crucial tasks that urgently need to be tackled effectively. This article aims to analyze the relevant factors that affect the maladaptation phenomenon and predict this phenomenon in advance. We develop a prediction framework (MAladaptive STudEnt pRediction, MASTER) for the early prediction of students with maladaptation. First, our framework uses the SMOTE (Synthetic Minority Oversampling Technique) algorithm to solve the data label imbalance issue. Moreover, a novel ensemble algorithm, priority forest, is proposed for outputting ranks instead of binary results, which enables us to perform proactive interventions in a prioritized manner where limited education resources are available. Experimental results on real-world education datasets demonstrate that the MASTER framework outperforms other state-of-art methods. © 2022 The Authors. Journal of the Association for Information Science and Technology published by Wiley Periodicals LLC on behalf of Association for Information Science and Technology.
Malicious node detection using machine learning and distributed data storage using blockchain in WSNs
- Nouman, Muhammad, Qasim, Umar, Nasir, Hina, Almasoud, Abdullah, Imran, Muhammad, Javaid, Nadeem
- Authors: Nouman, Muhammad , Qasim, Umar , Nasir, Hina , Almasoud, Abdullah , Imran, Muhammad , Javaid, Nadeem
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 6106-6121
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- Description: In the proposed work, blockchain is implemented on the Base Stations (BSs) and Cluster Heads (CHs) to register the nodes using their credentials and also to tackle various security issues. Moreover, a Machine Learning (ML) classifier, termed as Histogram Gradient Boost (HGB), is employed on the BSs to classify the nodes as malicious or legitimate. In case, the node is found to be malicious, its registration is revoked from the network. Whereas, if a node is found to be legitimate, then its data is stored in an Interplanetary File System (IPFS). IPFS stores the data in the form of chunks and generates hash for the data, which is then stored in blockchain. In addition, Verifiable Byzantine Fault Tolerance (VBFT) is used instead of Proof of Work (PoW) to perform consensus and validate transactions. Also, extensive simulations are performed using the Wireless Sensor Network (WSN) dataset, referred as WSN-DS. The proposed model is evaluated both on the original dataset and the balanced dataset. Furthermore, HGB is compared with other existing classifiers, Adaptive Boost (AdaBoost), Gradient Boost (GB), Linear Discriminant Analysis (LDA), Extreme Gradient Boost (XGB) and ridge, using different performance metrics like accuracy, precision, recall, micro-F1 score and macro-F1 score. The performance evaluation of HGB shows that it outperforms GB, AdaBoost, LDA, XGB and Ridge by 2-4%, 8-10%, 12-14%, 3-5% and 14-16%, respectively. Moreover, the results with balanced dataset are better than those with original dataset. Also, VBFT performs 20-30% better than PoW. Overall, the proposed model performs efficiently in terms of malicious node detection and secure data storage. © 2013 IEEE.
- Authors: Nouman, Muhammad , Qasim, Umar , Nasir, Hina , Almasoud, Abdullah , Imran, Muhammad , Javaid, Nadeem
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 6106-6121
- Full Text:
- Reviewed:
- Description: In the proposed work, blockchain is implemented on the Base Stations (BSs) and Cluster Heads (CHs) to register the nodes using their credentials and also to tackle various security issues. Moreover, a Machine Learning (ML) classifier, termed as Histogram Gradient Boost (HGB), is employed on the BSs to classify the nodes as malicious or legitimate. In case, the node is found to be malicious, its registration is revoked from the network. Whereas, if a node is found to be legitimate, then its data is stored in an Interplanetary File System (IPFS). IPFS stores the data in the form of chunks and generates hash for the data, which is then stored in blockchain. In addition, Verifiable Byzantine Fault Tolerance (VBFT) is used instead of Proof of Work (PoW) to perform consensus and validate transactions. Also, extensive simulations are performed using the Wireless Sensor Network (WSN) dataset, referred as WSN-DS. The proposed model is evaluated both on the original dataset and the balanced dataset. Furthermore, HGB is compared with other existing classifiers, Adaptive Boost (AdaBoost), Gradient Boost (GB), Linear Discriminant Analysis (LDA), Extreme Gradient Boost (XGB) and ridge, using different performance metrics like accuracy, precision, recall, micro-F1 score and macro-F1 score. The performance evaluation of HGB shows that it outperforms GB, AdaBoost, LDA, XGB and Ridge by 2-4%, 8-10%, 12-14%, 3-5% and 14-16%, respectively. Moreover, the results with balanced dataset are better than those with original dataset. Also, VBFT performs 20-30% better than PoW. Overall, the proposed model performs efficiently in terms of malicious node detection and secure data storage. © 2013 IEEE.
Exact string matching algorithms : survey, issues, and future research directions
- Hakak, Saqib, Kamsin, Amirrudin, Shivakumara, Palaiahnakote, Gilkar, Gulshan, Khan, Wazir, Imran, Muhammad
- Authors: Hakak, Saqib , Kamsin, Amirrudin , Shivakumara, Palaiahnakote , Gilkar, Gulshan , Khan, Wazir , Imran, Muhammad
- Date: 2019
- Type: Text , Journal article
- Relation: IEEE Access Vol. 7, no. (2019), p. 69614-69637
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- Description: String matching has been an extensively studied research domain in the past two decades due to its various applications in the fields of text, image, signal, and speech processing. As a result, choosing an appropriate string matching algorithm for current applications and addressing challenges is difficult. Understanding different string matching approaches (such as exact string matching and approximate string matching algorithms), integrating several algorithms, and modifying algorithms to address related issues are also difficult. This paper presents a survey on single-pattern exact string matching algorithms. The main purpose of this survey is to propose new classification, identify new directions and highlight the possible challenges, current trends, and future works in the area of string matching algorithms with a core focus on exact string matching algorithms. © 2013 IEEE.
