BCSE: Blockchain-based trusted service evaluation model over big data

Li, Fengyin; Yu, Xinying; Ge, Rui; Wang, Yanli; Cui, Yang; Zhou, Huiyu

doi:10.26599/bdma.2020.9020028

Cited by 38 publications

(23 citation statements)

References 15 publications

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“…As an intelligent information processing system, the core of the artificial neural network to realize its function is the algorithm. In the process of learning the BP neural network error return attribute algorithm, each neuron in the input layer receives external input information and sends it to each neuron in the hidden layer [ 18 ]. The hidden layer in the middle is the internal information conversion layer for processing information.…”

Section: Data Mining and Apriori Algorithm Based On Medical Big Datamentioning

confidence: 99%

[Retracted] Correlation between Collateral Compensation and Homocysteine Levels in Patients with Acute Cerebral Infarction after Intravenous Thrombolysis Based on Medical Big Data

Zhao

et al. 2022

BioMed Research International

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Homocysteine is an amino acid present in plasma, which is an important intermediate product in the metabolism of methionine and cysteine. Acute cerebral infarction (CI) is called acute CI of stroke. It is one of the most common diseases in neurology and has a serious impact, affecting people’s lives. This article is aimed at studying the effect of data mining algorithms based on medical big data and the improved apriori algorithm on the analysis of the correlation between collateral compensation and homocysteine levels in patients with acute CI. This article proposes that there are many factors in patients with acute CI, among which are collateral compensation and homocysteine levels that are not easily determined. From the data in the tables in the experiment of this article, it can be seen that the collateral circulation of patients with acute CI is 8%, and the collateral circulation of patients without acute CI is 35%. The results indicate that both collateral compensation and homocysteine levels affect patients with acute CI. The higher the homocysteine level, the greater the probability of acute CI, and the better the state of collateral circulation, the less likely it is to suffer from acute CI.

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Section: Data Mining and Apriori Algorithm Based On Medical Big Datamentioning

confidence: 99%

[Retracted] Correlation between Collateral Compensation and Homocysteine Levels in Patients with Acute Cerebral Infarction after Intravenous Thrombolysis Based on Medical Big Data

Zhao

et al. 2022

BioMed Research International

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“…193 Cloud and edge computing has been extensively studied for a 194 wide range of tasks, such as big data processing [20], task 195 offloading for the Internet of Things (IoT) combined with 196 blockchain technology [21], [22], and offloading of gen-197 eral tasks while leveraging between throughput and fairness 198 [23]. Another use case is gaming for providing high-quality 199 services with lightweight user-side computing [24].…”

Section: A Cloud Computing For Gaming and Vrmentioning

confidence: 99%

Edge-Computing-Assisted Virtual Reality Computation Offloading: An Empirical Study

et al. 2022

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Offloading heavy virtual reality (VR) computational operations to a network edge computation entity is receiving increasing attention as a tool to wirelessly and energy efficiently provide low-end client devices with high-quality and immersive interactive VR services anytime and anywhere across the globe. In this work, we aim to provide an understanding of various characteristics of VR computation offloading through comprehensive experiments conducted using a prototype testbed for edge-assisted VR processing and streaming. First, we investigate the benefits of VR offloading in terms of computational load and power consumption reduction for a client device compared to standalone operation. Next, we measure VR traffic patterns, including frame size and data and packet rates with various settings, such as different resolution and encoding options. We also measure several performance metrics associated with the quality of experience, namely, frame rate, packet loss rate, and image quality, with various configuration settings. Then, we present latency measurement studies and investigate per-component latency with various settings. Furthermore, we report the rigorous experiments performed to study the impacts of latency and motion patterns on the black borders formed due to image reprojection and the overfilling technique used to eliminate these black borders. 15 INDEX TERMS Virtual reality, edge computing, offloading, VR streaming, latency, overfilling. 814 compared to standalone operation, VR traffic patterns, quality 815 and latency are strongly affected by the encoding configura-816 tion, the extent of black border formation increases with an 817 increasing latency, and that overfilling successfully reduces 818 black borders but at the cost of increasing computational 819 overhead with an increasing latency. 820 The experimental study conducted in this paper has several 821 limitations: (1) only a single VR client at a time is consid-822 ered, (2) a limited set of hardware platforms is considered, 823 (3) wireless connections are not diverse, and (4) positional 824 tracking is not considered. Therefore, reliving the abovemen-825 tioned limitations, i.e., studying the characteristics of edge 826 VR in more diverse experimental environments, including 827 multiple VR clients at the same time, diverse hosts (e.g., 828 commercial edge and cloud services) and client platforms, 829 wireless connections, such as LTE and 5G NR, and positional 830 tracking remains for future work. The optimization of the 831 VR streaming framework and its communication protocols 832 to minimize the total latency is still an important issue to 833 explore. A holistic/joint design approach of VR content cre-834 ation, communication protocols and the radio resource man-835 agement of VR client links will maximize the efficiency of 836 edge VR, and thus, is a subject for future research. Moreover, 837 extending the service platform for augmented and mixed 838 reality will be another important direction for future work.

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“…However, anomaly detection issue is not considered. Blockchain is adopted in [ 36 , 37 ] to realize the protection of user privacy during the cross-platform data sharing and integration process. This way, the sensitive data stored in different cloud platform can be fully shared for value-added smart applications while guaranteeing not to disclose much private information of users.…”

Section: Related Workmentioning

confidence: 99%

Private anomaly detection of student health conditions based on wearable sensors in mobile cloud computing

et al. 2022

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With the continuous spread of COVID-19 virus, how to guarantee the healthy living of people especially the students who are of relative weak physique is becoming a key research issue of significant values. Specifically, precise recognition of the anomaly in student health conditions is beneficial to the quick discovery of potential patients. However, there are so many students in each school that the education managers cannot know about the health conditions of students in a real-time manner and accurately recognize the possible anomaly among students quickly. Fortunately, the quick development of mobile cloud computing technologies and wearable sensors has provided a promising way to monitor the real-time health conditions of students and find out the anomalies timely. However, two challenges are present in the above anomaly detection issue. First, the health data monitored by massive wearable sensors are often massive and updated frequently, which probably leads to high sensor-cloud transmission cost for anomaly detection. Second, the health data of students are often sensitive enough, which probably impedes the integration of health data in cloud environment even renders the health data-based anomaly detection infeasible. In view of these challenges, we propose a time-efficient and privacy-aware anomaly detection solution for students with wearable sensors in mobile cloud computing environment. At last, we validate the effectiveness and efficiency of our work via a set of simulated experiments.

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BCSE: Blockchain-based trusted service evaluation model over big data

Cited by 38 publications

References 15 publications

[Retracted] Correlation between Collateral Compensation and Homocysteine Levels in Patients with Acute Cerebral Infarction after Intravenous Thrombolysis Based on Medical Big Data

[Retracted] Correlation between Collateral Compensation and Homocysteine Levels in Patients with Acute Cerebral Infarction after Intravenous Thrombolysis Based on Medical Big Data

Edge-Computing-Assisted Virtual Reality Computation Offloading: An Empirical Study

Private anomaly detection of student health conditions based on wearable sensors in mobile cloud computing

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