Amr Tolba - Academia.edu (original) (raw)
Papers by Amr Tolba
Sustainable Cities and Society
Peer-to-Peer Networking and Applications
Complex & Intelligent Systems
The computer vision (CV) paradigm is introduced to improve the computational and processing syste... more The computer vision (CV) paradigm is introduced to improve the computational and processing system efficiencies through visual inputs. These visual inputs are processed using sophisticated techniques for improving the reliability of human–machine interactions (HMIs). The processing of visual inputs requires multi-level data computations for achieving application-specific reliability. Therefore, in this paper, a two-level visual information processing (2LVIP) method is introduced to meet the reliability requirements of HMI applications. The 2LVIP method is used for handling both structured and unstructured data through classification learning to extract the maximum gain from the inputs. The introduced method identifies the gain-related features on its first level and optimizes the features to improve information gain. In the second level, the error is reduced through a regression process to stabilize the precision to meet the HMI application demands. The two levels are interoperable ...
Sustainable Energy Technologies and Assessments
Journal of Ambient Intelligence and Humanized Computing
Computers, Materials & Continua
Image captioning aims to generate a corresponding description of an image. In recent years, neura... more Image captioning aims to generate a corresponding description of an image. In recent years, neural encoder-decoder models have been the dominant approaches, in which the Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM) are used to translate an image into a natural language description. Among these approaches, the visual attention mechanisms are widely used to enable deeper image understanding through fine-grained analysis and even multiple steps of reasoning. However, most conventional visual attention mechanisms are based on high-level image features, ignoring the effects of other image features, and giving insufficient consideration to the relative positions between image features. In this work, we propose a Position-Aware Transformer model with image-feature attention and position-aware attention mechanisms for the above problems. The image-feature attention firstly extracts multi-level features by using Feature Pyramid Network (FPN), then utilizes the scaled-dot-product to fuse these features, which enables our model to detect objects of different scales in the image more effectively without increasing parameters. In the position-aware attention mechanism, the relative positions between image features are obtained at first, afterwards the relative positions are incorporated into the original image features to generate captions more accurately. Experiments are carried out on the MSCOCO dataset and our approach achieves competitive BLEU-4, METEOR, ROUGE-L, CIDEr scores compared with some state-of-the-art approaches, demonstrating the effectiveness of our approach.
Future Generation Computer Systems
Computers, Materials & Continua
Applied Sciences
Employment of the Internet of Things (IoT) technology in the healthcare field can contribute to r... more Employment of the Internet of Things (IoT) technology in the healthcare field can contribute to recruiting heterogeneous medical devices and creating smart cooperation between them. This cooperation leads to an increase in the efficiency of the entire medical system, thus accelerating the diagnosis and curing of patients, in general, and rescuing critical cases in particular. In this paper, a large-scale IoT-enabled healthcare architecture is proposed. To achieve a wide range of communication between healthcare devices, not only are Internet coverage tools utilized but also satellites and high-altitude platforms (HAPs). In addition, the clustering idea is applied in the proposed architecture to facilitate its management. Moreover, healthcare data are prioritized into several levels of importance. Finally, NS3 is used to measure the performance of the proposed IoT-enabled healthcare architecture. The performance metrics are delay, energy consumption, packet loss, coverage tool usage,...
Sensors
Wireless Rechargeable Sensor Networks (WRSN) are not yet fully functional and robust due to the f... more Wireless Rechargeable Sensor Networks (WRSN) are not yet fully functional and robust due to the fact that their setting parameters assume fixed control velocity and location. This study proposes a novel scheme of the WRSN with mobile sink (MS) velocity control strategies for charging nodes and collecting its data in WRSN. Strip space of the deployed network area is divided into sub-locations for variant corresponding velocities based on nodes energy expenditure demands. The points of consumed energy bottleneck nodes in sub-locations are determined based on gathering data of residual energy and expenditure of nodes. A minimum reliable energy balanced spanning tree is constructed based on data collection to optimize the data transmission paths, balance energy consumption, and reduce data loss during transmission. Experimental results are compared with the other methods in the literature that show that the proposed scheme offers a more effective alternative in reducing the network pack...
Sensors
The development of the Internet of Things (IoT) plays a very important role for processing data a... more The development of the Internet of Things (IoT) plays a very important role for processing data at the edge of a network. Therefore, it is very important to protect the privacy of IoT devices when these devices process and transfer data. A mesh signature (MS) is a useful cryptographic tool, which makes a signer sign any message anonymously. As a result, the signer can hide his specific identity information to the mesh signature, namely his identifying information (such as personal public key) may be hidden to a list of tuples that consist of public key and message. Therefore, we propose an improved mesh signature scheme for IoT devices in this paper. The IoT devices seen as the signers may sign their publishing data through our proposed mesh signature scheme, and their specific identities can be hidden to a list of possible signers. Additionally, mesh signature consists of some atomic signatures, where the atomic signatures can be reusable. Therefore, for a large amount of data publ...