- Authors: Hakak, Saqib , Kamsin, Amirrudin , Shivakumara, Palaiahnakote , Gilkar, Gulshan , Khan, Wazir , Imran, Muhammad
- Date: 2019
- Type: Text , Journal article
- Relation: IEEE Access Vol. 7, no. (2019), p. 69614-69637
- Full Text:
- Reviewed:
- Description: String matching has been an extensively studied research domain in the past two decades due to its various applications in the fields of text, image, signal, and speech processing. As a result, choosing an appropriate string matching algorithm for current applications and addressing challenges is difficult. Understanding different string matching approaches (such as exact string matching and approximate string matching algorithms), integrating several algorithms, and modifying algorithms to address related issues are also difficult. This paper presents a survey on single-pattern exact string matching algorithms. The main purpose of this survey is to propose new classification, identify new directions and highlight the possible challenges, current trends, and future works in the area of string matching algorithms with a core focus on exact string matching algorithms. © 2013 IEEE.
Performance analysis of priority-based IEEE 802.15.6 protocol in saturated traffic conditions
- Ullah, Sana, Tovar, Eduardo, Kim, Ki, Kim, Kyong, Imran, Muhammad
- Authors: Ullah, Sana , Tovar, Eduardo , Kim, Ki , Kim, Kyong , Imran, Muhammad
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Access Vol. 6, no. (2018), p. 66198-66209
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- Description: Recent advancement in internet of medical things has enabled deployment of miniaturized, intelligent, and low-power medical devices in, on, or around a human body for unobtrusive and remote health monitoring. The IEEE 802.15.6 standard facilitates such monitoring by enabling low-power and reliable wireless communication between the medical devices. The IEEE 802.15.6 standard employs a carrier sense multiple access with collision avoidance protocol for resource allocation. It utilizes a priority-based backoff procedure by adjusting the contention window bounds of devices according to user requirements. As the performance of this protocol is considerably affected when the number of devices increases, we propose an accurate analytical model to estimate the saturation throughput, mean energy consumption, and mean delay over the number of devices. We assume an error-prone channel with saturated traffic conditions. We determine the optimal performance bounds for a fixed number of devices in different priority classes with different values of bit error ratio. We conclude that high-priority devices obtain quick and reliable access to the error-prone channel compared to low-priority devices. The proposed model is validated through extensive simulations. The performance bounds obtained in our analysis can be used to understand the tradeoffs between different priority levels and network performance. © 2018 IEEE.
- Authors: Ullah, Sana , Tovar, Eduardo , Kim, Ki , Kim, Kyong , Imran, Muhammad
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Access Vol. 6, no. (2018), p. 66198-66209
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- Description: Recent advancement in internet of medical things has enabled deployment of miniaturized, intelligent, and low-power medical devices in, on, or around a human body for unobtrusive and remote health monitoring. The IEEE 802.15.6 standard facilitates such monitoring by enabling low-power and reliable wireless communication between the medical devices. The IEEE 802.15.6 standard employs a carrier sense multiple access with collision avoidance protocol for resource allocation. It utilizes a priority-based backoff procedure by adjusting the contention window bounds of devices according to user requirements. As the performance of this protocol is considerably affected when the number of devices increases, we propose an accurate analytical model to estimate the saturation throughput, mean energy consumption, and mean delay over the number of devices. We assume an error-prone channel with saturated traffic conditions. We determine the optimal performance bounds for a fixed number of devices in different priority classes with different values of bit error ratio. We conclude that high-priority devices obtain quick and reliable access to the error-prone channel compared to low-priority devices. The proposed model is validated through extensive simulations. The performance bounds obtained in our analysis can be used to understand the tradeoffs between different priority levels and network performance. © 2018 IEEE.
COVID-19 datasets : a brief overview
- Sun, Ke, Li, Wuyang, Saikrishna, Vidya, Chadhar, Mehmood, Xia, Feng
- Authors: Sun, Ke , Li, Wuyang , Saikrishna, Vidya , Chadhar, Mehmood , Xia, Feng
- Date: 2022
- Type: Text , Journal article
- Relation: Computer Science and Information Systems Vol. 19, no. 3 (2022), p. 1115-1132
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- Description: The outbreak of the COVID-19 pandemic affects lives and social-economic development around the world. The affecting of the pandemic has motivated researchers from different domains to find effective solutions to diagnose, prevent, and estimate the pandemic and relieve its adverse effects. Numerous COVID-19 datasets are built from these studies and are available to the public. These datasets can be used for disease diagnosis and case prediction, speeding up solving problems caused by the pandemic. To meet the needs of researchers to understand various COVID-19 datasets, we examine and provide an overview of them. We organise the majority of these datasets into three categories based on the category of ap-plications, i.e., time-series, knowledge base, and media-based datasets. Organising COVID-19 datasets into appropriate categories can help researchers hold their focus on methodology rather than the datasets. In addition, applications and COVID-19 datasets suffer from a series of problems, such as privacy and quality. We discuss these issues as well as potentials of COVID-19 datasets. © 2022, ComSIS Consortium. All rights reserved.
- Authors: Sun, Ke , Li, Wuyang , Saikrishna, Vidya , Chadhar, Mehmood , Xia, Feng
- Date: 2022
- Type: Text , Journal article
- Relation: Computer Science and Information Systems Vol. 19, no. 3 (2022), p. 1115-1132
- Full Text:
- Reviewed:
- Description: The outbreak of the COVID-19 pandemic affects lives and social-economic development around the world. The affecting of the pandemic has motivated researchers from different domains to find effective solutions to diagnose, prevent, and estimate the pandemic and relieve its adverse effects. Numerous COVID-19 datasets are built from these studies and are available to the public. These datasets can be used for disease diagnosis and case prediction, speeding up solving problems caused by the pandemic. To meet the needs of researchers to understand various COVID-19 datasets, we examine and provide an overview of them. We organise the majority of these datasets into three categories based on the category of ap-plications, i.e., time-series, knowledge base, and media-based datasets. Organising COVID-19 datasets into appropriate categories can help researchers hold their focus on methodology rather than the datasets. In addition, applications and COVID-19 datasets suffer from a series of problems, such as privacy and quality. We discuss these issues as well as potentials of COVID-19 datasets. © 2022, ComSIS Consortium. All rights reserved.
