The Experts below are selected from a list of 9927 Experts worldwide ranked by ideXlab platform
Muhammad Aslam - One of the best experts on this subject based on the ideXlab platform.
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new zero watermarking algorithm using hurst exponent for protection of privacy in telemedicine
IEEE Access, 2018Co-Authors: Zulfiqar Ali, Shamim M Hossain, Ghulam Muhammad, Muhammad AslamAbstract:Telemedicine has numerous potential applications in the medical field due to the significant progress of telecommunication and information technology in recent years. In any category of telemedicine, such as offline, remote monitoring, and interactive, medical data and personal information of an individual must be transmitted to the healthcare center. An unauthorized access to the data and information is unacceptable in a telemedicine application, because it may create unavoidable circumstances for a person’s private and professional life. To avoid any potential threat of identity exposure in telemedicine, a zero-watermarking algorithm to protect the privacy of an individual is proposed in this paper. The proposed algorithm embeds the identity of a person without introducing any distortion in medical speech signals. Two measures, namely, Hurst exponent and zero-crossing, are computed to determine the suitable locations in the signal for insertion of identity. An analysis of the signals indicates that unvoiced speech frames are reliable in insertion and extraction of identity, as well as robust against a noise attack. In the proposed zero-watermarking algorithm, identity is inserted in a secret key instead of a signal by using a 1-D local Binary Operator. Therefore, imperceptibility is naturally achieved. Experiments are performed by using a publicly available voice disorder database, and experimental results are satisfactory and show that the proposed algorithm can be reliably used in telemedicine applications.
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new zero watermarking algorithm using hurst exponent for protection of privacy in telemedicine
IEEE Access, 2018Co-Authors: Shamim M Hossain, Ghulam Muhammad, Muhammad AslamAbstract:Telemedicine has numerous potential applications in the medical field due to the significant progress of telecommunication and information technology in recent years. In any category of telemedicine, such as offline, remote monitoring, and interactive, medical data and personal information of an individual must be transmitted to the healthcare center. An unauthorized access to the data and information is unacceptable in a telemedicine application, because it may create unavoidable circumstances for a person’s private and professional life. To avoid any potential threat of identity exposure in telemedicine, a zero-watermarking algorithm to protect the privacy of an individual is proposed in this paper. The proposed algorithm embeds the identity of a person without introducing any distortion in medical speech signals. Two measures, namely, Hurst exponent and zero-crossing, are computed to determine the suitable locations in the signal for insertion of identity. An analysis of the signals indicates that unvoiced speech frames are reliable in insertion and extraction of identity, as well as robust against a noise attack. In the proposed zero-watermarking algorithm, identity is inserted in a secret key instead of a signal by using a 1-D local Binary Operator. Therefore, imperceptibility is naturally achieved. Experiments are performed by using a publicly available voice disorder database, and experimental results are satisfactory and show that the proposed algorithm can be reliably used in telemedicine applications.
Shamim M Hossain - One of the best experts on this subject based on the ideXlab platform.
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new zero watermarking algorithm using hurst exponent for protection of privacy in telemedicine
IEEE Access, 2018Co-Authors: Zulfiqar Ali, Shamim M Hossain, Ghulam Muhammad, Muhammad AslamAbstract:Telemedicine has numerous potential applications in the medical field due to the significant progress of telecommunication and information technology in recent years. In any category of telemedicine, such as offline, remote monitoring, and interactive, medical data and personal information of an individual must be transmitted to the healthcare center. An unauthorized access to the data and information is unacceptable in a telemedicine application, because it may create unavoidable circumstances for a person’s private and professional life. To avoid any potential threat of identity exposure in telemedicine, a zero-watermarking algorithm to protect the privacy of an individual is proposed in this paper. The proposed algorithm embeds the identity of a person without introducing any distortion in medical speech signals. Two measures, namely, Hurst exponent and zero-crossing, are computed to determine the suitable locations in the signal for insertion of identity. An analysis of the signals indicates that unvoiced speech frames are reliable in insertion and extraction of identity, as well as robust against a noise attack. In the proposed zero-watermarking algorithm, identity is inserted in a secret key instead of a signal by using a 1-D local Binary Operator. Therefore, imperceptibility is naturally achieved. Experiments are performed by using a publicly available voice disorder database, and experimental results are satisfactory and show that the proposed algorithm can be reliably used in telemedicine applications.