Computer Systems Science and Engineering
In recent years, big data has been one of the hottest development directions in the information f... more In recent years, big data has been one of the hottest development directions in the information field. With the development of artificial intelligence technology, mobile smart terminals and high-bandwidth wireless Internet, various types of data are increasing exponentially. Huge amounts of data contain a lot of potential value, therefore how to effectively store and process data efficiently becomes very important. Hadoop Distributed File System (HDFS) has emerged as a typical representative of dataintensive distributed big data file systems, and it has features such as high fault tolerance, high throughput, and can be deployed on low-cost hardwares. HDFS nodes communicate with each other to make the big data systems work properly, using the Remote Procedure Call (RPC) mechanism. However, the RPC in HDFS is still not good enough to work better in terms of network throughput and abnormal response. This paper presents an optimization method to improve the performance of HDFS. The proposed method dynamically adjusts the RPC configurations between NameNode and DataNodes by sensing the data characters that stored in DataNodes. This method can effectively reduce the NameNode processing pressure, and improve the network throughput generated by the information transmission between NameNode and DataNodes. It can also reduce the abnormal response time of the whole system. Finally, the extensive experiments show the effectiveness and efficiency of our proposed method.
Journal of Ambient Intelligence and Humanized Computing
Sensors
Log anomaly detection is an efficient method to manage modern large-scale Internet of Things (IoT... more Log anomaly detection is an efficient method to manage modern large-scale Internet of Things (IoT) systems. More and more works start to apply natural language processing (NLP) methods, and in particular word2vec, in the log feature extraction. Word2vec can extract the relevance between words and vectorize the words. However, the computing cost of training word2vec is high. Anomalies in logs are dependent on not only an individual log message but also on the log message sequence. Therefore, the vector of words from word2vec can not be used directly, which needs to be transformed into the vector of log events and further transformed into the vector of log sequences. To reduce computational cost and avoid multiple transformations, in this paper, we propose an offline feature extraction model, named LogEvent2vec, which takes the log event as input of word2vec to extract the relevance between log events and vectorize log events directly. LogEvent2vec can work with any coordinate transfo...
Computers, Materials & Continua
As the number of sensor network application scenarios continues to grow, the security problems in... more As the number of sensor network application scenarios continues to grow, the security problems inherent in this approach have become obstacles that hinder its wide application. However, it has attracted increasing attention from industry and academia. The blockchain is based on a distributed network and has the characteristics of nontampering and traceability of block data. It is thus naturally able to solve the security problems of the sensor networks. Accordingly, this paper first analyzes the security risks associated with data storage in the sensor networks, then proposes using blockchain technology to ensure that data storage in the sensor networks is secure. In the traditional blockchain, the data layer uses a Merkle hash tree to store data; however, the Merkle hash tree cannot provide non-member proof, which makes it unable to resist the attacks of malicious nodes in networks. To solve this problem, this paper utilizes a cryptographic accumulator rather than a Merkle hash tree to provide both member proof and nonmember proof. Moreover, the number of elements in the existing accumulator is limited and unable to meet the blockchain's expansion requirements. This paper therefore proposes a new type of unbounded accumulator and provides its definition and security model. Finally, this paper constructs an unbounded accumulator scheme using bilinear pairs and analyzes its performance.
Sensors, Jan 30, 2020
The development of the Internet of Things (IoT) plays a very important role for processing data a... more The development of the Internet of Things (IoT) plays a very important role for processing data at the edge of a network. Therefore, it is very important to protect the privacy of IoT devices when these devices process and transfer data. A mesh signature (MS) is a useful cryptographic tool, which makes a signer sign any message anonymously. As a result, the signer can hide his specific identity information to the mesh signature, namely his identifying information (such as personal public key) may be hidden to a list of tuples that consist of public key and message. Therefore, we propose an improved mesh signature scheme for IoT devices in this paper. The IoT devices seen as the signers may sign their publishing data through our proposed mesh signature scheme, and their specific identities can be hidden to a list of possible signers. Additionally, mesh signature consists of some atomic signatures, where the atomic signatures can be reusable. Therefore, for a large amount of data published by the IoT devices, the atomic signatures on the same data can be reusable so as to decrease the number of signatures generated by the IoT devices in our proposed scheme. Compared with the original mesh signature scheme, the proposed scheme has less computational costs on generating final mesh signature and signature verification. Since atomic signatures are reusable, the proposed scheme has more advantages on generating final mesh signature by reconstructing atomic signatures. Furthermore, according to our experiment, when the proposed scheme generates a mesh signature on 10 MB message, the memory consumption is only about 200 KB. Therefore, it is feasible that the proposed scheme is used to protect the identity privacy of IoT devices.