CenGCN : centralized convolutional networks with vertex imbalance for scale-free graphs
- Xia, Feng, Wang, Lei, Tang, Tao, Chen, Xin, Kong, Xiangjie, Oatley, Giles, King, Irwin
- Authors: Xia, Feng , Wang, Lei , Tang, Tao , Chen, Xin , Kong, Xiangjie , Oatley, Giles , King, Irwin
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Transactions on Knowledge and Data Engineering Vol. 35, no. 5 (2023), p. 4555-4569
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- Reviewed:
- Description: Graph Convolutional Networks (GCNs) have achieved impressive performance in a wide variety of areas, attracting considerable attention. The core step of GCNs is the information-passing framework that considers all information from neighbors to the central vertex to be equally important. Such equal importance, however, is inadequate for scale-free networks, where hub vertices propagate more dominant information due to vertex imbalance. In this paper, we propose a novel centrality-based framework named CenGCN to address the inequality of information. This framework first quantifies the similarity between hub vertices and their neighbors by label propagation with hub vertices. Based on this similarity and centrality indices, the framework transforms the graph by increasing or decreasing the weights of edges connecting hub vertices and adding self-connections to vertices. In each non-output layer of the GCN, this framework uses a hub attention mechanism to assign new weights to connected non-hub vertices based on their common information with hub vertices. We present two variants CenGCN_D and CenGCN_E, based on degree centrality and eigenvector centrality, respectively. We also conduct comprehensive experiments, including vertex classification, link prediction, vertex clustering, and network visualization. The results demonstrate that the two variants significantly outperform state-of-the-art baselines. © 1989-2012 IEEE.
- Authors: Xia, Feng , Wang, Lei , Tang, Tao , Chen, Xin , Kong, Xiangjie , Oatley, Giles , King, Irwin
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Transactions on Knowledge and Data Engineering Vol. 35, no. 5 (2023), p. 4555-4569
- Full Text:
- Reviewed:
- Description: Graph Convolutional Networks (GCNs) have achieved impressive performance in a wide variety of areas, attracting considerable attention. The core step of GCNs is the information-passing framework that considers all information from neighbors to the central vertex to be equally important. Such equal importance, however, is inadequate for scale-free networks, where hub vertices propagate more dominant information due to vertex imbalance. In this paper, we propose a novel centrality-based framework named CenGCN to address the inequality of information. This framework first quantifies the similarity between hub vertices and their neighbors by label propagation with hub vertices. Based on this similarity and centrality indices, the framework transforms the graph by increasing or decreasing the weights of edges connecting hub vertices and adding self-connections to vertices. In each non-output layer of the GCN, this framework uses a hub attention mechanism to assign new weights to connected non-hub vertices based on their common information with hub vertices. We present two variants CenGCN_D and CenGCN_E, based on degree centrality and eigenvector centrality, respectively. We also conduct comprehensive experiments, including vertex classification, link prediction, vertex clustering, and network visualization. The results demonstrate that the two variants significantly outperform state-of-the-art baselines. © 1989-2012 IEEE.
Optimal fuzzy proportional-integral-derivative control for a class of fourth-order nonlinear systems using imperialist competitive algorithms
- Hadipour, Lakmesari, S., Safipour, Z., Mahmoodabadi, Mohammad Javad, Ibrahim, Yousef, Mobayen, Saleh
- Authors: Hadipour, Lakmesari, S. , Safipour, Z. , Mahmoodabadi, Mohammad Javad , Ibrahim, Yousef , Mobayen, Saleh
- Date: 2022
- Type: Text , Journal article
- Relation: Complexity Vol. 2022, no. (2022), p. 1-13
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- Description: The proportional integral derivative (PID) controller has gained wide acceptance and use as the most useful control approach in the industry. However, the PID controller lacks robustness to uncertainties and stability under disturbances. To address this problem, this paper proposes an optimal fuzzy-PID technique for a two-degree-of-freedom cart-pole system. Fuzzy rules can be combined with controllers such as PID to tune their coefficients and allow the controller to deliver substantially improved performance. To achieve this, the fuzzy logic method is applied in conjunction with the PID approach to provide essential control inputs and improve the control algorithm efficiency. The achieved control gains are then optimized via the imperialist competitive algorithm. Consequently, the objective function for the cart-pole system is regarded as the summation of the displacement error of the cart, the angular error of the pole, and the control force. This control concept has been tested via simulation and experimental validations. Obtained results are presented to confirm the accuracy and efficiency of the suggested method. © 2022 S. Hadipour Lakmesari et al.
- Authors: Hadipour, Lakmesari, S. , Safipour, Z. , Mahmoodabadi, Mohammad Javad , Ibrahim, Yousef , Mobayen, Saleh
- Date: 2022
- Type: Text , Journal article
- Relation: Complexity Vol. 2022, no. (2022), p. 1-13
- Full Text:
- Reviewed:
- Description: The proportional integral derivative (PID) controller has gained wide acceptance and use as the most useful control approach in the industry. However, the PID controller lacks robustness to uncertainties and stability under disturbances. To address this problem, this paper proposes an optimal fuzzy-PID technique for a two-degree-of-freedom cart-pole system. Fuzzy rules can be combined with controllers such as PID to tune their coefficients and allow the controller to deliver substantially improved performance. To achieve this, the fuzzy logic method is applied in conjunction with the PID approach to provide essential control inputs and improve the control algorithm efficiency. The achieved control gains are then optimized via the imperialist competitive algorithm. Consequently, the objective function for the cart-pole system is regarded as the summation of the displacement error of the cart, the angular error of the pole, and the control force. This control concept has been tested via simulation and experimental validations. Obtained results are presented to confirm the accuracy and efficiency of the suggested method. © 2022 S. Hadipour Lakmesari et al.