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new zero watermarking algorithm using hurst exponent for protection of privacy in telemedicine
IEEE Access, 2018Co-Authors: Shamim M Hossain, Ghulam Muhammad, Muhammad AslamAbstract:Telemedicine has numerous potential applications in the medical field due to the significant progress of telecommunication and information technology in recent years. In any category of telemedicine, such as offline, remote monitoring, and interactive, medical data and personal information of an individual must be transmitted to the healthcare center. An unauthorized access to the data and information is unacceptable in a telemedicine application, because it may create unavoidable circumstances for a person’s private and professional life. To avoid any potential threat of identity exposure in telemedicine, a zero-watermarking algorithm to protect the privacy of an individual is proposed in this paper. The proposed algorithm embeds the identity of a person without introducing any distortion in medical speech signals. Two measures, namely, Hurst exponent and zero-crossing, are computed to determine the suitable locations in the signal for insertion of identity. An analysis of the signals indicates that unvoiced speech frames are reliable in insertion and extraction of identity, as well as robust against a noise attack. In the proposed zero-watermarking algorithm, identity is inserted in a secret key instead of a signal by using a 1-D local Binary Operator. Therefore, imperceptibility is naturally achieved. Experiments are performed by using a publicly available voice disorder database, and experimental results are satisfactory and show that the proposed algorithm can be reliably used in telemedicine applications.
Yonggang Wen - One of the best experts on this subject based on the ideXlab platform.
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toward efficient distributed algorithms for in network Binary Operator tree placement in wireless sensor networks
IEEE Journal on Selected Areas in Communications, 2013Co-Authors: Yonggang Wen, Rui Fan, Sulim Tan, Jit BiswasAbstract:In-network processing is touted as a key technology to eliminate data redundancy and minimize data transmission, which are crucial to saving energy in wireless sensor networks (WSNs). Specifically, Operators participating in in-network processing are mapped to nodes in a sensor network. They receive data from downstream Operators, process them and route the output to either the upstream Operator or the sink node. The objective of Operator tree placement is to minimize the total energy consumed in performing in-network processing. Two types of placement algorithms, centralized and distributed, have been proposed. A problem with the centralized algorithm is that it does not scale to large WSN's, because each sensor node is required to know the complete topology of the network. A problem with the distributed algorithm is their high message complexity. In this paper, we propose a heuristic algorithm to place a treestructured Operator graph, and present a distributed implementation to optimize in-network processing cost and reduce the communication overhead. We prove a tight upper bound on the minimum in-network processing cost, and show that the heuristic algorithm has better performance than a canonical greedy algorithm. Simulation-based evaluations demonstrate the superior performance of our heuristic algorithm. We also give an improved distributed implementation of our algorithm that has a message overhead of O(M) per node, which is much less than the O(√NM log2 M) and O(√NM) complexities for two previously proposed algorithms, Sync and MCFA, respectively. Here, N is the number of network nodes and M is the size of the Operator tree.
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distributed and asynchronous solution to Operator placement in large wireless sensor networks
Mobile Ad-hoc and Sensor Networks, 2012Co-Authors: Yonggang WenAbstract:Due to energy limitation of wireless sensor networks, in-network aggregation and distributed data fusion are proposed to perform the desired aggregation (or fusion) Operators en route-eliminating data redundancy, minimizing transmissions and thus saving energy. An Operator involved with in-network processing will be placed on a network node, which receives the data from sources, process them and send the output to either the next Operator or sink node. As transmitting data from one Operator to other imposes a cost, which is dependent on the placement of Operators, the placement of Operators can greatly affect the energy cost of in-network processing. In this research work, we propose a minimum-cost forwarding based asynchronous algorithm (MCFA) to find the optimal placement for Operator tree with minimized energy cost of in-network processing. It is shown that minimum-cost forwarding can dramatically reduce message overhead of asynchronous algorithm. It is also shown that MCFA has less message overhead than synchronous algorithm by both mathematical analysis and simulation-based evaluation. For a regular grid network and a complete Binary Operator tree, the messages sent at each node are $O(\sqrt{N}M)$ for MCFA, meanwhile $O(\sqrt{N}M\log_2M)$ for synchronous algorithm, where $N$ is the number of network nodes and $M$ is the number of data objects in Operator tree.