Peer-to-Peer Networking and Applications
Sustainable Cities and Society
Peer-to-Peer Networking and Applications
Complex & Intelligent Systems
The computer vision (CV) paradigm is introduced to improve the computational and processing syste... more The computer vision (CV) paradigm is introduced to improve the computational and processing system efficiencies through visual inputs. These visual inputs are processed using sophisticated techniques for improving the reliability of human–machine interactions (HMIs). The processing of visual inputs requires multi-level data computations for achieving application-specific reliability. Therefore, in this paper, a two-level visual information processing (2LVIP) method is introduced to meet the reliability requirements of HMI applications. The 2LVIP method is used for handling both structured and unstructured data through classification learning to extract the maximum gain from the inputs. The introduced method identifies the gain-related features on its first level and optimizes the features to improve information gain. In the second level, the error is reduced through a regression process to stabilize the precision to meet the HMI application demands. The two levels are interoperable ...
Sustainable Energy Technologies and Assessments
Journal of Ambient Intelligence and Humanized Computing
Computers, Materials & Continua
Image captioning aims to generate a corresponding description of an image. In recent years, neura... more Image captioning aims to generate a corresponding description of an image. In recent years, neural encoder-decoder models have been the dominant approaches, in which the Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM) are used to translate an image into a natural language description. Among these approaches, the visual attention mechanisms are widely used to enable deeper image understanding through fine-grained analysis and even multiple steps of reasoning. However, most conventional visual attention mechanisms are based on high-level image features, ignoring the effects of other image features, and giving insufficient consideration to the relative positions between image features. In this work, we propose a Position-Aware Transformer model with image-feature attention and position-aware attention mechanisms for the above problems. The image-feature attention firstly extracts multi-level features by using Feature Pyramid Network (FPN), then utilizes the scaled-dot-product to fuse these features, which enables our model to detect objects of different scales in the image more effectively without increasing parameters. In the position-aware attention mechanism, the relative positions between image features are obtained at first, afterwards the relative positions are incorporated into the original image features to generate captions more accurately. Experiments are carried out on the MSCOCO dataset and our approach achieves competitive BLEU-4, METEOR, ROUGE-L, CIDEr scores compared with some state-of-the-art approaches, demonstrating the effectiveness of our approach.
Future Generation Computer Systems
Computers, Materials & Continua
Applied Sciences
Employment of the Internet of Things (IoT) technology in the healthcare field can contribute to r... more Employment of the Internet of Things (IoT) technology in the healthcare field can contribute to recruiting heterogeneous medical devices and creating smart cooperation between them. This cooperation leads to an increase in the efficiency of the entire medical system, thus accelerating the diagnosis and curing of patients, in general, and rescuing critical cases in particular. In this paper, a large-scale IoT-enabled healthcare architecture is proposed. To achieve a wide range of communication between healthcare devices, not only are Internet coverage tools utilized but also satellites and high-altitude platforms (HAPs). In addition, the clustering idea is applied in the proposed architecture to facilitate its management. Moreover, healthcare data are prioritized into several levels of importance. Finally, NS3 is used to measure the performance of the proposed IoT-enabled healthcare architecture. The performance metrics are delay, energy consumption, packet loss, coverage tool usage,...
Sensors
Wireless Rechargeable Sensor Networks (WRSN) are not yet fully functional and robust due to the f... more Wireless Rechargeable Sensor Networks (WRSN) are not yet fully functional and robust due to the fact that their setting parameters assume fixed control velocity and location. This study proposes a novel scheme of the WRSN with mobile sink (MS) velocity control strategies for charging nodes and collecting its data in WRSN. Strip space of the deployed network area is divided into sub-locations for variant corresponding velocities based on nodes energy expenditure demands. The points of consumed energy bottleneck nodes in sub-locations are determined based on gathering data of residual energy and expenditure of nodes. A minimum reliable energy balanced spanning tree is constructed based on data collection to optimize the data transmission paths, balance energy consumption, and reduce data loss during transmission. Experimental results are compared with the other methods in the literature that show that the proposed scheme offers a more effective alternative in reducing the network pack...
Sensors
The development of the Internet of Things (IoT) plays a very important role for processing data a... more The development of the Internet of Things (IoT) plays a very important role for processing data at the edge of a network. Therefore, it is very important to protect the privacy of IoT devices when these devices process and transfer data. A mesh signature (MS) is a useful cryptographic tool, which makes a signer sign any message anonymously. As a result, the signer can hide his specific identity information to the mesh signature, namely his identifying information (such as personal public key) may be hidden to a list of tuples that consist of public key and message. Therefore, we propose an improved mesh signature scheme for IoT devices in this paper. The IoT devices seen as the signers may sign their publishing data through our proposed mesh signature scheme, and their specific identities can be hidden to a list of possible signers. Additionally, mesh signature consists of some atomic signatures, where the atomic signatures can be reusable. Therefore, for a large amount of data publ...
