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Mingqiang Zhu

Bio: Mingqiang Zhu is an academic researcher from Beijing Jiaotong University. The author has contributed to research in topics: Materials science & Graphene. The author has an hindex of 2, co-authored 3 publications receiving 80 citations.

Papers
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Journal ArticleDOI
TL;DR: A smart collaborative tracking scheme by investigating advanced parameter prediction skills and improved particle filter approaches is proposed to enhance the performance and demonstrate acceptable reliability of the proposed algorithm.
Abstract: Ubiquitous power Internet of Things (IoT) is suffering unprecedented constraints and reliable tracing is a typical example. Motivated by software-defined and function virtualization capabilities of edge-cloud interplay, we propose a smart collaborative tracking scheme by investigating advanced parameter prediction skills and improved particle filter approaches. First, the range-based positioning issues are transformed into the vector nonlinear suboptimal estimation problem based on information fusion. Second, the importance of density function is provisioned to calculate locations and trajectories of the mobile node by obtaining cubature points, updating state estimation, and revising vector estimation. The Gauss–Newton iterative method has been utilized to achieve higher accuracy. Third, we implement our scheme into the simulation platform and prototype system. The practical deployment has been validated from multiple perspectives. Comparing with existing candidates, experimental results illustrate that the proposed algorithm is able to enhance the performance and demonstrate acceptable reliability. Potential usages are being expected in dynamic surveillance, equipment maintenance, and other emerging IoT scenarios.

112 citations

Journal ArticleDOI
TL;DR: A smart collaborative routing protocol with low delay and high reliability is proposed to accommodate mixed link scenarios and demonstrates that the end-to-end delay can be effectively cut down through comprehensive improvements.
Abstract: In the industrial Internet of things (IIoT), there is always a strong demand for real-time information transfer. Especially when deploying wireless/wired hybrid networks in smart factories, the requirement for low delay interaction is more prominent. Although tree routing protocols have been successfully executed in simple networks, more challenges in transmission speed can be observed in the manufacturing broadband communication system. Motivated by the progresses in deep learning, a smart collaborative routing protocol with low delay and high reliability is proposed to accommodate mixed link scenarios. First, we establish a one-hop delay model to investigate the potential affects of Media Access Control (MAC) layer parameters, which supports the subsequent design. Second, forwarding, maintenance, and efficiency strategies are created to construct the basic functionalities for our routing protocol. Relevant procedures and key approaches are highlighted as well. Third, two sub-protocols are generated and the corresponding implementation steps are described. The experimental results demonstrate that the end-to-end delay can be effectively cut down through comprehensive improvements. Even more sensor nodes and larger network scale are involved, our proposed protocol can still illustrate the advantages comparing with existing solutions within IIoT.

23 citations

Journal ArticleDOI
TL;DR: In this article , an artificial peroxidase with mAbs recognition activity by utilizing gallic acid (GA) to chelate with multivalent iron was successfully proposed for detecting clenbuterol in pork and chicken matrixes.

18 citations

Journal ArticleDOI
TL;DR: In this paper , a new type of MOF with both interior linker and metal valence modulation (m-MIL-101-1.0) is reported to boost photocatalytic activity owing to the formed charge migration pathway.

