8,404 research outputs found
Delay-limited Computation Offloading for MEC-assisted Mobile Blockchain Networks
The proof-of-work (PoW) mining process requires a large amount of intensive computing, which leads to some plights such as heavy equipment and fixed access nodes in traditional blockchain networks. A novel mobile blockchain network with the help of a mobile edge computing (MEC) server is presented, where all mobile users participate in the PoW mining process. The traditional Bitcoin network adjusts the target difficulty value to ensure a stable block time. However, for MEC-assisted mobile blockchain networks, the adjusted difficulty value needs to be broadcast to all mobile users, which results in expensive communication costs. To maintain a stable block time of mobile blockchain networks, we formulate the delay-limited computation offloading strategy of the PoW-based mining task as a non-cooperative game that maximizes an individual revenue in the MEC-assisted mobile blockchain network. Specifically, the non-cooperative game problem can be divided into multiple sub-game optimization problems to obtain final solutions for all users. We analyze the sub-game optimization problem and prove the existence of Nash equilibrium (NE) of the non-cooperative game. Moreover, we design an alternating iterative algorithm based on the continuous relaxation and greedy rounding (CRGR) to achieve the NE of this game. Given the sub-optimal delay-limited computation offloading results, we also derive the optimal transmit power for an individual user within the maximum mining delay range. From the analytical results, we can see that the proposed CRGR-based alternating iterative algorithm can efficiently attain the sub-optimal delay-limited computation offloading strategies of all mobile users in the polynomial time. The individual transmit power increases accordingly with the delay-limited computation offloading strategies of all users. Numerical results demonstrate that the proposed CRGR-based alternating iterative algorithm has fast convergence and good stability
Correlation effects in the ground state charge density of Mott-insulating NiO: a comparison of ab-initio calculations and high-energy electron diffraction measurements
Accurate high-energy electron diffraction measurements of structure factors
of NiO have been carried out to investigate how strong correlations in the Ni
3d shell affect electron charge density in the interior area of nickel ions and
whether the new ab-initio approaches to the electronic structure of strongly
correlated metal oxides are in accord with experimental observations. The
generalized gradient approximation (GGA) and the local spin density
approximation corrected by the Hubbard U term (LSDA+U) are found to provide the
closest match to experimental measurements. The comparison of calculated and
observed electron charge densities shows that correlations in the Ni 3d shell
suppress covalent bonding between the oxygen and nickel sublattices.Comment: 6 pages, LaTeX and 5 figures in the postscript forma
The effects of dog management on Echinococcus spp. prevalence in villages on the eastern Tibetan Plateau, China
Background The pastoral area of the eastern Tibetan plateau is a very important human echinococcosis endemic region. Domestic dogs are the main definitive host for the transmission of Echinococcus granulosus sensu lato (s.1.) and E. multilocularis to humans. To control the infection risks, a national-level canine echinococcosis prevention and control program has been implemented since 2015 in Shiqu County, Sichuan, China, The objective of this investigation was to evaluate its effect on Echinococcus spp. prevalence in dogs. Methods We surveyed 69 households with 84 owned dogs, for dog keeping information in the villages of Rizha and Eduoma. A total of 105 dog fecal samples, consisting of 75 from owned dogs and 30 unknown dog fecal samples were collected between 2015 and 2017 to determine Echinococcus spp. prevalence using copro-PCR. Eight variables based on household surveys were included into a logistic regression model for significantly relevant factors to canine echinococcosis prevalence in dogs. Results The overall Echinococcus spp. copro-DNA prevalence decreased significantly in dogs from 51.2% (2015) to 20.0% (2017) in Rizha, and insignificantly from 11.5% (2016) to 4.3% (2017) in Eduoma. Echinococcus multilocularis was the most prevalent species continually detected during the entire research period, while E. granulosus was rare and not detected in 2017. Echinococcus shiquicus prevalence was as high as E. multilocularis , although only detected in 2015 in Rizha. Unleashed dog feces were mainly collected in Rizha Village in 2015. Although 93.2% of owned dogs were leashed, and the monthly praziquantel dosing rate reached 97%, E. multilocularis infection could still be detected in 11.1% of owned dogs in 2017. Monthly deworming, leashing dogs 24h per day, and the avoidance of dogs feeding on livestock viscera are significant measures to prevent canine echinococcosis infection in owned dogs. Conclusion Carrying out a canine echinococcosis prevention and control program can significantly decrease the Echinococcus prevalence. The potential contact between leashed dogs and wild small mammals is still a risk to re-infect owned dogs. This study shows that the long term application of regular dog dosing in the vast remote echinococcosis endemic areas of west China is still challenging
Experimental research on night heat loss and dust effect of distillation-solar chimney power plant
To more comprehensively grasp the operating characteristics of the solar chimney power plants combined with
distillation and provide a valuable reference for the design and operation of the power plants, a comparative test
platform was built in this paper, which adopted manual covering of insulation layer and dust, and explored for
the first time the impact of the insulation layer and dust accumulation on the operational characteristics of power
plants. The results show that the insulation layer can increase the temperature rise of the airflow at night by a
maximum of 2.1 â—¦C, which is 25.9 %; but at the same time, it will reduce the temperature difference between the
seawater and the solar still cover, resulting in a decrease of more than 7 % in daily water yield. Therefore, if the
power plant pursues water production, it is not necessary to install insulation layers. Dust accumulation will
affect the heat collection and storage performance of the system, reduce the power output, and shorten the
effective power generation time; at the same time, lowering the seawater temperature will also reduce the water
yield of the system by more than 10 %, so the power plant must regularly clean the collector roof
Multivariate risks and depth-trimmed regions
We describe a general framework for measuring risks, where the risk measure
takes values in an abstract cone. It is shown that this approach naturally
includes the classical risk measures and set-valued risk measures and yields a
natural definition of vector-valued risk measures. Several main constructions
of risk measures are described in this abstract axiomatic framework.
It is shown that the concept of depth-trimmed (or central) regions from the
multivariate statistics is closely related to the definition of risk measures.
In particular, the halfspace trimming corresponds to the Value-at-Risk, while
the zonoid trimming yields the expected shortfall. In the abstract framework,
it is shown how to establish a both-ways correspondence between risk measures
and depth-trimmed regions. It is also demonstrated how the lattice structure of
the space of risk values influences this relationship.Comment: 26 pages. Substantially revised version with a number of new results
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System Framework for Digital Monitoring of the Construction of Asphalt Concrete Pavement Based on IoT, BeiDou Navigation System, and 5G Technology
In the construction of asphalt pavement, poor quality is often the main reason for damage to the pavement, which necessitates the use of monitoring systems during the construction stage. Therefore, this study focuses on building an asphalt concrete pavement construction monitoring system to monitor the construction phase. Through a literature review and semi-structured interviews with industry experts, this paper provides an in-depth understanding of the goals and obstacles of asphalt pavement monitoring and discusses directions for improvement. Subsequently, based on the analysis of the interview results, a system framework for asphalt concrete pavement construction monitoring was constructed, and the system was successfully developed and applied to a highway construction project. The results show that the monitoring system significantly improves the construction quality of asphalt concrete pavement, improves the intelligent level of pavement construction management, and promotes the digital development of highway construction
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