A novel counterbalanced implementation study design : methodological description and application to implementation research
- Sarkies, Mitchell, Skinner, Elizabeth, Bowles, Kelly-Ann, Morris, Meg, Martin, Jennifer
- Authors: Sarkies, Mitchell , Skinner, Elizabeth , Bowles, Kelly-Ann , Morris, Meg , Martin, Jennifer
- Date: 2019
- Type: Text , Journal article
- Relation: Implementation Science Vol. 14, no. 1 (2019), p.
- Full Text:
- Reviewed:
- Description: Background: Implementation research is increasingly being recognised for optimising the outcomes of clinical practice. Frequently, the benefits of new evidence are not implemented due to the difficulties applying traditional research methodologies to implementation settings. Randomised controlled trials are not always practical for the implementation phase of knowledge transfer, as differences between individual and organisational readiness for change combined with small sample sizes can lead to imbalances in factors that impede or facilitate change between intervention and control groups. Within-cluster repeated measure designs could control for variance between intervention and control groups by allowing the same clusters to receive a sequence of conditions. Although in implementation settings, they can contaminate the intervention and control groups after the initial exposure to interventions. We propose the novel application of counterbalanced design to implementation research where repeated measures are employed through crossover, but contamination is averted by counterbalancing different health contexts in which to test the implementation strategy. Methods: In a counterbalanced implementation study, the implementation strategy (independent variable) has two or more levels evaluated across an equivalent number of health contexts (e.g. community-acquired pneumonia and nutrition for critically ill patients) using the same outcome (dependent variable). This design limits each cluster to one distinct strategy related to one specific context, and therefore does not overburden any cluster to more than one focussed implementation strategy for a particular outcome, and provides a ready-made control comparison, holding fixed. The different levels of the independent variable can be delivered concurrently because each level uses a different health context within each cluster to avoid the effect of treatment contamination from exposure to the intervention or control condition. Results: An example application of the counterbalanced implementation design is presented in a hypothetical study to demonstrate the comparison of 'video-based' and 'written-based' evidence summary research implementation strategies for changing clinical practice in community-acquired pneumonia and nutrition in critically ill patient health contexts. Conclusion: A counterbalanced implementation study design provides a promising model for concurrently investigating the success of research implementation strategies across multiple health context areas such as community-acquired pneumonia and nutrition for critically ill patients. © 2019 The Author(s). **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Jennifer Martin" is provided in this record**
- Authors: Sarkies, Mitchell , Skinner, Elizabeth , Bowles, Kelly-Ann , Morris, Meg , Martin, Jennifer
- Date: 2019
- Type: Text , Journal article
- Relation: Implementation Science Vol. 14, no. 1 (2019), p.
- Full Text:
- Reviewed:
- Description: Background: Implementation research is increasingly being recognised for optimising the outcomes of clinical practice. Frequently, the benefits of new evidence are not implemented due to the difficulties applying traditional research methodologies to implementation settings. Randomised controlled trials are not always practical for the implementation phase of knowledge transfer, as differences between individual and organisational readiness for change combined with small sample sizes can lead to imbalances in factors that impede or facilitate change between intervention and control groups. Within-cluster repeated measure designs could control for variance between intervention and control groups by allowing the same clusters to receive a sequence of conditions. Although in implementation settings, they can contaminate the intervention and control groups after the initial exposure to interventions. We propose the novel application of counterbalanced design to implementation research where repeated measures are employed through crossover, but contamination is averted by counterbalancing different health contexts in which to test the implementation strategy. Methods: In a counterbalanced implementation study, the implementation strategy (independent variable) has two or more levels evaluated across an equivalent number of health contexts (e.g. community-acquired pneumonia and nutrition for critically ill patients) using the same outcome (dependent variable). This design limits each cluster to one distinct strategy related to one specific context, and therefore does not overburden any cluster to more than one focussed implementation strategy for a particular outcome, and provides a ready-made control comparison, holding fixed. The different levels of the independent variable can be delivered concurrently because each level uses a different health context within each cluster to avoid the effect of treatment contamination from exposure to the intervention or control condition. Results: An example application of the counterbalanced implementation design is presented in a hypothetical study to demonstrate the comparison of 'video-based' and 'written-based' evidence summary research implementation strategies for changing clinical practice in community-acquired pneumonia and nutrition in critically ill patient health contexts. Conclusion: A counterbalanced implementation study design provides a promising model for concurrently investigating the success of research implementation strategies across multiple health context areas such as community-acquired pneumonia and nutrition for critically ill patients. © 2019 The Author(s). **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Jennifer Martin" is provided in this record**
Individual and occupational differences in perceived organisational culture of a central hospital in vietnam
- Nguyen, Huy, Nguyen, Au, Nguyen, Thu, Nguyen, Ha, Bui, Hien
- Authors: Nguyen, Huy , Nguyen, Au , Nguyen, Thu , Nguyen, Ha , Bui, Hien
- Date: 2018
- Type: Text , Journal article
- Relation: BioMed Research International Vol. 2018, no. (2018), p.
- Full Text:
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- Description: Many hospitals in developing countries, including Vietnam, are facing the challenges of increasingly noncommunicable diseases and the financial autonomy policy from the government. To adapt to this new context requires understanding and changing the current organisational culture of the hospitals. However, little has been known about this in resource-constrained healthcare settings. The objectives of this study were to examine the four characteristics of the organisational culture and test selected individual and occupational differences in the organisational culture of a Vietnam central hospital. In a cross-sectional study using the Organisation Culture Assessment Instrument (OCAI) with the Competing Value Framework (CVF), including 4 factors, Clan, Adhocracy, Hierarchy, and Market, health workers currently working at Quang Nam General Hospital were interviewed. The results indicated the current cultural model was more internally focused with two dominant cultures, Clan and Hierarchy, while, for the desired model, the Clan culture was the most expected one. Comparing between the current and desired pattern, the down trend was found for all types of culture, except the Clan culture, and there were significant differences by domains of organisational culture. Furthermore, the current and desired models were differently distributed by key individual characteristics. These differences have raised a number of interesting directions for future research. They also suggest that, to build a hospital organisational culture to suit both current and future contexts as per employees' assessment and expectation, it is important to take individual and institutional variations into account. © 2018 Huy Nguyen Van et al. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Huy Nguyen” is provided in this record**
- Authors: Nguyen, Huy , Nguyen, Au , Nguyen, Thu , Nguyen, Ha , Bui, Hien
- Date: 2018
- Type: Text , Journal article
- Relation: BioMed Research International Vol. 2018, no. (2018), p.