Computer Systems Science and Engineering
In recent years, big data has been one of the hottest development directions in the information f... more In recent years, big data has been one of the hottest development directions in the information field. With the development of artificial intelligence technology, mobile smart terminals and high-bandwidth wireless Internet, various types of data are increasing exponentially. Huge amounts of data contain a lot of potential value, therefore how to effectively store and process data efficiently becomes very important. Hadoop Distributed File System (HDFS) has emerged as a typical representative of dataintensive distributed big data file systems, and it has features such as high fault tolerance, high throughput, and can be deployed on low-cost hardwares. HDFS nodes communicate with each other to make the big data systems work properly, using the Remote Procedure Call (RPC) mechanism. However, the RPC in HDFS is still not good enough to work better in terms of network throughput and abnormal response. This paper presents an optimization method to improve the performance of HDFS. The proposed method dynamically adjusts the RPC configurations between NameNode and DataNodes by sensing the data characters that stored in DataNodes. This method can effectively reduce the NameNode processing pressure, and improve the network throughput generated by the information transmission between NameNode and DataNodes. It can also reduce the abnormal response time of the whole system. Finally, the extensive experiments show the effectiveness and efficiency of our proposed method.
Journal of Ambient Intelligence and Humanized Computing
Sensors
Log anomaly detection is an efficient method to manage modern large-scale Internet of Things (IoT... more Log anomaly detection is an efficient method to manage modern large-scale Internet of Things (IoT) systems. More and more works start to apply natural language processing (NLP) methods, and in particular word2vec, in the log feature extraction. Word2vec can extract the relevance between words and vectorize the words. However, the computing cost of training word2vec is high. Anomalies in logs are dependent on not only an individual log message but also on the log message sequence. Therefore, the vector of words from word2vec can not be used directly, which needs to be transformed into the vector of log events and further transformed into the vector of log sequences. To reduce computational cost and avoid multiple transformations, in this paper, we propose an offline feature extraction model, named LogEvent2vec, which takes the log event as input of word2vec to extract the relevance between log events and vectorize log events directly. LogEvent2vec can work with any coordinate transfo...
Computers, Materials & Continua
As the number of sensor network application scenarios continues to grow, the security problems in... more As the number of sensor network application scenarios continues to grow, the security problems inherent in this approach have become obstacles that hinder its wide application. However, it has attracted increasing attention from industry and academia. The blockchain is based on a distributed network and has the characteristics of nontampering and traceability of block data. It is thus naturally able to solve the security problems of the sensor networks. Accordingly, this paper first analyzes the security risks associated with data storage in the sensor networks, then proposes using blockchain technology to ensure that data storage in the sensor networks is secure. In the traditional blockchain, the data layer uses a Merkle hash tree to store data; however, the Merkle hash tree cannot provide non-member proof, which makes it unable to resist the attacks of malicious nodes in networks. To solve this problem, this paper utilizes a cryptographic accumulator rather than a Merkle hash tree to provide both member proof and nonmember proof. Moreover, the number of elements in the existing accumulator is limited and unable to meet the blockchain's expansion requirements. This paper therefore proposes a new type of unbounded accumulator and provides its definition and security model. Finally, this paper constructs an unbounded accumulator scheme using bilinear pairs and analyzes its performance.
Sensors, Jan 30, 2020
The development of the Internet of Things (IoT) plays a very important role for processing data a... more The development of the Internet of Things (IoT) plays a very important role for processing data at the edge of a network. Therefore, it is very important to protect the privacy of IoT devices when these devices process and transfer data. A mesh signature (MS) is a useful cryptographic tool, which makes a signer sign any message anonymously. As a result, the signer can hide his specific identity information to the mesh signature, namely his identifying information (such as personal public key) may be hidden to a list of tuples that consist of public key and message. Therefore, we propose an improved mesh signature scheme for IoT devices in this paper. The IoT devices seen as the signers may sign their publishing data through our proposed mesh signature scheme, and their specific identities can be hidden to a list of possible signers. Additionally, mesh signature consists of some atomic signatures, where the atomic signatures can be reusable. Therefore, for a large amount of data published by the IoT devices, the atomic signatures on the same data can be reusable so as to decrease the number of signatures generated by the IoT devices in our proposed scheme. Compared with the original mesh signature scheme, the proposed scheme has less computational costs on generating final mesh signature and signature verification. Since atomic signatures are reusable, the proposed scheme has more advantages on generating final mesh signature by reconstructing atomic signatures. Furthermore, according to our experiment, when the proposed scheme generates a mesh signature on 10 MB message, the memory consumption is only about 200 KB. Therefore, it is feasible that the proposed scheme is used to protect the identity privacy of IoT devices.
Peer-to-Peer Networking and Applications