12 citations

Journal ArticleDOI
01 May 2022
TL;DR: In this paper , a review of dyestuff chemistry-encode signal tracers-based ICAs for food safety monitoring is presented, along with the challenges in this field.
Abstract: With the globalization of food supplies and worldwide concerns about foodborne illness, the food industry is confronting unprecedented safety challenges. Dyestuff chemistry, nanotechnology, and immunochromatography assay (ICA) have all been hot topics in recent decades, particularly in the respective professions. Regardless, the respective superiorities and weaknesses are difficult to integrate and overcome, hindering the widespread deployment in the food safety sector. In this review, the historical development and current mechanism design for various analysis patterns of dyestuff chemistry-encode signal tracers-based ICAs (dyestuff-based ICAs) for food safety monitoring are classified. And we highlight the construction strategy of dyestuff-encode signal tracers to obtain simpler steps, enhanced utilization efficiency, and brand-new function. Furthermore, the unique superiority and recent applications of dyestuff-based ICAs for food safety monitoring, as well as future-oriented innovation are reviewed. Finally, the challenges in this field were also spotlighted along with the outlook of profound developments for dyestuff-based ICAs in point-of-care (POC) settings. Dyestuff-based ICAs that combine multiple technologies emerge as POC tools for performing global food safety control owing to the rapidness, user-friendliness, and attraction on future-oriented innovation. Particularly with the maturation of traditional dyeing methods and the commercialization of related dyestuffs, dyestuff-based ICAs possess several merits, including cost-effectiveness, ease-of-labeling, and high performance while significantly shortening the distance from raw materials to ICA-based products. Following the advances in interdisciplinary innovations, dyestuff-based ICAs will undoubtedly reduce (or even eliminate) the inefficient back-and-forth between laboratories and tables, and spark a revolution in this field.

7 citations


Cited by
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Journal ArticleDOI
TL;DR: This paper presents an overview of IEEE 802.11p, with a particular focus on its adoption in an ITS setting, and analyzes both MAC and PHY layers in a dedicated short-range communication (DSRC) environment.
Abstract: Road safety is an active area of research for the automotive industry, and certainly one of ongoing interest to governments around the world. The intelligent transportation system (ITS) is one of several viable solutions with which to improve road safety, where the communication medium (e.g., among vehicles and between vehicles and the other components in an ITS environment, such as roadside infrastructure) is typically wireless. A typical communication standard adopted by car manufacturers is IEEE 802.11p for communications. Thus, this paper presents an overview of IEEE 802.11p, with a particular focus on its adoption in an ITS setting. Specifically, we analyze both MAC and PHY layers in a dedicated short-range communication (DSRC) environment.

127 citations

Journal ArticleDOI
TL;DR: A detailed comparative study reveals that DBACP-IoTSG supports more functionality features and provides better security apart from its low communication and computation costs as compared to recently proposed relevant schemes.
Abstract: We design a new blockchain-based access control protocol in IoT-enabled smart-grid system, called DBACP-IoTSG Through the proposed DBACP-IoTSG, the data is securely brought to the service providers from their respective smart meters (SMs) The peer-to-peer (P2P) network is formed by the participating service providers, where the peer nodes are responsible for creating the blocks from the gathered data securely from their corresponding SMs and adding them into the blockchain after validation of the blocks using the voting-based consensus algorithm In our work, the blockchain is considered as private because the data collected from the consumers of the SMs are private and confidential By the formal security analysis under the random oracle model, nonmathematical security analysis and software-based formal security verification, DBACP-IoTSG is shown to be resistant against various attacks We carry out the experimental results of various cryptographic primitives that are needed for comparative analysis using the widely used multiprecision integer and rational arithmetic cryptographic library (MIRACL) A detailed comparative study reveals that DBACP-IoTSG supports more functionality features and provides better security apart from its low communication and computation costs as compared to recently proposed relevant schemes In addition, the blockchain implementation of DBACP-IoTSG has been performed to measure computational time needed for the varied number of blocks addition and also the varied number of transactions per block in the blockchain