- Full Text:
- Reviewed:
- Description: Many hospitals in developing countries, including Vietnam, are facing the challenges of increasingly noncommunicable diseases and the financial autonomy policy from the government. To adapt to this new context requires understanding and changing the current organisational culture of the hospitals. However, little has been known about this in resource-constrained healthcare settings. The objectives of this study were to examine the four characteristics of the organisational culture and test selected individual and occupational differences in the organisational culture of a Vietnam central hospital. In a cross-sectional study using the Organisation Culture Assessment Instrument (OCAI) with the Competing Value Framework (CVF), including 4 factors, Clan, Adhocracy, Hierarchy, and Market, health workers currently working at Quang Nam General Hospital were interviewed. The results indicated the current cultural model was more internally focused with two dominant cultures, Clan and Hierarchy, while, for the desired model, the Clan culture was the most expected one. Comparing between the current and desired pattern, the down trend was found for all types of culture, except the Clan culture, and there were significant differences by domains of organisational culture. Furthermore, the current and desired models were differently distributed by key individual characteristics. These differences have raised a number of interesting directions for future research. They also suggest that, to build a hospital organisational culture to suit both current and future contexts as per employees' assessment and expectation, it is important to take individual and institutional variations into account. © 2018 Huy Nguyen Van et al. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Huy Nguyen” is provided in this record**
Molecular docking interaction of mycobacterium tuberculosis lipb enzyme with isoniazid, pyrazinamide and a structurally altered drug 2, 6 dimethoxyisonicotinohydrazide
- Authors: Namasivayam, Muthuraman
- Date: 2015
- Type: Text , Journal article
- Relation: Computational biology and bioinformatics (Print) Vol. 3, no. 4 (2015), p. 45
- Full Text:
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- Description: Tuberculosis is an infectious airborne disease caused by a bacterial infection that affects the lungs and other parts of the body. Vaccination against tuberculosis is available but proved to be unsuccessful against emerging multi drug and extensive drug resistant bacterial strains. This in turn raises the pressure to speed up the research on developing new and more efficient anti-tuberculosis drugs. Lipoate biosynthesis protein B (LipB) is found to play vital role in the lipoylation process in Mycobacterium tuberculosis and thus making it a very promising drug target. The existing first line drugs such as Isoniazid, Pyrazinamide and Rifampicin etc shows only profound binding affinity with this target protein. Therefore, new or modified drugs with better docking approach that exhibit a closer and stronger binding affinity is essential. This current study opens up a novel approach towards anti-tuberculosis agents by determining drugs that share similar structures with some of the best available first line drug and also happen to possess better binding affinity. In this article, a computational method by which, pristine as well certain first line and structurally modified drugs were docked with the LipB protein target; where, structurally modified 2, 6 Dimethoxyisonicotinohydrazide show superior target docking.
- Authors: Namasivayam, Muthuraman
- Date: 2015
- Type: Text , Journal article
- Relation: Computational biology and bioinformatics (Print) Vol. 3, no. 4 (2015), p. 45
- Full Text:
- Reviewed:
- Description: Tuberculosis is an infectious airborne disease caused by a bacterial infection that affects the lungs and other parts of the body. Vaccination against tuberculosis is available but proved to be unsuccessful against emerging multi drug and extensive drug resistant bacterial strains. This in turn raises the pressure to speed up the research on developing new and more efficient anti-tuberculosis drugs. Lipoate biosynthesis protein B (LipB) is found to play vital role in the lipoylation process in Mycobacterium tuberculosis and thus making it a very promising drug target. The existing first line drugs such as Isoniazid, Pyrazinamide and Rifampicin etc shows only profound binding affinity with this target protein. Therefore, new or modified drugs with better docking approach that exhibit a closer and stronger binding affinity is essential. This current study opens up a novel approach towards anti-tuberculosis agents by determining drugs that share similar structures with some of the best available first line drug and also happen to possess better binding affinity. In this article, a computational method by which, pristine as well certain first line and structurally modified drugs were docked with the LipB protein target; where, structurally modified 2, 6 Dimethoxyisonicotinohydrazide show superior target docking.
On robustness analysis of linear vibrational control systems
- Cheng, Xiaoxiao, Tan, Ying, Mareels, Iven
- Authors: Cheng, Xiaoxiao , Tan, Ying , Mareels, Iven
- Date: 2018
- Type: Text , Journal article
- Relation: Automatica Vol. 87, no. (2018), p. 202-209
- Full Text:
- Reviewed:
- Description: By injecting high frequency dither signals, it is possible to stabilize an inverted pendulum without any feedback. The concept of the vibrational control system is thus proposed to provide extra design freedom in stabilization or other performance indexes. Although various vibrational control algorithms have been proposed and implemented in literature, little work has been done to show their robustness with respect to disturbances and uncertainties. This paper focuses on the robustness analysis of linear vibrational control systems with additive disturbances. By applying perturbation techniques, the linear vibrational control system is shown to be input-to-state stable with respect to disturbances. When disturbances are periodic, frequency analysis technique obtains a less conservative estimate of the ultimate bound of the system, indicating that disturbances with high frequencies lead to relatively small ultimate bounds. When additive state-dependent disturbances are considered, weak averaging techniques can be used to show the robustness of the system when bounded disturbances are slow time-varying. Numerical results support the theoretic analysis.