Ghulam Muhammad - One of the best experts on this subject based on the ideXlab platform.
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new zero watermarking algorithm using hurst exponent for protection of privacy in telemedicine
IEEE Access, 2018Co-Authors: Zulfiqar Ali, Shamim M Hossain, Ghulam Muhammad, Muhammad AslamAbstract:Telemedicine has numerous potential applications in the medical field due to the significant progress of telecommunication and information technology in recent years. In any category of telemedicine, such as offline, remote monitoring, and interactive, medical data and personal information of an individual must be transmitted to the healthcare center. An unauthorized access to the data and information is unacceptable in a telemedicine application, because it may create unavoidable circumstances for a person’s private and professional life. To avoid any potential threat of identity exposure in telemedicine, a zero-watermarking algorithm to protect the privacy of an individual is proposed in this paper. The proposed algorithm embeds the identity of a person without introducing any distortion in medical speech signals. Two measures, namely, Hurst exponent and zero-crossing, are computed to determine the suitable locations in the signal for insertion of identity. An analysis of the signals indicates that unvoiced speech frames are reliable in insertion and extraction of identity, as well as robust against a noise attack. In the proposed zero-watermarking algorithm, identity is inserted in a secret key instead of a signal by using a 1-D local Binary Operator. Therefore, imperceptibility is naturally achieved. Experiments are performed by using a publicly available voice disorder database, and experimental results are satisfactory and show that the proposed algorithm can be reliably used in telemedicine applications.
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new zero watermarking algorithm using hurst exponent for protection of privacy in telemedicine
IEEE Access, 2018Co-Authors: Shamim M Hossain, Ghulam Muhammad, Muhammad AslamAbstract:Telemedicine has numerous potential applications in the medical field due to the significant progress of telecommunication and information technology in recent years. In any category of telemedicine, such as offline, remote monitoring, and interactive, medical data and personal information of an individual must be transmitted to the healthcare center. An unauthorized access to the data and information is unacceptable in a telemedicine application, because it may create unavoidable circumstances for a person’s private and professional life. To avoid any potential threat of identity exposure in telemedicine, a zero-watermarking algorithm to protect the privacy of an individual is proposed in this paper. The proposed algorithm embeds the identity of a person without introducing any distortion in medical speech signals. Two measures, namely, Hurst exponent and zero-crossing, are computed to determine the suitable locations in the signal for insertion of identity. An analysis of the signals indicates that unvoiced speech frames are reliable in insertion and extraction of identity, as well as robust against a noise attack. In the proposed zero-watermarking algorithm, identity is inserted in a secret key instead of a signal by using a 1-D local Binary Operator. Therefore, imperceptibility is naturally achieved. Experiments are performed by using a publicly available voice disorder database, and experimental results are satisfactory and show that the proposed algorithm can be reliably used in telemedicine applications.
Joshua Sack - One of the best experts on this subject based on the ideXlab platform.
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The logic of qualitative probability
Artificial Intelligence, 2019Co-Authors: James P Delgrande, Bryan Renne, Joshua SackAbstract:Abstract In this paper we present a theory of qualitative probability. The usual approach of earlier work was to specify a Binary Operator ⪯ on formulas with ϕ ⪯ ψ having the intended interpretation that the event expressed by ϕ is no more probable than that expressed by ψ. We generalise these approaches by extending the domain of the Operator ⪯ from the set of events to the set of finite sequences of events. If Φ and Ψ are finite sequences of events, Φ ⪯ Ψ has the intended interpretation that the combined probabilities of the elements of Φ are no greater than those of Ψ. A sound and complete axiomatisation for this Operator over finite outcome sets is given. We argue that our approach is more perspicuous and intuitive than previous accounts. As well, we show that the approach is sufficiently expressive to capture the results of axiomatic probability theory and to encode rational linear inequalities. We also prove that our approach generalises the two major accounts for finite outcome sets.