114 citations

Journal ArticleDOI
TL;DR: An anomaly detection method with a composite autoencoder model learning the normal pattern is proposed, which makes prediction and reconstruction on input data at the same time, which overcomes the shortcoming of using each one alone.
Abstract: As the Industrial Internet of Things (IIoT) develops rapidly, cloud computing and fog computing become effective measures to solve some problems, e.g., limited computing resources and increased network latency. The Industrial Control Systems (ICS) play a key factor within the development of IIoT, whose security affects the whole IIoT. ICS involves many aspects, like water supply systems and electric utilities, which are closely related to people’s lives. ICS is connected to the Internet and exposed in the cyberspace instead of isolating with the outside recent years. The risk of being attacked increases as a result. In order to protect these assets, intrusion detection systems (IDS) have drawn much attention. As one kind of intrusion detection, anomaly detection provides the ability to detect unknown attacks compared with signature-based techniques, which are another kind of IDS. In this paper, an anomaly detection method with a composite autoencoder model learning the normal pattern is proposed. Unlike the common autoencoder neural network that predicts or reconstructs data separately, our model makes prediction and reconstruction on input data at the same time, which overcomes the shortcoming of using each one alone. With the error obtained by the model, a change ratio is put forward to locate the most suspicious devices that may be under attack. In the last part, we verify the performance of our method by conducting experiments on the SWaT dataset. The results show that the proposed method exhibits improved performance with 88.5% recall and 87.0% F1-score.

46 citations

Journal ArticleDOI
TL;DR: The adaptability of the mining industry to IoT systems and its current development is reviewed and significant challenges of this progress are investigated and recommendations to develop a comprehensive model suited for different mining sections such as exploration, operation and safety are developed.
Abstract: The integration of computer-based technologies interacting with industrial machines or home appliances through an interconnected network, for teleoperation, workflow control, switching to autonomous mode, or collecting data automatically using a variety of sensors, is known as Internet of Things (IoT). When applied inside an industrial context, it is possible to immediately benefit from the analytics obtained, contributing to process optimization, machine health, the safety of workers and asset management. IoT can assist real-time platforms in remotely monitoring and operating a complex production system with minimal intervention of humans. Hence it can be beneficial for hazardous industries, such as mining, by increasing the safety of personnel and equipment while reducing operation costs. An ideal smart automated mine could potentially be achievable by gradually taking advantage of IoT. Currently, different sensors are used in mine-related activities, such as geophones in exploration and blast control, piezometers in dewatering and toxic gas detectors in working frontlines. However, a fully integrated automated system is challenging in practice due to infrastructural limitations in communication, data management and storage. Moreover, the tendency of mining companies to continue with traditional methods instead of relying on untested novel techniques decelerates this progress. In this study, the adaptability of the mining industry to IoT systems and its current development is reviewed. Significant challenges of this progress are investigated and recommendations to develop a comprehensive model suited for different mining sections such as exploration, operation and safety considering flexible technologies such as Wireless Sensor Networks and the introduction of Global Data Management.

43 citations

Journal ArticleDOI
TL;DR: A performance-to-cost analysis of Deterministic and Synchronous Multi-channel Extension (DSME) and Time-slotted Channel Hopping (TSCH) MAC modes of IEEE 802.15.4 MAC protocol is carried out to analyze the trade-off of choosing a particular MAC mode over others and present the applicability of different MAC modes to different application scenarios.
Abstract: The IEEE 802.15.4 standard is one of the widely adopted networking specification for Internet of Things (IoT). It defines several physical layer (PHY) options and medium access control (MAC) sub-layer protocols for interconnection of constrained wireless devices. These devices are usually battery-powered and need to support requirements like low-power consumption and low-data rates. The standard has been revised twice to incorporate new PHY layers and improvements learned from implementations. Research in this direction has been primarily centered around improving the energy consumption of devices. Recently, to meet specific Quality-of-Service (QoS) requirements of different industrial applications, the IEEE 802.15.4e amendment was released that focuses on improving reliability, robustness and latency. In this paper, we carry out a performance-to-cost analysis of Deterministic and Synchronous Multi-channel Extension (DSME) and Time-slotted Channel Hopping (TSCH) MAC modes of IEEE 802.15.4e with 802.15.4 MAC protocol to analyze the trade-off of choosing a particular MAC mode over others. The parameters considered for performance are throughput and latency, and the cost is quantified in terms of energy. A Markov model has been developed for TSCH MAC mode to compare its energy costs with 802.15.4 MAC. Finally, we present the applicability of different MAC modes to different application scenarios.

34 citations