- Authors: Cheng, Xiaoxiao , Tan, Ying , Mareels, Iven
- Date: 2018
- Type: Text , Journal article
- Relation: Automatica Vol. 87, no. (2018), p. 202-209
- Full Text:
- Reviewed:
- Description: By injecting high frequency dither signals, it is possible to stabilize an inverted pendulum without any feedback. The concept of the vibrational control system is thus proposed to provide extra design freedom in stabilization or other performance indexes. Although various vibrational control algorithms have been proposed and implemented in literature, little work has been done to show their robustness with respect to disturbances and uncertainties. This paper focuses on the robustness analysis of linear vibrational control systems with additive disturbances. By applying perturbation techniques, the linear vibrational control system is shown to be input-to-state stable with respect to disturbances. When disturbances are periodic, frequency analysis technique obtains a less conservative estimate of the ultimate bound of the system, indicating that disturbances with high frequencies lead to relatively small ultimate bounds. When additive state-dependent disturbances are considered, weak averaging techniques can be used to show the robustness of the system when bounded disturbances are slow time-varying. Numerical results support the theoretic analysis.
6G wireless systems : a vision, architectural elements, and future directions
- Khan, Latif, Yaqoob, Ibrar, Imran, Muhammad, Han, Zhu, Hong, Choong
- Authors: Khan, Latif , Yaqoob, Ibrar , Imran, Muhammad , Han, Zhu , Hong, Choong
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 147029-147044
- Full Text:
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- Description: Internet of everything (IoE)-based smart services are expected to gain immense popularity in the future, which raises the need for next-generation wireless networks. Although fifth-generation (5G) networks can support various IoE services, they might not be able to completely fulfill the requirements of novel applications. Sixth-generation (6G) wireless systems are envisioned to overcome 5G network limitations. In this article, we explore recent advances made toward enabling 6G systems. We devise a taxonomy based on key enabling technologies, use cases, emerging machine learning schemes, communication technologies, networking technologies, and computing technologies. Furthermore, we identify and discuss open research challenges, such as artificial-intelligence-based adaptive transceivers, intelligent wireless energy harvesting, decentralized and secure business models, intelligent cell-less architecture, and distributed security models. We propose practical guidelines including deep Q-learning and federated learning-based transceivers, blockchain-based secure business models, homomorphic encryption, and distributed-ledger-based authentication schemes to cope with these challenges. Finally, we outline and recommend several future directions. © 2013 IEEE.
- Authors: Khan, Latif , Yaqoob, Ibrar , Imran, Muhammad , Han, Zhu , Hong, Choong
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 147029-147044
- Full Text:
- Reviewed:
- Description: Internet of everything (IoE)-based smart services are expected to gain immense popularity in the future, which raises the need for next-generation wireless networks. Although fifth-generation (5G) networks can support various IoE services, they might not be able to completely fulfill the requirements of novel applications. Sixth-generation (6G) wireless systems are envisioned to overcome 5G network limitations. In this article, we explore recent advances made toward enabling 6G systems. We devise a taxonomy based on key enabling technologies, use cases, emerging machine learning schemes, communication technologies, networking technologies, and computing technologies. Furthermore, we identify and discuss open research challenges, such as artificial-intelligence-based adaptive transceivers, intelligent wireless energy harvesting, decentralized and secure business models, intelligent cell-less architecture, and distributed security models. We propose practical guidelines including deep Q-learning and federated learning-based transceivers, blockchain-based secure business models, homomorphic encryption, and distributed-ledger-based authentication schemes to cope with these challenges. Finally, we outline and recommend several future directions. © 2013 IEEE.
MESH : a flexible manifold-embedded semantic hashing for cross-modal retrieval
- Zhong, Fangming, Wang, Guangze, Chen, Zhikui, Xia, Feng
- Authors: Zhong, Fangming , Wang, Guangze , Chen, Zhikui , Xia, Feng
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 147569-147579
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- Description: Hashing based methods for cross-modal retrieval has been widely explored in recent years. However, most of them mainly focus on the preservation of neighborhood relationship and label consistency, while ignore the proximity of neighbors and proximity of classes, which degrades the discrimination of hash codes. And most of them learn hash codes and hashing functions simultaneously, which limits the flexibility of algorithms. To address these issues, in this article, we propose a two-step cross-modal retrieval method named Manifold-Embedded Semantic Hashing (MESH). It exploits Local Linear Embedding to model the neighborhood proximity and uses class semantic embeddings to consider the proximity of classes. By so doing, MESH can not only extract the manifold structure in different modalities, but also can embed the class semantic information into hash codes to further improve the discrimination of learned hash codes. Moreover, the two-step scheme makes MESH flexible to various hashing functions. Extensive experimental results on three datasets show that MESH is superior to 10 state-of-the-art cross-modal hashing methods. Moreover, MESH also demonstrates superiority on deep features compared with the deep cross-modal hashing method. © 2013 IEEE.
- Authors: Zhong, Fangming , Wang, Guangze , Chen, Zhikui , Xia, Feng
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 147569-147579
- Full Text:
- Reviewed:
- Description: Hashing based methods for cross-modal retrieval has been widely explored in recent years. However, most of them mainly focus on the preservation of neighborhood relationship and label consistency, while ignore the proximity of neighbors and proximity of classes, which degrades the discrimination of hash codes. And most of them learn hash codes and hashing functions simultaneously, which limits the flexibility of algorithms. To address these issues, in this article, we propose a two-step cross-modal retrieval method named Manifold-Embedded Semantic Hashing (MESH). It exploits Local Linear Embedding to model the neighborhood proximity and uses class semantic embeddings to consider the proximity of classes. By so doing, MESH can not only extract the manifold structure in different modalities, but also can embed the class semantic information into hash codes to further improve the discrimination of learned hash codes. Moreover, the two-step scheme makes MESH flexible to various hashing functions. Extensive experimental results on three datasets show that MESH is superior to 10 state-of-the-art cross-modal hashing methods. Moreover, MESH also demonstrates superiority on deep features compared with the deep cross-modal hashing method. © 2013 IEEE.
Network embedding : taxonomies, frameworks and applications
- Hou, Mingliang, Ren, Jing, Zhang, Da, Kong, Xiangjie, Zhang, Dongyu, Xia, Feng
- Authors: Hou, Mingliang , Ren, Jing , Zhang, Da , Kong, Xiangjie , Zhang, Dongyu , Xia, Feng
- Date: 2020
- Type: Text , Journal article , Review
- Relation: Computer Science Review Vol. 38, no. (2020), p.
- Full Text:
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- Description: Networks are a general language for describing complex systems of interacting entities. In the real world, a network always contains massive nodes, edges and additional complex information which leads to high complexity in computing and analyzing tasks. Network embedding aims at transforming one network into a low dimensional vector space which benefits the downstream network analysis tasks. In this survey, we provide a systematic overview of network embedding techniques in addressing challenges appearing in networks. We first introduce concepts and challenges in network embedding. Afterwards, we categorize network embedding methods using three categories, including static homogeneous network embedding methods, static heterogeneous network embedding methods and dynamic network embedding methods. Next, we summarize the datasets and evaluation tasks commonly used in network embedding. Finally, we discuss several future directions in this field. © 2020 Elsevier Inc.
- Authors: Hou, Mingliang , Ren, Jing , Zhang, Da , Kong, Xiangjie , Zhang, Dongyu , Xia, Feng
- Date: 2020
- Type: Text , Journal article , Review
- Relation: Computer Science Review Vol. 38, no. (2020), p.
- Full Text:
- Reviewed:
- Description: Networks are a general language for describing complex systems of interacting entities. In the real world, a network always contains massive nodes, edges and additional complex information which leads to high complexity in computing and analyzing tasks. Network embedding aims at transforming one network into a low dimensional vector space which benefits the downstream network analysis tasks. In this survey, we provide a systematic overview of network embedding techniques in addressing challenges appearing in networks. We first introduce concepts and challenges in network embedding. Afterwards, we categorize network embedding methods using three categories, including static homogeneous network embedding methods, static heterogeneous network embedding methods and dynamic network embedding methods. Next, we summarize the datasets and evaluation tasks commonly used in network embedding. Finally, we discuss several future directions in this field. © 2020 Elsevier Inc.
Enhancing quality-of-service conditions using a cross-layer paradigm for ad-hoc vehicular communication
- Rehman, Sabih, Arif Khan, M. Arif, Imran, Muhammad, Zia, Tanveer, Iftikhar, Mohsin
- Authors: Rehman, Sabih , Arif Khan, M. Arif , Imran, Muhammad , Zia, Tanveer , Iftikhar, Mohsin
- Date: 2017
- Type: Text , Journal article
- Relation: IEEE Access Vol. 5, no. (2017), p. 12404-12416
- Full Text:
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- Description: The Internet of Vehicles (IoVs) is an emerging paradigm aiming to introduce a plethora of innovative applications and services that impose a certain quality of service (QoS) requirements. The IoV mainly relies on vehicular ad-hoc networks (VANETs) for autonomous inter-vehicle communication and road-traffic safety management. With the ever-increasing demand to design new and emerging applications for VANETs, one challenge that continues to stand out is the provision of acceptable QoS requirements to particular user applications. Most existing solutions to this challenge rely on a single layer of the protocol stack. This paper presents a cross-layer decision-based routing protocol that necessitates choosing the best multi-hop path for packet delivery to meet acceptable QoS requirements. The proposed protocol acquires the information about the channel rate from the physical layer and incorporates this information in decision making, while directing traffic at the network layer level. Key performance metrics for the system design are analyzed using extensive experimental simulation scenarios. In addition, three data rate variant solutions are proposed to cater for various application-specific requirements in highways and urban environments. © 2013 IEEE.
- Authors: Rehman, Sabih , Arif Khan, M. Arif , Imran, Muhammad , Zia, Tanveer , Iftikhar, Mohsin
- Date: 2017
- Type: Text , Journal article
- Relation: IEEE Access Vol. 5, no. (2017), p. 12404-12416
- Full Text:
- Reviewed:
- Description: The Internet of Vehicles (IoVs) is an emerging paradigm aiming to introduce a plethora of innovative applications and services that impose a certain quality of service (QoS) requirements. The IoV mainly relies on vehicular ad-hoc networks (VANETs) for autonomous inter-vehicle communication and road-traffic safety management. With the ever-increasing demand to design new and emerging applications for VANETs, one challenge that continues to stand out is the provision of acceptable QoS requirements to particular user applications. Most existing solutions to this challenge rely on a single layer of the protocol stack. This paper presents a cross-layer decision-based routing protocol that necessitates choosing the best multi-hop path for packet delivery to meet acceptable QoS requirements. The proposed protocol acquires the information about the channel rate from the physical layer and incorporates this information in decision making, while directing traffic at the network layer level. Key performance metrics for the system design are analyzed using extensive experimental simulation scenarios. In addition, three data rate variant solutions are proposed to cater for various application-specific requirements in highways and urban environments. © 2013 IEEE.
Adherence to antiplatelet therapy after coronary intervention among patients with myocardial infarction attending Vietnam National Heart Institute
- Luu, Ngoc, Dinh, Anh, Nguyen, Thi, Nguyen, Huy
- Authors: Luu, Ngoc , Dinh, Anh , Nguyen, Thi , Nguyen, Huy
- Date: 2019
- Type: Text , Journal article
- Relation: BioMed Research International Vol. 2019, no. (2019), p.
- Full Text:
- Reviewed:
- Description: Adherence to antiplatelet therapy is critical to successful treatment of cardiovascular conditions. However, little has been known about this issue in the context of constrained resources such as in Vietnam. The objective of this study was to examine the adherence to antiplatelet therapy among patients receiving acute myocardial infarction interventions and its associated factors. In a cross-sectional survey design, 175 adult patients revisiting Vietnam National Heart Institute diagnosed with acute myocardial infarction were approached for data collection from October 2014 to June 2015. Adherence to antiplatelet therapy was assessed by asking patients whether they took taking antiplatelet regularly as per medication (do not miss any dose at the specified time) for any type of antiplatelet (aspirin, clopidogrel, ticlopidine.) during the last month before the participants came back to take re-examinations. The results indicated that the adherence to antiplatelet therapy among patients was quite high at 1 month; it begins to decline by 6 months, 12 months, and more than 12 months (less than 1 month was 90.29%; from 1 to 6 months 88.0%, from 6 to 12 months 75.43%, and after 12 months only 46.29% of patients). Multivariable logistic regression was utilized to detect factors associated with the adherence to antiplatelet therapy. It showed that patients with average income per month of $300 or more (OR=2.92, 95% CI=1.24-6.89), distance to the hospital of less than 50km (OR=2.48, 95% CI: 1.12-5.52), taking medicine under doctor's instructions (OR=3.65; 95% CI=1.13-11.70), and timely re-examination (OR=3.99, 95% CI=1.08-14.73) were more likely to follow the therapy. In general, the study suggested that to increase the likelihood of adherence to antiplatelet therapy it is important to establish a continuous care system after discharging from hospital. © 2019 Ngoc Minh Luu et al.
- Authors: Luu, Ngoc , Dinh, Anh , Nguyen, Thi , Nguyen, Huy
- Date: 2019
- Type: Text , Journal article
- Relation: BioMed Research International Vol. 2019, no. (2019), p.
- Full Text:
- Reviewed:
- Description: Adherence to antiplatelet therapy is critical to successful treatment of cardiovascular conditions. However, little has been known about this issue in the context of constrained resources such as in Vietnam. The objective of this study was to examine the adherence to antiplatelet therapy among patients receiving acute myocardial infarction interventions and its associated factors. In a cross-sectional survey design, 175 adult patients revisiting Vietnam National Heart Institute diagnosed with acute myocardial infarction were approached for data collection from October 2014 to June 2015. Adherence to antiplatelet therapy was assessed by asking patients whether they took taking antiplatelet regularly as per medication (do not miss any dose at the specified time) for any type of antiplatelet (aspirin, clopidogrel, ticlopidine.) during the last month before the participants came back to take re-examinations. The results indicated that the adherence to antiplatelet therapy among patients was quite high at 1 month; it begins to decline by 6 months, 12 months, and more than 12 months (less than 1 month was 90.29%; from 1 to 6 months 88.0%, from 6 to 12 months 75.43%, and after 12 months only 46.29% of patients). Multivariable logistic regression was utilized to detect factors associated with the adherence to antiplatelet therapy. It showed that patients with average income per month of $300 or more (OR=2.92, 95% CI=1.24-6.89), distance to the hospital of less than 50km (OR=2.48, 95% CI: 1.12-5.52), taking medicine under doctor's instructions (OR=3.65; 95% CI=1.13-11.70), and timely re-examination (OR=3.99, 95% CI=1.08-14.73) were more likely to follow the therapy. In general, the study suggested that to increase the likelihood of adherence to antiplatelet therapy it is important to establish a continuous care system after discharging from hospital. © 2019 Ngoc Minh Luu et al.
DC fault identification in multiterminal HVDC systems based on reactor voltage gradient
- Hassan, Mehedi, Hossain, M., Shah, Rakibuzzaman
- Authors: Hassan, Mehedi , Hossain, M. , Shah, Rakibuzzaman
- Date: 2021
- Type: Text , Journal article
- Relation: IEEE Access Vol. 9, no. (2021), p. 115855-115867
- Full Text:
- Reviewed:
- Description: With the increasing number of renewable generations, the prospects of long-distance bulk power transmission impels the expansion of point-to-point High Voltage Direct Current (HVDC) grid to an emerging Multi-terminal high-voltage Direct Current (MTDC) grid. The DC grid protection with faster selectivity enhances the operational continuity of the MTDC grid. Based on the reactor voltage gradient (RVG), this paper proposes a fast and reliable fault identification technique with precise discrimination of internal and external DC faults. Considering the voltage developed across the modular multilevel converter (MMC) reactor and DC terminal reactor, the RVG is formulated to characterise an internal and external DC fault. With a window of four RVG samples, the fault is detected and discriminated by the proposed main protection scheme amidst a period of five sampling intervals. Depending on the reactor current increment, a backup protection scheme is also proposed to enhance the protection reliability. The performance of the proposed scheme is validated in a four-terminal MTDC grid. The results under meaningful fault events show that the proposed scheme is capable to identify the DC fault within millisecond. Moreover, the evaluation of the protection sensitivity and robustness reveals that the proposed scheme is highly selective for a wide range of fault resistances and locations, higher sampling frequencies, and irrelevant transient events. Furthermore, the comparison results exhibit that the proposed RVG method improves the discrimination performance of the protection scheme and thereby, proves to be a better choice for future DC fault identification.
- Authors: Hassan, Mehedi , Hossain, M. , Shah, Rakibuzzaman
- Date: 2021
- Type: Text , Journal article
- Relation: IEEE Access Vol. 9, no. (2021), p. 115855-115867
- Full Text:
- Reviewed:
- Description: With the increasing number of renewable generations, the prospects of long-distance bulk power transmission impels the expansion of point-to-point High Voltage Direct Current (HVDC) grid to an emerging Multi-terminal high-voltage Direct Current (MTDC) grid. The DC grid protection with faster selectivity enhances the operational continuity of the MTDC grid. Based on the reactor voltage gradient (RVG), this paper proposes a fast and reliable fault identification technique with precise discrimination of internal and external DC faults. Considering the voltage developed across the modular multilevel converter (MMC) reactor and DC terminal reactor, the RVG is formulated to characterise an internal and external DC fault. With a window of four RVG samples, the fault is detected and discriminated by the proposed main protection scheme amidst a period of five sampling intervals. Depending on the reactor current increment, a backup protection scheme is also proposed to enhance the protection reliability. The performance of the proposed scheme is validated in a four-terminal MTDC grid. The results under meaningful fault events show that the proposed scheme is capable to identify the DC fault within millisecond. Moreover, the evaluation of the protection sensitivity and robustness reveals that the proposed scheme is highly selective for a wide range of fault resistances and locations, higher sampling frequencies, and irrelevant transient events. Furthermore, the comparison results exhibit that the proposed RVG method improves the discrimination performance of the protection scheme and thereby, proves to be a better choice for future DC fault identification.